Computational Prioritization of Coding and Non-Coding Variants in Congenital Heart Disease

先天性心脏病编码和非编码变体的计算优先级

基本信息

批准号：
10469306
负责人：
Sarah Morton
金额：
$ 17.58万
依托单位：
BOSTON CHILDREN'S HOSPITAL
依托单位国家：
美国
项目类别：
财政年份：
2021
资助国家：
美国
起止时间：
2021-09-01 至 2024-08-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10469306
关键词：
Address Affect Biological Assay Birth Cardiac Cardiac Myocytes Cardiac development Cardiovascular system Case-Control Studies Child Chromatin Chromosomes Code Collaborations Computer software Congenital Abnormality Data Databases Detection Development Developmental Gene Diagnosis Epidemiology Epigenetic Process Expenditure Fetal Heart Fostering Funding Gene Dosage Gene Expression Gene Expression Regulation Genes Genetic Genetic Diseases Genetic Risk Genetic Transcription Genome Genomic Segment Genotype Goals Haplotypes Health Heart Diseases Hi-C Histone Acetylation Hospitalization Human Human Genetics Hypoplastic Left Heart Syndrome Individual Infant Inherited Lead Letters Medical Modeling Molecular Molecular Conformation Morphology Mosaicism Mus Nucleic Acid Regulatory Sequences Outcome Parents Patients Phenotype Public Health Publishing Quantitative Trait Loci Recurrence Regulation Regulator Genes Regulatory Element Research Research Personnel Risk Role Single Nucleotide Polymorphism Structure Testing Tetralogy of Fallot Tissues Training Trans-Omics for Precision Medicine United States National Institutes of Health Untranslated RNA Variant adverse outcome base cardiogenesis causal variant cohort congenital anomaly congenital heart disorder disease phenotype disorder subtype dosage exome sequencing functional genomics genetic analysis genetic variant genome sequencing genome-wide genomic data heart disease risk histone methylation improved induced pluripotent stem cell innovation insertion/deletion mutation loss of function mortality novel proband programs relating to nervous system transcriptome sequencing transmission process whole genome

项目摘要

PROJECT SUMMARY: Congenital heart disease (CHD) is the most common anomaly at birth, affecting 1% of infants. Damaging genic variants contribute significantly to CHD risk but a likely genetic cause is identified in only 50% of patients. The genetic basis for the remaining half of CHD is unknown. The Gabriella Miller Kids First (GMKF) and TOPMed programs funded whole genome sequencing (WGS) to tests our hypothesis that variants undetected by whole exome sequencing (WES) contribute to CHD. WGS from 1813 CHD trios (affected probands and parents) provides a unique opportunity to define additional coding and noncoding variants that convey CHD risk. First, coding variants in CHD sequencing data will be comprehensively analyzed. WGS allows for improved detection of damaging coding variants that are not detected by WES, including structural variants and variants outside WES capture regions. Therefore, in Aim 1, damaging structural, mosaic and single nucleotide variants will be identified in WGS data. Novel CHD genes with a burden of damaging coding variants in CHD compared to non-CHD cohorts will be identified. Second, integration of CHD cardiac tissue gene expression with WGS data will to prioritize noncoding variants likely to impact developmental gene regulation. Aim 2a assesses the potential contribution of rare noncoding variants adjacent to cardiac expression quantitative trait loci (eQTLs) to CHD. In a parallel approach, Aim 2b will leverage 430 human cardiac developmental functional genomic annotations including those ascertained from human induced pluripotent stem cells throughout differentiation into cardiomyocytes. Human cardiac epigenetic landscape may be more successful in defining genetic mechanisms of the dominant CHD that typifies human CHD, as mouse CHD is typically a recessive phenotype. Available annotations include histone methylation and acetylation states, as well as chromatin accessibility (ATACseq), chromosome conformation (Hi-C), and RNA expression. A neural net will be trained on CHD eQTL variants to identify a subset of annotations that are able to separate eQTL from non-eQTL loci. Prioritized functional annotations will be used to calculate a per-base regulatory score across the genome (EpiCard), and score thresholds will be queried for a burden in the CHD cohort. Finally, Aim 3 addresses the role of common genetic variants in CHD risk and phenotypic variance. Leveraging the power of the trio structure, common variants over-transmitted to CHD probands will be identified. Over-transmitted loci will then be assessed for association with CHD in a case-control study in a second CHD cohort. Functional modeling of prioritized genes, variants and loci is essential; committed collaborators are already engaged in preliminary studies. Together this proposal will employ innovative computational approaches to prioritize variants and loci associated with CHD. These results will contribute towards the long-term objective of understanding the fundamental molecular basis of heart development and human genetic disease to improve diagnosis, better define risks for adverse outcomes and recurrence, and inspire novel treatments for CHD patients.

项目概要：先天性心脏病 (CHD) 是出生时最常见的异常情况，影响 1% 的婴儿。损害基因变异对冠心病风险有显着影响，但只有 50% 的患者发现了可能的遗传原因。这其余一半冠心病的遗传基础尚不清楚。加布里埃拉·米勒儿童优先 (GMKF) 和 TOPMed 计划资助全基因组测序（WGS）来检验我们的假设，即全基因组未检测到的变异外显子组测序 (WES) 有助于冠心病 (CHD)。 1813 年 CHD 三人组的全基因组测序（受影响的先证者和父母）提供了一个独特的机会来定义传达 CHD 风险的其他编码和非编码变体。首先，将全面分析CHD测序数据中的编码变异。 WGS 可以改进检测 WES 未检测到的破坏性编码变异，包括结构变异和变异 WES 捕获区域之外。因此，在目标 1 中，破坏结构、镶嵌和单核苷酸变异将在 WGS 数据中进行识别。与 CHD 中具有破坏性编码变异负担的新 CHD 基因相比将确定非 CHD 队列。二、CHD心脏组织基因表达与WGS的整合数据将优先考虑可能影响发育基因调控的非编码变异。目标 2a 评估与心脏表达数量性状基因座（eQTL）相邻的罕见非编码变异的潜在贡献冠心病。在并行方法中，Aim 2b 将利用 430 个人类心脏发育功能基因组注释包括从人类诱导多能干细胞整个分化过程中确定的注释进入心肌细胞。人类心脏表观遗传景观可能更成功地定义遗传人类先天性心脏病的典型显性先天性心脏病的机制，而小鼠先天性心脏病通常是隐性表型。可用的注释包括组蛋白甲基化和乙酰化状态，以及染色质可及性 (ATACseq)、染色体构象 (Hi-C) 和 RNA 表达。将针对 CHD eQTL 训练神经网络变体来识别能够将 eQTL 与非 eQTL 位点分开的注释子集。优先功能注释将用于计算整个基因组中每个碱基的监管分数（EpiCard），以及将查询分数阈值以了解 CHD 队列中的负担。最后，目标 3 阐述了共同的作用 CHD 风险和表型变异的遗传变异。发挥三重结构的力量，共同将鉴定过度传播给先证者的变异。然后将评估过度传播的位点在第二个 CHD 队列的病例对照研究中发现与 CHD 的关联。优先级的功能建模基因、变异和基因座至关重要；忠诚的合作者已经开始进行初步研究。该提案将共同采用创新的计算方法来确定变体和基因座的优先顺序与冠心病有关。这些结果将有助于实现了解心脏发育和人类遗传疾病的基本分子基础，以改善诊断，更好地确定不良后果和复发的风险，并激发针对先心病患者的新治疗方法。