AI Article Synopsis
- - The study focuses on rheumatoid arthritis (RA), highlighting the need for reliable diagnostic markers and treatment targets due to its chronic autoimmune symptoms like joint pain and stiffness.
- - Using gene expression data and advanced machine learning techniques, researchers identified five key necroptosis-related genes that could serve as potential biomarkers for diagnosing RA, as well as correlating with immune cell activity.
- - The findings suggest a new necroptosis-related subtype of RA and emphasize the importance of these biomarkers for future clinical diagnosis and immunotherapy approaches.
Article Abstract
Objectives: Rheumatoid arthritis (RA) is a chronic autoimmune inflammatory disease that is characterized by persistent morning stiffness, joint pain, and swelling. However, there is a lack of reliable diagnostic markers and therapeutic targets that are both effective and trustworthy.
Methods: In this study, gene expression profiles (GSE89408, GSE55235, GSE55457, and GSE77298) were obtained from the Gene Expression Omnibus database. Differentially expressed necroptosis-related genes were attained from intersection of necroptosis-related gene set, differentially expressed genes, and weighted gene co-expression network analysis. The LASSO, random forest, and SVM-RFE machine learning algorithms were utilized to further screen potential diagnostic genes for RA. Immune cell infiltration was analyzed using the CIBERSORT method. The expressions of diagnostic genes were validated through quantitative real-time PCR, western blotting, immunohistochemistry, and immunofluorescence staining in synovial tissues collected from three trauma controls and three RA patients.
Results: Five core necroptosis-related genes (FAS, CYBB, TNFSF10, EIF2AK2, and BIRC2) were identified as potential biomarkers for RA. Two different necroptosis patterns based on these five genes were confirmed to significantly correlated with immune cells (especially macrophages). In vitro experiments showed significantly higher mRNA and protein expression levels of CYBB and EIF2AK2 in RA patients compared to normal controls, consistent with the bioinformatics analysis results.
Conclusion: Our study identified a novel necroptosis-related subtype and five diagnostic biomarkers of RA, revealed vital roles in the development and occurrence of RA, and offered potential targets for clinical diagnosis and immunotherapy.
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| http://dx.doi.org/10.1016/j.intimp.2024.111809 | DOI Listing |
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