Mitochondrial Oxidative Stress Related Diagnostic Model Accurately Assesses Rheumatoid Arthritis Risk Stratification and Immune Infiltration Characterization

Abstract

Rheumatoid arthritis (RA) is a chronic autoimmune disease that affects synovial joints, leading to joint destruction, impaired physical function, and reduced quality of life. However, no accurate method for assessing RA risk currently exists. Given the critical role of early detection and intervention in RA management, further comprehensive risk assessments are essential. Mitochondrial oxidative stress (MOS) is a key factor in the initiation and progression of RA. The bidirectional interaction between RA and MOS supports the feasibility of MOS-based risk stratification for RA. Using public databases, we first applied the weighted gene co-expression network analysis (WGCNA) model to identify key genes involved in RA among MOS-related genes. Differential expression patterns of MOS-related genes were then analyzed using various machine learning algorithms to identify potential biomarkers. A nomogram model was established using CDKN1A, GADD45B, and MAFF genes to predict RA risk, followed by an evaluation of its reliability and stability. Additionally, we analyzed MOS-associated molecular subtypes and immune infiltration characteristics. Our findings highlight the significant role of MOS in RA development and underscore the clinical value of personalized treatment strategies.