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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

基本信息

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
项目类别：
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

项目摘要

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.

项目概要候选人。 Akl Fahed，医学博士、公共卫生硕士，是内科、心脏病学和公共卫生领域的委员会认证医师马萨诸塞州综合医院 (MGH) 的工作人员进行介入心脏病学。他也是以下领域的讲师哈佛医学院（HMS）医学博士和哈佛大学/麻省理工学院博德研究所博士后学者。他在每个培训阶段都有科学承诺和生产力的跟踪记录，并发表了 26 过去十年在心血管遗传学领域发表了 18 篇论文，其中 18 篇为第一作者。他现在寻求扩展之前在心脏病学和人类遗传学方面的培训，以促进专注于改善的职业生涯预防和治疗冠状动脉疾病。指导、培训活动和环境。博士。 Fahed 将在麻省总医院和博德医院在帕特里克·埃利诺 (Patrick Ellinor) 博士的指导下开展拟议的工作。心血管遗传学领域的医师科学家和国际领导者，在以下方面拥有杰出的记录导师和 Pradeep Natarajan 博士（一位在冠状动脉疾病遗传学方面具有专业知识的医师科学家）和预防。该指导团队将得到高度敬业且卓有成就的咨询顾问的补充博士委员会。彼得·克拉夫特和海蒂·雷姆。正式的课程作业将增强多学科的能力体验式学习努力获得计算生物学、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对危险因素的治疗有所改善。基因组风险为早期识别和预防提供了机会在风险因素出现之前进行有针对性的干预，但其使用存在两个主要障碍：1）没有结合基因组和非基因组因素来预测 CAD 绝对风险的单一模型，以及 2) 现有的基因组风险预测在非欧洲血统中表现不佳。为了解决这些知识差距，PI 将首先开发并验证结合单基因、多基因和体细胞的 CAD 基因组风险模型使用超过 460,000 名欧洲血统个体的数据进行变异。其次，他将开发并验证 CAD 综合风险模型结合了基因组和非基因组（血压、胆固醇、血液糖、运动、体重、饮食和吸烟）是欧洲血统个体的风险驱动因素。第三，他会优化该模型针对非洲、南亚、东亚和西班牙血统的个体，使用超过 150,000 人的数据来自多项多种族研究的个体。成功完成拟议的研究将为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有针对性的干预。此外，该提案将为 PI 提供关键培训，以促进他的工作过渡为心血管遗传学领域的独立医师研究者，生成的数据将用于作为未来 R01 应用的基础。