Bhattacharjee, Madhuchhanda, Rajeevan, Mangalathu S, Sillanpää, Mikko J · Human genomics · 2015 · DOI
Researchers used advanced statistical methods to analyze genetic information from ME/CFS patients to see if they could predict who has the disease. They tested a new approach that looks at many genetic variations together across different biological pathways, rather than just a few strong genetic markers. The method achieved 80% accuracy in predicting ME/CFS status, suggesting that genetic testing combined with clinical examination might someday help doctors diagnose ME/CFS earlier.
ME/CFS currently lacks laboratory biomarkers for objective diagnosis, making early identification difficult. This study demonstrates that integrating multiple genetic variants across relevant biological pathways could improve diagnostic accuracy when combined with clinical assessment, potentially enabling earlier diagnosis and intervention.
This study does not establish causation between the identified genetic variants and ME/CFS—it only identifies associations in the studied population. The 80% accuracy was achieved within the same dataset used for model training and cross-validation; external validation in independent populations is needed before clinical application. The study does not prove that genetic testing alone can diagnose ME/CFS without clinical assessment.
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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Primary citation
Bhattacharjee, Madhuchhanda, Rajeevan, Mangalathu S, & Sillanpää, Mikko J (2015). Prediction of complex human diseases from pathway-focused candidate markers by joint estimation of marker effects: case of chronic fatigue syndrome.. Human genomics. https://doi.org/10.1186/s40246-015-0030-6
BibTeX
@article{mecfsatlas-bhattacharjee-2015-prediction-complex,
author = {Bhattacharjee, Madhuchhanda and Rajeevan, Mangalathu S and Sillanpää, Mikko J},
title = {Prediction of complex human diseases from pathway-focused candidate markers by joint estimation of marker effects: case of chronic fatigue syndrome.},
journal = {Human genomics},
year = {2015},
doi = {10.1186/s40246-015-0030-6},
note = {PubMed: 26063326},
url = {https://www.mecfsatlas.com/evidence/bhattacharjee-2015-prediction-complex},
}Atlas snapshot reference
ME/CFS Atlas. Generator v1 / Scanner v1.4 / policy v0.1. Accessed 2026-05-25. https://www.mecfsatlas.com/evidence/bhattacharjee-2015-prediction-complex
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