Genome-Wide Association Meta-Analysis Supports Genes Involved in Valve and Cardiac Development to Associate With Mitral Valve Prolapse.
association
computational biology
heart valve diseases
meta-analysis
mitral valve prolapse
Journal
Circulation. Genomic and precision medicine
ISSN: 2574-8300
Titre abrégé: Circ Genom Precis Med
Pays: United States
ID NLM: 101714113
Informations de publication
Date de publication:
10 2021
10 2021
Historique:
pubmed:
1
9
2021
medline:
15
2
2022
entrez:
31
8
2021
Statut:
ppublish
Résumé
Mitral valve prolapse (MVP) is a common cardiac valve disease, which affects 1 in 40 in the general population. Previous genome-wide association study has identified 6 risk loci for MVP. But these loci explained only partially the genetic risk for MVP. We aim to identify additional risk loci for MVP by adding data set from the UK Biobank. We also incorporated 434 MVP cases and 4527 controls from the UK Biobank for discovery analyses. Genetic association was conducted using SNPTEST and meta-analyses using METAL. We used Functional Mapping and Annotation of Genome-Wide Association Studies for post-genome-wide association study annotations and Multi-marker Analysis of GenoMic Annotation for gene-based and gene-set analyses. We found Trans-Omics for Precision Medicine imputation to perform better in terms of accuracy in the lower ranges of minor allele frequency below 0.1. Our updated meta-analysis included UK Biobank study for ≈8 million common single-nucleotide polymorphisms (minor allele frequency >0.01) and replicated the association on Chr2 as the top association signal near We report an updated meta-analysis genome-wide association study for MVP using dense imputation coverage and an improved case-control sample. We describe several loci and genes with MVP spanning biological mechanisms highly relevant to MVP, especially during valve and heart development.
Sections du résumé
BACKGROUND
Mitral valve prolapse (MVP) is a common cardiac valve disease, which affects 1 in 40 in the general population. Previous genome-wide association study has identified 6 risk loci for MVP. But these loci explained only partially the genetic risk for MVP. We aim to identify additional risk loci for MVP by adding data set from the UK Biobank.
METHODS
We also incorporated 434 MVP cases and 4527 controls from the UK Biobank for discovery analyses. Genetic association was conducted using SNPTEST and meta-analyses using METAL. We used Functional Mapping and Annotation of Genome-Wide Association Studies for post-genome-wide association study annotations and Multi-marker Analysis of GenoMic Annotation for gene-based and gene-set analyses.
RESULTS
We found Trans-Omics for Precision Medicine imputation to perform better in terms of accuracy in the lower ranges of minor allele frequency below 0.1. Our updated meta-analysis included UK Biobank study for ≈8 million common single-nucleotide polymorphisms (minor allele frequency >0.01) and replicated the association on Chr2 as the top association signal near
CONCLUSIONS
We report an updated meta-analysis genome-wide association study for MVP using dense imputation coverage and an improved case-control sample. We describe several loci and genes with MVP spanning biological mechanisms highly relevant to MVP, especially during valve and heart development.
Identifiants
pubmed: 34461747
doi: 10.1161/CIRCGEN.120.003148
pmc: PMC8530910
mid: NIHMS1730913
doi:
Types de publication
Journal Article
Meta-Analysis
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
e003148Subventions
Organisme : Medical Research Council
ID : MC_PC_17228
Pays : United Kingdom
Organisme : NHLBI NIH HHS
ID : R01 HL149696
Pays : United States
Organisme : NHLBI NIH HHS
ID : R01 HL127692
Pays : United States
Organisme : NIGMS NIH HHS
ID : P20 GM103444
Pays : United States
Organisme : NHLBI NIH HHS
ID : R01 HL131546
Pays : United States
Organisme : Medical Research Council
ID : MC_QA137853
Pays : United Kingdom
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