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Weighted Co-Expression Network Analysis Identifies RNF181 as a Causal Gene of Coronary Artery Disease

Background: Coronary artery disease (CAD) exerts a global challenge to public health. Genetic heritability is one of the most vital contributing factors in the pathophysiology of CAD. Co-expression network analysis is an applicable and robust method for the interpretation of biological interaction f...

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Autores principales: Dang, Ruoyu, Qu, Bojian, Guo, Kaimin, Zhou, Shuiping, Sun, He, Wang, Wenjia, Han, Jihong, Feng, Ke, Lin, Jianping, Hu, Yunhui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8867041/
https://www.ncbi.nlm.nih.gov/pubmed/35222523
http://dx.doi.org/10.3389/fgene.2021.818813
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author Dang, Ruoyu
Qu, Bojian
Guo, Kaimin
Zhou, Shuiping
Sun, He
Wang, Wenjia
Han, Jihong
Feng, Ke
Lin, Jianping
Hu, Yunhui
author_facet Dang, Ruoyu
Qu, Bojian
Guo, Kaimin
Zhou, Shuiping
Sun, He
Wang, Wenjia
Han, Jihong
Feng, Ke
Lin, Jianping
Hu, Yunhui
author_sort Dang, Ruoyu
collection PubMed
description Background: Coronary artery disease (CAD) exerts a global challenge to public health. Genetic heritability is one of the most vital contributing factors in the pathophysiology of CAD. Co-expression network analysis is an applicable and robust method for the interpretation of biological interaction from microarray data. Previous CAD studies have focused on peripheral blood samples since the processes of CAD may vary from tissue to blood. It is therefore necessary to find biomarkers for CAD in heart tissues; their association also requires further illustration. Materials and Methods: To filter for causal genes, an analysis of microarray expression profiles, GSE12504 and GSE22253, was performed with weighted gene co-expression network analysis (WGCNA). Co-expression modules were constructed after batch effect removal and data normalization. The results showed that 7 co-expression modules with 8,525 genes and 1,210 differentially expressed genes (DEGs) were identified. Furthermore, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted. Four major pathways in CAD tissue and hub genes were addressed in the Hybrid Mouse Diversity Panel (HMDP) and Human Protein Atlas (HPA), and isoproterenol (ISO)/doxycycline (DOX)-induced heart toxicity models were used to validate the hub genes. Lastly, the hub genes and risk variants were verified in the CAD cohort and in genome-wide association studies (GWAS). Results: The results showed that RNF181 and eight other hub genes are perturbed during CAD in heart tissues. Additionally, the expression of RNF181 was validated using RT-PCR and immunohistochemistry (IHC) staining in two cardiotoxicity mouse models. The association was further verified in the CAD patient cohort and in GWAS. Conclusion: Our findings illustrated for the first time that the E3 ubiquitination ligase protein RNF181 may serve as a potential biomarker in CAD, but further in vivo validation is warranted.
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spelling pubmed-88670412022-02-25 Weighted Co-Expression Network Analysis Identifies RNF181 as a Causal Gene of Coronary Artery Disease Dang, Ruoyu Qu, Bojian Guo, Kaimin Zhou, Shuiping Sun, He Wang, Wenjia Han, Jihong Feng, Ke Lin, Jianping Hu, Yunhui Front Genet Genetics Background: Coronary artery disease (CAD) exerts a global challenge to public health. Genetic heritability is one of the most vital contributing factors in the pathophysiology of CAD. Co-expression network analysis is an applicable and robust method for the interpretation of biological interaction from microarray data. Previous CAD studies have focused on peripheral blood samples since the processes of CAD may vary from tissue to blood. It is therefore necessary to find biomarkers for CAD in heart tissues; their association also requires further illustration. Materials and Methods: To filter for causal genes, an analysis of microarray expression profiles, GSE12504 and GSE22253, was performed with weighted gene co-expression network analysis (WGCNA). Co-expression modules were constructed after batch effect removal and data normalization. The results showed that 7 co-expression modules with 8,525 genes and 1,210 differentially expressed genes (DEGs) were identified. Furthermore, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted. Four major pathways in CAD tissue and hub genes were addressed in the Hybrid Mouse Diversity Panel (HMDP) and Human Protein Atlas (HPA), and isoproterenol (ISO)/doxycycline (DOX)-induced heart toxicity models were used to validate the hub genes. Lastly, the hub genes and risk variants were verified in the CAD cohort and in genome-wide association studies (GWAS). Results: The results showed that RNF181 and eight other hub genes are perturbed during CAD in heart tissues. Additionally, the expression of RNF181 was validated using RT-PCR and immunohistochemistry (IHC) staining in two cardiotoxicity mouse models. The association was further verified in the CAD patient cohort and in GWAS. Conclusion: Our findings illustrated for the first time that the E3 ubiquitination ligase protein RNF181 may serve as a potential biomarker in CAD, but further in vivo validation is warranted. Frontiers Media S.A. 2022-02-10 /pmc/articles/PMC8867041/ /pubmed/35222523 http://dx.doi.org/10.3389/fgene.2021.818813 Text en Copyright © 2022 Dang, Qu, Guo, Zhou, Sun, Wang, Han, Feng, Lin and Hu. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Genetics
Dang, Ruoyu
Qu, Bojian
Guo, Kaimin
Zhou, Shuiping
Sun, He
Wang, Wenjia
Han, Jihong
Feng, Ke
Lin, Jianping
Hu, Yunhui
Weighted Co-Expression Network Analysis Identifies RNF181 as a Causal Gene of Coronary Artery Disease
title Weighted Co-Expression Network Analysis Identifies RNF181 as a Causal Gene of Coronary Artery Disease
title_full Weighted Co-Expression Network Analysis Identifies RNF181 as a Causal Gene of Coronary Artery Disease
title_fullStr Weighted Co-Expression Network Analysis Identifies RNF181 as a Causal Gene of Coronary Artery Disease
title_full_unstemmed Weighted Co-Expression Network Analysis Identifies RNF181 as a Causal Gene of Coronary Artery Disease
title_short Weighted Co-Expression Network Analysis Identifies RNF181 as a Causal Gene of Coronary Artery Disease
title_sort weighted co-expression network analysis identifies rnf181 as a causal gene of coronary artery disease
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8867041/
https://www.ncbi.nlm.nih.gov/pubmed/35222523
http://dx.doi.org/10.3389/fgene.2021.818813
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