Researchers at the University of East Anglia and Oxford BioDynamics have published a study in the Journal of Translational Medicine identifying a potential biological unifying theory of chronic fatigue. By examining three-dimensional genome architecture across long Covid, ME/CFS, PTSD, rheumatoid arthritis, and multiple sclerosis, the team found that distinct medical triggers converge on shared immune, metabolic, and stress-response networks.
Investigators Analyze How DNA Folds Inside Human Cells
Led by Prof Dmitry Pshezhetskiy from the UEA Norwich Medical School, investigators analyzed how DNA folds inside human cells rather than looking solely at linear genetic sequences. The team utilized Oxford BioDynamics’ EpiSwitch Orion platform to map genomic contact points. Because distant sections of DNA touch when folded, these spatial contact points dictate gene control and regulation. The study was strictly computational, drawing on existing genome-wide association studies for long Covid, PTSD, rheumatoid arthritis, and multiple sclerosis, alongside 3D genomic data from a previous ME/CFS cohort.
When evaluated at the individual gene level, researchers found surprisingly little direct overlap across the five conditions. However, analyzing how those genes interact within complex biological networks revealed a different picture. “Suddenly, the diseases appeared deeply connected,” Prof Pshezhetskiy stated. The computational models showed that disparate illnesses feed into major regulatory pathways, including mitochondrial energy production, metabolic regulation, and neuroendocrine signaling.
From Diverse Triggers to Shared Cellular Disruption
The findings offer a mechanistic explanation for why vastly different inciting events produce remarkably similar clinical presentations. While myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) often follows viral infections, long Covid develops after SARS-CoV-2 infection, post-traumatic stress disorder emerges after traumatic experiences, rheumatoid arthritis is an autoimmune disease attacking the joints, and multiple sclerosis attacks the nervous system. Despite these divergent origins, patients frequently report overlapping symptoms such as profound fatigue, brain fog, poor concentration, sleep disturbances, and autonomic dysfunction.
According to Dr Ewan Hunter, Chief Data Officer at Oxford BioDynamics, the Orion platform predicts where regulatory contact points occur within folded DNA. The analysis highlighted several hub genes positioned at active nodes within these shared networks. For ME/CFS specifically, the data pointed to the LAG3 gene, which has been linked to T-cell exhaustion—a phenomenon where immune cells become less effective after remaining activated for an extended period. This mechanism suggests why patients can remain chronically ill long after an initial viral infection, stressor, or other trigger is no longer present.
DNA Folding Reveals Common Biological Control Networks
- Beyond Linear DNA: Scientists mapped how DNA folds in three dimensions, revealing that conditions with different triggers share common biological control networks.
- Systems Failure: Chronic fatigue is identified not merely as a symptom, but as the visible consequence of persistent dysregulation in immune function, metabolism, and stress-response pathways.
- Diagnostic Potential: The discovery could eventually support the development of objective blood tests, moving clinical practice away from a reliance solely on patient-reported symptoms.
| Condition | Primary Trigger | Primary Target System |
|---|---|---|
| ME/CFS | Viral Infection | Immune & Mitochondrial Networks |
| Long Covid | SARS-CoV-2 Infection | Immune & Metabolic Pathways |
| PTSD | Psychological Trauma | Stress-Hormone & Inflammatory Pathways |
| Rheumatoid Arthritis | Autoimmune Activity | Joint Tissue & Immune Signaling |
| Multiple Sclerosis | Autoimmune Activity | Nervous System & Cellular Resilience |
Computational Study Does Not Change Current Treatment Protocols
Because the recent study is computational and relies on genomic modeling rather than immediate clinical trials or diagnostic deployments, it does not change current treatment protocols or offer an immediate therapeutic intervention. Diagnostic tools utilizing the EpiSwitch platform remain investigational and require further clinical validation before routine implementation in healthcare systems.
The research consortium involved the University of East Anglia, Oxford BioDynamics, the London School of Hygiene and Tropical Medicine, and Cornwall Partnership NHS Foundation Trust. Future investigations must validate these shared biological signatures in larger, prospective patient cohorts to translate computational network maps into reliable clinical blood tests and multi-condition therapeutics.
References
- University of East Anglia & Oxford BioDynamics. EpiSwitch and Orion Platform-powered 3D Genome Architecture Biomarkers Reveal Shared Biology Across ME/CFS, Long COVID, PTSD, Rheumatoid Arthritis, and Multiple Sclerosis. Journal of Translational Medicine.
