Long COVID, ME/CFS, PTSD, rheumatoid arthritis, and multiple sclerosis may seem to have little in common. Yet people living with these very different conditions often describe something strikingly similar: an exhaustion that goes far beyond simply feeling tired.
It can mean waking up unrefreshed, struggling to think clearly, and finding that activities that were once routine suddenly take an enormous toll. In ME/CFS, this can include post-exertional malaise, where symptoms worsen after even relatively minor physical or mental activity. Similar problems with fatigue, sleep, cognition, and everyday functioning can appear across the other conditions as well.
Why such different illnesses can produce overlapping symptoms has been difficult to explain. Long COVID can follow a viral infection, PTSD develops after trauma, while rheumatoid arthritis and multiple sclerosis involve immune dysfunction. On the surface, there is no obvious reason their effects should converge.
But a 2026 study published in the Journal of Translational Medicine suggests there may be biological connections beneath those differences. Researchers from the University of East Anglia and collaborating institutions identified patterns shared across all five conditions, not by looking for a single gene responsible for fatigue, but by examining how genes interact within larger biological networks.
What the study actually did
Rather than conventionally analyzing DNA sequences, researchers used Oxford BioDynamics’ EpiSwitch® Orion platform, which examines the three-dimensional architecture of the genome – studying how DNA folds and interacts inside living cells. The analysis was computational. Published genomic data for long COVID, PTSD, rheumatoid arthritis, and multiple sclerosis, drawn from existing genome-wide association studies, were combined with 3D genomic data from an earlier ME/CFS patient study, without collecting new patient samples.
A genome-wide association study identifies genomic variants statistically associated with disease risk – a population-level scan comparing the genomes of people with and without a given condition. Standard analysis reads DNA as a flat, linear sequence. The EpiSwitch® Orion platform goes further. “DNA is folded in our cells, so regions far apart in the linear sequence can touch, and those contact points are where genes get controlled,” said Dr. Ewan Hunter, Chief Data Officer at Oxford BioDynamics. Applied to the five conditions, Orion found that genetic changes appearing to have little in common connected into the same regulatory circuitry.
Three-dimensional chromatin architecture exerts fundamental roles in gene regulation, facilitating cell-specific factor binding – a layer of genomic control that conventional linear sequencing cannot capture. Their connections exist not in the gene sequence itself but in how those genes fold, touch, and regulate one another inside the cell nucleus.
The five conditions in the analysis
ME/CFS is defined by profound fatigue, postexertional malaise (PEM – a worsening of symptoms after even minor physical or mental activity), unrefreshing sleep, and cognitive dysfunction. According to the CDC, there is no known cure, and care typically focuses on treating the symptoms that most affect a person’s life.
Long COVID, formally known as post-acute sequelae of SARS-CoV-2 infection, shares much of ME/CFS’s clinical profile – post-infectious onset, brain fog, fatigue, muscle pain, and dysautonomia with orthostatic intolerance. Both ME/CFS and long COVID are diagnosed largely through symptoms, with no universally accepted laboratory test available.
Rheumatoid arthritis is a chronic systemic autoimmune disease primarily involving the joints, with damage mediated by cytokines and chemokines – signaling proteins that coordinate immune responses. Multiple sclerosis is a chronic autoimmune disorder affecting the central nervous system, where the immune system targets myelin, the protective sheath surrounding nerve fibers.
PTSD involves significant imbalances in pro-inflammatory and anti-inflammatory cytokines across multiple biological systems. HPA axis dysfunction – a disruption to the hormonal stress-response system – is characterized by glucocorticoid resistance, which weakens negative feedback regulation of inflammation, effectively locking the body into a state of chronic immune activity.
What the analysis found – and what the chronic fatigue syndrome biology reveals
Analysis of the ME/CFS dataset alone identified 552 unique 3D genomic anchors mapped to 567 genes. Direct overlap between disease-associated genes was limited across all five conditions. Higher-order network analyses, however, revealed substantial interconnectivity – a finding that only emerged when researchers examined how genes interact rather than at the genes themselves.
As Prof. Pshezhetskiy put it: “At an individual gene level, there was surprisingly little direct overlap between long COVID, ME/CFS, PTSD, multiple sclerosis, and rheumatoid arthritis. But when we analyzed how those genes interact in complex biological networks, the diseases appeared deeply connected.”
Shared circuitry spans immune and inflammatory signaling, mitochondrial energy production, metabolic regulation, stress-response mechanisms, and neuroendocrine signaling. The most notable convergence point is the RUNX1-PPARGC1A-STAT1 axis, a regulatory hub sitting at the intersection of immune function and cellular metabolism.
The chronic fatigue syndrome biology behind the shared hubs
Mitochondrial dysfunction and energy failure
Mitochondria produce ATP – the molecule cells use as fuel. ME/CFS research has documented reduced ATP production rates and impaired oxidative phosphorylation, and the 2026 study found overlapping pathway disruptions across all five conditions, including immune and cytokine signaling, interferon responses, mitochondrial function, and metabolism. When mitochondria cannot produce energy efficiently, muscles, cognition, immune regulation, and hormonal balance all bear the cost.
Immune cell exhaustion
Immune cell exhaustion is a state in which immune cells – particularly T cells – have been chronically activated for so long that they lose normal function. A 2026 study published in Nature Immunology found that long COVID patients showed persistent immune activation and T cell exhaustion for more than 180 days after initial infection, lending independent support to the UEA team’s network-level findings.
The gene LAG3 sits at the center of this mechanism. LAG3 is highly upregulated on exhausted T cells and transmits inhibitory signals, switching off immune responses that have been running too long. LAG3 appears as a strongly connected node within the ME/CFS network, with close functional relationships to established ME/CFS genes through modulation of immune responses following chronic immune activation. Highly connected hub genes also included components of the mTOR signaling pathway, implicating immunometabolic dysregulation as a mechanism common to all five disorders.
Neuroendocrine and stress-response pathways
The hypothalamic-pituitary-adrenal (HPA) axis controls the body’s response to stress and infection. In PTSD, HPA axis dysfunction weakens the negative feedback that would normally bring inflammation under control. The 2026 network analysis found neuroendocrine signaling pathways appearing across the regulatory circuitry shared by all five conditions, suggesting that disruptions to hormonal stress-response systems may be as central to fatigue biology as immune dysfunction itself.
A COVID infection may trigger prolonged immune activation. Traumatic stress may disrupt stress-hormone pathways and inflammatory responses. Both disturbances appear capable of converging on common biological circuits controlling energy production, immune regulation, and cellular resilience.
The limitations: what this study cannot yet prove
The computational methods used in the study are proprietary, locked within the EpiSwitch® platform, which means outside researchers cannot independently reproduce the analysis. Reproducibility is the bedrock of scientific validation, and a platform whose internal logic is inaccessible to outside scrutiny cannot, at this stage, be fully evaluated. The claim of “something approaching a biological unifying theory of fatigue,” made by the lead researcher, has been described by independent scientists as an overstatement. The study also draws on GWAS datasets that inherently capture only select populations and cover a limited fraction of the functional genome, with large regulatory regions in non-coding DNA remaining outside the analysis.
The researchers themselves acknowledge that further experimental and clinical validation is required before any of the identified hub genes and pathways can be confirmed as causal drivers of disease. The ME Association characterized the finding as suggesting these illnesses may involve disturbances in interconnected biological systems rather than completely separate mechanisms – a framing that appropriately reflects the study’s early-stage, computational nature.
Diagnostic and therapeutic implications
Limited gene-level overlap between the five conditions but substantial network-level interconnectivity opens a path toward cross-disease diagnostic and therapeutic strategies. Both ME/CFS and long COVID are diagnosed through symptoms alone, with no universally accepted laboratory test available. If validated through independent replication with new patient samples, the researchers’ findings could support the development of objective blood-based biomarker tests that measure biological signatures rather than relying solely on patient-reported symptoms.
Identifying shared network hubs such as LAG3 and the mTOR pathway raises the possibility that drugs already in development for one condition could be repurposed. Cancer immunotherapy has produced several LAG3-targeting agents, and the systems-level map generated by this study gives researchers a concrete set of targets to investigate in future trials. Confirmation through experimental work will be required before any of this translates to clinical use.
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What this means for patients and doctors
The September 2026 study published in the Journal of Translational Medicine is one of the most comprehensive attempts yet to identify a shared biological basis for the exhaustion that defines five distinct diseases. Its core finding – that the chronic fatigue syndrome biology driving ME/CFS appears to share regulatory networks with long COVID, PTSD, rheumatoid arthritis, and multiple sclerosis – shifts the framing from coincidence to mechanism. The connections are not in the letters of the genetic code but in the three-dimensional structure that determines which genes communicate with which, and when.
Proprietary tools, no new patient samples, and the acknowledged need for experimental validation all mean these are promising early findings – not a settled scientific conclusion. Computational network biology reveals associations, not causes. Independent scientists have described the lead researcher’s claim of a “biological unifying theory of fatigue” as premature. LAG3 activity, mTOR signaling, mitochondrial ATP production, and HPA axis regulation are the specific biological domains now linked to all five conditions – concrete areas to follow in the research pipeline and, in consultation with a physician, concrete questions to raise when existing symptom-based diagnoses feel insufficient.
Disclaimer: This information is not intended to be a substitute for professional medical advice, diagnosis, or treatment and is for information only. Always seek the advice of your physician or another qualified health provider with any questions about your medical condition and/or current medication. Do not disregard professional medical advice or delay seeking advice or treatment because of something you have read here.
AI Disclaimer: This article was created with the assistance of AI tools and reviewed by a human editor.
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