as a potential diagnostic biomarker for autophagy in rheumatoid arthritis: A bioinformatics study.

This study aimed to identify genes associated with autophagy and potential diagnostic biomarkers by comparing the gene expression profiles of synovial tissues in patients with rheumatoid arthritis (RA) and healthy individuals, aiming to offer new insights for clinical treatment strategies. We used publicly available datasets to analyze differentially expressed genes (DEGs) between the synovial tissue of RA patients and healthy individuals. Then, we intersected these DEGs with autophagy-related genes to identify autophagy genes in the synovial tissue of RA patients. We further analyzed the biological processes and functions of these genes. Furthermore, we used machine learning to identify characteristic autophagy genes in RA synovial tissue. Finally, we examined the differential expression of these characteristic genes in the blood of RA patients using an external dataset. Our study identified as a potential biomarker for diagnosing RA. gene expression was downregulated in both the synovial tissue and blood of RA patients, suggesting its involvement in multiple biological processes such as local inflammation, oxidative stress, metabolic processes, and immune responses. Our findings suggest that may be a novel biomarker for the clinical diagnosis of RA and may play a crucial role in the pathogenesis of RA. The study provides new insights into the molecular mechanisms of RA and potential new therapeutic targets.