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Identification of Atrial Fibrillation-Associated Genes ERBB2 and MYPN Using Genome-Wide Association and Transcriptome Expression Profile Data on Left–Right Atrial Appendages

More reliable methods are needed to uncover novel biomarkers associated with atrial fibrillation (AF). Our objective is to identify significant network modules and newly AF-associated genes by integrative genetic analysis approaches. The single nucleotide polymorphisms with nominal relevance signifi...

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Autores principales: Meng, Xiangguang, Nie, Yali, Wang, Keke, Fan, Chen, Zhao, Juntao, Yuan, Yiqiang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8278573/
https://www.ncbi.nlm.nih.gov/pubmed/34276800
http://dx.doi.org/10.3389/fgene.2021.696591
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author Meng, Xiangguang
Nie, Yali
Wang, Keke
Fan, Chen
Zhao, Juntao
Yuan, Yiqiang
author_facet Meng, Xiangguang
Nie, Yali
Wang, Keke
Fan, Chen
Zhao, Juntao
Yuan, Yiqiang
author_sort Meng, Xiangguang
collection PubMed
description More reliable methods are needed to uncover novel biomarkers associated with atrial fibrillation (AF). Our objective is to identify significant network modules and newly AF-associated genes by integrative genetic analysis approaches. The single nucleotide polymorphisms with nominal relevance significance from the AF-associated genome-wide association study (GWAS) data were converted into the GWAS discovery set using ProxyGeneLD, followed by merging with significant network modules constructed by weighted gene coexpression network analysis (WGCNA) from one expression profile data set, composed of left and right atrial appendages (LAA and RAA). In LAA, two distinct network modules were identified (blue: p = 0.0076; yellow: p = 0.023). Five AF-associated biomarkers were identified (ERBB2, HERC4, MYH7, MYPN, and PBXIP1), combined with the GWAS test set. In RAA, three distinct network modules were identified and only one AF-associated gene LOXL1 was determined. Using human LAA tissues by real-time quantitative polymerase chain reaction, the differentially expressive results of ERBB2, MYH7, and MYPN were observed (p < 0.05). This study first demonstrated the feasibility of fusing GWAS with expression profile data by ProxyGeneLD and WGCNA to explore AF-associated genes. In particular, two newly identified genes ERBB2 and MYPN via this approach contribute to further understanding the occurrence and development of AF, thereby offering preliminary data for subsequent studies.
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spelling pubmed-82785732021-07-15 Identification of Atrial Fibrillation-Associated Genes ERBB2 and MYPN Using Genome-Wide Association and Transcriptome Expression Profile Data on Left–Right Atrial Appendages Meng, Xiangguang Nie, Yali Wang, Keke Fan, Chen Zhao, Juntao Yuan, Yiqiang Front Genet Genetics More reliable methods are needed to uncover novel biomarkers associated with atrial fibrillation (AF). Our objective is to identify significant network modules and newly AF-associated genes by integrative genetic analysis approaches. The single nucleotide polymorphisms with nominal relevance significance from the AF-associated genome-wide association study (GWAS) data were converted into the GWAS discovery set using ProxyGeneLD, followed by merging with significant network modules constructed by weighted gene coexpression network analysis (WGCNA) from one expression profile data set, composed of left and right atrial appendages (LAA and RAA). In LAA, two distinct network modules were identified (blue: p = 0.0076; yellow: p = 0.023). Five AF-associated biomarkers were identified (ERBB2, HERC4, MYH7, MYPN, and PBXIP1), combined with the GWAS test set. In RAA, three distinct network modules were identified and only one AF-associated gene LOXL1 was determined. Using human LAA tissues by real-time quantitative polymerase chain reaction, the differentially expressive results of ERBB2, MYH7, and MYPN were observed (p < 0.05). This study first demonstrated the feasibility of fusing GWAS with expression profile data by ProxyGeneLD and WGCNA to explore AF-associated genes. In particular, two newly identified genes ERBB2 and MYPN via this approach contribute to further understanding the occurrence and development of AF, thereby offering preliminary data for subsequent studies. Frontiers Media S.A. 2021-06-30 /pmc/articles/PMC8278573/ /pubmed/34276800 http://dx.doi.org/10.3389/fgene.2021.696591 Text en Copyright © 2021 Meng, Nie, Wang, Fan, Zhao and Yuan. 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
Meng, Xiangguang
Nie, Yali
Wang, Keke
Fan, Chen
Zhao, Juntao
Yuan, Yiqiang
Identification of Atrial Fibrillation-Associated Genes ERBB2 and MYPN Using Genome-Wide Association and Transcriptome Expression Profile Data on Left–Right Atrial Appendages
title Identification of Atrial Fibrillation-Associated Genes ERBB2 and MYPN Using Genome-Wide Association and Transcriptome Expression Profile Data on Left–Right Atrial Appendages
title_full Identification of Atrial Fibrillation-Associated Genes ERBB2 and MYPN Using Genome-Wide Association and Transcriptome Expression Profile Data on Left–Right Atrial Appendages
title_fullStr Identification of Atrial Fibrillation-Associated Genes ERBB2 and MYPN Using Genome-Wide Association and Transcriptome Expression Profile Data on Left–Right Atrial Appendages
title_full_unstemmed Identification of Atrial Fibrillation-Associated Genes ERBB2 and MYPN Using Genome-Wide Association and Transcriptome Expression Profile Data on Left–Right Atrial Appendages
title_short Identification of Atrial Fibrillation-Associated Genes ERBB2 and MYPN Using Genome-Wide Association and Transcriptome Expression Profile Data on Left–Right Atrial Appendages
title_sort identification of atrial fibrillation-associated genes erbb2 and mypn using genome-wide association and transcriptome expression profile data on left–right atrial appendages
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8278573/
https://www.ncbi.nlm.nih.gov/pubmed/34276800
http://dx.doi.org/10.3389/fgene.2021.696591
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