Whole genome sequences in ethnically diverse individuals with functional assays and genome editing to characterize the biology of plasma lipids

通过功能测定和基因组编辑对不同种族个体的全基因组序列进行分析，以表征血浆脂质的生物学特征

• 批准号: 10393589
• 负责人: Pradeep Natarajan
• 金额: $ 53.28万
• 依托单位: MASSACHUSETTS GENERAL HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-05-01 至 2024-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10393589
• 关键词: Algorithms; Alleles; Architecture; Bioinformatics; Biological; Biological Assay; Biology; CRISPR/Cas technology; Cardiometabolic Disease; Cardiovascular Diagnostic Techniques; Cardiovascular Diseases; Cardiovascular system; Cause of Death; Cells; Cellular Assay; Cholesterol; Clinical; Code; Complement; Complex; Coronary heart disease; Data; Diagnosis; Diagnostic; Discrimination; Ethnic Origin; European; Evaluation; Familial Hypercholesterolemia; Gene Expression Profile; Gene Frequency; Generations; Genes; Genetic; Genetic Code; Genetic Determinism; Genetic Transcription; Genome; Genomics; Genotype; Goals; Hepatocyte; Heritability; High Density Lipoprotein Cholesterol; Human; In Vitro; Individual; Inherited; Knowledge; LDL Cholesterol Lipoproteins; Leadership; Lipids; Medical Genetics; Medicine; Methodology; Modeling; Molecular Profiling; National Heart, Lung, and Blood Institute; Nature; Open Reading Frames; Phenotype; Plasma; Population; Positioning Attribute; Prevalence; Prevention; Preventive care; Reporter; Research; Research Personnel; Risk; Risk Factors; Sample Size; Sequence Analysis; Technology; Testing; Therapeutic; Trans-Omics for Precision Medicine; Triglycerides; Untranslated RNA; Variant; Whole Blood; Work; base; cardiometabolism; cohort; ethnic difference; ethnic diversity; exome sequencing; functional genomics; genetic analysis; genetic testing; genetic variant; genome editing; genome sequencing; genomic variation; heart disease risk; hypercholesterolemia; improved; in silico; in vitro Assay; in vivo; innovation; insight; method development; novel; phenotypic data; pleiotropism; premature; prevent; programs; public health relevance; rare variant; risk prediction; success; therapeutic target; trait; transcriptomics; whole genome

PROJECT SUMMARY / ABSTRACT Coronary heart disease is the leading cause of death worldwide. Characterizing the inherited basis of plasma lipids, the strongest risk factor for coronary heart disease, has led to key biological and clinical insights. Large- scale deep-coverage whole genome sequencing is now feasible and offers the opportunity to characterize full genomic variation within a given individual. For any one individual, however, the interpretation of genomic variation is limited by 1) ethnic-specific impacts, and 2) prediction of functional impact, particularly for rare, non-coding variants. The goal of this R01 proposal is to fully characterize the inherited basis of plasma lipids through a novel `trans-omics' approach – complementing whole genome sequencing with novel statistical genetics and functional genomics. In Aim 1, we will discover novel genomic variation from ~100,000 ethnically- diverse individuals and associate with plasma lipids. We will complementarily use data-driven bioinformatic approaches to identify novel genetic regions. In Aim 2, we will improve the genomic diagnosis of familial hypercholesterolemia, characterized by severe hypercholesterolemia and marked increased risk for premature coronary heart disease. We will incorporate ethnicity, functional annotations, and pleiotropy to develop a novel polygenic model for familial hypercholesterolemia. We will jointly model the monogenic and polygenic components for risk of familial hypercholesterolemia. In Aim 3, we identify functional rare non-coding hypercholesterolemia variants with cell-based massively parallel reporter assays and CRISPR-based methods. We will further use these insights to improve power for discovering novel genes from whole genome sequence analysis. This work leverages data being generated within the NHLBI Trans-Omics for Precision Medicine (TOPMed) program. We have extensive expertise in whole genome sequence analysis, statistical genetics, functional genomics, and cardiovascular medicine. This proposal includes methodological, computational, and experimental innovations, and builds on established collaborative relationships between investigators with complementary strengths. Completion of our aims will yield novel insights to inform prevention, diagnosis, and treatments for coronary heart disease. Furthermore, we will demonstrate broad framework for trans-omics analysis to identify causally relevant genomic variants for both research and clinical genetic applications.

项目摘要/摘要 冠心病是世界范围内主要的死亡原因。表征血浆的遗传基础 血脂是冠心病的最大风险因素，它已经导致了关键的生物学和临床见解。大号- 大规模深度覆盖全基因组测序现在是可行的，并提供了充分表征 某一特定个体的基因组变异。然而，对于任何一个人来说，基因组的解释 变异受限于1)特定种族的影响，以及2)功能影响的预测，特别是对于罕见的， 非编码变体。该R01提案的目标是充分描述血浆脂类的遗传基础 通过一种新的“反式组学”方法--用新的统计学方法补充全基因组测序 遗传学和功能基因组学。在目标1中，我们将发现新的基因组变异，从大约10万个种族- 不同的个体，并与血浆脂类有关。我们将补充使用数据驱动的生物信息学 识别新基因区域的方法。在目标2中，我们将改进家族性遗传病的基因组诊断 高胆固醇血症，以严重的高胆固醇血症为特征，早产风险显著增加 冠心病。我们将结合民族性、功能注释和多效性来开发一部小说 家族性高胆固醇血症的多基因模型。我们将联合建模单基因和多基因 家族性高胆固醇血症的风险成分。在目标3中，我们确定了功能罕见的非编码 基于细胞的大规模平行报告分析和基于CRISPR的方法的高胆固醇血症变异体。 我们将进一步利用这些见解来提高从全基因组序列中发现新基因的能力 分析。这项工作利用了NHLBI Trans-Omics for Precision Medicine内产生的数据 (TOPMed)计划。我们在全基因组序列分析、统计遗传学、 功能基因组学和心血管医学。这项建议包括方法论、计算性和 试验性创新，并建立在调查人员与 优势互补。完成我们的目标将产生新的见解，为预防、诊断和 冠心病的治疗。此外，我们还将展示反式组学的广泛框架。 分析以确定因果相关的基因组变异，用于研究和临床遗传应用。