Random Field Methods for integrative genomic analysis and high-dimensional risk prediction of congenital heart defects

项目摘要 先天性心脏病(CHDS)是最常见的出生缺陷类型，也是 出生缺陷导致的婴儿死亡率。大多数先天性心脏病被认为是由于 母体暴露和遗传易感性。在过去的十年里，大规模的全基因组关联 已经进行了研究和全基因组测序研究，以全面调查 CHD基因变异的详细目录。尽管在身份识别方面取得了实质性进展 在与先天性心脏病相关的个体遗传变异中，胚胎发育过程中的复杂相互作用并没有 已经很好地理解了。识别具有异源基因的罕见遗传变异的成功就更少了。 遗传变异、表观遗传修饰和转录变化之间的作用及其调控途径 导致疾病的发展。到目前为止，冠心病的病因在很大程度上仍不清楚，而 疾病风险预测模型的临床实用性普遍较低。拟议的研究旨在解决 通过利用来自多个组织的现有资源，实现CHD的异质性、互动性和多组学病因研究 与CHD研究相关的联邦实体。我们将使用来自 国家出生缺陷预防研究(NBDPS)、儿科心脏基因组学联合会(PCGC)和 精准医学跨基因组学(TOPMed)CHD生物库。我们将解决冠心病的复杂病因 通过应用我们研究团队开发的新的随机场方法。计划的具体目标是：1) 在存在疾病异质性的情况下，识别和复制与冠心病风险相关的基因组区域 遗传交互作用，2)检测甲基化和表达数量性状基因座并发现生物学途径 在影响冠心病风险的多因素中，以及3)建立高维的冠心病风险预测模型 基于基因和母亲的生活方式。拟议的研究将由一个处于早期阶段的新的 他组建了一支在统计遗传学方面具有互补专业知识的研究团队， 生物信息学、因果推断、冠心病流行病学、生殖遗传学、临床心血管遗传学以及 儿科临床实践。这项研究的成功完成将导致发现新的疾病-- 导致冠心病的易感基因和生物途径。建立一个准确的战略，为 遗传风险预测将为精准产前咨询、规范遗传 在出生后进行诊断，并通知后续怀孕。

Project Summary Congenital heart defects (CHDs) are the most prevalent type of birth defects and the leading cause of infant mortality attributable to birth defects. Most CHDs are thought to result from a complex interaction between maternal exposures and genetic susceptibilities. In the past decade, large-scale genome-wide association studies and whole-genome sequencing studies have been conducted to comprehensively investigate the role of a deep catalog of genetic variants in CHDs. Although substantial progress has been made in the identification of individual genetic variants associated with CHDs, the complex interactions during embryogenesis have not been well understood. There has been even less success to identify rare genetic variants with heterogenous effect and the regulatory pathways among genetic variants, epigenetic modifications, and transcriptional changes leading to the disease development. To date, the etiology of CHDs has remained largely unknown, and the disease risk prediction models generally have low clinical utility. The proposed research aims to address the heterogeneous, interactive, and multi-omic etiology of CHDs by leveraging existing resources from multiple federal entities relevant to CHD research. We will conduct integrative genomic analysis using samples from the National Birth Defect Prevention Studies (NBDPS), the Pediatric Cardiac Genomics Consortium (PCGC) and the Trans-Omics for Precision Medicine (TOPMed) CHD Biobank. We will address the complex etiology of CHDs by applying novel random field methods developed by our research team. The planned specific aims are: 1) Identify and replicate genomic regions associated with CHD risk in the presence of disease heterogeneity and genetic interactions, 2) Detect methylation and expression quantitative trait loci and discover biological pathways among multi-omic factors contributing to CHD risk, and 3) Build a high-dimensional risk prediction model of CHDs based on genetic and maternal lifestyle profiles. The proposed research will be led by an early-stage new investigator, who has assembled a research team with complementary expertise in statistical genetics, bioinformatics, causal inference, CHD epidemiology, reproductive genetics, clinical cardiovascular genetics, and pediatric clinical practice. The successful completion of this research will lead to the discovery of novel disease- susceptible genes and biological pathways resulting in CHDs. The establishment of an accurate strategy for genetic risk prediction will provide new directions for precise preconceptional consultation, standardize genetic diagnosis after birth, and inform subsequent pregnancies.