Using Genetic Diversity to Manage Neurological Disease

利用遗传多样性来治疗神经系统疾病

• 批准号: 10321554
• 负责人: William Edward Balch
• 金额: $ 44.38万
• 依托单位: SCRIPPS RESEARCH INSTITUTE, THE
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-01-01 至 2025-12-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10321554
• 关键词: Address; Aging; Alleles; Alzheimer' s Disease; Amino Acid Sequence; Automobile Driving; Autophagocytosis; Basic Science; Biochemical; Biological Sciences; Birth; Brain; Buffers; Cells; Cessation of life; Characteristics; Chemicals; Cholesterol; Cholesterol Homeostasis; Clinical; Disease; Disease Management; Disease Progression; Environment; Etiology; GRP gene; Gaussian model; Genes; Genetic; Genetic Diseases; Genetic Variation; Genome; Genotype; Goals; Heat-Shock Proteins 70; Heat-Shock Response; Human; Individual; Inherited; Knowledge; Late Onset Alzheimer Disease; Lead; Learning; Light; Lipids; Lysosomes; Machine Learning; Modernization; Molecular; Molecular Chaperones; Molecular Mechanisms of Action; Neurodegenerative Disorders; Niemann-Pick Diseases; Pathology; Pathway interactions; Patients; Phenotype; Population; Process; Proteins; Rare Diseases; Resolution; Role; Signal Pathway; Specificity; Stress; Structure; System; Target Populations; Therapeutic; Therapeutic Intervention; Time; Ubiquitin; Uncertainty; United States National Library of Medicine; Variant; base; biochemical tools; biophysical tools; cell type; cholesterol control; druggable target; early onset; fitness; genomic variation; human model; improved; insight; loss of function; multicatalytic endopeptidase complex; nervous system disorder; novel; polypeptide; precision medicine; prevent; prognostic; protein folding; protein function; protein misfolding; proteostasis; rare genetic disorder; rare variant; response; small molecule; tool; trafficking

Project Summary/Abstract Understanding and treating genome abnormalities that lead to rare genetic neurodegenerative diseases such as Niemann-Pick C1 globally managing cholesterol homeostasis, or APOE alleles impacting cholesterol homeostasis in the brain triggering late-onset Alzheimer’s disease (LOAD), present a major challenge from both basic science and clinical perspectives. We have developed a Gaussian process regression (GPR) based machine learning (ML) approach that captures for the first time genomic variation in the population to understand the spatial covariance (SCV) relationships contributing to sequence-to-function-to-structure relationships in the individual. Genetic disease is fundamentally a problem of understanding the impact of altered folding intermediates found in response to variation in the protein fold and how they are managed by proteostasis. Proteostasis encompasses a broad range of chaperone and degradative components that manage the synthesis, folding/stability and function of the protein fold in response to inherited and environmental stress and aging. The general premise of this proposal is to develop a deep genome-based understanding of proteostasis that will teach us how to manage genetic diseases triggered by folding stress. The rationale for this proposal is that sparse genetic diversity found in the population, when used as a collective through application of GRP-ML defined SCV relationships, can provide us on a residue-by-residue basis insight into the folding intermediates that contribute to disease for the entire polypeptide sequence. The objective of this proposal is to understand the role of proteostasis in managing this genetic diversity for the benefit of therapeutic intervention. We hypothesize that management of the polypeptide fold of disease-causing variant proteins found in the population by targeting the function of the multivalent Hsp40 and Hsp70 co-chaperone/chaperone branch (the Hsp70 axis) of the proteostasis network will enable precision correction of misfolding phenotypes found in neurodegenerative disease. Our approach will study the impact of variation in the Niemann Pick C1 (NPC1) gene. NPC1 is an inherited, autosomal recessive, disorder characterized by the abnormal accumulation of unesterified cholesterol and other lipids in late endosomal (LE) and lysosome (Ly) compartments of all cell types. The primary effect of NPC1 variation results in early onset neurodegenerative disease in response to loss of cholesterol homeostasis. In Aim 1 we will explore the ability of small molecules to allosterically regulate the activity of components of the Hsp70 axis to retune the synthesis, folding/stability, trafficking and/or function of NPC1 variants. In Aim 2 we will explore the molecular mechanism of action (MoA) of the Hsp70 axis components that are responsible for enabling NPC1 variant correction. Completion of both aims will generate a comprehensive assessment of the role of Hsp70 axis in NPC1 disease progression and will be used as a guide for advancement of a precision medicine approach to reduce or prevent the onset of neurodegenerative disease triggered by genomic variation in NPC1 population.

项目总结/摘要 了解和治疗导致罕见遗传性神经退行性疾病的基因组异常， Niemann-Pick C1全面管理胆固醇稳态，或影响胆固醇的APOE等位基因 大脑中的稳态触发迟发性阿尔茨海默病（LOAD），提出了一个主要的挑战， 基础科学和临床前景。我们已经开发了一个高斯过程回归（GPR）的基础上， 机器学习（ML）方法，首次捕获人群中的基因组变异，以了解 空间协方差（SCV）关系有助于序列-功能-结构关系， 单独的.遗传疾病从根本上说是一个理解折叠改变的影响的问题 在响应蛋白质折叠的变化中发现的中间体以及它们如何通过蛋白质稳定来管理。 蛋白质稳态包括广泛的分子伴侣和管理合成的降解组分， 折叠/稳定性和功能的蛋白质折叠响应遗传和环境压力和老化。的 这项建议的一般前提是发展一个深刻的基于基因组的理解蛋白质，将 教我们如何控制由折叠压力引发的遗传疾病。提出这一建议的理由是， 稀疏的遗传多样性在人口中发现，当作为一个集体，通过应用GRP-ML 定义的SCV关系，可以为我们提供一个残基的基础上深入了解折叠中间体 导致整个多肽序列的疾病。本提案的目的是了解 蛋白质稳态在管理这种遗传多样性中的作用，以利于治疗干预。我们 假设在群体中发现致病变异蛋白的多肽折叠的管理 通过靶向多价Hsp 40和Hsp 70共分子伴侣/分子伴侣分支（Hsp 70轴）的功能， 蛋白质稳态网络的建立将能够精确校正神经退行性疾病中发现的错误折叠表型。 疾病我们的方法将研究尼曼皮克C1（NPC 1）基因变异的影响。NPC 1是一个 一种以非酯化胆固醇异常积累为特征的常染色体隐性遗传性疾病 以及所有细胞类型的晚期内体（LE）和溶酶体（Ly）区室中的其它脂质。的主要作用 NPC 1变异导致早发性神经退行性疾病对胆固醇稳态丧失的响应。 在目标1中，我们将探索小分子变构调节细胞内组分活性的能力。 Hsp 70轴来重新调节NPC 1变体的合成、折叠/稳定性、运输和/或功能。在目标2中， 将探索Hsp 70轴组件的分子作用机制（MoA），这些组件负责 使能NPC 1变体校正。这两个目标的完成将产生一个全面评估， Hsp 70轴在NPC 1疾病进展中的作用，并将用作提高精确度的指南。 减少或预防由基因组变异引发的神经退行性疾病发作的医学方法 在NPC 1人群中。