Identification of MYH6 as the potential gene for human ischaemic cardiomyopathy

Abstract

The present study aimed to explore the potential hub genes and pathways of ischaemic cardiomyopathy (ICM) and to investigate the possible associated mechanisms. Two microarray data sets (GSE5406 and GSE57338) were downloaded from the Gene Expression Omnibus (GEO) database. The limma package was used to analyse the differentially expressed genes (DEGs). Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment, Disease Ontology (DO) and Gene Ontology (GO) annotation analyses were performed. A protein-protein interaction (PPI) network was set up using Cytoscape software. Significant modules and hub genes were identified by the Molecular Complex Detection (MCODE) app. Then, further functional validation of hub genes in other microarrays and survival analysis were performed to judge the prognosis. A total of 1065 genes were matched, with an adjusted p < 0.05, and 17 were upregulated and 25 were downregulated with|log₂ (fold change)|≥1.2. After removing the lengthy entries, GO identified 12 items, and 8 pathways were enriched at adjusted p < 0.05 (false discovery rate, FDR set at <0.05). Three modules with a score >8 after MCODE analysis and MYH6 were ultimately identified. When validated in GSE23561, MYH6 expression was lower in patients with CAD than in healthy controls (p < 0.05). GSE60993 data suggested that MYH6 expression was also lower in AMI patients (p < 0.05). In the GSE59867 data set, MYH6 expression was lower in CAD patients than in AMI patients and lower in heart failure (HF) patients than in non-HF patients. However, there was no difference at different periods within half a year, and HF was increased when MYH6 expression was low (p < 0.05-0.01). We performed an integrated analysis and validation and found that MYH6 expression was closely related to ICM and HF. However, whether this marker can be used as a predictor in blood samples needs further experimental verification.

Keywords: functional enrichment; functional validation and prognostic analysis; gene expression omnibus; ischaemic cardiomyopathy.

FIGURE 1

Heatmaps and volcano plots for DEGs. (A) Heatmap for DEGs in GSE5406; (C) Heatmap for DEGs in GSE57338. ICM groups are in the red cluster, and healthy samples are in the green cluster. (B) Volcano plot for DEGs in GSE5406; (D) Volcano plot for DEGs in GSE57338. The two vertical lines are the 1.2‐fold change boundaries, and the horizontal line is the statistical significance boundary (adjusted p < 0.05). Items with statistical significance and upregulation are marked with red dots, and downregulated items are marked with dark blue dots in the volcano plots

FIGURE 2

Functional enrichment analyses of DEGs. The x‐axis shows the ratio of the number of genes, and the y‐axis shows the pathway terms. The ‐log10 (p‐value) of each term is coloured according to the legend. (A) Gene Ontology in GSE5406; (B) Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis in GSE5406; (C) Disease Ontology in GSE5406; (D) Gene Ontology in GSE57338; (E) Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis in GSE57338; (F) Disease Ontology in GSE57338

FIGURE 3

Removal of redundant entries for GO and KEGG analysis. GO and pathway categories were grouped according to functional themes, and the proportion of cases affected by individual pathway alterations was plotted per subgroup and across the series. (A) Gene Ontology and (B) Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses

FIGURE 4

Venn diagram for the intersection of DEGs in GSE5406 and GSE57338. The genes in the cross‐set were taken out for further analysis and validation

FIGURE 5

Protein‐protein interaction analysis. (A) Protein‐protein interaction network of the module genes. Each edge indicates the interaction between two genes. A colour scale was used to indicate the importance of protein nodes in the network; for example, dark red represents a high degree of importance, and light red represents a low degree importance. (B–D) The significant modules identified from the protein‐protein interaction network using the molecular complex detection method with a score of >8.0. MCODE_B score = 20.107, MCODE_c score = 18.280 and MCODE_D score = 8.174

FIGURE 6

Verification of MYH6 mRNA expression levels in different datasets. (A) Expression of MYH6 in different kinds of diseases in GSE23561; (B) Expression of MYH6 in ACS in GSE60993.p < 0.05 was judged to be statistically significant within the group

FIGURE 7

Verification of MYH6 mRNA expression in the GSE57338 data set. (A–C) Expression of MYH6 in different items. (D) A survival curve was drawn according to the expression level of MYH6, in which higher than the median was defined as high expression, and lower than the median was defined as low expression