ArticleAvicenna journal of medical biotechnology
Comparative Expression of
Article in Avicenna journal of medical biotechnology. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
6 authors.
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Abstract
Background: Rheumatoid Arthritis (RA) is a chronic inflammatory joint disease. Current treatments often have limited efficacy and cause side effects due to their nonspecific action, while early diagnosis is challenging. This study combined bioinformatics and experimental methods to identify key genes and pathways involved in RA, aiming to discover novel therapeutic targets and diagnostic biomarkers. Methods: RNA-seq data from immune cells of RA patients and healthy donors (GSE117769) were analyzed with DESeq to identify Differentially Expressed Genes (DEGs). Affected pathways were explored using EnrichR, and druggable genes were identified through DGIdb and a literature review. Expression of candidate genes was validated in additional RA blood and synovium microarray datasets (GSE45291, GSE82107, GSE77298) using the GEO2R tool. Finally, RT-qPCR was used to measure the expression of selected genes in Peripheral blood Mononuclear Cells (PBMCs) from newly-diagnosed and chronic RA patients and controls, with associations to clinical features and diagnostic accuracy assessed. Synovial fluid of RA patients were stained with Giemsa. Results: Combined Conclusion: This study identified
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