STATISTICAL METHODS FOR GENOMIC DISSECTION OF CARDIOVASCULAR DISEASES

心血管疾病基因组解剖的统计方法

• 批准号: 9097415
• 负责人: YunJu Sung
• 金额: $ 15.76万
• 依托单位: WASHINGTON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-12 至 2019-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9097415
• 关键词: Age related macular degeneration; Alcohol consumption; Alcohols; Alleles; American; Applications Grants; Architecture; Binding; Biochemical; Blood Pressure; Candidate Disease Gene; Cardiovascular Diseases; Cholesterol; Chromatin Structure; Clinical; Clinical Research; Clinical Trials; Code; Complement; Complex; Data; Deoxyribonucleases; Detection; Diabetes Mellitus; Diastolic blood pressure; Dissection; Dyslipidemias; Elements; Encyclopedia of DNA Elements; Environment; Environmental Risk Factor; Ethnic group; European; Family; Fasting; Foundations; Framingham Heart Study; Genes; Genetic; Genetic Research; Genetic Transcription; Genome; Genomics; Goals; Haplotypes; Health; Heart; High Density Lipoprotein Cholesterol; Hypertension; Insulin; Joints; LDL Cholesterol Lipoproteins; Letters; Link; Lipids; Maps; Mentors; Morbidity - disease rate; Nature; Nucleic Acid Regulatory Sequences; Participant; Pathogenesis; Pathway interactions; Pharmaceutical Preparations; Play; Prevalence; Province; Regulation; Research; Research Personnel; Risk Factors; Role; Smoking; Statistical Methods; Statistical Models; Training Programs; Translating; Triglycerides; Untranslated RNA; Variant; abstracting; analytical method; career; career development; cell type; clinical care; clinical practice; exome; fasting glucose; gene environment interaction; genetic association; genetic variant; genome sequencing; genome wide association study; genome-wide analysis; histone modification; improved; innovation; lifestyle factors; mortality; novel; personalized medicine; programs; racial and ethnic disparities; rare variant; trait; transcription factor; whole genome

DESCRIPTION (provided by applicant): Statistical Methods for Genomic Dissection of Cardiovascular Diseases Abstract This mentored career development grant application proposes a training program to integrate Dr. Sung's previous research in statistical genetics into cardiovascular disease (CVD). Her long-term career goal is to establish herself as an independent statistician in CVD genetics research so that she can more effectively participate in multi-disciplinary research programs with clinical and translational CVD researchers and be better equipped to develop and apply statistical methods to contribute more meaningfully to the field of CVD genetics. This will be achieved through building a strong foundation in the clinical and research aspects of CVD and enhancing her understanding of genomics and whole-genome sequence data. Dr. Sung's mentoring team consists of multi-disciplinary researchers with a strong research track record. Complex cardiometabolic traits including hypertension, dyslipidemia, and diabetes contribute to CVD, the leading cause of mortality and morbidity in the industrialized world. Genome-wide association studies (GWAS) have led to many exciting discoveries. However, most GWAS discoveries have not been translated to clinical care because the functional mechanisms underlying the genetic associations remain elusive and the roles played by the environment in modulating these associations remain poorly defined. The research objective of this K25 application is to decipher the genetic and environmental architecture of cardiometabolic traits by incorporating GxE interactions and regulatory annotation information. We hypothesize that joint analysis of the environment, regulatory variants and coding variants will enhance the discovery of putative genetic variants and the functional mechanisms underlying cardiometabolic traits. To evaluate this hypothesis, we aim to identify genetic variants involving GxE interactions and identify putative functional variants by incorporating ENCODE regulation information.

描述(由申请人提供)：心血管疾病基因组解剖的统计方法摘要这份由导师指导的职业发展补助金申请提出了一个培训计划，将宋博士以前在统计遗传学方面的研究整合到心血管疾病(CVD)中。她的长期职业目标是将自己确立为心血管疾病遗传学研究领域的独立统计员，以便能够更有效地与临床和翻译心血管疾病研究人员一起参与多学科研究计划，并更好地准备开发和应用统计方法，为心血管疾病遗传学领域做出更有意义的贡献。这将通过在心血管疾病的临床和研究方面建立坚实的基础，并加强她对基因组学和全基因组序列数据的理解来实现。宋博士的指导团队由多学科研究人员组成，具有良好的研究记录。复杂的心脏代谢特征，包括高血压、血脂异常和糖尿病，导致心血管疾病，在工业化世界中，心血管疾病是死亡和发病率的主要原因。全基因组关联研究带来了许多令人振奋的发现。然而，由于遗传关联背后的功能机制仍然难以捉摸，而且环境在调节这些关联中所扮演的角色仍然不明确，因此大多数GWAS的发现还没有转化为临床治疗。这个K25应用的研究目标是通过结合GxE相互作用和调控注释信息来破译心脏代谢特征的遗传和环境结构。我们假设，对环境、调节变量和编码变量的联合分析将加强对推测的遗传变量和心脏代谢特征潜在功能机制的发现。为了评估这一假说，我们的目标是识别涉及GxE相互作用的遗传变异，并通过纳入ENCODE调节信息来识别假定的功能变异。