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CeRNA network analysis and functional enrichment of salt sensitivity of blood pressure by weighted-gene co-expression analysis
BACKGROUND: Salt 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 (ceR...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6746216/ https://www.ncbi.nlm.nih.gov/pubmed/31565555 http://dx.doi.org/10.7717/peerj.7534 |
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author | Cao, Han Qi, Han Liu, Zheng Peng, Wen-Juan Guo, Chun-Yue Sun, Yan-Yan Pao, Christine Xiang, Yu-Tao Zhang, Ling |
author_facet | Cao, Han Qi, Han Liu, Zheng Peng, Wen-Juan Guo, Chun-Yue Sun, Yan-Yan Pao, Christine Xiang, Yu-Tao Zhang, Ling |
author_sort | Cao, Han |
collection | PubMed |
description | BACKGROUND: Salt 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. METHODS: 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. Gene ontology enrichment, gene set enrichment analysis (GSEA) and KEGG pathway analysis were performed to explore the functions of hub genes in networks. RESULTS: There 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. CONCLUSION: The 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. |
format | Online Article Text |
id | pubmed-6746216 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | PeerJ Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-67462162019-09-27 CeRNA network analysis and functional enrichment of salt sensitivity of blood pressure by weighted-gene co-expression analysis Cao, Han Qi, Han Liu, Zheng Peng, Wen-Juan Guo, Chun-Yue Sun, Yan-Yan Pao, Christine Xiang, Yu-Tao Zhang, Ling PeerJ Bioinformatics BACKGROUND: Salt 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. METHODS: 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. Gene ontology enrichment, gene set enrichment analysis (GSEA) and KEGG pathway analysis were performed to explore the functions of hub genes in networks. RESULTS: There 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. CONCLUSION: The 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. PeerJ Inc. 2019-09-13 /pmc/articles/PMC6746216/ /pubmed/31565555 http://dx.doi.org/10.7717/peerj.7534 Text en ©2019 Cao et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited. |
spellingShingle | Bioinformatics Cao, Han Qi, Han Liu, Zheng Peng, Wen-Juan Guo, Chun-Yue Sun, Yan-Yan Pao, Christine Xiang, Yu-Tao Zhang, Ling CeRNA network analysis and functional enrichment of salt sensitivity of blood pressure by weighted-gene co-expression analysis |
title | CeRNA network analysis and functional enrichment of salt sensitivity of blood pressure by weighted-gene co-expression analysis |
title_full | CeRNA network analysis and functional enrichment of salt sensitivity of blood pressure by weighted-gene co-expression analysis |
title_fullStr | CeRNA network analysis and functional enrichment of salt sensitivity of blood pressure by weighted-gene co-expression analysis |
title_full_unstemmed | CeRNA network analysis and functional enrichment of salt sensitivity of blood pressure by weighted-gene co-expression analysis |
title_short | CeRNA network analysis and functional enrichment of salt sensitivity of blood pressure by weighted-gene co-expression analysis |
title_sort | cerna network analysis and functional enrichment of salt sensitivity of blood pressure by weighted-gene co-expression analysis |
topic | Bioinformatics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6746216/ https://www.ncbi.nlm.nih.gov/pubmed/31565555 http://dx.doi.org/10.7717/peerj.7534 |
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