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Identification of key candidate genes and pathways revealing the protective effect of liraglutide on diabetic cardiac muscle by integrated bioinformatics analysis

BACKGROUND: Diabetes mellitus is becoming a significant health problem with the International Diabetes Federation (IDF) expecting a startling 642 million diabetes patients by 2040. Liraglutide, a glucagon-like peptide-1 (GLP-1) analog, is reported to protect against diabetic cardiomyopathy by bindin...

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Autores principales: Dong, Ying, Yan, Shi, Li, Guo-Yan, Wang, Min-Nan, Leng, Lei, Li, Qiang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7154457/
https://www.ncbi.nlm.nih.gov/pubmed/32309328
http://dx.doi.org/10.21037/atm.2020.01.94
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author Dong, Ying
Yan, Shi
Li, Guo-Yan
Wang, Min-Nan
Leng, Lei
Li, Qiang
author_facet Dong, Ying
Yan, Shi
Li, Guo-Yan
Wang, Min-Nan
Leng, Lei
Li, Qiang
author_sort Dong, Ying
collection PubMed
description BACKGROUND: Diabetes mellitus is becoming a significant health problem with the International Diabetes Federation (IDF) expecting a startling 642 million diabetes patients by 2040. Liraglutide, a glucagon-like peptide-1 (GLP-1) analog, is reported to protect against diabetic cardiomyopathy by binding to the receptor, GLP-1R. However, the underlying mechanism has yet to be clarified. This study aimed to investigate the underlying mechanisms and the effects of liraglutide on diabetic patient’s cardiac muscles. METHODS: GSE102194 genetic expression profiles were extracted from the Gene Expression Omnibus (GEO) database. The gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) enrichment analyses were carried out. Next, Cytoscape software was used to construct the protein-protein interaction (PPI) network of the differentially expressed genes (DEGs). DEGs were mapped onto a protein-protein interaction (PPI) network that comprised 249 nodes and 776 edges. RESULTS: A total of 520 DEGs were discovered, including 159 down-regulated genes and 361 up-regulated genes. DEGs that were upregulated were notably enriched in biological processes (BP) such as muscle system process, muscle system process, muscle structure development and anatomical structure morphogenesis while DEGs that were downregulated were rich in detection of chemical stimulus and neurological system process. KEGG pathway analysis showed the up-regulated DEGs were enriched in adrenergic signaling for cardiomyocytes, dopaminergic synapse, and circadian entrainment, while the down-regulated DEGs were enriched for factory transduction in 249 of the 520 tested samples. The modular analysis identified 4 modules that participated in some pathways associated with cardiac muscle contraction, hypertrophic cardiomyopathy (HCM), and MAPK signaling pathway. CONCLUSIONS: Our data showed that Glp-1 could decrease the protein expression of p38, JNK, ERK1/2, and MARS proteins induced by high glucose (22 mM, 72 h). This study highlights the potential physiological processes that take place in diabetic cardiac muscles exposed to liraglutide. Our findings elucidated the regulatory network in diabetic cardiomyopathy and might provide a novel diagnostic and therapeutic target for diabetic cardiomyopathy.
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spelling pubmed-71544572020-04-17 Identification of key candidate genes and pathways revealing the protective effect of liraglutide on diabetic cardiac muscle by integrated bioinformatics analysis Dong, Ying Yan, Shi Li, Guo-Yan Wang, Min-Nan Leng, Lei Li, Qiang Ann Transl Med Original Article BACKGROUND: Diabetes mellitus is becoming a significant health problem with the International Diabetes Federation (IDF) expecting a startling 642 million diabetes patients by 2040. Liraglutide, a glucagon-like peptide-1 (GLP-1) analog, is reported to protect against diabetic cardiomyopathy by binding to the receptor, GLP-1R. However, the underlying mechanism has yet to be clarified. This study aimed to investigate the underlying mechanisms and the effects of liraglutide on diabetic patient’s cardiac muscles. METHODS: GSE102194 genetic expression profiles were extracted from the Gene Expression Omnibus (GEO) database. The gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) enrichment analyses were carried out. Next, Cytoscape software was used to construct the protein-protein interaction (PPI) network of the differentially expressed genes (DEGs). DEGs were mapped onto a protein-protein interaction (PPI) network that comprised 249 nodes and 776 edges. RESULTS: A total of 520 DEGs were discovered, including 159 down-regulated genes and 361 up-regulated genes. DEGs that were upregulated were notably enriched in biological processes (BP) such as muscle system process, muscle system process, muscle structure development and anatomical structure morphogenesis while DEGs that were downregulated were rich in detection of chemical stimulus and neurological system process. KEGG pathway analysis showed the up-regulated DEGs were enriched in adrenergic signaling for cardiomyocytes, dopaminergic synapse, and circadian entrainment, while the down-regulated DEGs were enriched for factory transduction in 249 of the 520 tested samples. The modular analysis identified 4 modules that participated in some pathways associated with cardiac muscle contraction, hypertrophic cardiomyopathy (HCM), and MAPK signaling pathway. CONCLUSIONS: Our data showed that Glp-1 could decrease the protein expression of p38, JNK, ERK1/2, and MARS proteins induced by high glucose (22 mM, 72 h). This study highlights the potential physiological processes that take place in diabetic cardiac muscles exposed to liraglutide. Our findings elucidated the regulatory network in diabetic cardiomyopathy and might provide a novel diagnostic and therapeutic target for diabetic cardiomyopathy. AME Publishing Company 2020-03 /pmc/articles/PMC7154457/ /pubmed/32309328 http://dx.doi.org/10.21037/atm.2020.01.94 Text en 2020 Annals of Translational Medicine. All rights reserved. https://creativecommons.org/licenses/by-nc-nd/4.0/Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) .
spellingShingle Original Article
Dong, Ying
Yan, Shi
Li, Guo-Yan
Wang, Min-Nan
Leng, Lei
Li, Qiang
Identification of key candidate genes and pathways revealing the protective effect of liraglutide on diabetic cardiac muscle by integrated bioinformatics analysis
title Identification of key candidate genes and pathways revealing the protective effect of liraglutide on diabetic cardiac muscle by integrated bioinformatics analysis
title_full Identification of key candidate genes and pathways revealing the protective effect of liraglutide on diabetic cardiac muscle by integrated bioinformatics analysis
title_fullStr Identification of key candidate genes and pathways revealing the protective effect of liraglutide on diabetic cardiac muscle by integrated bioinformatics analysis
title_full_unstemmed Identification of key candidate genes and pathways revealing the protective effect of liraglutide on diabetic cardiac muscle by integrated bioinformatics analysis
title_short Identification of key candidate genes and pathways revealing the protective effect of liraglutide on diabetic cardiac muscle by integrated bioinformatics analysis
title_sort identification of key candidate genes and pathways revealing the protective effect of liraglutide on diabetic cardiac muscle by integrated bioinformatics analysis
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7154457/
https://www.ncbi.nlm.nih.gov/pubmed/32309328
http://dx.doi.org/10.21037/atm.2020.01.94
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