Giloteaux, Ludovic, Li, Jiayin, Hornig, Mady et al. · Journal of translational medicine · 2023 · DOI
Researchers studied tiny particles called extracellular vesicles found in the blood of ME/CFS patients and compared them to healthy controls. They found that ME/CFS patients had more of these particles and they contained different levels of immune chemicals, particularly one called IL2. Using computer algorithms to analyze 20 different blood proteins, they could correctly identify ME/CFS patients about 86% of the time, suggesting that blood tests might one day help diagnose this condition.
This research provides objective biomolecular evidence supporting ME/CFS as a disease with measurable physiological abnormalities, moving beyond subjective symptom reporting. The identification of potential blood-based biomarkers could facilitate earlier diagnosis and enable stratification of ME/CFS subtypes, while the immune and hemostasis pathway findings suggest specific therapeutic targets worth investigating.
This study identifies associations between proteins and ME/CFS but does not prove these proteins cause the disease or are directly responsible for symptoms. Machine learning accuracy, while promising, does not establish clinical utility in routine diagnostics without further validation in independent cohorts. The correlations observed do not determine whether immune dysregulation is a primary cause or a secondary consequence of ME/CFS pathophysiology.
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 →
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