Exploring the Joint Potential of Inflammation, Immunity, and Receptor-Based Biomarkers for Evaluating ME/CFS Progression, 2023 Berkis et al

Discussion in 'ME/CFS research' started by Sly Saint, Nov 28, 2023.

  1. Sly Saint

    Sly Saint Senior Member (Voting Rights)

    Messages:
    9,626
    Location:
    UK
    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 beta2adrenergic (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 receptorbased 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.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 outof-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.

    https://www.frontiersin.org/articles/10.3389/fimmu.2023.1294758/abstract
     
    shak8, Sean, MeSci and 1 other person like this.
  2. Dolphin

    Dolphin Senior Member (Voting Rights)

    Messages:
    5,317
    The full text has now been published:
    https://www.frontiersin.org/articles/10.3389/fimmu.2023.1294758/full

    ORIGINAL RESEARCH article

    Front. Immunol., 20 December 2023

    Sec. Autoimmune and Autoinflammatory Disorders : Autoimmune Disorders

    Volume 14 - 2023 | https://doi.org/10.3389/fimmu.2023.1294758

    Exploring the joint potential of inflammation, immunity, and receptor-based biomarkers for evaluating ME/CFS progression

    [​IMG]Uldis Berkis1* [​IMG]Simons Svirskis2 [​IMG]Angelika Krumina3 [​IMG]Sabine Gravelsina2 [​IMG]Anda Vilmane2 [​IMG]Diana Araja2 [​IMG]Zaiga Nora-Krukle2 [​IMG]Modra Murovska2
    • 1Development and Project Department, Riga Stradins University, Riga, Latvia
    • 2Institute of Microbiology and Virology, Riga Stradins University, Riga, Latvia
    • 3Department of Infectology, Riga Stradins University, Riga, Latvia
    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, the 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, and IgA), and receptor-based biomarkers (anti-M3, anti-M4, and anti-β2AdR)—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 individuals, namely, 54 healthy controls, 30 patients with a “mild” condition, 73 patients with a “moderate” condition, and 31 patients with a “severe” condition, clinically assessed by Fukuda/CDC 1994 and international consensus criteria. 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 analysis, linear discriminant analysis, and random forest classification; inter-group differences were 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 the severe group. Principal component factoring separates components associated with inflammatome, immunome, and receptor biomarkers. Random forest modeling demonstrates an excellent accuracy of over 90% for splitting healthy/with condition groups, and 45% for splitting healthy/severity groups. Classifiers with the highest potential are anti-β2AdR, anti-M4, IgG4, IL-2, and IL-6.

    Discussion:

    The 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, the coupling effects between inflammation and immunity are potentially beneficial for the identification of prognostic factors in the context of ME/CFS progression mechanism studies.

     
    Amw66 and shak8 like this.

Share This Page