1. Genome-wide association analysis identifies genetic variations in subjects with myalgic encephalomyelitis/chronic fatigue syndrome.
- Author
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Schlauch KA, Khaiboullina SF, De Meirleir KL, Rawat S, Petereit J, Rizvanov AA, Blatt N, Mijatovic T, Kulick D, Palotás A, and Lombardi VC
- Subjects
- Female, Genetic Predisposition to Disease genetics, Humans, Male, Middle Aged, Pilot Projects, Polymorphism, Single Nucleotide, Fatigue Syndrome, Chronic genetics, Genetic Variation genetics, Genome-Wide Association Study methods
- Abstract
Myalgic encephalomyelitis, also known as chronic fatigue syndrome or ME/CFS, is a multifactorial and debilitating disease that has an impact on over 4 million people in the United States alone. The pathogenesis of ME/CFS remains largely unknown; however, a genetic predisposition has been suggested. In the present study, we used a DNA single-nucleotide polymorphism (SNP) chip representing over 906,600 known SNPs to analyze DNA from ME/CFS subjects and healthy controls. To the best of our knowledge, this study represents the most comprehensive genome-wide association study (GWAS) of an ME/CFS cohort conducted to date. Here 442 SNPs were identified as candidates for association with ME/CFS (adjusted P-value<0.05). Whereas the majority of these SNPs are represented in non-coding regions of the genome, 12 SNPs were identified in the coding region of their respective gene. Among these, two candidate SNPs resulted in missense substitutions, one in a pattern recognition receptor and the other in an uncharacterized coiled-coil domain-containing protein. We also identified five SNPs that cluster in the non-coding regions of T-cell receptor loci. Further examination of these polymorphisms may help identify contributing factors to the pathophysiology of ME/CFS, as well as categorize potential targets for medical intervention strategies.
- Published
- 2016
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