In silico prediction and validation of potential therapeutic genes in pancreatic β-cells associated with type 2 diabetes.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:32952650", "kind": "science-record", "revision": 8, "content_hash": "sha256:a112f3c4468dd9f8a0c2436d85471e3e9c37f506fd228e48f69354c45f7cdf64", "created_at": "2026-11-01T15:41:10Z", "updated_at": "2026-11-01T22:45:21Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "In silico prediction and validation of potential therapeutic genes in pancreatic β-cells associated with type 2 diabetes.", "doi": "10.3892/etm.2020.9188", "pmid": "32952650", "authors": ["Di Yi Zhou", "Xin Mou", "Kaiyuan Liu", "Wen Hong Liu", "Ya Qing Xu", "Danyang Zhou"], "journal": "Experimental and therapeutic medicine", "year": 2020, "abstract": "Diabetes mellitus is becoming a major health burden worldwide. Pancreatic β-cell death is a characteristic of type 2 diabetes (T2D), but the underlying mechanisms of pancreatic β-cell death remain unknown. Therefore, the aim of the present study was to identify potential targets in the pancreatic islet of T2D. The GSE20966 dataset was obtained from the Gene Expression Omnibus (GEO) database, and differentially expressed genes (DEGs) were identified by using the GEO2R tool. The Gene Ontology terms and Kyoto Encyclopedia of Genes and Genomes Pathway enrichment analysis of DEGs were further assessed using the Database for Annotation, Visualization and Integrated Discovery. Furthermore, protein-protein interaction (PPI) networks were constructed for the up- and downregulated genes using STRING databases and were then visualized with Cytoscape. The body weight, fasting blood glucose (FBG), pancreatic index and biochemistry parameters were measured in db/db mice. Moreover, the morphology of the pancreas was detected by hematoxylin and eosin staining, and hub genes were assessed using reverse transcription-quantitative PCR (RT-qPCR) and western blot analysis. In total, 570 DEGs were screened, including 376 upregulated and 194 downregulated genes, which were associated with 'complement activation, classical pathway', 'proteolysis', 'complement activation' and 'pancreatic secretion pathway'. It was found that the body weight, FBG, alanine aminotransferase, aspartate aminotransferase, total cholesterol, triglycerides, blood urea nitrogen, creatinine, fasting serum insulin, glucagon and low-density lipoprotein cholesterol levels were significantly higher in db/db mice, while high-density lipoprotein cholesterol levels and the pancreatic index were significantly decreased. Furthermore, albumin, interleukin-8, CD44, C-C motif chemokine ligand 2, hepatocyte growth factor, cystic fibrosis transmembrane conductance regulator, histone cluster 1 H2B family member n, mitogen-activated protein kinase 11 and neurotrophic receptor tyrosine kinase 2 were identified as hub genes in PPI network. RT-qPCR and western blotting results demonstrated the same expression trend in hub genes as found by the bioinformatics analysis. Therefore, the present study identified a series of hub genes involved in the progression of pancreatic β-cell, which may help to develop effective therapeutic strategy for T2D.", "claims": [{"id": "claim-method", "statement": "Gene expression profiling of GSE20966, using the Agilent-014850 Whole Human Genome Microarray 4x44 K G4112F platform (Agilent Technologies, Inc.), deposited by Marselli et al (21) was downloaded from the GEO database (http://www.ncbi.nlm.nih.gov/geo/).\nSubsequently, the linear models for microarray data package (limma; Version: 3.26.8; https://www.bioconductor.org/) in R/Bioconductor (Version: R 3.2.3; https://www.r-project.org/) were used to screen the DEGs between T2D and healthy pancreatic β-cells, with P<0.05 and log2|(FC)|≥1 used as the cut-off criteria.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:32952650", "locator": "sections[4] \"Data collection\" paragraph 2", "quote": "Gene expression profiling of GSE20966, using the Agilent-014850 Whole Human Genome Microarray 4x44 K G4112F platform (Agilent Technologies, Inc.), deposited by Marselli et al (21) was downloaded from the GEO database (http://www.ncbi.nlm.nih.gov/geo/)."}, {"asset": "source:pmid:32952650", "locator": "sections[5] \"Data processing and identification of DEGs\" paragraph 2", "quote": "Subsequently, the linear models for microarray data package (limma; Version: 3.26.8; https://www.bioconductor.org/) in R/Bioconductor (Version: R 3.2.3; https://www.r-project.org/) were used to screen the DEGs between T2D and healthy pancreatic β-cells, with P<0.05 and log2|(FC)|≥1 used as the cut-off criteria."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:32952650", "locator": "sections[26] \"Availability of data and materials\" paragraph 2", "quote": "The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": null, "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:32952650"], "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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