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Deciphering the genetic architecture of atrial fibrillation offers insights into disease prediction, pathophysiology and downstream sequelae
AIMS: The study aimed to discover novel genetic loci for atrial fibrillation (AF), explore the shared genetic etiologies between AF and other cardiovascular and cardiometabolic traits, and uncover AF pathogenesis using Mendelian randomization analysis. METHODS AND RESULTS: We conducted a genome-wide...
Autores principales: | , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cold Spring Harbor Laboratory
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10402218/ https://www.ncbi.nlm.nih.gov/pubmed/37546828 http://dx.doi.org/10.1101/2023.07.20.23292938 |
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author | Yuan, Shuai Li, Yuying Wang, Lijuan Xu, Fengzhe Chen, Jie Levin, Michael G Xiong, Ying Voight, Benjamin F. Damrauer, Scott M Gill, Dipender Burgess, Stephen Åkesson, Agneta Michaëlsson, Karl Li, Xue Shen, Xia Larsson, Susanna C. |
author_facet | Yuan, Shuai Li, Yuying Wang, Lijuan Xu, Fengzhe Chen, Jie Levin, Michael G Xiong, Ying Voight, Benjamin F. Damrauer, Scott M Gill, Dipender Burgess, Stephen Åkesson, Agneta Michaëlsson, Karl Li, Xue Shen, Xia Larsson, Susanna C. |
author_sort | Yuan, Shuai |
collection | PubMed |
description | AIMS: The study aimed to discover novel genetic loci for atrial fibrillation (AF), explore the shared genetic etiologies between AF and other cardiovascular and cardiometabolic traits, and uncover AF pathogenesis using Mendelian randomization analysis. METHODS AND RESULTS: We conducted a genome-wide association study meta-analysis including 109,787 AF cases and 1,165,920 controls of European ancestry and identified 215 loci, among which 91 were novel. We performed Genomic Structural Equation Modeling analysis between AF and four cardiovascular comorbidities (coronary artery disease, ischemic stroke, heart failure, and vneous thromboembolism) and found 189 loci shared across these diseases as well as a universal genetic locus shared by atherosclerotic outcomes (i.e., rs1537373 near CDKN2B). Three genetic loci (rs10740129 near JMJD1C, rs2370982 near NRXN3, and rs9931494 near FTO) were associated with AF and cardiometabolic traits. A polygenic risk score derived from this genome-wide meta-analysis was associated with AF risk (odds ratio 2.36, 95% confidence interval 2.31–2.41 per standard deviation increase) in the UK biobank. This score, combined with age, sex, and basic clinical features, predicted AF risk (AUC 0.784, 95% CI 0.781–0.787) in Europeans. Phenome-wide association analysis of the polygenic risk score identified many AF-related comorbidities of the circulatory, endocrine, and respiratory systems. Phenome-wide and multi-omic Mendelian randomization analyses identified associations of blood lipids and pressure, diabetes, insomnia, obesity, short sleep, and smoking, 27 blood proteins, one gut microbe (genus.Catenibacterium), and 11 blood metabolites with risk to AF. CONCLUSIONS: This genome-wide association study and trans-omic Mendelian randomization analysis provides insights into disease risk prediction, pathophysiology and downstream sequelae. |
format | Online Article Text |
id | pubmed-10402218 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Cold Spring Harbor Laboratory |
record_format | MEDLINE/PubMed |
spelling | pubmed-104022182023-08-05 Deciphering the genetic architecture of atrial fibrillation offers insights into disease prediction, pathophysiology and downstream sequelae Yuan, Shuai Li, Yuying Wang, Lijuan Xu, Fengzhe Chen, Jie Levin, Michael G Xiong, Ying Voight, Benjamin F. Damrauer, Scott M Gill, Dipender Burgess, Stephen Åkesson, Agneta Michaëlsson, Karl Li, Xue Shen, Xia Larsson, Susanna C. medRxiv Article AIMS: The study aimed to discover novel genetic loci for atrial fibrillation (AF), explore the shared genetic etiologies between AF and other cardiovascular and cardiometabolic traits, and uncover AF pathogenesis using Mendelian randomization analysis. METHODS AND RESULTS: We conducted a genome-wide association study meta-analysis including 109,787 AF cases and 1,165,920 controls of European ancestry and identified 215 loci, among which 91 were novel. We performed Genomic Structural Equation Modeling analysis between AF and four cardiovascular comorbidities (coronary artery disease, ischemic stroke, heart failure, and vneous thromboembolism) and found 189 loci shared across these diseases as well as a universal genetic locus shared by atherosclerotic outcomes (i.e., rs1537373 near CDKN2B). Three genetic loci (rs10740129 near JMJD1C, rs2370982 near NRXN3, and rs9931494 near FTO) were associated with AF and cardiometabolic traits. A polygenic risk score derived from this genome-wide meta-analysis was associated with AF risk (odds ratio 2.36, 95% confidence interval 2.31–2.41 per standard deviation increase) in the UK biobank. This score, combined with age, sex, and basic clinical features, predicted AF risk (AUC 0.784, 95% CI 0.781–0.787) in Europeans. Phenome-wide association analysis of the polygenic risk score identified many AF-related comorbidities of the circulatory, endocrine, and respiratory systems. Phenome-wide and multi-omic Mendelian randomization analyses identified associations of blood lipids and pressure, diabetes, insomnia, obesity, short sleep, and smoking, 27 blood proteins, one gut microbe (genus.Catenibacterium), and 11 blood metabolites with risk to AF. CONCLUSIONS: This genome-wide association study and trans-omic Mendelian randomization analysis provides insights into disease risk prediction, pathophysiology and downstream sequelae. Cold Spring Harbor Laboratory 2023-07-25 /pmc/articles/PMC10402218/ /pubmed/37546828 http://dx.doi.org/10.1101/2023.07.20.23292938 Text en https://creativecommons.org/licenses/by-nc-nd/4.0/This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which allows reusers to copy and distribute the material in any medium or format in unadapted form only, for noncommercial purposes only, and only so long as attribution is given to the creator. |
spellingShingle | Article Yuan, Shuai Li, Yuying Wang, Lijuan Xu, Fengzhe Chen, Jie Levin, Michael G Xiong, Ying Voight, Benjamin F. Damrauer, Scott M Gill, Dipender Burgess, Stephen Åkesson, Agneta Michaëlsson, Karl Li, Xue Shen, Xia Larsson, Susanna C. Deciphering the genetic architecture of atrial fibrillation offers insights into disease prediction, pathophysiology and downstream sequelae |
title | Deciphering the genetic architecture of atrial fibrillation offers insights into disease prediction, pathophysiology and downstream sequelae |
title_full | Deciphering the genetic architecture of atrial fibrillation offers insights into disease prediction, pathophysiology and downstream sequelae |
title_fullStr | Deciphering the genetic architecture of atrial fibrillation offers insights into disease prediction, pathophysiology and downstream sequelae |
title_full_unstemmed | Deciphering the genetic architecture of atrial fibrillation offers insights into disease prediction, pathophysiology and downstream sequelae |
title_short | Deciphering the genetic architecture of atrial fibrillation offers insights into disease prediction, pathophysiology and downstream sequelae |
title_sort | deciphering the genetic architecture of atrial fibrillation offers insights into disease prediction, pathophysiology and downstream sequelae |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10402218/ https://www.ncbi.nlm.nih.gov/pubmed/37546828 http://dx.doi.org/10.1101/2023.07.20.23292938 |
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