Identification of Hub Genes in Patients with Alzheimer Disease and Obstructive Sleep Apnea Syndrome Using Integrated Bioinformatics Analysis.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:34916831", "kind": "science-record", "revision": 4, "content_hash": "sha256:05861f6ab235ad6020bb81752ba6cc9933d9aad8fe026918c7ce02debe71dcfb", "created_at": "2026-11-01T17:36:37Z", "updated_at": "2026-11-01T22:05:23Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of Hub Genes in Patients with Alzheimer Disease and Obstructive Sleep Apnea Syndrome Using Integrated Bioinformatics Analysis.", "doi": "10.2147/IJGM.S341078", "pmid": "34916831", "authors": ["Lanxiang Wu", "Wenjun Wang", "Sheng Tian", "Heqing Zheng", "Pan Liu", "Wei Wu"], "journal": "International journal of general medicine", "year": 2021, "abstract": "BACKGROUND: Obstructive sleep apnea syndrome (OSA) is associated with an increased risk of Alzheimer's disease (AD). This study aimed to identify the key common genes in AD and OSA and explore molecular mechanism value in AD.\nMETHODS: Expression profiles GSE5281 and GSE135917 were acquired from Gene Expression Omnibus (GEO) database, respectively. Weighted gene co-expression network analysis (WGCNA) and R 4.0.2 software were used for identifying differentially expressed genes (DEGs) related to AD and OSA. Function enrichment analyses using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, and the protein-protein interaction network (PPI) using the STRING database were subsequently performed on the shared DEGs. Finally, the hub genes were screened from the PPI network using the MCC algorithm of CytoHubba plugin.\nRESULTS: Seven modules and four modules were the most significant with AD and OSA by WGCNA, respectively. A total of 33 common genes were screened in AD and OSA by VENN. Functional enrichment analysis indicated that DEGs were mainly involved in cellular response to oxidative stress, neuroinflammation. Among these DEGs, the top 10 hub genes (high scores in cytoHubba) were selected in the PPI network, including AREG, SPP1, CXCL2, ITGAX, DUSP1, COL1A1, SCD, ACTA2, CCND2, ATF3.\nCONCLUSION: This study presented ten target genes on the basis of common genes to AD and OSA. These candidate genes may provide a novel perspective to explore the underlying mechanism that OSA leads to an increased risk of AD at the transcriptome level.", "claims": [{"id": "claim-method", "statement": "Weighted gene co-expression network analysis (WGCNA) and R 4.0.2 software were used for identifying differentially expressed genes (DEGs) related to AD and OSA.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34916831", "locator": "sections[0] \"Abstract\" paragraph 2", "quote": "Weighted gene co-expression network analysis (WGCNA) and R 4.0.2 software were used for identifying differentially expressed genes (DEGs) related to AD and OSA."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The GSE5281 dataset was based on GPL570 platforms (HG-U133_Plus_2); Affymetrix Human Genome U133 Plus 2.0 Array), including 87 brain samples from AD patients and 74 normal aged brain samples from healthy controls.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34916831", "locator": "sections[3] \"Dataset Preparation\" paragraph 2", "quote": "The GSE5281 dataset was based on GPL570 platforms (HG-U133_Plus_2); Affymetrix Human Genome U133 Plus 2.0 Array), including 87 brain samples from AD patients and 74 normal aged brain samples from healthy controls."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The analysis identified 33 common genes between AD and OSA and selected 10 hub genes: AREG, SPP1, CXCL2, ITGAX, DUSP1, COL1A1, SCD, ACTA2, CCND2, and ATF3.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:34916831", "locator": "sections[9] \"Identification of DEGs\" paragraph 3", "quote": "A total of 33 common genes were obtained by overlapping intersecting DEGs in key modules of OSA and AD (Figure 4C)."}, {"asset": "source:pmid:34916831", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "Among these DEGs, the top 10 hub genes (high scores in cytoHubba) were selected in the PPI network, including AREG, SPP1, CXCL2, ITGAX, DUSP1, COL1A1, SCD, ACTA2, CCND2, ATF3."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The analysis identified 33 common genes between AD and OSA and selected 10 hub genes: AREG, SPP1, CXCL2, ITGAX, DUSP1, COL1A1, SCD, ACTA2, CCND2, and ATF3.", "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:34916831"], "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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