The Bioinformatic Study Uncovers Probable Critical Genes Involved in the Pathophysiology of Biliary Atresia.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:35774294", "kind": "science-record", "revision": 4, "content_hash": "sha256:bcb5b6bf77163914ddeba77b14a2deec05688ec0f83c48229a21929477e2150b", "created_at": "2026-11-01T18:14:48Z", "updated_at": "2026-11-01T22:06:55Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "The Bioinformatic Study Uncovers Probable Critical Genes Involved in the Pathophysiology of Biliary Atresia.", "doi": "10.1155/2022/9108804", "pmid": "35774294", "authors": ["Si Chen", "Songli Wu", "Mingman Zhang"], "journal": "Computational and mathematical methods in medicine", "year": 2022, "abstract": "Background: Biliary atresia (BA) is an uncommon illness that causes the bile ducts outside and within the liver to become clogged in babies. If left untreated, the cholestasis causes increasing conjugated hyperbilirubinemia, cirrhosis, and hepatic failure. BA has a complicated aetiology, and the mechanisms that drive its development are unknown. The objective of this study was to show the role of probable critical genes involved in the pathophysiology of biliary atresia.\nMethods: We utilised the public Gene Expression Omnibus (GEO) microarray expression profiling dataset GSE46960 to find differentially expressed genes (DEGs) in 64 biliary atresia newborns, 14 infants with various causes of intrahepatic cholestasis, and 7 deceased-donor children as control subjects in our study. The relevant information was looked into. The important modules were identified after functional enrichment, GO and KEGG pathway analyses, protein-protein interaction (PPI) network analyses, and GSEA analysis.\nResults: The differential expression analysis revealed a total of 22 elevated genes. To further understand the biological activities of the DEGs, we run functional enrichment analyses on them. Meanwhile, KEGG analysis has revealed significant enrichment of pathways involved in activating cross-talking with inflammation and fibrosis in BA. SERPINE1, THBS1, CCL2, MMP7, CXCL8, EPCAM, VCAN, ITGA2, AREG, and HAS2, which may play a significant regulatory role in the pathogenesis of BA, were identified by PPI studies.\nConclusion: Our findings suggested 10 hub genes and probable mechanisms of BA in the current study through bioinformatic analysis.", "claims": [{"id": "claim-method", "statement": "P values and corrected P values were calculated using T-tests.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35774294", "locator": "sections[4] \"2.2. Differential Expression Analysis\" paragraph 2", "quote": "P values and corrected P values were calculated using T-tests."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The data could be obtained from contacting the corresponding author.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35774294", "locator": "sections[16] \"Data Availability\" paragraph 2", "quote": "The data could be obtained from contacting the corresponding author."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The study identified 10 hub genes and probable mechanisms of biliary atresia through bioinformatic analysis.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:35774294", "locator": "sections[0] \"Abstract\" paragraph 4", "quote": "Our findings suggested 10 hub genes and probable mechanisms of BA in the current study through bioinformatic analysis."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The study identified 10 hub genes and probable mechanisms of biliary atresia through bioinformatic analysis.", "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:35774294"], "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. This lane did not download the dataset or read its licence.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE46960"], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "complete", "blocked_on": null, "description": "Apply the paper's statistical method to the resolved series and compare the result with the published target.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE46960"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:35774294", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1155/2022/9108804", "sha256": "sha256:fac8ad437db20ade64ea553099ab944f6d83b11358e9cb674de303ac748738b2", "bytes": 22490, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1155/2022/9108804", "version": null, "note": "Full article fetched from PMC; 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