Two hub genes of bipolar disorder, a bioinformatics study based on the GEO database.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:39157463", "kind": "science-record", "revision": 3, "content_hash": "sha256:2cc6890c0349f08d7a1ab85dd8896fc1548a49c835d7457c950de5976c615ff1", "created_at": "2026-11-01T20:29:17Z", "updated_at": "2026-11-01T22:12:31Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Two hub genes of bipolar disorder, a bioinformatics study based on the GEO database.", "doi": "10.1016/j.ibneur.2024.07.006", "pmid": "39157463", "authors": ["Ping Sun", "Shunkang Feng", "Hui Yu", "Xiaoxiao Wang", "Yiru Fang"], "journal": "IBRO neuroscience reports", "year": 2024, "abstract": "Bipolar disorder is a mood illness that affects many people. It has a high recurrence frequency and will cause significant damage to the patient's social function. At present, the pathogenesis of BD is not clear. The National Center for Biotechnology Information (NCBI) established and maintained the Gene Expression Omnibus (GEO) database, a gene expression database. For bioinformatics analysis, researchers can obtain expression data from the internet. At present, the samples of the dataset used in the research of BD are mostly from brain tissue, and the data containing blood samples are rarely used. GEO databases (GSE46416, GSE5388, and GSE5389) were used to retrieve public data, and utilizing the online tool GEO2R, differentially expressed genes (DEGs) were retrieved. The common DEGs between the samples of patients with BD and the samples of the normal population were screened by Venn diagrams. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were used to perform functional annotation and pathway enrichment analysis of DEGs. A protein-protein interaction network (PPI) was built to investigate hub genes on this basis. There were 117 up-regulated DEGs and 38 down-regulated DEGs discovered, with two hub genes [SRC, CDKN1A] among the up-regulated DEGs. These two hub genes were also highly enriched in the oxytocin signaling pathway, proteoglycans in cancer and bladder cancer, according to KEGG analysis. The results of the receiver operating characteristic curve (ROC) of SRC and CDKN1A in the three datasets strongly suggested that SRC and CDKN1A were potential diagnostic markers of BD. The results strongly suggest that SRC and CDKN1A are related to the pathogenesis of BD.", "claims": [{"id": "claim-method", "statement": "To analyze the DEGs among all samples, the GEO2R analysis program was used online. ROC curves were used to assess expression levels in BD samples to demonstrate the diagnostic usefulness of SRC and CDKN1A.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39157463", "locator": "sections[4] \"Differentially expressed genes\" paragraph 2", "quote": "To analyze the DEGs among all samples, the GEO2R analysis program was used online."}, {"asset": "source:pmid:39157463", "locator": "sections[13] \"Diagnostic evaluation of SRC and CDKN1A\" paragraph 2", "quote": "ROC curves were used to assess expression levels in BD samples to demonstrate the diagnostic usefulness of SRC and CDKN1A."}], "state": "complete"}, {"id": "claim-data-access", "statement": "There are three datasets included in our research, GSE5388 and GSE5389 are microarrays based on GPL96 [HG-U133A] Affymetrix Human Genome U133A Array. 61 postmortem dorsolateral prefrontal brain samples, comprising 30 BD cases and 31 healthy samples, were included in GSE5388.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39157463", "locator": "sections[3] \"Source and filtering of datasets\" paragraph 2", "quote": "There are three datasets included in our research, GSE5388 and GSE5389 are microarrays based on GPL96 [HG-U133A] Affymetrix Human Genome U133A Array. 61 postmortem dorsolateral prefrontal brain samples, comprising 30 BD cases and 31 healthy samples, were included in GSE5388."}], "state": "complete"}, {"id": "claim-target-result", "statement": "SRC and CDKN1A may be useful diagnostic biomarkers in the identification of bipolar illness (AUC:0.60–1.00).", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:39157463", "locator": "sections[13] \"Diagnostic evaluation of SRC and CDKN1A\" paragraph 5", "quote": "SRC and CDKN1A may be useful diagnostic biomarkers in the identification of bipolar illness (AUC:0.60–1.00)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "SRC and CDKN1A may be useful diagnostic biomarkers in the identification of bipolar illness (AUC:0.60–1.00).", "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:39157463"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "complete", "blocked_on": null, "description": "The GEO series accession resolves and its sample accessions are listed. 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