Identification of Crucial Genes and Pathways in Human Arrhythmogenic Right Ventricular Cardiomyopathy by Coexpression Analysis

Abstract

As one common disease causing young people to die suddenly due to cardiac arrest, arrhythmogenic right ventricular cardiomyopathy (ARVC) is a disorder of heart muscle whose progression covers one complicated gene interaction network that influence the diagnosis and prognosis of it. In our research, differentially expressed genes (DEGs) were screened, and we established a weighted gene coexpression network analysis (WGCNA) and gene set net correlations analysis (GSNCA) for identifying crucial genes as well as pathways related to ARVC pathogenic mechanism (n = 12). In the research, the results demonstrated that there were 619 DEGs in total between non-failing donor myocardial samples and ARVC tissues (FDR < 0.05). WGCNA analysis identified the two gene modules (brown and turquoise) as being most significantly associated with ARVC state. Then the ARVC-related four key biological pathways (cytokine–cytokine receptor interaction, chemokine signaling pathway, neuroactive ligand receptor interaction, and JAK-STAT signaling pathway) and four hub genes (CXCL2, TNFRSF11B, LIFR, and C5AR1) in ARVC samples were further identified by GSNCA method. Finally, we used t-test and receiver operating characteristic (ROC) curves for validating hub genes, results showed significant differences in t-test and their AUC areas all greater than 0.8. Together, these results revealed that the new four hub genes as well as key pathways that might be involved into ARVC diagnosis. Even though further experimental validation is required for the implication by association, our findings demonstrate that the computational methods based on systems biology might complement the traditional gene-wide approaches, as such, might offer a new insight in therapeutic intervention within rare diseases of people like ARVC.

Proteomic and metabolomic characterization of cardiac tissue in acute myocardial ischemia injury rats

“…In addition, researchers have reported that the cardio protection effects of sevoflurane is associated with neuroactive ligandreceptor interaction in patients undergoing coronary artery bypass graft surgery [45]. Another study confirmed that neuroactive ligand-receptor interaction was closely related to human arrhythmogenic right ventricular cardiomyopathy [46]. Although the correlation of neuroactive ligand-receptor interaction in cardiovascular diseases has not been reported, this pathway may be a new mechanism in MI for future studies to investigate.…”

Crosstalk between coagulation and complement activation promotes cardiac dysfunction in arrhythmogenic right ventricular cardiomyopathy

“…By performing deep-proteome analyses of explanted hearts from patients with end-stage ARVC, we previously found that several complement system components, including factors C3, C6, C7, C8, and C9, are significantly upregulated in both ventricles 18 . Moreover, using weighted gene co-expression network analysis of patient samples, Chen et al recently found that the C5aR1 gene encoding complement receptor C5aR1 is one of four crucial hub genes in ARVC 19 . These two studies support our previous findings in Des -/- mice, indicating that activation of the complement system may play an important role in the pathophysiology of ARVC via a currently unknown mechanism.…”

Network-Based Approach to Identify the Antiproliferative Mechanisms of Bruceine D in Breast Cancer From the Cancer Genome Atlas

“…In addition, the w-values of three key genes above are increased in BRCA samples, indicating their regulatory roles in breast cancer samples and their loss in the control samples (21). Although the w-values of the three genes was decreased in control samples, these genes were still close to each other in structure of MST2 in control samples, this suggests that correlation of them with other genes was not completely lost (21). Additionally, to further find the intervention biological processes of BD, we also performed functional enrichment analysis.…”

“…It hinted regulatory changes of the pathway when hub genes in a pathway were different between two conditions. The colors of nodes represent weight factor (w)'s value distributed to all genes for suggesting the mean correlation with any other gene in the gene set co-expression (21). In this paper, it is worth noting that pathways only with 10 ≤ n ≤500 where n represents the number of genes were kept.…”

“…In this paper, it is worth noting that pathways only with 10 ≤ n ≤500 where n represents the number of genes were kept. Then, using structure of minimum spanning tree-2 (MST2), the most highly correlated pathways were distinguished (21). In this study, the pathway gene sets were used in C2 collection (curated gene sets) from Molecular Signatures Database (MSigDB).…”