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（CHD）是最常见的出生缺陷类型，也是导致先天性心脏病的主要原因。 出生缺陷造成的婴儿死亡率。大多数CHD被认为是由以下因素之间复杂的相互作用引起的： 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 冠心病遗传变异的深层目录虽然在查明 在与CHD相关的个体遗传变异中，胚胎发生过程中复杂的相互作用并没有 被很好地理解。在鉴定具有异质性的罕见遗传变异方面， 遗传变异、表观遗传修饰和转录变化之间的作用和调控途径 导致疾病的发展。迄今为止，CHD的病因学在很大程度上仍然未知， 疾病风险预测模型通常具有较低的临床实用性。拟议的研究旨在解决 通过利用来自多个国家的现有资源， 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盟（PCGC）和 Trans-Omics for Precision Medicine（TOPMed）CHD Biobank。我们将探讨冠心病的复杂病因 通过应用我们的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CHD风险相关的基因组区域， 遗传互作，2）检测甲基化和表达数量性状基因座并发现生物学途径 冠心病危险因素的多维预测模型 基于遗传和母亲的生活方式。这项拟议中的研究将由一个早期的新的 研究人员组成了一个研究小组，在统计遗传学方面具有互补专长， 生物信息学、因果推断、CHD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新疾病的发现- 易感基因和导致CHD的生物学途径。制定准确的战略， 遗传风险预测将为准确的孕前咨询、规范遗传学研究提供新的方向。 出生后的诊断，并告知随后的怀孕。

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.