Integrating KCNH2 Variant-Specific Features and Heterozygote Phenotypes to Estimate Long QT Penetrance

整合 KCNH2 变体特异性特征和杂合子表型来估计长 QT 外显率

• 批准号: 10343134
• 负责人: Brett M Kroncke
• 金额: $ 59.67万
• 依托单位: VANDERBILT UNIVERSITY MEDICAL CENTER
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-02-01 至 2027-01-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10343134
• 关键词: Address; All of Us Research Program; American; Arrhythmia; Autopsy; Bayesian Modeling; Benchmarking; Benign; Biological Assay; Cardiac; Cardiac Myocytes; Cell membrane; Cessation of life; Classification; Clinical; Code; Codon Nucleotides; Communities; Coupled; Data; Data Collection; Diagnosis; Diagnostic tests; Disease; Disease model; Electrocardiogram; Electronic Medical Records and Genomics Network; Electrophysiology (science); Etiology; Event; Foundations; Future; Generations; Genes; Genetic; Genome; Genomic medicine; Genomics; Genotype; Heterozygote; In Vitro; Incidence; Individual; Inherited; International; Ion Channel; Japan; Knowledge; Life; Location; Long QT Syndrome; Medical; Medical Genetics; Methods; Mutagenesis; Pathogenesis; Pathogenicity; Patients; Penetrance; Performance; Pharmaceutical Preparations; Phenotype; Population; Postpartum Period; Potassium Channel; Predictive Value; Probability; Procedures; Proteome; Publishing; Research Proposals; Resolution; Risk; Role; Sudden Death; Sudden infant death syndrome; Syndrome; Technology; Testing; Training; Validation; Variant; Vision; Woman; biobank; clinical phenotype; cohort; cost; data standards; disorder prevention; drug withdrawal; exome; exome sequencing; genetic variant; genome sequencing; heuristics; in silico; insight; interest; medical schools; novel; novel diagnostics; patch clamp; predictive modeling; predictive test; prospective; protein structure; rare variant; risk stratification; risk variant; segregation; sudden cardiac death; trafficking; variant of unknown significance

PROJECT SUMMARY/ABSTRACT Sequencing an individual’s genome now costs less than many routine medical procedures. A resulting vision is that everyone will have their genome sequenced early in life to enable individualized medical advice about disease prevention and drug selection. A major concern with this vision, however, is proper interpretation of the overwhelming volume of discovered novel and rare variants. In other contexts, a new diagnostic test can be benchmarked and validated in studies that compare large populations with and without a disorder to determine the predictive value of a positive result. In the genetic sequencing context, however, a positive test for most variants cannot be applied to enough heterozygous individuals for a definitive association with disease. Pathogenic variants in KCNH2 (a.k.a. hERG, a cardiac potassium channel gene critical for cardiomyocyte repolarization) can cause sudden cardiac death in the young and can predispose carriers to drug-induced arrhythmias. Genetic variants in KCNH2 are responsible for ~ 6% of autopsy-negative sudden unexplained death in the young and ~ 1% of sudden infant death syndrome cases. Additionally, among heterozygous carriers of variants in KCNH2, women are at greater overall risk of a severe event (including sudden cardiac death) which is increased in the postpartum period. Since most disease-associated variants in KCNH2 are rare, full exome sequencing has the potential to identify those individuals at greater risk early in life before any phenotype manifests. However, even among heterozygous carriers of KCNH2 variants definitively associated with disease, not all develop the same phenotype. To address the challenge of variant interpretation, the American College of Medical Genetics and Genomics suggests criteria to incorporate variant population, functional, computational, and segregation data using several described heuristics. Our foundational hypothesis is that clinically meaningful knowledge is lost in the compression of these variant-specific data to a dichotomous classification. To investigate this hypothesis, we will generate in vitro data for all missense variants in KCNH2 prospectively, build a prediction model of disease penetrance, and validate resulting predictions against the incidence of arrhythmias and cardiac events for variants observed in the Electronic Medical Records and Genomics Network (eMERGE), a Leducq Transatlantic Network, and the UK Biobank.

项目概要/摘要 现在，对个人基因组进行测序的成本低于许多常规医疗程序。 每个人都将在生命早期进行基因组测序，以便针对以下问题提供个性化的医疗建议 然而，这一愿景的一个主要问题是对这一愿景的正确解释。 在其他情况下，新的诊断测试可能会发现大量的新奇和罕见变异。 在比较大量患有和不患有疾病的人群的研究中进行基准测试和验证，以确定 然而，在基因测序背景下，阳性结果的预测价值。 变异不能应用于足够多的杂合个体来确定与疾病的关联。 KCNH2（又名 hERG，一种对心肌细胞至关重要的心脏钾通道基因）的致病性变异 复极）可导致年轻人心源性猝死，并使携带者易患药物诱发的心源性猝死。 KCNH2 的基因变异导致约 6% 的尸检阴性突发原因不明的心律失常。 年轻人死亡，约 1% 的婴儿猝死综合症病例。 如果携带 KCNH2 变异，女性发生严重事件（包括突发心脏病）的总体风险更大 死亡），这种情况在产后会增加，因为 KCNH2 中大多数与疾病相关的变异都是 罕见的全外显子组测序有可能在生命早期识别出那些面临更大风险的个体。 然而，即使在 KCNH2 变异的杂合携带者中，也存在明确的相关性。 患有疾病时，并非所有人都会产生相同的表型。 为了应对变异解释的挑战，美国医学遗传学和基因组学学院 提出了整合变异群体、功能、计算和分离数据的标准 我们的一些基本假设是，具有临床意义的知识丢失了。 将这些特定于变体的数据压缩为二分分类来研究这一点。 假设，我们将前瞻性地生成 KCNH2 中所有错义变异的体外数据，建立预测 疾病外显率模型，并验证对心律失常发生率的预测 电子病历和基因组学网络 (eMERGE) 中观察到的变异的心脏事件 Leducq 跨大西洋网络和英国生物银行。