Abstract
m6A modification is the most abundant mRNA modifications and plays an integral role in various biological processes in eukaryotes. However, the role of m6A regulators in rheumatoid arthritis remains unknown. To determine the expression of m6A RNA methylation regulators in rheumatoid arthritis and their possible functional and prognostic value. In this study, we performed differential analysis in the comprehensive gene expression database GSE93272 dataset between non-rheumatoid arthritis patients and rheumatoid arthritis patients to obtain 15 important m6A regulators. A random forest model and lasso regression were used to screen the five most important m6A regulators to predict the risk of developing rheumatoid arthritis. After further validation using in vitro qPCR experiments, a nomogram model was developed based on the four most important m6A regulators (ELAVL1, WTAP, YTHDF1, and ALKBH5). Immuno-infiltration analysis and consensus clustering analysis were then performed. An analysis of the decision curve showed that the nomogram model could be beneficial to patients. According to selected important m6A regulators, patients with rheumatoid arthritis were classified into two m6A models (ClusterA and ClusterB) via consensus approach. Activated B cells, CD56dim natural killer cells, immature B cells, monocytes, natural killer T cells, and T lymphocytes were associated with ClusterA in immune infiltration analysis. Importantly, immune infiltration in patients with high ELAVL1 expression was strikingly similar to ClusterA. m6A regulators play a non-negligible role in the development of rheumatoid arthritis. A study of m6A patterns may provide future therapeutic options for rheumatoid arthritis.
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Data Availability
The primary datasets obtained during this analysis are available for download in the Gene Expression Omnibus database (https://www.ncbi.nlm.nih.gov/geo/).
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HYW and XGZ conceptualized the article. HYW, JPL, and XGZ contributed to the methodology. SXZ and SS conducted the experimental validation. SXZ and XGZ visualized the results. Finally, SXZ and YJZ drafted the original manuscript.
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The study was conducted in accordance with the Declaration of Helsinki and was approved by the Ethics Committee of Yuxi People's Hospital (with protocol code: 2022kmykdx6f157 and date of approval: November 4, 2022).
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Zhang, S., Sun, S., Zhang, Y. et al. Comprehensive Analysis of N6-Methyladenosine RNA Methylation Regulators in the Diagnosis and Subtype Classification of Rheumatoid Arthritis. Biochem Genet (2023). https://doi.org/10.1007/s10528-023-10610-7
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DOI: https://doi.org/10.1007/s10528-023-10610-7