Evidence map›Paper›PMID 41057909›Full record

ArticleJournal of translational medicine2025

Development and validation of blood-based diagnostic biomarkers for Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) using EpiSwitch

Ewan Hunter, Heba Alshaker, Oliver Bundock, Cicely Weston, Shekinah Bautista, Abel Gebregzabhar, Anya Virdi, Joseph Croxford, Ann Dring, Ryan Powell and 7 more

Abstract readValidation Study
In one paragraph

Article in Journal of translational medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Observational
  4. Article
  5. Article
  6. Review
  7. Article
  8. Article
  9. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

17 authors.

Ewan HunterOxford BioDynamics Plc, Oxford, UK.
Heba AlshakerNorwich Medical School, University of East Anglia, Norwich, UK.
Oliver BundockOxford BioDynamics Plc, Oxford, UK.
Cicely WestonOxford BioDynamics Plc, Oxford, UK.
Shekinah BautistaOxford BioDynamics Plc, Oxford, UK.
Abel GebregzabharOxford BioDynamics Plc, Oxford, UK.
Anya VirdiOxford BioDynamics Plc, Oxford, UK.
Joseph CroxfordOxford BioDynamics Plc, Oxford, UK.
Ann DringOxford BioDynamics Plc, Oxford, UK.
Ryan PowellOxford BioDynamics Plc, Oxford, UK.
Dominik VugrinecOxford BioDynamics Plc, Oxford, UK.
Caroline KingdonThe London School of Hygiene & Tropical Medicine, London, UK.
Carol WilsonRoyal Cornwall Hospitals NHS Trust, Truro, UK.
Sarah DowrickRoyal Cornwall Hospitals NHS Trust, Truro, UK.
Jayne GreenOxford BioDynamics Plc, Oxford, UK.
Alexandre AkoulitchevOxford BioDynamics Plc, Oxford, UK.
Dmitri PchejetskiNorwich Medical School, University of East Anglia, Norwich, UK. d.pshezhetskiy@uea.ac.uk.ORCID 0000-0003-1074-9261

Funding

Oxford BioDynamics plc, Oxford UK 6514
6 · The paper itself

Abstract

Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a debilitating, multifactorial disorder characterised by profound fatigue, post-exertional malaise, cognitive impairments, and autonomic dysfunction. Despite its significant impact on quality of life, ME/CFS lacks definitive diagnostic biomarkers, complicating diagnosis and management. Recent evidence highlights potential blood tests for ME/CFS biomarkers in immunological, genetic, metabolic, and bioenergetic domains. Chromosome conformations (CCs) are potent epigenetic regulators of gene expression and cross-tissue exosome signalling. We have previously developed an epigenetic assay, EpiSwitch®, that employs an algorithm-based CCs analysis. Using EpiSwitch® technology, we have shown the presence of disease-specific CCs in peripheral blood mononuclear cells (PBMCs) of patients with amyotrophic lateral sclerosis (ALS), rheumatoid arthritis (RA), prostate and colorectal cancers, diffuse Large B-cell lymphoma and severe COVID-19. In a recent paper, we have identified a profile of systemic chromosome conformations in cancer patients reflective of the predisposition to respond to immune checkpoint inhibitors, PD-1/PD-L1 antagonists, with 85% accuracy. In this Retrospective case/control study (EPI-ME, Epigenetic Profiling Investigation in Myalgic Encephalomyelitis), we used whole blood samples retrospectively collected from n = 47 patients with severe ME/CFS and n = 61 age-matched healthy control patients to perform whole-genome 3D DNA screening for CCs correlating to ME/CFS diagnosis. We identified a 200-marker model for ME/CFS diagnosis (Episwitch®CFS test). First testing on the retrospective independent validation cohort demonstrated a strong systemic ME/CFS signal with a sensitivity of 92% and a specificity of 98%.Pathways analysis revealed several likely contributors to the pathology of ME/CFS, including interleukins, TNFα, neuroinflammatory pathways, toll-like receptor signalling and JAK/STAT. Comparison with pathways involved in the action of Rituximab and glatiramer acetate (Copaxone) (therapies with potential in ME/CFS treatment) identified IL2 as a shared pathway with clear patient clustering, indicating a possibility of a potential responder group for targeted treatment.

Indexed as

BiomarkersFatigue Syndrome, ChronicGene Expression ProfilingGenomicsFemaleHumansMaleMiddle AgedReproducibility of ResultsBiomarkers3D-genomic profilingAutonomic dysregulationBlood-based biomarkersBlood testChromosome conformationsChronic fatigue syndromeDiagnosisEpigeneticsME/CFSMyalgic encephalomyelitis

Identifiers

PMID41057909
PMCPMC12506310

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.