Linking genetic subtypes of Alzheimer's disease to biological and cognitive heterogeneity

项目摘要/摘要 拟议的职业发展奖的长期目标是为我提供必要的培训，以 制定一项独立的研究计划，专注于阐明遗传、生物和认知 阿尔茨海默病(AD)风险的异质性。对生物通路遗传学的重视 提议的项目将补充我在认知神经科学和神经成像方面的现有背景。这个 培训目标是：1)获得实验室管理方面的培训，并制定多学科研究计划，以 学习AD；2)获得分子遗传学方面的专门知识；3)接受生物过程方面的培训 这会导致AD。这些培训目标是相互提供信息的，并将通过以下组合实现 正式课程、实践方法培训和非正式讨论。精神病学系 加州大学圣地亚哥分校是接受这种培训的理想环境，因为 世界知名研究人员的强大存在，职业发展的跟踪记录，以及该领域的状况 研究设施。AD的标准模型提出了一系列特征性的病理事件，可能 准确描述一些人的进程，但不是所有人的进程。然而，AD治疗试验的失败 表明标准模型是不完整的。先前的研究已经确定了认知领域的可变性 病理事件的损害、程度和顺序，以及萎缩和病理的形态 大脑。有趣的是，这些生物指标的可变性似乎与认知的可变性有关。 减损。这些发现提供的证据表明，即使是“典型的”阿尔茨海默病也可能包括多种疾病 亚型，但尚不清楚它们在多大程度上是由需要不同治疗的不同病因引起的。 阿尔茨海默病等复杂疾病的遗传风险可以用多基因风险评分(PRSS)来总结，但 这些措施只考虑了单一连续体的风险，这可能会掩盖不同的遗传来源 风险。该项目的科学部分将寻求使用多个AD PRS来确定遗传亚型 特定于生物途径。该项目将解决两个关键问题：1)阿尔茨海默病的遗传病因 多维，以及2)阿尔茨海默病遗传风险的变异性如何与异质性生物学和 疾病的认知表现？具体目的是：1)确定AD是否有亚型 使用基于途径的PRSS的遗传风险；2)测试AD的生物学亚型是否与不同的 以及3)检查认知障碍亚型是否与不同的 阿尔茨海默病遗传风险的各种形式。该项目将集中于4项大规模研究，包括多种生物学、认知和 遗传学测量：阿尔茨海默病神经成像倡议，巴尔的摩老龄化纵向研究， 越南时代双胞胎老龄化研究，和英国生物库。表征疾病病因学的可变性将有助于 努力制定与疾病亚型相关的有针对性的干预战略。它还将允许更准确地 按亚型对个体进行分组，以提高检测疾病和治疗效果的敏感性。

PROJECT SUMMARY/ABSTRACT The long-term goal of the proposed career development award is to provide me with the training necessary to develop an independent research program focused on elucidating the genetic, biological and cognitive heterogeneity of Alzheimer’s disease (AD) risk. An emphasis on the genetics of biological pathways in the proposed project will complement my existing background in cognitive neuroscience and neuroimaging. The training goals are to: 1) gain training in lab management and develop a multi-disciplinary research program to study AD; 2) gain specific expertise in molecular genetics; and 3) receive training in the biological processes that contribute to AD. These training goals are mutually informative and will be achieved through a mix of formal coursework, hands-on methodological training, and informal discussion. The Psychiatry Department at the University of California, San Diego is an ideal environment in which to receive this training due to the strong presence of world-renown researchers, track record of career development, and state-of-the-field research facilities. Standard models of AD propose a characteristic sequence of pathological events that may accurately describe the progression of some, but not all individuals. However, the failure of AD treatment trials suggests that standard models are not complete. Prior studies have identified variability in domains of cognitive impairment, levels and sequence of pathological events, and the topography of atrophy and pathology in the brain. Interestingly, variability in these biological measures appears to correlate with variability in cognitive impairment. These findings provide evidence suggesting that even “typical” AD may comprise multiple disease subtypes, yet it is unclear to what extent they arise from different etiologies requiring different treatments. Genetic risk in complex diseases such as AD can be summarized using polygenic risk scores (PRSs), but these measures only consider risk along a single continuum, which may obscure different sources of genetic risk. The scientific component of the project will seek to identify genetic subtypes using multiple AD PRSs specific to biological pathways. This project will address two key questions: 1) Is the genetic etiology of AD multidimensional, and 2) how does variability in the genetic risk for AD relate to heterogenous biological and cognitive expressions of the disease? The specific aims are to: 1) determine whether there are subtypes of AD genetic risk using pathway-based PRSs; 2) test whether biological subtypes of AD are associated with different forms of AD genetic risk; and 3) examine whether cognitive impairment subtypes are associated with different forms of AD genetic risk. The project will focus on 4 large-scale studies with multiple biological, cognitive, and genetic measures: Alzheimer’s Disease Neuroimaging Initiative, Baltimore Longitudinal Study of Aging, Vietnam Era Twin Study of Aging, and UK Biobank. Characterizing the variability of disease etiology will inform efforts to develop targeted intervention strategies relevant for disease subtypes. It will also allow more accurate groupings of individuals by subtype to improve sensitivity in detecting disease and therapeutic effects.