Using Genetic Diversity to Manage Neurological Disease

项目摘要/摘要： 这项针对NOT-AG-22-025/PA-20-272的为期一年的行政补充申请是一项提案，旨在 使用我们首创的最先进的高斯过程(GP)机器学习技术 从逐个残基协方差的角度来看，Niemann-Pick C1(NPC1)对胆固醇的管理不善，AS 在父母赠款AG070209中描述，以解决世界范围内对自然变异知之甚少的种群 在遗传风险因子APOE、ABCA7和TREM2中发现参与大脑中胆固醇稳态的基因。 NPC1是一种蛋白质，它是管理细胞内胆固醇在所有细胞中分布所必需的 人体通过其中心溶酶体沿胞外和胞内途径定位。突变 在NPC1中导致早期(2-10岁)严重的神经系统疾病，类似于AD，原因是丢失 细胞内胆固醇管理对细胞生长和功能至关重要。相比之下，APOE、ABCA7和TREM2 是一个由遗传风险因素组成的团队，它们被认为对细胞外的管理起到了共同作用 大脑中的胆固醇稳态，当这种基因突变时，会导致迟发性阿尔茨海默病(AD) (加载)。这份为期一年的行政补充文件的主要目的是使用 AG070209构建了一套前所未有的新分子遗传工具，以生成全面的基于GP的 遗传风险因子APOE、ABCA7和TREM2的协方差观点，当突变时，这些因素会导致 胆固醇管理不善导致负荷。目标1将是产生分子工具来研究75天然 影响载脂蛋白E功能的变异导致细胞外胆固醇管理不善 ApoE4变种是负荷的一个公认的遗传风险因素；研究75个变种的影响 ABCA7，参与胆固醇管理的细胞表面跨膜脂/胆固醇通道 通过与含有脂质颗粒的APOE相互作用在细胞外界面转移；并产生75 小胶质细胞中的APOE信号受体单通路跨膜蛋白TREM2的变体参与了 AB42合计净空。在目标2中，对于胆固醇管理团队的每个成员，我们将 通过分析天然变异对蛋白质折叠和稳定性的影响，对其进行实验研究 通过胞外分泌途径(APOE)或定位于细胞表面(ABCA7和TREM2)。在……里面 目标3，如上所述，这些膜运输数据将被用来建立基于GP的表型景观 在AG070209中，根据每个残留物的热力学稳定性和临床影响，使用 ClinVar/阿尔茨堡数据库。这些表型景观将定量描述协方差 每个蛋白质序列中所有残基之间的关系，具有定义的不确定性，将每个残基与 控制其折叠的热力学属性和对其影响进行评分的临床指标。这些 分析将为未来研究APOE、ABCA7和TREM2的治疗反应提供基线 在亲本授权AG070209中描述的蛋白抑制调节剂的变体。

Project Summary/Abstract: This one-year Administrative Supplement request in response to NOT-AG-22-025/PA-20-272 is a proposal to use our state-of-the-art Gaussian Process (GP) machine learning technologies we have pioneered to understand from a residue-by-residue covariance perspective cholesterol mismanagement by Niemann-Pick C1 (NPC1), as described in parent grant AG070209, to address the poorly understood world-wide population of natural variants found in the genetic risk factors APOE, ABCA7, and TREM2 involved in cholesterol homeostasis in the brain. NPC1 is a protein that is required for the management of the intracellular distribution of cholesterol in all cells in the human body through its central lysosomal localization along the exocytic and endocytic pathways. Mutations in NPC1 lead to an early onset (2-10 years of age) severe neurological disease resembling AD due to loss of intracellular cholesterol management critical for cell growth and function. In contrast, APOE, ABCA7 and TREM2 is a team of genetic risk factors that are thought to contribute as a collective to management of extracellular cholesterol homeostasis in the brain and that, when mutated, lead to late-onset (LO) Alzheimer’s Disease (AD) (LOAD). The primary purpose of this one-year Administrative Supplement is to use the approach described in AG070209 build an unprecedented set of new molecular genetic tools to generate a comprehensive GP-based covariance view of the genetic risk factors APOE, ABCA7 and TREM2 that, when mutated, contribute to mismanagement of cholesterol leading to LOAD. Goal 1 will be to generate molecular tools to study 75 natural variants impacting APOE function in the population that contribute to extracellular cholesterol mismanagement with the ApoE4 variant being a well-established genetic risk factor for LOAD; to study the impact of 75 variants of ABCA7, a cell surface transmembrane lipid/cholesterol channel involved in management of cholesterol transfer at the extracellular interface through interaction with APOE containing lipid particles; and to generate 75 variants in the single pass transmembrane protein TREM2, an APOE signaling receptor in microglia involved in Ab42 aggregate clearance. In Goal 2, for each member of the cholesterol management team, we will experimentally address the impact of natural variants on protein folding and stability by analysis of their trafficking through the exocytic pathway for secretion (APOE) or localization at the cell surface (ABCA7 and TREM2). In Goal 3, these membrane trafficking data will be used to build GP based ‘phenotype landscapes’, as described in AG070209, in the context of the thermodynamic stability of each residue and clinical impact using ClinVar/ALZFORUM databases. These phenotype landscapes will describe quantitatively the covariance relationships between all residues in each protein sequence with defined uncertainty, linking each residue to the thermodynamic properties governing its fold and clinical metrics that score their impact on LOAD. These analyses will provide a baseline for future studies of the therapeutic response of APOE, ABCA7 and TREM2 variants to proteostasis modulators as described in parent grant AG070209.