Congenital Heart Disease Genetics and Clinical Outcomes

先天性心脏病遗传学和临床结果

• 批准号: 10226246
• 负责人: MARTINA BRUECKNER
• 金额: $ 42.69万
• 依托单位: YALE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-30 至 2025-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10226246
• 关键词: Address; Adult; Affect; Aneuploidy; Cardiac; Charge; Chromatin; Chromatin Remodeling Factor; Cilia; Clinical; Clinical Data; Code; Common Ventricle; Communities; Complex; Computerized Medical Record; Congenital Abnormality; Copy Number Polymorphism; Costs and Benefits; Coupled; Coupling; Data; Databases; Development; Disease Outcome; Enrollment; Evolution; Functional disorder; Gene Mutation; Genes; Genetic; Genetic Diseases; Genetic Heterogeneity; Genome; Genomics; Genotype; Goals; Heterogeneity; Human Resources; Infant; Informatics; Inherited; Internet; Introns; Link; Medical Records; Medical Societies; Molecular Abnormality; Morbidity - disease rate; Mutation; Outcome; Participant; Patient Care; Patient Recruitments; Patients; Pediatric cardiology; Phenotype; Population; Public Health; Records; Role; Societies; Structure; Survivors; Technology; Thoracic Surgeon; Untranslated RNA; Variant; Work; base; cancer risk; chromatin remodeling; clinical care; cohort; comorbidity; congenital heart disorder; cost effective; data management; data mining; de novo mutation; exome; exome sequencing; gene discovery; genetic architecture; genetic disorder diagnosis; genetic variant; genome browser; genome sequencing; genomic data; improved; novel; novel strategies; outreach; phenotypic data; proband; programs; recruit; success; targeted sequencing; whole genome

Congenital heart disease (CHD) is the most common birth defect and affects 1% of all live born infants, and genetics likely contribute to 90%. While ~90% of patients with CHD survive into adulthood, there are many comorbidities that make CHD an increasingly significant public health problem. During the first two project periods the PCGC has made significant progress in understanding the genetic architecture of CHD. The highlights of the genomics work are the identification of de-novo variants contributing to ~10% of CHD, the identification of chromatin remodeling genes contributing to 2.3% of all CHD and to a striking 28% of CHD that is associated with extracardiac and neurodevelopmental abnormalities, the identification of novel CHD genes underlying inherited CHD, and the contribution of genes involved in cilia structure and function to CHD. The other most significant finding from the PCGC genomic studies is the tremendous heterogeneity of CHD: over 440 genes contribute to CHD by a dominant inheritance mechanism alone. Combining these findings with previous data on the contribution of copy-number variants and aneuploidy identifies a likely genetic cause for ~40% of CHD. Our hypotheses are that many yet unidentified mutations affecting the genic region contribute to a significant portion of CHD, and that the specific mutations contributing to CHD impact outcomes. The two major questions addressed in this proposal are what is the genetic contribution to the “missing 55%”, and how do specific mutations impact the cardiac and non-cardiac outcomes and clinical care of patients with CHD? In the setting of large genetic heterogeneity and variable phenotypic expressivity that characterizes CHD, answers to these questions will require very large patient cohorts with genotype and phenotype data. Aim 1 will define the genetic architecture of CHD through analysis of 30,000 enrolled patients with genomic data in the combined PCGC cohort. Patients are recruited by outreach to the entire Pediatric Cardiology community along with internet-based direct patient recruiting. This will be coupled with a cost-effective tiered sequencing strategy that starts with MIPs-based targeted sequencing on all probands and progresses to whole-exome and whole- genome sequencing in MIPs-negative patients. Since the eventual goal of the PCGC program is to use genomic data to improve clinical care of CHD patients, we will need to link genomic and outcome data efficiently. Aim 2 will establish a central PCGC data mining center to directly link phenotypic data from the EMR and STS database with genomic data. We will initially focus on two outcomes that are readily available in the EMR and are associated with significant morbidity in CHD patients: the potential role of cilia mutations in progressive valve dysfunction in single-ventricle patients and the potential role of chromatin modifier gene mutations to cancer risk in adult CHD survivors. The informatics paradigms developed for this project can then be applied to investigate potential genetic contribution to a wide range of other CHD outcomes.

先天性心脏病（CHD）是最常见的出生缺陷，影响所有活产婴儿的1%， 基因可能占90%。虽然约90%的CHD患者存活至成年，但仍有许多 合并症使CHD成为日益严重的公共卫生问题。在前两个项目中， 期间，PCGC在了解CHD的遗传结构方面取得了重大进展。的 基因组学工作的亮点是鉴定了约10%的CHD的新生变异， 鉴定了2.3%的CHD和28%的CHD的染色质重塑基因， 与心外和神经发育异常有关， 潜在的遗传性CHD，以及参与纤毛结构和功能的基因对CHD的贡献。另 PCGC基因组研究中最重要的发现是CHD的巨大异质性：超过440 基因单独通过显性遗传机制促成CHD。将这些发现与以前的 关于拷贝数变异和非整倍体的贡献的数据确定了约40%的 冠心病我们的假设是，许多尚未确定的影响基因区域的突变导致了一个基因突变。 CHD的显著部分，并且导致CHD的特定突变影响结果。两大 本提案中提出的问题是，基因对“缺失的55%"的贡献是什么，以及如何贡献。 特定的突变是否会影响心脏和非心脏结局以及 冠心病？在冠心病具有较大遗传异质性和可变表型表达率的背景下， 这些问题的答案将需要具有基因型和表型数据的非常大的患者群。目标1将 通过分析30，000名入选患者的基因组数据， 联合PCGC队列。患者通过外展招募到整个儿科心脏病社区，沿着 通过互联网直接招募病人这将与具有成本效益的分层排序战略相结合 从对所有先证者进行基于MIP的靶向测序开始，发展到全外显子组和全外显子组， MIP阴性患者的基因组测序。由于PCGC计划的最终目标是使用基因组 为了改善CHD患者的临床护理，我们需要有效地将基因组和结果数据联系起来。目的2 将建立一个中央PCGC数据挖掘中心，直接链接EMR和STS数据库中的表型数据 with genomic基因data数据.我们将首先关注EMR中现成的两个结果， 与CHD患者的显著发病率相关：纤毛突变在进展性瓣膜病中的潜在作用 单心室患者的功能障碍和染色质修饰基因突变对癌症风险的潜在作用 成年CHD幸存者为该项目开发的信息学范式可以应用于调查 潜在的遗传因素对广泛的其他CHD结果的贡献。