Recursive ensemble feature selection provides a robust mRNA expression signature for myalgic encephalomyelitis/chronic fatigue syndrome

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a chronic disorder characterized by disabling fatigue. Several studies have sought to identify diagnostic biomarkers, with varying results. Here, we innovate this process by combining both mRNA expression and DNA methylation data. We per...

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Veröffentlicht in:Scientific reports Jg. 11; H. 1; S. 4541 - 11
Hauptverfasser: Metselaar, Paula I., Mendoza-Maldonado, Lucero, Li Yim, Andrew Yung Fong, Abarkan, Ilias, Henneman, Peter, te Velde, Anje A., Schönhuth, Alexander, Bosch, Jos A., Kraneveld, Aletta D., Lopez-Rincon, Alejandro
Format: Journal Article
Sprache:Englisch
Veröffentlicht: London Nature Publishing Group UK 25.02.2021
Nature Publishing Group
Nature Portfolio
Schlagworte:
631/114/1305
692/308/2056
692/53/2421
Chronic fatigue syndrome
Deoxyribonucleic acid
DNA
DNA methylation
Encephalomyelitis
Fatigue
Gene expression
Humanities and Social Sciences
Immune system
Leukocytes (mononuclear)
multidisciplinary
Peripheral blood mononuclear cells
Science
Science (multidisciplinary)
ISSN:2045-2322, 2045-2322
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Zusammenfassung:Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a chronic disorder characterized by disabling fatigue. Several studies have sought to identify diagnostic biomarkers, with varying results. Here, we innovate this process by combining both mRNA expression and DNA methylation data. We performed recursive ensemble feature selection (REFS) on publicly available mRNA expression data in peripheral blood mononuclear cells (PBMCs) of 93 ME/CFS patients and 25 healthy controls, and found a signature of 23 genes capable of distinguishing cases and controls. REFS highly outperformed other methods, with an AUC of 0.92. We validated the results on a different platform (AUC of 0.95) and in DNA methylation data obtained from four public studies on ME/CFS (99 patients and 50 controls), identifying 48 gene-associated CpGs that predicted disease status as well (AUC of 0.97). Finally, ten of the 23 genes could be interpreted in the context of the derailed immune system of ME/CFS.
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ISSN:2045-2322
2045-2322
DOI:10.1038/s41598-021-83660-9