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

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...

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Autores principales: Zhong, Ming, Wu, Yilong, Ou, Weijie, Huang, Linjing, Yang, Liyong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Portland Press Ltd. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6542763/
https://www.ncbi.nlm.nih.gov/pubmed/31088900
http://dx.doi.org/10.1042/BSR20182172
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author Zhong, Ming
Wu, Yilong
Ou, Weijie
Huang, Linjing
Yang, Liyong
author_facet Zhong, Ming
Wu, Yilong
Ou, Weijie
Huang, Linjing
Yang, Liyong
author_sort Zhong, Ming
collection PubMed
description 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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spelling pubmed-65427632019-06-07 Identification of key genes involved in type 2 diabetic islet dysfunction: a bioinformatics study Zhong, Ming Wu, Yilong Ou, Weijie Huang, Linjing Yang, Liyong Biosci Rep Research Articles 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. Portland Press Ltd. 2019-05-31 /pmc/articles/PMC6542763/ /pubmed/31088900 http://dx.doi.org/10.1042/BSR20182172 Text en © 2019 The Author(s). http://creativecommons.org/licenses/by/4.0/This is an open access article published by Portland Press Limited on behalf of the Biochemical Society and distributed under the Creative Commons Attribution License 4.0 (CC BY) (http://creativecommons.org/licenses/by/4.0/) .
spellingShingle Research Articles
Zhong, Ming
Wu, Yilong
Ou, Weijie
Huang, Linjing
Yang, Liyong
Identification of key genes involved in type 2 diabetic islet dysfunction: a bioinformatics study
title Identification of key genes involved in type 2 diabetic islet dysfunction: a bioinformatics study
title_full Identification of key genes involved in type 2 diabetic islet dysfunction: a bioinformatics study
title_fullStr Identification of key genes involved in type 2 diabetic islet dysfunction: a bioinformatics study
title_full_unstemmed Identification of key genes involved in type 2 diabetic islet dysfunction: a bioinformatics study
title_short Identification of key genes involved in type 2 diabetic islet dysfunction: a bioinformatics study
title_sort identification of key genes involved in type 2 diabetic islet dysfunction: a bioinformatics study
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6542763/
https://www.ncbi.nlm.nih.gov/pubmed/31088900
http://dx.doi.org/10.1042/BSR20182172
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