Exploring the Joint Potential of Inflammation, Immunity, and Receptor-Based Biomarkers for Evaluating ME/CFS Progression

Background: Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a debilitating chronic condition with no identified diagnostic biomarkers to date. Its prevalence is as high as 0.89% according to metastudies, with a quarter of patients bed- or home-bound, which presents a serious public health challenge. Investigations into the inflammation-immunity axis is encouraged by links to outbreaks and disease waves. Recently, research of our group revealed that antibodies to beta2-adrenergic (anti-β2AdR) and muscarinic acetylcholine (anti-M4) receptors demonstrate sensitivity to the progression of ME/CFS. The purpose of this study is to investigate the joint potential of inflammatome - characterized by interferon (IFN)-γ, tumor necrosis factor (TNF)-α, interleukin (IL)-2, IL-21, Il-23, IL-6, IL-17A, Activin-B, immunome (IgG1, IgG2, IgG3, IgG4, IgM, IgA) and receptor-based biomarkers (anti-M3, anti-M4, anti-β2AdR) determined -, for evaluating ME/CFS progression, and to identify an optimal selection for future validation in prospective clinical studies.
Methods: A dataset was used originating from 188 persons, including 54 healthy controls, 30 patients classified as "mild" by severity, 73 as "moderate," and 31 as "severe," clinically assessed by Fukuda/CDC 1994 and International consensus criteria. Markers characterizing inflammatome, immunome, and receptor-based biomarkers were determined in blood plasma via ELISA and multiplex methods. Statistical analysis was done via correlation analysis, principal component, and linear discriminant analysis, and random forest classification; inter-group differences tested via nonparametric Kruskal–Wallis H test followed by the two-stage linear step-up procedure of Benjamini, Krieger, and Yekutieli, and via Mann-Whitney U test.
Results: The association between inflammatome and immunome markers is broader and stronger (coupling) in severe group. Principal component factoring separate components affiliated with inflammatome, immunome, and receptor biomarkers. Random forest modeling demonstrates an out-of-box accuracy for splitting healthy/with condition groups of over 90%, and of 45% for healthy/severity groups. Classifiers with the highest potential are anti-β2AdR, anti-M4, IgG4, IL-2, and IL-6.
Discussion: Association between inflammatome and immunome markers is a candidate for controlled clinical study of ME/CFS progression markers that could be used for treatment individualization. Thus, coupling effects between inflammation and immunity have a potential for the identification of prognostic factors in the context of ME/CFS progression mechanism studies.