Whole genome sequence interpretation for lipids to discover new genes and mechanisms for coronary artery disease

脂质的全基因组序列解释，以发现冠状动脉疾病的新基因和机制

• 批准号: 10722515
• 负责人: Satoshi Koyama
• 金额: $ 16.5万
• 依托单位: BROAD INSTITUTE, INC.
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-01 至 2025-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10722515
• 关键词: Address; Age; All of Us Research Program; Alleles; Applied Skills; Atherosclerosis; Biological Assay; Boston; Cardiology; Cardiovascular Diseases; Cause of Death; Cholesterol; Clinical; Cloud Computing; Code; Collaborations; Complex; Coronary Arteriosclerosis; Data; Data Set; Dedications; Diagnosis; Diagnostic; Diagnostic Sensitivity; Disease; Disease-Free Survival; Early Diagnosis; Early Intervention; Early treatment; Exposure to; Familial Hypercholesterolemia; Family; General Hospitals; Generations; Genes; Genetic; Genetic Research; Genetic Risk; Genetic Screening; Genomic medicine; Genomics; Genotype; Guidelines; Hand; Healthcare; Heritability; Human Genetics; Hyperlipidemia; In Vitro; Individual; Inherited; Institution; Investigation; Investments; Knowledge; LDL Cholesterol Lipoproteins; Lipids; Machine Learning; Massachusetts; Mentors; Mentorship; Methods; Modeling; Molecular Biology; Molecular Diagnosis; Mutagenesis; Mutation; National Heart, Lung, and Blood Institute; Pathogenesis; Persons; Phase; Physicians; Population; Prevention; Preventive; Principal Investigator; Recommendation; Research; Research Personnel; Resources; Risk; Risk Factors; Scientist; Statistical Methods; Technical Expertise; Therapeutic; Trans-Omics for Precision Medicine; United States Department of Veterans Affairs; United States National Institutes of Health; Untranslated RNA; Update; Variant; Veterans; biobank; causal variant; cohort; data access; data handling; diagnostic criteria; disorder prevention; exome; exome sequencing; experience; family management; genetic analysis; genetic disorder diagnosis; genetic epidemiology; genetic predictors; genetic testing; genetic variant; genome sequencing; genome-wide; high risk population; hypercholesterolemia; improved; in silico; insight; machine learning method; mutation carrier; novel; novel diagnostics; polygenic risk score; precision medicine; premature; prevent; programs; risk prediction; risk stratification; risk variant; skills; trait; translational genomics; whole genome

PROJECT SUMMARY/ABSTRACT Coronary artery disease (CAD) is one of the leading causes of death worldwide. Family hypercholesterolemia (FH) is an extreme case of inherited hypercholesterolemia and an important risk factor for CAD. FH is caused by a single mutation in known cholesterol-related genes, and carriers of these mutations are exposed to severe hypercholesterolemia and develop CAD at an early age. Early intervention has been shown to reduce the progression of atherosclerosis and prolong CAD-free survival. Therefore, early diagnosis and treatment are important in the management of FH. Current guidelines recommend genetic screening and genotype-based risk stratification for people with severe hypercholesterolemia, as well as specific therapies. However, current genetic diagnostic criteria are limited to genes/variants that have already been described. Recent investigations, including ours, suggest that the diagnostic yield of genetic testing for FH is limited (< 2% of individuals with severe hypercholesterolemia). Furthermore, only ~2% have a similarly strong polygenic contribution despite studies indicating a sizable contribution of genetics to FH. From these findings, Dr. Koyama hypothesize that undiscovered FH alleles exist and may be important for diagnosis, surveillance, and treatment. With the aim of improving genetic diagnostic yields for FH and capturing potential carriers currently undiagnosed, Dr. Koyama proposes to develop an updated diagnostic criteria of FH using the population-scale genome sequence cohorts and comprehensive variant interpretation framework. In this proposal, first, Dr. Koyama will refine the list of FH associated variants/genes by associating ultrarare coding variants in the whole exome datasets. Second, Dr. Koyama will extend the analysis to the noncoding variants which were not conferred in the current diagnostic criteria using the whole genome sequencing dataset. Finally, Dr. Koyama will integrate common and rare genetic risk stratification models to comprehensively describe the genetic risk of hyperlipidemia. This project is built on Dr. Koyama’s clinical/research skills and experiences and allows him to gain more experience in genetic research in the cardiovascular disease. Under the mentorship of primary mentor Dr. Pradeep Natarajan, the Director of Preventive Cardiology and co-mentor Dr. Patrick Ellinor, the Chief of Cardiology of Massachusetts General Hospital, Dr. Koyama will significantly benefit from rich scientific resources and collaborations at the Broad Institute of MIT and Harvard and at the Division of Cardiology at the Massachusetts General Hospital.

项目摘要/摘要 冠状动脉疾病（CAD）是全球主要的死亡原因之一。家族性高胆固醇血症 (FH)是遗传性高胆固醇血症的极端病例，也是CAD的重要危险因素。FH是由 已知胆固醇相关基因的单一突变，这些突变的携带者暴露于严重的 高胆固醇血症并在早期发展为CAD。早期干预已被证明可以减少 动脉粥样硬化的进展和延长无CAD生存期。因此，早期诊断和治疗是 在FH的管理中非常重要。 目前的指南建议对患有严重糖尿病的人进行遗传筛查和基于基因型的风险分层。 高胆固醇血症，以及特定的治疗。然而，目前的遗传诊断标准仅限于 已经描述的基因/变体。 最近的研究，包括我们的研究，表明FH基因检测的诊断率是有限的（< 2%）。 患有严重高胆固醇血症的个体）。此外，只有约2%具有类似的强多基因 尽管研究表明遗传学对FH有相当大的贡献。根据这些发现，博士。 Koyama假设存在未被发现的FH等位基因，并且可能对诊断、监测和治疗很重要。 治疗为了提高FH的遗传学诊断率和捕获潜在的携带者， 未确诊，Koyama博士建议使用人群规模制定更新的FH诊断标准 基因组序列队列和综合变异解释框架。 在该提案中，首先，Koyama博士将通过将ultrarare 编码整个外显子组数据集中的变体。其次，Koyama博士将分析扩展到非编码 在使用全基因组测序的当前诊断标准中未赋予的变体 数据集。最后，Koyama博士将整合常见和罕见遗传风险分层模型， 全面描述高脂血症的遗传风险。 这个项目是建立在小山博士的临床/研究技能和经验，并使他获得更多 心血管疾病遗传学研究经验。在初级导师Dr. Pradeep Natarajan，预防心脏病学主任和共同导师帕特里克Ellinor博士， 马萨诸塞州总医院的心脏病学，小山博士将大大受益于丰富的科学 麻省理工学院和哈佛的布罗德研究所以及 马萨诸塞州综合医院。