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Weighted gene co-expression network analysis to define pivotal modules and genes in diabetic heart failure

This research was carried out to reveal specific hub genes involved in diabetic heart failure, as well as remarkable pathways that hub genes locate. The GSE26887 dataset from the GEO website was downloaded. The gene co-expression network was generated and central modules were analyzed to identify ke...

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Detalles Bibliográficos
Autores principales: Liang, Weiwei, Sun, FangFang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Portland Press Ltd. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7340867/
https://www.ncbi.nlm.nih.gov/pubmed/32602534
http://dx.doi.org/10.1042/BSR20200507
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author Liang, Weiwei
Sun, FangFang
author_facet Liang, Weiwei
Sun, FangFang
author_sort Liang, Weiwei
collection PubMed
description This research was carried out to reveal specific hub genes involved in diabetic heart failure, as well as remarkable pathways that hub genes locate. The GSE26887 dataset from the GEO website was downloaded. The gene co-expression network was generated and central modules were analyzed to identify key genes using the WGCNA method. Functional analyses were conducted on genes of the clinical interest modules via Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Gene ontology (GO) enrichment, associated with protein–protein interaction (PPI) network construction in a sequence. Centrality parameters of the PPI network were determined using the CentiScape plugin in Cytoscape. Key genes, defined as genes in the ≥95% percentile of the degree distribution of significantly perturbed networks, were identified. Twenty gene co-expression modules were detected by WGCNA analysis. The module marked in light yellow exhibited the most significant association with diabetes (P=0.08). Genes involved in this module were primarily located in immune response, plasma membrane and receptor binding, as shown by the GO analysis. These genes were primarily assembled in endocytosis and phagosomes for KEGG pathway enrichment. Three key genes, STK39, HLA-DPB1 and RAB5C, which may be key genes for diabetic heart failure, were identified. To our knowledge, our study is the first to have constructed the co-expression network involved in diabetic heart failure using the WGCNA method. The results of the present study have provided better understanding the molecular mechanism of diabetic heart failure.
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spelling pubmed-73408672020-07-17 Weighted gene co-expression network analysis to define pivotal modules and genes in diabetic heart failure Liang, Weiwei Sun, FangFang Biosci Rep Bioinformatics This research was carried out to reveal specific hub genes involved in diabetic heart failure, as well as remarkable pathways that hub genes locate. The GSE26887 dataset from the GEO website was downloaded. The gene co-expression network was generated and central modules were analyzed to identify key genes using the WGCNA method. Functional analyses were conducted on genes of the clinical interest modules via Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Gene ontology (GO) enrichment, associated with protein–protein interaction (PPI) network construction in a sequence. Centrality parameters of the PPI network were determined using the CentiScape plugin in Cytoscape. Key genes, defined as genes in the ≥95% percentile of the degree distribution of significantly perturbed networks, were identified. Twenty gene co-expression modules were detected by WGCNA analysis. The module marked in light yellow exhibited the most significant association with diabetes (P=0.08). Genes involved in this module were primarily located in immune response, plasma membrane and receptor binding, as shown by the GO analysis. These genes were primarily assembled in endocytosis and phagosomes for KEGG pathway enrichment. Three key genes, STK39, HLA-DPB1 and RAB5C, which may be key genes for diabetic heart failure, were identified. To our knowledge, our study is the first to have constructed the co-expression network involved in diabetic heart failure using the WGCNA method. The results of the present study have provided better understanding the molecular mechanism of diabetic heart failure. Portland Press Ltd. 2020-07-07 /pmc/articles/PMC7340867/ /pubmed/32602534 http://dx.doi.org/10.1042/BSR20200507 Text en © 2020 The Author(s). https://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).
spellingShingle Bioinformatics
Liang, Weiwei
Sun, FangFang
Weighted gene co-expression network analysis to define pivotal modules and genes in diabetic heart failure
title Weighted gene co-expression network analysis to define pivotal modules and genes in diabetic heart failure
title_full Weighted gene co-expression network analysis to define pivotal modules and genes in diabetic heart failure
title_fullStr Weighted gene co-expression network analysis to define pivotal modules and genes in diabetic heart failure
title_full_unstemmed Weighted gene co-expression network analysis to define pivotal modules and genes in diabetic heart failure
title_short Weighted gene co-expression network analysis to define pivotal modules and genes in diabetic heart failure
title_sort weighted gene co-expression network analysis to define pivotal modules and genes in diabetic heart failure
topic Bioinformatics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7340867/
https://www.ncbi.nlm.nih.gov/pubmed/32602534
http://dx.doi.org/10.1042/BSR20200507
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