Biomarker Discovery and Diagnostics

1 BioMapAI (Gut Microbiome and Metabolomics)

  • Principal Investigator:: Derya Unutmaz (Jackson Laboratory); AI platform developed with Duke University

  • Institution:: Jackson Laboratory (JAX) and Duke University School of Medicine, United States

  • Contact/URL:: https://medschool.duke.edu/news/ai-thats-finally-making-sense-chronic-fatigue-syndrome

  • Funder:: NIH and institutional funding

  • Status:: Active (longitudinal follow-up ongoing)

  • Phase:: Observational, AI-integrated multi-omics

  • Cohort:: 153 ME/CFS patients + 96 healthy controls, followed longitudinally over 4 years

  • Mechanism/Focus:: AI platform integrating gut metagenomics, plasma metabolomics, immune cell profiles, standard blood tests, and clinical symptoms. Achieved 90% accuracy in distinguishing ME/CFS from controls. Identified gut microbiome signatures as strong predictors.

  • Primary Outcomes:: Multi-modal diagnostic classifier; longitudinal trajectory modelling; microbiome-metabolome interaction networks

  • Estimated Completion:: Ongoing longitudinal follow-up; initial results published 2025

  • Timeline:: Recruitment 2020–2023; initial AI classifier published July 2025; longitudinal analysis ongoing

  • Publication Medium:: Initial results in high-impact journal (2025); longitudinal follow-up expected 2026–2027

  • Document Relevance:: Ch. 11 (gut microbiome), Ch. 6 (energy metabolism), Ch. 13 (integrative models), Ch. 20 (biomarker research)

BioMapAI is notable for its longitudinal design and AI-first analytical approach. Unlike cross-sectional biomarker studies, the 4-year follow-up can capture disease trajectory and distinguish state markers (fluctuating with symptoms) from trait markers (stable features of the disease). The gut microbiome component strengthens the microbiome–immune–metabolism axis described in Chapter 11. The 90% classification accuracy, while promising, requires external validation in independent cohorts.

2 ME Association PhD Project (Metabolite and Infection Markers)

  • Principal Investigator:: Aleyna Lumsden (PhD candidate); supervised across multiple institutions

  • Institution:: Rosalind Franklin Institute, Imperial College London, and National Phenome Centre, United Kingdom

  • Contact/URL:: https://meassociation.org.uk/2025/11/research-new-funding-awarded-to-phd-project-that-will-identify-key-metabolites-and-infection-markers-in-me-cfs/

  • Funder:: ME Association Ramsay Research Fund and UKRI (joint)

  • Status:: Active (PhD project started 2025)

  • Phase:: Observational, metabolomics and infection biomarkers

  • Cohort:: To be determined (likely leveraging existing biobank samples)

  • Mechanism/Focus:: Advanced mass spectrometry and informatics to identify unknown metabolites and uncover evidence of infection in ME/CFS. Uses facilities across three major UK research centres.

  • Primary Outcomes:: Novel metabolite identification; infection marker discovery; candidate biomarkers for further validation

  • Estimated Completion:: 2028–2029 (typical PhD duration)

  • Timeline:: Funding awarded November 2025; project started 2025–2026

  • Publication Medium:: PhD thesis and associated journal publications

  • Document Relevance:: Ch. 6 (energy metabolism), Ch. 7 (immune dysfunction), Ch. 20 (biomarker research)

This PhD project complements the larger Rosetta Stone Study by focusing specifically on unknown metabolites—compounds not yet characterised in standard metabolomics panels. The infection marker component addresses the long-standing hypothesis that persistent or reactivated infections drive ME/CFS pathology (Chapter 7). Access to the Rosalind Franklin Institute’s advanced mass spectrometry facilities gives this project analytical capabilities beyond typical academic metabolomics studies.

3 MEA–UCL Blood Biomarker Pilot

  • Principal Investigator:: Sophie Hicks (PhD student); supervisors Dr. Amanda Heslegrave, Dr. Michael Zandi, Prof. Henrik Zetterberg

  • Institution:: UK DRI Fluid Biomarker Laboratory, UCL Institute of Neurology, London

  • Contact/URL:: ME Association announcement, February 2026

  • Registry ID:: Not yet registered (pilot/observational)

  • Funder:: ME Association (UK)

  • Status:: Active (12-month project, started February 2026)

  • Phase:: Observational pilot

  • Cohort:: Blood samples from ME/CFS patients (UK ME/CFS Biobank), Long Covid patients (UCLH STIMULATE-ICP study), and healthy volunteers

  • Mechanism/Focus:: Searches for blood-based biomarkers linking specific symptom clusters (brain fog, headaches, muscle pain) to measurable biological changes. Applies neuroimmunology expertise from the Zetterberg group (world-leading in fluid biomarkers for neurodegeneration, e.g., neurofilament light chain).

  • Primary Outcomes:: Candidate blood biomarkers correlated with symptom clusters

  • Estimated Completion:: \(\sim\)February 2027

  • Timeline:: 12-month pilot; may lead to larger validation study

  • Publication Medium:: Not yet announced

  • Document Relevance:: Ch. 7 (immune dysfunction), Ch. 22 (mechanistic studies)

The Zetterberg laboratory’s involvement is notable: their deep expertise in neurofilament light chain and related neurodegeneration biomarkers has not previously been applied to ME/CFS. Cross-disease biomarker candidates (shared between ME/CFS and neurodegenerative conditions) could emerge from this work, informing the diagnostic overlap discussion in Chapter Speculative Cross-Disease Connections.

4 Cornell Cell-Free RNA Liquid Biopsy

  • Principal Investigator:: Iwijn De Vlaminck (Biomedical Engineering) and Maureen Hanson (Molecular Biology and Genetics)

  • Institution:: Cornell University, Ithaca, NY

  • Contact/URL:: https://doi.org/10.1073/pnas.2507345122

  • Funder:: NIH / institutional

  • Status:: Published August 2025

  • Phase:: Biomarker discovery (cross-sectional)

  • Cohort:: 93 ME/CFS cases + 75 healthy sedentary controls

  • Mechanism/Focus:: Profiled circulating cell-free RNA (cfRNA) in plasma by RNA sequencing. Identified over 700 differentially expressed transcripts. Immune cfRNA deconvolution revealed elevated plasmacytoid dendritic cell, monocyte, and T cell-derived cfRNA in ME/CFS, with signatures of cytokine signalling and T cell exhaustion.

  • Primary Outcomes:: GLM-LASSO classifier AUC 0.81, accuracy 77%. Not yet diagnostic-grade but substantial advance over prior attempts

  • Estimated Completion:: Published

  • Publication Medium:: Proceedings of the National Academy of Sciences

  • Document Relevance:: Ch. 7 (immune dysfunction), Ch. 20 (biomarker research), Ch. 25 (translational findings)

Cell-free RNA offers a minimally invasive “liquid biopsy” approach that captures tissue-level biology without biopsies. The 77% classification accuracy is insufficient for a standalone diagnostic but demonstrates that cfRNA carries ME/CFS-relevant biological signal (Gardella et al. 2025). The T cell exhaustion and platelet activation signatures align with independent findings from single-cell transcriptomics (Section Immune Profiling and T Cell Research) and proteomics (Section Biomarker Discovery and Diagnostics). Prospective validation in a larger, multi-site cohort with disease controls (fibromyalgia, depression, long COVID) is needed to assess clinical utility.

5 Cell Reports Medicine Multi-Modal Study

  • Principal Investigator:: Multiple collaborating groups

  • Institution:: Multi-centre (USA)

  • Contact/URL:: https://doi.org/10.1016/j.xcrm.2025.102012

  • Funder:: NIH / institutional

  • Status:: Published 2025

  • Phase:: Observational, multi-modal

  • Cohort:: ME/CFS patients + healthy controls

  • Mechanism/Focus:: Integrated energy metabolism assessment, immune profiling, and plasma proteomics. Immune cells from ME/CFS patients showed elevated AMP and ADP with reduced ATP/ADP ratio. NK cell and dendritic cell subset abnormalities. Vascular dysfunction markers including soluble THBS1, VWF, and VASN.

  • Primary Outcomes:: Converging evidence across energy, immune, and vascular axes; reduced CD56lowCD16+ NK cells (antiviral), increased plasmacytoid DCs

  • Estimated Completion:: Published

  • Publication Medium:: Cell Reports Medicine

  • Document Relevance:: Ch. 6 (energy metabolism), Ch. 7 (immune dysfunction), Ch. 10 (cardiovascular), Ch. 13 (integrative models)

This study is noteworthy for its simultaneous assessment of three pathophysiological axes—energy, immune, and vascular—in the same cohort, enabling correlation analyses that single-axis studies cannot perform (2025). The reduced ATP/ADP ratio in immune cells provides a mechanistic link between energy metabolism (Ch. 6) and immune dysfunction (Ch. 7). The vascular findings (elevated thrombospondin-1, von Willebrand factor) converge with coagulation abnormalities reported in the microclot literature (Nunes et al. 2022).

References

2025. “Mapping the Complexity of ME/CFS: Evidence for Abnormal Energy Metabolism, Altered Immune Profile, and Vascular Dysfunction.” Cell Reports Medicine. https://doi.org/10.1016/j.xcrm.2025.102012.
Gardella, Anne, Iwijn De Vlaminck, Maureen R Hanson, et al. 2025. “Circulating Cell-Free RNA Signatures for the Characterization and Diagnosis of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome.” Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.2507345122.
Nunes, Jean M., Arneaux Kruger, Amy Proal, Douglas B. Kell, and Etheresia Pretorius. 2022. “The Occurrence of Hyperactivated Platelets and Fibrinaloid Microclots in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS).” Pharmaceuticals 15 (8): 931. https://doi.org/10.3390/ph15080931.