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- W4310690216 abstract "Abstract Background Arthritis is the most common irreversible inflammatory disease of the bone and joints. We aimed to investigate the relationship between m6A methylation and arthritis and provide new strategies for diagnosis. Methods Microarray data and clinical data of 94 arthritis patients were downloaded from the GEO database. A total of 37 m6A methylated genes were obtained from the literature. A combined analysis of the data identified differentially expressed m6A genes associated with arthritis. Then, the least absolute shrinkage selection operator (LASSO) regression analysis was used to construct a risk prediction model for m6A methylated genes. Subsequently, unsupervised clustering of hub genes was performed to analyze biological and immunological level differences between the two subgroups. Drug sensitivity analysis identified drugs with potential efficacy in arthritis. Results A diagnostic model of arthritis consisting of nine m6A methylated genes was obtained. Among them, YTHDF2, YTHDC1, and YTDC2 had the greatest effect on the model. Meanwhile, the two m6A-related genes subgroups differed at the level of the immune microenvironment. Conclusion This study obtained predictive models that can guide the diagnosis of arthritis and drugs that may have potential efficacy, thus providing new ideas to explore the potential molecular mechanisms of m6A methylation in disease development." @default.
- W4310690216 created "2022-12-15" @default.
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- W4310690216 date "2022-12-05" @default.
- W4310690216 modified "2023-10-15" @default.
- W4310690216 title "Construction and analysis of a diagnostic model for arthritis based on N6-methyladenosine-related genes" @default.
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- W4310690216 doi "https://doi.org/10.21203/rs.3.rs-2321306/v1" @default.
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