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
Copyright © 2009 by AAN Enterprises, Inc.
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
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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
Copyright © 2009 by AAN Enterprises, Inc.
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-
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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
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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
Copyright © 2009 by AAN Enterprises, Inc.
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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491
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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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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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
Copyright © 2009 by AAN Enterprises, Inc.
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
February 10, 2009
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.
5.
6.
7.
8.
9.
10.
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.
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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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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
Superior frontal gyrus
10
⫺58
⫺44
40
3.81
Inferior parietal gyrus
40
⫺59
⫺43
35
2.56
Inferior parietal gyrus
40
⫺53
⫺49
43
2.48
Inferior parietal gyrus
40
⫺38
58
4
2.80
Superior frontal gyrus
10
⫺42
58
8
2.60
Superior frontal gyrus
10
4
⫺37
40
3.42
Posterior cingulate gyrus
31
⫺3
⫺44
42
3.24
Posterior cingulate gyrus
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
Middle temporal gyrus
21
151
⫺26
⫺16
⫺24
2.36
Parahippocampal gyrus
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
Middle temporal gyrus
21
58
4
⫺16
2.54
Middle temporal gyrus
21
63
⫺8
⫺4
2.13
Superior temporal gyrus
21/22
63
3
⫺41
28
2.43
Posterior cingulate gyrus
31
⫺4
⫺43
32
2.70
Posterior cingulate gyrus
31
30
63
1
2.48
Superior frontal gyrus
10
38
60
8
2.44
Superior frontal gyrus
10
27
⫺12
⫺20
2.45
Hippocampus
25
⫺15
⫺24
2.44
Parahippocampal gyrus
36
28
⫺15
⫺16
2.34
Hippocampus
110
⫺51
⫺49
45
2.29
Inferior parietal gyrus
40
88
⫺36
61
⫺1
2.45
Superior frontal gyrus
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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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
Inferior frontal gyrus
47
76
41
56
⫺4
4.48
Superior frontal gyrus
10
45
48
47
16
4.44
Superior frontal gyrus
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
Inferior frontal gyrus
45
36
61 ⫺15 ⫺16
4.81
Middle temporal gyrus
21
4.01
Inferior frontal gyrus
11
CMRglc reductions at follow-up as compared to baseline in FHm 5961
2534
61 ⫺37
32
7.99
Inferior parietal gyrus
40
⫺57 ⫺47
40
7.71
Inferior parietal gyrus
40
⫺3 ⫺67
40
5.94
Precuneus
⫺29 ⫺72
44
5.18
Precuneus
4 ⫺48
32
5.42
Posterior cingulate gyrus
31
⫺49 ⫺56
45
3.44
Inferior parietal gyrus
40
⫺61 ⫺56
4
4.44
Middle temporal gyrus
21/37
⫺60 ⫺54 734
150
7
⫺1
4.05
Middle temporal gyrus
21/37
7
⫺3
4.22
Superior temporal gyrus
22
63 ⫺11
21/22
59
⫺4
5.25
Superior temporal gyrus
4
1
3.58
Insula
64 ⫺29
⫺1
3.88
Middle temporal gyrus
21
60 ⫺42
4
3.84
Middle temporal gyrus
21
40
2
3.15
Superior frontal gyrus
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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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.
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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
Copyright © 2009 by AAN Enterprises, Inc.
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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537
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 sub
