Cargando…

Genome-wide association analysis identifies genetic variations in subjects with myalgic encephalomyelitis/chronic fatigue syndrome

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....

Descripción completa

Detalles Bibliográficos
Autores principales: Schlauch, K A, Khaiboullina, S F, De Meirleir, K L, Rawat, S, Petereit, J, Rizvanov, A A, Blatt, N, Mijatovic, T, Kulick, D, Palotás, A, Lombardi, V C
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4872418/
https://www.ncbi.nlm.nih.gov/pubmed/26859813
http://dx.doi.org/10.1038/tp.2015.208
_version_ 1782432722922242048
author Schlauch, K A
Khaiboullina, S F
De Meirleir, K L
Rawat, S
Petereit, J
Rizvanov, A A
Blatt, N
Mijatovic, T
Kulick, D
Palotás, A
Lombardi, V C
author_facet Schlauch, K A
Khaiboullina, S F
De Meirleir, K L
Rawat, S
Petereit, J
Rizvanov, A A
Blatt, N
Mijatovic, T
Kulick, D
Palotás, A
Lombardi, V C
author_sort Schlauch, K A
collection PubMed
description 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.
format Online
Article
Text
id pubmed-4872418
institution National Center for Biotechnology Information
language English
publishDate 2016
publisher Nature Publishing Group
record_format MEDLINE/PubMed
spelling pubmed-48724182016-05-27 Genome-wide association analysis identifies genetic variations in subjects with myalgic encephalomyelitis/chronic fatigue syndrome Schlauch, K A Khaiboullina, S F De Meirleir, K L Rawat, S Petereit, J Rizvanov, A A Blatt, N Mijatovic, T Kulick, D Palotás, A Lombardi, V C Transl Psychiatry Original Article 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. Nature Publishing Group 2016-02 2016-02-09 /pmc/articles/PMC4872418/ /pubmed/26859813 http://dx.doi.org/10.1038/tp.2015.208 Text en Copyright © 2016 Macmillan Publishers Limited http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
spellingShingle Original Article
Schlauch, K A
Khaiboullina, S F
De Meirleir, K L
Rawat, S
Petereit, J
Rizvanov, A A
Blatt, N
Mijatovic, T
Kulick, D
Palotás, A
Lombardi, V C
Genome-wide association analysis identifies genetic variations in subjects with myalgic encephalomyelitis/chronic fatigue syndrome
title Genome-wide association analysis identifies genetic variations in subjects with myalgic encephalomyelitis/chronic fatigue syndrome
title_full Genome-wide association analysis identifies genetic variations in subjects with myalgic encephalomyelitis/chronic fatigue syndrome
title_fullStr Genome-wide association analysis identifies genetic variations in subjects with myalgic encephalomyelitis/chronic fatigue syndrome
title_full_unstemmed Genome-wide association analysis identifies genetic variations in subjects with myalgic encephalomyelitis/chronic fatigue syndrome
title_short Genome-wide association analysis identifies genetic variations in subjects with myalgic encephalomyelitis/chronic fatigue syndrome
title_sort genome-wide association analysis identifies genetic variations in subjects with myalgic encephalomyelitis/chronic fatigue syndrome
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4872418/
https://www.ncbi.nlm.nih.gov/pubmed/26859813
http://dx.doi.org/10.1038/tp.2015.208
work_keys_str_mv AT schlauchka genomewideassociationanalysisidentifiesgeneticvariationsinsubjectswithmyalgicencephalomyelitischronicfatiguesyndrome
AT khaiboullinasf genomewideassociationanalysisidentifiesgeneticvariationsinsubjectswithmyalgicencephalomyelitischronicfatiguesyndrome
AT demeirleirkl genomewideassociationanalysisidentifiesgeneticvariationsinsubjectswithmyalgicencephalomyelitischronicfatiguesyndrome
AT rawats genomewideassociationanalysisidentifiesgeneticvariationsinsubjectswithmyalgicencephalomyelitischronicfatiguesyndrome
AT petereitj genomewideassociationanalysisidentifiesgeneticvariationsinsubjectswithmyalgicencephalomyelitischronicfatiguesyndrome
AT rizvanovaa genomewideassociationanalysisidentifiesgeneticvariationsinsubjectswithmyalgicencephalomyelitischronicfatiguesyndrome
AT blattn genomewideassociationanalysisidentifiesgeneticvariationsinsubjectswithmyalgicencephalomyelitischronicfatiguesyndrome
AT mijatovict genomewideassociationanalysisidentifiesgeneticvariationsinsubjectswithmyalgicencephalomyelitischronicfatiguesyndrome
AT kulickd genomewideassociationanalysisidentifiesgeneticvariationsinsubjectswithmyalgicencephalomyelitischronicfatiguesyndrome
AT palotasa genomewideassociationanalysisidentifiesgeneticvariationsinsubjectswithmyalgicencephalomyelitischronicfatiguesyndrome
AT lombardivc genomewideassociationanalysisidentifiesgeneticvariationsinsubjectswithmyalgicencephalomyelitischronicfatiguesyndrome