Anyone who has lived with, or cared for someone with, a chronic illness knows that fatigue is not ordinary tiredness. It is a heavy, disabling exhaustion that sleep does not fix. What has puzzled doctors for years is that this same exhaustion turns up in illnesses that seem to have nothing in common: a viral aftermath, a psychological trauma, an autoimmune attack on the joints, an autoimmune attack on the nervous system.

A new study from the University of East Anglia (UEA) and the biotech company Oxford BioDynamics suggests there may be a biological reason for that overlap. The researchers describe their findings as something approaching a biological unifying theory of fatigue.

Five conditions, very different triggers

The team looked at five conditions that are usually studied separately:

  • ME/CFS (myalgic encephalomyelitis / chronic fatigue syndrome), which often follows a viral infection
  • Long COVID, which develops after SARS-CoV-2 infection
  • PTSD, which emerges after traumatic experiences
  • Rheumatoid arthritis, an autoimmune disease that attacks the joints
  • Multiple sclerosis (MS), an autoimmune disease that attacks the nervous system

Despite the different origins, patients tend to describe a strikingly similar cluster of symptoms: overwhelming fatigue, brain fog, poor concentration, disturbed sleep, autonomic problems and a sharp drop in everyday functioning.

Looking at how DNA folds, not just what it spells

Instead of reading DNA only as a linear sequence of letters, the researchers used Oxford BioDynamics’ EpiSwitch Orion platform to study the genome’s three-dimensional organization. Inside a cell, DNA is folded, so regions that sit far apart along the strand can physically touch, and those contact points help control which genes are switched on. Orion predicts where such contacts are likely to occur.

The work was entirely computational. The team combined previously published genome-wide association data for long COVID, PTSD, rheumatoid arthritis and MS with 3D genome data from an earlier ME/CFS study, so no new patient samples were collected.

Little overlap in genes, a lot of overlap in networks

The surprise was that, gene by gene, the five conditions barely overlapped. The connection only appeared when the researchers looked at how the implicated genes interact within larger regulatory networks. At that level, the diseases looked much more alike. The shared networks fed into:

  • immune and inflammatory signaling
  • mitochondrial energy production
  • metabolic regulation
  • stress-response mechanisms
  • neuroendocrine signaling

The idea is that the starting point differs, while the downstream damage converges. A viral infection might leave the immune system activated for too long, while traumatic stress might disturb stress-hormone pathways and inflammation. Both could end up straining the same circuits that govern energy production, immune regulation and cellular resilience. If those systems stay dysregulated, the result could be the disabling fatigue seen across all five illnesses.

Hub genes and an exhausted-immune-cell clue

The analysis also flagged several “hub genes” sitting at especially busy points in the shared networks, linked to immune regulation, inflammation and mitochondrial energy production. The authors stress that these are candidates only, and that their exact roles still need to be established.

In the ME/CFS portion of the work, one gene stood out: LAG3, which has been linked to T-cell exhaustion, a state in which immune cells become less effective after being kept activated for a long time. If confirmed, this might help explain why some people stay ill long after the original infection or stressor has passed.

Why it matters: diagnosis and treatment

ME/CFS and long COVID are currently diagnosed mostly from symptoms, with no universally accepted lab test, which leaves many patients waiting years for answers. An earlier EpiSwitch-based blood test for ME/CFS showed promising accuracy but still needs further validation. The new results raise the possibility of shared biological signatures that could be detected across several conditions, and of treatments that might one day be relevant to more than one of them.

Caveats worth keeping in mind

  • It is a computational prediction. The study reanalyzed existing data and predicted where genome contacts occur. It did not measure new patients, so the findings need experimental confirmation.
  • Shared pathways are not shared causes. Converging on similar networks does not mean these five diseases are the same disease, and it does not show what triggers fatigue in any individual patient.
  • Industry involvement. The platform used was developed by Oxford BioDynamics, a collaborator on the study, and its Chief Data Officer is among the authors. That does not invalidate the results, but it makes independent replication especially valuable.
  • No clinical test yet. The blood-test idea is a hope for the future, not something available to patients today.

Even so, the central message is encouraging: chronic exhaustion may be less a mystery of five separate diseases than a visible sign of a deeper, shared disturbance in how the body handles immunity, energy and stress. The next step is for other labs to test whether the same networks show up in real patients.

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