PARCC, Inserm, Université de Paris, F-75015, Paris, France (M.Y., S.K., X.J., N.B.-N.).
Bordeaux Population Health Research Center, Inserm Center U1219, University of Bordeaux, France (S.D.).
Circ Genom Precis Med. 2021 Oct;14(5):e003148. doi: 10.1161/CIRCGEN.120.003148. Epub 2021 Aug 31.
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 identified an additional risk locus on Chr1 () and 2 suggestive risk loci on chr8 () and chr19 (), all driven by common variants. Gene-based association using Multi-marker Analysis of GenoMic Annotation revealed 6 risk genes for MVP with pronounced expression levels in cardiovascular tissues, especially the heart and globally part of enriched GO terms related to cardiac development.
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.
二尖瓣脱垂（MVP）是一种常见的心脏瓣膜病，在普通人群中的发病率为 1/40。先前的全基因组关联研究已经确定了 6 个与 MVP 相关的风险位点。但这些位点仅部分解释了 MVP 的遗传风险。我们旨在通过加入英国生物库的数据来确定 MVP 的其他风险位点。
我们还纳入了来自英国生物库的 434 例 MVP 病例和 4527 例对照进行发现分析。使用 SNPTEST 进行遗传关联分析，使用 METAL 进行荟萃分析。我们使用全基因组关联研究的功能映射和注释以及基于基因和基因集的多标记分析基因组注释进行后全基因组关联研究注释。
我们发现跨组学精准医学的单核苷酸多态性（SNP）推断在次要等位基因频率低于 0.1 的较低范围内具有更好的准确性。我们的更新荟萃分析包括英国生物库研究的约 800 万个常见单核苷酸多态性（次要等位基因频率 >0.01），并在 Chr2 上复制了与 附近的关联信号，该区域是最显著的关联信号。我们在 Chr1（）上确定了另一个风险位点，在 chr8（）和 chr19（）上确定了 2 个提示性风险位点，这些都是由常见变异驱动的。使用多标记分析基因组注释的基于基因的关联揭示了 MVP 的 6 个风险基因，这些基因在心血管组织（尤其是心脏）中具有明显的表达水平，并且在心脏发育等方面富集了大量的 GO 术语。
我们使用密集的 SNP 推断覆盖范围和改进的病例对照样本报告了 MVP 的更新全基因组关联研究荟萃分析。我们描述了 MVP 的几个位点和基因，这些基因跨越了与 MVP 高度相关的生物学机制，特别是在瓣膜和心脏发育过程中。
