Neurology Volume 72(6) February 10, 2009

This week in Neurology® Highlights of the February 10 issue Premutation allele pool in myotonic dystrophy type 2 Predi...

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This week in Neurology® Highlights of the February 10 issue

Premutation allele pool in myotonic dystrophy type 2

Predictors of driving safety in early Alzheimer disease

The authors identify DM2 premutation alleles that are highly unstable. Because of their instability, these alleles may expand to become disease-causing, representing a risk to carriers and their family members over time or successive generations.

Those who treat patients with Alzheimer disease often need to advise them concerning driving safety. This paper quantifies the increased rate of driving safety errors associated with Alzheimer disease, showing that neuropsychological tests give added value beyond diagnosis for predicting driver safety.

See p. 490; Editorial, p. 484

See p. 521

Transcranial magnetic stimulation in ALS: Utility of central motor conduction tests The authors prospectively studied 60 patients with amyotrophic lateral sclerosis subtypes using single pulse transcranial magnetic stimulation (TMS), recording from abductor digiti minimi and tibialis anterior muscles. While central motor conduction time and response threshold worsen by less than 2% per month, TMS amplitude decreases at an average of 8% per month and may be a useful objective marker of disease progression. See p. 498

Warm and cold complex regional pain syndromes: Differences beyond skin temperature? This paper explains that complex regional pain syndrome (CRPS) pathophysiology is not homogeneous and there are at least two different subtypes. Findings in warm CRPS resemble exaggerated posttraumatic inflammation, peripheral and subsequent central nociceptive changes. In cold CRPS changes favor a more complex pathophysiology indicating predominant central reorganization and psychosocial influences. See p. 505

Declining brain glucose metabolism in normal individuals with a maternal history of Alzheimer disease This study shows that individuals at risk for developing Alzheimer disease should be assessed on the basis of their brain profile, in addition to their clinical picture, and after considering their family history. This appears to be especially important at the early stages of disease, when clinical symptoms are not evident. See p. 513; Editorial, p. 486

Results of the Avonex Combination Trial (ACT) in relapsing-remitting MS Patients with relapsing-remitting multiple sclerosis frequently have continued disease activity despite treatment with approved medications. Despite a seemingly strong rationale for combination therapy in MS, this study does not support its utility. See p. 535

Early MRI in optic neuritis: The risk for disability Spinal cord imaging may have a prognostic role in patients with clinically isolated optic neuritis as clinically silent cord imaging changes at presentation increase the risk of greater disability at 6 years. In this study, however, the patients did remain minimally disabled. This may help in counseling and direction of services and therapy. See p. 542

VIEWS & REVIEWS

A neurologist’s guide to genome-wide association studies Complex inheritance underlies most common neurologic diseases, and genome-wide association studies are revolutionizing the understanding of complex inheritance and hence disease pathogenesis. This paper is an accessible introduction to the promise and limitations of genome-wide association studies. See p. 558

Epistasis: Multiple sclerosis and the major histocompatibility complex Epistatic gene interactions are not widely appreciated but have broad conceptual applications. This paper shows how specific parental haplotypes together (diplotype) are the main determinants of multiple sclerosis genetic risk. See p. 566

Podcasts can be accessed at www.neurology.org

Copyright © 2009 by AAN Enterprises, Inc.

483

EDITORIAL

How much expansion to be diseased? Toward repeat size and myotonic dystrophy type 2

Benedikt Schoser, MD Tetsuo Ashizawa, MD

Address correspondence and reprint requests to Dr. Tetsuo Ashizawa, Department of Neurology, UTMB, 301 University Blvd., JSA9.128, Galveston, TX 77555-0539 [email protected]

Neurology® 2009;72:484–485

Myotonic dystrophies (DMs) encompass at least two genetically distinct disorders: the classic type 1 (DM1), also known as Steiner disease, and type 2 (DM2), also referred to as proximal myotonic myopathy or Moxley-Ricker disease. Both disorders are characterized by variably expressed multisystem phenotypes with core features of progressive skeletal muscle weakness and degeneration with myotonia. DMs are caused by unstable repeat expansions: in DM1, a CTG repeat expansion in the 3= untranslated region of DMPK in chromosome 19q13.3, and in DM2, a CCTG repeat expansion in intron 1 of ZNF9 in 3q21.3.1,2 In DM1, a reservoir of premutation alleles in the population provides the source of de novo DM1 alleles. The expanded progenitor allele has a propensity to increase the CTG repeat size in successive generations, causing anticipation. The congenital form of DM1, with a large allele and the inability to reproduce offspring, represents the endpoint of anticipation. The stoichiometric balance between de novo mutations and losses of the mutant allele may explain the relatively stable prevalence of DM1. The gender of the transmitting parent is crucial in the instability, as de novo mutations occur with paternal and congenital DM1 with maternal transmission. Expanded alleles also tend to further expand variably in soma and germline throughout the life of the patient, potentially contributing to the progressive phenotype.1,3 In DM2, an uninterrupted variant of the CCTG portion of the repeat tract is elongated and shows unprecedented somatic instability with significant increases in length over time (e.g., 2,000 bp/3 years).4 The extraordinary somatic instability complicates the analysis of genotype–phenotype correlations including those in the effect of the gender of transmitting parents and anticipation. There have

been no reports of premutation alleles for DM2. The copy number of DM2 CCTG repeats is below 30 in normal individuals and up to about 11,000 in patients.2,4 The smallest reported expansion in DM2 had an uninterrupted mosaic (CCTG)75 as estimated by Southern blot.2 Thus, one of the enigmatic questions is which expansion size predicts the phenotypic expression in DM2. Haplotype analyses of DM1 and DM2 families suggested that the respective expansions may have originated from one or few founder mutations.2,5,6 While the original DM1 mutation has been estimated to have occurred around the time of the human migration out of Africa,3 the age of the DM2 expansion mutation on the founding haplotype is estimated at approximately 200 to 540 generations.6 A family of Afghan/Tajik ancestry provided some evidence that the DM2 expansion occurred prior to Aryan migration of the Indo-Europeans in 2000 – 1000 BC.6,7 In this issue of Neurology®, Bachinski et al.8 looked for the existence of premutation alleles in DM2. They found in normal Caucasian chromosomes a unimodal distribution of alleles at 132 bp with rare expanded alleles in the tail of the distribution. In contrast, in African Americans alleles revealed a secondary peak at 174 bp. However, sequence analyses showed that large alleles in African Americans have interruptions with multiple short stretches of uninterrupted CCTG repeats. While some large Caucasian alleles are also interrupted, a long uninterrupted tract of CCTG repeat was found exclusively among Caucasian alleles on the DM2 haplotype. Based on the sequence data, Bachinski et al.9 postulated that the long uninterrupted alleles have derived from interrupted alleles by unequal crossover, a model which is supported by previous observations of CCTG repeats in E coli. Furthermore, long uninterrupted alleles found in Caucasians

See page 490 From Ludwig Maximilians University Munich (B.S.), Friedrich-Baur Institute, Department of Neurology, Germany; and Department of Neurology (T.A.), University of Texas Medical Branch, Galveston. Disclosure: B.S. is a member of the German Muscular Dystrophy Network (MD-NET; 01GM0601) funded by the German Ministry of Education and Research (BMBF, Bonn, Germany). MD-NET is a partner of TREAT-NMD (EC, 6th FP, proposal 036825; www.treat-nmd.eu). Studies on myotonic dystrophies are supported by grants from the Deutsche Gesellschaft fu¨r Muskelkranke, Freiburg, Germany (to B.S.), and T.A. is supported by NIH (NS 041547). 484


have approximately three times higher average mutation load (⬍40%) than large interrupted alleles in African Americans. Large uninterrupted CCTG repeats have a lower thermodynamic stability when compared to the DM1 CTG repeats, which could make them better targets for DNA repair events, thus explaining their expansion-prone behavior. 9 Finally, the unstable, uninterrupted (CCTG)23–33 alleles with lengths of 92–132 bp found by Bachinski et al. are consistent with the threshold for instability at 100 –200 bp of uninterrupted repeats at other repeat loci.8,10 The claim that these unstable alleles with a long uninterrupted CCTG repeat tract are true DM2 premutations must be confirmed by identifying families in which these alleles do expand to the DM2 mutation range in a later generation (i.e., de novo mutation). The DM2 family in which brothers have predominant blood alleles of 55 and 61 repeats reported in this article is interesting, but whether these alleles are results of de novo mutation remains unknown. It also needs to be confirmed that subjects who have a premutation do not have a subtle DM2 phenotype. Furthermore, there are no cases of congenital DM2, indicating that a reservoir of premutations would increase the prevalence of DM2 unless there are other unidentified selection biases against DM2. Thus, the functional and clinical consequences of these premutation alleles remain unclear.8 However, identification of unstable CCTG repeat alleles in the general population is an important step toward understanding the origin of the DM2 mutation

and provides potentially useful information for genetic counseling. REFERENCES 1. Schoser B, Schara U. Myotonic dystrophies type 1 and 2: a summary on current aspects. Semin Pediatr Neurol 2006; 13:71–79. 2. Liquori CL, Ricker K, Moseley ML, et al. Myotonic dystrophy type 2 caused by a CCTG expansion in intron 1 of ZNF9. Science 2001;293:864–867. 3. Ashizawa T, Harper PS. Myotonic dystrophies: an overview. In: Ashizawa T, Wells RD, eds. Genetic Instabilities and Neurological Disorders. 2nd edition. Burlington, MA: Elsevier; 2006:21–35. 4. Day LW, Ranum LP. RNA pathogenesis of the myotonic dystrophies. Neuromuscul Disord 2005;15:5–16. 5. Bachinski LL, Udd B, Meola G, et al. Confirmation of DM2 (CCTG)n expansion mutation in PROMM/PDM patients of different European origins: a single shared haplotype indicates ancestral founder effects. Am J Hum Genet 2003;73:835–848. 6. Liquori CL, Ikeda Y, Weatherspoon M, et al. Myotonic dystrophy type 2: human founder haplotype and evolutionary conservation of the repeat tract Am J Hum Genet 2003;73:849–862. 7. Schoser BGH, Kress W, Walter MC, et al. Homozygosity for CCTG mutation in myotonic dystrophy type 2. Brain 2004;127:1868–1877. 8. Bachinski LL, Czernuszewicz T, Ramagli LS, et al. Premutation allele pool in myotonic dystrophy type 2. Neurology 2009;72:490–497. 9. Dere R, Wells RD. DM2 CCTG*CAGG repeats are crossover hotspots that are more prone to expansions than the DM1 CTG*CAG repeats in Escherichia coli. J Mol Biol 2006;360:21–36. 10. Gatchel JR, Zoghbi HY. Diseases of unstable repeat expansion: mechanisms and common principles. Nat Rev Genet 2005;6:743–755.

Neurology 72

February 10, 2009

485

EDITORIAL

Mom and me Brain metabolism links Alzheimer disease to maternal genes

Vijay Dhawan, PhD David Eidelberg, MD

Address correspondence and reprint requests to Dr. David Eidelberg, Center for Neurosciences, The Feinstein Institute for Medical Research, North Shore-Long Island Jewish Health System, 350 Community Drive, Manhasset, NY 11030 [email protected]

Neurology® 2009;72:486–487

In the current issue of Neurology®, Mosconi et al.1 use FDG PET to demonstrate a critical link between a maternal family history of Alzheimer disease (AD) and a pattern of regional metabolic abnormalities similar to that identified in patients with clinically diagnosed AD. Notably, the PET changes in these subjects progressed over the subsequent 2 years. By contrast, significant metabolic abnormalities (at baseline or follow-up) were not evident in subjects with a paternal history of AD nor in those without a family history of disease. Given that mitochondrial DNA is inherited maternally in humans, the authors speculate that their data are compatible with mitochondrial dysfunction as the root cause of AD. This mechanism has likewise been hypothesized for other common neurodegenerative conditions.2 Mosconi et al. used standard quantitative FDG PET methodology and analyzed their data on a voxel-by-voxel basis with statistical parametric mapping (SPM) tools. This metabolic imaging approach consistently supports a clinical diagnosis of AD, correlating well with postmortem assessment.3 In clinically diagnosed cases of AD, hypometabolism in the parieto-occipital, temporal, posterior cingulate, and frontal regions is well established.4 In recent years, qualitative and quantitative pattern recognition approaches have been developed to enhance the diagnostic accuracy of metabolic imaging at early stages of disease.5,6 Biomarkers based on the expression of spatial covariance patterns may be particularly relevant as disease-modifying therapies enter clinical trials. The size of the cohort reported by Mosconi et al. is admirable. However, there are concerns about some details in the parental history. For example, it is not known whether the parents who developed dementia by history actually had AD or another neurodegenerative disorder. Younger parents were considered unaffected at the time of the study, developing signs of AD later. Also, given variability in the age at onset of disease in the parents, the possibility of interac-

tions with environmental and other nongenetic factors cannot be dismissed. Despite these limitations, this study takes the field one step closer to the ultimate goal of accurately identifying individuals at risk for AD so that treatment can be given to slow the disease before it becomes clinically evident. It has been observed recently that amyloid precursor protein (APP) and its C-terminal-cleaved product beta-amyloid (A␤) accumulate in the mitochondrial compartment.7 Furthermore, evidence suggests that the accumulation of full-length APP and A␤ in the mitochondrial compartment has a causative role in impairing mitochondrial physiologic functions. One study found that the defective mitochondrial genes in AD cybrid cells led to increased damage from oxygen free radicals (oxidative stress) because of inefficient processing of oxygen into water.8 Subsequently, the activation of cell death pathways resulted in the oversecretion of beta amyloid peptides and the forming of plaque-like areas in the cells. Blocking the activation of cell death pathways eliminated the abnormal beta amyloid secretion. Although currently there is no way to image mitochondrial function with PET, efforts are under way to develop radiolabeled lipophilic salts (phosphonium cations) for noninvasive imaging. Other PET tracers have been developed to target abnormal protein aggregation (e.g., 11C-PIB, 18 F-FDDNP). In vivo PIB retention levels have been demonstrated to correlate directly with regionmatched postmortem measures of insoluble A␤ peptide levels and A␤ plaque load, but not with measures of neurofibrillary tangles (NFT).9 By contrast, FDDNP reflects both A␤ and NFT load.10 These tracers would be applicable to the development of drugs that reduce the burden of A␤ and tau proteins in the brains of patients with AD. The recently reported results of the methylthioninium chloride trial (reviewed recently in Neurology Today11) is an example of where PET imaging might ultimately serve as a surrogate marker for clinical tri-

See page 513 From The Feinstein Institute for Medical Research, Manhasset; and Departments of Neurology and Medicine, North Shore University Hospital and New York University School of Medicine, NY. Disclosure: The authors report no disclosures. 486


als with drugs directed at reducing abnormal tau proteins. The findings of the current article raise the possibility that healthy individuals with maternal histories of AD (and positive PET findings) could be appropriate subjects for a prevention study directed toward that mechanism. Indeed, improved functioning might be objectively demonstrated by an attenuation of the metabolic decline that was observed without therapy. The current article highlights the value of combining imaging and genetics in the study of large, at risk cohorts. More importantly, this work has practical significance in identifying a potential target population for early intervention. REFERENCES 1. Mosconi L, Mistur R, Switalski R, et al. Declining brain glucose metabolism in normal individuals with a maternal history of Alzheimer disease. Neurology 2009;72:513– 520. 2. Lin MT, Beal MF. Mitochondrial dysfunction and oxidative stress in neurodegenerative diseases. Nature 2006;443: 787–795. 3. Jagust W, Reed B, Mungas D, Ellis W, Decarli C. What does fluorodeoxyglucose PET imaging add to a clinical diagnosis of dementia? Neurology 2007;69:871–877. 4. Silverman DH, Mosconi L, Ercoli L, Chen W, Small GW. Positron emission tomography scans obtained for the eval-

5.

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11.

uation of cognitive dysfunction. Semin Nucl Med 2008; 38:251–261. Asllani I, Habeck C, Scarmeas N, Borogovac A, Brown TR, Stern Y. Multivariate and univariate analysis of continuous arterial spin labeling perfusion MRI in Alzheimer’s disease. J Cereb Blood Flow Metab 2008;28:725–736. Huang C, Eidelberg D, Habeck C, et al. Imaging markers of mild cognitive impairment: multivariate analysis of CBF SPECT. Neurobiol Aging 2007;28:1062–1069. Anandatheerthavarada HK, Biswas G, Robin MA, Avadhani NG. Mitochondrial targeting and a novel transmembrane arrest of Alzheimer’s amyloid precursor protein impairs mitochondrial function in neuronal cells. J Cell Biol 2003;161:41–54. Khan SM, Cassarino DS, Abramova NN, et al. Alzheimer’s disease cybrids replicate beta-amyloid abnormalities through cell death pathways. Ann Neurol 2000;48:148– 155. Ikonomovic MD, Klunk WE, Abrahamson EE, et al. Postmortem correlates of in vivo PiB-PET amyloid imaging in a typical case of Alzheimer’s disease. Brain 2008;131: 1630–1645. Barrio JR, Kepe V, Satyamurthy N, Huang SC, Small G. Amyloid and tau imaging, neuronal losses and function in mild cognitive impairment. J Nutr Health Aging 2008;12: 61S–65S. Valeo T. New therapies in the pipeline for AD: what’s promising, what’s not. Neurology Today 2008;8:13–14.

Neurology 72

February 10, 2009

487

IN MEMORIAM

Raymond D. Adams, MD (1911–2008)

Walter J. Koroshetz, MD, FAAN

488

On Saturday, October 18, Dr. Raymond D. Adams died in Boston at age 97. We mourn the loss of a truly great neurologist, but at the same time we fully celebrate his life. In many ways modern neurology has sprung from his lifelong work, in other ways it is still playing catch up with his vision. American medicine benefited from the convergence of unique attributes in this remarkable man. In describing Dr. Adams, most say he was “really smart,” with particularly strong emphasis on the “really.” They refer as much to his encyclopedic memory, exhaustive fund of knowledge, and skills of synthesis and analysis as to his superior intelligence or sometimes unnerving direct manner of speech. For over seven decades he remained passionate about neurology. To his mind, neurology encompassed all human disorders of muscle, nerve, and brain, whether primary or secondary, whether they had a known pathology or not. His contributions are too numerous to list but a few general themes are essential. Neuropathology (muscle, brain, nerve) was his strength and sculpted his thinking about nervous system disease; psychiatry was as intricately woven into his neurology as was internal medicine and pediatrics. His work was always patient centered. In the late 1950s, he established the Joseph P. Kennedy Jr. Laboratory for the Study of Neurologic Disorders. His academic contributions span many subspecialties, including multiple sclerosis, infections of the nervous system, neuropathy, stroke, muscle diseases, metabolic disorders of childhood, and the effects of alcohol and vitamin deficiency on the nervous system. He cared for adults as well as children and worked tirelessly to better understand the causes of mental retardation. In 1969 he helped to establish and then directed the Eunice Kennedy Schriver Center for Mental Retardation. Dr. Adams’ vision for neurology was all encompassing. It required full understanding of the medicine of human nervous system disorders from behavior to pathology, to pathophysiology, to molecular cause. His integrative sense of nervous system function is on display in his influential textbook, Principles of Neurology. Dr. Adams disdained mediocrity and imprecision, and he was self-critical first. His intense pursuit of neurologic knowledge attracted a large number of “smart” people to work Copyright © 2009 by AAN Enterprises, Inc.

Raymond D. Adams, MD

with him and to work in his departments. He helped each to choose a specialty and to become experimentalists, while cajoling them to remain grounded as generalists. The successes and failures of modern neurology are in large part related to how well his vision has played out. As many of his trainees continue to advance the field, the last word is not yet written. Indeed, though homebound in recent years, he regularly welcomed groups of residents to his home to hear about a case, examine neuropath slides, or “talk neurology.” Current journals opened on his desk and the ever present handwritten note cards attested to his continuing quest for new knowledge. Raymond Adams grew up in Portland, Oregon, graduated from the University of Oregon, and then attended medical school at Duke. He did medicine residency at Duke followed by a year of psychiatry at Yale and neurology residency at the Massachusetts General Hospital (MGH). He began his academic work in earnest at the neuropathology laboratories at the Boston City Hospital under Dr. Derek Denny Brown. He became chief of Neurology at the MGH in 1951 and led the department until the arrival of Dr. Joseph Martin in 1977. During that time, a large number of future leaders in neurology and neuroscience, both American and international, came to the MGH to work with Dr. Adams and his team. At the MGH, he and his lifelong colleagues were often referred to affectionately by their initials: Edward Peirson Richardson (EP), C. Miller Fisher (CMF),

Raymond D. Adams (RDA). The two neurology inpatient services at the MGH are named the RDA and the CMF in their honor. Dr. Adams is predeceased by his wife and the child neurologist Dr. Maria Salam-Adams, and is survived by four children, one stepdaughter, and multiple grandchildren and great grandchildren, and many more colleagues and friends. Over his career his work drew honors from a multitude of neurologic associations and universities, both in the United States and abroad. Many who worked with RDA have their own special memories. These mental pictures of the man

hold much more than words can—pictures of him feeding a patient, note-taking on 4 ⫻ 5 index cards, peering into the microscope, bending over the case at brain-cutting, becoming restless during a longwinded presentation, proposing profound research questions at the bedside or grand rounds, routinely recommending to out-of-town patients that they visit the glass flower gallery at Harvard, and my personal favorite—stat paging me at the age of 90, to protest that the mandatory psychiatry rotation for residents was shortened. These are the bricks from which legends are built.

Neurology 72

February 10, 2009

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ARTICLES

Premutation allele pool in myotonic dystrophy type 2

L.L. Bachinski, PhD T. Czernuszewicz, BS L.S. Ramagli, PhD T. Suominen, MS M.D. Shriver, PhD B. Udd, MD, PhD M.J. Siciliano, PhD R. Krahe, PhD

Address correspondence and reprint requests to Dr. Ralf Krahe, Department of Cancer Genetics, Unit 1010, University of Texas M.D. Anderson Cancer Center, 1515 Holcombe Blvd., Houston, TX 77030-4009 [email protected]

ABSTRACT

Background: The myotonic dystrophies (DM1, DM2) are the most common adult muscle diseases and are characterized by multisystem involvement. DM1 has been described in diverse populations, whereas DM2 seems to occur primarily in European Caucasians. Both are caused by the expression of expanded microsatellite repeats. In DM1, there is a reservoir of premutation alleles; however, there have been no reported premutation alleles for DM2. The (CCTG)DM2 expansion is part of a complex polymorphic repeat tract of the form (TG)n(TCTG)n(CCTG)n(NCTG)n(CCTG)n. Expansions are as large as 40 kb, with the expanded (CCTG)n motif uninterrupted. Reported normal alleles have up to (CCTG)26 with one or more interruptions.

Methods: To identify and characterize potential DM2 premutation alleles, we cloned and sequenced 43 alleles from 23 individuals. Uninterrupted alleles were identified, and their instability was confirmed by small-pool PCR. We determined the genotype of a nearby single nucleotide polymorphism (rs1871922) known to be in linkage disequilibrium with the DM2 mutation. Results: We identified three classes of large non-DM2 repeat alleles: 1) up to (CCTG)24 with two interruptions, 2) up to (CCTG)32 with up to four interruptions, and 3) uninterrupted (CCTG)22–33. Large non-DM2 alleles were more common in African Americans than in European Caucasians. Uninterrupted alleles were significantly more unstable than interrupted alleles (p ⫽ 10⫺4 to 10⫺7). Genotypes at rs1871922 were consistent with the hypothesis that all large alleles occur on the same haplotype as the DM2 expansion.

Conclusions: We conclude that unstable uninterrupted (CCTG)22-33 alleles represent a premutation allele pool for DM2 full mutations. Neurology® 2009;72:490–497 GLOSSARY AfrAm ⫽ African American; DM ⫽ myotonic dystrophy; EurCauc ⫽ European Caucasian; FISH ⫽ fluorescent in situ hybridization; MIM ⫽ Mendelian Inheritance in Man; NA ⫽ not available; SNP ⫽ single nucleotide polymorphism; SP-PCR ⫽ small-pool PCR.

Supplemental data at www.neurology.org

Myotonic dystrophy type 1 (DM1, Mendelian Inheritance in Man [MIM] 160900) and type 2 (DM2, MIM 602668) are the most common adult-onset muscle diseases, characterized by autosomal dominant inheritance, muscular dystrophy, myotonia, and multisystem involvement.1,2 DM is caused by unstable microsatellite repeat expansions—in DM1 a (CTG)n expansion in the 3= UTR of DMPK in chromosome 19q13.3,3-5 and in DM2 a (CCTG)n expansion in intron 1 of ZNF9 in 3q21.3.6 The principal features of the DMs are progressive distal muscle weakness and atrophy in DM1 and proximal muscle weakness in DM2. Muscle stiffness, myotonia, cataracts, cardiac conduction disturbances, endocrinologic abnormalities (including insulin resistance, male hypogonadism frontal balding), and elevated ␥-glutamyltransferase are common findings. However, in any individual patient, some of these symptoms may be absent, and in DM2, myotonia may be variable over time. Although DM1 and DM2

Editorial, page 484 e-Pub ahead of print on November 19, 2008, at www.neurology.org. From the Departments of Cancer Genetics (L.L.B., T.C., R.K.) and Molecular Genetics (L.S.R., M.J.S.), University of Texas M.D. Anderson Cancer Center, Houston, TX; Neurogenetics Program (T.S.), University of Tampere, Finland; Department of Neurology (B.U.), Tampere University Hospital, Finland; and Department of Anthropology (M.D.S.), Pennsylvania State University, University Park, PA. R.K. was supported in part by NIH grant AR48171 and MDA. B.U. was supported by Medicinska understo¨dsfo¨reningen Liv och Ha¨lsa r.f., the Tampere University Hospital Research Funds, and the Folkha¨lsan Institute of Genetics. Disclosure: The authors report no disclosures. 490


share the same core features, very apparent differences exist, and to the clinician these are clearly different diseases. Similar to DM1,7 DM2 has been reported with rare exception in populations of European descent.8-11 In populations where prevalence has been estimated, the occurrence of DM2 is at least as high as that of DM1 and may be even higher.8 DM2 expansions are generally much larger than those in DM1, with expansions commonly as large as 40 kb. The smallest reported expansion had an uninterrupted mosaic (CCTG)75 as estimated by Southern blot.6 For DM1, there is a reservoir of premutation alleles in the population.12 However, there have been no reports of premutation alleles for DM2, and the minimum size of a pathogenic expansion is not known. The repeat tract within intron 1 of ZNF9 is a complex array with several polymorphic elements, first described as (TG)n(TCTG)n (CCTG)n.6 In most individuals, there are two or more stretches of (CCTG)n interrupted by one or more (TCTG) or (GCTG) motifs. The most common interruption seems to be of the form (GCTG)1(CCTG)1(TCTG)1. It has been suggested that the loss of these cryptic repeats always accompanies expansion.6 We hypothesized that some larger alleles may represent a source of new expansion mutations. If premutations exist, we further predicted that they would have long uninterrupted (CCTG)n tracts, be somatically unstable, and occur on the same conserved haplotype as DM2 mutations. To determine the existence of DM2 premutation alleles, we cloned and sequenced a number of unusually large alleles along with short alleles and alleles from a DM2 family with an amplifiable expansion as controls. METHODS Samples. Enrollment of participants for this study was approved by the respective institutional review boards in accordance with the Declaration of Helsinki. After molecular genetic diagnosis, participants were recruited by their attending physicians. After obtaining informed consent, blood was drawn, and DNA was prepared using GenePure (Gentra). Three groups of population samples were used for genotyping. Group1 consisted of European Caucasian individuals, most of whom were normal relatives of DM2 patients. This group also included individuals with a molecular diagnosis of DM2, whose normal allele was counted in the population study. In all, group 1 contained 169 independent normal chromosomes. Sample group 2 consisted of 90 African American individuals (180 independent normal chromosomes). Group 3 was composed of 1,062 unrelated

normal individuals from Finland (2,124 independent chromosomes). With regard to the Caucasian samples, approximately 14% of the samples were anonymous, and no demographic information was available. Of the remainder, 48% were male and 52% were female. We do not have age information for the majority of the samples; however, all were adults. All the African American samples and Finnish samples were anonymous; therefore, only information on ethnicity is available. Altogether, DM2-repeat alleles of 23 samples were selected from the above populations, cloned, and sequenced, and 43 independent amplifiable alleles were characterized as summarized in the table. One sample was homozygous for a large allele, two samples (251001 and 251004) were related and shared their large allele, one sample (106001) had a large DM2 expansion as the second allele, and two related samples (874001 and 874003) had small expansion mutations.

Determination of allele size. DM2-repeat alleles were genotyped by PCR across the repeat tract. Three-primer amplification using a fluorescent-labeled universal primer was performed on an ABI 9700 thermocycler, using a Qiagen Hot Start Master Mix as previously described.9 Products were analyzed on an ABI 3100 Genetic Analyzer. For sizing of products larger than 350 bp, we used the Mapmarker 1000 standard (Bioventures, Murfreesboro, TN).

Amplification, cloning, genotyping, and sequencing. For cloning, alleles were amplified using unlabeled primers and the conditions described above in a two primer reaction. Products were cloned using the StrataClone PCR cloning kit according to the manufacturer’s instructions. For each sample, at least 45 colonies were amplified directly for genotyping. DNA from at least eight independent clones of representative alleles was prepared using a QIAprep Spin Miniprep kit. Plasmid DNA was sequenced directly using Big Dye terminator version 3 (ABI) and was visualized by capillary electrophoresis on an ABI 3100 Genetic Analyzer. Sequences were assembled using Sequencher software (Gene Codes, Ann Arbor, MI).

Single genome equivalent amplification. Samples were subjected to single genome equivalent amplification (small-pool PCR [SP-PCR]) as previously described.13 Briefly, DNA samples were diluted to approximately single diploid genome levels (6 pg). Multiple heminested SP-PCRs were conducted using the threeprimer reaction described above. At least 120 PCR replicates per sample were amplified to ensure counting at least 100 independent alleles. A Primus-96 plus thermocycler (MWG Biotech, High Point, NC) was used for PCR setup and amplification. Cycling conditions were 95°C/7 minutes, followed by 42 cycles of (95°C/45 seconds, 62°C/30 seconds, 72°C/30 seconds), and a final extension step of 72°C/7 minutes. Labeled amplification products were subjected to capillary electrophoresis as described above. Data analysis. After ABI GeneScan analysis, the data were scored for allele counts and variants. A model in which the number of alleles in replicate pools follows a Poisson distribution and in which particular allele frequencies constituted a fixed proportion of the total has been described.14 Maximum likelihood estimates of the mean number of alleles in each pool and the frequencies of each allele were derived accordingly. The mutant frequencies were compared between groups for significance using the arc-sin transformed mutant frequencies and a bootstrap standard error.14

Genotyping of SNP rs1871922. Genotyping of single nucleotide polymorphism (SNP) rs1871922 was previously described.9 The polymorphism alters a HaeIII restriction site such Neurology 72

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Table

Summary of 23 samples characterized Allele 1

Sample

Tract, bp

NC 162

124

NC 363 NC 374

Allele 2 No. seq.

No. (CCTG)n

Interruptions

Tract, bp

3

13

2

132

128

2

13

2

132

4

14

2

NC 380

124

2

15

1347-02

118

3

13

AA 307

148

4

AA 406

126

4

AA 418

134

AA 430

120

AA 314 8104001

No. seq.

No. (CCTG)n

Interruptions

5

13

2

132

6

13

134

4

14

2

132

6

2

130

5

24

2

172

12

2

172

3

14

2

3

15

2

136

4

16

128

4

13

AA 408

132

3

251001

132

5

251004

140

AA 473

142

AA 474 AA 479†

rs1871922 genotype

Ethnicity

46

A/C

NA

2

46

A/A

NA

2

46

A/A

NA

13

2

43

A/C

NA

14

2

47

C/C

EurCauc

4

23

2

41

C/C

AfrAm

4

23

2

42

A/C

AfrAm

172

3

23

2

41

C/C

AfrAm

166

5

20

2

44

C/C

AfrAm

2

217

1

32

3

37

C/C

AfrAm

2

154

4

17

3

45

A/C

EurCauc

14

2

172

4

22

4

45

C/C

AfrAm

13

2

180*

3

23

4

45

A/C

EurCauc

5

14

2

180*

2

23

4

44

A/C

EurCauc

4

13

2

174

4

23

4

45

A/C

AfrAm

132

4

15

2

174

3

22

4

45

C/C

AfrAm

179

3

22

4

179

3

22

4

39

C/C

AfrAm

896001

132

5

14

2

166

11

24

0

46

A/C

EurCauc

8102001

140

7

12

2

170

6

25

0

46

A/C

EurCauc

8103001

128

7

13

2

186

106001

186

14

32

0

Expansion

874001

132

6

13

2

874003

138

2

16

2

6

29

0

NA

NA

NA

276‡

7

55

300‡

2

61

Clones genotyped

45

A/C

EurCauc

276

C/C

EurCauc

0

44

A/C

EurCauc

0

43

A/C

EurCauc

*Same allele in related individuals. †Homozygous individual. ‡Same allele in related individuals. NA ⫽ not available; EurCauc ⫽ European Caucasian; AfrAm ⫽ African American.

that the C allele produces a fragment of 88 bp, whereas the A allele produces a fragment of 125 bp. The locus was PCR amplified; PCR products were digested with HaeIII (NEB), electrophoresed through 4% MetaPhor agarose gels (FMC), and visualized by ethidium bromide staining.

among 176 African American chromosomes, we identified 15 such alleles (8.5%), suggesting that large alleles are more common in the sub-Saharan populations (p ⫽ 1.769 ⫻ 10⫺6), consistent with the ethnic diversity of sub-Saharan Africans.

RESULTS Occurrence of larger-than-average alleles

is more common in African American samples. Nor-

mal Caucasian chromosomes show a unimodal distribution of alleles (mean tract length 132 bp) with most differing by 2 bp, indicating that the (TG)n motif is contributing significantly to the polymorphism at this locus. Alleles in the tail of the distribution were 4 bp apart, indicating additional variation in the (CCTG)n or (TCTG)n motifs. In contrast, a survey of African American alleles yielded a bimodal distribution with a secondary peak at around 174 bp (figure 1). Alleles with repeat tracts ⱖ160 bp are relatively rare in populations of European Caucasian descent. We identified only 17 such alleles among 973 non-DM2 chromosomes (1.8%). However, 492

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February 10, 2009

Sequence structure of large alleles at the DM2 locus.

To investigate the structure of these large alleles, we selected representative individuals from both European Caucasian and African American populations having alleles with repeat tracts ⱖ160 bp. Alleles were amplified, cloned, genotyped, and sequenced along with a number of smaller alleles with repeat tracts ⬍160 bp. In all, 23 samples were characterized as summarized in the table. At least 45 clones were genotyped for each sample, and at least 8 of the clones from each sample were sequenced. In all, 41 independent non– disease-causing DM2-repeat alleles were characterized along with amplifiable DM2 pathogenic expansions from two brothers. All alleles,

Figure 1

Distribution of normal repeat track sizes

(A) Alleles with a repeat track ⱖ160 bp are rare in European Caucasians (17 of 973 nonDM2 chromosomes, 1.8%). (B) Such large alleles occur more frequently in the African American population (8 of 180 chromosomes, 8.3%; p ⫽ 1.769 ⫻ 10⫺6).

regardless of size, showed hypervariability of cloned amplification products. Sequencing revealed that, for interrupted alleles, this variability was entirely confined to the (TG)n tract. We identified four individuals with uninterrupted (CCTG)24 –32 tracts, and these alleles showed hypervariability of the (CCTG)n motif as well as the (TG)n. We observed three types of interrupted alleles: 1) small alleles with (CCTG)12–16 containing two interruptions, 2) medium to large alleles with (CCTG)20 –24 and two interruptions, and 3) large alleles with (CCTG)17–32 containing four (or more rarely three) interruptions. Figure 2 shows the various repeat tract structures observed. Large alleles likely occur on the same haplotype as DM2 mutations. We previously identified a single

shared haplotype extending across at least 132 kb

among DM2 patients from different European populations.9 With the exception of the (CCTG)n expansion, the DM2 mutant haplotype was identical to the most common haplotype (47.2%) in normal individuals, a situation reminiscent of that seen in DM1.12,15,16 Taken together, these data suggested a single founding mutation in DM2 patients of European origin, occurring between 4,000 and 12,000 years ago.9 The majority of the known SNP markers in the region are monomorphic in the Caucasian population, and those that are not have minor allele frequencies ⬍5%. The single highly informative marker in this haplotype is rs1871922, located in intron 1 of ZNF9, approximately 12 kb from the repeat tract, with approximately equal allele frequencies in European Caucasians and the C allele in linkage disequilibrium with the DM2 expansion. This allele is monomorphic in the chimpanzee (UCSC Browser, dbSNP), indicating that this allele is ancestral. For the four premutation alleles, all individuals had at least one C allele at rs1871922 and one was homozygous for C, consistent with the hypothesis that the premutation allele occurs on the same haplotype as the DM2 expansion. Among the 88 African American samples genotyped, 69 were C/C, 2 were A/A, and 17 were A/C. These findings did not deviate significantly from Hardy–Weinberg equilibrium. This locus was not typed as part of the HapMap project, and no frequency information was available at this locus for sub-Saharan populations, but the C allele should be very common, based on our results. It is even possible that the C allele is monomorphic in sub-Saharan populations and that the presence of the A allele in our African American chromosomes is due to population admixture. Of the 10 independent large interrupted alleles sequenced, 7 are in individuals homozygous for the C allele at rs1871922. The remaining 4 individuals were heterozygous. No individual with a large allele was homozygous for the A allele. Thus, it is altogether possible that there is a single haplotype associated with all large alleles, of both uninterrupted and multiple-interruption types. However, lacking specific phase information for the African American samples, it is impossible to demonstrate this relationship conclusively. All SNP genotypes are included in the table. Large uninterrupted alleles are unstable. We observed

that the entire locus was surprisingly unstable in cloning, irrespective of allele size or presence of interruptions. Allele distributions observed on cloning are presented in figure e-1 on the Neurology® Web site at www.neurology.org. Sequencing showed that all alNeurology 72

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493

Figure 2

Repeat tract structures of the DM2 locus observed in 44 sequenced alleles

We observed three classes of repeat tracts at the DM2 locus: 1) interrupted short alleles with up to (CCTG)24 and two interruptions, 2) interrupted long alleles with up to (CCTG)32 and up to four interruptions, and 3) uninterrupted (CCTG)22–33. Repeat tracts ⱖ160 bp often showed duplication of the (GCTG)-(CCTG)-(TCTG)-(CCTG)n portion of the tract. Occasional variations in the interruption sequence were also observed. Repeat tract length in bp and number of alleles observed are indicated for each variant (n ⫽ 44). The most common short allele (A) is also found in the Rhesus monkey (NW_001096632), suggesting that it is ancestral. Variants B, D, and F were only seen in the African American samples. Uninterrupted alleles (G and H) were seen only in Caucasians.

leles had many clones with deletions in the (TG)n tract. On the other hand, only uninterrupted alleles showed variability in the (CCTG)n tract. To distinguish between inherent (CCTG)n instability and possible cloning artifacts, we performed single genome equivalent amplification (SP-PCR). Results of the SP-PCR are shown in figure 3. Interrupted alleles, both small and large, had average mutation frequencies of 12% to 14% and were considerably more stable than uninterrupted alleles, with average mutation frequency of approximately 40%. This difference was highly significant for all four uninterrupted alleles tested. The p values for the individual samples were 6.5 ⫻ 10⫺7 (896001), 4.3 ⫻ 10⫺4 (8103001), 1.4 ⫻ 10⫺4 (8102001), and 3.9 ⫻ 10⫺7 (106001). A muscle biopsy from an individual with a large interrupted allele [tract length of 180 bp or (CCTG)23 with four interruptions] was examined by RNAfluorescent in situ hybridization (FISH) and was found not to form ribonuclear inclusions characteristic of uninterrupted disease-causing repeats (data not shown). DISCUSSION We investigated the structure and stability of large repeat alleles at the DM2 locus. Such alleles are rare in the European Caucasian population (⬍2%) but significantly more common among African Americans (8.5% in our sample; p ⫽ 494

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1.769 ⫻ 10⫺6). We cloned and sequenced large alleles from nine independent African American samples. These alleles either had two interruptions with unusually long (CCTG)n or (TCTG)n tracts, or they had average (CCTG)n tract lengths with three or four interruptions. Four of the five large Caucasian alleles had uninterrupted (CCTG)23–33 tracts. The remaining large Caucasian allele was of the multiple interruption type. The four uninterrupted alleles were shown to be extremely unstable by SP-PCR when compared with alleles with interruptions. Thus, the instability of the (CCTG)n tract seemed to be preexistent in the somatic DNA of these individuals and was not an artifact of cloning. Studies of repeat instability, primarily in the trinucleotide expansion diseases DM1 and Huntington disease, have suggested that there exists a threshold for repeat expansion of between 100 and 200 bp. Uninterrupted repeats of less than this length are stable, whereas larger repeats expand with frequencies of 80% to 100%.17,18 The unstable (CCTG)23–33 alleles described here, with lengths of 92 to 132 bp, seem to support the threshold hypothesis and extend it to include tetranucleotide repeats. Interestingly, the mutation frequency for normal interrupted alleles at the DM2 locus by SP-PCR (12%–14%) is extraordinarily high. Other microsatellite repeats used to assess instability have typical mutation frequencies ⬍4%.13

Figure 3

Results of small-pool PCR experiment

The DM2 locus was constitutively more unstable than other microsatellite loci commonly used to assess instability. Sequencing revealed that this instability is confined to the (TG)n portion of the tract. Bars represent number of alleles counted in single genome equivalent amplification (small-pool PCR). Solid black and white bars represent the progenitor alleles and striped bars represent novel alleles identified. Both small (A) and large (B) interrupted alleles had average mutation frequencies of 12% to 14%. Uninterrupted alleles (C) had mutation frequencies ranging from 30% to 53%, with an average of 39.4%. These alleles showed instability of the (CCTG)n tract as well as the (TG)n. The mutation frequencies for uninterrupted alleles were highly significantly different from interrupted controls. The p values for the four premutation alleles were 6.5 ⫻ 10⫺7 (896001), 4.3 ⫻ 10⫺4 (8103001), 1.4 ⫻ 10⫺4 (8102001), and 3.9 ⫻ 10⫺7 (106001).

This observation is consistent with the instability observed in the clones. It is possible that the reason for this high mutation frequency is related to the tendency of the (TG)n tract to form Z-DNA.19 We identified a DM2 family with nonmendelian segregation of a small amplifiable DM2 expansion. Although the exact size of the mutant expansion was not determined, the proband and his brother had predominant alleles in their peripheral blood of (CCTG)55 and (CCTG)61, respectively. Clones of the four premutation alleles exhibited instability

of their (CCTG)n tracts comparable with those observed in these two small expansion alleles. Although phase could not be determined, we observed that all the large alleles occurred coincident with the C allele at rs1871922. This observation suggested a scenario by which such large alleles might have evolved from small alleles by unequal crossing over (figure 4A). The conversion of a normal stable allele to an expandable premutation allele at the DM2 locus would require both the loss of the stabilizing interruption(s) and an increase of the repeat length. Several mechanisms have been proposed by which stabilizing interruptions could be lost. It has been previously shown that loss of mismatch repair activity predisposes to loss of stabilizing interruptions in yeast.20 Alterations in replication origin through activation of cryptic initiation sites, insertion of repetitive elements, or epigenetic events have likewise been suggested.18 Although unequal meiotic recombination is unlikely to account for repeat expansion per se, it remains a possible mechanism by which interruptions could be lost.18 The reciprocal products of such an unequal crossover between two short normal alleles would be one long allele with four interruptions and another with no interruptions. If instability is a function of contiguous (CCTG)n length, over time such an uninterrupted allele could reach a threshold at which expansion accelerates. Figure 4B proposes an evolutionary model for the DM2 mutation. Most probably, the first large alleles arose in Africa, possibly by unequal meiotic crossing over. Although other mechanisms are certainly possible, the unequal crossing-over model is attractive, because both uninterrupted and multiply interrupted alleles would arise in the germ line from the same event. This event would have occurred while the C allele predominated in the population, as seems to be the case in individuals of sub-Saharan descent. Over time, the most common alleles, both large and small, acquired rare variants, involving mainly alternative interruptions, whereas the uninterrupted alleles continued to either expand or die out. There is no way to know whether selection has acted over time to keep the frequency of these alleles low. Based on current population frequencies, the predominant alleles in the population that migrated out of Africa were of the two-interruption variety. However, some uninterrupted alleles were also present. It is likely that the A allele at rs1871922 arose after the exodus from Africa on the same chromosome as a two-interruption allele. However, this haplotype seems to have rapidly increased in frequency, perhaps because of selection at some nearby locus. This inference is supported by the Tajima D statistic21 (UCSC Genome Browser) shown in figure 4C, which indicates positive selection in Europeans in the region approximately 100 kb centromeric to ZNF9. Neurology 72

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Figure 4

Model for evolution of the DM2 mutation

(A) Mis-pairing and unequal crossing over of DM2 repeat tracts (A1) can result in large alleles. Reciprocal crossover products can have either multiple interruptions (A2) or none (A3). These uninterrupted alleles are inherently unstable and eventually expand to pathogenic range (A4). (B) Evolutionary model for the DM2 locus. The ancestral hominid allele probably had a short (CCTG)n tract with two interruptions in cis with the C allele at rs1871922, the same as the most common modern allele (green line). Based on the higher frequency of large alleles in our African American samples, the first large alleles probably arose in Africa, possibly by unequal crossing over. Long alleles with multiple interruptions (orange line) accumulated variants, whereas uninterrupted alleles (pink line) gradually expanded, eventually reaching a pathogenic threshold (red line). The most parsimonious scenario is that the A allele at rs1871922 arose after the exodus from Africa on the same chromosome as a small two-interruption allele (blue line). The apparent rapid increase in frequency of the A allele could be due to selection at some nearby locus. (C) The Tajima D statistic21 indicates probable positive selection (D ⬍⫺2) in Europeans in the region approximately 100 kb centromeric to ZNF9.

Although this scenario is attractive and ties together a number of different observations, it also raises some interesting questions. For example, if large alleles actually arose by unequal crossing over, we would expect to find uninterrupted alleles in Africa. Did these alleles exist and subsequently disappear? If so, why? If not, why is there no DM2 in sub-Saharan Africans? Symptoms of DM2 are generally milder than DM1 and usually selfreported. Therefore, one explanation could simply be the unavailability of diagnostic opportunities. Larger population-based studies would be needed to determine whether uninterrupted alleles exist in subSaharan populations. Of primary importance is the frequency of premutation alleles among Caucasians of European de496

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scent, the population where DM2 occurs. In one set of 973 European Caucasian nondisease alleles (169 were independent chromosomes), we observed a single premutation allele (0.6%). In a second set of 1,062 Finns (2,124 independent chromosomes), we identified three additional premutation alleles (0.1%). Taken together, these findings would suggest a premutation frequency of approximately 0.1% to 0.6%, although for accurate assessment a more systematically ascertained sample set would be needed. Nevertheless, these results strongly suggest that DM2 premutation alleles are present in the European Caucasian population at an appreciable frequency. It is not yet known whether such alleles may have any clinical or phenotypic consequence.

ACKNOWLEDGMENT The authors thank the participating families for their cooperation. The authors thank Charles A. Thornton (University of Rochester) for contribution of DNA samples and Wolfram Kress (University of Wu¨rzburg) for sharing of molecular diagnostic data. The authors acknowledge Tamer Ahmed and Vlad Codrea for technical assistance with the genotyping, cloning, and sequencing; Marzena Wojciechowska for the RNA-FISH; and Keith A. Baggerly for statistical assistance. They also wish to thank the European Neuro-Muscular Centre for their continued support of the International Working Group on DM2/PROMM and Other Myotonic Dystrophies.

10.

11.

12.

Received April 21, 2008. Accepted in final form July 22, 2008. REFERENCES 1. Harper PS. Myotonic Dystrophy, 3rd ed. London, UK: W.B. Saunders; 2001. 2. Krahe R, Bachinski LL, Udd B. Myotonic dystrophy type 2: clinical and genetic aspects. In: Wells RD, Ashizawa T, eds. Genetic Instabilities and Neurological Diseases. Amsterdam, Boston: Academic Press/Elsevier; 2006:131–150. 3. Brook JD, et al. Correction: Molecular basis of myotonic dystrophy: expansion of a trinucleotide (CTG) repeat at the 3= end of a transcript encoding a protein kinase family member. Cell 1992;69:385. 4. Fu YH, Pizzuti A, Fenwick RG Jr, et al. An unstable triplet repeat in a gene related to myotonic muscular dystrophy. Science 1992;255:1256–1258. 5. Mahadevan M, Tsilfidis C, Sabourin L, et al. Myotonic dystrophy mutation: an unstable CTG repeat in the 3= untranslated region of the gene. Science 1992;255:1253–1255. 6. Liquori CL, Ricker K, Moseley ML, et al. Myotonic dystrophy type 2 caused by a CCTG expansion in intron 1 of ZNF9. Science 2001;293:864–867. 7. Ashizawa T, Epstein HF. Ethnic distribution of myotonic dystrophy gene. Lancet 1991;338:642–643. 8. Udd B, Meola G, Krahe R, et al. Report of the 115th ENMC workshop: DM2/PROMM and other myotonic dystrophies. 3rd Workshop, 14 –16 February 2003, Naarden, The Netherlands. Neuromuscul Disord 2003;13:589–596. 9. Bachinski LL, Udd B, Meola G, et al. Confirmation of the type 2 myotonic dystrophy (CCTG)n expansion mutation in patients with proximal myotonic myopathy/proximal myotonic dystrophy of different European origins: a single

13.

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18. 19. 20.

21.

shared haplotype indicates an ancestral founder effect. Am J Hum Genet 2003;73:835–848. Liquori CL, Ikeda Y, Weatherspoon M, et al. Myotonic dystrophy type 2: human founder haplotype and evolutionary conservation of the repeat tract. Am J Hum Genet 2003;73:849–862. Saito T, Amakusa Y, Kimura T, et al. Myotonic dystrophy type 2 in Japan: ancestral origin distinct from Caucasian families. Neurogenetics 2008;9:61–63. Imbert G, Kretz C, Johnson K, Mandel JL. Origin of the expansion mutation in myotonic dystrophy. Nat Genet 1993;4:72–76. Coolbaugh-Murphy MI, Xu J, Ramagli LS, Brown BW, Siciliano MJ. Microsatellite instability (MSI) increases with age in normal somatic cells. Mech Ageing Dev 2005; 126:1051–1059. Coolbaugh-Murphy M, Maleki A, Ramagli L, et al. Estimating mutant microsatellite allele frequencies in somatic cells by small-pool PCR. Genomics 2004;84:419–430. Neville CE, Mahadevan MS, Barcelo JM, Korneluk RG. High resolution genetic analysis suggests one ancestral predisposing haplotype for the origin of the myotonic dystrophy mutation. Hum Mol Genet 1994;3:45–51. Yamagata H, Miki T, Nakagawa M, Johnson K, Deka R, Ogihara T. Association of CTG repeats and the 1-kb Alu insertion/deletion polymorphism at the myotonin protein kinase gene in the Japanese population suggests a common Eurasian origin of the myotonic dystrophy mutation. Hum Genet 1996;97:145–147. Gatchel JR, Zoghbi HY. Diseases of unstable repeat expansion: mechanisms and common principles. Nat Rev Genet 2005;6:743–755. Mirkin SM. Expandable DNA repeats and human disease. Nature 2007;447:932–940. Sinden RR. Molecular biology: DNA twists and flips. Nature 2005;437:1097–1098. Rolfsmeier ML, Lahue RS. Stabilizing effects of interruptions on trinucleotide repeat expansions in Saccharomyces cerevisiae. Mol Cell Biol 2000;20:173–180. Tajima F. Statistical method for testing the neutral mutation hypothesis by DNA polymorphism. Genetics 1989; 123:585–595.

Learn. Earn. Network. 2009 AAN Annual Meeting: An Excellent Value • Learn about the latest scientific advances in neurology • Earn valuable CME credit and fulfill Maintenance of Certification requirements • Network with your peers at exciting social events all week long • Enjoy the convenience and value of all this and more—in just one meeting Early registration and hotel deadline is March 20, 2009. Register today at www.am.com/AM2009.

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497

Transcranial magnetic stimulation in ALS Utility of central motor conduction tests

A.G. Floyd, BA Q.P. Yu, PhD P. Piboolnurak, MD M.X. Tang, PhD Y. Fang, MS W.A. Smith, BA J. Yim L.P. Rowland, MD H. Mitsumoto, MD S.L. Pullman, MD

ABSTRACT

Objective: To investigate transcranial magnetic stimulation (TMS) measures as clinical correlates and longitudinal markers of amyotrophic lateral sclerosis (ALS).

Methods: We prospectively studied 60 patients with ALS subtypes (sporadic ALS, familial ALS, progressive muscular atrophy, and primary lateral sclerosis) using single pulse TMS, recording from abductor digiti minimi (ADM) and tibialis anterior (TA) muscles. We evaluated three measures: 1) TMS motor response threshold to the ADM, 2) central motor conduction time (CMCT), and 3) motor evoked potential amplitude (correcting for peripheral changes). Patients were evaluated at baseline, compared with controls, and followed every 3 months for up to six visits. Changes were analyzed using generalized estimation equations to test linear trends with time.

Results: TMS threshold, CMCT, and TMS amplitude correlated (p ⬍ 0.05) with clinical upper motor Address correspondence and reprint requests to Dr. Seth L. Pullman, The Neurological Institute, 710 West 168th Street, New York, NY 10032 [email protected]

neuron (UMN) signs at baseline and were different (p ⬍ 0.05) from normal controls in at least one response. Seventy-eight percent of patients with UMN (41/52) and 50% (4/8) of patients without clinical UMN signs had prolonged CMCT. All three measures revealed significant deterioration over time: TMS amplitude showed the greatest change, decreasing 8% per month; threshold increased 1.8% per month; and CMCT increased by 0.9% per month.

Conclusions: Transcranial magnetic stimulation (TMS) findings, particularly TMS amplitude, can objectively discriminate corticospinal tract involvement in amyotrophic lateral sclerosis (ALS) from controls and assess the progression of ALS. While central motor conduction time and response threshold worsen by less than 2% per month, TMS amplitude decrease averages 8% per month, and may be a useful objective marker of disease progression. Neurology® 2009;72:498–504 GLOSSARY ADM ⫽ abductor digiti minimi; ALS ⫽ amyotrophic lateral sclerosis; ANOVA ⫽ analysis of variance; CI ⫽ confidence interval; CMAP ⫽ compound motor action potential; CMCT ⫽ central motor conduction time; DTR ⫽ deep tendon stretch reflex; fALS ⫽ familial ALS; GEE ⫽ generalized estimation equations; LMN ⫽ lower motor neuron; MEP ⫽ motor evoked potential; PLS ⫽ primary lateral sclerosis; PMA ⫽ progressive muscular atrophy; sALS ⫽ sporadic ALS; TA ⫽ tibialis anterior; TMS ⫽ transcranial magnetic stimulation; UMN ⫽ upper motor neuron.

ALS is diagnosed by finding clinical upper motor neuron (UMN) and lower motor neuron (LMN) signs. LMN dysfunction can be confirmed objectively through electromyography, whereas UMN dysfunction lacks a comparable established marker. Detection of subclinical UMN dysfunction would be helpful for diagnostic purposes, and objective markers of UMN dysfunction may also help clarify the relationship between ALS and its variants, including progressive muscular atrophy (PMA). PMA has been diagnosed by the absence of clinical UMN signs in the presence of LMN findings for several years. However, autopsies on patients with clinically diagnosed PMA show corticospinal tract degeneration in half of the patients. Therefore, clinical examination alone does not disclose all relevant UMN pathology.1-3

From the Clinical Motor Physiology Laboratory (A.G.F., Q.P.Y., P.P., Y.F., W.A.S., J.Y., S.L.P.) and Eleanor and Lou Gehrig MDA/ALS Research Center (L.P.R., H.M.), Department of Neurology, and Department of Biostatistics and Sergievsky Center (M.X.T.), Columbia University Medical Center, New York, NY. Funded by NIH grant NS41672-01 (H.M.), the Muscular Dystrophy Association, and MDA Wings Over Wall Street. Disclosure: The authors report no disclosures. 498


Table 1

sALS

Demographic and clinical information

No.

Age at visit 1, y

M:F

41

53 ⫾ 11

30:11

Duration of illness: Onset to baseline visit, d 852 ⫾ 1,206

Site of onset, % bulbar/% limb 10/90

fALS

5

56 ⫾ 13

0:5

1,251 ⫾ 961

20/80

PLS

6

55 ⫾ 9

2:4

2,398 ⫾ 2,172

17/83

8

65 ⫾ 13

8:0

789 ⫾ 320

All UMN cases

52

53 ⫾ 11

32:20

1,069 ⫾ 1,387

12/88

All cases

60

55 ⫾ 12

40:20

1,032 ⫾ 1,298

10/90

PMA

0/100

When patients enrolled, the duration of disease from onset to baseline was less than 4 years, but patients were followed more than 4 years to satisfy PLS criteria. sALS ⫽ sporadic amyotrophic lateral sclerosis; fALS ⫽ familial amyotrophic lateral sclerosis; PLS ⫽ primary lateral sclerosis; PMA ⫽ progressive muscular atrophy; UMN ⫽ upper motor neuron.

Transcranial magnetic stimulation (TMS) is a neurophysiologic technique used to assess the function of central motor pathways. Standard TMS measures include motor threshold, central motor conduction time (CMCT), and motor evoked potential (MEP) amplitudes. There have been numerous studies of TMS in ALS for over 20 years, investigating a multitude of issues on UMN physiology, cortical excitability and inhibition, the utility of the silent period and other responses to detect early changes in ALS, and the relationship between the UMN and LMN, many of which have been contradictory.4-11 Threshold, CMCT, and MEP are three useful measures of single pulse TMS; however, the diagnostic success of these nonspecific UMN measures varies widely from 16% to 100%.5,9,12-17 Reasons include different muscle recording sites, different methods of calculating CMCT,4,18 and different thresholds for defining diagnostic success (i.e., 1/4 sites prolonged vs 4/4). The TMS MEP is activated through both UMN and LMN pathways after magnetic stimulation of the cortex. In ALS, TMS amplitudes are often attenuated or absent19-21; even patients with pseudobulbar features are prone to have small, desynchronized MEPs.12 Reduced TMS MEP/M-wave amplitude ratio may be more closely correlated with pyramidal tract involvement than prolonged CMCT.21 There are fewer investigations of TMS amplitude compared to CMCT. One study found TMS amplitude abnormalities in only 16 of 54 patients with ALS (30%),5

whereas another found a significant difference between patients and controls at three recording sites, with amplitude reductions in almost all patients.19 The sensitivity of baseline TMS measures in ALS has been studied extensively, with mixed results, but there have been few longitudinal studies of TMS changes in ALS. Most reports showed no change in TMS threshold with time6,22,23 but one noted significant increase.17 CMCT has generally been reported to not increase with time.6,22,24 In a small series, TMS MEP amplitude and MEP/peripheral compound motor action potential (CMAP) ratio did not change with disease progression.22 In this study, we report on TMS threshold, CMCT, and amplitude data that were not included in an overarching report on neurophysiologic, brain imaging, and clinical methods to quantify and track progression in patients with ALS.25 METHODS Subjects. Patients with suspected ALS or ALS variants were evaluated for eligibility and enrolled through the Eleanor and Lou Gehrig MDA/ALS Research Center at Columbia University as previously described.25 Qualifying patients included those with a suspected diagnosis according to El Escorial criteria26 of sporadic or familial ALS (sALS and fALS), primary lateral sclerosis (PLS), and PMA. The study enrolled 60 patients, 23 of whom had evaluations spanning a minimum of four visits up to 1.5 years (table 1) and measured clinical variables as described.25 Control data for CMCT baseline measures were from 33 normal subjects (mean ⫾ SD age 44.8 ⫾ 11.8 years) collected previously. All patients provided informed consent, and this study protocol was approved in accordance with Columbia University Medical Center Institutional Review Board guidelines.

Neuromuscular assessment. Clinical examination relevant to TMS testing at each baseline and follow-up visit consisted of height, forced vital capacity measurements, strength in 36 skeletal muscles including grip and pinch, muscle tone, deep tendon stretch reflexes (DTRs), pathologic responses (Babinski and Hoffmann), and finger and foot tapping speed. Examinations were performed by a senior neurologist and an experienced ALS clinical evaluator.25 Electrophysiologic procedures. Motor conduction tests using TMS and peripheral spinal root stimulation were obtained at baseline and at 3-month intervals up to six visits. TMS was performed using a cap stimulator (Cadwell MES-10; Cadwell Inc., Kennewick, WA) at Cz recording from bilateral abductor digiti minimi (ADM) and tibialis anterior (TA) muscles in a belly– tendon arrangement with 1-cm disc electrodes at 100% machine output. Electrical spinal root stimulation was performed over C7 and L1 using a high voltage stimulator (Digitimer, Ltd., Hertfordshire, UK) at the same output settings across all visits for each patient. Supramaximal stimulation was not possible with either TMS or spinal nerve root stimulation. Neurology 72

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Figure

Longitudinal tracings from a sample patient with sporadic amyotrophic lateral sclerosis from prestudy through visits 1 to 6

cluded from amplitude analyses due to missing data and low sample size (n ⫽ 5). Longitudinal change in TMS measures were analyzed using generalized estimation equations (GEE) to test linear trends as the percent change with time. Each patient’s data were treated as a cluster with repeated measurements at different visits, and used in an exchangeable working correlation matrix.28,29 Peripheral MEP amplitude measures were included as covariates when assessing change in TMS amplitudes over time. Interactions of time with diagnostic group (UMN vs PMA) and site of onset (bulbar vs limb) also were investigated.

Thirty-six of the 60 patients completed two or more follow-up visits, and 11 finished all six follow-up visits spanning a period of 1.5 years, including prestudy baseline visits (table 1).

RESULTS Amplitude and time are standardized across all visits. (A) Transcranial magnetic stimulation (TMS) motor evoked potential (MEP) responses from cortical stimulation over the vertex. Traces are from the right and left abductor digiti minimi (ADM) (A1 and A2), right and left tibialis anterior (TA) (A3 and A4). (B) Peripheral MEP responses stimulating over the cervical spine to the right and left ADM (B5 and B6), and lumbar spine to the right and left TA (B7 and B8).

Resting TMS threshold to the ADM was recorded as the minimum stimulus intensity producing consistent MEPs with peak-to-peak amplitudes greater than 50 ␮V in at least 5 of 10 consecutive stimulations.27 Stimulation was increased in 1% to 2% increments of maximum stimulator output until threshold was obtained. CMCT was calculated through subtraction of the minimal spinal root stimulation latency from the upper spine (for the arms) and lower spine (for the legs) from the minimal latency achieved by cortical stimulation. TMS and peripheral MEPs were recorded at an amplifier gain of 5 mV per division with high and low pass filters set at 10 Hz and 10 kHz. Latencies and amplitudes were determined manually at a sensitivity of 200 ␮V/division with a time base of 10 msec/division. Multiple TMS and electrical spinal stimuli were applied to obtain at least two identical trials at each stimulation site to confirm reproducibility. Amplitudes were calculated from baseline to highest negative peak of the MEP responses at each visit for both TMS and electrical spinal recordings (figure). When stimulus artifact obscured the signal baseline, the MEP amplitude was measured from the negative peak to an interpolated baseline point directly below. TMS and peripheral amplitudes were collated by a technician blinded to the patient and visit number.

Data analysis. Baseline analyses included all patients (n ⫽ 60). One-way analyses of variance (ANOVAs) were performed comparing the four diagnostic groups (sALS, PLS, PMA, and fALS). In the case of a significant ANOVA result, Tukey post hoc analyses were performed to determine which groups differed. Additionally, sALS, PLS, and fALS were collapsed into a single UMN group. t Tests were used to compare UMN vs PMA groups, and bulbar vs limb onset groups. Pearson product-moment correlation coefficients were used to correlate CMCT and threshold stimulation value, and clinical variables at baseline. Partial correlations were performed to determine the relationship between the TMS amplitudes and clinical variables, controlling for peripheral MEP amplitudes. CMCT was dichotomized into normal and abnormal categories for the purpose of assessing diagnostic sensitivity. CMCT was rated as abnormal when two SD greater than the average of the control group. The CMCT in the control group was 7.8 ⫾ 1.5 msec to the ADM, 13.5 ⫾ 1.6 msec to the TA. Amplitudes were not dichotomized. The diagnostic category fALS was ex500

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Threshold baseline. Baseline TMS thresholds were

greater in UMN than in PMA, but did reach significance (38 ⫾ 9% vs 31 ⫾ 6%, p ⫽ 0.058). There was no difference in TMS threshold by site of disease onset. When compared with clinical and physiologic variables, ADM threshold values correlated significantly with finger tapping rate, the brachioradialis DTR, ipsilateral CMCT, and TMS amplitudes (table 2). Threshold change over time. TMS thresholds in-

creased among all cases and UMN cases by 1.8% per month (p ⬍ 0.0001). Among the eight PMA cases available for analysis, threshold did not change significantly, nor were any trends apparent in that group. CMCT baseline. CMCT at baseline did not correlate with patient age or duration of disease. CMCT to the TA was prolonged relative to controls among patients with sALS (mean ⫽ 24.0 msec, 95% confidence interval [CI] ⫽ 19.7–28.3 msec; p ⬍ 0.0005) and patients with fALS (mean ⫽ 23 msec, 95% CI ⫽ 17.7–28.3 msec; p ⫽ 0.01). TA CMCT also was prolonged in the combined UMN group (sALS, fALS, and PLS, p ⬍ 0.0005) compared to control values to the TA (mean ⫽ 13.5 msec, 95% CI ⫽ 12.0 –15.0 msec). CMCT to the ADM showed no difference between patients and controls. There was no CMCT difference among the four diagnostic groups or between patients with bulbar vs limb onset. The combined UMN patients had significantly longer CMCTs to both arms and legs compared with PMA patients. Dichotomized CMCT values revealed that 78% (41/52) of UMN patients had at least one prolonged central conduction, and 13% (7/52) had CMCT prolongation to all four limbs. Four of the eight PMA cases (50%) had prolonged CMCT to the TA. CMCT to the ADM correlated significantly with increased DTRs in the brachioradialis, as well as decreased finger dexterity. CMCT to the TA correlated

Table 2

Clinical and physiologic correlations CMCT*

TMS amplitude†

Threshold* ADM

ADM

TA

ADM

TA

Brachioradialis

⫹0.28

⫹0.34

—

⫺0.34

—

Biceps

NS

⫹0.32

—

NS

—

Triceps

NS

⫹0.29

⫺0.32

—

Knee

—

—

⫹0.34

—

NS

Ankle

—

—

⫹0.33

—

NS

Babinski

—

—

⫹0.38

—

NS

⫹0.45

—

⫺0.47

—

DTR

Hoffmann Dexterity Finger tapping

⫺0.53

⫺0.32

—

⫹0.61

—

Foot tapping

—

—

NS

—

⫹0.55

NS

NS

—

NS

—

Grip

NS

NS

—

⫹0.35

—

First dorsal interosseous

NS

NS

—

NS

—

Strength Pinch

Abductor pollicis brevis

NS

NS

—

NS

—

Inversion

—

—

NS

—

⫹0.41

Dorsiflexion

—

—

NS

—

⫹0.48

Significance level set at two-tailed p ⬍ 0.05. *Pearson correlation coefficients. †Partial correlation coefficients, controlling for peripheral amplitude. ADM ⫽ abductor digiti minimi; CMCT ⫽ central motor conduction time; TA ⫽ tibialis anterior; TMS ⫽ transcranial magnetic stimulation; DTR ⫽ deep tendon reflex; NS ⫽ not significant.

with increased patellar and ankle DTRs. There was no correlation between CMCT and muscle strength measures. Patients with a Babinski sign had longer CMCT to the TA than those without findings (29.5 ⫾ 15.7 msec compared to 20.5 ⫾ 10.2 msec), and those with positive Hoffmann signs had longer CMCT to the ADM (18.2 ⫾ 14.6 msec compared to 7.5 ⫾ 0.7 msec). CMCT and clinical correlations are summarized in table 2. CMCT change over time. Averaged across all cases,

CMCT to the TA increased by an average of 0.9%

Table 3

Baseline TMS and peripheral MEP amplitudes TMS amplitude ADM (mV)

TMS amplitude TA (mV)

ADM peripheral amplitude (mV)

TA peripheral amplitude (mV)

sALS

1.3 ⫾ 1.2

0.7 ⫾ 0.8*

2.1 ⫾ 1.9*

3.0 ⫾ 2.6

fALS

1.4 ⫾ 2.2

0.9 ⫾ 1.0

2.6 ⫾ 1.9*

2.5 ⫾ 2.2

PLS

2.7 ⫾ 2.0

2.2 ⫾ 2.4

6.3 ⫾ 2.2

5.2 ⫾ 2.7

PMA

2.3 ⫾ 0.8

1.0 ⫾ 0.5

2.4 ⫾ 1.6*

2.2 ⫾ 2.5

*Significantly smaller than corresponding PLS amplitude. TMS ⫽ transcranial magnetic stimulation; MEP ⫽ motor evoked potential; ADM ⫽ abductor digiti minimi; TA ⫽ tibialis anterior; sALS ⫽ sporadic amyotrophic lateral sclerosis; fALS ⫽ familial amyotrophic lateral sclerosis; PLS ⫽ primary lateral sclerosis; PMA ⫽ progressive muscular atrophy.

per month (p ⫽ 0.016). The interaction between upper vs lower MN involvement and time was significant such that UMN cases had greater TA CMCT increase than did PMA cases. The increase in CMCT in PMA cases was not significant when analyzed independently. CMCT to the ADM did not show significant increase over time. Peripheral conduction times remained unchanged in UMN cases. However, in PMA cases peripheral conduction times for both the ADM and TA increased between 0.5% and 0.6% at each successive visit (p ⬍ 0.005). Amplitude baseline. A one-way ANOVA revealed significant amplitude differences among the diagnostic groups. Tukey HSD post hoc comparisons indicated that PLS had significantly larger, more polyphasic, and dispersed TMS amplitudes than sALS in the TA. Peripheral amplitudes for PLS, however, were neither polyphasic nor dispersed, and were significantly larger than all other diagnostic groups (sALS, fALS, PMA) in the ADM (table 3). There was no difference in baseline amplitude between bulbar and limb onset groups. Partial correlations between clinical signs and baseline TMS amplitudes, controlling for peripheral amplitudes using the latter as covariates in the GEE model, showed significant positive relationships between baseline TMS amplitudes, dexterity, and strength. There was a negative relationship between the brachioradialis and triceps DTRs and TMS amplitude to the ADM. Similarly, patients with positive Hoffmann signs had lower TMS amplitudes to the ADM (2.4 ⫾ 1.2 mV compared to 1.0 ⫾ 1.3 mV). Partial correlation results of Hoffmann sign presence vs TMS amplitude to the ADM, controlling for peripheral amplitude, was also significant (table 2). In the legs, TMS amplitudes correlated directly with foot tapping as well as dorsiflexion and inversion strength. Amplitude change over time. TMS amplitude changes over time were analyzed controlling for the peripheral MEP amplitude at each visit by including peripheral amplitude data as a covariate in the GEE model. Across all cases, there was a decrease in TMS amplitude to the ADM of 2.8% per month (p ⬍ 0.0001) as well as decrease in TMS amplitude to the TA of 8.0% per month (p ⬍ 0.05) after controlling for the corresponding peripheral amplitude decreases. Amplitude decreases were found in both UMN and PMA cases analyzed separately. TMS amplitude drop to the ADM and TA in PMA was greater than in UMN cases, but the effect did not reach significance. Neurology 72

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501

We demonstrate that central motor conduction tests using single pulse TMS can both detect corticospinal tract involvement in ALS and measure disease progression, in agreement with reviews of TMS methods.7,9 Three measures from this study (TMS threshold, CMCT and TMS amplitude) revealed differences at baseline and showed changes in patients with ALS over time. TMS amplitude was abnormal and worsened at a greater rate than either threshold or CMCT. TMS amplitude change, adjusting for peripheral change, was three to eight times greater per month than CMCT or threshold. Though neither motor cortex nor spinal roots could be stimulated supramaximally, this was corrected using peripheral changes in MEP amplitude in the GEE model, and TMS/peripheral amplitude ratios. The differentially greater changes on TMS amplitude in ALS could be due to diminished number of cortical motor neuron cell bodies, axonal loss, desynchronization, and conduction abnormalities affecting long tract axons. Though other longitudinal studies reported no significant CMCT prolongation over time,6,22,24 we found most patients had a prolonged baseline CMCT that gradually but significantly increased in UMN patients. We believe we were able to demonstrate this effect because our sample size was larger and data collection period was longer than previous studies. PMA patients revealed less prolonged CMCTs at baseline compared to UMN patients, and did not demonstrate longitudinal changes in this measure, possibly because PMA progresses slower than other ALS subtypes.4 Nevertheless, CMCT can be abnormal in purely LMN clinical syndromes14,17 and histopathologic and immunochemical studies reveal UMN pathology in LMN patients.1,2 We found that CMCT was prolonged in 50% of our patients without clinical UMN signs. CMCT correlated with hyperreflexia and loss of dexterity, presence of Hoffmann and Babinski signs, but not with strength measures. Thus, CMCT abnormalities parallel some clinical UMN findings, and could be used to mark UMN dysfunction.14,24 The lack of correlation between CMCT and strength, however, suggests that CMCT does not measure pathophysiologic mechanisms of strength. LMN dysfunction may be the primary cause of weakness in ALS.30 Motor unit number estimation correlates well with muscle strength, but not with UMN signs such as dexterity.25 We found that TMS amplitude correlated strongly with hyperreflexia, dexterity, and strength. However, TMS amplitude did not correlate with Hoffmann or Babinski signs, suggesting that these release responses are DISCUSSION

502

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modulated by different UMN pathways than strength and dexterity. There are several limitations to this study. The average age of our normal controls, used to compare differences in baseline CMCT, was 10 years younger than in our patients. This could diminish the strength of our findings. While we did not find a significant difference between patient age and baseline CMCT, this was likely due to the wide range of abnormal CMCT in ALS. Patient data only were factored into the GEE longitudinal analyses of threshold, CMCT, and TMS amplitude; control data were not obtained over time. We also did not analyze the ADM or TA MEP after peripheral nerve stimulation as another measure of lower motor neuron involvement. These probably would not have changed our results of up to 8% change in TMS amplitude. However, it would be important to determine the sensitivity of TMS amplitude in detecting UMN changes, as well as establish longitudinal findings in age-matched controls. Other concerns may be that minimal F-wave latency methods may be better at determining peripheral conduction times in comparison to magnetic paravertebral stimulation.4,9 However, our subtraction of method used high voltage electrical root stimulation, which arguably provided a more focused stimulus than a paravertebral magnetic pulse. We did not test bulbar or proximal muscles such as the masseter or biceps brachii where subclinical abnormalities may occur earlier and more reliably in ALS.31,32 Future investigations should study longer ALS disease progression by incorporating patients at the earliest stages of disease using GEE to analyze TMS amplitudes and peripheral changes. It would be important to assess TMS amplitude longitudinally, after controlling for peripheral MEP changes, using GEE in normal controls and patients with peripheral neuropathy. Advanced electrophysiologic methods33-35 might be helpful in parsing out the contributions of central and peripheral motor pathology. Combining TMS with routine EMG and nerve conduction studies, macro-EMG, and motor unit number estimation36 of the same muscles in patients with ALS may determine more precisely the relative contributions of UMN and LMN to TMS findings in ALS over time. AUTHOR CONTRIBUTIONS M.X. Tang, Department of Biostatistics and Sergievsky Center, Columbia University, conducted the statistical analyses.

ACKNOWLEDGMENT The authors thank the following individuals for assisting in study coordination and clinical assessment: Vanessa Batista, RN, Sheila Hayes, RPT, MS, and Jacqueline Montes, RPT, MA, Columbia University. The au-

thors also thank the patients and their families for their participation in this study.

18.

Received August 1, 2008. Accepted in final form October 31, 2008. 19. REFERENCES 1. Ince PG, Evans J, Knopp M, et al. Corticospinal tract degeneration in the progressive muscular atrophy variant of ALS. Neurology 2003;60:1252–1258. 2. Iwanaga K, Hayashi S, Oyake M, et al. Neuropathology of sporadic amyotrophic lateral sclerosis of long duration. J Neurol Sci 1997;146:139–143. 3. Leung D, Hays A, Geysu K, DelBene M, Rowland L. Diagnosis of ALS: clinico-pathologic analysis of 76 autopsies. Neurology 1999;52:A164. 4. Di Lazzaro V, Oliviero A, Profice P, et al. The diagnostic value of motor evoked potentials. Clin Neurophysiol 1999;110:1297–1307. 5. Pouget J, Trefouret S, Attarian S. Transcranial magnetic stimulation (TMS): compared sensitivity of different motor response parameters in ALS. Amyotroph Lateral Scler Other Motor Neuron Disord 2000;1 suppl 2:S45–S49. 6. Mills KR. The natural history of central motor abnormalities in amyotrophic lateral sclerosis. Brain 2003;126: 2558–2566. 7. Rossini PM, Rossi S. Transcranial magnetic stimulation: diagnostic, therapeutic, and research potential. Neurology 2007;68:484–488. 8. Zanette G, Tamburin S, Manganotti P, Refatti N, Forgione A, Rizzuto N. Different mechanisms contribute to motor cortex hyperexcitability in amyotrophic lateral sclerosis. Clin Neurophysiol 2002;113:1688–1697. 9. Curra A, Modugno N, Inghilleri M, Manfredi M, Hallett M, Berardelli A. Transcranial magnetic stimulation techniques in clinical investigation. Neurology 2002;59:1851– 1859. 10. Wittstock M, Wolters A, Benecke R. Transcallosal inhibition in amyotrophic lateral sclerosis. Clin Neurophysiol 2007;118:301–307. 11. Attarian S, Vedel JP, Pouget J, Schmied A. Progression of cortical and spinal dysfunctions over time in amyotrophic lateral sclerosis. Muscle Nerve 2008;37:364–375. 12. Eisen AA, Shtybel W. AAEM mini-monograph #35: clinical experience with transcranial magnetic stimulation. Muscle Nerve 1990;13:995–1011. 13. Mills KR, Nithi KA. Peripheral and central motor conduction in amyotrophic lateral sclerosis. J Neurol Sci 1998; 159:82–87. 14. Miscio G, Pisano F, Mora G, Mazzini L. Motor neuron disease: usefulness of transcranial magnetic stimulation in improving the diagnosis. Clin Neurophysiol 1999;110: 975–981. 15. Pohl C, Block W, Traber F, et al. Proton magnetic resonance spectroscopy and transcranial magnetic stimulation for the detection of upper motor neuron degeneration in ALS patients. J Neurol Sci 2001;190:21–27. 16. Schulte-Mattler WJ, Muller T, Zierz S. Transcranial magnetic stimulation compared with upper motor neuron signs in patients with amyotrophic lateral sclerosis. J Neurol Sci 1999;170:51–56. 17. Triggs WJ, Menkes D, Onorato J, et al. Transcranial magnetic stimulation identifies upper motor neuron involvement in motor neuron disease. Neurology 1999;53:605–611.

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35. Weber M, Eisen A, Nakajima M. Corticomotoneuronal activity in ALS: changes in the peristimulus time histogram over time. Clin Neurophysiol 2000;111:169– 177. 36. Gooch CL, Harati Y. Motor unit number estimation, ALS and clinical trials. Amyotroph Lateral Scler Other Motor Neuron Disord 2000;1:71–82.

Warm and cold complex regional pain syndromes Differences beyond skin temperature?

T. Eberle, MD B. Doganci, MD, PhD H.H. Kra¨mer, MD C. Geber, MD M. Fechir, MD W. Magerl, PhD F. Birklein, MD, PhD

Address correspondence and reprint requests to Dr. Tatiana Eberle, Department of Neurology, Johannes Gutenberg University, Langenbeckstrasse 1, 55101 Mainz, Germany [email protected]

ABSTRACT

Objective: To investigate clinical differences in warm and cold complex regional pain syndrome (CRPS) phenotypes.

Background: CRPS represents inhomogeneous chronic pain conditions; approximately 70% patients with CRPS have “warm” affected limbs and 30% have “cold” affected limbs.

Methods: We examined 50 patients with “cold” and “warm” CRPS (n ⫽ 25 in each group). Both groups were matched regarding age, sex, affected limb, duration of CRPS, and CRPS I and II to assure comparability. Detailed medical history and neurologic status were assessed. Moreover, quantitative sensory testing (QST) was performed on the affected ipsilateral and clinically unaffected contralateral limbs. Results: Compared with patients who had warm CRPS, patients who had cold CRPS more often reported a history of serious life events (p ⬍ 0.05) and chronic pain disorders (p ⬍ 0.05). In cold CRPS, the incidence of CRPS-related dystonia was increased (p ⬍ 0.05), and cold-induced pain had a higher prevalence (p ⬍ 0.01). Furthermore, QST revealed a predominant sensory loss in patients with cold CRPS (p ⬍ 0.05). In contrast, patients with warm CRPS were characterized by mechanical hyperalgesia (p ⬍ 0.05) in the QST of affected limbs. Conclusion: Our results indicate that warm and cold complex regional pain syndromes (CRPS) are associated with different clinical findings, beyond skin temperature changes. This might have implications for the understanding of CRPS pathophysiology. Neurology® 2009;72:505–512 GLOSSARY A ⫽ anxiety; ANOVA ⫽ analysis of variance; CDT ⫽ cold detection threshold; CPT ⫽ cold pain threshold; CRPS ⫽ chronic regional pain syndrome; D ⫽ depression; DMA ⫽ dynamic mechanical allodynia; HADS ⫽ Hospital Anxiety and Depression Scale; HPT ⫽ heat pain threshold; MDT ⫽ mechanical detection threshold; MPS ⫽ mechanical pain sensitivity; MPT ⫽ mechanical pain threshold; NRS ⫽ numeric rating scale; NS ⫽ not significant; PHS ⫽ paradoxical heat sensations; PPT ⫽ pressure pain threshold; TSL ⫽ thermal sensory limen; QST ⫽ quantitative sensory testing; VDT ⫽ vibration detection threshold; WDT ⫽ warm detection threshold; WUR ⫽ windup ratio.

Complex regional pain syndromes (CRPS) might develop after limb trauma.1 Patients with CRPS show signs of peripheral inflammation and CNS disturbances including movement disorder,2 body perception disturbances,3 and sympathetic dysfunction.4 Considering the diversity of symptoms, it seems unlikely that CRPS is a homogeneous condition. It can be subdivided into CRPS I or II, depending on identification of peripheral nerve lesions.1 Another subclassification relies on predominating skin temperature at disease onset.5 Most CRPS cases are primarily “warm,” later turning into “cold” if CRPS becomes chronic. Yet approximately 30% have a decreased skin temperature from the beginning (primarily cold) and usually stay cold in CRPS course.6 Warm skin fits the hypothesis that CRPS reflects exaggerated post-traumatic inflammation,7 and cold skin should have a different etiology: alteration of sympathetic outflow8 or vascular disturbances.9 This differentiation is supported by the difficult treatment of primarily cold CRPS.10 Supplemental data at www.neurology.org From the Department of Neurology (T.E., B.D., H.H.K., C.G., M.F., F.B.), Johannes Gutenberg University Mainz; and Department of Physiology (W.M.), Ruprecht-Karls-Universita¨t Heidelberg, Faculty of Medicine Mannheim, Germany. Supported by the German Research Foundation, DFG Bi 579/1 and Bi 579/4 to F.B., and by the Bundesministerium f u¨ r Bildung und Forschung (DFNS; Grant: 01EM0506). Disclosure: The authors report no disclosures. Copyright © 2009 by AAN Enterprises, Inc.

505

If pathophysiologies in warm and cold CRPS are different, different clinical symptoms should be present. Such clinical differences have not yet been described. Therefore, in this study patients with primarily warm and cold CRPS were matched for age, sex, presence of CRPS I or II, affected extremity, and duration of symptoms— confounders otherwise responsible for clinical differences. We focused on history, clinical signs, and sensory profiles. METHODS Subjects. Patients were recruited from our CRPS outpatient clinic at the Neurological Department of the University Hospital Mainz, Germany. All patients fulfilled the revised diagnostic criteria as proposed by the International Association for the Study of Pain.1 Patients were immediately classified as primarily warm or primarily cold if 1) patients firmly stated that the initial skin temperature on the affected side was either increased or decreased and 2) if this statement was consistent with the skin temperature difference at the day of examination. Cases with inconsistent findings were excluded. As a measure of stability of this classification, approximately 80% of the patients were routinely reassessed 6 weeks later, and no switch between warm and cold had been observed. Patients provided written consent, and the study was approved by the local ethics committee. From all patients investigated in our department within the last years (n ⫽ 163), all 25 primarily cold cases were selected. One of the authors (W.M.), who was not involved in patient recruitment, was supplied with a file containing information about age, sex, CRPS type, affected extremity, and duration of symptoms of all patients. Based solely on these data, he selected a matched group (n ⫽ 25) from the 98 primarily warm cases for further analysis. We sought to investigate patients not treated for CRPS. This was not successful in cases with longer CRPS duration. However, for most of treatments before referral proof of efficacy is lacking and was also not reported by the patients. It is unlikely that clinical and quantitative sensory testing (QST; mainly thresholds) data are affected in a systematic manner. For details see table 1 and table e-1 on the Neurology® Web site at www.neurology.org.

Clinical investigation. All patients underwent a structured interview and detailed neurologic examination. In particular, we assessed the prevalence of other types of chronic pain, social conflicts, and known psychological comorbidities. Then, the patients completed the German versions of the Hospital Anxiety and Depression Scale and McGill Pain Questionnaire (MPQ).11 The MPQ was chosen for pain assessment because of its frequent use in previous CRPS studies. After environmental adaptation (60 minutes), skin temperature was recorded at the volar aspects of the affected and unaffected extremity by an infrared thermometer.

Quantitative sensory testing. QST was performed according to the protocol of the German Research Network on Neuropathic Pain.12 We examined the affected dorsum of the hand or foot. The corresponding mirror image site of the contralateral extremity served as a control. QST comprised the following detection and pain thresholds. Thermal sensation. We investigated detection thresholds for cold (CDT) and warm (WDT), a sequence of alternating 506

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Table 1

Summary of study patients’ characteristics CRPS type

CRPS I/II Sex, M/F

Primarily warm

Primarily cold

23/2

23/2

8/17

6/19

47 ⫾ 8

45 ⫾ 12

2/23

2/23

21 ⫾ 3

22 ⫾ 3

10

10

Sprain

4

10

After surgery

8

4

No event identified

3

1

16/9

16/9

Age, y Familial history of CRPS, positive/negative Duration of CRPS, wk Cause of CRPS Limb fracture

Affected body region, hand/foot

CRPS ⫽ complex regional pain syndrome.

cold and warm stimuli for the thermal sensory limen (TSL), cold pain threshold (CPT), and heat pain threshold (HPT). We used a thermotester equipped with a 2.8 ⫻ 2.8-cm Peltier thermode (TSA 2001-II, Medoc, Israel). Thresholds were assessed at a ramp rate of 1°C/second. During thermal testing, patients were asked to report paradoxical heat sensations (PHS). Mechanical sensation. Mechanical detection thresholds (MDTs) were investigated using von Frey filaments (Optihair2, Fruhstorfer, Marburg, Germany), and vibration detection thresholds (VDTs) were investigated at the processus styloideus ulnae or the internal malleolus using a 64-Hz Rydel-Seiffer tuning fork (average of three repetitions). Pressure pain thresholds (PPTs) were assessed at the thenar eminence or the instep using a handheld blunt pressure gauge device (1-cm2 contact area; FDN200, Wagner Instruments, Greenwich, CT). Mechanical pain thresholds (MPTs) were obtained by using sets of calibrated pinpricks with a 0.25-mm flat top cylindrical tip and a series of seven forces (8 and 512 mN) geometrically spaced by a factor of 2 (The PinPrick, Department of Physiology, Mainz, Germany). Mechanical pain sensitivity (MPS) was assessed from stimulus response functions (5 repetitions of all pinprick forces). Dynamic mechanical allodynia (DMA) was assessed by moving a cotton swab, Q-Tip, or standardized brush (Somedic, Ho¨rby, Sweden) over the painful skin.

Statistical analysis. For comparison with sensitivity of normal subjects, we contrasted the patient data to data from a recently published reference database using the same set of QST methods.12 First, all data were transformed into standard normal distributions corrected for body region, sex, and age (Z values).13 Z transformation allows the comparison of values independent of their physical dimensions. Increased sensitivity results in positive Z scores, whereas decreased sensitivity results in negative Z scores, expressed in units of SD of the control group. Statistical comparisons to reference data were made using a Web-based statistics program.14

Table 2

Detailed comparison of patients with warm and cold CRPS regarding history, HADS scores, pain characteristics, McGill pain rating index, and motor and autonomic disturbances Warm CRPS, n ⴝ 25, no. (%)

Cold CRPS, n ⴝ 25, no. (%)

␹2

p Value

Patient history Psychosomatic disorders

4 (16)

9 (36)

2.60

NS

Serious life events: family conflict, death of relative, job-related problems

4 (16)

10 (40)

3.57

⬍0.05

Chronic pain history*

8 (32)

15 (60)

3.95

⬍0.05

Headache

3

3

Low back pain

4

8

Painful joints

0

3

Neuropathic pain: CRPS, neuralgia

2

5

HADS-A

7.4 ⫾ 0.9

5.9 ⫾ 0.9

0.53 (t value)

NS

HADS-D

6.7 ⫾ 0.9

5.3 ⫾ 0.8

0.48 (t value)

NS

Pain and hyperalgesia Pain at rest

22 (88)

18 (72)

2.00

NS

McGill PRI

24.2 ⫾ 3.0

22.4 ⫾ 3.9

0.30 (t value)

NS

By lowering

16 (64)

10 (40)

2.89

NS

By striking

19 (76)

16 (64)

0.25

NS

By physical effort

20 (80)

17 (68)

0.94

NS

By night

13 (52)

12 (48)

0.08

NS

By upset

5 (20)

6 (24)

0.12

NS

Cold

4 (16)

15 (60)

10.27

Warm

7 (28)

6 (24)

0.10

NS

Allodynia

12 (48)

10 (40)

0.33

NS

Amplification of pain

By temperature ⬍0.002

Motor disturbances 19 (76)

12 (48)

4.16

⬍0.05

Movement initiation difficulties

8 (32)

10 (40)

0.35

NS

Dystonia

0 (0)

4 (16)

4.35

⬍0.05

Weakness

Autonomic disturbances Temperature difference Warm Cold

20 (80)

2 (8)

2 (8)

20 (80)

26.30

⬍0.0001

Skin temperature, °C Ipsilateral

31.1 ⫾ 0.7

28.7 ⫾ 1.0

1.97 (t value)

Contralateral

30.1 ⫾ 0.5

29.7 ⫾ 0.8

0.43 (t value)

Difference: ipsilateral ⴚ contralateral

⫹1.0 ⫾ 0.4

⫺1.0 ⫾ 0.4

Skin color

3.16 (t value) 13.34

(0.056) NS ⬍0.01 ⬍0.01

Reddish

9 (36)

1 (4)

8.00

⬍0.005

White

3 (12)

0 (0)

3.19

0.07

Cyanotic

8 (32)

18 (72)

8.01

⬍0.005

No difference

5 (20)

6 (24)

0.12

NS

Edema

22 (88)

18 (72)

2.00

NS

Sweating

16 (64)

14 (56)

0.33

NS

0.40

NS

Increased

7 (28)

9 (36)

0.37

NS

Decreased

4 (16)

4 (16)

0.00

NS

Trophic changes: hair/nail

*Chronic pain history: patients may have more than one type of chronic pain. CRPS ⫽ chronic regional pain syndrome; HADS ⫽ Hospital Anxiety and Depression Scale; NS ⫽ not significant; A ⫽ anxiety; D ⫽ depression.

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Figure 1

QST profile of primarily warm CRPS: Affected and contralateral side vs controls

(A) Quantitative sensory testing (QST) Z profiles from patients with primarily warm complex regional pain syndrome (CRPS). Vertical line (zero) indicates mean of age- and sex-matched healthy controls. Positive Z scores indicate gain of function, and negative Z scores indicate loss of function. (B) Absolute values of dynamic mechanical allodynia (DMA) and paradoxical heat sensations (PHS). The CRPS side is indicated by filled circles, and the contralateral limbs are indicated by open circles. Asterisks indicate significant differences between affected and unaffected limb: **p ⬍ 0.01, *p ⬍ 0.05. NRS ⫽ numeric rating scale; CDT ⫽ cold detection threshold; WDT ⫽ warm detection threshold; TSL ⫽ thermal sensory limen; CPT ⫽ cold pain threshold; HPT ⫽ heat pain threshold; PPT ⫽ pressure pain threshold; MPT ⫽ mechanical pain threshold; MPS ⫽ mechanical pain sensitivity; WUR ⫽ windup ratio; MDT ⫽ mechanical detection threshold; VDT ⫽ vibration detection threshold.

All further statistical calculations were performed using STATISTICA for Windows (StatSoft Inc., Tulsa, OK). Differences between warm and cold CRPS were analyzed by ␹2 statistics for ordinal data (categorical variables) or by t tests for normally distributed variables. To compare QST in patients with warm and cold CRPS, the affected and unaffected extremity, three-way repeated-measures analyses of variance (ANOVAs) were separately calculated for comparison of sensory (CDT, WDT, TSL, VDT, MDT) and nociceptive QST values (CPT, HPT, PPT, MPT, MPS). Post hoc analysis was performed as planned comparisons (least significant difference tests). PHS and DMA were analyzed separately by nonparametric statistics. Ipsilateral (according to the affected limb) and contralateral sides of the body were compared using the Wilcoxon matched-pairs signed rank test, and warm and cold CRPS were compared using the Mann–Whitney U test. All data are presented as mean ⫾ SEM, and p ⬍ 0.05 was considered significant.

At inspection, patients with warm CRPS had predominantly reddish skin (9/25), and patients with cold CRPS had bluish skin (18/25) (p ⬍ 0.01). Skin temperature difference (⌬T affected ⫺ unaffected) was positive (i.e., warmer) in the warm CRPS group (⫹1.0° ⫾ 0.4°C) and negative (i.e., colder) in the cold group (⫺1.0° ⫾ 0.4°C) (p ⬍ 0.01).

RESULTS Patients’ history and clinical signs.

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There was a trend for more challenging life events (death of a close relative, serious family and workrelated problems) associated in time with the trauma in patients with cold CRPS (10/25) vs warm CRPS (4/25) (p ⫽ 0.059). Furthermore, patients with cold CRPS more often report chronic pain disorders (mostly headache or low back pain) unrelated to CRPS (15/25 vs 8/25, p ⬍ 0.05). Psychiatric comorbidity (anxiety and depression) was not different between the groups. Patients with warm and cold CRPS reported different types of temperature-induced pain. Few patients with CRPS (warm: 7/25 vs 6/25, not significant) explicitly stated an increase of pain and symptoms in warm environment, and patients with cold CRPS frequently reported a diminished cold tolerance (15/25), which rarely occurred in warm CRPS (4/25) (p ⬍ 0.01). The feeling of “motor weakness” was more prevalent in warm CRPS (19/25 vs 12/25, p ⬍ 0.05), whereas post-traumatic movement disorder (dystonia) could only be found in cold CRPS (4/25 vs 0/25, p ⬍ 0.05). Details of results and statistical values are shown in table 2. Quantitative sensory testing. Patients with warm CRPS were less sensitive in the affected side when nonnociceptive QST was compared with reference data in CDT (t ⫽ ⫺4.54, p ⬍ 0.001), WDT (t ⫽ ⫺2.82, p ⬍ 0.01), TSL (t ⫽ ⫺3.61, p ⬍ 0.001), and VDT (t ⫽ ⫺5.00, p ⬍ 0.001). In the nociceptive QST, they were more sensitive (hyperalgesic) for MPT (t ⫽ 2.57, p ⬍ 0.05) and PPT (t ⫽ 3.01, p ⬍ 0.01). Contralateral changes were less distinct: increased TSL (t ⫽ ⫺2.17, p ⬍ 0.05), MDT (t ⫽ ⫺2.57, p ⬍ 0.01), and VDT (t ⫽ ⫺4.30, p ⬍ 0.001) indicated that loss of sensation also occurred in the apparently unaffected limb, whereas decreased MPT (t ⫽ 3.30, p ⬍ 0.05) indicated hyperalgesia (figure 1). In patients with cold CRPS, sensory changes were also more obvious in the affected limb: negative Z scores in CDT (t ⫽ ⫺4.59, p ⬍ 0.001), WDT (t ⫽ ⫺3.03, p ⬍ 0.005), TSL (t ⫽ ⫺5.02, p ⬍ 0.001), and VDT (t ⫽ ⫺4.58, p ⬍ 0.001) indicated sensory loss, and positive Z scores in PPT (t ⫽ 4.61, p ⬍ 0.001) indicated hyperalgesia. On the unaffected side, Z scores for VDT were negative (t ⫽ ⫺2.98, p ⬍ 0.01), whereas HPT was positive, indicating hyperalgesia (t ⫽ 2.47, p ⬍ 0.02). The remaining data were not different from controls (figure 2). The finding that the ipsilateral (i.e., CRPS) side showed more sensory abnormalities than the contralateral clinically unaffected side was confirmed by direct side-to-side comparisons. Most prominent was

Figure 2

QST profile of primarily cold CRPS: Affected and contralateral side vs controls

(A) Quantitative sensory testing (QST) Z profiles from patients with primarily cold complex regional pain syndrome (CRPS). Vertical line (zero) indicates mean of age- and sex-matched healthy controls. Positive Z scores indicate gain of function, and negative Z scores loss of function. (B) Absolute values of dynamic mechanical allodynia (DMA) and paradoxical heat sensations (PHS). The CRPS side is indicated by filled circles, and the contralateral limbs are indicated by open circles. Asterisks indicate significant differences between affected and unaffected limb: **p ⬍ 0.01, *p ⬍ 0.05. NRS ⫽ numeric rating scale; CDT ⫽ cold detection threshold; WDT ⫽ warm detection threshold; TSL ⫽ thermal sensory limen; CPT ⫽ cold pain threshold; HPT ⫽ heat pain threshold; PPT ⫽ pressure pain threshold; MPT ⫽ mechanical pain threshold; MPS ⫽ mechanical pain sensitivity; WUR ⫽ windup ratio; MDT ⫽ mechanical detection threshold; VDT ⫽ vibration detection threshold.

a reduction of sensitivity in nonnociceptive sensory modalities (CDT, WDT, TSL, MDT, and VDT) in the affected extremity, and hyperalgesia to blunt pressure. This pattern of sensory differences between affected and unaffected extremities was the same in cold and warm CRPS. PHS were prevalent in the affected limb (20.7%, p ⬍ 0.001) but also in the contralateral limb (9.3%, p ⬍ 0.05) (side difference p ⬍ 0.05). When stratified for warm or cold CRPS and body side, PHS in the affected hand of cold CRPS (28%) were more frequent than any other combination (i.e., warm CRPS both hands and cold CRPS contralateral: 8.0%– 13.3%, p ⬍ 0.05 each; figure 1). The incidence of DMA was approximately 45% on the affected side. In warm CRPS, DMA (i.e., the amount of brush-evoked pain) on the CRPS side (0.42 ⫾ 0.25) was increased as compared with the unaffected side (0.06 ⫾ 0.06) (p ⬍ 0.05). In cold CRPS, neither the affected nor the unaffected side displayed significant DMA (0.01 ⫾ 0.01 vs 0 ⫾ 0). For details, see figures 1 and 2. Overall pattern of differences between warm and cold CRPS. Three-way mixed-model ANOVA on the set

of nonnociceptive QST values revealed no differ-

ences between CRPS type [cold vs warm CRPS: F(1,48) ⫽ 0.41, p ⫽ 0.53], but significant side differences [affected vs unaffected body side: F(1,48) ⫽ 46.04, p ⬍⬍ 0.0001] and differences between the values for CDT, WDT, TSL, MDT, and VDT [F(1,192) ⫽ 24.18, p ⬍⬍ 0.0001]. There was also an interaction between CRPS type and affected/ contralateral side [F(1,48) ⫽ 4.98, p ⬍ 0.05]. Patients with cold CRPS exhibited a greater side difference in nonnociceptive QST values than warm CRPS (average across all tests: ⫺1.56 ⫾ 0.29 vs ⫺0.79 ⫾ 0.19 z values, p ⬍ 0.05). This difference was based on pronounced sensory loss on the ipsilateral side (cold vs warm CRPS across all tests: ⫺1.88 ⫾ 0.31 and ⫺1.32 ⫾ 0.24 z values, p ⬍ 0.05), but not on the contralateral side (⫺0.31 ⫾ 0.14 vs ⫺0.53 ⫾ 0.16 z values, p ⫽ 0.39). These differences were found in all individual nonnociceptive thresholds and reached significance for MDT (p ⬍ 0.02) and TSL (p ⬍ 0.05). In the mixed-model ANOVA on nociceptive CPT, HPT, PPT, MPT, and MPS, main effects exhibited a similar pattern with no impact of CRPS type [cold vs warm CRPS: F(1,48) ⫽ 0.431, p ⫽ 0.58; ⫹0.42 vs ⫹ 0.32 z values, p ⫽ 0.85], significant side differences [F(1,48) ⫽ 8.78, p ⬍ 0.005], and differences between different nociceptive QST findings [F(1,240) ⫽ 74.64, p ⬍ 0.001]. The interaction between CRPS type and body side was not significant [F(1,48) ⫽ 1.59, p ⫽ 0.214]. However, there was an interaction between CRPS type and different nociceptive QST values [F(1,192) ⫽ 3.08, p ⬍ 0.05] based on hyperalgesia for CPT, HPT, and PPT in cold CRPS but less hyperalgesia to pinprick. Moreover, there was an interaction between body side and nociceptive QST values [F(1,192) ⫽ 9.97, p ⬍⬍ 0.0001] based on a pronounced hyperalgesia to blunt pressure in the affected but not in the contralateral hand (⫹1.54 vs ⫹ 0.16 z values, p ⬍⬍ 0.0001). There were no side differences in all other nociceptive QST findings (see figure 3 for details). Neither on the affected nor on the unaffected side did PHS differ between warm and cold CRPS. In contrast, DMA was significantly higher on the affected side in warm CRPS than in cold CRPS, but no difference was found on the unaffected side. DISCUSSION Warm and cold CRPS are defined according to skin temperature difference between affected and unaffected side at onset of CRPS.15 In due CRPS course, this differentiation must not be fixed. Cold CRPS most often remains cold, whereas warm CRPS usually turns into cold when the CRPS becomes chronic16: regarding latest pathophysiologic findings, CRPS might represent an exaggerated inNeurology 72

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509

Figure 3

QST side differences of primarily warm and cold CRPS

(A) Z profiles of the differences between affected and unaffected limbs for patients with warm complex regional pain syndrome (CRPS) (filled circles) and cold CRPS (open circles). Vertical (zero) line indicates the contralateral limb as reference. Positive Z scores indicate gain of function on affected side, and negative Z scores indicate loss of function. Patients with cold CRPS in general had a more pronounced loss of nonpainful sensations (multivariate analysis of variance, p ⬍ 0.02). (B) Difference between affected and unaffected limbs of absolute values of dynamic mechanical allodynia (DMA) and paradoxical heat sensations (PHS). Asterisks indicate significant differences between warm and cold CRPS side differences in the post hoc least significant difference test and the Mann–Whitney U test for DMA: *p ⬍ 0.05, (*)p ⫽ 0.07. QST ⫽ quantitative sensory testing; NRS ⫽ numeric rating scale; CDT ⫽ cold detection threshold; WDT ⫽ warm detection threshold; TSL ⫽ thermal sensory limen; CPT ⫽ cold pain threshold; HPT ⫽ heat pain threshold; PPT ⫽ pressure pain threshold; MPT ⫽ mechanical pain threshold; MPS ⫽ mechanical pain sensitivity; WUR ⫽ windup ratio; MDT ⫽ mechanical detection threshold; VDT ⫽ vibration detection threshold.

flammation or an extensive CNS reorganization.17 However, no conclusive concept for the synergy of these different pathophysiologic mechanisms leading to either warm or cold CRPS exists to date. The present results indicate similarities but also differences between both CRPS subtypes, which go beyond skin temperature. We found disparities regarding individual history, motor function, nociception (pain and hyperalgesia), and finally nonnociceptive sensations. These findings might contribute to a more comprehensive understanding of CRPS. Trigger events for CRPS usually are limb traumas such as fractures or surgery. After such traumas, signs of inflammation, such as edema, hyperthermia, and pain, are frequently found, usually dwindling within some weeks. Previous studies and the present results suggest that particularly in warm CRPS, this posttraumatic inflammation is exaggerated. Proinflammatory cytokines are up-regulated, and anti-inflammatory cytokines are diminished.18 This leads to peripheral sensitization, mainly of deeper tissues, and is clinically characterized by hyperalgesia to blunt pressure. Tumor necrosis factor ␣ furthermore contributes to secondary central sensitization indicated by pinprick 510

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hyperalgesia and allodynia.19 Both types of hyperalgesia were more pronounced in patients with warm CRPS. Furthermore, motor weakness in warm CRPS was not a true neurologic paresis, but a “giving-way” weakness due to pain and hyperalgesia during movement and muscle tension. In addition to hyperalgesia, cytokines also amplify neurogenic inflammation.7,20 The major mediators of neurogenic inflammation are vasoactive neuropeptides responsible for vasodilatation and increased skin temperature,21 further key features of warm CRPS. In cold CRPS, obvious signs of exaggerated inflammation are lacking. Our results suggest that in these patients, the most important site of sensory and motor dysfunction might be either the spinal cord or the brain, for the following reasons: 1. Dystonia is part of the posttraumatic movement disorder in CRPS. In our patient cohort, dystonia was exclusively found in cold CRPS. The mechanisms of CRPS-related dystonia have not been fully explored, but recent studies suggest insufficient spinal motor-inhibitory ␥-aminobutyric acid–mediated circuits, which might explain spreading of dystonia to previously unaffected extremities,2 a fact that can only be explained by central changes. 2. Indications for CNS changes of pain processing in cold CRPS come from PHS and the exaggeration of CRPS pain in cold environments. PHS have been demonstrated in patients with multiple sclerosis22 due to dysfunction of thermoreceptive projection neurons in the spinal cord. Hyperalgesia to cold has been found in patients with spinal cord injury associated with central neuropathic pain.23 3. CRPS I excludes major nerve lesions, and in CRPS II we performed QST outside the respective nerve territory. That is, there should be no or only minor24 structural damage in the peripheral nervous system. Nevertheless, there was a loss of nonpainful sensitivity, significantly more prevalent in cold CRPS, and not only on the affected but also on the clinically unaffected contralateral side. We have recently been able to show that experimental pain in healthy subjects induces hypesthesia in the vicinity of the painful skin, suggesting presynaptic inhibition of spinal processing of innocuous information.25 However, such a spinal suppression of nonnoxious processing is spatially restricted and thus contributes only to sensory loss on the CRPS side. Important to notice is that numbness of a painful extremity is not unique to CRPS. It has also been described in chronic myofascial pain, which is also charac-

terized by lacking peripheral skin nerve pathology.25 However, suppression of spinal sensory processing could not account for the sensory loss in nonpainful limbs in CRPS.26 Patients with CRPS have difficulties in detecting not only skin sensations, but also visual, auditory, and haptic information, leading to impaired self-perception.27 All these phenomena must be assigned to altered sensory processing in the brain.28 Thus, another explanation for the impairment of nonpainful sensations might be the shift of attention toward pain in our patients, which suppresses the perception of stimuli not related to pain and thus reinforcing the negative symptoms.29 4. Finally, patients with cold CRPS more often report a history of pain, disorder suggesting an increased risk for chronic pain as compared with warm CRPS. This risk may be genetically or psychologically (“pain proneness”) determined or both. Coping with pain could also be determined by biography.30 This view is supported by the higher incidence of serious life events in relation to the inciting trauma in patients with cold CRPS. Serious life events are stressors and insufficient coping with such a stressor during adolescence might lead to insufficient defense mechanisms in these patients. These insufficient mechanisms could maintain CRPS symptoms.31 It is unlikely that a full distinction between cold and warm CRPS can be achieved clinically. All changes “typical” of cold CRPS also apply to some extent to warm CRPS and vice versa. Nevertheless, the present results suggest that warm and cold CRPS might be representatives of peripheral and central CRPS pathophysiology. Future, i.e., longitudinal, studies should focus on how the predominance of one of these mechanisms translates to CRPS symptoms. Ideally, such studies include two further control groups: the first with temperature difference but without pain, and the second with pain but without temperature difference. Thereby the specificity of sensory abnormalities for CRPS can be addressed.

4.

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8.

9.

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11. 12.

13.

14.

15.

16.

17.

Received July 2, 2008. Accepted in final form October 31, 2008.

18.

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Calling All New and International Members! Don’t miss these FREE AAN Annual Meeting events designed just for you: • New Member Information Session Sunday, April 26 / 5:00 p.m. to 6:00 p.m. Learn about the AAN, its resources and benefits, and network with Academy leaders. • International Attendee Summit Monday, April 27 / 7:00 a.m. to 9:00 a.m. Meet Academy leaders and make your voice heard on matters most important to you. Learn more at www.aan.com/specialevents.

Calling All Artists! Submit Your Art to Help Raise Money for Neurologic Research Are you an artist? The AAN Foundation invites you to donate your work to the Art for Research: An AAN Gallery Show. Pieces will be displayed at the Annual Meeting in Seattle and put on sale with proceeds going to support clinical research training in neuroscience. Academy members and/or their families may donate pieces for the show. The show accepts paintings, sculptures, textiles, ceramics, and more. Choose how to make your donations: ● Donate a piece of art for the Academy to sell at the meeting ● Sell a piece of art with 20% of the proceeds going to support research ● Submit your art for showcase only for a $50.00 fee For additional details on this event and to learn how to contribute, visit www.aan.com/art.

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Declining brain glucose metabolism in normal individuals with a maternal history of Alzheimer disease L. Mosconi, PhD R. Mistur, BA R. Switalski, MD M. Brys, MD L. Glodzik, MD K. Rich, MD E. Pirraglia, MA W. Tsui, MS S. De Santi, PhD M.J. de Leon, EdD

Address correspondence and reprint requests to Dr. Lisa Mosconi, Department of Psychiatry, NYU School of Medicine, 550 First Avenue, New York, NY 10016 [email protected]; or Dr. Mony de Leon, Department of Psychiatry, NYU School of Medicine, 560 First Avenue, New York, NY 10016 [email protected]

ABSTRACT

Background: At cross-section, cognitively normal individuals (NL) with a maternal history of lateonset Alzheimer disease (AD) have reduced glucose metabolism (CMRglc) on FDG-PET in the same brain regions as patients with clinical AD as compared to those with a paternal and a negative family history (FH) of AD. This longitudinal FDG-PET study examines whether CMRglc reductions in NL subjects with a maternal history of AD are progressive.

Methods: Seventy-five 50- to 82-year-old NL received 2-year follow-up clinical, neuropsychological, and FDG-PET examinations. These included 37 subjects with negative family history of AD (FH⫺), 9 with paternal (FHp), and 20 with maternal AD (FHm). Two subjects had parents with postmortem confirmed AD. Statistical parametric mapping was used to compare CMRglc across FH groups at baseline, follow-up, and longitudinally.

Results: At both time points, the FH groups were comparable for demographic and neuropsychological characteristics. At baseline and at follow-up, FHm subjects showed CMRglc reductions in the parieto-temporal, posterior cingulate, and medial temporal cortices as compared to FH⫺ and FHp (p ⬍ 0.001). Longitudinally, FHm had significant CMRglc declines in these regions, which were significantly greater than those in FH⫺ and FHp (p ⬍ 0.05). Conclusions: A maternal history of Alzheimer disease (AD) predisposes normal individuals to progressive CMRglc reductions in AD-vulnerable brain regions, which may be related to a higher risk for developing AD. Neurology® 2009;72:513–520 GLOSSARY AD ⫽ Alzheimer disease; ApoE-4 ⫽ apolipoprotein E-4 genotype; CMRglc ⫽ cerebral metabolic rate for glucose; FDG-PET ⫽ 2-[18F]fluoro-2-deoxy-D-glucose positron emission tomography; FH ⫽ family history; FHⴚ ⫽ negative family history of AD; FHm ⫽ maternal history of AD; FHp ⫽ paternal history of AD; FWHM ⫽ full-width at half maximum; GDS ⫽ Global Deterioration Scale; GLM ⫽ General Linear Model; MCI ⫽ mild cognitive impairment; MMSE ⫽ Mini-Mental State Examination; MNI ⫽ McGill Neurologic Institute; mtDNA ⫽ mitochondrial DNA; NL ⫽ normal individuals; PCC ⫽ posterior cingulate cortex; PHG ⫽ parahippocampal gyrus; SMC ⫽ subjective memory complaints.

Alzheimer disease (AD) is an age-dependent neurodegenerative disorder associated with progressive loss of cognitive function. After advanced age, having a first-degree family history of late-onset AD, especially when a parent is affected, is the major risk factor for developing AD among cognitively normal (NL) subjects.1 While the rare familial forms of early onset AD follow conventional patterns of autosomal dominant Mendelian inheritance, the vast majority of AD cases appear late in life, without clear nuclear genetic associations. However, first-degree relatives of affected probands are at 4- to 10-fold higher risk for AD as compared to individuals with no family history.2-4 The apolipoprotein E (ApoE) epsilon 4 genotype is an established genetic risk factor for late-onset AD, but it is found in less than 40% of AD cases,1 indicating that other factors contribute to the etiology and expression of disease. Although there is mixed evidence for parent of origin effects in late-onset AD families,5,6 epidemiology data indicate Supplemental data at www.neurology.org Editorial, page 486 e-Pub ahead of print on November 12, 2008, at www.neurology.org. From New York University School of Medicine (L.M., R.M., R.S., M.B., L.G., K.R., E.P., W.T., S.D.S., M.J.d.L.), New York; and Nathan S. Kline Institute for Psychiatric Research (W.T., M.J.d.L.), Orangeburg, NY. Supported by NIH-NIA AG13616, AG12101, AG08051, AG022374, NIH-NCRR MO1RR0096, and the Alzheimer’s Association. Disclosure: The authors report no disclosures. Copyright © 2009 by AAN Enterprises, Inc.

513

that having an AD-affected mother confers greater risk than having an AD-affected father,5 is associated with poorer cognitive performance in late life,7 and a more predictable age at dementia onset in the offspring.8 The biologic mechanisms through which a parental history of AD confers increased risk for developing dementia are unknown. Our recent 2-[18F]fluoro-2-deoxy-D-glucose positron emission tomography (FDG-PET) study showed that NL individuals with a maternal history of AD had marked reductions in the cerebral metabolic rate for glucose (CMRglc) as compared to subjects with a paternal history and without a family history of AD.9 NL subjects with an AD-affected mother showed reduced CMRglc in the parieto-temporal, posterior cingulate, and medial temporal cortices, which are typically hypometabolic in patients with clinical AD.9 FDG-PET studies in AD have shown that CMRglc reductions in these regions occur years prior to symptoms onset10-13 and correlate with clinical progression.13,14 This 2-year longitudinal FDG-PET study examines whether CMRglc reductions in NL individuals with a maternal history of AD are progressive. METHODS Subjects. We retrospectively examined 75 clinically and cognitively NL individuals who completed a 2-year follow-up FDG-PET examination and thorough family history (FH) evaluations. Subjects were recruited at NYU School of Medicine to participate as volunteers for longitudinal FDG-PET studies, including individuals interested in research participation and risk consultation; self-referred individuals with cognitive complaints; and spouses, family members, and caregivers of patients participating in other studies. Informed consent was obtained from all subjects. The study was approved by the NYU and Brookhaven National Laboratory (BNL, Upton, NY) IRB. At baseline and follow-up, subjects received a standard diagnostic evaluation that included medical, psychiatric, neuropsychological, clinical MRI, and FDG-PET examinations within 2 months. Individuals with medical conditions or history of conditions that may affect brain structure or function, i.e., stroke, diabetes, head trauma, any neurodegenerative diseases, depression, hydrocephalus, intracranial mass, and infarcts on MRI, and use of psychoactive medications were excluded. All subjects had normal fasting blood glucose levels, blood pressure, cholesterol levels, and Modified Hachinski Ischemia Scale scores ⬍4.15 ApoE genotype was determined using standard PCR procedures. Subjects were 50 – 82 years of age at baseline, had education ⱖ12 years, Global Deterioration Scale (GDS) scores ⱕ2,16 and Mini-Mental State Examination ⱖ28. All subjects had normal cognitive test performance relative to normative values on the immediate and delayed recall of a paragraph and of paired associates, the digit-symbol substitution, designs, object naming, and 514

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WAIS-vocabulary tests.13 A FH of dementia that included at least one first-degree relative with dementia onset between 65 and 80 years was elicited by using the NYU Brain Aging Family History questionnaire (appendix e-1 on the Neurology® Web site at www.neurology.org). Participants were asked to fill in information of affected family members, which was confirmed by other family members in the interview with the examining neurologist. Subjects were not included if their parents had not lived to the age at risk of late-onset AD (i.e., 65 years). Subjects with maternal (FHm; i.e., only the mother was affected with AD), paternal (FHp; i.e., only the father was affected with AD), and negative FH of AD (FH⫺) were included in the study. The AD-affected parents of two subjects (one FHm and one FHp) received an autopsy and the postmortem diagnosis of AD.17

Brain imaging. Subjects received a standardized whole-brain MRI scan protocol on a 1.5 T Signa imager (General Electric, Milwaukee, MI), including a contiguous 3 mm axial T2weighted and a T1-weighted fast-gradient-echo image (25 cm field of view [FOV], number of excitations ⫽ 1, 256 ⫻ 128 matrix, 35 msec relaxation time, 9 msec excitation time, 1.2 mm sections, and 60º flip angle). These scans were used to rule out MRI evidence of hydrocephalus, intracranial mass, cortical strokes, subcortical gray matter lacunes, and moderate to severe white matter disease.18 All subjects received a PET scan at BNL on an ECAT 931 scanner (Siemens, Knoxville, TN; 6.2 mm full-width at half maximum [FWHM]; 6.75 mm slice thickness, 10 cm axial FOV). Subjects received 5– 8 mCi of FDG IV while lying supine in a dimly lit room. PET images were obtained 35 minutes after injection over 20 minutes. Scans were acquired as two interleaved 15-slice PET volumes that overlapped by a half-slice thickness (⬃3.4 mm) over two 10-minute frames.19 Arterial blood samples were drawn at standard intervals throughout the study and absolute CMRglc (␮mol/100 g/min) was calculated using Sokoloff model with standard kinetic constants.20 Data were reconstructed using filtered back-projection (Fourier rebinning/2D back-projection, Hanning filter with a frequency cutoff of 0.5 cycles/pixel) and corrected for attenuation, scatter, and radioactive decay, yielding 128 ⫻ 128 matrix with a pixel size of 1.56 mm.

Image analysis. FDG-PET scans were processed using Statistical Parametric Mapping (SPM2, Wellcome Department of Cognitive Neurology, London, UK).21 Scans were realigned, spatially normalized to an elderly brain template22 in the McGill Neurologic Institute (MNI) space, which approximates the Talairach and Tournoux space,23 by estimating the least squares 12-parameter affine transformation followed by an iterative estimate of local alignment, and smoothed with a 12 mm FWHM gaussian filter.21 Only voxels with values greater than 80% of the whole brain CMRglc were included in the analysis and only clusters exceeding an extent threshold of 30 voxels were considered significant. Anatomic location of brain regions showing significant effects was described using the Talairach and Tournoux coordinates using Talairach Daemon 12.0 (http://ric.uthscsa. edu/projects/talairachdaemon.html), after coordinates conversion to the Talairach space.23 CMRglc measures were extracted from the clusters of voxels showing significant effects using the Marsbar tool (http://www.mrc-cbu.cam.ac.uk/Imaging/marsbar. html) to be examined in further analyses. Statistical analysis. Analyses were done with SPSS 12.0 (SPSS Inc., Chicago, IL) and SPM2. Differences in demographic and neuropsychological measures between the study groups were

Table 1

Subject characteristics by family history groups

No.

FHⴚ

FHp

FHm

37

9

20

Age at baseline, y

64 (7)

60 (6)

64 (6)

Gender , F/M (% F)

29/8 (78)

4/5 (44)

15/4 (75)

16 (2)

16 (1)

16 (2)

ApoE-4, ⴚ/ⴙ (% ApoE-4)

28/9 (24)

4/5 (55)

10/10 (50)

SMC, yes/no (% SMC)

29/8 (78)

4/5 (55)

13/7 (65)

Baseline

29.2 (1.1)

29.6 (0.8)

29.6 (0.6)

Follow-up

29.2 (0.8)

29.6 (0.5)

29.7 (0.8)

Baseline

6.3 (2.4)

7.4 (2.0)

6.4 (2.3)

Follow-up

6.2 (2.6)

7.5 (2.6)

6.5 (2.4)

Education, y

Neuropsychological measures MMSE

Designs

Digit symbol substitution Baseline

55.8 (9.3)

62.1 (8.5)

56.5 (10.8)

Follow-up

55.7 (10.7)

56.7 (14.2)

55.5 (11.0)

Baseline

55.8 (4.8)

56.9 (4.7)

54.6 (5.3)

Follow-up

55.0 (5.8)

57.5 (2.3)

54.3 (6.6)

Baseline

9.3 (3.4)

10.2 (2.4)

8.9 (2.3)

Follow-up

9.2 (3.3)

11.5 (3.3)

8.5 (2.5)

Baseline

6.4 (2.4)

6.6 (2.7)

6.3 (2.7)

Follow-up

6.3 (2.8)

6.8 (3.5)

6.3 (3.2)

Object naming

results were considered significant at p ⬍ 0.001, uncorrected for multiple comparisons. Results were re-examined controlling for other potential risk factors for late-onset AD, such as age, female gender, education, ApoE-4 genotype, and presence of subjective memory complaints. In addition, due to the small sample of FHp, we created three groups of nine subjects each, matched for age, gender, education, and ApoE genotype, and re-examined CMRglc for group effects using the GLM with post hoc LSD tests, as well as nonparametric Mann-Whitney rank sum tests (␣ ⫽ 0.05, exact significance, one-tailed). Linear regressions were used to estimate the number of years prior to baseline when statistical differentiation across groups was possible. This was done for the brain regions showing baseline and longitudinal group effects by estimating the mean CMRglc for each group every 0.5 years prior to baseline, using the baseline CMRglc and the annual rate of CMRglc decline in each group.13 At each time point, CMRglc was compared between groups using independent-sample t tests at p ⬍ 0.05 (one-sided). The spatially normalized FDG-PET scans of the two subjects with parents with pathology-verified AD were processed using NEUROSTAT25 to highlight CMRglc abnormalities in each subject as compared to an FDG-PET database of healthy controls.26 Results were examined at p ⱕ 0.01 (one-sided) and three-dimensional stereotactic surface projections of the Z scores generated to visualize CMRglc deviations from controls.25,26

Paired associates recall

Paragraph delayed recall

WAIS vocabulary Baseline

66.5 (8.1)

72.5 (5.1)

68.0 (9.7)

Follow-up

67.6 (10.4)

70.3 (7.5)

67.6 (9.2)

Values are means (SD). FH ⫽ parental family history of AD; FH⫺ ⫽ negative FH; FHp ⫽ paternal FH; FHm ⫽ maternal FH; ApoE-4 ⫽ apolipoprotein E-4 genotype; SMC ⫽ subjective memory complaints; MMSE ⫽ Mini-Mental State Examination.

examined with ␹2 tests, Fisher exact test, and the General Linear Model (GLM) with post hoc LSD tests, as appropriate. For all analyses, results were considered significant at p ⬍ 0.05. The GLM/univariate analysis with post hoc t tests was used to test for CMRglc differences across FH groups at baseline and at the 2-year follow-up. The GLM/repeated measures analysis with post hoc t tests was used to test for differential effects across groups over time, and to examine longitudinal CMRglc changes within each FH group. All analyses were performed using absolute CMRglc values and controlling for the individual’s global CMRglc, as done in previous FDG-PET study with similar subject groups to highlight regional differences.9,24 Prior to analysis, we confirmed that there were no cross-sectional (F[2,63] ⬍ 0.6, p ⬎ 0.55) or longitudinal (F[2,63] ⫽ 1.26, p ⫽ 0.20) differences in global CMRglc across groups (baseline: FH⫺ ⫽ 33.1 ⫾ 6.5, FHp ⫽ 34.2 ⫾ 6.3, FHm ⫽ 33.7 ⫾ 6.7 ␮mol/100 g/min; follow-up: FH⫺ ⫽ 37.7 ⫾ 7.4, FHp ⫽ 32.0 ⫾ 8.5, FHm ⫽ 30.8 ⫾ 5.2 ␮mol/100 g/min). Since we previously identified the brain regions showing CMRglc differences across FH groups,9

Of the 75 baseline subjects, 66 were examined in this study including 37 FH⫺, 9 FHp, and 20 FHm subjects. Of the remaining nine subjects, one had both parents affected, two had only siblings affected, three had only second-degree relatives affected, and three had a family history of an unspecified dementia and were conservatively excluded. There were no significant differences between FH groups for age, education, and prevalence of subjective memory complaints (SMC) (table 1). The prevalence of females was lower in FHp (44%) as compared to FH⫺ and FHm (78% and 75%; ␹2(2) ⫽ 8.3, p ⫽ 0.01). The prevalence of ApoE-4 carriers was slightly lower in FH⫺ (24%) as compared to FHp and FHm (55% and 50%; ␹2(2) ⫽ 5.3, p ⫽ 0.07). There were no differences in neuropsychological scores across groups at baseline, follow-up, or longitudinally (table 1). At baseline, FHm subjects showed CMRglc reductions as compared to FH⫺ and FHp (figure 1). As compared to FH⫺, FHm subjects showed CMRglc reductions in the parietal, temporal, posterior cingulate (PCC), and frontal cortices, and parahippocampal gyrus (PHG), bilaterally (p ⬍ 0.001, table 2). As compared to FHp, FHm showed reduced CMRglc in the PCC and frontal cortices, bilaterally, in the right temporal cortex, PHG, and hippocampus, and in the left parietal cortex (p ⬍ 0.001, table 2). These results remained significant after accounting for age, gender, education, ApoE genotype, and RESULTS

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515

Figure 1

Maternal history of Alzheimer disease (FHm) subjects as compared to negative family history (FHⴚ) (in blue) and paternal history (FHp) (in red) groups, and to both FHⴚ and FHp (in purple)

Anatomic location and description of brain regions are found in table 2. Areas of hypometabolism are displayed onto the superior, anterior, and inferior views of a volume-rendered spatially normalized MRI.

SMC. There were no differences between FH⫺ and FHp groups. At the 2-year follow-up, as compared to FH⫺ and FHp groups, FHm subjects showed CMRglc reductions in the same brain regions as at baseline (p ⬍ 0.001). The clusters of hypometabolism were slightly more extended with respect to the baseline results, but the topography of CMRglc reductions remained unchanged (data not shown). As with the baseline, there were no differences between FH⫺ and FHp groups. At both time points, there were no regions showing higher CMRglc in FHm as compared to FH⫺ and FHp. Longitudinal group by time interaction effects were detected in the PCC/precuneus, inferior parietal, and superior temporal cortex, bilaterally (p ⬍ 0.001). Post hoc comparisons showed that the longitudinal effects in the PCC and parieto-temporal cortices were driven by FHm subjects, who showed CMRglc reductions at follow-up as compared to baseline, whereas FH⫺ and FHp groups did not show CMRglc reductions in these regions over time (p ⬍ 0.001, table 3 ). In FHm subjects, CMRglc within AD-related regions (i.e., the average of the parieto-temporal and PCC CMRglc) was reduced 13% at baseline and 23% at follow-up (p ⬍ 0.001), and the CMRglc reductions over time were more severe (F[2,63] ⫽ 17.9; p ⬍ 0.001) as compared to FH⫺ and FHp (figure 2). The mean annual CMRglc decline in AD regions in FHm (⫺3.14 ⫾ 1.3 ␮mol/100 g/min) was greater than that observed in FH⫺ (⫺0.75 ⫾ 1.5 ␮mol/100 g/min) and in FHp (⫺0.56 ⫾ 0.91 ␮mol/100 g/min) (p ⬍ 0.001). This corresponded to higher annual rates of CMRglc reductions in AD regions in FHm (⫺5.8%) than in FHp and FH⫺ (⫺0.9% and ⫺1.4%, p ⬍ 0.05). Additionally, all FH groups showed modest lon516

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gitudinal CMRglc reductions in the frontal cortex (p ⬍ 0.001, table 3), but there were no interaction effects in this region. There were no regions showing CMRglc increases over time in any FH group. Analysis of three demographically and size matched FH groups confirmed the above CMRglc effects in AD brain regions. As compared to FH⫺, the FHm group showed CMRglc reduced 17% at baseline CMRglc and 25% at follow-up (Mann Whitney p ⫽ 0.001 and p ⫽ 0.002, respectively), as well as greater CMRglc decreases over time (FHm: ⫺2.8 ⫾ 1.1 ␮mol/100 g/min per year vs FH⫺: ⫺0.54 ⫾ 2.2 ␮mol/100 g/min per year, Mann Whitney p ⫽ 0.005). This corresponded to higher annual rates of CMRglc reductions in AD regions in FHm (⫺5.0% per year) than in FH⫺ (⫺1.1% per year, p ⬍ 0.05). Assuming a linear progression of CMRglc reductions and constant SEM, CMRglc reductions in FHm were estimated to reach significance 2 ⫾ 0.5 years before baseline as compared to FH⫺, and 1.5 ⫾ 0.5 years before baseline as compared to FHp (figure e-1). Examination of the FDG-PET scans of the offspring of patients with postmortem verified AD showed that, as compared to controls, a 68-year-old NL son of an AD-affected father did not show hypometabolism, whereas a 58-year-old NL daughter of an AD-affected mother showed significant CMRglc reductions in the PCC and medial temporal cortex, bilaterally (Z scores range: 2.3– 4), and to a lesser extent in the parieto-temporal cortex (p ⬍ 0.01, figure e-2). DISCUSSION We previously reported that, in cross-section, NL FHm individuals show CMRglc reductions in the same brain regions as patients with clinical AD as compared to FHp and FH⫺. The

Table 2

Cluster extent

Brain regions showing significant CMRglc differences across family history groups at baseline Coordinates*

Z†

Functional area

Brodmann area

CMRglc reductions in FHm as compared to FHⴚ 1474

1031

924

481

34

61

4

4.05

Superior frontal gyrus

10

37

62

⫺1

3.11


10

⫺58

⫺44

40

3.81

Inferior parietal gyrus

40

⫺59

⫺43

35

2.56


40

⫺53

⫺49

43

2.48


40

⫺38

58

4

2.80


10

⫺42

58

8

2.60


10

4

⫺37

40

3.42

Posterior cingulate gyrus

31

⫺3

⫺44

42

3.24


31

286

21

⫺16

⫺20

2.51

Parahippocampal gyrus

28

243

⫺61

⫺53

1

2.23

Middle temporal gyrus

21

213

63

⫺9

⫺12

2.22


21

151

⫺26

⫺16

⫺24

2.36


28/36

133

41

⫺59

20

2.14

Angular gyrus

39/40

CMRglc reductions in FHm as compared to FHp 1192

352

226

203

⫺6

⫺8

3.04


21

58

4

⫺16

2.54


21

63

⫺8

⫺4

2.13

Superior temporal gyrus

21/22

63

3

⫺41

28

2.43


31

⫺4

⫺43

32

2.70


31

30

63

1

2.48


10

38

60

8

2.44


10

27

⫺12

⫺20

2.45

Hippocampus

25

⫺15

⫺24

2.44


36

28

⫺15

⫺16

2.34

Hippocampus

110

⫺51

⫺49

45

2.29


40

88

⫺36

61

⫺1

2.45


10

*Coordinates (x, y, z) from the atlas of Talairach and Tournoux23: x is the distance in mm to the right (⫹) or left (⫺) of midline; y is the distance anterior (⫹) or posterior (⫺) to the anterior commissure; and z is the distance superior (⫹) or inferior (⫺) to a horizontal plane through the anterior and posterior commissures. †Z values at the peak of maximum statistical significance at p ⬍ 0.001. FH ⫽ parental family history of AD; FHm ⫽ maternal FH; FH⫺ ⫽ negative FH; FHp ⫽ paternal FH.

present longitudinal FDG-PET study replicates previous findings in a larger cohort, and shows that regional CMRglc continued to decline in FHm individuals during the 2-year follow-up. The decline in CMRglc preceded any evidence of cognitive deterioration and was significantly greater than in FH⫺ and FHp subjects. These effects remained significant after accounting for potential risk factors for lateonset AD such as age, female gender, education, ApoE-4 genotype, and SMC. Longitudinally, all FH groups showed CMRglc declines in the frontal regions, in agreement with previous age-related FDG-PET findings in NL elderly.12,13,27 However, the FHm subjects uniquely

showed CMRglc declines also in the same ADvulnerable brain regions that were hypometabolic at baseline, the parieto-temporal and PCC cortices, in which the rates of CMRglc decline were significantly higher in FHm as compared to the other groups. Regression analyses showed that CMRglc reductions in AD regions in FHm originated a few years prior to the baseline PET, suggesting that hypometabolism in FHm subjects may be a late-life phenomenon. Other studies with longer follow-ups and younger individuals are needed to replicate these findings. Examination of two persons with parents with pathologically confirmed AD revealed that while the FHp subject did not show CMRglc abnormalities, the FHm subject showed a pattern of hypometabolism involving the PCC and medial temporal cortices, and to a lesser extent, the parieto-temporal regions as compared to controls. A similar pattern is consistently found in patients with mild cognitive impairment (MCI), a condition that places patients at very high risk for developing AD.14,22,28 Hypometabolism in these brain regions is known to precede the onset of cognitive symptoms in AD by many years,10,12,13 and to correlate with disease progression in NL elderly12,13 and patients with MCI14 declining to AD. Our FHm subjects showed a similar regional pattern of longitudinal CMRglc deficits, suggesting that progressive hypometabolism may be one of the biologic mechanisms that confer increased vulnerability to AD. Continued follow-up examination of our subjects and replication studies are necessary to determine whether the observed CMRglc reductions are predictive of AD. The causes of the early CMRglc abnormalities in FHm subjects are not known. Although Mendelian inheritance is not evident in late-onset AD, the fact that children of affected individuals have an increased risk of developing the disease suggests a genetic component.1 Moreover, the fact that only children of affected mothers show CMRglc reductions consistent with AD suggests maternally inherited predisposition to brain “energetic” failure. FDG-PET studies of NL ApoE-4 carriers have shown longitudinal CMRglc reductions similar to those observed in our FHm subjects.24 However, our results remained significant after controlling for ApoE genotype, which indicates that other factors contribute to the CMRglc abnormalities observed in FHm. With all that is known about the molecular processes involved in glucose metabolism, hypometabolism in FHm may be due to a combination of defective mitochondrial function, increased oxidative stress, and possible mitochondrial DNA (mtDNA) mutations, leading to CMRglc alterations in brain tissue.29 The fact that mtDNA is entirely maternally Neurology 72

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517

Table 3

Cluster extent

Brain regions showing significant longitudinal CMRglc effects within FH groups Coordinates*

Z†

Functional area

Brodmann area

CMRglc reductions at follow-up as compared to baseline in FHⴚ ⫺29

28

⫺9

4.69

Inferior frontal gyrus

11/47

⫺54

23

⫺4

4.45


47

76

41

56

⫺4

4.48


10

45

48

47

16

4.44


10/46

102

Figure 2

Longitudinal CMRglc changes in Alzheimer disease (AD)-vulnerable brain regions (parieto-temporal and posterior cingulate cortex) in negative family history (FHⴚ) (top, white circles), paternal history (FHp) (middle, white triangles), and maternal history (FHm) subjects (bottom, black squares)

CMRglc reductions at follow-up as compared to baseline in FHp 50

⫺5

57 ⫺20

40

55

37

4

4.85


45

36

61 ⫺15 ⫺16

4.81


21

4.01


11

CMRglc reductions at follow-up as compared to baseline in FHm 5961

2534

61 ⫺37

32

7.99


40

⫺57 ⫺47

40

7.71


40

⫺3 ⫺67

40

5.94

Precuneus

⫺29 ⫺72

44

5.18

Precuneus

4 ⫺48

32

5.42


31

⫺49 ⫺56

45

3.44


40

⫺61 ⫺56

4

4.44


21/37

⫺60 ⫺54 734

150

7

⫺1

4.05


21/37

7

⫺3

4.22


22

63 ⫺11

21/22

59

⫺4

5.25


4

1

3.58

Insula

64 ⫺29

⫺1

3.88


21

60 ⫺42

4

3.84


21

40

2

3.15


10

43 236

7

58

*Coordinates (x, y, z) from the atlas of Talairach and Tournoux23: x is the distance in mm to the right (⫹) or left (⫺) of midline; y is the distance anterior (⫹) or posterior (⫺) to the anterior commissure; and z is the distance superior (⫹) or inferior (⫺) to a horizontal plane through the anterior and posterior commissures. †Z values at the peak of maximum statistical significance at p ⬍ 0.001. FH ⫽ parental family history of AD; FH⫺ ⫽ negative FH; FHp ⫽ paternal FH; FHm ⫽ maternal FH.

inherited in humans, and diseases associated with mtDNA mutations often present as sporadic disorders,29 lends support to this hypothesis. mtDNA abnormalities in AD correlate with increased reactive oxygen species production, mitochondrial respiratory enzymes defects, decreased ATP production, and enhanced amyloid-beta toxicity.30,31 A deficient energy metabolism could change the oxidative microenvironment for neurons during the pathogenesis of AD, rendering synapses more vulnerable to degeneration.29 Oxidative stress is strongly associated with neuronal loss in AD, which mainly affects the medial temporal, PCC, and parieto-temporal cortices.32,33 These regions were progressively hypometabolic in our FHm subjects. Despite showing CMRglc reductions, FHm subjects did not show cognitive deficits, indicating that they may be compensating for advancing brain damage. Although no CMRglc increases were observed in 518

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CMRglc are ␮mol/100 g/min.

FHm, resting-state FDG-PET is not the ideal tool to probe functional compensatory mechanisms, which may be better detected by techniques such as fMRI, using specific challenges. Hypometabolism on FDGPET is known to precede cognitive deficits in NL elderly,12,13 suggesting that the metabolic declines in FHm may be related to a pathologic process. Our results are consistent with epidemiologic observations that a maternal history of AD negatively influ-

ences AD risk5,7,8 and offer a biologic substrate that may account for the clinical findings. Confirmation of this hypothesis awaits further longitudinal studies examining clinical decline in these subjects. Our determination of parental AD in the absence of neuropathologic confirmation is vulnerable to error. We relied on a consensus diagnostic conference to review FH medical records, diagnoses were based on established clinical diagnostic criteria for AD,34,35 and FH questionnaires are known to have good agreement with neuropathologic findings.36 Nonetheless, our affected FH cohort may have included subjects whose parents did not have AD but another dementia. This would lead to erroneous inclusion of subjects in FH groups, with the potential effect of conservatively reducing the power to detect group differences.

12.

13.

14.

15.

16.

17. Received April 30, 2008. Accepted in final form July 24, 2008. REFERENCES 1. Farrer LA, Cupples LA, Haines JL, et al. Effects of age, sex, and ethnicity on the association between apolipoprotein E genotype and Alzheimer disease. JAMA 1997;278:1349– 1356. 2. Cupples LA, Farrer LA, Sadovnik AD, Relkin N, Whitehouse P, Green P. Estimating risk curves for first-degree relatives of patients with Alzheimer’s disease: the REVEAL study. Genet Med 2004;6:192–196. 3. Green RC, Cupples LA, Go R, et al. Risk of dementia among white and African American relatives of patients with Alzheimer disease. JAMA 2002;287:329–336. 4. Silverman JM, Ciresi G, Smith CJ, Marin DB, SchnaiderBeeri M. Variability of familial risk of Alzheimer disease across the late life span. Arch Gen Psychiatry 2005;62: 565–573. 5. Edland SD, Silverman JM, Peskind ER, Tsuang D, Wijsman E, Morris JC. Increased risk of dementia in mothers of Alzheimer’s disease cases: evidence for maternal inheritance. Neurology 1996;47:254–256. 6. Ehrenkrantz D, Silverman JM, Smith CJ, et al. Genetic epidemiological study of maternal and paternal transmission of Alzheimer’s disease. Am J Med Genet 1999;88: 378–382. 7. Au R, Seshadri S, Wolf PA, et al. New norms for a new generation: cognitive performance in the Framingham offspring cohort. Exp Aging Res 2004;30:333–358. 8. Gomez-Tortosa E, Barquero MS, Baron M, et al. Variability of age at onset in siblings with familial Alzheimer disease. Arch Neurol 2007;64:1743–1748. 9. Mosconi L, Brys M, Switalski R, et al. Maternal family history of Alzheimer’s disease predisposes to reduced brain glucose metabolism. Proc Natl Acad Sci USA 2007;104: 19067–19072. 10. Mosconi L, Sorbi S, de Leon MJ, et al. Hypometabolism exceeds atrophy in presymptomatic early-onset Familial Alzheimer’s disease. J Nucl Med 2006;47:1778–1786. 11. Minoshima S, Giordani B, Berent S, Frey KA, Foster NL, Kuhl DE. Metabolic reduction in the posterior cingulate cortex in very early Alzheimer’s disease. Ann Neurol 1997; 42:85–94.

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de Leon MJ, Convit A, Wolf OT, et al. Prediction of cognitive decline in normal elderly subjects with 2-[18F]fluoro-2-deoxy-D-glucose/positron-emission tomography (FDG/PET). Proc Natl Acad Sci USA 2001;98: 10966–10971. Mosconi L, De Santi S, Li J, et al. Hippocampal hypometabolism predicts cognitive decline from normal aging. Neurobiol Aging 2008;29:676–692. Drzezga A, Lautenschlager N, Siebner H, et al. Cerebral metabolic changes accompanying conversion of mild cognitive impairment into Alzheimer’s disease: a PET follow-up study. Eur J Nucl Med Mol Imaging 2003;30: 1104–1113. Hachinski VC, Lassen NA, Marshall J. Multi-infarct dementia, a cause of mental deterioration in the elderly. Lancet 1974;2:207–210. Reisberg B, Ferris SH, de Leon MJ, Crook T. The global deterioration scale for assessment of primary degenerative dementia. Am J Psychiatry 1982;139:1136–1139. The National Institute on Aging, the Reagan Institute Working Group on Diagnostic Criteria for the Neuropathological Assessment of Alzheimer’s disease. Consensus recommendations for the postmortem diagnosis of Alzheimer’s disease. Neurobiol Aging 1997;18:S1–S2. George AE, de Leon MJ, Kalnin A, Rosner L, Goodgold A, Chase N. Leukoencephalopathy in normal and pathologic aging: 2. MRI and brain lucencies. Am J Neuroradiol 1986;7:567–570. Bendriem B, Dewey SL, Schlyer DJ, Wolf AP, Volkow ND. Quantitation of the human basal ganglia with positron emission tomography: a phantom study of the effect of contrast and axial positioning. IEEE Trans Nucl Sci 1991;10:216–222. Reivich M, Alavi A, Wolf A, et al. Glucose metabolic rate kinetic model parameter determination in humans: The lumped constants and rate constants for [18F]fluorodeoxyglucose and [11C]deoxyglucose. J Cereb Blood Flow Metab 1985;5:179–192. Friston KJ, Frith CD, Liddle PF, Frackowiak RSJ. Comparing functional (PET) images: the assessment of significant change. J Cereb Blood Flow Metab 1991;11: 690–699. Mosconi L, Tsui WH, De Santi S, et al. Reduced hippocampal metabolism in mild cognitive impairment and Alzheimer’s disease: automated FDG-PET image analysis. Neurol 2005;64:1860–1867. Talairach J, Tournoux P. Co-Planar Stereotaxic Atlas of the Human Brain. Stuttgart: Thieme; 1988. Reiman EM, Caselli RJ, Chen K, Alexander GE, Bandy D, Frost J. Declining brain activity in cognitively normal apolipoprotein E epsilon 4 heterozygotes: a foundation for using positron emission tomography to efficiently test treatments to prevent Alzheimer’s disease. Proc Natl Acad Sci USA 2001;98:3334–3339. Minoshima S, Frey KA, Koeppe RA, Foster NL, Kuhl DE. A diagnostic approach in Alzheimer’s disease using threedimensional stereotactic surface projections of Fluorine18-FDG PET. J Nucl Med 1995;36:1238–1248. Mosconi L, Tsui WH, Pupi A, et al. (18)F-FDG PET database of longitudinally confirmed healthy elderly improves detection of MCI and AD. J Nucl Med 2007;48: 1129–1134.

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Herholz K, Salmon E, Perani D, et al. Discrimination between Alzheimer dementia and controls by automated analysis of multicenter FDG PET. Neuroimage 2002;17:302–316. Nestor PJ, Fryer TD, Smielewski P, Hodges JR. Limbic hypometabolism in Alzheimer’s disease and mild cognitive impairment. Ann Neurol 2003;54:343–351. Lin MT, Beal MF. Mitochondrial dysfunction and oxidative stress in neurodegenerative diseases. Nature 2006;443:787–795. Trimmer PA, Swerdlow RH, Parks JK, et al. Abnormal mitochondrial morphology in sporadic Parkinson’s and Alzheimer’s disease cybrid cell lines. Exp Neurol 2000; 162:37–50. Swerdlow RH, Parks JK, Cassarino DS, et al. Cybrids in Alzheimer’s disease: a cellular model of the disease? Neurol 1997;49:918–925. Hirai K, Aliev G, Nunomura A, et al. Mitochondrial abnormalities in Alzheimer’s disease. J Neurosci 2001;21: 3017–3023.

33. Valla J, Berndt JD, Gonzales-Lima F. Energy hypometabolism in posterior cingulate cortex of Alzheimer’s patients: superficial laminar cytochrome oxidase associated with disease duration. J Neurosci 2001;21: 4923–4930. 34. McKhann G, Drachman D, Folstein M, Katzman R, Price D, Stadlan EM. Clinical diagnosis of Alzheimer’s disease: report of the NINCDS-ADRDA Work Group under the auspices of Department of Health and Human Services Task Force on Alzheimer’s Disease. Neurology 1984;34: 939–944. 35. American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders (Fourth Edition). 4 ed. Washington, DC: American Psychiatric Association; 1994. 36. Kawas C, Segal J, Stewart WF, Corrada M, Thal LJ. A validation study of the Dementia Questionnaire. Arch Neurol 1994;51:901–906.

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Predictors of driving safety in early Alzheimer disease

J.D. Dawson, ScD S.W. Anderson, PhD E.Y. Uc, MD E. Dastrup, MS M. Rizzo, MD

Address correspondence and reprint requests to Dr. Jeffrey D. Dawson, Department of Biostatistics, University of Iowa College of Public Health, 200 Hawkins Dr., C-22 GH, Iowa City, IA 52242 [email protected]

ABSTRACT

Objective: To measure the association of cognition, visual perception, and motor function with driving safety in Alzheimer disease (AD).

Methods: Forty drivers with probable early AD (mean Mini-Mental State Examination score 26.5) and 115 elderly drivers without neurologic disease underwent a battery of cognitive, visual, and motor tests, and drove a standardized 35-mile route in urban and rural settings in an instrumented vehicle. A composite cognitive score (COGSTAT) was calculated for each subject based on eight neuropsychological tests. Driving safety errors were noted and classified by a driving expert based on video review.

Results: Drivers with AD committed an average of 42.0 safety errors/drive (SD ⫽ 12.8), compared to an average of 33.2 (SD ⫽ 12.2) for drivers without AD (p ⬍ 0.0001); the most common errors were lane violations. Increased age was predictive of errors, with a mean of 2.3 more errors per drive observed for each 5-year age increment. After adjustment for age and gender, COGSTAT was a significant predictor of safety errors in subjects with AD, with a 4.1 increase in safety errors observed for a 1 SD decrease in cognitive function. Significant increases in safety errors were also found in subjects with AD with poorer scores on Benton Visual Retention Test, Complex Figure Test-Copy, Trail Making Subtest-A, and the Functional Reach Test.

Conclusion: Drivers with Alzheimer disease (AD) exhibit a range of performance on tests of cognition, vision, and motor skills. Since these tests provide additional predictive value of driving performance beyond diagnosis alone, clinicians may use these tests to help predict whether a patient with AD can safely operate a motor vehicle. Neurology® 2009;72:521–527 GLOSSARY AD ⫽ Alzheimer disease; AVLT ⫽ Auditory Verbal Learning Test; Blocks ⫽ Block Design subtest; BVRT ⫽ Benton Visual Retention Test; CFT ⫽ Complex Figure Test; CI ⫽ confidence interval; COWA ⫽ Controlled Oral Word Association; CS ⫽ contrast sensitivity; FVA ⫽ far visual acuity; JLO ⫽ Judgment of Line Orientation; MCI ⫽ mild cognitive impairment; MMSE ⫽ Mini-Mental State Examination; NVA ⫽ near visual acuity; SFM ⫽ structure from motion; TMT ⫽ Trail-Making Test; UFOV ⫽ Useful Field of View.

People who develop Alzheimer disease (AD) will generally, at some point in the course of their progressive cognitive decline, become unable to safely drive an automobile. However, as the ability to diagnose AD in early and mild stages continues to improve, many individuals with a diagnosis of probable AD or mild cognitive impairment (MCI) may remain cognitively competent to continue driving for several more years. The obvious goal is to prevent crashes and other dramatic incidents while maximizing patients’ rights and freedom of mobility. Complicating the decision-making process are the biases that patients and families may bring to the situation, e.g., patients may desire to continue driving beyond a point of safety, while family members may either prematurely restrict driving or unwisely encourage driving. Poor awareness of acquired deficits and impaired judgment associated with AD further complicates the decision-making process of patients and their compliance with driving recommendations.1-3

From the Department of Biostatistics (J.D.D., E.D.), Division of Neuroergonomics, Department of Neurology (J.D.D., S.W.A., E.Y.U., E.D., M.R.), Department of Mechanical and Industrial Engineering (M.R.), and Public Policy Center (M.R.), University of Iowa; and VA Medical Center (E.Y.U.), Iowa City, IA. Supported by NIA AG 17717 and NIA AG 15071. Disclosure: The authors report no disclosures. Copyright © 2009 by AAN Enterprises, Inc.

521

The prevalence of dementia is increasing as the population ages, and automobile-dependent societies such as the United States will face a growing public health problem with elderly and demented drivers.4 One approach to addressing this problem is to identify empirically based predictors of unsafe driving in persons with AD. A standardized road test can classify older drivers with a recent history of at-fault crashes,5 lending itself to be used as an index of driver safety. Performance on tests of cognition, visual perception, and motor function has been shown to be associated with driving safety in older drivers5-9 and drivers with dementia.10-12 The use of neuropsychological tests to predict driver performance on a standardized road test may provide a noninvasive and relatively inexpensive index of cognitive impairments in AD that may decrease driver safety. Neuropsychological test performance has previously been shown to be associated with driving safety in studies with a combination of AD and nondemented elderly individuals,13-15 but it has not been clear whether such tests provided additional predictive value beyond that of diagnosis alone. AD is known to impair visual, perception, and motor functions,16 which are critical for safe driving. The goal of the present study was to determine if performances on tests of cognition, visual perception, and motor function could predict the level of safety in licensed drivers with probable AD. METHODS Subjects. Subjects were 40 participants (33 men and 7 women) with mild AD and 115 elderly drivers without dementia (60 men and 55 women). Participants with AD were recruited from a registry maintained by the Department of Neurology. The diagnosis of probable AD was based on National Institute of Neurological and Communicative Disorders and Stroke–Alzheimer’s Disease and Related Disorders Association criteria.17 Accordingly, all AD participants had symptoms of memory impairment and related cognitive complaints that interfered with their social or occupational life. Mini-Mental State Examination (MMSE) screening reflected mild early cognitive decline in these still licensed drivers (mean MMSE ⫾ SD ⫽ 26.5 ⫾ 2.9). Ten Subjects with AD were taking Aricept. Impairments of memory and other cognitive domains on a standardized battery of neuropsychological tests (table 1) were consistent with early AD.18 Control participants were recruited from volunteers in the local community, who had no neurologic diagnosis or complaints, and no personal or family report of abnormal cognitive decline. All participants held a valid state driver’s license and were still driving, although some had reduced driving activity because of self-imposed or family-imposed restrictions. Exclusion criteria in both groups included non-AD neurologic disease, brain le522

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sions due to cerebrovascular or neoplastic disease, alcoholism, stroke, depression or other psychiatric conditions, vestibular disease, and motion sickness. This study was approved by the Institutional Review Board at the University of Iowa, and informed consent was obtained in accord with institutional and federal guidelines for human subjects’ safety and confidentiality.

Off-road neuropsychological battery. All participants were tested on a battery of cognitive, visual, and motor tasks (table 1). The Rey-Osterreith Complex Figure Test-Copy version (CFT-Copy) requires participants to copy a complex geometric figure, which provides an index of visuoconstructional ability. In the CFT-Recall version, a measure of visual anterograde memory, the subject is asked to draw the figure from memory 30 minutes after copying the CFT. The Block Design subtest (Blocks) from the WAIS-R provides an additional measure of visuoconstructional ability that correlates with performance IQ. The Benton Visual Retention Test (BVRT) stresses visual working memory. The Trail-Making Test subtest A (TMT-A) assesses visual search and visual motor speed, while subtest B (TMT-B) places demands on executive functions, including working memory and attentional set shifting. Rey Auditory Verbal Learning Test (AVLT) measures anterograde verbal memory. Judgment of Line Orientation (JLO) assesses visuospatial perception, by requiring matching lines of different orientation to target. The Controlled Oral Word Association (COWA) Test requires subjects, within a 1-minute time limit, to generate as many words as possible that begin with a certain letter of the alphabet. All of the above tasks are described in detail elsewhere.19,20 We calculated a composite measure of cognitive impairment (COGSTAT) by assigning and summing standard t scores (mean ⫽ 50, SD ⫽ 10) to each of the eight tests from the neuropsychological assessment battery (COWA, CFT-Copy, CFT-Recall, AVLT, BVRT, Blocks, JLO, and TMT-B), as in our previous work.21,22 The Useful Field of View (UFOV) task (Visual Attention Analyzer, Visual Resources Inc.) measures speed (in msec) of visual processing, divided attention, and selective attention.23,24 UFOV loss correlates with increased crash risk in simulated driving scenarios and real life crashes.23,24 We used the sum of four subtests of the UFOV task (UFOV-Total) in our analyses. Contrast sensitivity (CS) was assessed using the Pelli-Robson chart.25 The best-corrected visual acuity was measured using the Early Treatment Diabetic Retinopathy Study chart26 for far visual acuity (FVA) and reduced Snellen chart for near visual acuity (NVA), both expressed as logarithm of the minimum angle of resolution (logMAR), with 0 representing 20/20 vision. Perception of three-dimensional structure from motion (SFM) and motion direction were tested using computer-generated animation sequences.22 We also administered tests of motor abilities. Functional Reach is the difference between arm length and maximal forward reach using a fixed base of support. It is portable, inexpensive, precise, reliable, quick to administer, and useful for detecting balance impairment and change of balance performance over time.27,28 The Get-Up-and-Go task requires subjects to stand up from a chair, walk a short distance, turn around, return, and sit down again. It is safe, shows excellent interrater reliability, and appears to predict an elderly individual’s ability to safely go outside alone.28 The Grooved Pegboard task measures the time that it takes for subjects to insert noncylindrical metal pins into a small base stand using one hand per trial; we used the average time of the two trials per subject as a measure of motor dexterity and speed. Instrumented vehicle. The experimental drive was conducted aboard an instrumented vehicle known as ARGOS (the Automobile

Table 1

Characteristics of Alzheimer disease (AD) and non-AD control groups, mean (SD) p Values for difference AD (n ⴝ 40)

Controls (n ⴝ 115)

Crude

Age- and gender-adjusted

Demographics Age, y

75.1 (7.7)

69.4 (7.0)

⬍0.0001

Education, y

15.6 (3.1)

15.8 (2.5)

0.5696

No. of vision-related comorbidities

0.6 (0.7)

0.1 (0.3)

0.1101

No. of medications

2.2 (2.8)

2.7 (2.3)

0.048

28.3 (4.9)

31.8 (3.5)

⬍0.0001

0.0003

8.7 (4.5)

15.3 (5.6)

⬍0.0001

⬍0.0001

25.2 (11.5)

39.1 (10.3)

⬍0.0001

⬍0.0001

9.3 (3.4)

4.8 (2.5)

⬍0.0001

⬍0.0001

TMT-A

53.8 (18.4)

35.8 (19.9)

⬍0.0001

⬍0.0001

TMT-B*

173.6 (87.3)

84.0 (41.7)

⬍0.0001

⬍0.0001

Cognitive tests CFT-Copy* CFT-Recall* Blocks* BVRT (errors)*

2.8 (2.5)

10.0 (3.1)

⬍0.0001

⬍0.0001

JLO*

23.5 (4.2)

25.8 (3.7)

0.0022

⬍0.0001

COWA*

33.0 (9.8)

38.7 (11.2)

0.0057

0.0348

297.2 (54.4)

404.6 (43.7)

⬍0.0001

⬍0.0001

1.65 (0.18)

1.83 (0.14)

⬍0.0001

⬍0.0001

AVLT*

COGSTAT Visual tests Contrast sensitivity

1232 (292)

676 (211)

⬍0.0001

⬍0.0001

Near visual acuity

0.05 (0.08)

0.02 (0.04)

0.0016

0.0042

Far visual acuity

0.03 (0.12)

⫺0.07 (0.12)

⬍0.0001

0.0003

Structure from motion

12.9 (5.7)

10.3 (2.7)

0.0240

0.0003

11.1 (2.1)

8.8 (2.5)

⬍0.0001

0.0001

11.7 (2.9)

13.2 (2.7)

Useful Field of View-Total

Motor tests Get-Up-and-Go Functional Reach Grooved Pegboards

115.0 (33.4)

87.6 (17.4)

0.0034

0.1112

⬍0.0001

⬍0.0001

Groups were compared using Wilcoxon rank sum for crude p values and multiple linear regression for adjusted p values. *The eight individual components of COGSTAT. CFT ⫽ Complex Figure Test; Blocks ⫽ Block Design subtest; BVRT ⫽ Benton Visual Retention Test; TMT ⫽ Trail-Making Test; AVLT ⫽ Auditory Verbal Learning Test; JLO ⫽ Judgment of Line Orientation; COWA ⫽ Controlled Oral Word Association.

for Research in Ergonomics and Safety), a mid-sized car with an automatic transmission and hidden instrumentation and sensors.14,29-31 Experimental performance data (steering wheel position, accelerator and brake pedal position, lateral and longitudinal acceleration, and vehicle speed) were recorded at 10 Hz. Control of speed32 and lane position33 are critical aspects of driving, and unplanned lane deviations occur with degradation of driving performance.34 Driver’s lane tracking and visual scanning activity of the environment were recorded by videotape at 10 frames per second using four miniature lipstick-size cameras mounted unobtrusively within the vehicle.

Administering the road test. The road test was generally administered within 2 months of the off-road battery, with a median of 28 days elapsed between the two visits. Each subject was seated in the driver’s seat, with the experimenter in the front

passenger seat to give instructions and operate the dual controls, if needed. The experimental drive started after the driver acclimated to the vehicle on a short test drive, and lasted approximately 45 minutes. Road testing was carried out only during the day on specific roads within and surrounding Iowa City. Drivers were not tested in inclement weather that might cause poor visibility or road conditions. The drive incorporated several essential maneuvers such as turns, stopping at a stop sign, and maintaining vehicle control.

Safety errors. A certified driving instructor reviewed the videotapes to assess the number and type of safety errors committed by the drivers. This instructor used a taxonomy based on the Iowa Department of Transportation’s Drive Test Scoring Standards (September 7, 2005 version), which included 76 error types (e.g., “unsafe passing,” “tailgating”) organized into 15 categories (e.g., “turns,” “lane observance”). Of the 76 error types, 30 were classified by our research team as “more serious,” and the rest were considered “less serious.” For example, if a subject failed to yield the right of way at a stop sign, this was judged as more serious, since this behavior may lead to a near crash or crash. We tabulated the total number of safety errors, the number of safety errors within each category, and the total number of more serious and less serious safety errors. Statistical analysis. We compared the groups with respect to demographics, neuropsychological measures, and safety error outcomes using the Wilcoxon rank sum test. Multiple linear regression was used to adjust for age and gender when comparing neuropsychological measures and safety errors. We also used multiple linear regression to test for associations between neuropsychological measures and total safety errors within the AD group, after adjusting for age and gender. For these analyses, we expressed the regression coefficients in terms of the average difference in safety errors per 1 SD difference in each neuropsychological measure, facilitating comparisons of magnitude of effect across predictors. In addition to examining the effect of neuropsychological tests individually, we modeled their simultaneous effects using multiple linear regression. We used standard regression diagnostic methods to assess the appropriateness of our models. RESULTS Table 1 presents demographic and neuropsychological descriptions of the two groups. Compared to subjects without AD, the subjects with AD were older and on fewer medications. They also had more vision-related comorbidities, but this was not significant. The AD group performed worse than the control group on almost all neuropsychological tests. As shown in table 2, drivers with AD committed an average of 42.0 total safety errors/drive, compared to an average of 33.2 for controls without AD. Adjusting for age and gender, the mean (95% confidence interval [CI]) of the between-group difference was 5.9 (1.2, 10.6) for total errors, 2.3 (1.5, 3.0) for more serious errors, 3.7 (0.0, 7.5) for less serious errors, and 5.1 (1.7, 8.5) for lane observance errors. Increased age was predictive of total safety errors, with a mean of 2.3 more errors per drive observed for each 5-year age increment; gender was not significant. Neurology 72

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523

Table 2

Driver safety errors in Alzheimer disease (AD) and normal control groups

Table 3

Changes in total safety errors for a 1 SD increase in cognitive, visual, and motor predictors

p Values for difference Predictors Safety errors

AD (n ⴝ 40)

Controls (n ⴝ 115)

Crude

Age- and gender-adjusted

Starting and pulling away from curve

1.08 (0.97)

1.09 (0.81)

0.7097

0.4392

Traffic signals

2.35 (1.56)

2.18 (1.56)

0.5101

0.4739

Stop signs

3.80 (1.98)

3.61 (1.89)

0.7610

0.6587

Other signs

0 (0)

0 (0)

6.50 (3.09)

5.44 (2.79)

0.0838

0.1412

10.84 (7.77)

0.0003

0.0039

Turns Lane observance

17.03 (11.00)

—

—

Lane change

5.75 (2.86)

5.00 (2.75)

0.1253

0.9386

Overtaking

0.10 (0.38)

0.15 (0.46)

0.5075

0.5539

Control of speed

4.03 (2.71)

3.56 (2.79)

0 (0)

0 (0)

Parallel parking

0.38 (0.49)

0.37 (0.52)

Head-in parking

0 (0)

0 (0)

Curves

0.00 (0.00)

0.01 (0.09)

0.5653

0.7983

Railroad crossing

0.03 (0.16)

0.19 (0.58)

0.1115

0.0533

Miscellaneous

0.98 (1.03)

0.73 (1.05)

0.0859

0.4132

42.00 (12.84)

33.18 (12.22)

⬍0.0001

0.0148

⬍0.0001

⬍0.0001

0.0009

0.0516

Backing up

Total safety errors Total more serious errors

4.35 (2.97)

1.90 (1.59)

Total less serious errors

37.65 (11.66)

31.26 (11.49)

0.2634 — 0.8172 —

0.7504 — 0.7172 —

Groups were compared using Wilcoxon rank sum for crude p values and multiple linear regression for adjusted p values.

Other than lane observance errors (a.k.a., lane deviations), no other general category of errors was significantly more common in the AD group. Among more serious errors, straddling the center line (one of eight types of errors within the general category of lane observance errors) was the most common type, followed by failing to proceed through intersection even though the light had turned green (a specific type of traffic signal error). Both of these error types were significantly more common in drivers with AD than in drivers without AD. There was a borderline indication that railroad crossing errors may have been higher in the non-AD group (adjusted p ⫽ 0.053). We randomly selected videotapes from 30 participants for a second video review by our driving expert, as well as by a second rater. Among these 30 drivers, we found that the intrarater correlation for total safety errors was 95%, while the interrater correlation was 73%. Table 3 shows that the drivers with AD with higher overall cognitive function (measured by COGSTAT) tended to make fewer total safety errors. Several individual tests also were significant predictors of safety errors among drivers with AD, including measures of working memory (BVRT), vi524

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Coefficient estimate (SE)

Cognitive tests CFT-Copy

⫺3.54 (1.54)*

CFT-Recall

⫺4.44 (2.38)†

JLO

⫺0.58 (1.97)

Blocks

⫺2.29 (1.91)

BVRT (Errors)

4.12 (1.55)*

TMT-A

2.97 (1.46)*

TMT-B

2.40 (1.35)†

AVLT

2.43 (2.48)

COWA

⫺2.37 (2.31)

COGSTAT

⫺4.14 (1.66)*

Visual tests Contrast sensitivity

0.32 (1.86)

UFOV-Total

3.44 (1.72)†

Near visual acuity Far visual acuity Structure from motion

⫺1.48 (1.38) 0.22 (2.06) ⫺0.25 (1.49)

Motor tests Get-Up-and-Go Functional Reach Grooved Pegboard

2.79 (2.55) ⫺4.31 (1.99)* 0.80 (1.54)

Coefficients and p values for multiple linear regression, adjusting for age and gender. Values expressed as coefficient estimate (SE). *p ⬍ 0.05. †p ⬍ 0.10. CFT ⫽ Complex Figure Test; JLO ⫽ Judgment of Line Orientation; Blocks ⫽ Block Design subtest; BVRT ⫽ Benton Visual Retention Test; TMT ⫽ Trail-Making Test; AVLT ⫽ Auditory Verbal Learning Test; COWA ⫽ Controlled Oral Word Association; UFOV ⫽ Useful Field of View.

sual search and visual motor speed (TMT-A), visuoconstructional abilities (CFT-Copy), and motor function (Functional Reach). Tests that were nearly significant in subjects with AD included CFTRecall, TMT-B, and UFOV-Total. Since lane observance errors were the most common type of safety error, accounting for the majority of the between-group differences, we repeated our analyses using lane observance errors as the outcome. We found that this outcome was significantly predicted by worse scores on CFT-Copy, UFOV-Total, and Functional Reach. COGSTAT, BVRT, and Get-Up-and-Go were nearly significant predictors. When predicting total errors in subjects with AD, we found that age, BVRT, and TMT-A modeled together resulted in an appropriate balance of model fit (adjusted R2 near the maximum achieved) and parsimony (e.g., only three predictor variables). Accord-

Table 4

Multivariable regression model predicting total safety errors in subjects with Alzheimer disease (R2 ⴝ 0.29; adjusted R2 ⴝ 0.23)

Variable

Coefficient estimate

Standard error

t Statistic

p Value

Intercept

⫺20.06

20.201

⫺0.99

0.3273

Age

0.5095

0.2381

2.14

0.0392

BVRT (Errors)

1.4083

0.5328

2.64

0.0121

TMT-A

0.1985

0.0985

2.02

0.0513

BVRT ⫽ Benton Visual Retention Test; TMT ⫽ Trail-Making Test.

ing to this model (table 4), an increase of 2 years in age corresponded to an increase of 1.0 driving error, an increase of 1 error on BVRT corresponded to an average increase of 1.4 driving errors, and an additional 5 seconds to complete the TMT-A task corresponded to an increase of 1.0 driving error. Table 5 illustrates how these three risk factors predict safety errors. For each of these risk factors, we chose low, medium, and high levels representative of the subjects with AD in our study. Across these ranges of risk factors, table 5 shows that subjects with AD with high-risk profiles tend to commit noticeably more safety errors than those with low-risk profiles, even when keeping age fixed. This model assumed that the factor effects were additive, which was supported by nonsignificant tests of interaction. DISCUSSION This study aimed to measure the association of cognition, visual perception, and motor function with driving safety in drivers with AD. We found that drivers with AD make more total safety errors, lane observance errors, and serious safety errors than elderly drivers without AD. For predicting safety errors within the AD group, off-road neuropsychological tests of cognition, vision, and motor abilities gave additional information above and beyond diagnosis alone. Hence, performance on these

Table 5

Expected total of driving safety errors as a function of age, TMT-A, and BVRT in subjects with Alzheimer disease Expected total of driving safety errors

TMT-A 40 sec

55 sec

70 sec

BVRT (Errors) 6

Age 70 y

Age 75 y

Age 80 y

32.0

34.5

37.1

9

36.2

38.8

41.3

12

40.4

43.0

45.5

6

35.0

37.5

40.1

9

39.2

41.7

44.3

12

43.4

46.0

48.5

6

37.9

40.5

43.0

9

42.2

44.7

47.3

12

46.4

48.9

51.5

TMT ⫽ Trail-Making Test; BVRT ⫽ Benton Visual Retention Test.

tests can be helpful when predicting whether a patient with AD can safely drive a vehicle. Our results showing that drivers with mild AD make more safety errors than older drivers without dementia on a standardized road test are compatible with other studies of driving in dementia.10,35 Previous studies of driving safety often have not adjusted analyses for diagnosis,36 making it difficult to assess the added value of tests beyond the diagnosis of dementia. In AD, it is expected that cognitive abilities will continue to decline after the diagnosis, and there is a great range of cognitive abilities and impairments in individuals with a diagnosis of AD. Our finding that active drivers with AD and poorer cognitive abilities show greater performance impairments leading to safety errors is an important step in defining the hypothetical causal relationships between cognition, driving errors, and car crashes. We found that a composite score reflecting test performances across multiple cognitive domains was the best predictor of driving safety in persons with AD. This is consistent with both the multifaceted cognitive demands of driving and the range of cognitive impairments resulting from AD. Given that driving puts demands on diverse cognitive functions, it is unlikely that a test of any single cognitive ability will be an accurate predictor of driving safety. It is clear that impairment of anterograde memory, generally considered to be the hallmark of AD, is not a good indicator of driving ability in this population, and we have previously found that even persons with severe amnesia can perform most aspects of automobile operation without substantial difficulty.37 Lane deviations were the most common safety violations committed by the subjects with AD and, consistent with the findings of a recent meta-analysis,36 we found that tests placing demands on both visuospatial abilities and motor responses were among the best predictors of driving safety. It appears likely that these tests are measuring impairments of the requisite visuospatial and visuomotor abilities for maintaining a moving vehicle within lane boundaries. Given that AD results in progressive and widespread dysfunction in posterior association cortices, which are known to provide necessary substrates for visuospatially mediated tasks, this is a plausible key contributor to the unsafe driving of persons with AD. Of the 15 general categories of errors that we examined (table 2), only lane observance errors were significantly more common in drivers with AD. This suggests that drivers with mild AD have the ability to handle certain aspects of driving. Also, though not quite significant, the drivers with AD made fewer errors at railroad crossings. This may be an example where drivers without AD are likely to be confident Neurology 72

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when approaching an area of potential hazard, while drivers with AD are likely to be cautious. Being overly confident often leads to safety errors when the potential hazard is a railroad crossing (where drivers without AD may make more errors), whereas in the case of traffic signals, being overly cautious can lead to the safety error of failing to proceed through a green light (committed more often by drivers with AD). Our study has a number of limitations. Although our driving test was designed to be as unobtrusive as possible, it was still an experimental setting and drivers may have performed differently than they would have in their own vehicles in a more naturalistic setting. Also, driving safety is likely to be affected by a number of other environmental factors that we did not investigate, such as presence of family members in the vehicle, weather and road conditions, distance traveled, and time of day. Also, our sample of patients with AD only included seven women, so our study may have been underpowered to detect gender effects. Additionally, our subject identification numbering system was such that our expert rater may have been aware of a driver’s diagnosis status (though not the specific off-road scores) when reviewing the tapes for errors. Finally, although we had videotaped information based on views from four cameras, our rater may have missed some errors that would have been easier to detect if he had been in the vehicle during the drive. Our current results underscore the fact that linkages between driving performance and abilities measured by off-road tests of cognitive, visual, and motor abilities can help standardize the assessment of fitness to drive. By understanding patterns of driver errors that may cause crashes, it may be possible to design interventions to reduce these errors and injuries and preserve mobility.

5.

6.

7.

8.

9.

10.

11.

12. 13.

14.

15.

16.

17.

AUTHOR CONTRIBUTIONS Statistical analysis was conducted by J.D.D. and E.D.

Received August 4, 2008. Accepted in final form October 31, 2008.

REFERENCES 1. Anderson SW, Tranel D. Awareness of disease states following cerebral infarction, dementia, and head trauma: standardized assessment. Clin Neuropsychol 1989;3:327– 339. 2. Starkstein SE, Mizrahi R, Jorge R, Robert R. A diagnostic formulation for anosognosia in Alzheimer’s disease. J Neurol Neurosurg Psychiatry 2006;77:719–725. 3. Souchay C. Metamemory in Alzheimer’s disease. Cortex 2007;43:987–1003. 4. Hopkins RW, Kilik L, Day DJ, Rows C, Tseng H. Driving and dementia in Ontario: a quantitative assessment of the problem. Can J Psychiatry 2004;49:434–438. 526

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De Raedt R, Ponjaert-Kristoffersen I. Predicting at-fault car accidents of older drivers. Accid Anal Prev 2001;33: 809–819. Odenheimer GL, Beaudet M, Jette AM, Albert MS, Grande L, Minaker KL. Performance-based driving evaluation of the elderly driver: safety, reliability, and validity. J Gerontol 1994;49:M153–M159. McGwin G, Jr, Chapman V, Owsley C. Visual risk factors for driving difficulty among older drivers. Accid Anal Prev 2000;32:735–744. Owsley C, Ball K, McGwin G Jr, et al. Visual processing impairment and risk of motor vehicle crash among older adults. JAMA 1998;279:1083–1088. Marottoli RA, Cooney LM Jr, Wagner R, Doucette J, Tinetti ME. Predictors of automobile crashes and moving violations among elderly drivers. Ann Intern Med 1994; 121:842–846. Ott BR, Heindel WC, Papandonatos GD, et al. A longitudinal study of drivers with Alzheimer disease. Neurology 2008;70:1171–1178. Ott BR, Festa EK, Amick MM, Grace J, Davis JD, Heindel WC. Computerized maze navigation and on-road performance by drivers with dementia. J Geriatr Psychiatry Neurol 2008;21:18–25. Brown LB, Ott BR. Driving and dementia: a review of the literature. J Geriatr Psychiatry Neurol 2004;17:232–240. Grace J, Amick MM, D’Abreu A, Festa EK, Heindel WC, Ott BR. Neuropsychological deficits associated with driving performance in Parkinson’s and Alzheimer’s disease. JINS 2005;11:766–775. Rizzo M, McGehee D, Petersen AD, Dingus TA. Development of an unobtrusively instrumented field research vehicle for objective assessments of driving performance. In: Rothengatter T, Carbonnel VE, eds. Traffic and Transport Psychology: Theory and Application. New York: Pergamon; 1997:203–208. Uc EY, Rizzo M, Anderson SW, Shi Q, Dawson JD. Driver route-following and safety errors in early Alzheimer disease. Neurology 2004;63:832–837. Rizzo M, Anderson SW, Dawson J, Nawrot M. Vision and cognition in Alzheimer’s disease. Neuropsychologia 2000; 38:1157–1169. McKhann G, Drachman D, Folstein M, Katzman R, Price D, Stadlan EM. Clinical diagnosis of Alzheimer’s disease: report of the NINCDS-ADRDA Work Group under the auspices of Department of Health and Human Services Task Force on Alzheimer’s Disease. Neurology 1984;34: 939–944. Salmon DP, Thomas RG, Pay MM, et al. Alzheimer’s disease can be accurately diagnosed in very mildly impaired individuals. Neurology 2002;59:1022–1028. Lezak MD. Neuropsychological Assessment. New York: Oxford University Press; 1995. Spreen O, Strauss E. A Compendium of Neuropsychological Tests. New York: Oxford University Press; 1991. Rizzo M, McGehee DV, Dawson JD, Anderson SW. Simulated car crashes at intersections in drivers with Alzheimer disease. Alzheimer Dis Assoc Disord 2001;15:10–20. Rizzo M, Nawrot M. Perception of movement and shape in Alzheimer’s disease. Brain 1998;121:2259–2270. Ball K, Owsley C, Sloane ME, Roenker DL, Bruni JR. Visual attention problems as a predictor of vehicle crashes in older drivers. Invest Ophthalmol Vis Sci 1993;34:3110–3123.

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Owsley C, Ball K, Sloane ME, Roenker DL, Bruni JR. Visual/cognitive correlates of vehicle accidents in older drivers. Psychol Aging 1991;6:403–415. Pelli DG, Robson JG, Wilkins AJ. The design of a new letter chart for measuring contrast sensitivity. Clin Vis Sci 1988;2:187–199. Ferris FL, III, Kassoff A, Bresnick GH, Bailey I. New visual acuity charts for clinical research. Am J Ophthalmol 1982;94:91–96. Duncan PW, Weiner DK, Chandler J, Studenski S. Functional reach: a new clinical measure of balance. J Gerontol 1990;45:M192–M197. Alexander NB. Postural control in older adults. J Am Geriatr Soc 1994;42:93–108. Barry CJ, Smith D, Lennarson P, et al. The effect of wearing a restrictive neck brace on driver performance. Neurosurgery 2003;53:98–102. Uc EY, Rizzo M, Anderson SW, Shi Q, Dawson JD. Driver identification of landmarks and traffic signs after a stroke. Transportation Research Record J Transportation Research Board 2005;1922:9–14. Rizzo M, Stierman L, Skaar N, Dawson JD, Anderson SW, Vecera SP. Effects of a controlled auditory-verbal dis-

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Increased striatal dopamine (D2/D3) receptor availability and delusions in Alzheimer disease Suzanne Reeves, MRCPsych Richard Brown, PhD Robert Howard, MD Paul Grasby, FMed Sci

ABSTRACT

Objective: Dysfunction within corticostriatal dopaminergic neurocircuitry has been implicated in neuropsychiatric symptoms associated with Alzheimer disease (AD). This study aimed to test the hypothesis that the symptom domains delusions and apathy would be associated with striatal dopamine (D2) receptor function in AD.

Methods: In vivo dopamine (D2/D3) receptor availability was determined with [11C]raclopride Address correspondence and reprint requests to Dr. Suzanne Reeves, Section of Old Age Psychiatry, MRC Centre for Neurodegeneration Research, Institute of Psychiatry, De Crespigny Park, Camberwell, London SE5 8AF, UK [email protected]

(RAC) PET in 23 patients with mild and moderate probable AD. Behavioral symptoms were measured using the Neuropsychiatric Inventory and the Apathy Inventory. Imaging data were analyzed using a region-of-interest approach. The potential confounding effects of age, sex, and disease stage were explored using a linear mixed model. Correlational and independent samples comparisons were used to examine the relationship between behavioral and binding potential (BPND) measures.

Results: Mean [11C]RAC BPND was higher in patients with delusions (n ⫽ 7; 5 men) than in patients without delusions (n ⫽ 16; 6 men) (p ⫽ 0.006). When women were excluded from the analysis, [11C]RAC BPND was higher in men with delusions than in men without delusions (p ⫽ 0.05). Apathy measures showed no association with [11C]RAC BPND.

Conclusions: Striatal dopamine (D2/D3) receptor availability is increased in Alzheimer disease patients with delusions, to an extent comparable to that observed in drug-naive patients with schizophrenia. Whether this represents up-regulation of dopamine (D2) or possibly dopamine (D3) receptors and how this relates to responsivity of the striatal dopaminergic system merit further exploration. Neurology® 2009;72:528–534 GLOSSARY AD ⫽ Alzheimer disease; AI ⫽ Apathy Inventory; AST ⫽ associative striatum; BP ND ⫽ binding potential; CAMCOG ⫽ Cambridge Cognitive Examination; DA ⫽ dopamine; LS ⫽ limbic striatum; MMSE ⫽ Mini-Mental State Examination; MRC ⫽ Medical Research Council; non-AC ⫽ non–attenuated corrected; NPI ⫽ Neuropsychiatric Inventory; RAC ⫽ raclopride; ROI ⫽ region of interest; SMST ⫽ sensorimotor striatum.

The neurochemical changes that underpin neuropsychiatric symptoms in Alzheimer disease (AD) have been poorly elucidated. In vivo studies that avoid the confounding influences of illness duration and exposure to psychotropics that are encountered postmortem1 could identify potential treatment targets. Perturbation of cholinergic– dopaminergic influences within corticostriatal neurocircuitry have been implicated in the development of psychosis2 and apathy.3 Excessive striatal dopamine (DA) activity is viewed as the final common pathway in the development of psychotic symptoms; and in AD progressive cholinergic loss, within the context of a functionally intact dopaminergic system, may increase the propensity of patients with AD to develop psychosis because of a relative striatal hyperdopaminergia.2 Apathy is believed to represent a deficit in corticostriatal (ventral striatum, prefrontal cortex) processing,4 characterSupplemental data at www.neurology.org From the Medical Research Council (MRC) Centre for Neurodegeneration Research (S.R., R.B., R.H.), Institute of Psychiatry, De Crespigny Park, Camberwell; and MRC Clinical Science Centre (P.G.), Imperial College, Hammersmith Hospital, London, UK. Supported by the Wellcome Research Trust, as part of a Research Training Fellowship, and by the MRC. Disclosure: The authors report no competing interests. R.H. discloses that he has received honoraria as speaker’s fee from Lundbeck and Pfizer-Eisai. Pfizer-Eisai and Lundbeck have provided medication and placebo for independently funded randomized controlled trials on which R.H. is Chief Investigator. P.G. has served as an occasional consultant to GlaxoSmithKline, Merck, and Pfizer. 528


Table 1

Descriptive and neuropsychological test data Whole sample (n ⴝ 23)

Men (n ⴝ 11)

Women (n ⴝ 12)

Mean (SD); range Age, y

78.7 (6.3); 66–89

79.7 (5.5); 74–89

77.8 (7.0); 66–86

Education, y

11.4 (2.9); 9–18

11.4 (3.2); 9–16

11.4 (2.7); 9–18

MMSE, maximum ⴝ 30

21.5 (3.0); 16–26

21.4 (3.2); 16–25

21.6 (3.0); 17–26

CAMCOG (n ⴝ 21) (maximum ⴝ 105)

72.5 (9.6); 50–90

69.8 (12.2); 50–82

74.5 (6.9); 62–90

NPI total score (n ⴝ 23) (range 0–144)

15.6 (12.5); 0–50

14.5 (8.6); 0–29

16.7 (15.6); 0–50

No. (%) presenting with symptom Delusions

7 (30)

5 (46)

2 (17)

Hallucinations

1 (4)

0

1 (8)

Agitation

8 (35)

3 (27)

5 (42)

Depression

10 (43)

4 (36)

6 (50)

Anxiety*

10 (83)

13 (57)

3 (27)

Elation

2 (9)

2 (18)

0

Apathy

16 (70)

8 (73)

8 (67)

7 (30)

3 (27)

4 (33)

12 (52)

7 (64)

5 (42)

Abnormal motor behavior

9 (39)

5 (46)

4 (33)

Sleep

6 (26)

3 (27)

3 (25)

Appetite

5 (22)

2 (18)

3 (25)

Disinhibition Irritability

*Frequency of symptoms was higher in women (Fisher exact test, p ⫽ 0.01). MMSE ⫽ Mini-Mental State Examination; CAMCOG ⫽ Cambridge Cognitive Examination; NPI ⫽ Neuropsychiatric Inventory.

ized by a reduced ability to process emotionally significant stimuli.5 In vivo studies in small numbers of patients with moderately severe AD (n ⫽ 10) have reported higher DA (D2) receptor availability in association with wandering behavior6 and lower striatal DA (D2) receptor availability in more behaviorally disturbed patients.7 More recently, higher striatal DA transporter availability has been correlated with apathy (“loss of initiative”) in a larger sample (n ⫽ 24) that included 8 patients with Lewy body dementia.8 We aimed to test the hypothesis that striatal DA (D2) receptor availability— using the DA (D2/D3) receptor ligand [11C]raclopride (RAC)—would be associated with delusions and apathy in psychotropic-naive patients with mild to moderate AD. METHODS Sample. Twenty-three patients with probable late-onset Alzheimer dementia were recruited as part of wider study aiming to investigate the influence of donepezil on striatal DA release. Twenty-one patients were recruited from a dedicated memory clinic (the Croydon Memory Service), and two were recruited from community mental health teams. All patients fulfilled National Institute of Neurological and Communicative

Disorders and Stroke–Alzheimer’s Disease and Related Disorders Association criteria for AD9 and were eligible to receive treatment with a cholinesterase inhibitor but had not yet commenced medication. Clinical assessment included screening with the Mini-Mental State Examination (MMSE)10 (all patients) and, in patients assessed by the Croydon Memory Service (n ⫽ 21), the Cambridge Cognitive Examination (CAMCOG).11 Where scores were above the suggested cutoff for questionable dementia (⬎24/30 on the MMSE or ⬎79/105 on the CAMCOG), neuropsychological testing was conducted to establish the diagnosis. All subjects underwent standard laboratory investigation and structural (MRI) imaging to rule out other cause of memory loss and to quantify the extent of vascular pathology: Seven patients (30.4%) showed radiologic signs of vascular pathology—small vessel disease (n ⫽ 4) or silent lacunar infarcts (n ⫽ 3). Patients were excluded on the basis of past or current psychiatric illness or the prescription of medication that might influence DA function. The study was approved by the Charing Cross and Joint South London and Maudsley and The Institute of Psychiatry Research Ethics Committees. The Administration of Radioactive Substances Advisory Committee granted permission to administer [11C]RAC. Written and verbal consent was obtained at the time of recruitment and repeated before the scanning procedure.

Behavioral ratings. The Neuropsychiatric Inventory (NPI)12 evaluates 12 symptom domains (shown in table 1) over the preceding month, and scores range from 0 (not present) to 12 if present very frequently4 and are very disruptive.3 The Apathy Inventory (AI)13 separates apathy into three components: emotional blunting, lack of interest, and lack of initiative. Scoring follows the same rules as the NPI (maximum score of 12 on each of the three domains). Ratings were made by a live-in carer on the day of the scan. No cutoff point was used to categorize any of the symptom domains.

PET procedure. [11C]RAC PET is an established in vivo method for estimating the availability of DA (D2) receptors in the brain. Participants were scanned at rest on a 962-Siemens/ CTI PET camera in three-dimensional mode. Head movement was minimized using a molded headrest and straps. Each scan consisted of 1) a short (10-minute) transmission scan to enable correction for tissue attenuation of radioactivity and 2) dynamic scanning: [11C]RAC was administered as a bolus injection followed by a constant-rate infusion with a ␬bol of 60 minutes.14 The bolus infusion method enables a state of equilibrium to be reached which avoids potential artifacts introduced through blood flow change during the scan.15 Total administered activity was 370 MBq per scan. The sampling period for calculation of the binding potential (BPND), after RAC equilibrium had been established, was 35 to 60 minutes collected over 20 serial time frames. Head movement was corrected using a frame-by-frame realignment procedure, previously described.16 Non–attenuated corrected (non-AC) images were used for realignment, to provide additional information by reducing the influence of redistribution of radiotracer producing erroneous realignments. The non-AC image was denoised using a level 2, order 64 Battle Lemarie wavelet. A mutual information algorithm was applied for frame realignment to a single frame acquired 35 minutes after injection, in which there was a high signal-to-noise ratio. Finally, transformation parameters were applied to the corresponding attenuation-corrected dynamic images for frames 15 through 20 to generate a frame-by-frame corrected dynamic image.

Region-of-interest analysis. Region-of-interest (ROI) templates for striatal and cerebellar areas were defined on a magnetic Neurology 72

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Figure 1

Striatal regions of interest

Right-sided sensorimotor (SMS), associative (AST), and limbic (LS) striatal regions of interest, defined on a magnetic resonance scan, have been superimposed on a [11C]raclopride (dynamic) image positioned in standard Montreal Neurological Institute space. (A) Transverse view, SMS and AST. (B) Coronal view, AST and LS. (C) Sagittal view, AST and LS.

resonance scan positioned in standard Montreal Neurological Institute space. Three striatal subregions were defined bilaterally, based on previously described criteria17: the limbic striatum (LS) corresponds to the ventral striatum, and the caudate and putamen were subdivided along their rostrocaudal axis using the anterior commissure to derive the associative striatum (AST; precommissural and postcommissural dorsal caudate and precommissural dorsal putamen) and the sensorimotor striatum (SMST; postcommissural putamen). Delineation of ROI templates in the right striatum are shown in figure 1. Templates were applied to dynamic images to generate the time–activity curves for striatal (ROI) and cerebellar (reference) regions. Images were sampled between 35 and 60 minutes, and BPND18 was expressed as the ratio at equilibrium of specifically bound radioligand to that of nondisplaceable radioligand in tissue [(striatal/cerebellar binding) ⫺ 1].

Statistical analysis. Data were analyzed using SPSS 15.0. Previous imaging studies have shown that age,19 sex,20 and global impairment21 may potentially modulate the relationship between dopaminergic and behavioral indices. It was thus important to explore and control for their potentially confounding effects. A linear mixed model was used to determine the effect of sex on mean [11C]RAC BP and the interaction between age and sex. Correlation coefficients (Spearman ␳) were used to describe the associations between behavioral ratings and other variables, including age, MMSE, and [11C]RAC BPND. Sex differences were investigated using the independent-samples t test, Mann–Whitney U test, and Fisher exact test. RESULTS Descriptive and neuropsychological test performance. The mean age of the sample was 78.7

years (range 66 – 89 years), and there were 11 men (48%). The majority of patients (n ⫽ 14; 61%) were in the mild stage of disease (MMSE ⬎20 out of 30), 21 (91%) were right-handed, and 14 (61%) were prescribed medication for chronic physical health problems. There were no sex differences in mean age, educational level, or global cognitive or behavioral function (table 1). 11

Dopamine (D2) receptor measures. The mean [ C]RAC BPND for the whole striatum was 2.17 (SD 0.29, 530

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range 1.74 –2.97). There was an effect of sex [F(1,97) ⫽ 27.8, p ⬍ 0.0001]: mean values for the striatum were higher in men (mean 2.26, SD 0.34) than in women (mean 2.08, SD 0.21). The sex difference was explained by an interaction between age and sex [F(1,97) ⫽ 30.4, p ⬍ 0.0001]: mean BP decreased with age in women (r ⫽ ⫺0.77, p ⫽ 0.003) but not in men (r ⫽ 0.41, p ⫽ 0.21) (figure e-1 on the Neurology® Web site at www.neurology.org). The presence or absence of vascular pathology had no effect on mean [11C]RAC BPND (p ⫽ 0.77). Neuropsychiatric symptoms. Frequencies of each of the symptom domains from the NPI are shown in table 1. Apathy was present in 16 (69%) of the sample. Delusions were present in 7 patients (30%; 5 men) and were characteristic of AD, including beliefs regarding theft or the presence of an intruder in the house. One woman exhibited hallucinations as well as delusions. Anxiety was more common in women (Fisher exact test, p ⫽ 0.01). Mean (SD) scores and ranges for the AI and NPI (delusions, apathy) are shown in table 2. Carer ratings of emotional blunting were higher in men (Mann–Whitney U, p ⫽ 0.05). Total AI scores were correlated with the NPI apathy domain (Spearman ␳ ⫽ 0.72, p ⬍ 0.0001). Delusions showed no interrelationships with other symptom domains or with the presence of vascular pathology (Mann–Whitney U, p ⫽ 0.41), and mean age, educational level, and MMSE were not correlated with scores on any of the symptom domains. Relationship between [11C]RAC BPND and neuropsychiatric symptoms. A correlation was found be-

tween delusions and [11C]RAC BP in the whole striatum (␳ ⫽ 0.54, p ⫽ 0.008) and in each subregion (SMST: ␳ ⫽ 0.61, p ⫽ 0.002; AST: ␳ ⫽ 0.48,

Correlation between neuropsychiatric symptoms and [11C]raclopride binding potential

Table 2

Correlation (Spearman ␳) with [11C]RAC BPND Subscale*

Mean (SD); range

Apathy (range 0 –12)

3.4 (3.1); 0–12

Delusions (range 0–12) AI total (range 0–36)

Striatum

SMST

⫺0.04

0.16

0.9 (1.8); 0–6

0.54‡

0.61‡

10.2 (7.9); 0–27

⫺0.004

0.12

AST

LS

⫺0.07 0.48 ⫺0.09

§

⫺0.23 0.44§ ⫺0.15

Emotional blunting (range 0–12)

2.3 (3.4); 0–12†

0.07

0.20

⫺0.04

0.03

Loss of initiative (range 0–12)

4.6 (3.5); 0–12

⫺0.11

⫺0.07

⫺0.17

⫺0.21

Loss of interest (range 0–12)

3.3 (3.5); 0–12

⫺0.16

0.03

⫺0.20

⫺0.30

*Higher scores indicate greater behavioral disturbance for all subscales. †Mean scores were higher in men than in women (Mann–Whitney U, p ⫽ 0.05). ‡p ⱕ 0.01. § p ⱕ 0.05. RAC ⫽ raclopride; BPND ⫽ binding potential; SMST ⫽ sensorimotor striatum; AST ⫽ associative striatum; LS ⫽ limbic striatum; AI ⫽ Apathy Inventory.

p ⫽ 0.02; LS: ␳ ⫽ 0.44, p ⫽ 0.03) (table 2). When patients were analyzed by group (presence/absence of delusions), mean [11C]RAC BPND was higher in patients with delusions (mean 2.4, SD 0.3) than in patients without delusions (mean 2.1, SD 0.2) (independent-samples t test: t21 ⫽ ⫺3.1, p ⫽ 0.006), and this was seen in all striatal subregions. Table 3 summarizes descriptive and BPND data in patients with and without delusions. There were no differences in mean age and global impairment, but the proportion of men in the group with delusions was higher (71.4%) than in patients without delusions (37.5%) (Fisher exact test, p ⫽ 0.19). It was possible that the higher mean [11C]RAC BPND in patients with delusions might be explained simply by the higher BPND values in men. When the analysis was restricted to men, however, differences between patients with delusions (mean 2.5, SD 0.3) and patients without delusions (mean 2.1, SD 0.3) were comparable to the total sample (p ⫽ 0.05). Mean BP values for the whole striatum in the presence or absence of delusions are shown in figure 2.

Table 3

Mean [11C]raclopride binding potential in the presence (n ⴝ 7) or absence (n ⴝ 16) of delusions

Age, mean (SD), y Men, no. (%) MMSE score, mean (SD) [11C]RAC BPND: striatum, mean (SD)

No delusions

Delusions

p Value*

78.1 (5.8)

80.1 (7.3)

0.48

6 (37.5)

5 (71.4)

None of the apathy measures was found to correlate with [11C]RAC BPND in the whole striatum or in any of the subregions (table 2). An exploratory analysis of the associations between [11C]RAC BPND and other symptom domains from the NPI revealed a relationship only with disinhibition (␳ ⫽ 0.42, p ⫽ 0.05; SMST: ␳ ⫽ 0.31, p ⫽ 0.15; AST: ␳ ⫽ 0.40, p ⫽ 0.06; LS: ␳ ⫽ 0.41, p ⫽ 0.06). However, because this analysis was not hypothesis driven, it did not survive correction for multiple comparisons. We found patients with delusions to have significantly (14%) higher striatal DA (D2/D3) receptor availability than their counterparts without delusions, a difference not explained by age, disease stage, or vascular pathology. After controlling for the significant effect of sex on BPND by excluding women from the analysis, [11C]RAC BPND was found to be 16% higher in men with delusions than in men without delusions. Contrary to our hypothesis, there was no relationship between [11C]RAC BPND and apathy. This was DISCUSSION

Figure 2

[11C]raclopride binding potential in patients with and without delusions

0.19

21.0 (2.9)

22.5 (3.0)

0.26

2.061 (0.2)

2.40 (0.3)

0.006

SMST

2.4 (0.3)

2.8 (0.3)

0.002

AST

1.9 (0.3)

2.3 (0.3)

0.01

LS

1.8 (0.2)

2.1 (0.3)

0.02

*Calculated using independent-samples t test or Fisher exact test. MMSE ⫽ Mini-Mental State Examination; RAC ⫽ raclopride; BPND ⫽ binding potential; SMST ⫽ sensorimotor striatum; AST ⫽ associative striatum; LS ⫽ limbic striatum.

Mean [11C]raclopride (RAC) binding potential (BPND) in the striatum, in the presence or absence of delusions. Neurology 72

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not explained by a low frequency or narrow range of apathy scores, but the possibility of a type II error cannot be ruled out. Our findings are somewhat at odds with recently published data in a mixed sample of patients with AD and Lewy body dementia,8 and there are several possible explanations for this. It is possible that previous findings reflect primarily an association between apathy and striatal DA transporter function in patients with Lewy body dementia, or—assuming that the association is representative of the AD population—that presynaptic neuronal integrity is a more sensitive indicator of apathy than postsynaptic receptor sites. We cannot rule out the involvement of extrastriatal DA (D2/D3) receptors in apathy in AD, because this was beyond the scope of our study. The relative importance of noradrenergic innervation of the ventral striatum—implicated in apathy in PD22—must also be considered, because alterations in the cholinergic–noradrenergic balance might similarly contribute to symptoms in AD. Our finding of a significant age ⫻ sex interaction warrants discussion, because it does not seem to have been explained by differences in the age distribution, disease stage, or presence of vascular pathology in our sample. It is unclear whether lower [11C]RAC BPND in women with AD reflects a reduction in receptor density or differences in endogenous DA levels, as has been reported in young adults.20 It is also possible that higher BPND in patients with delusions may have contributed to our findings (figure e-1), because this reduced our ability to detect an influence of age on BPND in men. This will need to be explored through further studies in patients without psychosis. Contemporary models of psychosis suggest that a variety of pathologic processes—neonatal hypoxia, hippocampal damage, cortical lesions, and cholinergic denervation—may lead to the sensitization of striatal dopaminergic neurons and the expression of positive symptoms.23-25 In support of this model are data on young adults with schizophrenia, who exhibit increased presynaptic DA synthesis capacity, increased postsynaptic receptor DA (D2/D3) receptor availability, and an exaggerated response to amphetamine, in terms of both endogenous DA release and symptom exacerbation.26 Young psychotic patients with bipolar illness exhibit similar increases in postsynaptic striatal DA (D2/D3) receptor availability,27 without evidence of the alterations in presynaptic function observed in schizophrenia,28,29 and it is thus probable that the relative importance of presynaptic and postsynaptic mechanisms may depend on the primary pathologic process. Our findings provide in vivo evidence of a direct relationship between the expression of positive symptoms and altered postsynaptic striatal DA (D2/D3) receptor function in AD. 532

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Further, the extent of the increase in [11C]RAC BPND in patients with delusions is comparable to that observed in young adults with psychosis.27,30 The functional significance of an increase in DA (D2) receptor availability is difficult to interpret, because [11C]RAC binding does not simply reflect the density of DA (D2/D3) receptors, but competes with endogenous DA for receptor sites.31 It is thus not possible to determine the extent to which differences in endogenous DA between the two groups contributed to our findings. The potential contribution of higher DA (D3) receptor availability in the group with delusions must also be considered. In vitro, a 70% increase in DA (D3) receptor density has been found in the ventral caudate of psychotic (neuroleptic naive or intolerant) compared with nonpsychotic patients with AD.32 It is not possible to distinguish between DA (D2 and D3) receptors through the use of [11C]RAC, because it binds with equal affinity to both subtypes. However, DA (D3) receptor binding accounts for only 10% of the total signal because of the lower density of expression in regions other than the ventral striatum.33 Although it remains possible that our findings represent differences in DA (D3) receptor availability in patients with delusions, the fact that the greatest percentage differences between the two groups were found in the associative striatum would tend to argue against this. It is possible that partial volume effects—as a result of greater atrophy in the striatum of patients without delusions—might have contributed to the observed differences. Although data suggest that there may be structural differences between patients with and without psychosis in relation to cortical atrophy—right frontal34 and temporal35 regions have been specifically implicated—there are no such data relating to the striatum. The presence of psychosis has considerable clinical and economic implications, generally predicting a greater speed of cognitive decline and early institutionalization.36 It has been suggested that psychosis in AD may represent not one but several different phenotypes, each with genetically, biologically, and neurochemically distinct markers.37,38 Attempts to further categorize psychotic symptoms through the use of factor analytic approaches have identified two broad subtypes: a paranoid subtype (defined by the presence of persecutory delusions) and a “misidentification” subtype (defined by misidentification phenomena and hallucinations).39 Whether increased striatal DA (D2) receptor availability primarily reflects the paranoid subtype is a question that will need to be answered through future studies. Perhaps most relevant clinically is the fact that we found measurable differences between patients with and without delusions who were at an early stage in

the disease process and in whom the presence of delusional beliefs was not associated with other behavioral symptoms, such as agitation or aggression. This would indicate that increased DA (D2/D3) receptor availability—and possibly other indices of striatal dopaminergic function—might act as markers of psychosis proneness in AD. Future studies should similarly aim to better characterize psychosis in AD in terms of presynaptic and postsynaptic dopaminergic indices, to identify those most vulnerable to its development. AUTHOR CONTRIBUTIONS All statistical analyses were performed by S.R.

ACKNOWLEDGMENT The authors thank the staff at the Croydon Memory Service, the team of radiographers at the MRC Cyclotron Unit, Steve Nobes for his help in transporting participants to scanning sessions, and all those who kindly gave up their time to take part in the study.

Received July 28, 2008. Accepted in final form November 10, 2008. REFERENCES 1. Perry E, Court J, Goodchild R, et al. Clinical neurochemistry: developments in dementia research based on brain bank material. J Neural Transm 1998;105:915–933. 2. Cummings JL, Back C. The cholinergic hypothesis of neuropsychiatric symptoms in Alzheimer’s disease. Am J Geriatr Psychiatry 1998;6:S64–S78. 3. White KE, Cummings JL. Schizophrenia and Alzheimer’s disease: clinical and pathophysiologic analogies. Compr Psychiatry 1996;37:188–195. 4. Levy R, Dubois B. Apathy and the functional anatomy of the prefrontal cortex-basal ganglia circuits. Cereb Cortex 2006;16:916–928. 5. Cummings JL, Kaufer D. Neuropsychiatric aspects of Alzheimer’s disease: the cholinergic hypothesis revisited. Neurology 1996;47:876–883. 6. Meguro K, Yamaguchi S, Itoh M, Fujiwara T, Yamadori A. Striatal dopamine metabolism correlated with frontotemporal glucose utilization in Alzheimer’s disease: a double-tracer PET study. Neurology 1997;49:941–945. 7. Tanaka Y, Meguro K, Yamaguchi S, et al. Decreased striatal D2 receptor density associated with severe behavioral abnormality in Alzheimer’s disease. Ann Nucl Med 2003; 17:567–573. 8. David R, Koulibaly M, Benoit M, et al. Striatal dopamine transporter levels correlate with apathy in neurodegenerative diseases: a SPECT study with partial volume effect correction. Clin Neurol Neurosurg 2008;110:19–24. 9. McKhann G, Drachman D, Folstein M, Katzman R, Price D, Stadlan EM. Clinical diagnosis of Alzheimer’s disease: report of the NINCDS-ADRDA Work Group under the auspices of Department of Health and Human Services Task Force on Alzheimer’s Disease. Neurology 1984;34: 939–944. 10. Folstein MF, Folstein SE, McHugh PR. “Mini-Mental State”: a practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res 1975;12:189– 198. 11. Huppert FA, Brayne C, Gill C, Paykel ES, Beardsall L. CAMCOG—a concise neuropsychological test to assist

dementia diagnosis: socio-demographic determinants in an elderly population sample. Br J Clin Psychol 1995;34(pt 4):529–541. 12. Cummings JL, Mega M, Gray K, Rosenberg-Thompson S, Carusi DA, Gornbein J. The Neuropsychiatric Inventory: comprehensive assessment of psychopathology in dementia. Neurology 1994;44:2308–2314. 13. Robert PH, Clairet S, Benoit M, et al. The apathy inventory: assessment of apathy and awareness in Alzheimer’s disease, Parkinson’s disease and mild cognitive impairment. Int J Geriatr Psychiatry 2002;17:1099–1105. 14. Watabe H, Endres CJ, Breier A, Schmall B, Eckelman WC, Carson RE. Measurement of dopamine release with continuous infusion of [11C]raclopride: optimization and signal-to-noise considerations. J Nucl Med 2000;41:522–530. 15. Carson RE, Breier A, de Bartolomeis A, et al. Quantification of amphetamine-induced changes in [11C]raclopride binding with continuous infusion. J Cereb Blood Flow Metab 1997;17:437–447. 16. Montgomery AJ, Thielemans K, Mehta MA, Turkheimer F, Mustafovic S, Grasby PM. Correction of head movement on PET studies: comparison of methods. J Nucl Med 2006;47:1936–1944. 17. Martinez D, Slifstein M, Broft A, et al. Imaging human mesolimbic dopamine transmission with positron emission tomography, part II: amphetamine-induced dopamine release in the functional subdivisions of the striatum. J Cereb Blood Flow Metab 2003;23:285–300. 18. Innis RB, Cunningham VJ, Delforge J, et al. Consensus nomenclature for in vivo imaging of reversibly binding radioligands. J Cereb Blood Flow Metab 2007;27:1533–1539. 19. Backman L, Nyberg L, Lindenberger U, Li SC, Farde L. The correlative triad among aging, dopamine, and cognition: current status and future prospects. Neurosci Biobehav Rev 2006;30:791–807. 20. Pohjalainen T, Rinne JO, Nagren K, Syvalahti E, Hietala J. Sex differences in the striatal dopamine D2 receptor binding characteristics in vivo. Am J Psychiatry 1998;155: 768–773. 21. Rodriguez G, Morbelli S, Brugnolo A, et al. Global cognitive impairment should be taken into account in SPECTneuropsychology correlations: the example of verbal memory in very mild Alzheimer’s disease. Eur J Nucl Med Mol Imaging 2005;32:1186–1192. 22. Remy P, Doder M, Lees A, Turjanski N, Brooks D. Depression in Parkinson’s disease: loss of dopamine and noradrenaline innervation in the limbic system. Brain 2005; 128:1314–1322. 23. Laruelle M, Abi-Dargham A, Gil R, Kegeles L, Innis R. Increased dopamine transmission in schizophrenia: relationship to illness phases. Biol Psychiatry 1999;46:56–72. 24. Seeman P, Weinshenker D, Quirion R, et al. Dopamine supersensitivity correlates with D2High states, implying many paths to psychosis. Proc Natl Acad Sci USA 2005; 102:3513–3518. 25. Mattsson A, Olson L, Svensson TH, Schilstrom B. Cortical cholinergic deficiency enhances amphetamine-induced dopamine release in the accumbens but not striatum. Exp Neurol 2007;208:73–79. 26. Breier A, Su TP, Saunders R, et al. Schizophrenia is associated with elevated amphetamine-induced synaptic dopamine concentrations: evidence from a novel positron emission tomography method. Proc Natl Acad Sci USA 1997;94:2569–2574. Neurology 72

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Pearlson GD, Wong DF, Tune LE, et al. In vivo D2 dopamine receptor density in psychotic and nonpsychotic patients with bipolar disorder. Arch Gen Psychiatry 1995;52:471–477. 28. Anand A, Verhoeff P, Seneca N, et al. Brain SPECT imaging of amphetamine-induced dopamine release in euthymic bipolar disorder patients. Am J Psychiatry 2000;157: 1108–1114. 29. Yatham LN, Liddle PF, Shiah IS, et al. PET study of [(18)F]6-fluoro-L-dopa uptake in neuroleptic- and moodstabilizer-naive first-episode nonpsychotic mania: effects of treatment with divalproex sodium. Am J Psychiatry 2002; 159:768–774. 30. Laruelle M. Imaging dopamine transmission in schizophrenia: a review and meta-analysis. Q J Nucl Med 1998; 42:211–221. 31. Laruelle M. Imaging synaptic neurotransmission with in vivo binding competition techniques: a critical review. J Cereb Blood Flow Metab 2000;20:423–451. 32. Sweet RA, Hamilton RL, Healy MT, et al. Alterations of striatal dopamine receptor binding in Alzheimer disease are associated with Lewy body pathology and antemortem psychosis. Arch Neurol 2001;58:466–472. 33. Gurevich EV, Joyce JN. Distribution of dopamine D3 receptor expressing neurons in the human forebrain: comparison with

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D2 receptor expressing neurons. Neuropsychopharmacology 1999;20:60–80. Forstl H, Besthorn C, Burns A, Geiger-Kabisch C, Levy R, Sattel A. Delusional misidentification in Alzheimer’s disease: a summary of clinical and biological aspects. Psychopathology 1994;27:194–199. Geroldi C, Akkawi NM, Galluzzi S, et al. Temporal lobe asymmetry in patients with Alzheimer’s disease with delusions. J Neurol Neurosurg Psychiatry 2000;69:187–191. Ropacki SA, Jeste DV. Epidemiology of and risk factors for psychosis of Alzheimer’s disease: a review of 55 studies published from 1990 to 2003. Am J Psychiatry 2005;162: 2022–2030. Sweet RA, Nimgaonkar VL, Devlin B, Jeste DV. Psychotic symptoms in Alzheimer disease: evidence for a distinct phenotype. Mol Psychiatry 2003;8:383–392. Borroni B, Grassi M, Agosti C, et al. Cumulative effect of COMT and 5-HTTLPR polymorphisms and their interaction with disease severity and comorbidities on the risk of psychosis in Alzheimer disease. Am J Geriatr Psychiatry 2006;14:343–351. Cook SE, Miyahara S, Bacanu SA, et al. Psychotic symptoms in Alzheimer disease: evidence for subtypes. Am J Geriatr Psychiatry 2003;11:406–413.

New Categories of Resident & Fellow Section Clinical Reasoning: Case presentations to aid in developing clinical reasoning skills. Right Brain: Neurology and the medical humanities — history, literature, and arts. Child Neurology: Patient case with detailed discussion about topic of focus. Pearls and Oy-sters: Clinical insights (pearls) and advice for avoiding mistakes (oysters). International: Educational exchanges, experiences in low and middle income countries. Emerging Subspecialities: History of fields such as Pain Medicine and Headache. Continue to submit articles about education research and educational topics, training videos, and teaching NeuroImages!

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Results of the Avonex Combination Trial (ACT) in relapsing-remitting MS

J.A. Cohen, MD P.B. Imrey, PhD P.A. Calabresi, MD K.R. Edwards, MD T. Eickenhorst, MD, PhD W.L. Felton III, MD E. Fisher, PhD R.J. Fox, MD A.D. Goodman, MD C. Hara-Cleaver, RN, MSN G.J. Hutton, MD B.F. Mandell, MD, PhD T.F. Scott, MD H. Zhang, PhD C. Apperson-Hansen, MStat G.J. Beck, PhD P.L. Houghtaling, MS M.T. Karafa, PhD M. Stadtler For the ACT Investigators*

Address correspondence and reprint requests to Dr. Jeffrey A. Cohen, Mellen Center U-10, Cleveland Clinic Foundation, 9500 Euclid Avenue, Cleveland, OH 44195 [email protected]

ABSTRACT

Objective: To assess the safety, tolerability, and efficacy of interferon beta-1a (IFN␤-1a) combined with methotrexate (MTX), IV methylprednisolone (IVMP), or both in patients with relapsingremitting multiple sclerosis (RRMS) with continued disease activity on IFN␤-1a monotherapy.

Methods: Eligibility criteria included RRMS, Expanded Disability Status Scale score 0 –5.5, and ⱖ1 relapse or gadolinium-enhancing MRI lesion in the prior year on IFN␤-1a monotherapy. Participants continued weekly IFN␤-1a 30 ␮g IM and were randomized in a 2 ⫻ 2 factorial design to adjunctive weekly placebo or MTX 20 mg PO, with or without bimonthly IVMP 1,000 mg/day for 3 days. The primary endpoint was new or enlarged T2 lesion number at month 12 vs baseline. The study was industry-supported, collaboratively designed, and governed by an investigator Steering Committee with independent Advisory and Data Safety Monitoring committees. Study operations, MRI analyses, and aggregated data were managed by an academic coordinating center. Results: The 313 participants had clinical and MRI characteristics typical of RRMS. Combinations of IFN␤-1a with MTX or IVMP were generally safe and well tolerated. Although trends suggesting modest benefit were seen for some outcomes for IVMP, the results did not demonstrate significant benefit for either adjunctive therapy. The data suggested IVMP reduced anti-IFN␤ neutralizing antibody titers.

Conclusions: This trial did not demonstrate benefit of adding low-dose oral methotrexate or every other month IV methylprednisolone to interferon beta-1a in relapsing-remitting multiple sclerosis. Neurology® 2009;72:535–541 GLOSSARY ACT ⫽ Avonex Combination Trial; BPF ⫽ brain parenchymal fraction; DEXA ⫽ dual energy X-ray absorptiometry; EDSS ⫽ Expanded Disability Status Scale; GdE ⫽ gadolinium-enhancing; IFN␤-1a ⫽ interferon beta-1a; IVMP ⫽ IV methylprednisolone; MSFC ⫽ MS Functional Composite; MTX ⫽ methotrexate; N/E ⫽ new or enlarged; NAb ⫽ neutralizing antibody; OR ⫽ odds ratio; RRMS ⫽ relapsing-remitting multiple sclerosis; SENTINEL ⫽ Safety and Efficacy of Natalizumab in Combination with Interferon ␤-1a in Patients with Relapsing-Remitting MS.

Several lines of evidence support the rationale for combination therapy for patients with relapsing-remitting multiple sclerosis (RRMS) with continued disease activity despite diseasemodifying monotherapy. MS pathogenesis has numerous potential mechanisms, and may be heterogeneous across patients and within patients over time. Partially effective agents could work additively or synergistically. Agents in combination might allow lower dosing and side effects. Combination therapies are useful for other immune-mediated diseases, hypertension, infections, and cancers. The Avonex Combination Trial (ACT) assessed the safety, tolerability, and efficacy of interferon beta-1a (IFN␤-1a) combined with low-dose oral methotrexate (MTX), IV methylpred-

Supplemental data at www.neurology.org *The ACT study sites and committee members are listed in appendix e-1 on the Neurology® Web site at www.neurology.org. From the Cleveland Clinic (J.A.C., P.B.I., E.F., R.J.F., C.H.-C., B.F.M., G.J.B., P.L.H., M.T.K., M.S.), OH; Johns Hopkins University (P.A.C.), Baltimore, MD; MS Center of Southern Vermont (K.R.E.), Bennington; Biogen Idec (T.E., H.Z.), Cambridge, MA; Virginia Commonwealth University Medical Center (W.L.F.), Richmond; University of Rochester (A.D.G.), NY; Baylor College of Medicine (G.J.H.), Houston, TX; Drexel College of Medicine (T.F.S.), Pittsburgh, PA; and Case Western Reserve University (C.A.-H.), Cleveland, OH. Biogen Idec, Inc. funded this study. Pfizer, Inc. provided methylprednisolone. Preliminary results presented at the annual meeting of the American Academy of Neurology, Boston, MA, May 2007. Disclosure: Author disclosures are provided at the end of the article. Copyright © 2009 by AAN Enterprises, Inc.

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nisolone (IVMP), or both in participants with active RRMS on IFN␤-1a alone. Although clinical experience and preliminary studies supported the safety and benefit of these combinations, additional data were needed to justify widespread use. METHODS ClinicalTrials.gov identifier: NCT00112034.

Study design. ACT was a randomized, multicenter, investigatorrun 2 ⫻ 2 factorial clinical trial. The rationale and design were reported previously.1 Seventy-two centers participated (appendix e-1 on the Neurology® Web site at www.neurology.org), including 28 university clinics, 7 multispecialty groups, and 37 general neurology practices. A treating neurologist and treating nurse supervised medical management. An examining neurologist performed a standardized neurologic examination, calculated Functional System and Expanded Disability Status Scale (EDSS)2,3 scores at scheduled and unscheduled visits, and confirmed protocol-defined relapses. An examining technician performed the MS Functional Composite (MSFC)4 at scheduled and unscheduled visits. Both were trained and certified at prestudy investigators’ meetings. Participants. Protocol and consent documents were approved by local institutional review boards. Participants provided written informed consent before any study-related procedures, and were reconsented after major protocol revisions. Key inclusion criteria included age 18 –55, MS diagnosis,5 RR course,6 EDSS 0.0 –5.5,2,3 IFN␤-1a treatment for ⱖ6 months, active disease in prior 12 months (ⱖ1 relapse or ⱖ1 gadolinium-enhancing [GdE] cranial/ spinal MRI lesion ⱖ6 months after initiating IFN␤-1a), MRI demonstrating T2-hyperintense lesions (T2 lesions) consistent with MS, and ability to perform the MSFC.4 Key exclusion criteria included medical conditions or laboratory abnormalities contraindicating study medications, relapse within 60 days, inability to undergo MRI with Gd, MS treatments (specified washouts), and prior anti-IFN␤ neutralizing antibody (NAb) titer ⱖ1:5.

Treatment. Eligible participants continued weekly IFN␤-1a 30 ␮g IM and were randomized with equal probabilities to the following groups: group 1 weekly oral placebo, group 2 weekly oral MTX 20 mg, group 3 weekly oral placebo and bimonthly IVMP 1,000 mg/day 3 consecutive days, and group 4 weekly MTX and bimonthly IVMP. All participants received daily oral folic acid 1 mg. MTX/placebo was uptitrated from 10 to 20 mg over 2 months. The dose could be divided, reduced, or temporarily discontinued according to a prespecified algorithm for laboratory abnormalities or side effects. Participants, study personnel, and steering committee including study statistician were blinded to MTX/placebo assignment. Clinical and MRI evaluators and study statistician were blinded to IVMP assignment. Outcome measures. The primary endpoint was new or enlarged (N/E) T2 lesion number at month 12 vs baseline. Secondary outcomes were GdE lesion number, relapse rate, MSFC change, and brain parenchymal fraction (BPF) percent change. Analyses of T2- and T1-hypointense (T1) lesion volumes, time to first relapse, relapse-free proportion, and EDSS change were preplanned. Participants were classified on a composite outcome defined as any combination of EDSS worsening (increase by ⱖ1.5 from 0 or ⱖ1.0 from ⱖ1.0), relapse within 365 days, or GdE or N/E T2 lesion on follow-up MRI. 536

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Screening, baseline, and follow-up assessments. Follow-up was 12 months postrandomization. Screening visit included vital signs, physical examination, EDSS, three MSFC practice sessions, blood chemistry, complete blood count, hepatitis screen, HIV antibody screen, serum pregnancy test, urinalysis, chest X-ray, and brain MRI. Baseline visit, within 30 days, included vital signs, EDSS, MSFC, blood chemistry, complete blood count, urinalysis, and anti-IFN␤ NAb. Participants were randomized by interactive voice response system. Participants randomized to IVMP underwent dual energy X-ray absorptiometry (DEXA) scanning of nondominant or bilateral total hip and femoral neck and anteroposterior lumbar spine before treatment. Safety and laboratory evaluations were scheduled at months 1, 2, 3, 4, 6, 8, 10, 12, and 1 month after completion of treatment, or at early termination. EDSS, MSFC, and anti-IFN␤ NAb were repeated at months 6 and 12 or at early termination. Cranial MRI and DEXA scan were repeated at month 12 (2 months after the last scheduled IVMP course) or early termination. On-study relapse was defined as new/recurrent neurologic symptoms developing ⱖ30 days after onset of a previous confirmed relapse; evolution ⬍3 months; duration ⱖ24 hours; with corresponding change on examination, and without fever or intercurrent illness. An unscheduled visit was conducted within 72 hours of site notification. Relapses confirmed by the examining neurologist were treated, if needed, with IVMP 1,000 mg/day for 3–5 days without oral taper. MRI acquisition and analyses. Magnetic resonance images were acquired at 1.5 T per standardized protocol,1 and shipped electronically to the MRI Analysis Center. Before enrolling participants, sites submitted an MS patient test scan for approval of scanning and data transfer techniques. Scans underwent subvoxel registration to the baseline scan, and N/E T2 lesion number, T2 and T1 lesion volumes, GdE lesion number and volume, and BPF were analyzed using automated software.1,7,8 Enlarged T2 lesions had volume increase ⱖ20%. Anti-IFN␤ NAb. Serum anti-IFN␤ NAb were measured at Biogen Idec using a two-step assay.9 Samples with titer ⱖ20 were classified as positive. Study governance and management. The steering committee of investigators plus representatives of Cleveland Clinic MS Academic Coordinating Center and sponsor (appendix e-1) held monthly teleconferences for protocol development, study oversight, analysis plan approval, and results interpretation. An independent data safety monitoring committee met semiannually to review trial conduct and unblinded interim safety data. The data safety monitoring committee provided input concerning study design, analysis, and interpretation. An advisory committee provided additional clinical, imaging, and statistical input. MS academic coordinating center responsibilities included site management, administrative support of study committees, MRI analysis center, medication and visit tracking, methylprednisolone distribution, medication and adverse event coding, data management, and statistical analyses.1 Statistical considerations. ACT used permuted-blocks randomization with blocks of four and eight, start based on anticipated site enrollment, and restrictions limiting intrasite confounding. Power against the primary endpoint was estimated using month 12–24 data from 260 participants (32.4% of 802) at both doses in the European Study Group on Interferonbeta-1a in MS Dose Comparison Study (IFN␤-1a dosecomparison study),10 whose baseline–month 18 disease activity mimicked ACT entry criteria. Power for either treatment assum-

ing inefficacy of the other was estimated at 89% against a beneficial cumulative odds ratio (OR) ⫽ 0.45 in a proportional odds model, and 81% against OR ⫽ 0.50. Power estimates declined to 81% and 72% with the other therapy assumed highly effective (OR ⫽ 0.20). Re-estimates based on ACT data suggest these values exceeded achieved power by an absolute 10%. MRI lesions were analyzed by proportional odds models11 for counts and rank-based nonparametric analysis of variance or covariance12,13 for volume changes. Relapse rates were analyzed by negative binomial regression,14 time to first relapse by Cox proportional hazards regression, relapse-free proportions by logistic regression, and individual annualized relapse rates by proportional odds model for five categories. A proportional odds model was fit to trichotomized EDSS change: worsening (increase by ⱖ1.5 from 0 or ⱖ1.0 from ⱖ1.0), improved (decrease ⱖ1.0), or stable. MSFC change was evaluated by factorial analysis of variance, and relative BPF change by Gaussian generalized linear model with log link.15 A composite freedom-from-MS activity dichotomy was analyzed by logistic regression. Categorical data and rank analyses were used for skewed outcomes to avoid heavy influences by participants exhibiting unusually large values on analyses of means or totals. Most variables were screened for MTX ⫻ IVMP interactions using the interaction test for a factorial model of indicated type, at prespecified 1% level. Lesion volume variables were screened for interaction using stratified exact tests on residuals from main effects models. Absent significant interaction, treatment effects were tested at prespecified 5% level in a main effects model. Analyses were adjusted for prespecified baseline covariates selected blind to ACT outcome data based on analyses of the IFN␤-1a dose-comparison study10 and the placebo group of Safety and Efficacy of Natalizumab in Combination with Interferon ␤-1a in Patients with RelapsingRemitting MS (SENTINEL).16 Reported analyses followed strict intention-to-treat. N/E T2 lesion and relapse rate analyses used multiple imputation by predictive mean matching for participants not undergoing month 12 MRI scans, and to project data forward for early dropouts. Imputations used treatment-group-specific models, including prespecified covariates, time-dependent variables identifying cessation of MTX or IVMP, and, for relapses, on-study relapses prior to withdrawal and 6-month MSFC if available. For other outcomes except MSFC, missing data were imputed by last observation carried forward or, when no follow-up observation was obtained, averaging the four treatment group means of study completers. MSFC was calculated by averaging Timed 25-Foot Walk, Nine-Hole Peg Test, and 3-second Paced Auditory Serial Addition Test Z-scores, using pooled baseline data as reference population.17 Missing MSFC values were imputed using standard conventions.18 Adverse events were coded using MedDRA (version 6.1) preferred terms and systems, and analyzed using 2 ⫻ 2 factorial and main effects logistic regression models, with exact tests and mid-p values for events with cell expected values ⬍4. Generalized additive modeling19 was used to study vital sign trends. Treatment effects on anti-IFN␤ NAb titer were tested by exact stratified Wilcoxon test.20 Appendix e-2 provides additional statistical details. RESULTS Enrollment and follow-up. ACT initiated enrollment in June 2003 with a 900-participant target. Because of slow enrollment, the protocol was revised in January 2005, reducing target enrollment to 300 –350, changing the primary endpoints from relapse rate for MTX and BPF change for IVMP to N/E T2 lesions for both, and shortening follow-up

from 24 to 12 months. The protocol revision process was detailed previously.1 Enrollment closed in May 2005 with 313 participants. The figure summarizes follow-up. Discontinuation numbers, timing, and reasons were comparable across treatments (table e-1). Baseline characteristics. Baseline demographic, clinical, and MRI characteristics were typical of RRMS and generally comparable across groups (table e-2). Participants had relatively mild neurologic impairment. The majority (86.5%) qualified for enrollment by clinical relapse in the preceding year. Most participants qualifying by MRI only had brain activity. Despite recently active disease and significant MRI lesion burden, only 22.4% had baseline GdE lesions. Efficacy results. Table 1 shows the distribution by

treatment of the primary endpoint, N/E T2 lesion number. Sixty-six to eighty percent of patients had ⱕ1 lesion for all groups. Although the group 4 mean was half that of group 1, this was largely due to the distribution across treatments of 7 participants (2.2%) with 12–22 lesions, including 5 controls. Without these participants, the control group mean was the lowest of the four treatment groups. Overall, 216/ 442 (49.0%) of the N/E lesions were enlarged and 58/ 442 (13.1%) were also GdE. Conversely, 58/77 (75.3%) of GdE lesions at month 12 were N/E. Table 2 and table e-3 summarize data on secondary outcomes. Table 3 and table e-4 report main effects of both therapies for study outcomes. No MTX ⫻ IVMP interactions were significant. Main effects were small to moderate. Specifically, for lesion volume measures, the mean rank differences of 1.6 to 10.6 were small relative to the possible maximum with strong treatment effect of 78.25. Modest trends favoring MTX were observed for several outcomes; no effect approached significance. Trends with IVMP were favorable for the primary outcome of N/E T2 lesions (OR ⫽ 0.74), the secondary outcomes GdE lesions (OR ⫽ 0.69) and relapse rate (RR ⫽ 0.70), other relapse-derived measures, EDSS change (OR ⫽ 0.76), MSFC change (difference in means ⫽ 0.02), the composite disease activity outcome (OR ⫽ 0.78), and T2 lesion volumes (for which trends were marginally significant: p ⫽ 0.07 for absolute and p ⫽ 0.04 for relative changes). However, p values for the primary and four secondary outcomes were 0.12 or higher. Trends with GdE and T1 lesion volumes were negligible, and BPF showed an unfavorable trend (change ratio ⫽ 1.08). Safety and tolerability. Combination regimens were

generally well-tolerated. While participants remained on treatment, 97.1% of IFN␤-1a, 89.6% of MTX, and 94.2% of IVMP doses were full doses. There were 3,413 total AEs including all follow-up (a minorNeurology 72

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Figure

Study summary

*Two participants discontinued interferon beta-1a (IFN␤-1a) and placebo. †Three participants discontinued IFN␤-1a and methotrexate (MTX). ‡One participant discontinued IFN␤-1a and placebo, and two participants discontinued placebo and IV methylprednisolone (IVMP). §Two participants discontinued IFN␤-1a and MTX.

ity of participants were followed ⬎1 year under the original 24-month protocol). There were no malignant neoplasms, opportunistic infections, or unanticipated toxicities (tables e-5 and e-6). Forty-one serious adverse events occurred in 36 participants, including one sudden death assessed as probably due to myocardial infarction, and considered unrelated to study medications by the investigator. No autopsy was performed. BradycarTable 1

Frequency distribution of the primary endpoint: new or enlarged T2-hyperintense lesions

No. of new or enlarged T2 lesions

Group 1: Placebo (n ⴝ 70)

Group 2: MTX (n ⴝ 76)

Group 3: Placebo ⴙ IVMP (n ⴝ 66)

Group 4: MTX ⴙ IVMP (n ⴝ 74)

0

57.1

43.4

56.1

60.8

1

20.0

22.4

16.7

18.9

2

2.9

9.2

4.5

10.8

3

7.1

9.2

6.1

2.7

4

2.9

5.3

4.5

2.7

1.5

—

5

1.4

6

—

7

—

8

—

2.6

9

1.4

2.6

—

12ⴙ

7.1

1.3

1.5

Maximum Mean

20 1.8

— 3.9

4.5

—

22

3.0

—

1.5

—

16

1.9

1.5

MTX ⫽ methotrexate; IVMP ⫽ IV methylprednisolone. 538

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1.4 — 9 0.9

dia in group 2 and spontaneous abortion in group 4 were assessed as related to MTX, which was permanently stopped. Pneumonia in group 4 was assessed as likely related to oral study medication and IVMP, neither of which were stopped. The only significant time trend in vital signs was respiratory rate decline (approximately 1 breath per minute) over 1 year in Group 3 (p ⫽ 0.0002), with a nonsignificant trend in group 4. There were moderate overall decreases in hemoglobin and hematocrit and increased mean corpuscular volume with MTX. No clinically significant effects of IVMP on hematologic parameters were seen. Clinically significant effects of MTX on alanine transaminase and aspartate transaminase were infrequent and generally mild. Mean transaminase levels increased modestly over time in IVMP-treated participants, with very few clinically significant abnormal values. There were no clinically important treatment differences in frequencies of urinalysis abnormalities. DEXA results will be reported separately, but this IVMP regimen appeared not to accelerate bone mineral density loss. Anti-IFN␤ neutralizing antibodies. Overall, 38/808

(4.7%) of assays in 18/313 (2.6%) of participants were positive. The data suggested IVMP inhibited serum anti-IFN␤ NAb at months 6 (p ⫽ 0.015) and 12 (p ⫽ 0.018) (table 4). DISCUSSION The safety of ACT combination therapies was consistent with known effects of MTX

Table 2

Descriptive statistics of secondary outcomes by treatment group Group 1: Placebo

Group 2: MTX

Group 3: Placebo ⴙ IVMP

Group 4: MTX ⴙ IVMP

68 (87.2)

72 (86.7)

66 (89.2)

72 (92.3)

1–2

7 (9.0)

10 (12.0)

6 (8.1)

5 (6.4)

3–4

3 (3.8)

0 (0.0)

1 (1.4)

1 (1.3)

>5

0 (0.0)

1 (1.2)

1 (1.4)

0 (0.0)

Mean

0.27

0.23

0.36

0.10

0.53

0.40

0.40

0.020

0.148

0.37

0.45

Endpoint GdE lesion no., n (%) 0*

Relapses per patient year, mean† MSFC absolute change, mean‡

⫺0.084

BPF relative decline, mean %§

0.56

0.28 ⫺0.030 0.54

*Using last observation carried forward data. Based on 70, 76, 65, and 74 patients in the respective treatment groups with GdE data from follow-up scans. †Adjudicated relapses within 1-year follow-up, based on all follow-up of all patients. ‡Negative values indicate decline and positive values indicate improved function. Based on 74, 79, 70, and 74 patients in the respective treatment groups with follow-up MSFC. § Using last observation carried forward data. Based on 70, 76, 66, and 74 patients in the respective treatment groups with BPF data from follow-up scans. MTX ⫽ methotrexate; IVMP ⫽ IV methylprednisolone; GdE ⫽ gadolinium-enhancing; MSFC ⫽ Multiple Sclerosis Functional Composite; BPF ⫽ brain parenchymal fraction.

and IVMP and raised no new concerns when combined with IFN␤-1a. Trends favorable to IVMP were seen for several clinical and MRI endpoints, but these were not significant. The data did not suggest benefit of MTX combined with IFN␤-1a. Previous publications discussed the rationale for combination therapy in MS, selection of MTX and IVMP as adjunctive therapies, and the dose regimens.1,21 Numerous trials of MS combination thera-

Table 3

pies have been conducted, almost all pilot studies.21 SENTINEL, the largest combination therapy trial to date, demonstrated the tolerability and efficacy of natalizumab combined with IM IFN␤-1a compared to IM IFN␤-1a.16 The design precluded comparison of the combination to natalizumab, and illustrated the potential for unanticipated toxicity (progressive multifocal leukoencephalopathy).22,23 Despite a seemingly strong rationale for combination MS ther-

Summary of efficacy main effects for primary and secondary endpoints Adjuvant treatment MTX

Endpoints

Effect measure

Adjusted effect size

Odds ratio

0.98

IVMP Wald p value

Adjusted effect size

0.63–1.54

0.93

0.74

95% CI

95% CI

Wald p value

Primary N/E T2 lesions*

0.47–1.15

0.18

Secondary GdE lesion no.†

Odds ratio

0.69

0.33–1.44

0.32

0.69

0.33–1.45

0.33

Relapse rate‡

Rate ratio

0.77

0.51–1.15

0.20

0.71

0.46–1.09

0.12

MSFC change§

Difference in means

0.03

⫺0.07–0.13

0.52

0.02

⫺0.08–0.12

0.65

BPF relative change¶

Change ratio

0.88

0.65–1.19

0.41

1.08

0.80–1.46

0.60

*Main effects ordinal regression (proportional cumulative odds) covariance model of categories (0, [1], 5⫹), with prespecified adjustment for baseline age and GdE lesion number (0, [1], 6⫹). †Main effects ordinal regression (proportional cumulative odds) covariance model of categories (0, 1, 2⫹), with prespecified adjustment for baseline GdE lesion number (0, [1], 6⫹). ‡Main effects negative binomial analysis of covariance, with prespecified adjustment for baseline age, GdE lesion number (0, [1], 6⫹), relapses in the prior 3 years, and MSFC. § Main effects analysis of variance model. ¶ Main effects Gaussian generalized linear covariance model with log link function and prespecified adjustment for baseline GdE lesion number (0, [1], 6⫹). MTX ⫽ methotrexate; IVMP ⫽ IV methylprednisolone; CI ⫽ confidence interval; N/E ⫽ new or enlarged; GdE ⫽ gadoliniumenhancing; MSFC ⫽ Multiple Sclerosis Functional Composite; BPF ⫽ brain parenchymal fraction. Neurology 72

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Table 4

Changes in serum anti-interferon beta-1a neutralizing antibody titer from baseline to month 6 and month 12 Group 1: Placebo

Group 3: Placebo ⴙ IVMP

Group 2: MTX

Group 4: MTX ⴙ IVMP

Baseline to:

1

↔

2

1

↔

2

1

↔

2

1

↔

2

Month 6

4

0

1

1

1

2

0

0

2

0

0

4

Month 12

2

0

1

3

0

1

0

0

2

0

0

4

MTX ⫽ methotrexate; IVMP ⫽ IV methylprednisolone; 1 ⫽ increase in titer; ↔ ⫽ no change in titer; 2 ⫽ decrease in titer.

apy, no large-scale study has yet definitively shown an advantage over both platform and adjunctive agents. ACT had several noteworthy features in design, conduct, and analysis.1 Most important, although ACT was a large-scale trial funded by a pharmaceutical company, scientific governance and study management were investigator-run. It was hoped this would foster innovation in design and conduct, promote analyses of interest to the field, and contribute to acceptance of results. In general, administrative aspects of ACT functioned well. Also of interest was the 2 ⫻ 2 factorial design, the advantages of which are illustrated by comparison to alternative two- and three-group designs, assuming 300 total available participants. The factorial approach allows evaluation of each adjunct by comparing 150 patients allocated to it with all remaining patients as controls. Moreover, the MTX ⫹ IVMP group provides data on use of both adjuncts. Separate two-group studies with roughly 75 participants per group would have lower statistical power and provide no data on combined adjunct use. A threegroup study allows comparison of placebo vs MTX vs IVMP adjunct therapies in groups of about 100 patients each, but again joint use is not tested. The 2 ⫻ 2 factorial design retains much of the flexibility of separate two-group designs, for example allowing distinct endpoints with different levels of masking for the two agents, as in the original ACT design. This is advantageous when distinct mechanisms of action targeting different disease manifestations are hypothesized. The sample size advantage of the factorial approach, though, assumes that a second adjunct leaves the statistical effect of the first unchanged. ACT data were consistent with this assumption, showing no significant MTX ⫻ IVMP interactions. ACT had several shortcomings. First, although the MTX comparison was placebo-controlled, IVMP was compared to no treatment. IV placebo was considered, but ethical and practical issues, including difficulty of blinding due to infusion-related adverse effects, were felt to outweigh advantages. To minimize potential bias, clinical and MRI evaluators (including the evaluating neurologist who adjudicated 540

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potential relapses) and the study statistician were blinded to IVMP assignment during the trial. Second, largely due to financial constraints, DEXA scans were performed only on participants receiving bimonthly IVMP, precluding isolating IVMP’s bone mineral density effects from those of MS or other causes. Third, sample size was limited by unexpectedly slow enrollment. The factorial approach requires participants accept randomization to both test agents. Some potential participants who might have enrolled in an MTX trial were deterred by potential randomization to IVMP.1 Finally, event rates in ACT were lower than previous studies. For example, mean N/E T2 lesions were 1.8 in ACT group 1 (IFN␤-1a alone) vs 2.5 in the IFN␤-1a dosecomparison study10 30 ␮g group at month 24 vs 12 and 2.4 in the SENTINEL16 IFN␤-1a alone group at year 1 vs baseline. In consequence, achieved power was modestly reduced, but remained substantial against effects half or less those of natalizumab. ACT outcomes, particularly MRI measures, were highly skewed. This renders analyses based on average lesion counts or volumes vulnerable to distortion by uncommon very high observations. Hence, ordinal (rank-based) statistical methods were chosen for most analyses, including for the primary endpoint. The nonsignificant benefit with IVMP observed largely in the upper tail of N/E T2 lesions may represent a substantial treatment effect limited to a small subpopulation, a widespread but small benefit missed by chance, or a chance effect of randomization. ACT data do not distinguish these possibilities. Overall, 5.1% of participants had a positive baseline IFN␤ NAb titer, a slightly higher proportion than in other studies of IM IFN␤-1a.10 The increased prevalence might reflect selection of participants with active disease on IFN␤-1a therapy. Although the number of participants with positive baseline NAb titers was small, ACT data suggest that IVMP might lower NAb titers, which deserves further study. AUTHOR CONTRIBUTIONS The study statistician was P.B.I.

ACKNOWLEDGMENT

7.

The authors thank John Barnard, PhD, for consultations on multiple imputation methods in general and their approach in particular.

DISCLOSURE Dr. Cohen has received personal compensation as a consultant or speaker from Biogen Idec, Eisai, Eli Lilly, Genentech, Genzyme, Glaxo Smith Kline, IMPAX, Incyte, Novartis, Schering Plough, Serono, Teva, and Wyeth. He has received research support paid to his institution from Artielle, Biogen Idec, BioMS, Genzyme, Orchestra Therapeutics, Novartis, and Teva. Dr. Imrey holds stock in Sepracor. Dr. Calabresi has received personal compensation as a consultant for Amgen, Biogen Idec, Eisai, Genentech, Millenium, Novartis, Serono, Teva, and Vertex. He has received research support paid to his institution from Biogen Idec, Eisai, Genentech, Millenium, Novartis, Serono, and Teva. Dr. Edwards has received personal compensation as a consultant or speaker from Biogen Idec, Novartis, Pfizer, Serono, and Teva. Dr. Felton has received personal compensation as a speaker from Biogen Idec, Bristol Myers Squibb, Pfizer, Sanofi-Aventis, Serono, and Teva. He has received research support paid to his institution from NIH, Merck, Novartis, Eli Lilly, Centocor, NMT Medical, Boehringer Ingelheim, Ono Pharma, Biogen Idec, Sanofi-Aventis, and Taisho. Dr. Fisher has received personal compensation as a consultant or speaker from Biogen Idec and Millenium. She has received research support paid to her institution from Biogen Idec and Millenium. Dr. Fox has received personal compensation as a consultant or speaker from Biogen Idec, Genentech, Novartis, and Teva. He has received research support paid to his institution from Biogen Idec and Genentech. Dr. Goodman has received personal compensation as a consultant or speaker from Alza, Berlex, Biogen Idec, Genentech, SeronoPfizer, and Teva. He received personal compensation for serving on the editorial board of Reviews in Neurological Disease. He received research support paid to his institution from Acorda, Berlex, Biogen Idec/Elan, Serono, and Teva. Dr. Hutton has received personal compensation as a consultant from Bayer, Biogen Idec, and EMD Serono. He has received research support paid to his institution from Biogen Idec, Genzyme, Genentech, Opexa, and Novartis. Dr. Mandell has received personal compensation as a consultant from Pfizer, Sanofi, and Savient. He is Editorin-Chief of Cleveland Clinic Journal of Medicine. Dr. Scott has received personal compensation as a consultant or speaker from Biogen Idec, Cephalon, Pfizer, and Teva. Drs. Eickenhorst and Zhang are full-time employees of Biogen Idec. Ms. Hara-Cleaver. Dr. Apperson-Hansen, Dr. Beck, Dr. Houghtaling, Dr. Karafa, and Ms. Stadtler have nothing to disclose.

Received June 3, 2008. Accepted in final form October 16, 2008. REFERENCES 1. Cohen JA, Calabresi PA, Chakraborty S, et al. Avonex Combination Trial (ACT) in relapsing-remitting MS: rationale, design, and baseline data. Mult Scler 2008;14:370–382. 2. Kappos L. Neurostatus. Basel, Switzerland: Department of Neurology, University Hospital, CH4031; 2002. 3. Kurtzke JF. Rating neurologic impairment in multiple sclerosis: an expanded disability status scale (EDSS). Neurology 1983;33:1444–1452. 4. Rudick R, Antel J, Confavreux C, et al. Recommendations from the National Multiple Sclerosis Society Clinical Outcomes Assessment Task Force. Ann Neurol 1997;42:379– 382. 5. McDonald WI, Compston DA, Edan G, et al. Recommended diagnostic criteria for multiple sclerosis: guidelines from the International Panel on the Diagnosis of Multiple Sclerosis. Ann Neurol 2001;50:121–127. 6. Lublin FD, Reingold SC. Defining the clinical course of multiple sclerosis: results of an international survey. Neurology 1996;46:907–911.

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Fisher E, Cothren RM, Tkach JA, Masaryk TJ, Cornhill JF. Knowledge-based 3D segmentation of MR images for quantitative MS lesion tracking. SPIE Medical Imaging 1997;3034:19–25. Rudick RA, Fisher E, Lee J-C, Simon J, Jacobs L, the Multiple Sclerosis Collaborative Research Group. Use of the brain parenchymal fraction to measure whole brain atrophy in relapsing-remitting MS. Neurology 1999;53:1698– 1704. Rudick RA, Simonian NA, Alam JA, et al. Incidence and significance of neutralizing antibodies to interferon beta-1a in multiple sclerosis. Neurology 1998;50:1266– 1272. Clanet M, Radue EW, Kappos L, et al. A randomized, double-blind, dose-comparison study of weekly interferon ␤-1a (Avonex) in relapsing MS. Neurology 2002;59:1507– 1517. Ananth CV, Kleinbaum DG. Regression models for ordinal responses: a review of methods and applications. Int J Epidemiol 1997;26:1323–1333. Koch GG, Tangen CM, Jung J-W, Amara IA. Issues for covariance analysis of dichotomous and ordered categorical data from randomized trials and non-parametric strategies for addressing them. Stat Med 1998;17:1863–1892. Tangen CM, Koch GG. Nonparametric analysis of covariance for hypothesis testing with logrank and Wilcoxon scores and survival-rate estimation in a randomized clinical trial. J Biopharm Stat 1999;9:307–338. Gardner W, Mulvey EP, Shaw EC. Regression analyses of counts and rates: Poisson, over-dispersed Poisson, and negative binomial models. Psychol Bull 1995;118:392– 404. Khuri AI, Mukhurjee B, Sinha BK, Ghosh M. Design issues for generalized linear models: a review. Stat Sci 2006; 21:376–399. Rudick RA, Stuart WH, Calabresi PA, et al. Natalizumab plus interferon beta-1a for relapsing multiple sclerosis. N Engl J Med 2006;354:911–923. Fox RJ, Lee J-C, Rudick RA. Optimal reference population for the Multiple Sclerosis Functional Composite. Mult Scler 2007;13:909–914. Fischer JS, Jak AJ, Knicker JE, Rudick RA, Cutter G. Multiple Sclerosis Functional Composite (MSFC). Administration and Scoring Manual: Unitech. National Multiple Sclerosis Society; 2001. Wood SN. Thin plate regression splines. JR Stat Soc B 2003;65:95–114. La Vange LM, Koch GG. Rank score tests. Circulation 2006;114:2528–2533. Cohen JA, Confavreux C. Combination therapy in multiple sclerosis. In: Cohen JA, Rudick RA, eds. Multiple Sclerosis Therapeutics, 3rd ed. London: Informa Healthcare; 2007:681–697. Kleinschmidt-Demasters BK, Tyler KL. Progressive multifocal leukoencephalopathy complicating treatment with natalizumab and interferon-beta-1a for multiple sclerosis. N Engl J Med 2005;353:369–374. Langer-Gould A, Atlas SW, Bollen AW, Pelletier D. Progressive multifocal leukoencephalopathy in a person treated with natalizumab. N Engl J Med 2005;353:375–381.

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Early MRI in optic neuritis The risk for disability

J.K. Swanton, MBBS K.T. Fernando, MBBS C.M. Dalton, MD K.A. Miszkiel, FRCP D.R. Altmann, DPhil G.T. Plant, FRCP A.J. Thompson, FRCP D.H. Miller, FRCP

Address correspondence and reprint requests to Dr. J. Swanton, NMR Unit, Institute of Neurology, Queen Square, London WC1N 3BG, UK [email protected]

ABSTRACT

Background: MRI findings influence the risk of patients with optic neuritis (ON) developing clinically definite (CD) multiple sclerosis (MS) but their influence on future disability is less clear.

Objective: To investigate in patients with ON the influence of lesion number, location and activity, and non-lesion MRI measures obtained on early scans on disability.

Methods: A total of 106 of 143 prospectively recruited patients with ON had reached a scheduled 5-year follow-up, of whom 100 were evaluated clinically. Lesion number, location, and activity measures were analyzed at baseline (within 3 months of onset) and lesion activity measures were studied at 3-month follow-up. Brain atrophy, magnetization transfer ratio, and spectroscopy measures were also analyzed. Ordinal logistic regression assessed the association between early MRI findings and subsequent disability.

Results: At median 6 years follow-up, 48% had converted to CDMS and 52% remained with clinically isolated syndrome (median Expanded Disability Status Scale 2 and 1). In the final models, both the presence and the number of spinal cord lesions at baseline (odds ratios [OR] 3.30, 1.94) and new T2 lesions at follow-up (OR 7.12, 2.06) were significant independent predictors of higher disability. Disability was also predicted by the presence at baseline of gadoliniumenhancing lesions (OR 2.78) and number of infratentorial lesions (OR 1.82). Only spinal cord lesions predicted disability in patients converting to CDMS.

Conclusion: Spinal cord, infratentorial, and gadolinium lesions within 3 months of optic neuritis onset and new T2 lesions after 3 months predicted disability after 6 years; only spinal cord lesions were predictive of disability in those developing clinically definite multiple sclerosis. Neurology® 2009;72:542–550 GLOSSARY BPF ⫽ brain parenchymal fraction; CD ⫽ clinically definite; CI ⫽ confidence interval; CIS ⫽ clinically isolated syndrome; EDSS ⫽ Expanded Disability Status Scale; FOV ⫽ field of view; Gd ⫽ gadolinium; GM ⫽ gray matter; GMF ⫽ gray matter parenchymal fraction; IQR ⫽ interquartile range; LR ⫽ likelihood ratio; MS ⫽ multiple sclerosis; MTI ⫽ magnetization transfer imaging; MTR ⫽ MT ratio; NAGM ⫽ normal-appearing gray matter; NAWM ⫽ normal-appearing white matter; ON ⫽ optic neuritis; OR ⫽ odds ratio; PRESS ⫽ point resolved spectroscopy; RRMS ⫽ relapsing remitting MS; SPMS ⫽ secondary progressive MS; TE ⫽ echo time; TR ⫽ repetition time; WM ⫽ white matter; WMF ⫽ white matter parenchymal fraction.

Of the 38 –78% of patients with clinically isolated syndrome (CIS) converting to clinically definite MS (CDMS),1-4 the subsequent clinical course is variable. Up to two thirds of patients have minimal disability after 10 years,2,5 whereas up to half require aid to walk after 15 years.1,6,7 In this article, we report features of lesion number, location, and activity of an optic neuritis (ON)–CIS cohort that are independently predictive of disability. Studies of mixed CIS cohorts have found a significant, although modest, association between baseline lesion load and disability at up to 20-year follow-up,1,4,8,9 not found in the Optic Neuritis Treatment Trial at 10 years.2 The association of disability with markers of disease activity, such as gadolinium (Gd)

From the NMR Unit (J.K.S., K.T.F., C.M.D., D.H.M.) and Department of Neurorehabilitation (A.J.T.), Institute of Neurology; Department of Neuroradiology (K.A.M.), National Hospital for Neurology and Neurosurgery; Medical Statistics Unit (D.R.A.), London School of Hygiene & Tropical Medicine; and Neuroophthalmology Clinic (G.T.P.), Moorfields Eye Hospital, London, UK. Funded by the MS Society for Great Britain and Northern Ireland. Disclosure: Author disclosures are provided at the end of the article. 542


enhancement, has not been investigated in unselected CIS cohorts.1,2,4 Lesion location may also be important for prognosis.3 The potential of nonlesion measures, demonstrated within a year of CIS onset using nonconventional MRI,10-14 to predict disability has not yet been explored. We have limited this follow-up report to patients with ON because 1) 80% of our cohort presented with ON, 2) some studies report a more benign disease course in ON than other CIS presentations,15-17 and 3) owing to the potential difficulty in differentiating asymptomatic lesions in brainstem or spinal cord CIS. The aim of this study was to identify independent, early MRI predictors of subsequent disability after 6 years in patients who present with isolated ON. METHODS Patients. Patients aged 16 –50 years within 3 months of ON onset with no previous neurologic history suggestive of demyelination or evidence of CNS abnormality outside the optic nerves were consecutively recruited from a neuroophthalmology clinic at Moorfields Eye Hospital between 1995 and 2004 as part of a prospective follow-up study. All patients were reviewed by a single neuro-ophthalmologist (G.T.P.) and blood tests were performed as required to exclude other causes. Local ethics committee approval was obtained before starting the study, and informed consent was obtained from patients at baseline and each subsequent visit (planned at 3 months, 1, 3, and 5 years from baseline). Follow-up visits included MRI, history of further events, clinical examination, and documentation of Expanded Disability Status Scale (EDSS). Only patients who had reached the scheduled 5-year follow-up were included in this analysis. All examinations and EDSS scores at 5 years were performed by a single physician (J.S.) having completed EDSS training. Patients were defined as having CDMS using the Poser criteria.18 (The clinical criteria defined by Poser for CDMS, i.e., requiring clinical evidence of dissemination in space and time, were used as the aim was to investigate early MRI parameters predicting clinical outcome.)

MRI acquisition protocols and image analysis. All images were acquired on a 1.5 Tesla GE scanner and have been described in detail where referenced. In this report, MRI findings at baseline and 3-month follow-up only are considered as the focus is on early imaging predictors. MRI acquisition protocols and image analysis are summarized in table 1. Statistical analysis. Spearman correlation identified associations with MRI parameters and 5-year EDSS. Ordinal logistic regression was performed, with ranked follow-up EDSS as the dependent variable (cutoffs chosen to make approximately equal groups: EDSS 0, 1, 1.5–2, ⱖ2.5) and MRI parameters as the independent variables. Univariate regression analysis identified significant predictors from the parameter types: baseline lesion load (T2 lesion number, T2- and T1-hypointense lesion volume), location (periventricular, juxtacortical, discrete cerebral,

infratentorial, and spinal cord), lesion activity (Gd-enhancing lesions), volumetric measures (gray matter, white matter, and brain parenchymal fractions [GMF, WMF, BPF], ventricular volume); 3-month follow-up new lesion activity (Gd-enhancing and new T2 lesions) spectroscopy (N-acetylaspartate, myoInositol) and MTR (mean, peak height, peak location in normalappearing white matter [NAWM] and normal-appearing gray matter [NAGM]) measures.

Multiple regression performed in three stages. Stage 1. Multiple regression identified the strongest of the significant predictors within each variable type (lesion number, location, volumetric measures, lesion activity, spectroscopy, and MTR) for each of the two time points separately. Stage 2. The significant predictors of different variable types from stage 1 were entered together to identify the strongest independent predictors for each time point scan. Stage 3. The variables from both time point scans were entered together, to identify the strongest overall independent predictors. Stages 1 to 3 were repeated, first excluding patients with EDSS obtained by telephone, and second in the subgroup of patients who had converted to CDMS18 by final follow-up. When variables did not remain significant in multivariate analysis, they were dropped stepwise (manually) from the model, and their contribution tested with the likelihood ratio (LR) test. When the LR test was borderline significant (p ⬍ 0.1), the variable was maintained in the model, except in the final model where only variables p ⬍ 0.05 were reported. Number of lesions were categorized into groups for statistical analysis. For analysis of baseline brain lesion number, patients were grouped by lesion number according to percentiles to ensure similar sized groups (0, 1– 4, 5–14, and ⱖ15 lesions). Other lesion measures (location, Gd enhancing, new lesions) were grouped into binary (0, ⱖ1) and ordinal (0, 1, 2, and ⱖ3 lesions) variables. If there was no evidence of non-linearity, the ordinal score was entered into the model. Volumetric measures and nonconventional MRI parameters were analyzed as continuous variables. Other covariates (age, gender, baseline EDSS, diseasemodifying treatment, and duration of follow-up) were added to the model at the end. Statistical analysis was performed using Stata 9.2 statistical software (Stata Corporation, College Station, TX).

Of 143 patients with ON recruited, 106 were recruited at least 5 years earlier, and of these 100 were successfully followed up at 5 years (phone EDSS obtained for 25 patients unable to attend for clinical follow-up19). Demographic and clinical details are summarized in table 2. Baseline and follow-up MRI findings are shown in table 3 and results of univariate correlation and regression analysis are shown in table 4. Lesion volume measures were not significant in univariate regression, except on exclusion of a single outlier (T2- and T1-hypointense lesion volumes odds ratios [ORs] 2.13 and 1.26). No brain tissue volume measures were significant.

RESULTS

Logistic regression: Multivariate analysis of relationship between early MRI measures and EDSS at followup. Baseline scan measures. Lesion load. The ordinal brain

lesion variable (subsequently referred to as brain leNeurology 72

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Table 1

MRI acquisition protocols and image analysis Slice thickness, mm

Brain: postcontrast, baseline, and 3 months

46 ⫻ 3

Orientation

Matrix

FOV, cm

TR/TE, ms (comments)

Contiguous axial slices

256 ⫻ 256

24

3,200/15 3,200/90 600/17

Image analysis No. and location of T2, Gdenhancing, T1-hypointense lesions identified by neuroradiologist (K.A.M.) and contoured using semiautomated thresholding technique to calculate volume32 Ventricular volume measured on T1-weighted scans at baseline using MIDAS28, 33 GMF, WMF and BPFcalculated from SPM99 segmented T2-weighted images following lesion masking29: GMF ⫽ GM/TIV, WMF ⫽ WM ⫹ lesion volume/TIV, BPF ⫽ GM ⫹ WM ⫹ lesion volume/TIC

9⫻3

Cord: postcontrast, baseline MTI12, 34: precontrast, 3 months

28 ⫻ 5

1 H-MRS11: precontrast, 3 months

Contiguous sagittal slices

512 ⫻ 512

48

2,500/56 2,500/92 500/19

No. of T2, Gd-enhancing lesions identified by neuroradiologist (K.A.M.)

Contiguous axial oblique slices

256 ⫻ 128

24

1,720/30 1,720/80 (MT weighted with application of presaturation pulse)

Lesion masks created on non-MT images, whole brain mass generated in SPM99 and applied to calculated MTR map determining NAWM and GM pixels; normalized NAWM and GM histograms generated

3,000/30 (PRESS sequence with 192 averages with optimized shimming and water suppression)

Metabolite concentrations estimated using LCModel and spectra assessed for quality of acquisition and processing by observer blinded to the clinical data (K.T.F.)

Single voxel manually placed in NAWM

FOV ⫽ field of view; TR ⫽ repetition time; TE ⫽ echo time; Gd ⫽ gadolinium; GMF ⫽ gray matter parenchymal fraction; WMF ⫽ white matter parenchymal fraction; BPF ⫽ brain parenchymal fraction; GM ⫽ gray matter; TIV ⫽ total intracranial volume; WM ⫽ white matter; MTI ⫽ magnetization transfer imaging; MTR ⫽ MT ratio; NAWM ⫽ normal-appearing white matter; PRESS ⫽ point resolved spectroscopy.

sion number) was the strongest of the lesion load variables. T2- and T1-hypointense lesion volumetric measures did not contribute independently even on exclusion of the outlier (ORs for brain lesion number in analysis with T2- and T1-hypointense lesion volumes 1.78 [95% confidence interval (CI) 1.14 –2.80] and 2.00 [95% CI 1.37–2.90], both p ⬍ 0.001). Lesion location. All five possible, mutually exclusive locations were analyzed together (periventricular, juxtacortical, infratentorial, discrete cerebral, spinal cord), adjusting for brain lesion number. In the binary model, only spinal cord lesions remained significant, and infratentorial lesions approached significance. In the ordinal model, infratentorial and spinal cord lesions were both significant. After stepwise removal of noncontributing variables, only infratentorial, spinal cord, and brain lesion number remained. In the binary model, the contribution from infratentorial lesions was borderline significant and was therefore retained. See model 5a in table 5. Lesion activity. When baseline Gd lesions were added to model 5a, brain lesion number no longer re544

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mained significant and was therefore dropped. In addition, in the binary model, spinal cord lesions did not remain significant, but removal showed that their contribution to that model was borderline, and was therefore retained (see model 5b in table 5). Tissue volumetric measures. No volumetric measures were significant when added to the multivariate model 5b. Three-month follow-up scan measures. New lesion activity.

In analysis of Gd-enhancing and new T2 lesions at 3 months, only new T2 lesions remained significant with a binary OR of 11.51 (95% CI 3.14 – 42.21) and ordinal OR of 2.42 (95% CI 1.23– 4.78). Other variables. No spectroscopy or MTR measures at 3 months were significant in univariate analysis and were therefore not further investigated. Multivariate analysis combining baseline and 3-month

Combining the significant baseline (spinal cord, infratentorial locations, and Gd-enhancing lesions) and 3-month parameters (new T2 lesions), Gd-enhancing lesions became borderline significant in the ordinal model. Infratentorial lesions did not remain significant in the binary follow-up scan measures.

Table 2

Demographic data of the 100 patients with optic neuritis followed up at the scheduled 5-year time point*

Data

Values

Median age at CIS onset, y (IQR)

31.9 (28.2–37.9)

Male/female, n (%) Median time from CIS onset to baseline MRI, wk (IQR)

33 (33)/67 (67) 5 (4–8)

Median time from CIS onset to follow-up MRI, wk (IQR)

20 (18–23)

Median duration of follow-up, y (IQR)

6.1 (5.1–7.2)

Clinical vs phone (19) EDSS

75:25

Median EDSS in all patients at 5 years* (range)

1 (0–8.5)

Median EDSS in patients remaining CIS at 5 years* (IQR)

1 (0–1)

Median EDSS in patients CDMS at 5 years* (IQR)

2 (1-3)

EDSS at 5 years,* n (%) 0

21 (21)

1

40 (40)

1.5–2

23 (23)

>2.5

16 (16)

CIS at 5 years,* n (%)

52 (52)

RRMS at 5 years,* n (%)

43 (43)

SPMS at 5 years,* n (%)

5 (5)

Median time to CDMS, mo (IQR)

7 (6 to 36)

*Median follow-up actually 6 years. CIS ⫽ clinically isolated syndrome; IQR ⫽ interquartile range; EDSS ⫽ Expanded Disability Status Scale; CDMS ⫽ clinically definite multiple sclerosis; RRMS ⫽ relapsing remitting MS; SPMS ⫽ secondary progressive MS.

analysis. These variables were therefore dropped from the final model; see model 5c in table 5. Other covariates. Age, gender, baseline EDSS,

disease-modifying therapy, and time between symptom onset and 5-year follow-up inserted into the models individually were not significant. Examination-based EDSS patients only. Similar results were obtained at all three stages if we repeated the analysis for patients whose EDSS was based on examination findings rather than telephone assessment (n ⫽ 75 at baseline and 69 at 3-month followup). The final binary and ordinal models contained only baseline spinal cord lesions (OR 4.41, 95% CI 1.47–13.24, p ⫽ 0.008, and OR 2.35, 95% CI 1.35– 4.07, p ⫽ 0.002) and new T2 lesions at 3 months (OR 6.89, 95% CI 2.44 –19.47, p ⬍ 0.001, and 1.87, 95% CI 1.19 –2.93, p ⫽ 0.007). CDMS patients only. If only those patients with ON converting to CDMS by 6 years are investigated (n ⫽ 48), no measures of baseline brain lesion load, location, or activity were significant in univariate

analysis. Only baseline cord lesions, GMF, and BPF were significant in univariate analysis; however, the volumetric measures did not remain significant after adjusting for age, and only cord lesions remained significant (ordinal OR 1.92, 95% CI 1.14 –3.26, binary OR 5.07, 95% CI 1.60 –16.11). No variable from the 3-month follow-up visit remained significant in the patients who had converted to CDMS at 6 years. No other covariates were significant in the analysis of patients with CDMS. DISCUSSION In this study, early independent MRI predictors of disability in patients with ON were measures of lesion location (spinal cord and infratentorial lesions) and activity (baseline Gd enhancement and new T2 lesions at follow-up) rather than lesion load. In this ON cohort, lesion number was a significant predictor of the 6-year EDSS in univariate analysis in agreement with the recently reported mixed CIS cohorts followed up at 7 and 20 years.1,4,8,9 An important new finding in the present cohort is that baseline lesion number was no longer significant in analysis including other MRI lesion location and activity parameters, not investigated in these other studies. Analysis of our earlier mixed CIS cohort also found brain lesion load at 5 years, cross-sectional and increase from baseline, correlated more strongly with EDSS at 14 and 20 years than did baseline measures.1,9 It may be that lesion increase over time is more predictive than one baseline measure and the significant effect of new T2 lesions at 3 months in the present study supports this idea: investigation of longer term changes in T2 number and volume in the present cohort will be of interest. Due to the presence of a single outlier, the continuous variable lesion volume was significant in Spearman correlation (sensitive to values’ rank) but not in logistic regression (sensitive to values’ magnitude) where lesion number, analyzed as an ordinal variable, was significant. The significant association between baseline brain lesion number and 6-year disability did not remain so in analysis of the patients converting to CDMS. Although still significant in our earlier CIS cohort, the correlation between baseline T2 lesion volume and 20-year EDSS was weaker in the CDMS subgroup.9 The Barcelona CIS study does not report this subgroup analysis.4 Our findings—from both CIS cohorts—suggest that baseline brain lesion load per se is a better predictor of conversion to CDMS than disability. That brain lesion load did not remain significant in the analyses including measures of lesion location and activity suggests that the latter lesion Neurology 72

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545

Table 3

MRI findings at baseline and 3 months in all patients and in the 5-year EDSS subgroups All patients

EDSS 0

EDSS 1

EDSS 1.5–2

EDSS >2.5

Baseline Brain T2 lesion no. Gd lesion no. T2 lesion volume, mL

5 (1–16)

0 (0–4)

0 (0–1)

0 (0–0)

0.46 (0.05–1.81)

0 (0–0.34)

3 (0–16)

0 (0–0) 0.19 (0–1.67)

6 (3–16)

0 (0–1)

15 (6–29)

2 (0–6)

0.79 (0.23–1.81)

2.08 (0.48–4.13)

0.03 (0–0.25)

0.09 (0–0.54)

T1 hypointense lesion volume, mL

0 (0–0.15)

0 (0–0)

0 (0–0.15)

Cord T2 lesion no.

0 (0–1)

0 (0–0)

0 (0–0)

0 (0–1)

1 (0–2)

No. of infratentorial lesions

0 (0–1)

0 (0–0)

0 (0–0)

0 (0–2)

1 (0–2)

No. of periventricular lesions

2 (0–7)

0 (0–1)

1 (0–7)

3 (1–8)

7 (2–12)

No. of juxtacortical lesions

1 (0–4)

0 (0–1)

1 (0–3)

1 (0–5)

4 (1–9)

No. of discrete cerebral lesions

1 (0–43)

0 (0–0)

0 (0–4)

1 (0–3)

2 (0–5)

Ventricular volume

6.41 (4.02–10.13)

6.27 (4.00–8.40)

5.97 (3.27–10.71)

6.86 (4.57–10.76)

5.98 (4.07–8.75)

Grey matter fraction

0.49 (0.47–0.51)

0.50 (0.49–0.51)

0.49 (0.47–0.51)

0.48 (0.48–0.51)

0.48 (0.46–0.50

White matter fraction

0.37 (0.36–0.39)

0.37 (0.36–0.38)

0.37 (0.36–0.39)

0.37 (0.36–0.38)

0.38 (0.36–0.40)

Brain parenchymal fraction

0.86 (0.85–0.87)

0.87 (0.85–0.88)

0.86 (0.85–0.88)

0.86 (0.85–0.87)

0.85 (0.84 – 0.87)

3-month follow-up No. of new T2 lesions No. of Gd lesions Nacetylaspartate Myo-inositol MTR NAWM peak height

0 (0–1)

0 (0–0)

0 (0–0)

0 (0–0)

0 (0–0)

0 (0–0)

1 (0–1)

0 (0–1)

2 (1–8)

1 (0–6)

8.16 (7.61–8.84)

7.75 (7.37–9.36)

8.14 (7.54–8.73)

8.56 (8.12–9.42)

8.14 (7.26–8.84)

3.82 (3.06–4.43)

4.00 (3.38–4.64)

3.82 (2.78–4.15)

4.12 (3.31–4.65)

3.29 (2.74–5.01)

20.88 (19.80–21.87) 19.76 (18.92–21.62) 20.63 (19.41–21.41) 20.78 (19.71–22.26) 21.11 (19.87–22.12)

MTR NAWM peak location MTR NAWM mean

38.4 (38.0–38.7)

38.4 (38.2–38.6

38.4 (38.0–38.8)

38.4 (38.0–38.7)

38.2 (37.7–38.5)

38.14 (37.84–38.42) 38.16 (37.89–38.28) 38.14 (37.86–38.55) 38.21 (37.89–38.47) 38.11 (37.54–38.39)

MTR NAGM peak 13.05 (12.33–13.73) 12.78 (12.46–13.68) 13.07 (12.33–13.72) 12.52 (11.83–13.11) 13.20 (12.12–14.04) height, MTR NAGM peak location, MTR NAGM mean

33.2 (32.9–33.5)

33.1 (32.7–33.3)

33.1 (32.9–33.5)

33.1 (32.8–33.6)

33.4 (32.8–33.6)

32.32 (32.05–32.61) 32.05 (31.98–32.41) 32.33 (32.11–32.55) 31.89 (32.46–32.63) 32.26 (32.08–32.71)

Values are median (interquartile range). EDSS ⫽ Expanded Disability Status Scale; Gd ⫽ gadolinium; MTR ⫽ magnetization transfer ratio; NAWM ⫽ normalappearing white matter; NAGM ⫽ normal-appearing gray matter.

measures are more important with respect to disability than overall lesion load per se. The spinal cord is considered a characteristic location for demyelination. Asymptomatic cord lesions, seen in 26% of our ON cohort, are reported in 27– 546

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42% of patients with CIS at presentation.20,21 Whether cord lesions add independent prognostic information in patients with brain lesions has not been clear.21 However, this study shows the presence of asymptomatic cord lesions at ON presentation sig-

Table 4

Univariate analysis with Spearman rank correlation coefficients and ordinal logistic regression derived odds ratios for baseline and follow-up MRI parameters

No. of patients

Spearman correlation coefficient

p Value

Odds ratio

p Value

2.068

⬍0.001

Baseline T2 brain lesion no.*

100

0.425

⬍0.001

T2 brain lesion volume

100

0.422

⬍0.001

1.104

0.108

T1 hypointense brain lesion volume

100

0.313

0.002

1.575

0.092

T2 cord no.†

100

0.367

⬍0.001

2.067

0.001

Infratentorial lesion no.†

100

0.372

⬍0.001

2.500

⬍0.001

Periventricular lesion no.†

100

0.387

⬍0.001

1.809

⬍0.001

Juxtacortical lesion no.†

100

0.333

⬍0.001

1.556

0.002

Gd lesion no.†

100

0.428

⬍0.001

2.072

⬍0.001

Grey matter fraction

100

⫺0.222

0.027

0.894

0.088

White matter fraction

100

0.077

0.448

1.040

0.687

Brain parenchymal fraction

100

⫺0.178

0.077

0.852

0.058

Ventricular volume, mL

100

0.084

0.433

1.027

0.450

No. of new T2 lesions†

87

0.510

⬍0.001

2.470

⬍0.001

No. of Gd lesions†

87

0.383

⬍0.001

2.514

0.001

3-month follow-up

N-acetylaspartate

74

0.180

0.427

1.246

0.389

Myo-inositol

74

⫺0.049

0.097

0.932

0.743

MTR NAWM peak height

72

0.163

0.202

1.248

0.167

MTR NAWM peak location

72

⫺0.089

0.486

0.848

0.735

MTR NAWM mean

72

⫺0.079

0.537

0.883

0.811

MTR NAGM peak height

72

⫺0.052

0.684

0.934

0.740

MTR NAGM peak location

72

0.158

0.216

2.030

0.212

MTR NAGM mean

72

0.102

0.426

1.493

0.494

For regression analysis, lesion number variables were analyzed as score variables. Grouped *0, 1– 4, 5–14, ⱖ15 lesions or †0, 1, 2, ⱖ3 lesions. Gd ⫽ gadolinium; MTR ⫽ magnetization transfer ratio; NAWM ⫽ normal-appearing white matter; NAGM ⫽ normalappearing gray matter.

nificantly increased the odds of higher disability at 6 years and in this effect was independent of and stronger than brain lesion load; there may therefore be a role for cord MRI in patients with ON in considering the risk for future disability. Infratentorial lesions were significant in ordinal but not binary analysis, suggesting the number of infratentorial lesions influences the risk for disability. This study is concordant with the findings from a Dutch CIS cohort that two or more baseline infratentorial lesions in patients with CIS were significant predictors of time to EDSS ⱖ3.3 Asymptomatic infratentorial lesions are found in patients with CIS on MRI. An early study found brainstem and cerebellar lesions in 14% and 11% of patients with ON and CIS.22 We found brainstem or cerebellar lesions in 31% of our ON cohort, and the increase in detection may be due to improvement in imaging technology. A role for infratentorial lesions in disability was supported by a study in which

patients with progressive MS had similar numbers of supratentorial lesions but higher numbers of infratentorial lesions than age-, sex- and disease duration– matched patients with benign MS.23 Lesions in the spinal cord or brainstem are more likely to affect a clinically strategic pathway than supratentorial lesions. Although not always clinically eloquent at presentation, they may result in delayed symptoms through secondary degeneration or when subject to further episodes of inflammatory demyelination. The presence of such lesions at presentation may indicate a propensity for further lesions in the same region which themselves cause symptoms and subsequent sustained disability. In the supratentorial compartment there is potential for compensatory mechanisms and reorganization of functional pathways; this potential may be less in the spinal cord and infratentorial regions where the threshold of axonal damage needed before clinical deficits develops may be lower. Neurology 72

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Table 5

Models 5a, 5b, and 5c

Models

Odds ratio

95% CI

p

Binary model 5a (grouped 0, >1), n ⴝ 100 Location Infratentorial

2.36

0.95–5.86

0.065

Spinal cord

2.51

1.02–6.15

0.044*

Grouped brain lesions

1.66

1.15–2.40

0.007*

Ordinal model 5a (grouped 0, 1, 2, >3), n ⴝ 100 Location Infratentorial

1.80

1.08–3.03

0.025*

Spinal cord

1.62

1.04–2.51

0.031*

Grouped brain lesions

1.87

1.08–2.29

0.019*

3.37

1.37–8.29

0.008*

Binary model 5b (grouped 0, >1), n ⴝ 100 Location/enhancement Infratentorial Spinal cord

2.18

0.89–5.33

Gd enhancing

4.93

2.21–10.98

0.088 ⬍0.001*

Ordinal model 5b (grouped 0, 1, 2, >3), n ⴝ 100 Location/enhancement Infratentorial

2.22

1.34–3.70

0.002*

Spinal cord

1.65

1.07–2.55

0.023*

Gd enhancing

1.84

1.25–2.70

0.002*

Binary model 5c (grouped 0, >1), n ⴝ 87 Parameter Baseline Spinal cord

3.30

1.26–8.68

0.015*

Gd enhancing

2.78

1.02–7.59

0.045*

7.12

2.64–19.18

3 mo New T2 3 mo

⬍0.001*

Ordinal model 5c (grouped 0, 1, 2, >3), n ⴝ 87 Parameter Baseline Infratentorial

1.82

1.06–3.11

0.030*

Spinal cord

1.94

1.23–3.06

0.004*

2.06

1.34–3.18

0.001*

3 mo New T2 3 mo

Models 5a (analysis of five possible baseline lesion locations, adjusting for baseline lesion number, after removal of variables not contributing significantly to the models), 5b (analysis of all significant baseline lesion variables, baseline lesion load, location, and activity measures, after serial removal of variables not contributing to the model), and 5c (showing the final model in all patients with optic neuritis with significant lesion variables from baseline and 3-month follow-up MRI after serial removal of variables not contributing to the models). *Significant. CI ⫽ confidence interval; Gd ⫽ gadolinium.

The lesion locations investigated were relatively large areas of the CNS rather than specific pathways that have immediate functional relevance. 548

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For example, lesions in specific tracts such as the internal capsule may have significant effects on later disability, and were not investigated in this study. MRI evidence of lesion activity added significant prognostic information with regards to disability in the whole CIS cohort, with both Gd-enhancing lesions at baseline and (more consistently) new T2 lesions on the follow-up scan being independent predictors of disability in the final model (model 5c). However, neither of these remained significant predictors of disability when analysis was confined to the subgroup who converted to CDMS. New T2 lesions significantly increased the risk of CDMS at 1 year in an earlier study of this cohort.24 These findings suggest that the lesion activity variables may be predicting conversion to CDMS rather than disability per se. This idea is supported by other studies which have found Gd lesions predict relapse occurrence but not later disability.25,26 MTR and MRS parameters obtained 20 weeks from CIS onset were not significantly associated with disability at 6 years in the ON cohort. Although changes in MTR and MRS have been detected in patients with CIS compared to controls,11-14 it is possible that the abnormalities in the NAWM and GM are mild at such an early stage of disease and unlikely to manifest clinically. Longitudinal studies of patients with CDMS have demonstrated changes in MTR13 and MRS27 over time, some of which correlated with clinical impairment.13,27 Further longitudinal investigation of CIS cohorts is required of the evolution of non-lesion MR measures and their relationship to the clinical course. In this study, baseline GMF was an independent significant predictor of disability in the subgroup of patients who converted to CDMS, but was confounded by age. Longitudinal atrophy measures were associated with the concurrent development of CDMS in this CIS cohort.28,29 Future analysis should investigate the relationship between longitudinal atrophy with later disability. The study has several limitations. First, tissue volumetric measures were generated from twodimensional acquisitions as three-dimensional acquisitions were not available in the patients recruited before 1998. Second, only about three-quarters of patients had MRS or MTR due to quality of acquisition or processing and lack of availability before 1998. Nevertheless, it seems likely that had there been a clear predictive effect of these MR measures an effect should have been apparent. Third, this study was limited to the ON subgroup and is not necessarily applicable to non-ON presen-

tations; some15-17 but not all1,30,31 studies have suggested that ON has a better long-term prognosis than non-ON presentations. When investigating the predictive role of lesion location in patients with brainstem and spinal cord CIS, special care will be needed to identify clinically silent infratentorial and spinal cord lesions. Fourth, EDSS has been criticized for its emphasis on ambulation, which may help explain the association with spinal cord lesions. MSFC was not used due to ceiling effects in a relatively unimpaired cohort. Also, EDSS was obtained over the phone in 25% of our cohort. Although clinical examination would have been preferable, in these patients it was impractical. Reassuringly similar results were obtained on their exclusion. Finally, only 12% of our cohort had EDSS ⱖ3 at ⬍6 years and the median EDSS of the patients with CDMS was 2. In our earlier CIS cohort, the median EDSS of the CDMS group was 3.25 and 4.0 after 14 and 20 years.1,9 More prolonged follow-up is needed to determine whether the early predictors identified in this study are still relevant in the cohort as more disability emerges.

6.

7.

8.

9.

10.

11.

12.

13.

AUTHOR CONTRIBUTIONS Statistical analysis was conducted by D.R.A.

14.

DISCLOSURE J.K.S., K.T.F., C.M.D., K.A.M., D.R.A., and G.T.P. report no conflicts of interest. A.J.T. received consulting fees/expenses from Teva for work as chairman of the Data Safety Monitoring Board for trial GA for ALS and Novartis for participating in Advisory Board on PPMS; honoraria/expenses for speaking from Schering and Serono; and is Editor-in-Chief of Multiple Sclerosis. D.H.M. received honoraria from Biogen, Schering, and GlaxoSmithKline for consulting services; reimbursement as Co-Chief Editor of Journal of Neurology; and financial support from GlaxoSmithKline, Biogen, Schering, and Novartis through grants held by the Institute of Neurology. The organizations mentioned did not participate in any aspect of the study design, execution, analysis, or write-up.

Received June 16, 2008. Accepted in final form November 6, 2008. REFERENCES 1. Brex PA, Ciccarelli O, O’Riordan JI, Sailer M, Thompson AJ, Miller DH. A longitudinal study of abnormalities on MRI and disability from multiple sclerosis. N Engl J Med 2002;346:158–164. 2. Beck RW, Smith CH, Gal RL, et al. Neurologic impairment 10 years after optic neuritis. Arch Neurol 2004;61: 1386–1389. 3. Minneboo A, Barkhof F, Polman CH, Uitdehaag BM, Knol DL, Castelijns JA. Infratentorial lesions predict longterm disability in patients with initial findings suggestive of multiple sclerosis. Arch Neurol 2004;61:217–221. 4. Tintore M, Rovira A, Rio J, et al. Baseline MRI predicts future attacks and disability in clinically isolated syndromes. Neurology 2006;67:968–972. 5. Bradley WG, Whitty CW. Acute optic neuritis: prognosis for development of multiple sclerosis. J Neurol Neurosurg Psychiatry 1968;31:10–18.

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Weinshenker BG, Bass B, Rice GP, et al. The natural history of multiple sclerosis: a geographically based study. 2. Predictive value of the early clinical course. Brain 1989; 112:1419–1428. Confavreux C, Aimard G, Devic M. Course and prognosis of multiple sclerosis assessed by the computerized data processing of 349 patients. Brain 1980;103:281–300. O’Riordan JI, Thompson AJ, Kingsley DP, et al. The prognostic value of brain MRI in clinically isolated syndromes of the CNS. A 10-year follow-up. Brain 1998;121: 495–503. Fisniku LK, Brex PA, Altmann DR, et al. Disability and T2 MRI lesions: a 20-year follow-up of patients with relapse onset of multiple sclerosis. Brain 2008;131:808–817. Lutterbey G, Behrends K, Falkenhausen MV, et al. Is the body-coil at 3 Tesla feasible for the MRI evaluation of the painful knee? A comparative study. Eur Radiol 2007;17: 503–508. Fernando KT, McLean MA, Chard DT, et al. Elevated white matter myo-inositol in clinically isolated syndromes suggestive of multiple sclerosis. Brain 2004;127:1361– 1369. Fernando KT, Tozer DJ, Miszkiel KA, et al. Magnetization transfer histograms in clinically isolated syndromes suggestive of multiple sclerosis. Brain 2005;128:2911– 2925. Agosta F, Rovaris M, Pagani E, Sormani MP, Comi G, Filippi M. Magnetization transfer MRI metrics predict the accumulation of disability 8 years later in patients with multiple sclerosis. Brain 2006;129:2620–2627. Traboulsee A, Dehmeshki J, Brex PA, et al. Normalappearing brain tissue MTR histograms in clinically isolated syndromes suggestive of MS. Neurology 2002;59: 126–128. Eriksson M, Andersen O, Runmarker B. Long-term follow up of patients with clinically isolated syndromes, relapsingremitting and secondary progressive multiple sclerosis. Mult Scler 2003;9:260–274. Phadke JG. Clinical aspects of multiple sclerosis in northeast Scotland with particular reference to its course and prognosis. Brain 1990;113:1597–1628. Tintore M, Rovira A, Rio J, et al. Is optic neuritis more benign than other first attacks in multiple sclerosis? Ann Neurol 2005;57:210–215. Poser CM, Paty DW, Scheinberg L, et al. New diagnostic criteria for multiple sclerosis: guidelines for research protocols. Ann Neurol 1983;13:227–231. Lechner-Scott J, Kappos L, Hofman M, et al. Can the Expanded Disability Status Scale be assessed by telephone? Mult Scler 2003;9:154–159. O’Riordan JI, Losseff NA, Phatouros C, et al. Asymptomatic spinal cord lesions in clinically isolated optic nerve, brain stem, and spinal cord syndromes suggestive of demyelination. J Neurol Neurosurg Psychiatry 1998;64:353– 357. Dalton CM, Brex PA, Miszkiel KA, et al. Spinal cord MRI in clinically isolated optic neuritis. J Neurol Neurosurg Psychiatry 2003;74:1577–1580. Ormerod IE, McDonald WI, du Boulay GH, et al. Disseminated lesions at presentation in patients with optic neuritis. J Neurol Neurosurg Psychiatry 1986;49:124– 127. Koopmans RA, Li DK, Grochowski E, Cutler PJ, Paty DW. Benign versus chronic progressive multiple sclerosis:

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magnetic resonance imaging features. Ann Neurol 1989; 25:74–81. Brex PA, Miszkiel KA, O’Riordan JI, et al. Assessing the risk of early multiple sclerosis in patients with clinically isolated syndromes: the role of a follow up MRI. J Neurol Neurosurg Psychiatry 2001;70:390–393. Rashid W, Davies GR, Chard DT, et al. Relationship of triple dose contrast enhanced lesions with clinical measures and brain atrophy in early relapsing-remitting multiple sclerosis: a two-year longitudinal study. Mult Scler 2007; 13:178–185. Kappos L, Moeri D, Radue EW, et al. Predictive value of gadolinium-enhanced magnetic resonance imaging for relapse rate and changes in disability or impairment in multiple sclerosis: a meta-analysis: Gadolinium MRI Meta-analysis Group. Lancet 1999;353:964–969. De Stefano N, Matthews PM, Fu L, et al. Axonal damage correlates with disability in patients with relapsingremitting multiple sclerosis. Results of a longitudinal magnetic resonance spectroscopy study. Brain 1998;121: 1469–1477. Dalton CM, Brex PA, Jenkins R, et al. Progressive ventricular enlargement in patients with clinically isolated syndromes is associated with the early development of

multiple sclerosis. J Neurol Neurosurg Psychiatry 2002; 73:141–147. 29. Dalton CM, Chard DT, Davies GR, et al. Early development of multiple sclerosis is associated with progressive grey matter atrophy in patients presenting with clinically isolated syndromes. Brain 2004;127:1101–1107. 30. Comi G, Filippi M, Barkhof F, et al. Effect of early interferon treatment on conversion to definite multiple sclerosis: a randomised study. Lancet 2001;357:1576–1582. 31. Jacobs LD, Beck RW, Simon JH, et al. Intramuscular interferon beta-1a therapy initiated during a first demyelinating event in multiple sclerosis. CHAMPS Study Group. N Engl J Med 2000;343:898–904. 32. Sailer M, O’Riordan JI, Thompson AJ, et al. Quantitative MRI in patients with clinically isolated syndromes suggestive of demyelination. Neurology 1999;52:599–606. 33. Freeborough PA, Fox NC, Kitney RI. Interactive algorithms for the segmentation and quantitation of 3-D MRI brain scans. Comput Methods Programs Biomed 1997;53: 15–25. 34. Barker GJ, Tofts PS, Gass A. An interleaved sequence for accurate and reproducible clinical measurement of magnetization transfer ratio. Magn Reson Imaging 1996;14:403– 411.

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Nonviolent elaborate behaviors may also occur in REM sleep behavior disorder

D. Oudiette, MSc V.C. De Cock, MD, PhD S. Lavault, MSc S. Leu, MD M. Vidailhet, MD I. Arnulf, MD, PhD

Address correspondence and reprint requests to Dr. Isabelle Arnulf, Unite´ des Pathologies du Sommeil, Hoˆpital Pitie´Salpeˆtrie`re, 47-83 boulevard de l’Hoˆpital, 75651 Paris Cedex 13, France [email protected]

ABSTRACT

Objective: To document unusual, nonviolent behaviors during REM sleep behavior disorder (RBD) and evaluate their frequency in Parkinson disease (PD).

Background: Most behaviors previously described during RBD mimic attacks, suggesting they proceed from archaic defense generators in the brainstem. Feeding, drinking, sexual behaviors, urination, and defecation have not been documented yet in RBD.

Methods: We collected 24 cases of nonviolent behaviors during idiopathic and symptomatic RBD (narcolepsy, dementia with Lewy bodies, PD), reported or observed in videopolysomnography. The frequency of violent and nonviolent behaviors during RBD was evaluated by face to face interview of patients and their cosleepers in a prospective series of 100 patients with PD.

Results: Incidental cases of nonviolent behaviors during RBD included masturbating-like behavior and coitus-like pelvic thrusting, mimicking eating and drinking, urinating and defecating, displaying pleasant behaviors (laughing, singing, dancing, whistling, smoking a fictive cigarette, clapping and gesturing “thumbs up”), greeting, flying, building a stair, dealing textiles, inspecting the army, searching a treasure, and giving lessons. Speeches were mumbled or contained logical sentences with normal prosody. In PD with RBD (n ⫽ 60), 18% of patients displayed nonviolent behaviors. In this series (but not in incidental cases), all RBD patients with nonviolent behaviors also showed violent behaviors. Conclusions: Although they are less frequent than violent behaviors, nonviolent behaviors during REM sleep behavior disorder (RBD) fill a large spectrum including learned speeches and culturespecific behaviors, suggesting they proceed from the cortex activation. Sexual behaviors during RBD may expose patients and cosleepers to forensic consequences. Neurology® 2009;72:551–557 GLOSSARY PD ⫽ Parkinson disease; RBD ⫽ REM sleep behavior disorder.

REM sleep behavior disorder (RBD) is characterized by abnormal behaviors corresponding to enacted dreams. These behaviors emerge during REM sleep and may cause injury or sleep disruption. During RBD, there is a loss of the physiologic REM sleep-associated muscle atonia. Sleep monitoring demonstrates an excess of phasic or tonic muscle activity during REM sleep.1,2 Chronic RBD can be idiopathic or associated with various neurologic conditions, including narcolepsy and neurodegenerative diseases.3-6 In addition, idiopathic RBD frequently predates synucleopathies.5,7 The behaviors during RBD are various, nonstereotyped, and complex. They include talking, laughing, shouting, swearing, yelling, crying, gesturing, reaching, grabbing, arm flailing, slapping, punching, kicking, jerking, strangulating, thrashing, sitting up, leaping from bed, crawling, and running.8-11 Most descriptions emphasize on forceful motor behaviors during RBD, usually associated with an unpleasant, action-filled, violent aspect of dreams.9,12 Typically, the individuals or their spouses are being pursued or attacked by Supplemental data at www.neurology.org From the Sleep Disorders Unit, Pitie´-Salpeˆtrie`re Hospital, APHP, Team 106, CRICM, and Paris 6 University, France. Supported by a grant from Fe´de´ration pour la Recherche sur le Cerveau, 2006-02. Disclosure: The authors report no disclosures. Copyright © 2009 by AAN Enterprises, Inc.

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unfamiliar people or animals. In contrast, nonviolent RBD such as laughing or quietly gesturing are rarely reported. Moreover, chewing, feeding, drinking, urinating, defecating, or performing a sexual behavior have yet not been documented in patients, mirroring an animal model of RBD.2,13 The abnormal motor behaviors during REM sleep parallel abnormal dreaming. Indeed, patients with RBD remember an increased proportion of dreams with aggressive contents compared to controls, despite normal levels of daytime aggressiveness.12,14 These observations led several authors to suggest that RBD would proceed from archaic defense generators and other locomotor generators in the brainstem.6,15 We wondered whether violent RBD may be more easily detected and referred to a physician than nonviolent behaviors. Hence, nonviolent RBD could be underestimated. We recently observed several cases of nonviolent RBD, including eating and sexual behaviors. They are reported here. In addition, we used our systematic interview of a series of 100 consecutive patients with PD to determine the frequency of nonviolent RBD. METHODS We retrospectively collected 24 cases of nonviolent RBD observed in the Sleep Disorders Clinic during the last 2 years. Nonviolent RBD were defined as behaviors that would be usual and perceived as nonaggressive in normal, awake life (e.g., eating, clapping, smoking) whether associated with a dream recall or not. When a given behavior was not previously experienced during normal life (e.g., flying, being a police-duck), the perception by the patient that the dream/behavior was nonviolent was sufficient. All cases had a history of clinical RBD if their bed partners reported purposeful limb or body movements (as if patients were acting out their dreams) associated with a dream recall. RBD was proved on videopolysomnography (enhanced chin muscle tone or complex movements during REM sleep) in 18 of 24 patients, while 6 patients with PD had not been monitored. We determined in a previous PD series, using a two-step procedure, that our face-to-face interview had a 97.2% positive predictive value for the diagnosis of polysomnographyproved RBD.16 In order to minimize the risk of including patients with RBD combined with sleepwalking (the overlap syndrome,17 which has been reported in rare, isolated cases of PD),18 we checked for any abnormal behaviors emerging from slow wave sleep in monitored patients. In the other patients with PD, we requested 1) no history of sleepwalking even as a child; 2) no behavior of getting out of bed or walking at home; 3) a clear memory of the corresponding, elaborated dream scenario; and 4) age greater than 50 years. We also estimated the prevalence of nonviolent RBD in a prospective series of 100 unselected patients with PD and their 552

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spouses, who were systematically interviewed about clinical RBD (60 positive patients). Among them, 36 of 60 patients underwent a videopolysomnography which documented either enhanced chin muscle tone or RBD. All enacted dream reports were collected, which brought a median of two dreams per patient. Patients with clinical RBD were split into two groups: those with exclusively violent RBD and those with at least one report of nonviolent RBD. We compared the demographic, clinical, and treatment characteristics in both groups. The clinical evaluation included RBD severity,19 depression (Beck Depression Inventory),20 cognition (Mini-Mental State Evaluation and Frontal Assessment Battery),21,22 motor disability (Unified Parkinson’s Disease Rating Scale–III while treated),23 daytime aggressiveness (evaluated by bed partner), and daytime sleepiness (Epworth Sleepiness Scale score).24 The patients signed an informed consent for the prospective study that was approved by the local ethics committee. The case reports and videos of RBD were shown to the patients, who gave written consent for their publication in this journal. The demographic, clinical, and treatment characteristics of patients with PD were compared using the ␹2 test for qualitative measures (with Yates correction when appropriate) and Student t test for quantitative measures.

A 74-year-old retired carpenter had typical narcolepsy/cataplexy for 51 years. He had three sleepwalking episodes as a child but never deambulated as an adult. He was referred to the Sleep Disorders Unit when sleepiness and hallucinations worsened. He was treated with modafinil and clomipramine. Incidentally, his wife reported some typical, nonviolent nocturnal behaviors. He would frequently enact behaviors related to his former job, giving orders to his employees. Once he pushed his wife out of the bed, digging in the sheets, while he was dreaming that he was digging up a treasure. The couple never consulted a doctor for these behaviors. During the videopolysomnography, REM sleep was a single, 115-minute-long episode at the end of the night, with a complete loss of atonia (figure). The next morning, he reported having drawn and then built a stair with a plank in a dream. On the video, his eyes were closed and he exhibited sequences of complex, nonstereotyped behaviors during REM sleep (video, patient 1). He would shake an invisible hand, while he introduced himself as “I am Mr. Do.” Later, he seemed to draw while whistling, to measure, pull, and then hit something with a fictive hammer. He said in Spanish (his mother tongue) “One, two, three” and moved his arms as if he were dancing. He whistled and said in French “Get up! Eh, eh (laughing).” Although he quit smoking 4 years ago (ex-heavy smoker for 60 years), he quietly mimicked smoking during the RBD, expired the smoke, and scratched a fictive cigarette, with a relaxed attitude (crossed legs and rocking foot). He also scratched himself in his pajamas and seemed to briefly masturbate, with regular, 25-second lasting, backwards and forwards motions of the hand in the pajamas. He did

RESULTS Patient 1.

Figure

Polysomnographic recordings

year, although he had no prostatism, nocturia, or polyuria and did not take clonazepam. He indeed dreamed that he was urinating, as a young man, in the Senegal River. During the videopolysomnography, there were three episodes of REM sleep, all of them without atonia, but movements occurred mainly during the last episode. These behaviors, which occurred with eyes closed, were complex, various, and usually accompanied with sentences resembling a teacher with children (first sequence) or a captain inspecting his troop (second sequence): “(Professorial) Can we all return to our seats! (pause) (Overbearing) What do you do, standing there in the middle? (pause) Remove your finger away from the switch! (pause) Well, if that’s so, I’ll take the numbers. (Ironic) And . . . late! (pause). (Professorial) Get back to your seats. I’m going to start.” Mumbles for 6 minutes. Then: “(bossy) Raise your hands, raise your hands, raise your hands, I said raise! I didn’t say to pull away! I said: raise your hands!” Here the patient quickly raised his left arm and waved his hand it as if he were showing something. “(Bossy and rhythmic) Halt! (pause) Halt! (pause) Halt!” Three minutes later, he shouted “(Bossy, like in a military parade) Attention! Gentleman, please, attention! (pause) Halt, halt, I said! (pause) Halt, I said!” (video, patient 2). Patient 2 spoke here with a loud and clear voice, but other speeches were shorter or muttered. He did not urinate during the polysomnography. Nonviolent RBD in clinical practice. In our RBD da-

Two examples of the polysomnographic recordings while patient 1 (A) and patient 2 (B) exhibited nonviolent behaviors during REM sleep. They include from the top to the bottom the EEG (Fp1-A2, C3-A2, C3-O1), eye movements (EOG1, EOG2), and EMG (chin, left and right anterior tibialis muscles). (A) Two-minute period of REM sleep. There is an intermittent loss of chin muscle atonia, with muscle bursts corresponding to speeches (gives orders). (B) Thirty-second period of REM sleep, including sawtooth waves, eyes in opposition of phase, and intermittent loss of atonia, during which the patient speaks.

not report any associated sexual dream, but was not awakened at that very moment. Patient 2. A 76-year-old retired civil servant at the Department of Defense had a mild, probable dementia with Lewy bodies for 1 year. He had abnormal movements several times per night, every night for 2 years, gesticulating, speaking about his family, and grumbling. He never injured himself but had already hit his wife while asleep. He used to play basketball and football and many of his night behaviors were linked to his sport activity. His wife reported he would urinate at home twice a month while asleep, and had defecated twice a

tabase, we found 11 additional patients (aged 33 to 76 years) with nonviolent RBD (table 1 and video). They did not complain of these behaviors, contrary to the violent behaviors. RBD was idiopathic in four patients, associated with parkinsonism in six patients, and associated with narcolepsy in one patient. There were newly described behaviors, included eating a fictive soup (video, patient 3), making business and deal, collecting apples, greeting friends, clapping at a show (video, patient 10), and displaying pelvic, coitus-like thrusting (video, patient 12). This last patient also swore profanities at home during the night, but he did not remember any sexual dreams for several years, and did not attempt to rape or have sex with his wife. Frequency and characteristics of nonviolent RBD in PD. In

the group of 60 patients with PD and clinical RBD, 11 (18%) patients exhibited nonviolent enacted dreams (examples in table 2). Among them, 6 patients had no videopolysomnography, but their clinical history strongly supported the diagnosis of RBD in the context of PD, including elaborate movements with closed eyes and inappropriate use of the enviNeurology 72

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Table 1 Patient no.

Types of nonviolent behaviors during the RBD Age, y/sex

Condition

3

86/M

PD

4

33/F

5

Behaviors on video (or reported), and “verbatim”

Associated dream

Violent RBD

Quietly eats and swallows a fictive soup (video)

Did not remember

No

Narcolepsy/cataplexy

“It’s not a good deal (pause). I don’t know what happens to him, I don’t know,” with associated verbal gesticulating and shrugging

Bought a bike

Yes

69/F

Idiopathic

Grabs her husband’s head

Was picking apples

No

6

66/M

Idiopathic

“Someone I know told me (mumbling). Put it six folds, six folds (pause). Listen, 2.30 meters (pause). Give me 500 Euros (pause). Everything is displayed here (two folds, then pause). That’s a 110,000 Francs deal (pause). Super quality, eh?” The speech is synchronized with appropriate gestures (points his finger, measures with his hands, flails arms)

Was selling fabric (his daily business)

Yes

7

68/M

Idiopathic

“Who’s rung the bell? Who has rung?” Later: “Hello” while shaking an invisible hand and sitting on his bed

Met an eminent politician, who told him “What, don’t you greet your old friend?” So he greeted him

Yes

8

76/F

Guadeloupean parkinsonism

Laughs, “Hello, how are you? (pause) I didn’t see him leaving” (in West Indies dialect), gesticulated

Gossip with a neighbor

Yes

9

67/F

PD

Cries, then laughs

Did not remember

Yes

10

70/M

Idiopathic

Claps hands, followed by a “thumbs up” gesture (video)

Did not remember

Yes

11

76/M

Lewy body disease

Handles out and throws invisible, small objects

Was sorting buttons in different barrels, for a top designer (Christian Dior, his former job)

Unknown

12

76/M

PD

Displays repetitive pelvic thrusting resembling coital behavior (video); swears profanities

Did not remember

Yes

13

71/M

PD

Verbal gestures

Was in a meeting, developing new projects in mining (his former job)

No

RBD ⫽ REM sleep behavior disorder; PD ⫽ Parkinson disease.

ronment, observed at the end of the night by the caregiver, and congruent with clearly reported, complex dreams. All patients with nonviolent RBD also experienced violent enacted dreams, during the same or during different nights. The other 49 (82%) patients reported only violent enacted dreams. There were no demographic, clinical, or treatment differences between the violent and nonviolent group, except for an older age in patients with nonviolent RBD (table 3). Except for patient 1, no patient had a history of sleepwalking, confusional arousal, or sleep terror. In the patients who underwent videopolysomnography, there was no EEG epileptiform activity. Some patients show awakenings during slow wave sleep, not preceded by hypersynchronous delta waves, and not associated with any abnormal behavior. 554

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This catalogue of nonviolent behaviors associated with idiopathic and symptomatic RBD is an unusual, overlooked aspect of RBD. They include coitus-like pelvic thrusting and masturbatinglike behavior, mimicking eating and drinking, urinating and defecating, displaying pleasant behaviors (laughing, singing, dancing, smoke a fictive cigarette, clapping, and gesturing thumbs up), greeting, flying, performing one’s job, ordering soldiers, and giving lessons. Most of the behaviors are visible on videopolysomnography. The frequency of nonviolent behaviors is 18% in a systematic, prospective series of 60 patients with PD and RBD. In this series (but not in incidental cases), all RBD patients with nonviolent behaviors also display violent behaviors. Eating or displaying coitus-like behavior has been described in sleepwalkers (but with real food intake, not fic-

DISCUSSION

Table 2

Description of nonviolent behaviors during RBD in a consecutive series of 60 patients with Parkinson disease

Patient no.

Observed behaviors during the RBD (dream content)

14

Sits on the bed, singing, with a wide smile on his face. Laughs.

15

Punches his wife (flew in the sky with his feet forward, slowed down with his arms opened, in order to avoid a wall). Kicks his wife (played soccer). Laughs.

16

Speaks about his past job as a cameraman, seems to shoot scenes.

17

Sings. Makes long, moral speeches (gave lessons of appropriate behavior to young people) .

18

Laughs.

19

Talks with a childlike voice.

20

Squats on the bed, waves his arm as if was flying, shouts “pin pon” (the two-tone sound of a siren) with a duck’s voice (he was a police-duck pursuing a pigeon-thief). Test his students (he’s a teacher) giving as topic paper: “1/Liberty, 2/ Economy, and 3/How liberty and economy are exploited by men and women?” (equivalent dream). Laughs.

21

Speaks about professional matters (he is an engineer). Seems to drink a coffee and to eat.

22

Gives a conference in English (her mother language is French).

23

Gives authoritative orders (working [was the boss in his company]).

24

Shoots scenes of a movie, talks to the filmmaker and to technicians (is a former movie-maker).

RBD ⫽ REM sleep behavior disorder.

tive). In addition, rare cases of overlap syndrome have been recently reported in patients with PD.18 Yet one may wonder if some of the behaviors we observed could not belong to the borderland of RBD, including the overlap syndrome, the confused behaviors associated with arousal from sleep apnea,25 or the status dissociatus (a loss of identifiable sleep stages associated with dream enactment).2 We took several cautions to avoid these pitfalls. First, the patients had scorable sleep stages, and did not display any abnormal behavior during non REM sleep, or during arousals from sleep (even associated with an apnea). In addition, none of them walked or stood up at home or in the sleep laboratory. Third, the patients did not handle their environment appropriately and had their eyes closed (while the eyes are open during sleepwalking). Eventually, the abnormal behaviors preferentially happened at the end of the night. Consequently, we are confident that our patients had RBD and no other parasomnia. Interestingly, both men and women had nonviolent behaviors, suggesting no gender influence on enacted dream. Some nonviolent behaviors during RBD were previously reported. In a series of 67 pa-

tients with RBD, a minority of patients reported sports (2%) and adventure (9%) dreams, without aggressive content.8 A woman who sings the “Star Spangled Banner” and pedals in bed like on a bicycle while asleep was also described.26 However, this was a single case among numerous violent RBD cases. The 18% frequency of nonviolent RBD that we found in the series of patients with PD may be more realistic, but probably still underestimates nonviolent behaviors. Nonviolent behaviors are less susceptible to cause arousal or injure the patients and their cosleepers than violent behaviors. Moreover, the dreams associated with nonviolent RBD may also be less vivid and therefore less memorized. These reasons may account for the previous underestimates of nonviolent behaviors during RBD. Similarly, in a detailed analysis of five patients with PD plus RBD, only 3.6% of movements on video and sleep monitoring were violent.27 One may therefore wonder if the nonviolent behaviors constitute a genuine disorder, when they are pleasant, not vivid, and poorly disturbing. The fact that they are associated with violent behaviors (systematically in PD, and occasionally in other cases) argues against a distinct disorder. Furthermore, some patients (e.g., patient 13) developed parkinsonism after several years of displaying exclusively nonviolent RBD. As there is an ongoing awareness that RBD can precede, by several years, the first symptoms of parkinsonism or dementia, the underestimated nonviolent symptoms may be the first step of a neurodegenerative process, even without the altered dreaming previously described. The coitus-like thrusting behavior observed in patient 12 could be confused with a rhythmic movement disorder, as similar pelvic thrusting has been documented at sleep onset in an elderly patient with restless legs syndrome.28 Furthermore, rhythmic head rolling (but not pelvic thrusting) was found in two patients with otherwise complex RBD.29 In patient 12, the pelvic movements are not regular in frequency and amplitude, suggesting they are rather coitus-like than just rhythmic. There are however no associated sexual dreams, at least remembered by the patient, mirroring the findings that RBD patients never experience sexual dreams.12 So far, only sexsomnia associated with sleepwalking has been in cause in forensic cases.30 Three cases of amnesic sexual behavior in young men have been classified as RBD on the basis of enhanced muscle tone during REM sleep,31 but they are not supported by sleep video monitoring, old age, and corresponding sexual dream recall. Since patients with RBD rarely stand up, do not use their environment appropriately (e.g., cannot take a knife or open a door), and would wake up without confusion when alerted by their cosleepNeurology 72

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Table 3

Demographic and clinical characteristics of 60 consecutive patients with Parkinson disease and exclusively violent or combined nonviolent/violent RBD

Group

Nonviolent and violent RBD

Exclusively violent RBD

No. of patients (%)

11 (18.3)

49 (81.7)

Age, y

69.3 ⫾ 5.0

63.7 ⫾ 10.3

0.013

Sex, % male

73

69

NS

RBD severity (% with severe RBD)

9.1 (1/11)

34.7 (17/49)

NS

Mini-Mental State Examination Score (score/30)

28.1 ⫾ 1.4

27.9 ⫾ 2.5

0.76

p

Frontal Assessment Battery (score/18)

16.0 ⫾ 1.0

16.0 ⫾ 2.1

0.92

Beck Depression Inventory (score/39)

10.6 ⫾ 6.2

10.8 ⫾ 6.8

0.96

Motor disability* (score/108)

18.3 ⫾ 10.0

21.7 ⫾ 12.1

0.35

Levodopa-equivalent dose, mg/d

929 ⫾ 633

603 ⫾ 317

0.13

Domineering/aggressive daytime personality (% patients)

27.3 (3/11)

8.2 (4/49)

NS

7.5 ⫾ 2.9

9.4 ⫾ 4.7

Antidepressant use (% patients)

27.3 (3/11)

28.6 (14/49)

NS

Benzodiazepine use (% patients)

36.4 (4/11)

20.4 (10/49)

NS

Epworth sleepiness scale/24

0.092

*Unified Parkinson’s Disease Rating Scale, part III. RBD ⫽ REM sleep behavior disorder.

ers, they may be at lower risk of forensic sexual behaviors and rape than with sleepwalkers with sexsomnia. Urination and defecation have also not been documented during RBD. In our series, a single patient reports these two behaviors, but they are infrequent and were not observed during the singlenight sleep recording. While urinating, he has a corresponding elaborate dream. Some cases of enuresis in elderly subjects could therefore be associated with RBD. This rich, various catalogue of nonviolent behaviors can give several objective indications about dreams (owing to the isomorphism between dream content and explicit behavior), and about central pattern generator during REM sleep. Most nonviolent behaviors are complex and correspond to learned procedures rather than to innate behaviors. Patient 3 does not eat in a greedy way, but manipulates his invisible spoon as a socialized man. Patient 10 claps and places his hand in the “thumbs up” position, a culturally acquired gesture. Most patients practice their usual work (whether they are retired or not) during RBD, leading to behaviors as complex as manual works (building a stair, sorting buttons) or more intellectual works (dealing fabric, giving lessons or orders, and planning development in a mine project). Patients seem to replay enacted dream schemes performed year after year, while awake, and perfectly mastered, suggesting a release of learned, engraved programs (and not only recently acquired procedures), that suggests an activation of the frontal 556

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lobe. The pleasant emotions associated with laughing or smoking suggest that the limbic system could also be activated during nonviolent RBD. Most patients speak during RBD, sometimes quite easily, supporting an activation of cortical language areas. Indeed, the tone of voice suits the meaning of the sentences. Patient 2 gives orders with a loud, explosive voice that characterizes the imperative tone. The prosody is also maintained. Singing is possible with correct musicality (patients 14 and 17). The local accent is maintained (patient 8 speaks with the French West Indies dialect and the typical “singing” tone). Furthermore, patients can modulate their voices according to the dream context (child voice or duck voice, for example) and use foreign languages (patient 1). The ability to speak can sometimes be close to their way of speaking when awake, and even better.16 Some patients with PD16 or supranuclear palsy32 are indeed almost anarthric while awake, and suddenly able to speak loudly during RBD. Most patients, however, mutter unintelligible words, while others move lips as if speaking without any sound emission, suggesting that some outputs of the vocal system remain blocked or bypassed during RBD. Interestingly, when the dreamers speak with one or several persons (patients 2, 6, 8), they leave an appropriate silence as if listening to a response from their fictive talker. This means that the dreamers speak only those words which, in the dream, they experience as their own. Remarkably, the speech is quasi-constantly accompanied by gestures corresponding to appropriate culture-specific nonverbal communication. The presence of appropriate prosody, gesturing, fluency, and syntax suggests that cortical language networks are partially functional during REM sleep. Received June 13, 2008. Accepted in final form October 30, 2008.

REFERENCES 1. Schenck CH, Bundlie SR, Ettinger MG, Mahowald MW. Chronic behavioral disorders of human REM sleep: a new category of parasomnia. Sleep 1986;9:293–308. 2. American Academy of Sleep Medicine. The International Classification of Sleep Disorders–Revised. Chicago, IL: American Academy of Sleep Medicine; 2005. 3. Schenck CH, Mahowald MW. Motor dyscontrol in narcolepsy: rapid-eye-movement (REM) sleep without atonia and REM sleep behavior disorder. Ann Neurol 1992;32: 3–10. 4. Gagnon JF, Bedard MA, Fantini ML, et al. REM sleep behavior disorder and REM sleep without atonia in Parkinson’s disease. Neurology 2002;59:585–589. 5. Iranzo A, Molinuevo JL, Santamaria J, et al. Rapid-eyemovement sleep behaviour disorder as an early marker for a neurodegenerative disorder: a descriptive study. Lancet Neurol 2006;5:572–577.

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Boeve BF, Silber MH, Saper CB, et al. Pathophysiology of REM sleep behaviour disorder and relevance to neurodegenerative disease. Brain 2007;130:2770–2788. Schenck CH, Bundlie SR, Mahowald MW. Delayed emergence of a parkinsonian disorder in 38% of 29 older men initially diagnosed with idiopathic rapid eye movement sleep behaviour disorder. Neurology 1996;46:388–393. Olson EJ, Boeve BF, Silber MH. Rapid eye movement sleep behaviour disorder: demographic, clinical and laboratory findings in 93 cases. Brain 2000;123:331–339. Schenck CH, Mahowald MW. REM sleep behavior disorder: clinical, developmental, and neuroscience perspectives 16 years after its formal identification in SLEEP. Sleep 2002;25:120–138. Sforza E, Krieger J, Petiau C. REM sleep behavior disorder: clinical and physiopathological findings. Sleep Med Rev 1997;1:57–69. Ferini-Strambi L, Fantini M, Zucconi M, et al. REM sleep behaviour disorder. Neurol Sci 2005;26:s186–192. Fantini ML, Corona A, Clerici S, Ferini-Strambi L. Aggressive dream content without daytime aggressiveness in REM sleep behavior disorder. Neurology 2005;65:1010–1015. Sastre J, Jouvet M. Oneiric behavior in cats. Physiol Behav 1979;22:979–989. Borek LL, Kohn R, Friedman JH. Phenomenology of dreams in Parkinson’s disease. Mov Disord 2007;22:198– 202. Tassinari CA, Rubboli G, Gardella E, et al. Central pattern generators for a common semiology in fronto-limbic seizures and in parasomnias: a neuroethologic approach. Neurol Sci 2005;26 suppl 3:s225–232. De Cock VC, Vidailhet M, Leu S, et al. Restoration of normal motor control in Parkinson’s disease during REM sleep. Brain 2007;130:450–456. Schenck CH, Boyd JL, Mahowald MW. A parasomnia overlap disorder involving sleepwalking, sleep terrors, and REM sleep behavior disorder in 33 polysomnographically confirmed cases. Sleep 1997;20:972–981. Poryazova R, Waldvogel D, Bassetti CL. Sleepwalking in patients with Parkinson disease. Arch Neurol 2007;64: 1524–1527. Iranzo A, Santamaria J, Rye DB, et al. Characteristics of idiopathic REM sleep behavior disorder and that associated with MSA and PD. Neurology 2005;65:247–252.

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Beck AT, Ward CH, Mendelson M, et al. An inventory for measuring depression. Arch Gen Psychiatry 1961;4:561–571. Folstein MF, Folstein SE, McHugh PR. “Mini-mental state”: a practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res 1975;12:189– 198. Dubois B, Slachevsky A, Litvan I, Pillon B. The FAB: a Frontal Assessment Battery at bedside. Neurology 2000; 55:1621–1626. Fahn S, Elton RL, members of the UPDRS Development Committee. Unified Parkinson’s Disease Rating Scale. In: Fahn S, Marsden CD, Goldstein M, Calne DB, eds. Recent Developments in Parkinson’s Disease. Vol. II. Florham Park, NJ: Macmillan; 1987:153–163. Johns MH. A new method for measuring daytime sleepiness: the Epworth Sleepiness Scale. Sleep 1991;14:540– 545. Iranzo A, Santamaria J. Severe obstructive sleep apnea/ hypopnea mimicking REM sleep behavior disorder. Sleep 2005;28:203–206. Schenck CH. Paradox Lost: Midnight in the Battleground of Sleep and Dreams. Minneapolis: Extreme-nights, LLC; 2005. Frauscher B, Gschliesser V, Brandauer E, et al. Video analysis of motor events in REM sleep behavior disorder. Mov Disord 2007;22:1464–1470. Lombardi C, Provini F, Vetrugno R, et al. Pelvic movements as rhythmic motor manifestation associated with restless legs syndrome. Mov Disord 2003;18:110–113. Manni R, Terzaghi M. Rhythmic movements in idiopathic REM sleep behavior disorder. Mov Disord 2007;22:1797– 1800. Schenck CH, Arnulf I, Mahowald MW. Sleep and sex: what can go wrong? A review of the literature on sleep related disorders and abnormal sexual behaviors and experiences. Sleep 2007;30:683–702. Guilleminault C, Moscovitch A, Yuen K, Poyares D. Atypical sexual behavior during sleep. Psychosom Med 2002; 64:328–336. Pareja J, Caminero A, Masa J, Dobato J. A first case of progressive supranuclear palsy and pre-clinical REM sleep behavior disorder presenting as inhibition of speech during wakefulness and somniloquy with phasic muscle twitching during REM sleep. Neurologia 1996;11:304–306.

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VIEWS & REVIEWS

A neurologist’s guide to genome-wide association studies

S.A. Mullen, MBBS D.E. Crompton, PhD P.W. Carney, BMed I. Helbig, MD S.F. Berkovic, MD, FRS

Address correspondence and reprint requests to Prof. Samuel F. Berkovic, Epilepsy Research Centre and Department of Medicine (Neurology), University of Melbourne, Austin Health, 145 Studley Rd., Heidelberg, Victoria 3084, Australia [email protected]

ABSTRACT

Genome-wide association studies are utilized for gene discovery in common diseases. Genotypes of large groups of unrelated patients are compared to controls. This has become feasible due to the recent technical advances in genomics and convincing positive results are now regularly being published. This review is an accessible introduction to the genetic and technical knowledge needed to interpret such studies. Genome-wide association studies are being applied to many neurologic diseases. Here we use idiopathic generalized epilepsy as an example to highlight the phenotyping, sample size, and statistical issues that must be addressed in such studies. These studies are likely to transform our understanding of complex neurologic diseases in the next few years. Neurology® 2009;72:558–565 GLOSSARY CAE ⫽ childhood absence epilepsy; CDCV ⫽ common disease-common variant; CDMRV ⫽ common disease-multiple rare variant; CNV ⫽ copy number variation; GTCS ⫽ generalized tonic-clonic seizures; GWAS ⫽ genome-wide association studies; IGE ⫽ idiopathic generalized epilepsy; JAE ⫽ juvenile absence epilepsy; JME ⫽ juvenile myoclonic epilepsy; LD ⫽ linkage disequilibrium; MS ⫽ multiple sclerosis; RLS ⫽ restless legs syndrome; RR ⫽ relative risk; SNP ⫽ single nucleotide polymorphism.

Enormous advances in understanding the molecular basis of Mendelian genetic diseases have recently occurred. Despite this, the genetic bases of complex diseases, diseases in which multiple genetic and environmental factors combine to confer the disease state, remain illunderstood. Genome-wide association studies (GWAS) now appear to be unlocking this complexity (figure 1). GWAS aim to survey the entire genome for common variants that might underlie genetic disease. These studies rely upon genetic and statistical principles which have suddenly acquired direct relevance to a broad range of clinicians and researchers. We begin by discussing the theory underpinning GWAS and review recent GWAS successes. We then consider the potential for a GWAS in idiopathic generalized epilepsy (IGE), highlighting principles pertinent to neurologic diseases. In dominant Mendelian conditions, the presence of a single copy of a mutated gene causes the disease; i.e., the mutation has a very high effect size. In autosomal recessive disorders, two mutant alleles of the same gene confer the disease state. The genes associated with these diseases have been identified by linkage analysis in large families. Linkage determines the section of genome shared by the affected family members. This shared region should then contain the mutation causing the genetic disease. Although the disease processes discovered may be broadly applicable, such conditions tend to be rare. The bulk of genetic morbidity is not transmitted in a Mendelian manner. When families of individuals with non-Mendelian genetic diseases (or complex diseases) are studied, close relatives are affected at rates in excess of the population frequency but without patterns of inheritance suggesting a single, causative gene. This is believed to be because multiple different alleles of multiple genes, combined with environmental factors, result in disease. Because there is

MENDELIAN AND COMPLEX GENETIC DISORDERS

From the Epilepsy Research Centre and Department of Medicine (Neurology) (S.A.M., D.E.C., P.W.C., I.H., S.F.B.), University of Melbourne, Austin Health, Heidelberg, Victoria, Australia; and Department of Neuropediatrics (I.H.), Christian Albrechts University, Kiel, Germany. Supported by an NHMRC program grant to S.F.B., an NHMRC postgraduate fellowship to S.M., a University of Melbourne Foundation scholarship to P.W.C., a UCB Pharma unrestricted clinical fellowship to D.E.C., and a Fritz-Thyssen-Stiftung postdoctoral scholarship to I.H. Disclosure: The authors report no disclosures. 558


Figure 1

Three ways of identifying disease-related genes

(A) Family linkage: A pedigree suggesting a single gene of major effect is required but prior knowledge of the pathophysiology of the disease is not. The chromosomal region shared by the affected members of the family can be determined in a family of sufficient size. By systematically sequencing genes in the shared chromosomal region, the critical mutation may be identified. To establish proof of causation, mutations in the same gene in unrelated families should be found or the mutation shown to result in a major effect on gene function. (B) Candidate gene sequencing: A gene of interest is chosen based on a biologic hypothesis for the disease. This gene is then sequenced in a large number of cases and controls to allow the detection of both common and rare variants (as illustrated by the blue asterisk). Not all variants are likely to have a biologic effect. A combination of lower frequency in controls and clearly altered function of the gene product is needed to infer a pathologic effect. (C) Genome-wide association: Instead of a gene of interest, genome-wide association attempts to survey the whole genome at once in a hypothesis-free manner. A very large number of case-control studies are performed in parallel by typing thousands of markers simultaneously in thousands of cases and controls. This will only detect common rather than rare variation. The single nucleotide polymorphism associations found are likely to be of modest effect. The connection to the pathophysiology of disease is more difficult to establish than in family linkage studies or candidate gene sequencing.

no single gene of major effect, conventional linkage is not applicable and other linkage approaches have been unsuccessful. GWAS is coming of age as a technique to interrogate this complexity. HUMAN GENETIC VARIATION AND HOW TO SAMPLE IT The human haploid genome contains ap-

proximately 3 billion DNA bases, encoding around 25,000 genes, divided among 23 chromosomes.1 Variation occurs at a number of levels. Gross changes in chromosomes detectable by karyotyping are not of relevance to complex disease genetics. At the molecular level there are two major classes of variation: copy number variation (CNV) and single nucleotide polymorphisms (SNPs).2,3 CNV are deletions or duplications of submicroscopic DNA segments. SNPs are single base positions where the sequence con-

tent varies among different chromosomes within a population. At any given base position four alleles are possible, but in practice no more than two alleles are commonly found. SNPs are measured in GWAS though SNPs and CNV can be measured together on current experimental platforms.4 A large amount of the genetic variation in the human genome is not thought to have pathologic consequences. The challenge is to identify those components of it which increase the risk of disease. The optimal approach would be to sequence whole genomes in patients and controls. This is not presently practicable, despite rapid progress. GWAS type a large number of SNPs as a surrogate of the total genomic variation. This relies upon alleles at adjacent SNPs tending to travel together in blocks through evolutionary time, a phenomenon known as linkage disequilibrium (LD). It follows that if we know a tagging SNP which is representative of each block of LD then we have a handle on total genomic variation.5 A helpful way to consider what tagging SNPs can and cannot tell us is to consider a simplified “SNP’s eye view” of evolution (figure 2A). The colored spots represent the sequence at a single DNA base within a population over hundreds of generations. The nucleotide has a single allele (blue) until a variant (yellow) arises in the population. The base thus becomes a SNP. Initially the new variant is rare but it is not heavily selected against so, by random chance over many generations, becomes frequent in the population. Let us now consider alleles conferring a large relative risk (RR) of disease (high effect-size) arising in the same LD block as our SNP. This is represented by a colored ring round the spot (figure 2C). Such high-risk alleles are likely to reduce the chance of a person reproducing, thus tending to be removed from the population.6 It follows that alleles conferring a high RR of disease in the present-day population (right hand row of figure 2C) will be evolutionarily recent. These have arisen at random on a background of ancient, benign polymorphisms; including, in this example, the blue or yellow SNP allele. GWAS utilize a case-control design.4 DNA is isolated from cases with disease and healthy controls from the same ethnic group. SNP allele frequencies are then compared between the two groups. Each SNP measured is essentially an epidemiologic risk factor, varying in frequency between the cases and controls. Current technologies cannot simultaneously measure every known SNP but can type a significant proportion. If LD holds true then measured SNPs act as tagging SNPs and should predict the majority of the rest of the SNPs.7,8 We can now consider a GWAS in which the SNP highlighted is one of hundreds of thousands whose Neurology 72

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Figure 2

Schematic illustration of a genome-wide association study in diseases due to common or rare variants

See text for details. GWAS ⫽ genome-wide association studies; SNP ⫽ single nucleotide polymorphism.

allele frequencies (blue vs yellow) are compared between cases and controls. The situation where the yellow SNP variant confers a small increased RR of disease is illustrated in figure 2B. This effect is presumed to be small enough that selection pressure would not remove the SNP. In this case the SNP would be seen at a higher rate in those with the disease, much as smoking rates are higher in heart disease. In figure 2D, the SNP is not a disease allele, merely adjacent to a number of high-risk alleles, each individually rare. These alleles will tend to be clustered within the disease group, but have arisen at random adjacent to a blue or yellow SNP allele. The SNP genotype is not then related to the disease, leaving the frequency of blue and yellow alleles the same in cases and controls. The SNP would therefore not be detected in a GWAS. It can be appreciated from this simple model that only common disease-associated alleles are expected 560

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to be detected by GWAS. The theory that such common variation underlies complex disease is known as the common disease-common variant (CDCV) model.9 Under CDCV, complex disease would be caused by multiple alleles, each with a RR around 1.2–2. For meaningful results in GWAS, the CDCV model must be at least partly true. To put these relative risks into perspective, other disease-associated alleles can be considered. In Mendelian diseases the measure of genetic risk is penetrance, the chance that a person carrying a mutation will have the disease. It is equally possible to describe Mendelian mutations by RR. The RR any allele confers also depends on the population risk of the disease. For instance, mutations of the gene coding for the ␣2 subunit of the Na/K-pump (ATP1A2) cause familial hemiplegic migraine; 90% of family members carrying a mutation have at least migraine with aura.10 This translates to a RR of migraine with aura of around 30 (90% vs 3% population risk). The ADassociated allele apolipoprotein E4 epsilon (APOE), discovered before the advent of GWAS, carries a RR of 4.11 GWAS have identified alleles with RR 1.2–2. Although this appears low in comparison with a Mendelian disease, hypertension, hypercholesterolemia, and smoking all confer RRs of coronary artery disease between 1.5 and 2.12 HOW TO PERFORM A GWAS Most GWAS have used a two-stage design. DNA is isolated from cases with disease, and from a control group. DNA from a subpopulation of cases and controls is then hybridized to quartz chips on which multiple oligonucleotide sequences flanking identified SNPs have been synthesized and differentially labeled according to the SNP variant. This allows hundreds of thousands of SNPs to be rapidly genotyped.13 This is followed by quality controls and analysis with statistical correction for the millions of simultaneous experiments as well as population stratification.14 Population stratification is difference in SNP frequencies between cases and controls due to systematic differences in ancestry rather than disease status. Numerical correction can be applied for this, though the confounding effect of population stratification appears to be lower than initially feared.15,16 SNPs showing potentially significant association with the disease are then retested in a second group of cases and controls. SNP selection for commercial platforms has used three main strategies.7 The tagging SNP approach is where SNPs are chosen to be representative of known LD blocks (e.g., Illumina HapMap 300 and HapMap 500).17 A dispersed approach selects approximately equally distributed SNPs to maximize physical

coverage of the genome, ignoring LD patterns (e.g., Affymetrix 111K and 500K). Platforms may include SNPs from both approaches.7,18 With modern platforms of over a million SNPs, there is effective genome coverage in Caucasian populations, where high LD makes tagging efficient. However, efficiency is lower in African and in geographically isolated populations.5,19

associations so that, although 20,000 cases may be required to guarantee identifying a given SNP, smaller studies may still identify a proportion of SNP associations. Again, in breast cancer a series of three GWAS were published near simultaneously. The smaller two with around 2,000 cases in their initial cohorts each detected a subset of the SNPs published by the massive study mentioned above.22,25,26

The main determinants of required sample size are the strength of the underlying association and the statistical threshold set for significance.20 The underlying association depends on both the potency of the allele to cause disease (expressed in the RR or the odds ratio) and the population frequency of the allele, neither of which can be known a priori. Statistical threshold is dependent on the corrections applied to account for multiple testing (expressed in the p value). A GWAS begins without an assumption as to which gene, or indeed noncoding region, is involved in the disease. It could include any one of the 25,000 predicted genes, each with its own parallel and independent hypothesis.21 To further complicate matters, SNP methods do not measure genes per se but alleles, multiplying the hypotheses in parallel by the number of common alleles per gene. Recent large GWAS have provided empirical justification for stringent p values. A recently reported, two-stage GWAS in breast cancer included over 25,000 cases and 25,000 controls.22 In the first stage, 4,000 cases and controls were genotyped. The most significant SNPs were retested in an independent sample of 21,000 cases and controls. This large study offers insight into the relationship between p values in stage 1 and confirmation in stage 2. No SNPs with a p value less stringent than 10⫺6 survived stage 2 and p values between 10⫺7 and 10⫺8 had some chance of failure. Hence, while it has been argued that p values as high as 10⫺5 may be sufficient in stage 1, there is increasing consensus that p values of 10⫺8 are required.16,23 Sample size calculations for GWAS are complex, requiring assumptions about both the potency of the alleles and their frequency in the population.24 For any given disease, such factors must be estimated as they cannot be measured without actually performing a GWAS. A reasonable place to start is with the alleles already identified. Altshuler and Daly23 calculated sample sizes required to have 90% power to repeat the findings of previous GWAS at a p value threshold of 10⫺8. The most strongly associated SNPs would individually require 2,500 cases and controls; most would need 10,000 –20,000. In many of the diseases studied so far there are multiple SNP

Traditional linkage in dominant disorders proceeds by finding the section of genome shared by affected family members.27 A mutation is likely to be found within the shared region of a few million bases. Mutations usually have significant differences in the protein product that alter function. The mutation thus found should be absent in controls. With a GWAS the interval found is in the thousands, rather than the millions, of bases. What this interval implies is also fundamentally different.16 The allele driving the association exists in many people with only a slightly increased frequency in those with disease. There is no shared region containing a single mutation of major physiologic effect but rather an epidemiologic indication that something nearby is of importance.28 Neither linkage nor association proves causation. To infer a causative role, pathologic alteration of protein function must be demonstrated.29 It is here that the proposed common allele-based mechanism of weak, additive effects becomes most experimentally challenging. With each allele conferring only a modest contribution to disease causation, experimental corroboration of a subtle biologic effect is expected to be difficult. This is illustrated by the type 2 diabetes associated gene, transcription factor seven-like 2 (TCF7L2).16,30-32 SNP loci spread through this gene have been identified from GWAS. The protein product of TCF7L2 is involved with transcription regulation in the gut and might influence glucose levels.33 It is not clear which one, or combination, of the identified SNPs confers the risk. Many SNPs are in strong LD so resolving statistically between them is difficult or impossible.30 Therefore not only is the effect small but the variant causing that effect is not clear. Even more difficult are results of the type seen in prostate cancer where a statistically convincing variation is seen in a region without any known genes.34,35 Although in time these results may offer fundamental information about the biology of this disease, at this stage that is only a potential. The biologic insight offered by an association finding is less immediate than for a mutation identified through linkage. Methods to assess the biologic function of common

POWER AND SAMPLE SIZE

RESULTS IN GWAS

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Table 1

Disease loci confirmed by genome-wide association studies in multiple samples

Disease

Gene or locus odds ratio (95% confidence interval)

Breast cancer22,25 Prostate cancer

34,35

FGFR2 (fibroblast growth receptor 2), 1.26 (1.23–1.30) 8q24, 1.71 (1.49–1.95)

Crohn disease37,56

IL23R (interleukin 23 receptor), 1.74 (1.57–1.85)

Type II diabetes30-32

TCF7L2 (transcription factor 7-like 2), 1.65 (1.46–1.84)

Type I diabetes28,57

PTPN22 (protein tyrosine phosphatase nonreceptor type 22), 1.80 (1.44–2.24)

Systemic lupus erythematosis58,59

ITGAM (integrin ␣ M), 1.62 (1.47–1.78)

Restless legs syndrome39

BTBD9 (BTB domain containing 9), 1.74 (1.57–1.92)

All loci have been replicated in independent populations (in single or multiple studies) and have p values of ⬍10⫺8 in more than one population. Only a single locus is given for each disease with odds ratio and 95% confidence intervals. For additional information, the National Institutes of Health maintain a comprehensive Web site of GWAS findings (www. genome.gov/26525384).

variants in complex disorders are in their infancy. Despite this difficulty, common variants are common and, although their effect sizes are individually modest, collectively they contribute greatly to the population burden of disease. GWAS IN NEUROLOGIC DISEASES GWAS have

already demonstrated a number of robust associations in different diseases (table 1), including neurologic conditions (table 2). In ALS, a SNP in the gene encoding dipeptidyl peptidase 6 (DPP6) has shown an association passing the 10⫺8 threshold.36 DPP6 is a plausible candidate that modifies potassium channel function and neuropeptide activity. In multiple sclerosis (MS), a SNP in the gene for an interleukin receptor (IL2RA) has been identified in a single sample.37 Both of these intriguing findings await replication. In restless legs syndrome (RLS), a number of loci have been identified within one gene, BTB domain containing 9 (BTBD9), passing p ⬍ 10⫺8 in two studies.38,39 Both studies were quite small, with one having only 300 cases. This is remarkable given the 4,000 used for MS and the retrospective estimates of 2,500 to 20,000 mentioned above. The use of a geTable 2

Disease loci identified by genome-wide association studies in neurologic conditions and awaiting confirmation

Disease

Gene or locus odds ratio (95% confidence interval)

Multiple sclerosis37

IL2R␣ (interleukin 2 receptor ␣ subunit), 1.25 (1.11–1.36)

Amyotrophic lateral sclerosis36

DPP6 (dipeptidyl peptidase VI), 1.30 (1.18–1.43)

APOE*e4 carriers with late onset Alzheimer disease60

GAB2 (GRB2-associated binding protein 2), 4.06 (2.81–14.69)

These loci have p values less than or equal to 10⫺8 but have not yet been independently replicated. Only a single locus is given for each disease with odds ratio and 95% confidence intervals. 562

netically relevant phenotype, RLS with documented periodic leg movements, as well as the isolated Icelandic population are likely to have helped. Although these studies were successful, a sample size of 300 is probably too low in most cases.

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A GWAS FOR IDIOPATHIC GENERALIZED EPILEPSY In many neurologic diseases, such as mi-

graine and RLS, the diagnosis is based on clinical grounds, while for others the pathology is known but difficult to measure antemortem. The right phenotype selection can significantly influence outcome in GWAS, as the success in RLS illustrates. However, what the right phenotype is may not be obvious beforehand. IGE is used to highlight the challenges of phenotype selection and sample size but similar questions of subclassification and strength of genetic contribution might apply to migraine, Parkinson disease, or a variety of other neurologic illnesses. Idiopathic generalized epilepsy accounts for approximately one quarter of all epilepsies. IGE is characterized by occurrence in an otherwise normal individual of generalized seizure types and generalized EEG abnormalities.40 IGE is further subdivided by age at onset and predominant seizure type. IGE has a strong genetic contribution, demonstrated in twin studies.41 Most cases of IGE are sporadic and believed to be due to complex inheritance. The risk to siblings is increased by a factor of 4 –9 compared to the general population.42 This is a similar sibling risk increase to that in migraine with aura or MS.43,44 In multiplex families, if the proband has absence seizures, relatives are more likely to have absence rather than myoclonic seizures and vice versa.45 Twin data support this; monozygotic twins concordant for IGE are also concordant for subsyndrome while only 25% of dizygotic twins are similarly concordant.46 This tendency suggests some distinct genetic determinants for different subsyndromes, or at least for different seizure types. However, this phenomenon is not absolute and the relative contribution of distinct and shared genetic factors in IGE subsyndromes is unknown. Most known Mendelian epilepsies are due to mutations of ion channels, including rare families with Mendelian inheritance of IGE and the closely related disorder of generalized epilepsy with febrile seizures plus.42,47,48 Ion channel genes have therefore been a major focus of candidate gene association studies. This has failed to provide convincing, reproducible results in common IGE.49,50 It is plausible that common variants contribute to the genetic architecture of IGE, making it an attractive disease for a GWAS. GENETICS OF IGE

ENSURING A GENETICALLY HOMOGENEOUS PHENOTYPE IGE and its subsyndromes are diag-

nosed using clinical and electrographic criteria; a GWAS could use the broad IGE phenotype, subsyndromes, or seizure types as the phenotype. If the shared genetic contribution to IGE subsyndromes is minor, then using the broad IGE phenotype for a GWAS would likely fail. The use of subsyndromes, however, is difficult for at least two reasons. First, exact diagnostic boundaries of these conditions do not exist.40 For instance, juvenile myoclonic epilepsy (JME) is an IGE with myoclonus with or without generalized tonic-clonic seizures (GTCS) and absence seizures; juvenile absence epilepsy (JAE) is an IGE with absence with or without myoclonus and GTCS. The point at which a patient crosses from myoclonus with absence to absence with myoclonus and thus from JME to JAE is clinically arbitrary and without known biologic basis. Second, cohorts of patients with subsyndrome phenotypes are smaller. Another approach is to use seizure types without reference to subsyndromes.51 This is precise and reproducible but loses some of the resolution of syndromic diagnosis. For example, childhood absence epilepsy (CAE) and JAE would appear in the same diagnostic category despite the better prognosis of the childhood form. Moreover, classifying individuals with two or more seizure types becomes problematic. IGE has a cumulative incidence around 0.25%, so the pool of patients to recruit from may be limited.52 Using the ballpark estimates of sample sizes discussed above, a definitive GWAS with 20,000 cases would require 2.5% of the people with IGE in the United States to enroll.52 If CAE were the phenotype, then 25% of affected subjects nationwide would be needed. A smaller study may well yield some results but would still need a large, multicenter collaboration. It is not clear whether a broad IGE, modified subsyndrome, or seizure-based categorization is more likely to yield results. ALTERNATIVES TO A GWAS GWAS assume that the common disease-common variant model is at least partly true for the disease under investigation. The main alternative hypothesis is that complex disease is caused by multiple rare variants, the common disease-multiple rare variant (CDMRV) model.53 Under CDMRV, a small number of alleles with RR around 5–10 contribute to disease in an individual. Testing of the CDMRV hypothesis involves detection of rare variants with high-throughput sequencing of candidate genes.54 High-throughput

sequencing is a methodologic advance over older candidate gene studies but is still limited by a preordained gene list without the potential for novel discovery inherent in a GWAS. The results may also be difficult to interpret. Any given variant may be rare so that demonstrating an association with the disease requires studying many control chromosomes. Functional validation is still needed but may be easier due to high effect sizes. The relative contribution of common and rare variants is unknown for most complex diseases. The common variant hypothesis can now be tested by GWAS; the methodology for this is robust. While GWAS results are appropriately generating great excitement, successful studies to date explain only a fraction of the genetic risk. Given this, testing a SNP profile and extrapolating to an individual’s risk of disease is not yet possible, although it may become so. How that information should be used, both in terms of privacy and for personalized medicine, remains an open question and is the subject of a proposed clinical study into public attitudes.55 We have used IGE as a case study in this review but comparable challenges of phenotype definition, sample size, and functional validation are applicable to many other neurologic conditions. Furthermore, the challenge of deciphering the biologic implications of alleles identified through GWAS means that a SNP association is a beginning rather than an end in itself. Despite these caveats, GWAS are yielding novel genetic discoveries that promise fresh insights into the mechanisms of common neurologic diseases. ACKNOWLEDGMENT The authors thank Dr. Alan Connelly and Dr. John Archer for reading the manuscript and Dr. John Mulley for discussions.

Received June 13, 2008. Accepted in final form October 30, 2008.

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Kryukov GV, Pennacchio LA, Sunyaev SR. Most rare missense alleles are deleterious in humans: implications for complex disease and association studies. Am J Hum Genet 2007;80:727–739. 55. McBride CM, Alford SH, Reid RJ, Larson EB, Baxevanis AD, Brody LC. Putting science over supposition in the arena of personalized genomics. Nat Genet 2008;40:939– 942. 56. Duerr RH, Taylor KD, Brant SR, et al. A genome-wide association study identifies IL23R as an inflammatory bowel disease gene. Science 2006;314:1461–1463. 57. Hakonarson H, Grant SF, Bradfield JP, et al. A genomewide association study identifies KIAA0350 as a type 1 diabetes gene. Nature 2007;448:591–594. 58. Harley JB, Alarcon-Riquelme ME, Criswell LA, et al. Genome-wide association scan in women with systemic lupus erythematosus identifies susceptibility variants in ITGAM, PXK, KIAA1542 and other loci. Nat Genet 2008; 40:204–210. 59. Hom G, Graham RR, Modrek B, et al. Association of systemic lupus erythematosus with C8orf13-BLK and ITGAM-ITGAX. N Engl J Med 2008;358:900–909. 60. Reiman EM, Webster JA, Myers AJ, et al. GAB2 alleles modify Alzheimer’s risk in APOE [var epsilon] 4 carriers. Neuron 2007;54:713–720.

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VIEWS & REVIEWS

Epistasis Multiple sclerosis and the major histocompatibility complex

Sreeram V. Ramagopalan, MA George C. Ebers, MD, FRCPC, FRCP, FMedSci

Address correspondence and reprint requests to Professor George C. Ebers, University Department of Clinical Neurology, Level 3, West Wing, John Radcliffe Hospital, Oxford, OX3 9DU, UK [email protected]

Recent studies in multiple sclerosis (MS) have taken epistasis from speculation and expectation to the reality of its key roles in susceptibility and outcome. Bateson1 first used the term epistasis to describe the effects on a biologic trait of one gene masking another. Usage has broadened to more generally encompass the explanation of phenotype. Although this has meant gene– gene interactions, environmentally mediated influences up to and including gene modification are part of this concept.2 Many prior examples of epistasis in clinical medicine may be unfamiliar but well-documented. Bhende et al.3 first demonstrated that lack of the H antigen, an intermediary point in the production of the corresponding A and B antigens at the ABO locus, prevents the expression of A and B alleles and blood is classed as O. This null phenotype, discovered among the natives of Bombay, India, was called the Bombay phenotype, to distinguish it from that of other individuals with the O blood group. At least two genes, FUT1 and FUT2, encoding alpha (1,2) fucosyltransferases, control this complex epistatic effect. MS well illustrates informative paradigms for gene– gene interaction in complex disease. For the main association in the major histocompatibility complex (MHC) it is now clear that the notion of HLA-DRB1*15 acting solely to increase MS risk4,5 is a gross oversimplification. Three types of epistasis have been documented in the MHC4-6 where HLADRB1*15 haplotypes exert the single strongest effect on MS risk. These dwarf any non-MHC effect but it took large cohorts and systematic methods of analysis to make progress. Several epistatic interactions were uncovered between MHC alleles or haplotypes, fundamental in determining susceptibility to MS. These had remained occult over the three decades since the MHC association was first described because they had to be specifically sought. The key strategy was to examine families lacking HLA-DRB1*15 to control for the obligate distorted transmission of all alleles from parents secondary to this primary association.4,5 When these families were studied, it emerged that

many other alleles were operative in risk. A genotyperather than allele- or haplotype-dependent hierarchy unfolded (figure). At an individual level this can be grouped into the following three types. HLA-DRB1*14, dominantly protective, has a stronger effect in reducing than HLA-DRB1*15 has in increasing susceptibility. This allele abrogates risk associated with HLADRB1*15, so that a HLA-DRB1*14/*15 genotype has a risk of 1 (compared to a HLA-DRB1*15 allelic risk of 3)4 (figure). As yet, no functional explanation can be given for the dominant protective effect of HLADRB1*14, which extends to other susceptible haplotypes. Understanding this epistatic interaction could be critical for treatment or prevention.

DOMINANT NEGATIVE EPISTASIS

On its own, HLADRB1*08 modestly increases the risk of MS but when present in conjunction with HLA-DRB1*15 on the other parental haplotype, it more than doubles the risk associated with a single copy of HLADRB1*154 (figure). This observation highlights how a variant with a marginal independent effect on risk may turn out to have a strong effect in certain genetic backgrounds. Indeed, using case– control analyses, an association may only be observed when allele frequencies are statistically different. However, if an effect of a gene on disease depends on the presence/ absence of other genes, variations across populations in allele frequencies among interacting loci can markedly affect the power to detect effects.7 This phenomenon may result in false negative association results.7 SYNERGISTIC EPISTASIS

Modifier genes represent biologic phenomena that few clinicians can ignore in the genomic era. HLA-DRB1*01 and HLA-DRB1*15 alleles interact to influence MS clinical phenotypes, producing a milder disease course,6 but play very little or no role in modifying clinical course independently. These interacting geEPISTASIS AND CLINICAL PHENOTYPE

From the Wellcome Trust Centre for Human Genetics and Department of Clinical Neurology, University of Oxford, UK. Disclosure: The authors report no disclosures. 566


Figure

Genotypic relative risks for multiple sclerosis (MS) for combinations of alleles at the HLA-DRB1 locus

of magnitude smaller than these recently described epistatic effects evident within the MHC. The net effect of the two parental haplotypes in combination can be conveniently called the diplotype. Although the genetic architecture of the MHC is unlike that of any other region of the genome, and epistasis is likely to have arisen as an evolutionary advantage, the lessons learnt from the MS HLA association are unlikely to be unique. Common episodic neurologic disorders such as migraine and epilepsy seem good candidates for disease- associated genemasking by epistatic loci.10 Ion channel variation leading to greater than average inhibitory/excitatory influences may be masked by protective polymorphisms reducing clinical penetrance and expressivity. Epistasis is no longer a textbook anomaly illustrated by remote animal models. Recent studies show it to be at the heart what is most clinically relevant in MS—susceptibility and disability outcome. Received August 12, 2008. Accepted in final form October 31, 2008.

Data derived from HLA-DRB1 genotyping performed by the Canadian Collaborative Study Group, comprising 2,535 individuals with definite MS and 4,799 of their unaffected firstdegree relatives. Analysis was performed as previously described.4 X/X ⫽ individual with no disease-associated alleles with baseline risk of 1; X ⫽ any non-diseaseassociated allele; 15, 17, 11, 08, 14, 10, 01 ⫽ HLA-DRB1 alleles. All genotypes are statistically significantly different from baseline, except for HLA-DRB1*14/15 and HLADRB1*11/17. No HLA-DRB1*14 homozygotes were observed, and it should be noted that HLA-DRB1*10 and *01 provide greater protection against HLA-DRB1*15 than HLA-DRB1*14.

netic variants clearly affect critically important long term phenotypes, holding potential for developing potential therapeutic strategies. HLA-DRB5*0101 interacts with HLA-DRB1*15 to reduce the number of autoreactive CD4⫹ T cells in experimental autoimmune encephalomyelitis, reducing its severity.8 HLA-DRB1*01 may operate in a similar manner. Furthermore, HLA-DRB1*01 may operate differently in disease susceptibility as compared to clinical outcome. Recent genome-wide association studies9 have received wide attention and more associations may come from small genetic isolates. However, effects confirmed to date with this methodology (explaining perhaps 1% of risk variance) are more than an order

REFERENCES 1. Bateson W. Mendel’s Principles of Heredity. Cambridge: Cambridge University Press; 1909. 2. Waddington CH. The Strategy of the Genes: A Discussion of Some Aspects of Theoretical Biology. London: Allen & Unwin; 1957. 3. Bhende YM, Deshpande CK, Bhatia HM, et al. A “new” blood group character related to the ABO system. Lancet 1952;1:903–904. 4. Ramagopalan SV, Morris AP, Dyment DA, et al. The inheritance of resistance alleles in multiple sclerosis. PLoS Genet 2007;3:e150. 5. Dyment DA, Herrera BM, Cader MZ, et al. Complex interactions among MHC haplotypes in multiple sclerosis: susceptibility and resistance. Hum Mol Genet 2005;14: 2019–2026. 6. DeLuca GC, Ramagopalan SV, Herrera BM, et al. An extremes of outcome strategy provides evidence that multiple sclerosis severity is determined by alleles at the HLADRB1 locus. Proc Natl Acad Sci USA 2007;104:20896– 20901. 7. Marchini J, Donnelly P, Cardon LR. Genome-wide strategies for detecting multiple loci that influence complex diseases. Nat Genet 2005;37:413–417. 8. Gregersen JW, Kranc KR, Ke X, et al. Functional epistasis on a common MHC haplotype associated with multiple sclerosis. Nature 2006;443:574–577. 9. Hafler DA, Compston A, Sawcer S, et al. Risk alleles for multiple sclerosis identified by a genomewide study. N Engl J Med 2007;357:851–862. 10. Glasscock E, Qian J, Yoo JW, Noebels JL. Masking epilepsy by combining two epilepsy genes. Nat Neurosci 2007;10:1554–1558.

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Clinical/Scientific Notes

R.G. Whittaker, MRCP J.K. Blackwood, PhD C.L. Alston, BSc E.L. Blakely, PhD J.L. Elson, PhD R. McFarland, MRCPCH P.F. Chinnery, FRCP D.M. Turnbull, FRCP R.W. Taylor, PhD

568

URINE HETEROPLASMY IS THE BEST PREDICTOR OF CLINICAL OUTCOME IN THE m.3243A>G mtDNA MUTATION

The m.3243 A⬎G point mutation in the mitochondrial-encoded MTTL1 gene is the single most common cause of mitochondrial disease.1 The range of clinical phenotypes is highly variable, from isolated diabetes and deafness to the devastating mitochondrial encephalomyopathy, lactic acidosis, and stroke-like episodes (MELAS) syndrome. Mitochondria contain multiple copies of mtDNA, and both wild-type and mutated mtDNA molecules can coexist in the same cell, a condition referred to as heteroplasmy. The expression of different clinical phenotypes is presumed to relate to different heteroplasmy levels within affected tissues.2 Being able to predict which patients are likely to develop complications of mitochondrial disease is essential for optimal clinical management. An important question therefore is which of the tissues which are suitable for analysis best reflect the level of mutation in clinically affected tissues, and hence are likely to best predict clinical outcome. Although the m.3243A⬎G mutation is readily measurable in blood leukocytes, the level of mutation declines over time.3 Thus even in severely affected patients presenting with MELAS, the level of m.3243A⬎G mutation may be very low, or even escape detection. Muscle biopsy is the current gold standard for the measurement of heteroplasmy to predict the incidence of specific clinical features. However, although a high heteroplasmy level of the m.3243A⬎G mutation in muscle increases the probability of developing some of the clinical features seen in this mutation, for example epilepsy and stroke-like episodes, for other clinical features such as myopathy, external ophthalmoplegia, and deafness, this is not the case.4 Furthermore, no published data exist as to the stability of mutation load in muscle over time. In recent years, several laboratories have investigated screening for the m.3243A⬎G mutation using a range of noninvasive tissues, including hair follicles, fibroblasts, buccal mucosa, and urinary epithelium.5,6 Of these, urinary epithelium shows the most consistent mutation load within individual patients. For example, in a small cohort of 12 patients studied over Neurology 72

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a 5-year period, we find that there is negligible change in the mutation load of m.3243A⬎G in urine (J. Blackwood, unpublished data), possibly reflecting replicative differences between urinary epithelium and blood leukocytes, where the mutation is lost. The main advantage of using urine is the ease of obtaining tissue; a 30 mL sample of urine provides enough DNA for accurate detection and quantitation of the m.3243A⬎G mutation, avoiding the need for patients to undergo a painful and expensive muscle biopsy. We therefore wanted to investigate whether urine was a useful tissue for assessing disease severity. We studied 24 adult patients harboring the m.3243A⬎G mutation recruited via a specialist mitochondrial clinic. In all patients, the initial molecular diagnosis had been made using skeletal muscle DNA obtained at muscle biopsy. In addition, an early morning sample of urine and EDTA-blood sample was obtained and the m.3243A⬎G percentage heteroplasmy level determined. Skeletal muscle and urine samples were obtained from all 24 patients, with blood samples from 21. The time between the initial diagnosis using muscle DNA and subsequent blood and urine samples was 0 – 6 years. Clinical features were assessed using the Newcastle Mitochondrial Disease Adult Scale (NMDAS), a validated scale in which 29 clinical features are rated according to a numerical scale to give an overall value indicating disease severity.7 We examined the correlation between mutation load in these three tissues and disease severity as indicated by the total score on the NMDAS (table). We found a very weak correlation between both blood and muscle m.3243A⬎G mutation load and total NMDAS score (rho ⫽ 0.205, p ⫽ 0.372 for blood, rho ⫽ 0.191, p ⫽ 0.372 for muscle). The highest correlation with clinical score was with m.3243A⬎G mutation load in urinary epithelium (rho ⫽ 0.451, p ⫽ 0.027). When we extended the analysis to include all our patients in whom m.3243A⬎G mutation load in urinary epithelium had been obtained (n ⫽ 58), we found a similar correlation (rho ⫽ 0.327, p ⫽ 0.012). Far from being a compromise in terms of ease of obtaining tissue over diagnostic accuracy, screening

Table

Patient ID

Comparison of Newcastle Mitochondrial Disease Adult Scale clinical score with m.3243A>G heteroplasmy level in blood, skeletal muscle, and urinary epithelium

Age, y*

Clinical score

Blood heteroplasmy (%)

Muscle heteroplasmy (%)

Urine heteroplasmy (%)

1

33

3

2

4

4

2

45

7

1

11

8

3

78

25

N/A

29

30

4

45

39

16

32

91

5

33

27

14

35

14

6

60

52

6

39

55

7

32

4

1

41

18

8

35

3

8

47

22

9

38

21

8

50

54

10

54

4

14

52

51

11

47

29

2

53

54

12

36

1

14

56

72

13

38

6

16

58

55

14

58

32

24

66

52

15

31

16

16

66

57

16

58

43

N/A

67

60

17

30

1

15

67

62

18

30

50

71

71

96

19

27

5

36

71

52

20

30

32

N/A

71

96

21

63

18

18

76

49

22

41

84

13

81

82

23

50

20

22

87

74

24

29

23

35

87

80

m.3243A⬎G mutation. We have adopted this approach in our practice, and believe that if this approach were to become widespread, then countless patients would avoid the need to undergo an unnecessary muscle biopsy. From the Mitochondrial Research Group, The Medical School (R.G.W., J.K.B., C.L.A., E.L.B., J.L.E., R.M., P.F.C., D.M.T., R.W.T.), and Institutes of Human Genetics and Ageing and Health (P.F.C., D.M.T., R.W.T.), Newcastle University, Newcastle upon Tyne, UK. Funded by a project grant from SPARKS and by the Wellcome Trust. R.G.W. is funded by EUmitocombat. Disclosure: The authors report no disclosures. Received August 12, 2008. Accepted in final form September 15, 2008. Address correspondence and reprint requests to Dr. Roger G. Whittaker, Mitochondrial Research Group, The Medical School, Newcastle University, Framlington Place, Newcastle upon Tyne, NE2 4HH, UK; [email protected] Copyright © 2009 by AAN Enterprises, Inc. 1.

2.

3.

4.

*Refers to the age of the patient at the time that the urine and blood samples were taken and clinical score assessed. N/A ⫽ not available.

5.

of m.3243A⬎G mutation load in urinary epithelium is a better predictor of outcome than the present gold standard of skeletal muscle tissue. We believe that urinary epithelium completely replaces muscle biopsy as the most suitable tissue for the initial diagnosis in patients suspected of harboring the

6.

A.L. Green, FRCS(SN) S. Wang, PhD J.F. Stein, D Phil E.A.C. Pereira, MB ChB M.L. Kringelbach, D Phil X. Liu, PhD J.-S. Brittain, PhD T.Z. Aziz, D Med Sci

NEURAL SIGNATURES IN PATIENTS WITH NEUROPATHIC PAIN

The mechanisms by which neural signals are encoded to produce conscious sensations remain a central question in neuroscience. Invasive recordings from human brain structures in vivo give us the opportunity to study neural correlates of these sensations. Pain is a sensation fundamental to survival and its subjective nature in the clinical setting makes it difficult to quantify. It remains without direct objective neuronal correlates. Here we describe an 8 –14 Hz,

7.

Schaefer AM, McFarland R, Blakely EL, et al. Prevalence of mitochondrial DNA disease in adults. Ann Neurol 2008;63:35–39. Macmillan C, Lach B, Shoubridge EA. Variable distribution of mutant mitochondrial DNAs (tRNA(Leu[3243])) in tissues of symptomatic relatives with MELAS: the role of mitotic segregation. Neurology 1993;43:1586–1590. Rahman S, Poulton J, Marchington D, et al. Decrease of 3243 A⬎G mtDNA mutation from blood in MELAS syndrome: a longitudinal study. Am J Hum Genet 2001;68: 238–240. Chinnery PF, Howell N, Lightowlers RN, et al. Molecular pathology of MELAS and MERRF. The relationship between mutation load and clinical phenotypes. Brain 1997; 120:1713–1721. Shanske S, Pancrudo J, Kaufmann P, et al. Varying loads of the mitochondrial DNA A3243G mutation in different tissues: implications for diagnosis. Am J Med Genet A 2004;130A:134–137. McDonnell MT, Schaefer AM, Blakely EL, et al. Noninvasive diagnosis of the 3243A⬎G mitochondrial DNA mutation using urinary epithelial cells. Eur J Hum Genet 2004;12:778–781. Schaefer AM, Phoenix C, Elson JL, et al. Mitochondrial disease in adults: a scale to monitor progression and treatment. Neurology 2006;66:1932–1934.

spindle-shaped neural signal present in both the sensory thalamus and periaqueductal gray area (PAG) in humans that directly correlates to the subjective reporting of pain intensity. Local field potentials (LFPs) recorded by deep brain macroelectrodes reveal the ensemble activity of neuronal groups in particular brain regions.1 The oscillatory amplitude of such ensembles is proportionate to the degree of synchrony with which they oscillate.2 Properties of oscillations including their synchrony, frequency, and correNeurology 72

February 10, 2009

569

Figure

Local field potential changes in different pain states

(A) 10-Hz spindle-shaped activity in the ventroposterolateral nucleus of the thalamus in a patient with chronic neuropathic poststroke pain. The three graphs represent three bipolar channels of the same electrode (four contacts). Note the onset of each period of activity as indicated by the orange arrows on the x-axis as well as the relative pain that the patient was experiencing, as indicated by the colored overlay (green ⫽ moderate pain [VAS ⫽ 5/10], blue ⫽ severe pain [VAS ⫽ 9/10]). (B) Comparison of spindle–nonspindle activity in each nucleus showed a significant exponential correlation between VAS and spindle activity. Each point represents a different patient (15 electrodes in 12 patients, as 3 had PAG and VPL). R2 ⫽ 0.67, ␹2 ⫽ 0.00373. (C) Timefrequency analysis of local field potentials during pain. This shows a 1-second segment of the power spectrum of the local field potentials recorded from the sensory thalamus in a patient with intense pain (VAS ⫽ 8/10). Based on time-variant autoregressive modeling, this time-frequency distribution demonstrates the changes in dominant frequencies during a 1-second burst of spindle activity over time. It demonstrates the maximum power of approximately 8 –10 Hz with entry from high frequency to low frequency during the 1-second burst of spindle activity. This provides an individual signature of pain for this patient. Frequencies above 20 Hz have been omitted for clarity. (D) Mean power spectral changes for each nucleus. Power spectra showing the dominant frequencies for each nucleus in two conditions. In the nonpain condition, patients were at rest. In the painful condition, pain was evoked using an ice-cold stimulus on the skin of the affected part. Pain increases power in the 8 –12 Hz frequency in the PAG and 17–30 Hz in the sensory thalamus. Light-colored lines show 1 SD of the mean. VAS ⫽ Visual Analogue Score; PVG ⫽ periventricular gray area; PAG ⫽ periaqueductal gray area; VPL ⫽ ventroposterolateral.

570

Neurology 72

February 10, 2009

sponding power spectra vary both between brain structures and dynamically, depending upon the activity performed.3 Methods. Twelve patients (11 male, 1 female) underwent deep brain stimulation for treatment of chronic neuropathic pain. Etiology was as follows; poststroke pain (4), phantom limb pain (3), facial pain of various causes (4), and brachial plexus injury (1). Nuclei targeted were periaqueductal gray (PAG) alone in 3 patients, ventroposterolateral/medial nucleus of the thalamus (VPL/VPM) in 6 patients, and both in 3 patients. This was decided upon based on clinical grounds (in general, sensory thalamus was avoided if the patient had had a thalamic stroke). Three patients had both nuclei implanted as stimulation of the first did not show convincing pain relief intraoperatively. Mean age was 51.6 years (range 35–74 years). LFPs were recorded postoperatively. The experiment was started with 10 minutes of rest before recording. Recording of LFPs then lasted 10 minutes, during which time Visual Analogue Score (VAS) of pain was recorded every 60 seconds. This protocol was repeated three times for each patient, on 3 separate days. Results. The most prominent finding was characteristic spindle-shaped bursts of increased amplitude at approximately 10 Hz (slightly different in different subjects, range 8 –14 Hz, mean 10 Hz) in both the sensory thalamus and PAG concomitant with subjective awareness of pain (figure, A). Statistical analysis revealed a significant increase in the number of bursts and increasing VAS for each individual subject as well as an increased ratio of burst-time to non-bursttime activity in the pain state (figure, B). Plotting burst activity against the background power spectrum of LFP activity over a finite time course reveals an individual neural signature of pain for each subject (figure, C). In general, power spectra reveal that there is a significant rise in the 8 –12 Hz activity in the PAG and a rise in the 17–30 Hz activity, i.e., beta frequency, in the sensory thalamus (figure, D). Discussion. Noninvasive electrophysiologic and functional neuroimaging technologies have, until now, provided the most convincing evidence of changes in human brain activity associated with pain.4 They have also enhanced understanding of whole brain responses to deep brain stimulation.5 Although previous studies have looked at electrical coupling between brain nuclei in pain,6 they have not revealed convincing characteristic waveforms that may represent pain perception. These previous stud-

ies have suggested 0.2– 0.4 Hz frequency changes in the sensory thalamus in the pain state, but these frequencies were reduced during analgesia induced by periventricular gray area stimulation and this frequency is rather close to that of respiration. The correlation of the pain spindles in the thalamus may be explained by the fact that they represent direct activity in a relay nucleus. In the PAG, they are harder to understand as this is an antinociceptive area but they may be due to the “pain inhibits pain” mechanism of diffuse noxious inhibitory controls on which the PAG has been shown to have an influence.7 Our findings are significant in that not only do they provide a direct neural signature of a subjective conscious state but they may also allow for objective measurements and predictions of the relative level of subjective pain. We intend to investigate these preliminary findings in a more methodical and robust manner. From the Department of Physiology, Anatomy & Genetics (A.L.G., S.W., J.F.S., E.A.C.P., M.L.K., T.Z.A.), University of Oxford; Department of Neurosurgery (A.L.G., J.-S.B., T.Z.A.), West Wing, John Radcliffe Hospital, Oxford; and Division of Neurosciences & Mental Health (X.L.), Imperial College London, Charing Cross Campus, London, UK. Shouyan Wang is supported by the Norman Collison Foundation, and Tipu Aziz by the Medical Research Council, Wellcome Trust, and Templeton Foundation. Disclosure: The authors report no disclosures. Received July 16, 2008. Accepted in final form September 16, 2008. Address correspondence and reprint requests to Dr. Alexander L. Green, Department of Neurosurgery, West Wing Level 3, John Radcliffe Hospital, Oxford, OX3 9DU, UK; [email protected] Copyright © 2009 by AAN Enterprises, Inc. AUTHOR CONTRIBUTIONS The statistical analysis was performed by A.L.G.

1. 2.

3.

4.

5.

6.

7.

Buzsaki G. Large-scale recording of neuronal ensembles. Nat Neurosci 2004;7:446–451. Pfurtscheller G, Lopes da Silva FH. Event-related EEG/ MEG synchronization and desynchronization: basic principles. Clin Neurophysiol 1999;110:1842–1857. Engel AK, Fries P, Singer W. Dynamic predictions: oscillations and synchrony in top-down processing. Nat Rev Neurosci 2001;2:704–716. Peyron R, Laurent B, Garcia-Larrea L. Functional imaging of brain responses to pain. A review and meta-analysis. Neurophysiol Clin 2000;30:263–288. Kringelbach ML, Jenkinson N, Green AL, et al. Deep brain stimulation for chronic pain investigated with magnetoencephalography. Neuroreport 2007;18:223– 228. Nandi D, Aziz T, Carter H, et al. Thalamic field potentials in chronic central pain treated by periventricular gray stimulation: a series of eight cases. Pain 2003;101:97–107. Bouhassira D, Villanueva L, Le Bars D. Effects of systemic morphine on diffuse noxious inhibitory controls: role of the periaqueductal grey. Eur J Pharmacol 1992;216:149– 156.

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571

Bernhard Baier, MD, PhD Marianne Dieterich, MD


OCULAR TILT REACTION: A CLINICAL SIGN OF CEREBELLAR INFARCTIONS?

Ocular tilt reaction (OTR) consists of head tilt, ocular torsion (OT), and skew deviation (SKD) combined with perceptual tilts such as deviations of the subjective visual vertical (SVV). Few case reports have shown that OTR also occurs in patients with cerebellar infarctions.1-4 However, no systematic clinical studies are available on the frequency of signs of OTR in patients with cerebellar lesions. Therefore, the questions arose as to whether OTR is a common clinical sign of an acute cerebellar lesion and whether the time course of its components is similar to those from brainstem infarctions. The cerebellar structures involved in 31 patients were studied in detail elsewhere.5 Methods. All 56 patients with acute unilateral cerebellar infarctions (51 ischemic; 5 hemorrhagic) admitted at

Figure

our department were included in the study (median age 65 years, range 37– 84 years; 37 men and 19 women). Forty-three patients had unilateral, and 13 patients with unilateral cerebellar infarctions had additional brainstem lesions (27 patients had right-sided, 29 left-sided lesions). All patients underwent a neuro-ophthalmologic examination including testing tilt of SVV, OT, SKD (for details, see the video5), electronystagmography including caloric irrigation, and MRI scanning. Only two of the patients with infarctions in the territory of the anterior inferior cerebellar artery showed a unilateral hyporesponsiveness in the caloric testing. The median latency between infarction and investigation was 3 days (range 1–12 days). The vascular territory was determined by using the anatomic diagrams of Tatu et al.6 Results. Most of the 43 patients with purely unilateral cerebellar lesions presented with contralateral

Time course plotted against (A) skew deviation, (B) binocular tilts of SVV, (C) ocular torsion, and (D) monocular tilts of SVV and ocular torsion for each eye

Open circles represent monocular tilts of subjective visual vertical (SVV) of each eye; filled circles represent ocular torsion of each eye. Only absolute values were taken. 572

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signs: 58% showed tilts of SVV (median of the binocular SVV deviation 5.1°), whereas 35% had OT (median net tilt angle of OT of the right eyes: 7°; and of the left eyes: 5°) and 14% SKD (median 3°). Ipsilateral signs were less frequent: 26% had tilts of SVV (median SVV deviation 5.8°), 14% OT, and 9% SKD (median net tilt angle of the right eyes: 6°; and of SKD 5°). For both ipsi- and contralateral signs of OTR, all patients with SKD (9 patients) also showed the other signs of OTR. Thus, a complete OTR was seen in 21% (table e-1 on the Neurology® Web site at www.neurology.org). The patients with combined cerebellar and brainstem lesions showed opposite results: only 15% (2 patients) had contralateral (SVV deviation 7.0° and 3.0°), but 46% had ipsilateral tilts of SVV (median 5.0°). Contralateral OT occurred in 15% (2 patients) (net tilt angle of the right eyes: 5°, 11°; and of the left eyes: 7°, 13°) and ipsilateral OT in 23% of the patients (median net tilt angle of the right eyes: 7.5°, and of the left eyes: 6°). Contralateral SKD was seen in one patient (5°); none had an ipsilateral SKD. Thus, there was a difference of the frequency between contra- and ipsilateral tilts of SVV in patients with pure and combined cerebellar lesions (␹219.58; p ⫽ 0). This indicates that more patients with purely cerebellar lesions had contralateral tilts of SVV. In patients with pure unilateral cerebellar lesions, the nonlinear regression models (p ⬍ 0.01) suggest that with increasing time since lesion, OT and tilts of the SVV last longer than 10 days, whereas SKD wears off within around 6 days (figure).

Thus, signs of OTR not only indicate brainstem, thalamic, or peripheral vestibular lesions but also unilateral cerebellar lesions, which affect structures involved in the processing of vestibular signals. These structures seem to form a pathway from the brainstem to the vermis (including the cerebellar peduncles, the dentate nucleus, pyramid of the vermis, nodulus, and uvula) and to the flocculus and tonsil.5 The specific structures lesioned, however, determine the directive of the signs, ipsilateral or contralateral. An affection of the dentate nucleus in particular was associated with contralateral signs of OTR, whereas in ipsilateral signs the dentate nucleus was spared and lesions were located in the middle cerebellar peduncle, tonsil, biventer, and inferior semilunar lobules.5

Discussion. Our data give evidence that OTR is a common sign in patients with unilateral cerebellar lesions, indicating that lesions of the cerebellum induce a dysfunction in otoliths pathways that mediate vestibular information in the roll plane. Single components such as tilts of the SVV can occur in up to 85% and show similar time courses to those in brainstem infarctions7 with the skew deviation as the most transient sign. However, the amount of the deviations in the acute phase was less in patients with cerebellar lesions (median of contralateral [5.1°] and ipsilateral SVV deviation [5.8°]), and highest in patients with medullary brainstem infarctions (Wallenberg syndrome, 9.8°) compared to that in acute vestibular neuritis (7.0°).7

2.

From the Department of Neurology (B.B., M.D.), University of Mainz; and Department of Neurology (M.D.), LudwigMaximillians-University, Munich, Germany. Supported by the DFG (DI 379/4-4). Disclosure: The authors report no disclosures. Received April 29, 2008. Accepted in final form September 24, 2008. Address correspondence and reprint requests to Dr. Bernhard Baier, Department of Neurology, University of Mainz, Langenbeckstr. 1, 55131 Mainz, Germany; [email protected] Copyright © 2009 by AAN Enterprises, Inc. AUTHOR CONTRIBUTIONS The statistical analysis was conducted by B.B.

ACKNOWLEDGMENT The authors thank Mrs. Benson for critically reading the manuscript.

1.

3.

4.

5.

6.

7.

Mossman S, Halmagyi GM. Partial ocular tilt reaction due to unilateral cerebellar lesion. Neurology 1997;49:491–493. Min W, Kim J, Park S, Suh C. Ocular tilt reaction due to unilateral cerebellar lesion. Neuroophthalmology 1999;22:81–85. Lee H, Lee SY, Lee SR, Park BR, Baloh RW. Ocular tilt reaction and anterior inferior cerebellar artery syndrome. J Neurol Neurosurg Psychiatry 2005;76:1742–1743. Wong AM, Sharpe JA. Cerebellar skew deviation and the torsional vestibuloocular reflex. Neurology 2005;65: 412–419. Baier B, Bense S, Dieterich M. Are signs of ocular tilt reaction in patients with cerebellar lesions mediated by the dentate nucleus? Brain 2008;131:1445–1454. Tatu L, Moulin T, Bogousslavsky J, Duvernoy H. Arterial territories of human brain. Brainstem and cerebellum. Neurology 1996;47:1125–1135. Cnyrim CD, Rettinger M, Mansmann U, et al. Central compensation of deviated subjective visual vertical in Wallenberg’s syndrome. J Neurol Neurosurg Psychiatry 2007;78:527–528.

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573

Clinical/Scientific Notes

R.G. Whittaker, MRCP J.K. Blackwood, PhD C.L. Alston, BSc E.L. Blakely, PhD J.L. Elson, PhD R. McFarland, MRCPCH P.F. Chinnery, FRCP D.M. Turnbull, FRCP R.W. Taylor, PhD

568

URINE HETEROPLASMY IS THE BEST PREDICTOR OF CLINICAL OUTCOME IN THE m.3243A>G mtDNA MUTATION

The m.3243 A⬎G point mutation in the mitochondrial-encoded MTTL1 gene is the single most common cause of mitochondrial disease.1 The range of clinical phenotypes is highly variable, from isolated diabetes and deafness to the devastating mitochondrial encephalomyopathy, lactic acidosis, and stroke-like episodes (MELAS) syndrome. Mitochondria contain multiple copies of mtDNA, and both wild-type and mutated mtDNA molecules can coexist in the same cell, a condition referred to as heteroplasmy. The expression of different clinical phenotypes is presumed to relate to different heteroplasmy levels within affected tissues.2 Being able to predict which patients are likely to develop complications of mitochondrial disease is essential for optimal clinical management. An important question therefore is which of the tissues which are suitable for analysis best reflect the level of mutation in clinically affected tissues, and hence are likely to best predict clinical outcome. Although the m.3243A⬎G mutation is readily measurable in blood leukocytes, the level of mutation declines over time.3 Thus even in severely affected patients presenting with MELAS, the level of m.3243A⬎G mutation may be very low, or even escape detection. Muscle biopsy is the current gold standard for the measurement of heteroplasmy to predict the incidence of specific clinical features. However, although a high heteroplasmy level of the m.3243A⬎G mutation in muscle increases the probability of developing some of the clinical features seen in this mutation, for example epilepsy and stroke-like episodes, for other clinical features such as myopathy, external ophthalmoplegia, and deafness, this is not the case.4 Furthermore, no published data exist as to the stability of mutation load in muscle over time. In recent years, several laboratories have investigated screening for the m.3243A⬎G mutation using a range of noninvasive tissues, including hair follicles, fibroblasts, buccal mucosa, and urinary epithelium.5,6 Of these, urinary epithelium shows the most consistent mutation load within individual patients. For example, in a small cohort of 12 patients studied over Neurology 72

February 10, 2009

a 5-year period, we find that there is negligible change in the mutation load of m.3243A⬎G in urine (J. Blackwood, unpublished data), possibly reflecting replicative differences between urinary epithelium and blood leukocytes, where the mutation is lost. The main advantage of using urine is the ease of obtaining tissue; a 30 mL sample of urine provides enough DNA for accurate detection and quantitation of the m.3243A⬎G mutation, avoiding the need for patients to undergo a painful and expensive muscle biopsy. We therefore wanted to investigate whether urine was a useful tissue for assessing disease severity. We studied 24 adult patients harboring the m.3243A⬎G mutation recruited via a specialist mitochondrial clinic. In all patients, the initial molecular diagnosis had been made using skeletal muscle DNA obtained at muscle biopsy. In addition, an early morning sample of urine and EDTA-blood sample was obtained and the m.3243A⬎G percentage heteroplasmy level determined. Skeletal muscle and urine samples were obtained from all 24 patients, with blood samples from 21. The time between the initial diagnosis using muscle DNA and subsequent blood and urine samples was 0 – 6 years. Clinical features were assessed using the Newcastle Mitochondrial Disease Adult Scale (NMDAS), a validated scale in which 29 clinical features are rated according to a numerical scale to give an overall value indicating disease severity.7 We examined the correlation between mutation load in these three tissues and disease severity as indicated by the total score on the NMDAS (table). We found a very weak correlation between both blood and muscle m.3243A⬎G mutation load and total NMDAS score (rho ⫽ 0.205, p ⫽ 0.372 for blood, rho ⫽ 0.191, p ⫽ 0.372 for muscle). The highest correlation with clinical score was with m.3243A⬎G mutation load in urinary epithelium (rho ⫽ 0.451, p ⫽ 0.027). When we extended the analysis to include all our patients in whom m.3243A⬎G mutation load in urinary epithelium had been obtained (n ⫽ 58), we found a similar correlation (rho ⫽ 0.327, p ⫽ 0.012). Far from being a compromise in terms of ease of obtaining tissue over diagnostic accuracy, screening

Table

Patient ID

Comparison of Newcastle Mitochondrial Disease Adult Scale clinical score with m.3243A>G heteroplasmy level in blood, skeletal muscle, and urinary epithelium

Age, y*

Clinical score

Blood heteroplasmy (%)

Muscle heteroplasmy (%)

Urine heteroplasmy (%)

1

33

3

2

4

4

2

45

7

1

11

8

3

78

25

N/A

29

30

4

45

39

16

32

91

5

33

27

14

35

14

6

60

52

6

39

55

7

32

4

1

41

18

8

35

3

8

47

22

9

38

21

8

50

54

10

54

4

14

52

51

11

47

29

2

53

54

12

36

1

14

56

72

13

38

6

16

58

55

14

58

32

24

66

52

15

31

16

16

66

57

16

58

43

N/A

67

60

17

30

1

15

67

62

18

30

50

71

71

96

19

27

5

36

71

52

20

30

32

N/A

71

96

21

63

18

18

76

49

22

41

84

13

81

82

23

50

20

22

87

74

24

29

23

35

87

80

m.3243A⬎G mutation. We have adopted this approach in our practice, and believe that if this approach were to become widespread, then countless patients would avoid the need to undergo an unnecessary muscle biopsy. From the Mitochondrial Research Group, The Medical School (R.G.W., J.K.B., C.L.A., E.L.B., J.L.E., R.M., P.F.C., D.M.T., R.W.T.), and Institutes of Human Genetics and Ageing and Health (P.F.C., D.M.T., R.W.T.), Newcastle University, Newcastle upon Tyne, UK. Funded by a project grant from SPARKS and by the Wellcome Trust. R.G.W. is funded by EUmitocombat. Disclosure: The authors report no disclosures. Received August 12, 2008. Accepted in final form September 15, 2008. Address correspondence and reprint requests to Dr. Roger G. Whittaker, Mitochondrial Research Group, The Medical School, Newcastle University, Framlington Place, Newcastle upon Tyne, NE2 4HH, UK; [email protected] Copyright © 2009 by AAN Enterprises, Inc. 1.

2.

3.

4.

*Refers to the age of the patient at the time that the urine and blood samples were taken and clinical score assessed. N/A ⫽ not available.

5.

of m.3243A⬎G mutation load in urinary epithelium is a better predictor of outcome than the present gold standard of skeletal muscle tissue. We believe that urinary epithelium completely replaces muscle biopsy as the most suitable tissue for the initial diagnosis in patients suspected of harboring the

6.

A.L. Green, FRCS(SN) S. Wang, PhD J.F. Stein, D Phil E.A.C. Pereira, MB ChB M.L. Kringelbach, D Phil X. Liu, PhD J.-S. Brittain, PhD T.Z. Aziz, D Med Sci

NEURAL SIGNATURES IN PATIENTS WITH NEUROPATHIC PAIN

The mechanisms by which neural signals are encoded to produce conscious sensations remain a central question in neuroscience. Invasive recordings from human brain structures in vivo give us the opportunity to study neural correlates of these sensations. Pain is a sensation fundamental to survival and its subjective nature in the clinical setting makes it difficult to quantify. It remains without direct objective neuronal correlates. Here we describe an 8 –14 Hz,

7.

Schaefer AM, McFarland R, Blakely EL, et al. Prevalence of mitochondrial DNA disease in adults. Ann Neurol 2008;63:35–39. Macmillan C, Lach B, Shoubridge EA. Variable distribution of mutant mitochondrial DNAs (tRNA(Leu[3243])) in tissues of symptomatic relatives with MELAS: the role of mitotic segregation. Neurology 1993;43:1586–1590. Rahman S, Poulton J, Marchington D, et al. Decrease of 3243 A⬎G mtDNA mutation from blood in MELAS syndrome: a longitudinal study. Am J Hum Genet 2001;68: 238–240. Chinnery PF, Howell N, Lightowlers RN, et al. Molecular pathology of MELAS and MERRF. The relationship between mutation load and clinical phenotypes. Brain 1997; 120:1713–1721. Shanske S, Pancrudo J, Kaufmann P, et al. Varying loads of the mitochondrial DNA A3243G mutation in different tissues: implications for diagnosis. Am J Med Genet A 2004;130A:134–137. McDonnell MT, Schaefer AM, Blakely EL, et al. Noninvasive diagnosis of the 3243A⬎G mitochondrial DNA mutation using urinary epithelial cells. Eur J Hum Genet 2004;12:778–781. Schaefer AM, Phoenix C, Elson JL, et al. Mitochondrial disease in adults: a scale to monitor progression and treatment. Neurology 2006;66:1932–1934.

spindle-shaped neural signal present in both the sensory thalamus and periaqueductal gray area (PAG) in humans that directly correlates to the subjective reporting of pain intensity. Local field potentials (LFPs) recorded by deep brain macroelectrodes reveal the ensemble activity of neuronal groups in particular brain regions.1 The oscillatory amplitude of such ensembles is proportionate to the degree of synchrony with which they oscillate.2 Properties of oscillations including their synchrony, frequency, and correNeurology 72

February 10, 2009

569

Figure

Local field potential changes in different pain states

(A) 10-Hz spindle-shaped activity in the ventroposterolateral nucleus of the thalamus in a patient with chronic neuropathic poststroke pain. The three graphs represent three bipolar channels of the same electrode (four contacts). Note the onset of each period of activity as indicated by the orange arrows on the x-axis as well as the relative pain that the patient was experiencing, as indicated by the colored overlay (green ⫽ moderate pain [VAS ⫽ 5/10], blue ⫽ severe pain [VAS ⫽ 9/10]). (B) Comparison of spindle–nonspindle activity in each nucleus showed a significant exponential correlation between VAS and spindle activity. Each point represents a different patient (15 electrodes in 12 patients, as 3 had PAG and VPL). R2 ⫽ 0.67, ␹2 ⫽ 0.00373. (C) Timefrequency analysis of local field potentials during pain. This shows a 1-second segment of the power spectrum of the local field potentials recorded from the sensory thalamus in a patient with intense pain (VAS ⫽ 8/10). Based on time-variant autoregressive modeling, this time-frequency distribution demonstrates the changes in dominant frequencies during a 1-second burst of spindle activity over time. It demonstrates the maximum power of approximately 8 –10 Hz with entry from high frequency to low frequency during the 1-second burst of spindle activity. This provides an individual signature of pain for this patient. Frequencies above 20 Hz have been omitted for clarity. (D) Mean power spectral changes for each nucleus. Power spectra showing the dominant frequencies for each nucleus in two conditions. In the nonpain condition, patients were at rest. In the painful condition, pain was evoked using an ice-cold stimulus on the skin of the affected part. Pain increases power in the 8 –12 Hz frequency in the PAG and 17–30 Hz in the sensory thalamus. Light-colored lines show 1 SD of the mean. VAS ⫽ Visual Analogue Score; PVG ⫽ periventricular gray area; PAG ⫽ periaqueductal gray area; VPL ⫽ ventroposterolateral.

570

Neurology 72

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sponding power spectra vary both between brain structures and dynamically, depending upon the activity performed.3 Methods. Twelve patients (11 male, 1 female) underwent deep brain stimulation for treatment of chronic neuropathic pain. Etiology was as follows; poststroke pain (4), phantom limb pain (3), facial pain of various causes (4), and brachial plexus injury (1). Nuclei targeted were periaqueductal gray (PAG) alone in 3 patients, ventroposterolateral/medial nucleus of the thalamus (VPL/VPM) in 6 patients, and both in 3 patients. This was decided upon based on clinical grounds (in general, sensory thalamus was avoided if the patient had had a thalamic stroke). Three patients had both nuclei implanted as stimulation of the first did not show convincing pain relief intraoperatively. Mean age was 51.6 years (range 35–74 years). LFPs were recorded postoperatively. The experiment was started with 10 minutes of rest before recording. Recording of LFPs then lasted 10 minutes, during which time Visual Analogue Score (VAS) of pain was recorded every 60 seconds. This protocol was repeated three times for each patient, on 3 separate days. Results. The most prominent finding was characteristic spindle-shaped bursts of increased amplitude at approximately 10 Hz (slightly different in different subjects, range 8 –14 Hz, mean 10 Hz) in both the sensory thalamus and PAG concomitant with subjective awareness of pain (figure, A). Statistical analysis revealed a significant increase in the number of bursts and increasing VAS for each individual subject as well as an increased ratio of burst-time to non-bursttime activity in the pain state (figure, B). Plotting burst activity against the background power spectrum of LFP activity over a finite time course reveals an individual neural signature of pain for each subject (figure, C). In general, power spectra reveal that there is a significant rise in the 8 –12 Hz activity in the PAG and a rise in the 17–30 Hz activity, i.e., beta frequency, in the sensory thalamus (figure, D). Discussion. Noninvasive electrophysiologic and functional neuroimaging technologies have, until now, provided the most convincing evidence of changes in human brain activity associated with pain.4 They have also enhanced understanding of whole brain responses to deep brain stimulation.5 Although previous studies have looked at electrical coupling between brain nuclei in pain,6 they have not revealed convincing characteristic waveforms that may represent pain perception. These previous stud-

ies have suggested 0.2– 0.4 Hz frequency changes in the sensory thalamus in the pain state, but these frequencies were reduced during analgesia induced by periventricular gray area stimulation and this frequency is rather close to that of respiration. The correlation of the pain spindles in the thalamus may be explained by the fact that they represent direct activity in a relay nucleus. In the PAG, they are harder to understand as this is an antinociceptive area but they may be due to the “pain inhibits pain” mechanism of diffuse noxious inhibitory controls on which the PAG has been shown to have an influence.7 Our findings are significant in that not only do they provide a direct neural signature of a subjective conscious state but they may also allow for objective measurements and predictions of the relative level of subjective pain. We intend to investigate these preliminary findings in a more methodical and robust manner. From the Department of Physiology, Anatomy & Genetics (A.L.G., S.W., J.F.S., E.A.C.P., M.L.K., T.Z.A.), University of Oxford; Department of Neurosurgery (A.L.G., J.-S.B., T.Z.A.), West Wing, John Radcliffe Hospital, Oxford; and Division of Neurosciences & Mental Health (X.L.), Imperial College London, Charing Cross Campus, London, UK. Shouyan Wang is supported by the Norman Collison Foundation, and Tipu Aziz by the Medical Research Council, Wellcome Trust, and Templeton Foundation. Disclosure: The authors report no disclosures. Received July 16, 2008. Accepted in final form September 16, 2008. Address correspondence and reprint requests to Dr. Alexander L. Green, Department of Neurosurgery, West Wing Level 3, John Radcliffe Hospital, Oxford, OX3 9DU, UK; [email protected] Copyright © 2009 by AAN Enterprises, Inc. AUTHOR CONTRIBUTIONS The statistical analysis was performed by A.L.G.

1. 2.

3.

4.

5.

6.

7.

Buzsaki G. Large-scale recording of neuronal ensembles. Nat Neurosci 2004;7:446–451. Pfurtscheller G, Lopes da Silva FH. Event-related EEG/ MEG synchronization and desynchronization: basic principles. Clin Neurophysiol 1999;110:1842–1857. Engel AK, Fries P, Singer W. Dynamic predictions: oscillations and synchrony in top-down processing. Nat Rev Neurosci 2001;2:704–716. Peyron R, Laurent B, Garcia-Larrea L. Functional imaging of brain responses to pain. A review and meta-analysis. Neurophysiol Clin 2000;30:263–288. Kringelbach ML, Jenkinson N, Green AL, et al. Deep brain stimulation for chronic pain investigated with magnetoencephalography. Neuroreport 2007;18:223– 228. Nandi D, Aziz T, Carter H, et al. Thalamic field potentials in chronic central pain treated by periventricular gray stimulation: a series of eight cases. Pain 2003;101:97–107. Bouhassira D, Villanueva L, Le Bars D. Effects of systemic morphine on diffuse noxious inhibitory controls: role of the periaqueductal grey. Eur J Pharmacol 1992;216:149– 156.

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Bernhard Baier, MD, PhD Marianne Dieterich, MD


OCULAR TILT REACTION: A CLINICAL SIGN OF CEREBELLAR INFARCTIONS?

Ocular tilt reaction (OTR) consists of head tilt, ocular torsion (OT), and skew deviation (SKD) combined with perceptual tilts such as deviations of the subjective visual vertical (SVV). Few case reports have shown that OTR also occurs in patients with cerebellar infarctions.1-4 However, no systematic clinical studies are available on the frequency of signs of OTR in patients with cerebellar lesions. Therefore, the questions arose as to whether OTR is a common clinical sign of an acute cerebellar lesion and whether the time course of its components is similar to those from brainstem infarctions. The cerebellar structures involved in 31 patients were studied in detail elsewhere.5 Methods. All 56 patients with acute unilateral cerebellar infarctions (51 ischemic; 5 hemorrhagic) admitted at

Figure

our department were included in the study (median age 65 years, range 37– 84 years; 37 men and 19 women). Forty-three patients had unilateral, and 13 patients with unilateral cerebellar infarctions had additional brainstem lesions (27 patients had right-sided, 29 left-sided lesions). All patients underwent a neuro-ophthalmologic examination including testing tilt of SVV, OT, SKD (for details, see the video5), electronystagmography including caloric irrigation, and MRI scanning. Only two of the patients with infarctions in the territory of the anterior inferior cerebellar artery showed a unilateral hyporesponsiveness in the caloric testing. The median latency between infarction and investigation was 3 days (range 1–12 days). The vascular territory was determined by using the anatomic diagrams of Tatu et al.6 Results. Most of the 43 patients with purely unilateral cerebellar lesions presented with contralateral

Time course plotted against (A) skew deviation, (B) binocular tilts of SVV, (C) ocular torsion, and (D) monocular tilts of SVV and ocular torsion for each eye

Open circles represent monocular tilts of subjective visual vertical (SVV) of each eye; filled circles represent ocular torsion of each eye. Only absolute values were taken. 572

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signs: 58% showed tilts of SVV (median of the binocular SVV deviation 5.1°), whereas 35% had OT (median net tilt angle of OT of the right eyes: 7°; and of the left eyes: 5°) and 14% SKD (median 3°). Ipsilateral signs were less frequent: 26% had tilts of SVV (median SVV deviation 5.8°), 14% OT, and 9% SKD (median net tilt angle of the right eyes: 6°; and of SKD 5°). For both ipsi- and contralateral signs of OTR, all patients with SKD (9 patients) also showed the other signs of OTR. Thus, a complete OTR was seen in 21% (table e-1 on the Neurology® Web site at www.neurology.org). The patients with combined cerebellar and brainstem lesions showed opposite results: only 15% (2 patients) had contralateral (SVV deviation 7.0° and 3.0°), but 46% had ipsilateral tilts of SVV (median 5.0°). Contralateral OT occurred in 15% (2 patients) (net tilt angle of the right eyes: 5°, 11°; and of the left eyes: 7°, 13°) and ipsilateral OT in 23% of the patients (median net tilt angle of the right eyes: 7.5°, and of the left eyes: 6°). Contralateral SKD was seen in one patient (5°); none had an ipsilateral SKD. Thus, there was a difference of the frequency between contra- and ipsilateral tilts of SVV in patients with pure and combined cerebellar lesions (␹219.58; p ⫽ 0). This indicates that more patients with purely cerebellar lesions had contralateral tilts of SVV. In patients with pure unilateral cerebellar lesions, the nonlinear regression models (p ⬍ 0.01) suggest that with increasing time since lesion, OT and tilts of the SVV last longer than 10 days, whereas SKD wears off within around 6 days (figure).

Thus, signs of OTR not only indicate brainstem, thalamic, or peripheral vestibular lesions but also unilateral cerebellar lesions, which affect structures involved in the processing of vestibular signals. These structures seem to form a pathway from the brainstem to the vermis (including the cerebellar peduncles, the dentate nucleus, pyramid of the vermis, nodulus, and uvula) and to the flocculus and tonsil.5 The specific structures lesioned, however, determine the directive of the signs, ipsilateral or contralateral. An affection of the dentate nucleus in particular was associated with contralateral signs of OTR, whereas in ipsilateral signs the dentate nucleus was spared and lesions were located in the middle cerebellar peduncle, tonsil, biventer, and inferior semilunar lobules.5

Discussion. Our data give evidence that OTR is a common sign in patients with unilateral cerebellar lesions, indicating that lesions of the cerebellum induce a dysfunction in otoliths pathways that mediate vestibular information in the roll plane. Single components such as tilts of the SVV can occur in up to 85% and show similar time courses to those in brainstem infarctions7 with the skew deviation as the most transient sign. However, the amount of the deviations in the acute phase was less in patients with cerebellar lesions (median of contralateral [5.1°] and ipsilateral SVV deviation [5.8°]), and highest in patients with medullary brainstem infarctions (Wallenberg syndrome, 9.8°) compared to that in acute vestibular neuritis (7.0°).7

2.

From the Department of Neurology (B.B., M.D.), University of Mainz; and Department of Neurology (M.D.), LudwigMaximillians-University, Munich, Germany. Supported by the DFG (DI 379/4-4). Disclosure: The authors report no disclosures. Received April 29, 2008. Accepted in final form September 24, 2008. Address correspondence and reprint requests to Dr. Bernhard Baier, Department of Neurology, University of Mainz, Langenbeckstr. 1, 55131 Mainz, Germany; [email protected] Copyright © 2009 by AAN Enterprises, Inc. AUTHOR CONTRIBUTIONS The statistical analysis was conducted by B.B.

ACKNOWLEDGMENT The authors thank Mrs. Benson for critically reading the manuscript.

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7.

Mossman S, Halmagyi GM. Partial ocular tilt reaction due to unilateral cerebellar lesion. Neurology 1997;49:491–493. Min W, Kim J, Park S, Suh C. Ocular tilt reaction due to unilateral cerebellar lesion. Neuroophthalmology 1999;22:81–85. Lee H, Lee SY, Lee SR, Park BR, Baloh RW. Ocular tilt reaction and anterior inferior cerebellar artery syndrome. J Neurol Neurosurg Psychiatry 2005;76:1742–1743. Wong AM, Sharpe JA. Cerebellar skew deviation and the torsional vestibuloocular reflex. Neurology 2005;65: 412–419. Baier B, Bense S, Dieterich M. Are signs of ocular tilt reaction in patients with cerebellar lesions mediated by the dentate nucleus? Brain 2008;131:1445–1454. Tatu L, Moulin T, Bogousslavsky J, Duvernoy H. Arterial territories of human brain. Brainstem and cerebellum. Neurology 1996;47:1125–1135. Cnyrim CD, Rettinger M, Mansmann U, et al. Central compensation of deviated subjective visual vertical in Wallenberg’s syndrome. J Neurol Neurosurg Psychiatry 2007;78:527–528.

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REFLECTIONS: NEUROLOGY AND THE HUMANITIES

A punder in Catch-22

Section Editor Michael H. Brooke, MD

Christopher J. Hammond Hubert H. Fernandez, MD Michael S. Okun, MD

Address correspondence and reprint requests to Dr. Hubert H. Fernandez, Department of Neurology, McKnight Brain Institute/University of Florida College of Medicine, PO Box 1000236, Gainesville, FL 32610 [email protected]

There was only one catch, and that was Catch-22, which specified that a concern for one’s safety in the face of dangers that were real and immediate was the process of a rational mind. Orr, a pilot and one of the main characters, was crazy and could be grounded. All he had to do was ask; and as soon as he did, he would no longer be crazy and he would have to fly more missions. Orr would be crazy to fly more missions and sane if he didn’t, but if he was sane he had to fly them. If he flew them he was crazy and didn’t have to, but if he didn’t want to, he was sane and had to. Yossarian was moved very deeply by the absolute simplicity of this clause of “Catch-22” and let out a respectful whistle. —Joseph Heller, Catch-22

These words from Joseph Heller’s dark and satirical novel have always stayed with us, reminding us of the vicious cycles that we get caught in as we proceed through our lives. The Oxford English Dictionary defines catch-22 as a “set of circumstances in which one requirement, etc., is dependent upon another, which is in turn dependent upon the first.” Into his first novel, Heller interweaves a series of these circular dilemmas, and, in doing so, has placed himself into the pages of literary history. But is there something more to this novel— does it provide an early example of a cyclic and pathologic behavior that might have a neurologic origin? Catch-22 tells the story of World War II flier John Yossarian and his fellow lead bombardiers as they attempt to survive the war while living under the shadow of a catch-22. In chapter 3, titled Havermayer, Yossarian, the main character and one of the pilots, returns from the infirmary to find a fellow bombardier named Orr performing an odd behavior. Orr, who, on the day Yossarian came back, was tinkering with the faucet that fed gasoline into the stove he had started building while Yossarian was in the hospital. “What are you doing?” Yossarian asked guardedly when he entered the tent, although he saw at once. “There’s a leak here,” Orr said. “I’m trying to fix it.” Orr was kneeling on the floor of the tent. He worked without pause, taking the faucet apart, spreading all the tiny pieces out carefully, counting and then studying each one interminably as though he had never seen anything remotely similar before, and then reassembling the whole small apparatus, over and over and over and over again, with no loss of patience or interest, no sign of fatigue, no indication of ever concluding.

There is a phenomenon in the neurology literature referred to as punding, which is very close in definition to the behaviors described in Heller’s book. The term punding has been used to describe the prolonged and purposeless complex stereotypical motor behaviors of amphetamine abusers. Punding is 574


characterized by an intense fascination with repetitive manipulation of technical or mechanical equipment, the continued handling, examining, and sorting of common objects, grooming, hoarding, abnormally increased writing, and even excessive nonsocially sanctioned dancing. The term punding comes from the amphetamine abusers themselves, who described their odd stereotyped behavior, which others have referred to as “being hung up,” “pottering,” or “knick knocking.” Punding can also be translated from Swedish slang to mean “blockhead.” Examples of punding behaviors include picking at oneself or taking apart watches and radios or sorting and arranging common objects such as lining up pebbles, rocks, or other small objects. Punding is probably best known from its description in patients with Parkinson disease who are being treated with dopamine agonists and L-dopa. Orr’s behavior during chapter 3 fits the current definition of punding as it is used in the neurology literature. When Yossarian returns from the infirmary, Orr is “hung up” in a purposeless complex behavior: taking apart a faucet, arranging the pieces, and putting it back together. In his description, Heller notes that Orr continues this perseverative behavior with no signs of fatigue, loss of interest, or indication of stopping. The literature has demonstrated that punders continue their behaviors for extended periods of time even to the point of urinating or defecating themselves instead of terminating the behavior. Another component of punding is that punders often lack insight into the bizarre and dysfunctional nature of their behaviors. When Yossarian approaches Orr and questions what he is doing and why, Orr responds that he is fixing a leak. This rationalization of his perseverative behavior has also been observed in some case reports of punding. Attempts to stop the stereotyped behaviors are in real life often met with resistance, irritability, and dysphoria from the punder. In Heller’s novel, Yossarian, after asking Orr what he is doing and why he is doing it, elects to not attempt to stop Orr from continuing his perseverative behavior. While the novel does not directly address his reasoning, it is implied that Yossarian does not feel he will be effective in stopping the behaviors, and for this reason he chooses not to inter-

fere as Orr continues dismantling and reassembling the faucet. Punding was first described in the medical literature by Rylander et al. in 1972. Joseph Heller wrote Catch-22 in the early 1950s and it was first published in 1961, 11 years before Rylander’s description. The thought must therefore cross one’s mind when reading this book: Is what I am reading the first description of punding? Did Joseph Heller describe punding 11 years before Rylander? If we are to assume that Heller’s character Orr represents, in actuality, the first case of punding, then this character would have to be based upon a real patient. Further exploration into Heller’s own personal history may help to shed light on this issue. In 1942, Joseph Heller joined the United States Army Air Corps. As a World War II bombardier, he flew 60 combat missions in B-25s over Northern Africa and Italy. While Heller did not intend his novel to be autobiographical in nature, he reported that much of his material came from his personal experiences as well as from the experiences of other friends who fought in World War II. The character of Orr was based upon a pilot named Edward Ritter, who was Joseph Heller’s tent-mate during the war. Heller himself describes Ritter as “something of a tireless

wonder as a handyman, one with unlimited patience who took pleasure in making and fixing things.” Heller’s description of Ritter is consistent with the intense fascination with and repetitive manipulation of technical, mechanical equipment that typifies punding, but it is unclear if Ritter’s behaviors are pathologic in nature. Heller does not reveal a background that would provide us with a likely etiology for his character’s punding, although the character was recovering from a closed head injury inflicted by the stiletto heel of a prostitute. Heller leaves much room for speculation as he reports, “it was on these qualities of his, his patient genius for building and fixing things and these recurring close calls in aerial combat, only on these, that I fashioned the character of Orr in Catch-22.” While it is speculative and he does not use the term punding in his novel, Heller likely observed and later integrated a case of punding into Catch-22, 11 years before Rylander’s description in the medical literature. We end this reflection with a question that is in the spirit of Catch-22. If Orr’s punding-like behaviors were not based upon Ritter, then we are faced with a circular dilemma: Which came first, the literary or the medical observation of punding?

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NEUROIMAGES

Bilateral radial nerve palsy in a newborn

Figure 1

Bilateral wrist drop

Figure 2

Induration with localized erythema

A boy was born at 42 weeks’ gestation following 4 days of labor. Epidural anesthesia was used. Bilateral wrist drop was noted immediately after delivery (figure 1). Induration with localized erythema was seen symmetrically on the dorsal aspect of both upper limbs (figure 2). Examination was in keeping with isolated bilateral radial nerve palsies. An ultrasound scan of the upper arms revealed symmetric thickening of the radial nerves distal to the radial groove at the posterolateral humerus. Electrophysiology tests suggested no evidence of acute denervation. Following physiotherapy and occupational therapy, improvement in the infant’s wrist position was seen within 2 weeks of birth. Postulated mechanisms for these injuries include reduced fetal activity for reasons including reduced amniotic fluid volume.1,2 Claire T. Lundy, MRCPCH, Sushma Goyal, MRCPCH, Silke Lee, FRCPCH, Tammy Hedderly, MRCPCH, London, UK Disclosure: The authors report no disclosures. Address correspondence and reprint requests to Dr. Claire Lundy, Department of Paediatric Neurology, Evelina Children’s Hospital, St Thomas’ Hospital, Lambeth Palace road, London, SE1 7EH, UK; [email protected] 1. 2.

576

Hayman M, Roland EH, Hill A. Newborn radial nerve palsy: report of four cases and review of published reports. Pediatr Neurol 1999;21:648–651. Richardson GA, Humphrey MS. Congenital compression of the radial nerve. J Hand Surg [Am] 1989;14:901–903.


RESIDENT & FELLOW SECTION Section Editor Mitchell S.V. Elkind, MD, MS

Michelle L. Mauermann, MD Ted M. Burns, MD

Address correspondence and reprint requests to Dr. Michelle L. Mauermann, Mayo Clinic, 200 First Street SW., Rochester, MN 55902 [email protected]

Pearls and Oy-sters: Evaluation of peripheral neuropathies

Peripheral neuropathy is common, with an estimated prevalence of ⬃2% in the general population and prevalence as high as 8% in those over the age of 55 years.1 Residents and fellows will undoubtedly evaluate many patients with various types of peripheral neuropathies during their careers. The evaluation for the etiology of a patient’s peripheral neuropathy can be challenging given the vast number of potential etiologies2,3 and the fact that despite an appropriate evaluation, a high percentage of cases will remain idiopathic.4,5 In this article, we provide a simple, easy-toremember algorithm that can simplify the evaluation of peripheral neuropathy. The evaluation of peripheral neuropathy should begin with the gathering of clinical data including the history of present illness, past medical history, family history, and physical examination. The determination of what of that clinical data is relevant requires knowledge of various diseases and the risk factors for those diseases. The information then needs to be synthesized in order to characterize the complaints and findings and determine an appropriate workup. The appropriate characterization of the complaints and findings is essential in order to perform an efficient, cost-effective, and successful evaluation. We recommend characterizing the neuropathy by answering four basic questions about the neuropathy: What? Where? When? What setting? (figure).6 This simple algorithm should facilitate the early step in clinical reasoning of creating a mental abstraction—that is, a problem representation or one-sentence summary of the defining and discriminating characteristics of the case.7 The creation of an accurate problem representation will allow the evaluating physician to focus on a small list of potential etiologies. This critical step in diagnostic reasoning will usually guide the physician down the correct diagnostic path, but it must be kept in mind that our algorithm is not absolute and there will always be cases that prove to be exceptions. The creation PERIPHERAL NEUROPATHY ALGORITHM

and utilization of problem representations will also serve as anchor points in memory that should allow the physician to more efficiently evaluate future cases and particularly to identify subtle but meaningful variations in similar cases.7 PEARLS FOR EVALUATING PERIPHERAL NEUROPATHY What? Determine what nerve fiber modali-

ties—motor, sensory, or autonomic—are involved. If sensory fibers are involved, sensory symptoms should be characterized into those with a positive sensation, such as prickling, tingling, or buzzing, vs those with a negative sensation, such as loss of sensation or imbalance. This differentiation is helpful because these positive sensory symptoms often suggest a neuropathy is acquired rather than inherited.4 Acquired neuropathies with large fiber dysfunction (either motor or sensory with loss of vibration, proprioception, or light touch) due to demyelination often have symptoms of weakness with or without ataxia with positive sensory symptoms such as tingling. Those with small fiber dysfunction (loss of pain or temperature) often have symptoms such as burning without weakness or ataxia. Small fiber neuropathies can have positive sensory symptoms such as burning, regardless of whether they are acquired or inherited. However, most types of inherited neuropathies tend to have more signs (examination abnormalities) than symptoms. The identification of sensory nerve fiber involvement in almost all instances excludes disorders of the anterior horn cell, neuromuscular junction, and muscle. Deciding whether weakness or sensory symptoms are more prominent can also be helpful because the inflammatory demyelinating neuropathies often manifest with weakness overshadowing sensory nerve fiber disturbance. Autonomic nerve involvement can be an important clue because only a small number of neuropathic processes affect both autonomic and somatic nerves such as diabetes, amyloidosis, acquired inflammatory demyelinating polyneuropathies, paraneoplastic syndromes,

From the Mayo Clinic (M.L.M.), Rochester, MN; and University of Virginia (T.M.B.), Charlottesville. Disclosure: The authors report no disclosures. e28


Figure

Pearls for classification of peripheral neuropathies

A suggested construct for the approach to neuropathy, using the “what, where, when, and what setting” approach to characterizing the neuropathy and placing the neuropathy into a presumed etiologic category. PNSS ⫽ positive neuropathic sensory symptoms; CMT ⫽ Charcot-Marie-Tooth; HMSN ⫽ hereditary motor and sensory neuropathies; HNPP ⫽ hereditary neuropathy with liability to pressure palsy; GBS ⫽ Guillain-Barre ´ syndrome; CIDP ⫽ chronic inflammatory demyelinating polyradiculoneuropathy; MMN ⫽ multifocal motor neuropathy; PAN ⫽ polyarteritis nodosa; SLE ⫽ systemic lupus erythematosus; RA ⫽ rheumatoid arthritis. Modified and reprinted with permission from Mauermann ML, Burns TM. The evaluation of acquired neuropathies. Semin Neurol 2008;28:133–151.6

Sjo¨gren syndrome, porphyria, HIV, and hereditary sensory and autonomic neuropathies. Where? Next decide if the distribution is length-

dependent and symmetric or not. Length-dependent neuropathies manifest first in the feet and are symmetric. Non-length-dependent neuropathies may be asymmetric, focal, or multifocal. The etiology of length-dependent neuropathies is usually inherited, metabolic/toxic, or idiopathic, whereas a neuropathy that is not lengthdependent is often caused by an immune-mediated or infectious process. Some examples of non-lengthdependent neuropathies are polyradiculoneuropathies (e.g., acquired inflammatory demyelinating polyneuropathies), plexopathies (often inflammatory), sensory polyganglionopathies (e.g., paraneoplastic subacute sensory neuronopathy caused by small cell lung cancer), and mononeuritis multiplex (caused by vasculitis). At times it may be difficult to determine whether the neuropathy is symmetric or asymmetric due to clinical pro-

gression, so it is best to ask the patient to describe the location of onset of symptoms followed by the distribution of subsequent progression. When? The onset of the neuropathy should be classified. The neuropathies that are acute or subacute in onset are more typical of an immune-mediated or infectious etiology. As patients have difficulty recalling the course, it is helpful to determine whether the symptoms had a definite date of onset. A less-exact date of onset suggests a gradual or insidious onset, indicative of inherited, idiopathic, or toxic/metabolic etiologies. The tempo following symptom onset is also an important consideration. Symptom onset and tempo often correlate in a predictable manner, owing largely to the underlying mechanism.6 What setting? The neuropathy has to be considered

within the context of the patient’s unique clinical circumstances. This is aided by determining what is Neurology 72

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relevant in the patient’s medical history, medication list, social history, family history, and the review of systems. An understanding of the significance of these clinical factors requires knowledge of the risk factors of neuropathy and knowledge of the clinical features of the diseases that may be risk factors for neuropathy. For example, unexplained weight loss raises concern for immune or neoplastic causes such as vasculitis, lymphoma, diabetic and nondiabetic lumbosacral radiculoplexus neuropathy, or a paraneoplastic autoimmune process. The clinician should always consider the most common causes of neuropathy such as diabetes, alcohol use, or inherited etiologies. Family members should be examined whenever possible. It is important for the neurologist to obtain an accurate alcohol consumption history and smoking history in a nonthreatening, nonjudgmental manner. Alcoholism is a very common problem and neuropathies due to alcohol use or secondary nutritional deficiencies can occur, so appropriate effort must be spent during the clinic visit investigating this possibility.6,8 Clinical neurophysiologic assessment. Characteriza-

tion using electrodiagnostic testing (EDX) is usually helpful in confirming the presence of a neuropathy and to further define motor and sensory involvement. EDX testing can be normal in small fiber neuropathies, very distal length-dependent neuropathies, and early neuropathic processes, particularly within the first few days. Normal EDX testing can also point to another etiology for the patient’s complaints, for example a myelopathy. EDX aids in determining if the neuropathy is primarily axonal or demyelinating. EDX can also help with defining symmetry, length-dependence, and subclinical involvement and provide baseline parameters in case future EDX in needed to monitor the patient’s course. Autonomic function may be assessed through autonomic reflex testing or other provocative testing, such as a thermoregulatory sweat test, which specifically assess the autonomic nervous system. AVOID THE OY-STERS There are three important tips

to keep in mind when evaluating peripheral neuropathies. 1. Do not let your sensory examination mislead you.

First, your patient almost certainly has sensory involvement if he or she complains of sensory symptoms, regardless of what you find on examination. It is well known that symptoms of sensory involvement are more sensitive for detecting sensory nerve dysfunction than signs on examination. For example, ⬃75% of patients with acute inflammatory neuropathies (i.e., Guillain-Barre´ syndrome) will complain of sensory symptoms at hospital admission but only e30

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⬃40% will have confirmatory findings on examination.9 Do not let that dissuade you from timely diagnosis and treatment. The second point about the sensory examination is that it is frequently misgraded as abnormal in the unaffected elderly patient and conversely misgraded as normal in the affected young patient. Age (and to a lesser extent height and other anthropomorphic features) must be factored into the judgment of whether sensory testing is normal or abnormal. Also remember that myelopathies can mimic peripheral neuropathy, particularly acute-onset neuropathies such as acute inflammatory neuropathies. Myelopathies often have more profound proprioceptive loss compared to vibration but this is not absolute and the physician should have a low threshold for obtaining imaging of the spinal cord in cases of possible myelopathy. The presence of bowel and bladder impairment can be a helpful differentiator as it strongly favors a myelopathy as the cause. 2. Not all asymmetric neuropathies are acquired.

While most inherited neuropathies cause symmetric symptoms and impairments, hereditary neuropathy with liability to pressure palsies (HNPP) often presents with multiple compressive mononeuropathies (e.g., ulnar, median, and peroneal nerves). Thus, HNPP is a relatively common neuropathy that does not conform well to our paradigm. However, family history, foot deformity, subtle details about the history, and the specific EDX characteristics of HNPP usually provide enough clues to prompt consideration and eventual diagnosis. Electrodiagnostic studies demonstrate multiple mononeuropathies with focal conduction blocks as well as generalized prolongation of distal latencies. 3. If it does not fit, acquit. If the characterization of a

particular neuropathy does not fit well with the clinical context, for example the medical history or an associated laboratory abnormality, one needs to look elsewhere. Conditions such as diabetes mellitus, hypothyroidism, and renal insufficiency are common in the general population and are most often associated with a length-dependent sensorimotor neuropathy without other systemic features. However, just because these conditions are common does not mean they are always the cause of the neuropathy. Furthermore, these patients are not immune to the development of other acquired neuropathies such as Guillain-Barre´ syndrome, chronic inflammatory demyelinating polyneuropathy, amyloidosis, or B12 deficiency. For example, approximately 2% of patients with type 1 diabetes and approximately 6% of patients with type 2 diabetes have other causes of neuropathy.10 REFERENCES 1. Martyn CN, Hughes RA. Epidemiology of peripheral neuropathy. J Neurol Neurosurg Psychiatry 1997;62:310–318.

2.

England JD, Asbury AK. Peripheral neuropathy. Lancet 2004;363:2151–2161. 3. Dyck PJ, Dyck PJ, Grant IA, Fealey RD. Ten steps in characterizing and diagnosing patients with peripheral neuropathy. Neurology 1996;47:10–17. 4. Dyck PJ, Oviatt KF, Lambert EH. Intensive evaluation of referred unclassified neuropathies yields improved diagnosis. Ann Neurol 1981;10:222–226. 5. Lubec D, Mullbacher W, Finsterer J, Mamoli B. Diagnostic work-up in peripheral neuropathy: an analysis of 171 cases. Postgrad Med J 1999;75:723–727. 6. Mauermann ML, Burns TM. The evaluation of chronic axonal polyneuropathies. Semin Neurol 2008;28:133–151.

7. Bowen JL. Educational strategies to promote clinical diagnostic reasoning. N Engl J Med 2006;355:2217– 2225. 8. Monforte R, Estruch R, Valls-Sole J, Nicolas J, Villalta J, Urbano-Marquez A. Autonomic and peripheral neuropathies in patients with chronic alcoholism: a doserelated toxic effect of alcohol. Arch Neurol 1995;52: 45–51. 9. Ropper AH. The Guillain-Barre´ syndrome. N Engl J Med 1992;326:1130–1136. 10. Dyck P. In: Horizons in Mayo Neurology and Neurosurgery: Perspectives on 100 Years and Future Trends. Rochester, MN: 2006.

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RESIDENT & FELLOW SECTION Section Editor Mitchell S.V. Elkind, MD, MS

A. Cianfoni, MD M. Luigetti, MD F. Madia, MD A. Conte, MD G. Savino, MD C. Colosimo, MD P.A. Tonali, MD M. Sabatelli, MD

Teaching NeuroImage: MRI of diabetic lumbar plexopathy treated with local steroid injection Figure 1

MRI findings in diabetic lumbar plexopathy

Address correspondence and reprint requests to Dr. Mario Sabatelli, Istituto di Neurologia, Pol. “A: Gemelli”, Largo Gemelli, 8, 00168 Rome, Italy [email protected]

MR neurography coronal images show increased caliber and T2 signal (A, B), and abnormal T1 contrast enhancement (C, D), of the right L3 nerve (short thin arrow), L4 nerve (long thin arrow), proximal portion of the femoral nerve (short thick arrow), and right obturator nerve (arrowheads).

Diabetic lumbosacral plexopathy is a well-recognized subacute, painful, asymmetric lower limb neuropathy associated with type II diabetes mellitus.1 MRI

findings of lumbosacral plexopathies have rarely been reported.2 A 60-year-old man with diabetes experienced subacute right L4 dermatome dysesthesias, as-

From the Department of Neurology (M.L., F.M., A. Conte, P.A.T., M.S.), and from Department of Bio-images and Radiological Sciences (A. Cianfoni, G.S., C.C.), Università Cattolica del Sacro Cuore-Policlinico “A Gemelli,” Rome, Italy. Disclosure: The authors report no disclosures. e32


Figure 2

CT-guided local steroid injection and follow-up MRI

CT-guided steroid injection (A, B) in the right L4 nerve sheet. The hyperdense contrast agent predicts the injectate spread. The follow-up MR neurography shows persistence of increased T2 signal and caliber of the right L4 nerve root (C), but marked reduction of contrast enhancement of the right lumbar plexus (D).

sociated with right lower extremity weakness graded on the Medical Research Council scale as 3/5 in the psoas, 0/5 in the quadriceps femoris, and 3/5 in the thigh adductors. Electromyography revealed evidence of widespread spontaneous activity in the same muscles. MRI disclosed abnormalities in the right L4 root and lumbar plexus (figure 1). A CT-guided steroid injection of triamcinolone acetonide 80 mg into the L4 nerve root sheet (figure 2, A and B) resulted in a reduction in the patient’s symptoms. A repeat MRI performed 1 month after the injection demonstrated marked reduction of radiologic abnormalities (figure 2, C and D); the patient’s dysesthesias resolved along with an improvement in muscle strength to 4/5 in the psoas and thigh adductors as well as 1/5 in the quadriceps. At last follow-up, 3 months after the injection, muscle strength was further improved (4/5 in the psoas, 2/5 in the quadriceps femoris, and 5/5 in thigh adductor muscles). Local CT-guided injection of corticosteroids may be a means of reducing the patient’s symptoms while minimizing the systemic side effects of oral or IV steroid therapy. This case study’s findings need to be confirmed in a randomized, double-blind, placebo-controlled trial.

REFERENCES 1. Dyck PJ, Windebank AJ. Diabetic and nondiabetic lumbosacral radiculoplexus neuropathies: new insights into pathophysiology and treatment. Muscle Nerve 2002;25:477–491. 2. Ishii K, Tamaoka A, Shoji S. MRI of idiopathic lumbosacral plexopathy. Neurology 2004;63:E6.

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Correspondence

MOTOR CORTEX STIMULATION FOR CHRONIC PAIN: SYSTEMATIC REVIEW AND META-ANALYSIS OF THE LITERATURE

To the Editor: I read the interesting review by Lima and Fregni.1 Motor cortical stimulation— especially invasive— can have significant beneficial effects on chronic pain. However, stimulations of any kind on the cortex, especially the motor cortex and thalamus, are known to precipitate seizures.2 From this study involving a novel modality of cortical stimulation, we would expect data on occurrence of seizures in the study populations. There are other studies where the effect of low-frequency electric stimulation had inhibitory effects on epileptic activity.3 It would have been ideal if the authors discussed epilepsy episodes as well, since seizures could be one of the major limiting side effects of this procedure. Joe Jacob Alappat, Safat, Kuwait

Rosa et al.5 and Wasserman6 provide a review of seizures and other adverse effects associated with rTMS. Nevertheless, numerous studies and expert opinions suggest that the induction of seizures can be avoided by careful consideration of the Summary of Guidelines for rTMS proposed by Wasserman.6 The safety guidelines specify the variables such as stimulus intensity, train duration, and frequency that are recommended to avoid seizures. Despite this, the induction of seizure is still possible as shown by our review of accidental cases and remains the greatest safety concern in the application of rTMS. We would also urge increased reporting of this adverse effect. Soroush Zaghi, Moises C. Lima, Felipe Fregni, Boston, MA Disclosure: The authors report no disclosures. Copyright © 2009 by AAN Enterprises, Inc. 1.

Disclosure: The author reports no disclosures. 2.

Reply from the Authors: Because repetitive transcranial magnetic stimulation (rTMS) can increase cortical excitability, this method of noninvasive brain stimulation can indeed induce seizures, especially when the stimulation is applied at high frequency for long durations with short intervals between the trains of stimulation. Low-frequency rTMS has an antiepileptic effect.4 Dr. Allapat mentions that our review lacks a discussion of the seizure-inducing profile of the invasive and noninvasive forms of motor cortex stimulation. Although it is true that the most common site of stimulation for the induction of seizure is the motor cortex, cases of unintentionally induced seizures are rare. Rosa et al.5 identified only eight cases of accidental seizure in their review. Our personal review of 140 relevant articles (updated through February 2008) of correct application of rTMS has yielded five cases in which convulsion was reported: two patients with depression; one with bipolar disorder; one with multiple sclerosis; and one healthy volunteer with a family history of epilepsy. No cases of convulsion or seizure-like activity were reported in any of the articles that we cited in our review.1

3.

4.

5.

6.

Lima MC, Fregni F. Motor cortex stimulation for chronic pain: systemic review and meta-analysis of the literature. Neurology 2008;70:2329 –2337. Rosa MA, Picarelli H, Teixeira MJ, et al. Accidental seizure with repetitive transcranial magnetic stimulation. J ECT 2006;22:265–266. Yamamoto J, Ikeda A. Low-frequency electric cortical stimulation has an inhibitory effect on epileptic focus in mesial temporal lobe epilepsy. Epilepsia 2002;43:491– 495. Fregni F, Otachi PT, Do Valle A, et al. A randomized clinical trial of repetitive transcranial magnetic stimulation in patients with refractory epilepsy. Ann Neurol 2006;60: 447– 455. Rosa MA, Odebrecht M, Rigonatti SP, Marcolin MA. Transcranial magnetic stimulation: review of accidental seizures. Rev Bras Psiquiatr [online] 2004;26:131–134. Wassermann EM. Risk and safety of repetitive transcranial magnetic stimulation: report and suggested guidelines from the International Workshop on the Safety of Repetitive Transcranial Magnetic Stimulation, June 5–7, 1996. Electroencephalogr Clin Neurophysiol 1998;108:1–16.

ELECTROCLINICAL CHARACTERISTICS OF MICTURITION-INDUCED REFLEX EPILEPSY

To the Editor: In this Teaching Video NeuroImage, Rathore et al.1 infer that a possible restricted midline epileptogenic focus based on observed ictal electroencephalography (EEG) activity was “confined to the Cz electrode.” The ictal activity seen in the figure appears to be limited to the Cz electrode. EEG is displayed using Neurology 72

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the common average montage, a referential montage that shows an ictal “beta burst” at the Cz electrode (without clear reflection at the adjacent scalp electrodes: C3, C4, Fz, Pz) and only lasting for ⬍1 sec (as seen in the 10-sec EEG page of the accompanying Video NeuroImage). There appears to be little or no further evolution of this activity so the inference that this represents an ictal pattern may be overstatement of the activity. In clinical EEG, activities confined to a single scalp electrode should be interpreted with caution and may represent noncerebral artifacts. Furthermore, there appears to be no clear evolution of this initial ictal discharge in terms of frequency, morphology, or distribution. Panel 3 of the figure shows evidence of diffuse attenuation and slowing of EEG activity which is a nonspecific finding, and may be seen in the context of cerebral hypoperfusion and other conditions. The child subsequently appears to recover on video and corresponding EEG activity is no longer attenuated. Furthermore, an apparently postictal, high amplitude, repetitive discharge (described as “2 Hz spikewave”) appears on the scalp recording, again fairly localized to the Cz electrode. We are not proposing an alternative diagnosis in this case but we would request clarification of the following: What happened to consciousness during the spells? Were the spells stereotyped (from the clinical and EEG perspectives)? How many spells were recorded under Video-EEG? Did the patient have spontaneous seizures? Were there any abnormalities noted during the interictal EEG recording? What was the course of treatment/response to anticonvulsants and follow-up? We would like to highlight the difficulties of scalp EEG interpretation in the provided images. While we agree that this is an interesting case to review, it may not be the best paradigm to promulgate for teaching purposes. Perhaps the same EEG epoch reformatted and using a longitudinal and transverse bipolar and an ipsilateral ear reference montage may provide additional clues. In addition, we would suggest recording multiple, electroclinically stereotyped events. Andreas V. Alexopoulos, Richard C. Burgess, Cleveland, OH Disclosure: The authors report no disclosures.

Reply from the Authors: We thank Drs. Alexopoulos and Burgess for their comments. Eight seizures were recorded and all of them had identical electroclinical semiology. The beta buzz in Cz was consistent in all of the seizures. The beta activity was followed by rhythmic spikes in Cz, which denotes 578

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evolution. These points exclude the suspicion of artifact. In addition to micturition-related seizures, the child has had two GTCS in the past during sleep. Interictal EEG showed few spikes at Cz during sleep. The child responded favorably to carbamazepine and has been seizure-free for nearly 10 months. C. Rathore, A. Radhakrishnan, S. Dinesh Nayak, K. Radhakrishnan, Kerala, India Disclosure: The authors report no disclosures. Copyright © 2009 by AAN Enterprises, Inc. 1.

Rathore C, Radhakrishnan A, Dinesh Nayak S, Radhakrishnan K. Teaching Video NeuroImage: Electroclinical characteristics of micturition-induced reflex epilepsy. Neurology 2008;70:e86.

USE OF ANTIHYPERTENSIVES AND THE RISK OF PARKINSON DISEASE

To the Editor: The objective of the article by Becker et al.1 was “to explore the association between antihypertensive drug use and the risk of developing a firsttime diagnosis of Parkinson’s disease (PD).” However, the authors mention the possible neuroprotective effects of angiotensin converting enzyme inhibitors and calcium channel blockers. If addressing possible neuroprotective effects is the primary purpose of the investigation, the logical analysis would be to examine whether use of different classes of antihypertensives among individuals who do not have PD is associated with future risk of developing PD. The results of such analysis were not included. The authors focused their main analyses on current use of antihypertensives, defined as at least one prescription during the 90 days preceding the date of the first recording of a diagnosis of PD in the electronic medical record. Because all patients with a diagnosis of PD will have had symptoms for at least a few months before the diagnosis, “current use” may not accurately reflect use during the relevant period of exposure, which is before the onset of PD symptoms. As the authors mention, tremor may lead to a new prescription of beta-blockers. Furthermore, a decline in blood pressure, which is frequent in individuals with PD, may lead to termination or change in antihypertensive medications. To overcome this potential source of bias, previous investigations using the same database—for example, to address the association between nonsteroidal anti-inflammatory drugs and PD risk2— considered only exposures during a period of at least 2 years before the recording in the medical record of the first symptoms of PD. This is because the disease onset is insidious and often preceded by several months of neurologic symptoms. We encourage Dr. Becker et al. to complement their interesting article by reporting whether use of

antihypertensives up to 2 years before the onset of PD symptoms was related to risk of PD. Alberto Ascherio, Caroline M. Tanner, Boston, MA Disclosure: The authors report no disclosures. Editor’s Note: The authors of the article were offered the opportunity to respond but declined. Copyright © 2009 by AAN Enterprises, Inc. 1.

2.

Becker C, Jick S, Meier C. Use of antihypertensives and the risk of Parkinson disease. Neurology 2008;70:1438 – 1444. Hernan MA, Logroscino G, Garcia Rodriguez LA. Nonsteroidal anti-inflammatory drugs and the incidence of Parkinson disease. Neurology 2006;66:1097–1099.

out Evidence of Dopaminergic Deficit (SWEDDs) findings2— has disadvantages. By using the term parkinsonism and not PD, patients may think that an atypical parkinsonism is being implied. However, this is probably not the case and the term should be carefully explained. Furthermore, time is required to observe whether the condition follows a typical course including response to treatment, and that no atypical features develop. In addition, patients and their families may conclude that the neurologist does not even know how to diagnose PD. Peter G. Bain, London, UK Disclosure: The author reports no disclosures.

CHANGING CONCEPTS IN PARKINSON DISEASE: MOVING BEYOND THE DECADE OF THE BRAIN

To the Editor: I congratulate Marras and Lang on their invited article concerning the changing concepts in Parkinson disease (PD). They provide three alternatives to define PD: 1) a clinical syndrome dominated by levodopa responsive parkinsonism; 2) a neuropathologic entity characterized by degeneration of the substantia nigra and formation of Lewy bodies; or 3) levodopa responsive parkinsonism associated with Lewy bodies. They opt for “an adult onset progressive disorder dominated by parkinsonism responsive to levodopa and commonly associated with motor complications.”1 The authors had previously termed this “classic parkinsonism.” I agree with Marras and Lang’s implicit view that clinicians need an accurate, nonspeculative, working definition for what can be observed. Thus current definitions based on pathologic findings (2 and 3 above) are outside in vivo clinical practice. As evidence for multiple etiologies for PD increases, it is clear that clinically it is a syndrome. Clinical terminology needs to evolve to avoid speculation about underlying pathology and to encompass advancing knowledge. Acknowledging these issues, I have used the term parkinsonism at the initial diagnosis. Subsequently, when the natural history and responsiveness to dopaminergic treatment is apparent, I switch to the term typical parkinsonism for what Marras and Lang deemed classic parkinsonism. However, neither label can be applied initially. This approach, although honest—particularly in the light of the Scans With1

Reply from the Authors: We thank Dr. Bain for his comments. We also regularly use the term parkinsonism when seeing patients initially and admit to them that, although PD is the most common cause of this syndrome, there is potential for confusion between this and other causes especially in the early years, even in the absence of red flags suggesting an alternative diagnosis. Like Dr. Bain, we have witnessed the skepticism that patients and families convey when a definitive diagnosis is not made. However, we agree that it is important to present these uncertainties using an honest and open approach to patients and their families. A concern about their belief that we are incapable of making a diagnosis of PD should not be a reason for presenting a level of diagnostic certainty that is not justified. Importantly, when we are incorrect about our initial suspicions that the patient has PD, their resentment can be considerable and understandable if they actually have a disease with a much graver prognosis. Anthony Lang, Connie Marras, Toronto, Ontario, Canada Disclosure: The authors report no disclosures. Copyright © 2009 by AAN Enterprises, Inc. 1.

2.

Marras C, Lang A. Changing concepts in Parkinson’s disease: moving beyond the decade of the brain. Neurology 2008;70:1996 –2003. Schneider SA, Edwards MJ, Mir P, et al. Patients with adult-onset dystonic tremor resembling parkinsonian tremor have scans without evidence of dopaminergic deficit (SWEDDs). Mov Disord 2007;22:2210 –2215.

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Calendar

Neurology® publishes short announcements of meetings and courses related to the field. Items must be received at least 6 weeks before the first day of the month in which the initial notice is to appear. Send Calendar submissions to Calendar, Editorial Office, Neurology®, Suite 214, 20 SW 2nd Ave., P.O. Box 178, Rochester, MN 55903 [email protected]

2009 FEB. 9 –11 Case Studies in Epilepsy Surgery will be held at the Silver Tree and Snowmass Conference Center in Snowmass, CO. Contact Martha Tobin at (216) 445-3449 or (800) 2232273, ext 53449, or at [email protected] for seminar details. FEB. 9 –13 The 22nd Annual Practicing Physician’s Approach to the Difficult Headache Patient will be held at the Camelback Inn, Scottsdale, AZ. Approved for AMA PRA Category 1 credit. Diamond Headache Clinic Research & Educational Foundation: tel (877) 706-6363 or (733) 883-2062; [email protected]; www.dhc-fdn.org. FEB. 16 –17 Fifth Annual Update Symposium on Clinical Neurology and Neurophysiology will be held in Tel Aviv, Israel. Presented by Weill Cornell Medical College, Department of Neurology, and Tel Aviv University, Adams Brain Supercenter. www.neurophysiology-symposium.com. FEB. 20 –22 International Symposium on Stereotactic Body Radiation Therapy and Stereotactic Radiosurgery will be held at the Floridian Resort & Spa in Lake Buena Vista, FL. Contact Martha Tobin at (216) 445-3449 or (800) 223-2273, ext 53449, or at [email protected] for seminar details. APR. 2– 4 The Innsbruck Colloquium on Status Epilepticus 2009 will be held at the Congress Innsbruck, Austria. [email protected]; www.innsbruck-SE2009.eu. APR. 3 5th Annual Contemporary Issues in Pituitary: Casebase Management Update will be held at the Cleveland Clinic Lerner Research Institute in Cleveland, OH. Contact Martha Tobin at (216) 445-3449 or (800) 223-2273, ext 53449, or at [email protected] for seminar details. APR. 20 –22 Leksell Gamma Knife® Perfexion™ Upgrade Course will be held at the Gamma Knife Center in Cleveland, OH. Contact Martha Tobin at (216) 445-3449 or (800) 2232273, ext 53449, or at [email protected] for seminar details. APR. 25–MAY 2 AAN Annual Meeting will be held in Seattle, Washington State Convention & Trade Center, WA. American Academy of Neurology: tel (800) 879-1960; www.aan.com/am. MAY 3– 6 2nd International Epilepsy Colloquium, Pediatric Epilepsy Surgery Cite´ Internationale will be held in Lyon, France. http://epilepsycolloquium2009ams.fr. MAY 6 –10 International SFEMG Course and Xth Quantitative EMG conference will be held in Venice, Italy. tel 39041-951112; [email protected]; www.congressvenezia.it.

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MAY 8 The Office of Continuing Medical Education at the University of Michigan Medical School is sponsoring a CME conference entitled: Movement Disorders: A Practical Approach. It is located at The Inn at St. John’s in Plymouth, Michigan. tel (734) 763-1400; fax (734) 936-1641. MAY 11–12 Music and the Brain will be held at the InterContinental Hotel & Bank of America Conference Center in Cleveland, OH. Contact Martha Tobin at (216) 4453449 or (800) 223-2273, ext 53449, or at [email protected] for seminar details. MAY 15–17 The Fifth International Conference on Alzheimer’s Disease and Related Disorders in the Middle East will be held in Limassol, Cyprus. www.worldeventsforum.com/alz. MAY 28 –30 6th International Headache Seminary. Focus on Headaches: New Frontier in Mechanisms and Management will be held at the Grand Hotel des Iles Borromees in Stresa (Italy); tel/fax 02 7063 8067; [email protected]. JUN. 8 –12 Leksell Gamma Knife® Perfexion™ Introductory Course will be held at the Gamma Knife Center in Cleveland, OH. Contact Martha Tobin at (216) 445-3449 or (800) 223-2273, ext 53449, or at [email protected] for seminar details. JUN. 12 Mellen Center Regional Symposium on Multiple Sclerosis will be held at the InterContinental Hotel & Bank of America Conference Center in Cleveland, OH. Contact Martha Tobin at (216) 445-3449 or (800) 223-2273, ext 53449, or at [email protected] for seminar details. JUN. 19 –24 Epileptology Symposium will be held at the InterContinental Hotel & Bank of America Conference Center, in Cleveland, OH. Contact Martha Tobin at (216) 445-3449 or (800) 223-2273, ext 53449, or at [email protected] for seminar details. JUL. 7–10 SickKids Centre for Brain & Behaviour International Symposium. [email protected]; www.sickkids.ca/ learninginstitute. JUL. 16 –18 Mayo Clinic Neurology in Clinical Practice2009 will be held at the InterContinental Hotel, Chicago, IL. Mayo CME: tel: (800) 323-2688; [email protected]; http:// www.mayo.edu/cme/neurology-neurologic-surgery.html. JUL. 21–27 Cleveland Spine Review 2009 will be held at the Embassy Suites Cleveland–Rockside Hotel in Independence, OH. Contact Martha Tobin at (216) 445-3449 or (800) 223-2273, ext 53449, or at [email protected] for seminar details.

AUG. 17–19 Leksell Gamma Knife® Perfexion™ Upgrade Course will be held at the Gamma Knife Center in Cleveland, OH. Contact Martha Tobin at (216) 445-3449 or (800) 223-2273, ext 53449, or at [email protected] for seminar details. SEP. 12–15 13th Congress of the European Federation of Neurological Societies will be held in Florence, Italy. For more information: tel ⫹41 22 908 0488; http://www.kenes.com/efns2009/ index.asp; [email protected]. SEP. 25 Practical Pearls in Neuro-Ophthalmology–International Symposium in Honour of Dr. James Sharpe will be held on September 25, 2009 at the University of Toronto Conference Centre, Toronto, Ontario. For further information contact the Office of Continuing Education & Professional Development, Faculty of Medicine, University of Toronto: tel (416) 978-2719; (888) 5128173; fax (416) 946-7028; [email protected]; http:// events.cmetoronto.ca/website/index/OPT0907. OCT. 8 –11 The Third World Congress on Controversies in Neurology. Full information is available at: ComtecMed - Medical Congresses, PO Box 68, Tel-Aviv, 61000 Israel; tel ⫹972– 3-5666166; fax ⫹972–3-5666177; [email protected]; www.comtecmed.com/cony.

OCT. 24 –30 19th World Congress of Neurology, WCN 2009, will be held in Bangkok, Thailand. www.wcn2009bangkok.com. NOV. 19 –22 The Sixth International Congress on Vascular Dementia will be held Barcelona, Spain. For further details, please contact: Kenes International 17 Rue du Cendrier, P.O. Box 1726, CH-1211, Geneva 1, Switzerland; tel ⫹41 22 908 0488; fax ⫹41 22 732 2850; [email protected]; http://www. kenes.com/vascular. DEC. 3– 6 Neuromodulation 2009 Encore will be held at Wynn Las Vegas in NV. Contact Martha Tobin at (216) 445-3449 or (800) 223-2273, ext 53449, or at [email protected] for seminar details. DEC. 7–11 Leksell Gamma Knife® Perfexion™ Introductory Course will be held at the Gamma Knife Center in Cleveland, OH. Contact Martha Tobin at (216) 445-3449 or (800) 223-2273, ext 53449, or at [email protected] for seminar details.

2010 MAY 2–7 11th International Child Neurology Congress will be held in Cairo, Egypt; http://www.icnc2010.com/.

Save These Dates for AAN CME Opportunities! Mark these upcoming dates on your calendar for these exciting continuing education opportunities, where you can catch up on the latest neurology information. AAN Annual Meetings ● April 25—May 2, 2009, Seattle, Washington State Convention & Trade Center ● April 10 –17, 2010, Toronto, Ontario, Canada, Toronto Convention Centre

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