PrecisionLife has released the most detailed genetic analysis of myalgic encephalomyelitis (ME/CFS) to date, identifying more than 250 core genes and 76 overlaps with long COVID.
The findings also point to dozens of drug-repurposing opportunities backed by genetic biomarker tests.
The study applied PrecisionLife's AI-led combinatorial analytics platform to analyse genomic data from two DecodeME cohorts together with the UK Biobank to confirm reproducibility of results across three independent datasets.
The analysis identified 7555 genetic variants (including the eight identified by the recent DecodeME GWAS study) that were consistently associated with increased disease risk in three different populations.
These results confirm that ME is a deeply polygenic and biologically heterogeneous condition with at least four major disease mechanisms implicated by genetic signals: neurological dysregulation, inflammation, cellular stress response and calcium signalling.
These findings have important implications for the future of ME research and treatment.
They reinforce the need for a stratified approach, with genetic evidence pointing to multiple biological subgroups within the disease.
This means that future clinical trials are likely to be more successful when they target specific patient subtypes rather than treating ME as a single, uniform condition.
This also aligns closely with the lived experience of many people in the ME community, who have long recognised the diversity of symptoms and disease patterns.
The study also demonstrated a strong genetic overlap between ME and long COVID, with 76 of 180 genes previously linked to long COVID also significantly associated with ME in the DecodeME dataset.
This indicates that ME and long COVID are overlapping but different conditions, where their shared biological pathways offer promising potential for developing drug therapies that could successfully treat patients with either condition.
To support global research efforts, PrecisionLife has published the full list of SNPs and genes identified in this analysis, enabling academic groups, clinicians and biopharma researchers to accelerate drug repurposing studies, target discovery and development of new mechanism-based therapies.
ME and long COVID together affect an estimated 400 million people worldwide, contributing more than $1tn annually to healthcare costs and lost economic productivity.
The lack of diagnostic tools, effective treatments or biological clarity on its causes has contributed to decades of unmet need for patients and prolonged underinvestment in development of research and healthcare pathways.
Dr Steve Gardner, CEO of PrecisionLife, said: "These results reinforce that ME has a clear biological and genetic basis and is a complex multisystemic disease."
"ME is highly polygenic and heterogeneous, so no single drug will help everyone."
"Stratifying patients by the mechanisms that are driving their disease will be essential for predicting who will benefit from which therapies and for developing accurate diagnostic tests."
"We’re beginning to have this level of insight and we hope that in the future the genetic biomarkers we’ve identified for existing and new drug repurposing candidates could help make trials with collaborators worldwide more successful."
Sonya Chowdhury, CEO of Action for ME, added: "These findings offer further hope to people with ME around the world."
"For decades, people affected by ME have lacked recognition, access to proper diagnosis and effective treatments."
"PrecisionLife’s results represent a major step forward in understanding the biology of the disease and provide real opportunities for targeted therapies to move into clinical testing."
"We are proud that DecodeME has helped pave the way for this progress and we will continue to champion research that delivers meaningful benefits for the community."
Prof Chris Ponting, Chair of Medical Bioinformatics at the Institute of Genetics and Cancer, University of Edinburgh and investigator on the DecodeME study, said: "DecodeME was designed to reveal the complex genetics of ME by providing a dataset of the scale and quality required for robust discovery."
"PrecisionLife has shown how making such datasets available can quickly generate new insights into ME disease biology."
"This is an exciting outcome of making consented DecodeME data available to research partners and we look forward to enabling further future collaborations."
The research forms part of the LOCOME (LOng COvid and Myalgic Encephalomyelitis) programme, led by PrecisionLife and funded in part by Innovate UK.
The LOCOME programme was delivered in collaboration with Action for ME and the University of Edinburgh.