Bioinformatics Analysis of the Molecular Mechanism and Potential Treatment Target of Ankylosing Spondylitis.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:34335866", "kind": "science-record", "revision": 7, "content_hash": "sha256:c30c11e08869be4608cd2256e33bdc5b4edc50389ef7abe0041a479d4eefb519", "created_at": "2026-11-01T15:41:46Z", "updated_at": "2026-11-01T22:04:23Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Bioinformatics Analysis of the Molecular Mechanism and Potential Treatment Target of Ankylosing Spondylitis.", "doi": "10.1155/2021/7471291", "pmid": "34335866", "authors": ["Fanyan Meng", "Ningna Du", "Daoming Xu", "Li Kuai", "Lanying Liu", "Minning Xiu"], "journal": "Computational and mathematical methods in medicine", "year": 2021, "abstract": "Ankylosing spondylitis (AS) is an autoimmune disease that mainly affects the spinal joints, sacroiliac joints, and adjacent soft tissues. We conducted bioinformatics analysis to explore the molecular mechanism related to AS pathogenesis and uncover novel potential molecular targets for the treatment of AS. The profiles of GSE25101, containing gene expression data extracted from the blood of 16 AS patients and 16 matched controls, were acquired from the Gene Expression Omnibus (GEO) database. The background correction and standardization were carried out utilizing the transcript per million (TPM) method. After analysis of AS patients and the normal groups, we identified 199 differentially expressed genes (DEGs) with upregulation and 121 DEGs with downregulation by the limma R package. The results of the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Gene Ontology (GO) biological process enrichment analysis revealed that the DEGs with upregulation were mainly associated with spliceosome, ribosome, RNA-catabolic process, electron transport chain, etc. And the DEGs with downregulation primarily participated in T cell-associated pathways and processes. After analysis of the protein-protein interaction (PPI) network, our data revealed that the hub genes, comprising MRPL13, MRPL22, LSM3, COX7A2, COX7C, EP300, PTPRC, and CD4, could be the treatment targets in AS. Our data furnish new hints to uncover the features of AS and explore more promising treatment targets towards AS.", "claims": [{"id": "claim-method", "statement": "We obtained the top 20 significantly enriched terms with regard to the P values which were obtained on the basis of the accumulative hypergeometric distribution.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34335866", "locator": "sections[5] \"2.3. 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