Weighted correlation network bioinformatics uncovers a key molecular biosignature driving the left-sided heart failure

Jiamin Zhou,Wei Zhang,Ran Yin,Xiaoping Peng,Yunfeng Wei,Chunying Wei,Zeqi Zheng,Dasong Yi,Tong Wen,Hongmei Qi,Zhiliang Zhang,Jingtian Peng

doi:10.1186/s12920-020-00750-9

Abstract

BackgroundLeft-sided heart failure (HF) is documented as a key prognostic factor in HF. However, the relative molecular mechanisms underlying left-sided HF is unknown. The purpose of this study is to unearth significant modules, pivotal genes and candidate regulatory components governing the progression of left-sided HF by bioinformatical analysis.MethodsA total of 319 samples in GSE57345 dataset were used for weighted gene correlation network analysis (WGCNA). ClusterProfiler package in R was used to conduct functional enrichment for genes uncovered from the modules of interest. Regulatory networks of genes were built using Cytoscape while Enrichr database was used for identification of transcription factors (TFs). The MCODE plugin was used for identifying hub genes in the modules of interest and their validation was performed based on GSE1869 dataset.ResultsA total of six significant modules were identified. Notably, the blue module was confirmed as the most crucially associated with left-sided HF, ischemic heart disease (ISCH) and dilated cardiomyopathy (CMP). Functional enrichment conveyed that genes belonging to this module were mainly those driving the extracellular matrix-associated processes such as extracellular matrix structural constituent and collagen binding. A total of seven transcriptional factors, including Suppressor of Zeste 12 Protein Homolog (SUZ12) and nuclear factor erythroid 2 like 2 (NFE2L2), adrenergic receptor (AR), were identified as possible regulators of coexpression genes identified in the blue module. A total of three key genes (OGN, HTRA1 and MXRA5) were retained after validation of their prognostic value in left-sided HF. The results of functional enrichment confirmed that these key genes were primarily involved in response to transforming growth factor beta and extracellular matrix.ConclusionWe uncovered a candidate gene signature correlated with HF, ISCH and CMP in the left ventricle, which may help provide better prognosis and therapeutic decisions and in HF, ISCH and CMP patients.

Highlights

Left-sided heart failure (HF) is documented as a key prognostic factor in HF
The Eigengene adjacency heatmap showing the correlation and clustering of the modules was reported in Fig. 2b, and hinted that the six significant correlation modules were divisible into two distinct clusters based on their module eigengene (ME) correlation with a great level of independence within the modules
The results showed that the blue module was positively and pointedly associated with the HF, ischemic heart disease (ISCH), and CMP traits (Fig. 2c)

Summary

Introduction

Left-sided heart failure (HF) is documented as a key prognostic factor in HF. the relative molecular mechanisms underlying left-sided HF is unknown. Advances in molecular biology and especially the advent of latest generation sequencing platforms have allowed the accumulation of a large amount of data on the expression of genes regulating the initiation and development of various diseases [5,6,7,8]. Correct analysis of these data could help us to uncover the underlying biological functions of genes in different diseases [9, 10]. This is possible thanks to bioinformatics approaches which are available today

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