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Journal of Translational Medicine

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Open Access 01-12-2022 | Fibromyalgia | Research

Genetic risk factors for ME/CFS identified using combinatorial analysis

Authors: Sayoni Das, Krystyna Taylor, James Kozubek, Jason Sardell, Steve Gardner

Published in: Journal of Translational Medicine | Issue 1/2022

Abstract

Background

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a debilitating chronic disease that lacks known pathogenesis, distinctive diagnostic criteria, and effective treatment options. Understanding the genetic (and other) risk factors associated with the disease would begin to help to alleviate some of these issues for patients.

Methods

We applied both GWAS and the PrecisionLife combinatorial analytics platform to analyze ME/CFS cohorts from UK Biobank, including the Pain Questionnaire cohort, in a case–control design with 1000 cycles of fully random permutation. Results from this study were supported by a series of replication and cohort comparison experiments, including use of disjoint Verbal Interview CFS, post-viral fatigue syndrome and fibromyalgia cohorts also derived from UK Biobank, and compared results for overlap and reproducibility.

Results

Combinatorial analysis revealed 199 SNPs mapping to 14 genes that were significantly associated with 91% of the cases in the ME/CFS population. These SNPs were found to stratify by shared cases into 15 clusters (communities) made up of 84 high-order combinations of between 3 and 5 SNPs. p-values for these communities range from 2.3 × 10^–10 to 1.6 × 10^–72. Many of the genes identified are linked to the key cellular mechanisms hypothesized to underpin ME/CFS, including vulnerabilities to stress and/or infection, mitochondrial dysfunction, sleep disturbance and autoimmune development. We identified 3 of the critical SNPs replicated in the post-viral fatigue syndrome cohort and 2 SNPs replicated in the fibromyalgia cohort. We also noted similarities with genes associated with multiple sclerosis and long COVID, which share some symptoms and potentially a viral infection trigger with ME/CFS.

Conclusions

This study provides the first detailed genetic insights into the pathophysiological mechanisms underpinning ME/CFS and offers new approaches for better diagnosis and treatment of patients.

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Title: Genetic risk factors for ME/CFS identified using combinatorial analysis
Authors: Sayoni Das
Krystyna Taylor
James Kozubek
Jason Sardell
Steve Gardner
Publication date: 01-12-2022
Publisher: BioMed Central
Keywords: Fibromyalgia
Fibromyalgia
Published in: Journal of Translational Medicine / Issue 1/2022
Electronic ISSN: 1479-5876
DOI: https://doi.org/10.1186/s12967-022-03815-8

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