M6A-related bioinformatics analysis indicates that LRPPRC is an immune marker for ischemic stroke.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:38632288", "kind": "science-record", "revision": 3, "content_hash": "sha256:09f9a2c3d20dd1e43d1cc3c580bda83965911b4919f8e24f6b61840d2e1916ab", "created_at": "2026-11-01T19:20:36Z", "updated_at": "2026-11-01T22:11:42Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "M6A-related bioinformatics analysis indicates that LRPPRC is an immune marker for ischemic stroke.", "doi": "10.1038/s41598-024-57507-y", "pmid": "38632288", "authors": ["Lianwei Shen", "Shouwei Yue"], "journal": "Scientific reports", "year": 2024, "abstract": "Ischemic stroke (IS) is a common cerebrovascular disease whose pathogenesis involves a variety of immune molecules, immune channels and immune processes. 6-methyladenosine (m6A) modification regulates a variety of immune metabolic and immunopathological processes, but the role of m6A in IS is not yet understood. We downloaded the data set GSE58294 from the GEO database and screened for m6A-regulated differential expression genes. The RF algorithm was selected to screen the m6A key regulatory genes. Clinical prediction models were constructed and validated based on m6A key regulatory genes. IS patients were grouped according to the expression of m6A key regulatory genes, and immune markers of IS were identified based on immune infiltration characteristics and correlation. Finally, we performed functional enrichment, protein interaction network analysis and molecular prediction of the immune biomarkers. We identified a total of 7 differentially expressed genes in the dataset, namely METTL3, WTAP, YWHAG, TRA2A, YTHDF3, LRPPRC and HNRNPA2B1. The random forest algorithm indicated that all 7 genes were m6A key regulatory genes of IS, and the credibility of the above key regulatory genes was verified by constructing a clinical prediction model. Based on the expression of key regulatory genes, we divided IS patients into 2 groups. Based on the expression of the gene LRPPRC and the correlation of immune infiltration under different subgroups, LRPPRC was identified as an immune biomarker for IS. GO enrichment analyses indicate that LRPPRC is associated with a variety of cellular functions. Protein interaction network analysis and molecular prediction indicated that LRPPRC correlates with a variety of immune proteins, and LRPPRC may serve as a target for IS drug therapy. Our findings suggest that LRPPRC is an immune marker for IS. Further analysis based on LRPPRC could elucidate its role in the immune microenvironment of IS.", "claims": [{"id": "claim-method", "statement": "Then Wilcoxon test was used to detect the difference between ischemic stroke patients and controls in the above m6A-related gene expression model, and the difference in m6A-related genes was screened as statistically significant at P < 0.05.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38632288", "locator": "sections[4] \"Screening for m6A-regulated differential genes in IS patients\" paragraph 2", "quote": "Then Wilcoxon test was used to detect the difference between ischemic stroke patients and controls in the above m6A-related gene expression model, and the difference in m6A-related genes was screened as statistically significant at P < 0.05."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The dataset for this study is GSE58294 from the GEO database, which contains transcriptome-wide data on blood from 69 cardioembolic ischaemic stroke samples and 22 control samples. 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