Chandelier
Senior Member (Voting Rights)
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
Although these conditions differ in diagnosis and clinical presentation, their underlying biological mechanisms remain poorly understood and may involve convergent regulatory pathways.
Three-dimensional genomic anchors were mapped to coding genes and analysed using STRING protein–protein interaction networks and Cytoscape-based systems biology approaches.
Disease-specific anchor datasets were generated and compared at both gene and network levels to identify shared biological processes and regulatory mechanisms.
Direct overlap between disease-associated genes was limited; however, higher-order network analyses revealed substantial interconnectivity and convergence across conditions.
Shared biological pathways included immune and cytokine signalling, interferon responses, mitochondrial function, metabolic regulation, and neuroendocrine processes.
Highly connected hub genes included immune regulatory nodes such as LAG3 and components of the mTOR signalling pathway, implicating T-cell exhaustion, chronic immune activation, and immunometabolic dysregulation as common mechanisms underlying these disorders.
Despite limited genetic overlap, substantial convergence at the network level suggests shared biological architecture across ME/CFS, LC19, PTSD, RA, and MS.
The identification of common regulatory pathways provides a mechanistic framework for the development of cross-disease diagnostic and therapeutic strategies.
By capturing dynamic regulatory states, 3D genomic biomarkers offer significant potential for objective blood-based diagnostics, patient stratification, and the identification of shared therapeutic targets across complex chronic disorders.
These findings support the application of precision medicine approaches and may accelerate the development of novel interventions for fatigue-associated multisystem diseases.
None of the remaining authors has competing interests.
Web | DOI | Journal of Translational Medicine | Open Access
Hunter, Ewan; Alshaker, Heba; Vugrinec, Dominik; Bautista, Shekinah; Gebregzabhar, Abel; Virdi, Anya; Croxford, Joseph; Dring, Ann; Powell, Ryan; Salter, Matthew; Kingdon, Caroline; Green, Jayne; Akoulitchev, Alexandre; Pchejetski, Dmitri
Abstract
Background
Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS), Long COVID (LC19), post-traumatic stress disorder (PTSD), rheumatoid arthritis (RA), and multiple sclerosis (MS) are clinically distinct disorders that share substantial symptom overlap, including persistent fatigue, cognitive impairment, autonomic dysfunction, and immune dysregulation.Although these conditions differ in diagnosis and clinical presentation, their underlying biological mechanisms remain poorly understood and may involve convergent regulatory pathways.
Methods
The EpiSwitch® 3D genomics platform and Orion knowledgebase were used to integrate chromosome conformation signatures with genome-wide association study (GWAS)-derived datasets across ME/CFS, LC19, PTSD, RA, and MS.Three-dimensional genomic anchors were mapped to coding genes and analysed using STRING protein–protein interaction networks and Cytoscape-based systems biology approaches.
Disease-specific anchor datasets were generated and compared at both gene and network levels to identify shared biological processes and regulatory mechanisms.
Results
Analysis of the ME/CFS dataset identified 552 unique 3D genomic anchors mapped to 567 genes, with analogous disease-specific anchor sets generated for LC19, PTSD, RA, and MS.Direct overlap between disease-associated genes was limited; however, higher-order network analyses revealed substantial interconnectivity and convergence across conditions.
Shared biological pathways included immune and cytokine signalling, interferon responses, mitochondrial function, metabolic regulation, and neuroendocrine processes.
Highly connected hub genes included immune regulatory nodes such as LAG3 and components of the mTOR signalling pathway, implicating T-cell exhaustion, chronic immune activation, and immunometabolic dysregulation as common mechanisms underlying these disorders.
Conclusions
These findings support a systems-level model in which clinically overlapping fatigue-associated syndromes arise from perturbations of interconnected regulatory networks rather than discrete disease-specific pathways.Despite limited genetic overlap, substantial convergence at the network level suggests shared biological architecture across ME/CFS, LC19, PTSD, RA, and MS.
The identification of common regulatory pathways provides a mechanistic framework for the development of cross-disease diagnostic and therapeutic strategies.
By capturing dynamic regulatory states, 3D genomic biomarkers offer significant potential for objective blood-based diagnostics, patient stratification, and the identification of shared therapeutic targets across complex chronic disorders.
These findings support the application of precision medicine approaches and may accelerate the development of novel interventions for fatigue-associated multisystem diseases.
Funding
This work was funded by Oxford BioDynamics plc.Ethics declarations
Competing interest
EH, DV, SB, AG, AV, JC, AD, RP, MS, JG, and AA are full-time employees at Oxford BioDynamics plc and have no other competing financial or other interests.None of the remaining authors has competing interests.
Web | DOI | Journal of Translational Medicine | Open Access
