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A study published in Journal of Translational Medicine looks at shared biological mechanisms between ME/CFS, Long COVID, PTSD, Rheumatoid Arthritis, and Multiple Sclerosis.
Dr Sjoerd Beentjes, Lecturer & Chancellor’s Fellow, Institute of Genetics and Cancer (IGC), UoE, University of Edinburgh, said:
“The study’s authors use the proprietary EpiSwitch computational methods and posit that regulatory pathways are shared across five conditions, ME/CFS, Long Covid, post-traumatic stress disorder, multiple sclerosis, and rheumatoid arthritis. However, the claim “What we discovered is something approaching a biological unifying theory of fatigue” made by the lead researcher seems an overstatement.
“Methodologically, sample splitting is applied to honestly assess the performance of trained prediction models on a completely separate validation set to avoid data leakage, and the authors take care to adjust for the many statistical tests that are performed.
“A limitation is that precise metrics are missing that quantify how similar (or indeed unifying) the StringDB regulatory networks are for the five conditions above, relative to a network produced from a set of five other conditions. In this sense, the results seem mostly descriptive. What is unhelpful in understanding the work’s main conclusions, is the fact that the EpiSwitch computational tools leading to this result, are proprietary and not open to scrutiny by the scientific community.”
Prof Chris Ponting, Chair of Medical Bioinformatics and Principal Investigator at the MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, said:
“This study’s authors propose that there are regulatory pathways common to Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS), Long COVID (LC), post-traumatic stress disorder (PTSD), multiple sclerosis (MS) and/or rheumatoid arthritis (RA). In their press release, they say that: “What we discovered is something approaching a biological unifying theory of fatigue.”
“Their approach was to integrate their previously described ME/CFS chromosome conformation data set (Hunter et al., 2025) with genome-wide association study summary statistics for these diseases. As I summarised previously,their 2025 ME/CFS results could have been confounded by sex, age, and batch.
“Unfortunately, the 2026 study’s claims are impossible to evaluate because the computational methods they used are proprietary, locked within black boxes they term EpiSwitch® Analytical and Data Portals, Knowledgebase and Orion v1 anchor detection. Researchers are thus disallowed from reproducing this study independently.
“What is clear from the methods is that “3D genomic anchors” are predicted for each disease using genome-wide association study summary statistics. Most of these anchors will have only very weak statistical support from genetics. This is because the authors apply a highly permissive filter (p < 0.01), rather than the usual stringent threshold of p < 5 x10-8.
“Another likely limitation is a cellular mismatch between the chromosome conformation data, derived from circulating blood cells, and the GWAS data that implicates other cell types: lung epithelial cells and alveolar macrophages for Long Covid, and cortical neurons for PTSD and likely ME/CFS. This is important because different types of cell (e.g., T-cells vs neurons) typically adopt different chromosome conformations.”
Prof Carmine Pariante, Professor of Biological Psychiatry at the Institute of Psychiatry, Psychology and Neuroscience at King’s College London, said:
“The study by Hunter et al. presents largely confirmatory evidence that immune-related mechanisms are involved not only in autoimmune disorders but also in stress-related conditions like post-traumatic stress disorder (PTSD) as well as conditions at the interface between the brain and the body, like long-Covid and ME/CFS. They use an innovative method to integrate data from different genetic signatures, but they do so with already collected and published datasets, and they do not really identify novel mechanisms or concepts. Nevertheless, the strength of the confirmatory evidence in the article will be helpful for researchers in the field as well as people with lived experience of these disorders.”
‘Beyond Genes: EpiSwitch® and Orion Platform-powered 3D Genome Architecture Biomarkers Reveal Shared Biology Across ME/CFS, Long COVID, PTSD, Rheumatoid Arthritis, and Multiple Sclerosis’ by Hunter et al. was published in Journal of Translational Medicine at 00:01 UK time on Thursday 3 September.
Declared interests
Dr Sjoerd Beentjes: Dr Sjoerd Beentjes has received funding from ME Research UK for his ME/CFS research.
Prof Chris Ponting has received funding from the MRC, NIHR, the UK Government, Action for ME and ME Research UK for his ME/CFS research.
Prof Carmine Pariante: Professor Pariante’s research on depression and inflammation is funded by the Wellcome Trust. He is also part of a collaboration between KCL and UCB looking at molecular mechanisms underpinning fatigue.