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pmid:31088900

Identification of key genes involved in type 2 diabetic islet dysfunction: a bioinformatics study.

Ming Zhong · Yilong Wu · Weijie Ou · Linjing Huang · Liyong Yang

Bioscience reports · 2019 doi:10.1042/BSR20182172

Paper

complete

Experiment

complete

Data

partial

Analysis

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Execution

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title
Identification of key genes involved in type 2 diabetic islet dysfunction: a bioinformatics study.
doi
10.1042/BSR20182172
pmid
31088900
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Ming Zhong
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Yilong Wu
[2]
Weijie Ou
[3]
Linjing Huang
[4]
Liyong Yang
journal
Bioscience reports
year
2019
abstract
Aims: To identify the key differentially expressed genes (DEGs) in islet and investigate their potential pathway in the molecular process of type 2 diabetes.Methods: Gene Expression Omnibus (GEO) datasets (GSE20966, GSE25724, GSE38642) of type 2 diabetes patients and normal controls were downloaded from GEO database. DEGs were further assessed by enrichment analysis based on the Database for Annotation, Visualization and Integrated Discovery (DAVID) 6.8. Then, by using Search Tool for the Retrieval Interacting Genes (STRING) 10.0 and gene set enrichment analysis (GSEA), we identified hub gene and associated pathway. At last, we performed quantitative real-time PCR (qPCR) to validate the expression of hub gene.Results: Forty-five DEGs were co-expressed in the three datasets, most of which were down-regulated. DEGs are mostly involved in cell pathway, response to hormone and binding. In protein-protein interaction (PPI) network, we identified ATP-citrate lyase (ACLY) as hub gene. GSEA analysis suggests low expression of ACLY is enriched in glycine serine and threonine metabolism, drug metabolism cytochrome P450 (CYP) and NOD-like receptor (NLR) signaling pathway. qPCR showed the same expression trend of hub gene ACLY as in our bioinformatics analysis.Conclusion: Bioinformatics analysis revealed that ACLY and the pathways involved are possible target in the molecular mechanism of type 2 diabetes.
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st, we performed quantitative real-time PCR (qPCR) to validate the expression of hub gene.Resu
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d NOD-like receptor (NLR) signaling pathway. qPCR showed the same expression trend of hub gene
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Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:31088900", "kind": "science-record", "revision": 9, "content_hash": "sha256:944a48c2d93904899b0b81b5817f2c5e229f98bce2734809dbcfdb76d15a9fd2", "created_at": "2026-11-01T15:40:45Z", "updated_at": "2026-11-01T22:43:57Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of key genes involved in type 2 diabetic islet dysfunction: a bioinformatics study.", "doi": "10.1042/BSR20182172", "pmid": "31088900", "authors": ["Ming Zhong", "Yilong Wu", "Weijie Ou", "Linjing Huang", "Liyong Yang"], "journal": "Bioscience reports", "year": 2019, "abstract": "Aims: To identify the key differentially expressed genes (DEGs) in islet and investigate their potential pathway in the molecular process of type 2 diabetes.Methods: Gene Expression Omnibus (GEO) datasets (GSE20966, GSE25724, GSE38642) of type 2 diabetes patients and normal controls were downloaded from GEO database. DEGs were further assessed by enrichment analysis based on the Database for Annotation, Visualization and Integrated Discovery (DAVID) 6.8. Then, by using Search Tool for the Retrieval Interacting Genes (STRING) 10.0 and gene set enrichment analysis (GSEA), we identified hub gene and associated pathway. At last, we performed quantitative real-time PCR (qPCR) to validate the expression of hub gene.Results: Forty-five DEGs were co-expressed in the three datasets, most of which were down-regulated. DEGs are mostly involved in cell pathway, response to hormone and binding. In protein-protein interaction (PPI) network, we identified ATP-citrate lyase (ACLY) as hub gene. GSEA analysis suggests low expression of ACLY is enriched in glycine serine and threonine metabolism, drug metabolism cytochrome P450 (CYP) and NOD-like receptor (NLR) signaling pathway. qPCR showed the same expression trend of hub gene ACLY as in our bioinformatics analysis.Conclusion: Bioinformatics analysis revealed that ACLY and the pathways involved are possible target in the molecular mechanism of type 2 diabetes.", "claims": [{"id": "claim-method", "statement": "Gene differential analysis was conducted using the limma R package.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:31088900", "locator": "sections[4] \"Screening of differentially expressed genes\" paragraph 2", "quote": "Gene differential analysis was conducted using the limma R package."}], "state": "complete"}, {"id": "claim-data-access", "statement": "Gene Expression Omnibus (GEO) datasets (GSE20966, GSE25724, GSE38642) of type 2 diabetes patients and normal controls were downloaded from GEO database.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:31088900", "locator": "sections[0] \"Abstract\" paragraph 2", "quote": "Gene Expression Omnibus (GEO) datasets (GSE20966, GSE25724, GSE38642) of type 2 diabetes patients and normal controls were downloaded from GEO database."}], "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:31088900"], "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:GSE20966"], "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:GSE20966"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:31088900", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1042/BSR20182172", "sha256": 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