Bhattacharjee, M, Botting, C H, Sillanpää, M J · Genomics · 2008 · DOI
This study developed statistical methods to find biological markers (biomarkers) that could help identify and diagnose ME/CFS. The researchers used blood protein measurements and genetic information from ME/CFS patients to find which markers are most closely linked to the disease. Finding these biomarkers is important because ME/CFS is currently hard to diagnose and measure, and having reliable biological tests could change that.
ME/CFS lacks objective diagnostic biomarkers, making diagnosis challenging and delayed for many patients. Developing computational methods to systematically identify protein and genetic markers associated with ME/CFS could lead to diagnostic tests and better understanding of disease mechanisms. This study demonstrates a replicable statistical approach that could accelerate biomarker discovery in this understudied disease.
This methods paper does not establish which specific biomarkers are definitively associated with ME/CFS, as the abstract does not report the identified markers or their validation in independent cohorts. The study does not prove causation—identified biomarkers may be consequences of disease rather than contributing factors. Results require external validation and clinical utility assessment before application to patient diagnosis.
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
Bhattacharjee, M, Botting, C H, & Sillanpää, M J (2008). Bayesian biomarker identification based on marker-expression proteomics data.. Genomics. https://doi.org/10.1016/j.ygeno.2008.06.006
BibTeX
@article{mecfsatlas-bhattacharjee-2008-bayesian-biomarker,
author = {Bhattacharjee, M and Botting, C H and Sillanpää, M J},
title = {Bayesian biomarker identification based on marker-expression proteomics data.},
journal = {Genomics},
year = {2008},
doi = {10.1016/j.ygeno.2008.06.006},
note = {PubMed: 18657605},
url = {https://www.mecfsatlas.com/evidence/bhattacharjee-2008-bayesian-biomarker},
}Atlas snapshot reference
ME/CFS Atlas. Generator v1 / Scanner v1.4 / policy v0.1. Accessed 2026-05-30. https://www.mecfsatlas.com/evidence/bhattacharjee-2008-bayesian-biomarker
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