Abstract

BackgroundSalt sensitivity of blood pressure (SSBP) is an independent risk factor for cardiovascular disease. The pathogenic mechanisms of SSBP are still uncertain. This study aimed to construct the co-regulatory network of SSBP and data mining strategy based on the competitive endogenous RNA (ceRNA) theory.MethodsLncRNA and mRNA microarray was performed to screen for candidate RNAs. Four criteria were used to select the potential differently expressed RNAs. The weighted correlation network analysis (WGCNA) package of R software and target miRNA and mRNA prediction online databases were used to construct the ceRNA co-regulatory network and discover the pathways related to SSBP. Gene ontology enrichment, gene set enrichment analysis (GSEA) and KEGG pathway analysis were performed to explore the functions of hub genes in networks.ResultsThere were 274 lncRNAs and 36 mRNAs that differently expressed between salt-sensitive and salt-resistant groups (P < 0.05). Using WGCNA analysis, two modules were identified (blue and turquoise). The blue module had a positive relationship with salt-sensitivity (R = 0.7, P < 0.01), high-density lipoprotein (HDL) (R = 0.53, P = 0.02), and total cholesterol (TC) (R = 0.55, P = 0.01). The turquoise module was positively related with triglyceride (TG) (R = 0.8, P < 0.01) and low-density lipoprotein (LDL) (R = 0.54, P = 0.01). Furthermore, 84 ceRNA loops were identified and one loop may be of great importance for involving in pathogenesis of SSBP. KEGG analysis showed that differently expressed mRNAs were mostly enriched in the SSBP-related pathways. However, the enrichment results of GSEA were mainly focused on basic physical metabolic processes.ConclusionThe microarray data mining process based on WGCNA co-expression analysis had identified 84 ceRNA loops that closely related with known SSBP pathogenesis. The results of our study provide implications for further understanding of the pathogenesis of SSBP and facilitate the precise diagnosis and therapeutics.

Highlights

  • Salt sensitivity of blood pressure (SSBP), first proposed by Kawasaki in 1978 (Kawasaki et al, 1978), is defined as the blood pressure of some people exhibiting changes parallel to changes in salt intake (Elijovich et al, 2016)

  • The microarray data mining process based on weighted correlation network analysis (WGCNA) co-expression analysis had identified 84 competitive endogenous RNA (ceRNA) loops that closely related with known SSBP pathogenesis

  • There was no significant difference in gender, age, total cholesterol (TC), high-density lipoprotein (HDL), low-density lipoprotein (LDL), or GLU between groups (P > 0.05) (Supplementary Table 1)

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Summary

Introduction

Salt sensitivity of blood pressure (SSBP), first proposed by Kawasaki in 1978 (Kawasaki et al, 1978), is defined as the blood pressure of some people exhibiting changes parallel to changes in salt intake (Elijovich et al, 2016). It is important to elucidate the ceRNA co-regulatory of SSBP with bioinformatic analysis and data mining, which could construct the systematic regulatory network and explore the interactive relationship of different biomarkers. This study aimed to construct the co-regulatory network of SSBP and data mining strategy based on the competitive endogenous RNA (ceRNA) theory. LncRNA and mRNA microarray was performed to screen for candidate RNAs. Four criteria were used to select the potential differently expressed RNAs. The weighted correlation network analysis (WGCNA) package of R software and target miRNA and mRNA prediction online databases were used to construct the ceRNA co-regulatory network and discover the pathways related to SSBP. KEGG analysis showed that differently expressed mRNAs were mostly enriched in the SSBP-related pathways. The enrichment results of GSEA were mainly focused on basic physical metabolic processes

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