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

Frontiers in Medicine

article

Alba González-Cebrián¹  Eloy Almenar-Pérez²  Jiabao Xu⁴  Tong Yu⁴  Wei E. Huang⁴  Karen Giménez-Orenga⁵  Sarah Hutchinson³  Tiffany Lodge³  Lubov Nathanson⁶  Karl J. Morten³  Alberto Ferrer¹  Elisa Oltra² 

[1] Grupo de Ingeniería Estadística Multivariante, Departamento de Estadística e Investigación Operativa Aplicadas y Calidad, Universitat Politècnica de València;Department of Pathology, School of Health Sciences, Universidad Católica de Valencia San Vicente Mártir;Nuffield Department of Women's and Reproductive Health, The Women Centre, University of Oxford;Department of Engineering Science, University of Oxford;Escuela de Doctorado, Universidad Católica de Valencia San Vicente Mártir;Kiran C. Patel College of Osteopathic Medicine, Nova Southeastern University;Institute for Neuro Immune Medicine, Nova Southeastern University;Centro de Investigación Traslacional San Alberto Magno, Universidad Católica de Valencia San Vicente Mártir

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

DOI  :  10.3389/fmed.2022.842991

学科分类：社会科学、人文和艺术（综合）

来源: Frontiers

【 摘 要 】

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.

【 授权许可】

CC BY