Mendelian Randomization Integrating GWAS, eQTL, and mQTL Data Identified Genes Pleiotropically Associated With Atrial Fibrillation.
Mendelian Randomization Integrating GWAS, eQTL, and mQTL Data Identified Genes Pleiotropically Associated With Atrial Fibrillation.
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DOI：
10.3389/fcvm.2021.745757
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发表时间：
2021
影响因子：
3.6
通讯作者：
Liu Q
中科院分区：
文献类型：
--
作者：
Liu Y;Li B;Ma Y;Huang Y;Ouyang F;Liu Q
背景：心房颤动（AF）是最常见的心律失常。全基因组关联研究（GWAS）已经确定了100多个与AF相关的基因座，但潜在的生物学解释在很大程度上仍然未知。本研究的目的是确定基因表达和DNA甲基化（DNAm）是多效性或潜在的因果关系与AF，并整合从转录组和甲基化组的结果。研究方法：我们使用基于汇总数据的孟德尔随机化（SMR）将GWAS与表达数量性状基因座（eQTL）研究和甲基化数量性状基因座（mQTL）研究整合。引入HEIDI（非独立工具异质性）检验来检验零假设，即存在潜在关联的单一因果变量。结果：通过eQTL分析和mQTL分析分别筛选出22个和50个基因，通过SMR和HEIDI检验。其中有6个基因是重叠的。通过整合DNA m和AF之间、基因表达和AF之间以及DNA m和基因表达之间一致的SMR关联，我们确定了几种介导模型，在这些模型中，遗传变异通过改变DNA m水平对AF产生影响，DNA m水平调节功能基因的表达水平。一个例子是遗传变异-cg 18693985-CPEB 4-AF轴。结论：总之，我们的综合分析确定了多个基因和DNAm的网站，有潜在的因果关系的影响AF。我们还查明了合理的机制，其中遗传变异对AF的影响是通过DNAm转录的遗传调控介导的。进一步的实验验证是必要的，以将所识别的基因和可能的机制转化为临床实践。
Background: Atrial fibrillation (AF) is the most common arrhythmia. Genome-wide association studies (GWAS) have identified more than 100 loci associated with AF, but the underlying biological interpretation remains largely unknown. The goal of this study is to identify gene expression and DNA methylation (DNAm) that are pleiotropically or potentially causally associated with AF, and to integrate results from transcriptome and methylome. Methods: We used the summary data-based Mendelian randomization (SMR) to integrate GWAS with expression quantitative trait loci (eQTL) studies and methylation quantitative trait loci (mQTL) studies. The HEIDI (heterogeneity in dependent instruments) test was introduced to test against the null hypothesis that there is a single causal variant underlying the association. Results: We prioritized 22 genes by eQTL analysis and 50 genes by mQTL analysis that passed the SMR & HEIDI test. Among them, 6 genes were overlapped. By incorporating consistent SMR associations between DNAm and AF, between gene expression and AF, and between DNAm and gene expression, we identified several mediation models at which a genetic variant exerted an effect on AF by altering the DNAm level, which regulated the expression level of a functional gene. One example was the genetic variant-cg18693985-CPEB4-AF axis. Conclusion: In conclusion, our integrative analysis identified multiple genes and DNAm sites that had potentially causal effects on AF. We also pinpointed plausible mechanisms in which the effect of a genetic variant on AF was mediated by genetic regulation of transcription through DNAm. Further experimental validation is necessary to translate the identified genes and possible mechanisms into clinical practice.