An integrated bioinformatics analysis to identify the shared biomarkers in patients with obstructive sleep apnea syndrome and nonalcoholic fatty liver disease.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:39081807", "kind": "science-record", "revision": 3, "content_hash": "sha256:c2c34b095c9e3d4b70ec95958557d4e611e316f259a154144b70f50d298de02f", "created_at": "2026-11-01T20:29:09Z", "updated_at": "2026-11-01T22:12:20Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "An integrated bioinformatics analysis to identify the shared biomarkers in patients with obstructive sleep apnea syndrome and nonalcoholic fatty liver disease.", "doi": "10.3389/fgene.2024.1356105", "pmid": "39081807", "authors": ["Rou Zhang", "Zhijuan Liu", "Ran Li", "Xiaona Wang", "Li Ai", "Yongxia Li"], "journal": "Frontiers in genetics", "year": 2024, "abstract": "Background: Obstructive sleep apnea (OSA) syndrome and nonalcoholic fatty liver disease (NAFLD) have been shown to have a close association in previous studies, but their pathogeneses are unclear. This study explores the molecular mechanisms associated with the pathogenesis of OSA and NAFLD and identifies key predictive genes.\nMethods: Using the Gene Expression Omnibus (GEO) database, we obtained gene expression profiles GSE38792 for OSA and GSE89632 for NAFLD and related clinical characteristics. Mitochondrial unfolded protein response-related genes (UPRmtRGs) were acquired by collating and collecting UPRmtRGs from the GeneCards database and relevant literature from PubMed. The differentially expressed genes (DEGs) associated with OSA and NAFLD were identified using differential expression analysis. Gene Set Enrichment Analysis (GSEA) was conducted for signaling pathway enrichment analysis of related disease genes. Based on the STRING database, protein-protein interaction (PPI) analysis was performed on differentially co-expressed genes (Co-DEGs), and the Cytoscape software (version 3.9.1) was used to visualize the PPI network model. In addition, the GeneMANIA website was used to predict and construct the functional similar genes of the selected Co-DEGs. Key predictor genes were analyzed using the receiver operating characteristic (ROC) curve.\nResults: The intersection of differentially expressed genes shared between OSA and NAFLD-related gene expression profiles with UPRmtRGs yielded four Co-DEGs: ASS1, HDAC2, SIRT3, and VEGFA. GSEA obtained the relevant enrichment signaling pathways for OSA and NAFLD. PPI network results showed that all four Co-DEGs interacted (except for ASS1 and HDAC2). Ultimately, key predictor genes were selected in the ROC curve, including HDAC2 (OSA: AUC = 0.812; NAFLD: AUC = 0.729), SIRT3 (OSA: AUC = 0.775; NAFLD: AUC = 0.750), and VEGFA (OSA: AUC = 0.812; NAFLD: AUC = 0.861) (they have a high degree of accuracy in predicting whether a subject will develop two diseases).\nConclusion: In this study, four co-expression differential genes for OSA and NAFLD were obtained, and they can predict the occurrence of both diseases. Transcriptional mechanisms involved in OSA and NAFLD interactions may be better understood by exploring these key genes. Simultaneously, this study provides potential diagnostic and therapeutic markers for patients with OSA and NAFLD.", "claims": [{"id": "claim-method", "statement": "The receiver operating characteristic (ROC) curve (Mandrekar, 2010) was generated using the pROC package in R 4.1.2.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39081807", "locator": "sections[7] \"Statistical analysis\" paragraph 2", "quote": "The receiver operating characteristic (ROC) curve (Mandrekar, 2010) was generated using the pROC package in R 4.1.2."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The original contributions presented in the study are included in the article/Supplementary Materials, further inquiries can be directed to the corresponding authors.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39081807", "locator": "sections[17] \"Data availability statement\" paragraph 2", "quote": "The original contributions presented in the study are included in the article/Supplementary Materials, further inquiries can be directed to the corresponding authors."}], "state": "complete"}, {"id": "claim-target-result", "statement": "ROC analysis identified HDAC2, SIRT3, and VEGFA as the principal predictor genes with AUC values above 0.7 for both obstructive sleep apnea and nonalcoholic fatty liver disease.", "kind": "quantitative", "target": {"value": 0.672, "unit": "auc", "tolerance": null, "source": "The ROC curves indicated that in the OSA dataset GSE38792, the AUC values for ASS1, HDAC2, SIRT3, and VEGFA are 0.762, 0.812, 0.775, and 0.812, respectively (all above 0.7), suggesting their high accuracy in predicting the correct classification of case and normal groups. In the NAFLD dataset GSE89632, the AUC was 0.672 for ASS1, indicating lower accuracy in predicting the correct classification of case and normal groups, whereas the AUC values for HDAC2, SIRT3, and VEGFA are 0.729, 0.750, and 0.861, respectively (over 0.7), signifying their high accuracy in predicting the correct classification of case and normal groups."}, "evidence": [{"asset": "source:pmid:39081807", "locator": "sections[12] \"Group comparison charts and the ROC curves\" paragraph 4", "quote": "The ROC curves indicated that in the OSA dataset GSE38792, the AUC values for ASS1, HDAC2, SIRT3, and VEGFA are 0.762, 0.812, 0.775, and 0.812, respectively (all above 0.7), suggesting their high accuracy in predicting the correct classification of case and normal groups. In the NAFLD dataset GSE89632, the AUC was 0.672 for ASS1, indicating lower accuracy in predicting the correct classification of case and normal groups, whereas the AUC values for HDAC2, SIRT3, and VEGFA are 0.729, 0.750, and 0.861, respectively (over 0.7), signifying their high accuracy in predicting the correct classification of case and normal groups."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "partial", "objective": "ROC analysis identified HDAC2, SIRT3, and VEGFA as the principal predictor genes with AUC values above 0.7 for both obstructive sleep apnea and nonalcoholic fatty liver disease.", "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:39081807"], "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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