Huang, Katherine, G C de Sá, Alex, Thomas, Natalie et al. · Communications medicine · 2024 · DOI
Researchers studied blood samples from nearly 1,200 people with ME/CFS and compared them to people with other common conditions like depression, asthma, and thyroid problems. They found nine specific markers in the blood that, combined with basic health information, could identify ME/CFS patients about 70% of the time. This blood test approach could eventually help doctors diagnose ME/CFS more easily, since there is currently no definitive test for the condition.
ME/CFS currently lacks objective diagnostic markers, making it frequently misdiagnosed or underdiagnosed. This study demonstrates that measurable blood abnormalities could support clinical diagnosis and provides a methodological framework applicable to other difficult-to-diagnose conditions. Validating such biomarker-based approaches could significantly improve diagnostic accuracy and patient access to appropriate care.
This study does not prove that these blood markers cause ME/CFS or explain the underlying disease mechanisms. The 70% recall rate means 30% of ME/CFS cases would be missed, so this test cannot yet replace clinical diagnosis. As a cross-sectional study, it cannot establish whether metabolic changes precede symptom onset or result from the disease.
About the PEM badge: “PEM required” means post-exertional malaise was an explicit required diagnostic criterion for participant inclusion in this study — not that PEM was studied, observed, or discussed. Studies using criteria that do not require PEM (e.g. Fukuda, Oxford) are tagged “PEM not required”. How the atlas works →
The first block is for the primary paper and is the citation you should use in research work. The atlas-snapshot line only applies if you are specifically referring to this atlas’s reading of the paper on the date shown.
Primary citation
Huang, Katherine, G C de Sá, Alex, Thomas, Natalie, Phair, Robert D, Gooley, Paul R, Ascher, David B, et al. (2024). Discriminating Myalgic Encephalomyelitis/Chronic Fatigue Syndrome and comorbid conditions using metabolomics in UK Biobank.. Communications medicine. https://doi.org/10.1038/s43856-024-00669-7
BibTeX
@article{mecfsatlas-huang-2024-discriminating-myalgic,
author = {Huang, Katherine and G C de Sá, Alex and Thomas, Natalie and Phair, Robert D and Gooley, Paul R and Ascher, David B and Armstrong, Christopher W},
title = {Discriminating Myalgic Encephalomyelitis/Chronic Fatigue Syndrome and comorbid conditions using metabolomics in UK Biobank.},
journal = {Communications medicine},
year = {2024},
doi = {10.1038/s43856-024-00669-7},
note = {PubMed: 39592839},
url = {https://www.mecfsatlas.com/evidence/huang-2024-discriminating-myalgic},
}Atlas snapshot reference
ME/CFS Atlas. Generator v1 / Scanner v1.4 / policy v0.1. Accessed 2026-05-28. https://www.mecfsatlas.com/evidence/huang-2024-discriminating-myalgic
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