Precision Cardiovascular Medicine for Multi-Ethnic Populations

项目摘要/摘要 该奖项将支持Arjun K.Manrai博士过渡到 独立研究员职位，连接生物医学信息学、心血管医学和人口 健康。在整个奖项过程中，Manrai博士将得到Isaac S.Kohane博士、Joseph Loscalzo博士和 约翰·P·A·约阿尼迪斯。Manrai博士研究的长期目标是改善心血管护理并减少 多民族人口之间的健康差距。实现这一目标的一个必要步骤是澄清 过去的研究和目前的临床实践之间的种族差距。Manrai博士的K01建议研究建立 直接来自于他之前在多种族人群中翻译临床基因组学的工作，包括 对不同人群(N&GT；4500万)进行大规模分析，以调查现有 不同种族病理性左心室肥厚的遗传学和临床诊断标准 组。Manrai博士将使用不同的数据集(基因组、临床和保险索赔数据 数以千万计的个人)，以澄清正常的范围-以及现有的 定义不同人群中异常分子和临床变异的标准。这项工作将使Dr。 Manrai to：(1)描述与遗传性心脏病相关的基因变异的疾病风险 肥厚型心肌病(HCM)跨越祖先不同的人群；(2)发展种族特异性 心脏形态测量的表型参考范围；以及(3)测量相关的保健 使用大规模保险索赔数据的系统影响。 除了拟议的研究，Manrai博士还将利用这一奖项来扩展他的背景 生物医学数据科学和临床基因组学，具有广泛的、动手的临床心脏病学培训和职业生涯 发展活动。具体地说，Manrai博士将：(1)参加正式的超声心动图培训课程并 获得临床心脏病学经验；(2)参加领先的心脏病学会议；(3)获得健康培训 差异和翻译研究；以及(4)促进专业发展。作为他K01职业生涯的一部分 开发活动，Manrai博士将在波士顿周围的心脏病诊所广泛工作，并探索 与欧洲和非洲的诊所开展国际临床和研究合作。 这个职业发展奖预计将使Manrai博士能够过渡到一个独立的 调查员定位并直接领导应用所获得的研究和培训的R01研究计划 在获奖期间研究更广泛的心肌疾病(遗传性心肌病 包括扩张型心肌病和致心律失常的右室心肌病)。Manrai博士的K01 拟议的研究预计将产生现有最大的多种族心脏形态和 遗传变异与左心室肥厚有关。这些信息将帮助医生、研究人员和患者 每天使用这些数据进行决策。

PROJECT SUMMARY/ABSTRACT This award will support mentored training and research needed for Dr. Arjun K. Manrai to transition to an independent investigator position bridging biomedical informatics, cardiovascular medicine, and population health. Throughout this award, Dr. Manrai will be mentored by Drs. Isaac S. Kohane, Joseph Loscalzo, and John P.A. Ioannidis. The long-term goal of Dr. Manrai's research is to improve cardiovascular care and reduce health disparities in multi-ethnic populations. A necessary step towards this goal is to clarify the impact of the ethnicity gap between past studies and current clinical practice. Dr. Manrai's K01 proposed research builds directly off of his previous work in translating clinical genomics across multi-ethnic populations, and includes large-scale analyses of diverse populations (N > 45,000,000) to investigate the appropriateness of existing genetic and clinical criteria for defining pathologic left ventricular hypertrophy (LVH) across different ethnic groups. Dr. Manrai will use heterogeneous datasets (genomic, clinical, and insurance claims data spanning tens of millions of individuals) to clarify the range of normal—and the appropriateness and impact of extant criteria for defining abnormal—molecular and clinical variation in diverse populations. This work will enable Dr. Manrai to: (1) characterize disease risks for genotype variation associated with the inherited heart disease hypertrophic cardiomyopathy (HCM) across ancestrally diverse populations; (2) develop ethnicity-specific phenotype reference ranges for cardiac morphology measures; and (3) measure the related healthcare systems impact using large-scale insurance claims data. In addition to the proposed research, Dr. Manrai will use this award to extend his background in biomedical data science and clinical genomics with extensive, hands-on clinical cardiology training and career development activities. Specifically, Dr. Manrai will: (1) enroll in formal echocardiography training courses and obtain clinical cardiology exposure; (2) attend leading cardiology meetings; (3) obtain training in health disparities and translational research; and (4) increase professional development. As part of his K01 career development activities, Dr. Manrai will work extensively in cardiology clinics around Boston and explore international clinical and research collaborations with clinics in Europe and Africa. This career development award is expected to enable Dr. Manrai to transition to an independent investigator position and lead directly to an R01 research proposal applying the research and training acquired during the award period to study a broader set of diseases of the heart muscle (inherited cardiomyopathies including dilated cardiomyopathy and arrhythmogenic right ventricular cardiomyopathy). Dr. Manrai's K01 proposed research is expected to yield the largest existing catalogue of multi-ethnic cardiac morphology and genetic variation related to LVH. This information will assist physicians, researchers, and patients making decisions with these data daily.