Integrating genomic and nongenomic risk for coronary artery disease

整合冠状动脉疾病的基因组和非基因组风险

• 批准号: 10681391
• 负责人: Akl C Fahed
• 金额: $ 16.91万
• 依托单位: MASSACHUSETTS GENERAL HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-08-10 至 2027-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10681391
• 关键词: Active Learning; Address; Adherence; Adoption; Advisory Committees; African; Age; All of Us Research Program; Asian ancestry; Attenuated; Birth; Blood Glucose; Blood Pressure; Board Certification; Cardiology; Cardiovascular system; Caregivers; Cause of Death; Cholesterol; Circulation; Clinical; Clinical Data; Complement; Complex; Computational Biology; Coronary Arteriosclerosis; Data; Data Set; Derivation procedure; Diet; East Asian; Environment; Environmental Exposure; European ancestry; Exercise; Familial Hypercholesterolemia; Foundations; Funding; Future; General Hospitals; Genes; Genetic; Genetic Diseases; Genetic Risk; Genome; Genomic medicine; Genomics; Genotype; Grant; Hand; Hematopoiesis; Hematopoietic stem cells; Heritability; Hispanic ancestry; Human Genetics; Individual; Inherited; Internal Medicine; International; Intervention; K-Series Research Career Programs; Knowledge; Life; Life Style; Massachusetts; Medicine; Mentors; Mentorship; Methods; Modeling; Morbidity - disease rate; Myocardial Infarction; Paper; Participant; Performance; Phase; Physicians; Play; Population; Populations at Risk; Positioning Attribute; Postdoctoral Fellow; Predictive Analytics; Prevention; Probability; Process; Productivity; Prospective, cohort study; Publishing; Race; Research; Research Personnel; Risk; Risk Factors; Role; Scientist; Smoking; Somatic Mutation; South Asian; Subgroup; System; Testing; Time; Training; Training Activity; United States National Institutes of Health; Validation; Variant; Weight; Work; Writing; age related; biobank; cardiovascular risk factor; career; clinical practice; clinical risk; cloud based; data access; disorder risk; experience; genomic variation; healthy lifestyle; improved; individual variation; instructor; lifestyle data; medical schools; mortality; multi-ethnic; multidisciplinary; non-genomic; pharmacologic; portability; predictive modeling; responsible research conduct; risk prediction; risk prediction model; risk stratification; skill acquisition; skills; staff intervention; treatment risk; Active Learning; Address; Adherence; Adoption; Advisory Committees; African; Age; All of Us Research Program; Asian ancestry; Attenuated; Birth; Blood Glucose; Blood Pressure; Board Certification; Cardiology; Cardiovascular system; Caregivers; Cause of Death; Cholesterol; Circulation; Clinical; Clinical Data; Complement; Complex; Computational Biology; Coronary Arteriosclerosis; Data; Data Set; Derivation procedure; Diet; East Asian; Environment; Environmental Exposure; European ancestry; Exercise; Familial Hypercholesterolemia; Foundations; Funding; Future; General Hospitals; Genes; Genetic; Genetic Diseases; Genetic Risk; Genome; Genomic medicine; Genomics; Genotype; Grant; Hand; Hematopoiesis; Hematopoietic stem cells; Heritability; Hispanic ancestry; Human Genetics; Individual; Inherited; Internal Medicine; International; Intervention; K-Series Research Career Programs; Knowledge; Life; Life Style; Massachusetts; Medicine; Mentors; Mentorship; Methods; Modeling; Morbidity - disease rate; Myocardial Infarction; Paper; Participant; Performance; Phase; Physicians; Play; Population; Populations at Risk; Positioning Attribute; Postdoctoral Fellow; Predictive Analytics; Prevention; Probability; Process; Productivity; Prospective, cohort study; Publishing; Race; Research; Research Personnel; Risk; Risk Factors; Role; Scientist; Smoking; Somatic Mutation; South Asian; Subgroup; System; Testing; Time; Training; Training Activity; United States National Institutes of Health; Validation; Variant; Weight; Work; Writing; age related; biobank; cardiovascular risk factor; career; clinical practice; clinical risk; cloud based; data access; disorder risk; experience; genomic variation; healthy lifestyle; improved; individual variation; instructor; lifestyle data; medical schools; mortality; multi-ethnic; multidisciplinary; non-genomic; pharmacologic; portability; predictive modeling; responsible research conduct; risk prediction; risk prediction model; risk stratification; skill acquisition; skills; staff intervention; treatment risk

PROJECT SUMMARY Candidate. Akl Fahed, MD, MPH is a board-certified physician in internal medicine, cardiology, and interventional cardiology on staff at the Massachusetts General Hospital (MGH). He is also instructor in medicine at Harvard Medical School (HMS) and postdoctoral scholar at the Broad Institute of Harvard/MIT. He has a track record of scientific commitment and productivity at each phase of training and has published 26 papers – including 18 as first author – in cardiovascular genetics over the past decade. He now seeks to expand upon previous training in cardiology and human genetics to catalyze a career focused on improving prevention and treatment of coronary artery disease. Mentorship, Training Activities, and Environment. Dr. Fahed will perform the proposed work at MGH and the Broad under the mentorship of Dr. Patrick Ellinor, a physician-scientist and international leader in cardiovascular genetics with an outstanding track record for mentorship and Dr. Pradeep Natarajan, a physician-scientist with expertise in coronary artery disease genetics and prevention. This mentorship team will be complemented by a highly committed and accomplished Advisory Committee of Drs. Peter Kraft and Heidi Rehm. Formal coursework will enhance a multi-disciplinary experiential learning effort to gain requisite skills in computational biology, predictive analytics, and responsible research conduct. Research. Coronary artery disease (CAD) remains a leading cause of death worldwide despite improved treatment of risk factors. Genomic risk provides opportunity for earlier recognition and targeted intervention prior to onset of risk factors, but there are two key barriers for its use: 1) There is no single model that combines genomic and nongenomic factors to predict absolute risk of CAD, and 2) existing genomic risk prediction underperforms in non-European ancestries. To address these knowledge gaps, the PI will first develop and validate a genomic risk model for CAD that combines monogenic, polygenic, and somatic variation using data on >460,000 European ancestry individuals. Second, he will develop and validate an integrated risk model for CAD that combines genomic and nongenomic (blood pressure, cholesterol, blood sugar, exercise, weight, diet, and smoking) risk drivers in European ancestry individuals. Third, he will optimize this model for individuals of African, South Asian, East Asian and Hispanic ancestries using data on >150,000 individuals from several multiethnic studies. Successful completion of the proposed studies will lay the scientific foundation for disclosing integrated risk information for CAD to individuals and their caregivers to facilitate targeted interventions. Furthermore, the proposal will provide key training of the PI to facilitate his transition to an independent physician investigator in cardiovascular genetics and the data generated will serve as the basis for a future R01 application.

项目摘要 候选人。 AKL Fahed，MD，MPH是内科，心脏病学和 马萨诸塞州综合医院（MGH）工作人员的介入心脏病学。他也是教练 哈佛医学院（HMS）和哈佛大学广告学院的博士后医学。他 在培训的每个阶段都有科学承诺和生产力的记录，并已发表26 在过去十年中，论文（包括18名作为第一作者）在心血管遗传学中。他现在试图 扩展心脏病学和人类遗传学的先前培训，以促进专注于改善的职业 预防和治疗冠状动脉疾病。指导，培训活动和环境。博士 Fahed将在MGH和Broad进行拟议的工作，并在Patrick Ellinor博士的心态下进行 身体科学家和国际心血管遗传学领导者，具有出色的往绩记录 Menorship和Pradeep Natarajan博士，具有冠状动脉疾病遗传学专业知识的身体科学家 和预防。这支高度忠诚和有成就的咨询团队将完成这个攻向工作团队 博士委员会。彼得·卡夫（Peter Kraft）和海蒂·雷姆（Heidi Rehm）。正式的课程将增强多学科 经验学习工作，以获得计算生物学，预测分析和负责任的必要技能 研究行为。研究。冠状动脉疾病（CAD）仍然是全球死亡的主要原因 尽管改善了危险因素的治疗。基因组风险为早期认可和 危险因素发作之前有针对性的干预措施，但使用了两个关键障碍：1）没有 结合了基因组和非基因组因子以预测CAD绝对风险的单个模型，2）现有 基因组风险预测在非欧洲祖先中表现不佳。为了解决这些知识差距，PI 将首先开发并验证结合单基因，多基因和躯体的CAD的基因组风险模型 使用> 460,000个欧洲血统的数据的差异。其次，他将发展并验证 结合基因组和非基因组学的CAD的综合风险模型（血压，胆固醇，血液 欧洲血统中的糖，运动，体重，饮食和吸烟）风险驱动器。第三，他将优化 这种模型使用> 150,000 来自几个多种族研究的个人。拟议研究的成功完成将是 向个人及其护理人员披露CAD综合风险信息的科学基础 促进目标干预措施。此外，该提案将提供PI的重要培训，以促进他的 过渡到心血管遗传学的独立物理研究者和生成的数据将服务 作为未来R01申请的基础。