ArticleJournal of orthopaedic surgery and research2023
RNA sequencing and bioinformatics analysis of differentially expressed genes in the peripheral serum of ankylosing spondylitis patients.
Article in Journal of orthopaedic surgery and research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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Who cites it
4 citing papers in PubMed, 6 citations in OpenAlex.
- Article
- mRNAome Analysis of Whole Blood of Patients with Psoriatic Arthritis, Ankylosing Spondylitis, and Rheumatoid Arthritis.Current rheumatology reviews · 2026Review
- Identification and bioinformatics analysis of lncRNAs in serum of patients with ankylosing spondylitis.BMC musculoskeletal disorders · 2024Review
- Article
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Authors and funding
7 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAnkylosing spondylitis (AS) is a chronic progressive autoimmune disease characterized by spinal and sacroiliac arthritis, but its pathogenesis and genetic basis are largely unclear.
methodsWe randomly selected three serum samples each from an AS and a normal control (NC) group for high-throughput sequencing followed by using edgeR to find differentially expressed genes (DEGs). Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes, Reactome pathway analyses, and Gene Set Enrichment Analysis were used to comprehensively analyze the possible functions and pathways involved with these DEGs. Protein-protein interaction (PPI) networks were constructed using the STRING database and Cytoscape. The modules and hub genes of these DEGs were identified using MCODE and CytoHubba plugins. Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) was used to validate the expression levels of candidate genes in serum samples from AS patients and healthy controls.
resultsWe successfully identified 100 significant DEGs in serum. When we compared them with the NC group, 49 of these genes were upregulated in AS patients and 51 were downregulated. GO function and pathway enrichment analysis indicated that these DEGs were mainly enriched in several signaling pathways associated with endoplasmic reticulum stress, including protein processing in the endoplasmic reticulum, unfolded protein response, and ubiquitin-mediated proteolysis. We also constructed a PPI network and identified the highly connected top 10 hub genes. The expression levels of the candidate hub genes PPARG, MDM2, DNA2, STUB1, UBTF, and SLC25A37 were then validated by RT-qPCR analysis. Finally, receiver operating characteristic curve analysis suggested that PPARG and MDM2 may be the potential biomarkers of AS.
conclusionsThese findings may help to further elucidate the pathogenesis of AS and provide valuable potential gene biomarkers or targets for the diagnosis and treatment of AS.
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