Using Genetic Diversity to Manage Neurological Disease

项目概要/摘要： 根据NOT-AG-22-025/PA-20-272提出的一年期行政补充申请是一项提案， 使用我们最先进的高斯过程（GP）机器学习技术，我们已经率先了解 从逐个残基协方差的角度来看，Niemann-Pick C1（NPC 1）的胆固醇管理不善，因为 在母基金AG 070209中描述，以解决对世界范围内的自然变异群体知之甚少的问题。 在参与大脑胆固醇稳态的遗传风险因子APOE、ABCA 7和TREM 2中发现。 NPC 1是一种蛋白质，其在所有细胞中管理胆固醇的细胞内分布是必需的。 人体通过其中央溶酶体定位沿着胞吐和胞吞途径。突变 在NPC 1中，由于丧失了神经元， 细胞内胆固醇管理对细胞生长和功能至关重要。相反，APOE、ABCA 7和TREM 2 是一组遗传风险因素，被认为有助于作为一个集体管理细胞外 胆固醇在大脑中的稳态，当突变时，导致迟发性（LO）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采用 AG 070209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 遗传风险因素APOE、ABCA 7和TREM 2的协方差观点，当突变时， 胆固醇管理不当导致LOAD。目标1将是产生分子工具来研究75种天然 影响人群中APOE功能的变异导致细胞外胆固醇管理不当 ApoE 4变异是LOAD的一个公认的遗传风险因素;研究75种变异的影响 ABCA 7是一种参与胆固醇管理的细胞表面跨膜脂质/胆固醇通道， 通过与含APOE的脂质颗粒相互作用在细胞外界面转移;并产生75 在小胶质细胞中的一种APOE信号受体，一种单次跨膜蛋白TREM 2的变体， Ab 42聚集体清除率。在目标2中，对于胆固醇管理团队的每个成员，我们将 通过分析其运输，实验性地解决天然变体对蛋白质折叠和稳定性的影响 通过胞外分泌途径（APOE）或定位在细胞表面（ABCA 7和TREM 2）。在 目标3，这些膜运输数据将用于构建基于GP的“表型序列”，如所述 在AG 070209中，在各残留物的热力学稳定性和临床影响的背景下，使用 ClinVar/ALZFORUM数据库。这些表型景观将定量描述协方差 每个蛋白质序列中的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性质和对LOAD影响评分的临床指标。这些 这些分析将为未来研究APOE、ABCA 7和TREM 2的治疗反应提供基线 如在母案授权AG 070209中所述的蛋白质稳态调节剂的变体。

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.