Literature DB >> 36220923

Bioinformatic identification and validation of autophagy-related genes in rheumatoid arthritis.

Dan-Dan Fan1, Peng-Yu Tan1, Li Jin1, Yuan Qu1, Qing-Hong Yu2.   

Abstract

OBJECTIVES: Rheumatoid arthritis (RA) is a chronic systemic autoimmune disorder characterized by progressive synovial inflammation and joint destruction, with a largely unknown etiology. Studies have suggested that autophagy and its expression may be involved in the pathogenesis of RA; however, autophagy-related genes in RA are still largely unidentified. Therefore, in this study, we aimed to identify and validate autophagy-related genes in RA.
METHODS: We identified differentially expressed autophagy-related genes between patients with RA and healthy individuals using gene expression profiles in the GSE55235 dataset and R software. Subsequently, correlation analysis, protein-protein interaction, gene ontology enrichment, and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were carried out using these differentially expressed autophagy-related genes. Finally, our results were validated by examining the expression of differentially expressed autophagy-related hub genes in clinical samples using qRT-PCR.
RESULTS: We identified 52 potential autophagy-related genes in RA based on bioinformatic analyses. Ten hub genes, CASP8, CTSB, TNFSF10, FADD, BAX, MYC, FOS, CDKN1A, GABARAPL1, and BNIP3, were validated to be differentially expressed and may serve as valuable prognostic markers and new potential therapeutic targets for RA via the regulation of autophagy.
CONCLUSIONS: Our results may help improve the understanding of RA pathogenesis. Autophagy-related genes in RA could be valuable biomarkers for diagnosis and prognosis and they might be exploited clinically as therapeutic targets in the future.
© 2022. The Author(s), under exclusive licence to International League of Associations for Rheumatology (ILAR).

Entities:  

Keywords:  Autophagy; Bioinformatic analyses; Gene expression, Gene expression Omnibus dataset; Rheumatoid arthritis

Year:  2022        PMID: 36220923     DOI: 10.1007/s10067-022-06399-2

Source DB:  PubMed          Journal:  Clin Rheumatol        ISSN: 0770-3198            Impact factor:   3.650


  32 in total

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