Researchers have identified 259 genes associated with chronic fatigue syndrome, or myalgic encephalomyelitis, in the largest genetic analysis to date. This finding multiplies the number of implicated genes by six compared to a study just four months earlier. The work suggests potential paths for new treatments by targeting genetic factors.
Chronic fatigue syndrome, also known as myalgic encephalomyelitis (ME/CFS), is a debilitating condition often triggered by infections, featuring severe post-exertional malaise where minor activities cause extended exhaustion. A new study, led by Steve Gardner at Precision Life in Oxford, analyzed genomic data from over 10,500 individuals diagnosed with ME/CFS, collected through the DecodeME project. By comparing this to data from the UK Biobank, the team examined single nucleotide polymorphisms (SNPs), which are single-letter changes in the DNA sequence.
Unlike traditional methods that assess SNPs individually, the researchers grouped them to capture interactions in complex diseases. They identified 22,411 groups involving 7,555 SNPs linked to ME/CFS risk, noting that more such groups increase the likelihood of developing the condition. These SNPs mapped to 2,311 genes, with 259 core genes showing the strongest associations and most common variants.
This builds on an August DecodeME analysis that pinpointed 43 genes and variants in eight genomic regions. The current study confirmed all eight regions, validating them as true risk factors. Gardner emphasized the potential: “It’s opening up a huge number of new avenues, either for novel therapy development or for drug repurposing.” Currently, no targeted treatments exist; management relies on painkillers, antidepressants, and energy conservation strategies.
The research also explores overlaps with long covid, another infection-triggered illness with similar symptoms. About 42 percent of genes linked to long covid appeared in the ME/CFS analysis, indicating partial genetic similarity, though methodological differences caution against overconfidence. Experts like Jacqueline Cliff at Brunel University London praised the approach: “That’s where they start to take the thing forward.” Danny Altmann at Imperial College London views this as a breakthrough: “We’re at a coming of age in terms of genomics and pathophysiology,” after decades of neglect.
Previous smaller studies yielded inconsistent results due to limited scale, but larger datasets now reveal clearer signals. Ongoing efforts, including a £1.1 million project by Altmann and Rosemary Boyton, will probe immune, viral, and microbiome factors in both conditions to enable personalized interventions.
