Ferroptosis-Related Molecular Clusters and Diagnostic Model in Rheumatoid Arthritis

Abstract

Rheumatoid arthritis (RA) is a systemic autoimmune disease characterized by synovitis, joint damage and deformity. A newly described type of cell death, ferroptosis, has an important role in the pathogenesis of RA. However, the heterogeneity of ferroptosis and its association with the immune microenvironment in RA remain unknown. Synovial tissue samples from 154 RA patients and 32 healthy controls (HCs) were obtained from the Gene Expression Omnibus database. Twelve of twenty-six ferroptosis-related genes (FRGs) were differentially expressed between RA patients and HCs. Furthermore, the patterns of correlation among the FRGs were significantly different between the RA and HC groups. RA patients were classified into two distinct ferroptosis-related clusters, of which cluster 1 had a higher abundance of activated immune cells and a corresponding lower ferroptosis score. Enrichment analysis suggested that tumor necrosis factor-α signaling via nuclear factor-κB was upregulated in cluster 1. RA patients in cluster 1 responded better to anti-tumor necrosis factor (anti-TNF) therapy, which was verified by the GSE 198520 dataset. A diagnostic model to identify RA subtypes and immunity was constructed and verified, in which the area under the curve values in the training (70%) and validation (30%) cohorts were 0.849 and 0.810, respectively. This study demonstrated that there were two ferroptosis clusters in RA synovium that exhibited distinct immune profiles and ferroptosis sensitivity. Additionally, a gene scoring system was constructed to classify individual RA patients.

Machine learning and bioinformatics analysis to identify autophagy-related biomarkers in peripheral blood for rheumatoid arthritis

“…In contrast to other bioinformatics studies examining the role of programmed death genes in RA ( Xie et al, 2023 ; Zhou et al, 2023 ), this study focused on the diagnostic value of autophagy-related genes in RA. In addition, compared to the previous study ( Fan et al, 2023 ), this research utilized three machine learning algorithms to screen diagnostic biomarkers for the construction of the diagnostic model that showed excellent diagnostic efficacy in multiple cohorts containing samples from different tissues and diseases.…”

“…The production of IL-17 and IFN-γ from CD4 T cells in peripheral blood may directly contribute to the pathogenesis of RA (Park et al, 2014), while TNFSF10 may selectively activate CD4 T cells to promote IFN-γ production (Tsai et al, 2004), indicating that TNFSF10 may be a potential therapeutic target for RA. In contrast to other bioinformatics studies examining the role of programmed death genes in RA (Xie et al, 2023;Zhou et al, 2023), this study focused on the diagnostic value of autophagyrelated genes in RA. In addition, compared to the previous study (Fan et al, 2023), this research utilized three machine learning algorithms to screen diagnostic biomarkers for the construction of the diagnostic model that showed excellent diagnostic efficacy in multiple cohorts containing samples from different tissues and diseases.…”

Iron metabolism and arthritis: Exploring connections and therapeutic avenues

“…A separate study demonstrated the presence of two ferroptosis clusters in the RA synovium that exhibit distinct immune profiles and ferroptosis sensitivity. [ 30 ] The development of appropriate clinical treatment plans for different groups of ferroptotic cells is beneficial for treating RA.…”