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

Ann Transl Med. 2020 Mar;8(5):181. doi: 10.21037/atm.2020.01.94.

Abstract

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.

Keywords: Liraglutide; bioinformatics analysis; differentially expressed genes (DEGs); microarray; network modules.