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Genome-wide estimate of the heritability of Multiple System Atrophy.
Federoff, M; Price, T R; Sailer, A; Scholz, S; Hernandez, D; Nicolas, A; Singleton, A B; Nalls, M; Houlden, H.
Affiliation
  • Federoff M; Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD 20892, USA; Department of Molecular Neuroscience, UCL Institute of Neurology, London, UK. Electronic address: monica.federoff22@gmail.com.
  • Price TR; Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD 20892, USA.
  • Sailer A; Department of Molecular Neuroscience, UCL Institute of Neurology, London, UK.
  • Scholz S; Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD 20892, USA; Neurodegenerative Diseases Research Group, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA.
  • Hernandez D; Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD 20892, USA.
  • Nicolas A; Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD 20892, USA.
  • Singleton AB; Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD 20892, USA.
  • Nalls M; Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD 20892, USA.
  • Houlden H; Department of Molecular Neuroscience, UCL Institute of Neurology, London, UK.
Parkinsonism Relat Disord ; 22: 35-41, 2016 Jan.
Article in En | MEDLINE | ID: mdl-26589003
ABSTRACT

INTRODUCTION:

Multiple System Atrophy (MSA) is a neurodegenerative disease which presents heterogeneously with symptoms and signs of parkinsonism, ataxia and autonomic dysfunction. Although MSA typically occurs sporadically, rare pathology-proven MSA families following either autosomal recessive or autosomal dominant patterns have been described, indicating a heritable contribution to the pathogenesis.

METHODS:

We used Genome-Wide Complex Trait Analysis (GCTA) to estimate the heritable component of MSA due to common coding variability in imputed genotype data of 907 MSA cases and 3866 population-matched controls. GCTA only assesses the effect of putative causal variants in linkage disequilibrium (LD) with all common SNPs on the genotyping platform.

RESULTS:

We estimate the heritability among common variants of MSA in pooled cases at 2.09-6.65%, with a wider range of values in geographic and diagnostic subgroups. Meta-analysis of our geographic cohorts reveals high between-group heterogeneity. Contributions of single chromosomes are generally negligible. We suggest that all calculated MSA heritability among common variants could be explained by the presence of misdiagnosed cases in the clinical subgroup based on a Bayesian estimate using literature-derived rates of misdiagnosis.

DISCUSSION:

MSA is a challenging disease to study due to high rates of misdiagnosis and low prevalence. Given our low estimates of heritability, common genetic variation appears to play a less prominent role in risk for MSA than in other complex neurodegenerative diseases such as Parkinson's disease, Alzheimer's disease, and Amyotrophic Lateral Sclerosis. The success of future gene discovery efforts rests on large pathologically-confirmed case series and an interrogation of both common and rare genetic variants.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Multiple System Atrophy Type of study: Etiology_studies / Incidence_studies / Observational_studies / Risk_factors_studies Limits: Humans Language: En Journal: Parkinsonism Relat Disord Journal subject: NEUROLOGIA Year: 2016 Document type: Article

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Multiple System Atrophy Type of study: Etiology_studies / Incidence_studies / Observational_studies / Risk_factors_studies Limits: Humans Language: En Journal: Parkinsonism Relat Disord Journal subject: NEUROLOGIA Year: 2016 Document type: Article
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