Genetic Analyses of Lipids in Cerebral Hemorrhage and Small Vessel Disease

描述（由申请人提供）：Christopher D. Anderson 博士是马萨诸塞州总医院 (MGH) 的神经重症监护和中风神经科医生，其职业目标是作为计算遗传生物学家开发一个独立的研究项目，能够使用先进的生物信息学和统计方法从大规模遗传和基因组研究中获得最大的科学成果，目的是返回有意义和可操作的结果，以增进对脑小血管疾病 (CSVD) 的理解并确定治疗开发的新靶点。作为实现这一目标的第一步，他计划利用全基因组研究的数据来检查与脂质水平相关的生物网络内的遗传变异，以揭示脂质影响脑小血管病的机制。该提案解决了一个有争议的关键领域，因为目前的数据表明，根据所研究的脑血管疾病的特定形式，血脂水平的作用是相互矛盾的。脑小血管疾病是脑出血（ICH）、放射学白质疾病和脑微出血的基础，可能因脂质水平降低而恶化，而总体缺血性中风风险似乎受益于这一策略。安德森博士在分析常见遗传变异数据方面建立了早期职业记录，以识别缺血性中风、脑出血和阿尔茨海默病的新关联，他的初步数据证明了生物信息遗传分析在脑血管疾病中的可行性。他的职业规划在 Jonathan Rosand 博士和 Drs. Sekar Kathiresan、Mark Daly 和 Ona Wu。在本次职业发展奖中，Anderson 博士建议：1) 发现已知影响血脂水平的常见遗传变异对 ICH 风险和 CSVD 神经影像学表现严重程度的影响，2) 确定基因网络中罕见遗传变异对血脂水平的影响，以及这些相同神经影像学指标的严重程度，以及 3) 使用先进的生物信息学工具构建与血脂水平相关的新型基因网络，并测试这些网络与 ICH 和神经影像学指标的关联，发现新的生物靶点。 拟议的研究将采用遗传和信息工具来证明脂质对脑小血管病的影响方向和程度。这些分析为药物开发提供了新靶点的希望，并将进一步我们对调脂疗法潜在风险的理解。安德森博士组建了一支在复杂疾病遗传学、脂质流行病学、神经影像学和先进生物信息学技术方面拥有专业知识的团队，这将确保该提案最大限度地利用生成的数据。该奖项将为安德森博士提供发展成为一名独立临床医生科学家的技能，其计算研究项目可以灵活地分析大型遗传数据集，以获得与临床患者群体中脑血管疾病的预防和治疗高度相关的结果。

DESCRIPTION (provided by applicant): Dr. Christopher D. Anderson is a Neurocritical Care and Stroke Neurologist at Massachusetts General Hospital (MGH), whose career goal is to develop an independent research program as a computational genetic biologist capable of using advanced bioinformatic and statistical methods to obtain maximal scientific yield from large-scale genetic and genomic studies, with the aim of returning meaningful and actionable results that improve understanding of cerebral small vessel disease (CSVD) and identify novel targets for therapeutic development. As a first step toward this goal, he plans to use data from genome-wide studies to examine genetic variants within biological networks associated with lipid levels to uncover the mechanisms by which lipids influence CSVD. This proposal addresses a key area of controversy, as current data suggest conflicting roles for lipid levels depending on the particular form of cerebrovascular disease under study. Cerebral small vessel disease, which underlies intracerebral hemorrhage (ICH), radiographic white matter disease, and cerebral microbleeds, may be worsened by reduced lipid levels, while overall ischemic stroke risk appears to benefit from this strategy. Dr. Anderson has established an early career track record in the analysis of common genetic variant data to identify new associations in ischemic stroke, ICH, and Alzheimer Disease, and his preliminary data demonstrate the feasibility of biologically-informed genetic analysis in cerebrovascular disease. His career plan leverages the extensive resources and exceptional environments of Massachusetts General Hospital and the Broad Institute, under the mentorship of Dr. Jonathan Rosand and co-mentorship of Drs. Sekar Kathiresan, Mark Daly, and Ona Wu. In this Career Development Award, Dr. Anderson proposes to: 1) discover the impact of common genetic variants known to affect lipid levels on the risk of ICH and severity of neuroimaging manifestations of CSVD, 2) determine the impact of rare genetic variants in gene networks with a role in lipid levels on risk of ICH and severity of these same neuroimaging measures, and 3) use advanced bioinformatics tools to construct novel gene networks associated with lipid levels, and test these networks for association with ICH and neuroimaging measures to uncover new biological targets. The proposed study will employ genetic and informatic tools to demonstrate the direction and magnitude of effect that lipids exert on CSVD. These analyses offer the promise of yielding novel targets for drug development, and will further our understanding of the potential risks of lipid modifying therapy. Dr. Anderson has assembled a team with expertise in complex disease genetics, lipid epidemiology, neuroimaging, and advanced bioinformatics techniques that will ensure that this proposal maximally leverages the data generated. This Award will provide Dr. Anderson with the skills to evolve into an independent clinician-scientist with a computational research program that can nimbly analyze large genetic datasets to derive results that are highly relevant to the prevention and treatment of cerebrovascular disease in his clinical patient population.