• Medicine · Dec 2022

    Identification of ferroptosis-related gene signatures associated with multiple sclerosis using weighted gene co-expression network analysis.

    • Si-Chun Gu, Can-Xing Yuan, and Chao Gu.
    • Department of Neurology, Longhua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China.
    • Medicine (Baltimore). 2022 Dec 23; 101 (51): e31802e31802.

    AbstractMultiple sclerosis (MS) is a chronic inflammatory disease of central nervous system leading to demyelination followed by neurological symptoms. Ferroptosis is a newly discovered pathogenic hallmark important for the progression of MS. However, the gene markers of ferroptosis in MS are still uncertain. In this study, mRNA expression profiles and clinical data of MS samples were retrieved from Gene Expression Omnibus database. Weighted gene co-expression network analysis and receiver operating characteristic curve analysis were utilized to identify ferroptosis-related gene (FRG) signatures of MS. Gene set enrichment analysis and gene set variation analysis were performed to explore the biological functions of single FRG signature. HMOX1, LPCAT3 and RPL8 were firstly identified as FRG signatures of MS with the predictive capacity confirmed. Gene set enrichment analysis and gene set variation analyses revealed that metabolism-related, immune and inflammation-related, microglia-related, oxidation-related, and mitochondria-related biological functions were enriched, providing implications of the mechanisms underlying ferroptosis in MS. This study presented a systematic analysis of FRG in MS and explored the potential ferroptosis targets for new interventional strategies in MS.Copyright © 2022 the Author(s). Published by Wolters Kluwer Health, Inc.

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