Maya et al. (2025)
- Authors: Jessica Maya, Elizabeth R. Unger, Jin-Mann S. Lin, Mangalathu S. Rajeevan
- Institutes: Division of High-Consequence Pathogens & Pathology, Centers for Disease Control & Prevention, Atlanta, GA, USA
- Publisher: Preprints.org
- Link: DOI
Summary
This research identifies a distinct genetic and inflammatory signature in a subset of ME/CFS patients involving the complement system. By linking specific genetic variants to protein levels, it provides a biological basis for the ‘inflammatory subgroup’ of the disease. These results could lead to more accurate diagnostic tests and targeted treatments for patients whose illness is driven by these specific immune pathways. The validation using UK Biobank data adds significant weight to the relevance of these findings for broader fatigue-related conditions.
What was researched?
The study investigated whether genetic variants, specifically protein quantitative trait loci (pQTLs), are associated with plasma complement protein levels in ME/CFS patients. It aimed to identify genetic drivers of immune dysregulation within the complement system to help explain patient heterogeneity.
Why was it researched?
ME/CFS is a complex illness with unclear biological causes and significant patient variability. The researchers sought to understand the genetic basis of previous findings showing immune and complement system involvement in the disease to improve patient stratification.
How was it researched?
Researchers performed pQTL analyses on a cohort of 50 ME/CFS patients and 121 non-fatigued controls to identify genetic variants associated with plasma complement protein levels. They analyzed 9,146 single-nucleotide polymorphisms (SNPs) and compared significant results with fatigue-related phenotypes in the UK Biobank. Statistical models were adjusted for relevant covariates to ensure the robustness of the genetic associations.
What has been found?
The study identified 3,192 SNPs associated with complement proteins, including 11 variants previously linked to ME/CFS. A distinct patient subgroup was characterized by a ‘high C3/low Bb’ profile, indicating specific dysregulation of the alternative complement pathway. Six significant pQTLs were independently validated through their association with fatigue-related phenotypes in the UK Biobank database.
Discussion
The findings highlight a genetic mechanism by which risk alleles contribute to the inflammatory diversity observed in ME/CFS. While the study identifies potential predictive markers like C3 and Factor B, the relatively small sample size necessitates further validation in larger cohorts. The integration of genetic and proteomic data is shown to be a powerful method for subtyping complex chronic illnesses.
Conclusion & Future Work
The research establishes a genetic link to complement system dysregulation in a specific subgroup of ME/CFS patients. This discovery supports the use of pathway-focused subtyping to guide future personalized diagnostic and therapeutic strategies for the illness.