4.6 Article

Diagnosis of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome With Partial Least Squares Discriminant Analysis: Relevance of Blood Extracellular Vesicles

Journal

FRONTIERS IN MEDICINE
Volume 9, Issue -, Pages -

Publisher

FRONTIERS MEDIA SA
DOI: 10.3389/fmed.2022.842991

Keywords

myalgic encephalomyelitis; chronic fatigue syndrome (ME; CFS); extracellular vesicles (EVs); partial least squares-differential analysis (PLS-DA); Raman spectroscopy; microRNAs; carotenoids; biomarker

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Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is diagnosed clinically and is characterized by persistent fatigue and post-exertional malaise. Differential expression of miRNAs in the blood has been observed in patients, but their diagnostic power is limited. Blood vesicles may carry relevant disease information. Raman micro-spectroscopic analysis identified carotenoid peaks as ME/CFS fingerprints, but their diagnostic capacity is limited. However, Raman data helped refine the number of miRNAs in a previous model, ensuring a perfect classification of subjects.
Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS), a chronic disease characterized by long-lasting persistent debilitating widespread fatigue and post-exertional malaise, remains diagnosed by clinical criteria. Our group and others have identified differentially expressed miRNA profiles in the blood of patients. However, their diagnostic power individually or in combinations seems limited. A Partial Least Squares-Discriminant Analysis (PLS-DA) model initially based on 817 variables: two demographic, 34 blood analytic, 136 PBMC miRNAs, 639 Extracellular Vesicle (EV) miRNAs, and six EV features, selected an optimal number of five components, and a subset of 32 regressors showing statistically significant discriminant power. The presence of four EV-features (size and z-values of EVs prepared with or without proteinase K treatment) among the 32 regressors, suggested that blood vesicles carry relevant disease information. To further explore the features of ME/CFS EVs, we subjected them to Raman micro-spectroscopic analysis, identifying carotenoid peaks as ME/CFS fingerprints, possibly due to erythrocyte deficiencies. Although PLS-DA analysis showed limited capacity of Raman fingerprints for diagnosis (AUC = 0.7067), Raman data served to refine the number of PBMC miRNAs from our previous model still ensuring a perfect classification of subjects (AUC=1). Further investigations to evaluate model performance in extended cohorts of patients, to identify the precise ME/CFS EV components detected by Raman and to reveal their functional significance in the disease are warranted.

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