Disease Model Development and Phenotyping Project

疾病模型开发和表型分析项目

• 批准号: 10708111
• 负责人: Gareth R Howell
• 金额: $ 534.3万
• 依托单位: INDIANA UNIV-PURDUE UNIV AT INDIANAPOLIS
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-09-30 至 2027-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10708111
• 关键词: 3-Dimensional; Acceleration; Address; Affect; Age Months; Alleles; Alzheimer' s disease model; Alzheimer' s disease pathology; Amyloid beta-42; Amyloid beta-Protein; Amyloid beta-Protein Precursor; Animal Model; Biochemistry; Bioinformatics; Biological Assay; Biological Markers; Biological Models; Brain; CRISPR/Cas technology; Chronic; Clinic; Clinical Trials; Cognitive; Communities; Consumption; Coupled; Data; Development; Diet; Disease model; Environmental Risk Factor; Evaluation; Fatty acid glycerol esters; Female; Funding; Genetic; Genetic Risk; Genotype; Haplotypes; Heterogeneity; High Fat Diet; Hippocampus; Human; Image; Late Onset Alzheimer Disease; Ligands; Liquid substance; Long-Term Potentiation; MAPT gene; Magnetic Resonance Imaging; Medicine; Modeling; Mus; Mutation; PET/CT scan; Pathology; Phenotype; Polygenic Traits; Positron-Emission Tomography; Pre-Clinical Model; Preclinical Testing; Predictive Factor; Predisposition; Proteomics; Research; Risk; Risk Factors; Scheme; Synapses; TREM2 gene; Testing; Translating; Translations; United States Food and Drug Administration; Variant; Vertebral column; Work; age related; aged; amyloid imaging; apolipoprotein E-4; cognitive testing; comparison control; data management; design; digital; disease phenotype; efficacy testing; familial Alzheimer disease; genetic risk factor; genetic variant; improved; in vivo imaging; longitudinal design; male; metabolomics; model development; model organism; mouse genetics; mouse model; multiple omics; nano-string; neuroinflammation; neuron loss; neuropathology; novel; preclinical efficacy; preclinical study; risk variant; screening; sugar; synergism; tau aggregation; transcriptome; transcriptomics

PROJECT SUMMARY DISEASE MODEL DEVELOPMENT AND PHENOTYPING (DMP) PROJECT In the initial funding period, the DMP created and evaluated more than forty new models incorporating 33 LOAD- relevant alleles. This included a set of platform strains that incorporated humanized APOE4, Trem2*R47H and humanized Aβ sequence. Platform strains were evaluated from 4 to 24 months through the IU/JAX/PITT MODEL- AD phenotyping pipeline that included PET/CT, multi-omics (transcriptomics, proteomics and metabolomics), neuropathology, and fluid biomarker analysis. The first platform strain, LOAD1 (double homozygous for APOE4 and Trem2*R47H) showed primarily age-dependent affects and few genotype-specific effects. For our second platform strain, LOAD2 (triple homozygous for APOE4, Trem2*R47H and hAβ), we included a high fat/high sugar diet (HFD) group as an environmental risk factor. Compared to control mice, at 12 months, HFD-fed LOAD2 mice showed elevated levels of insoluble Aβ42, loss of neurons in the subiculum, reduced long-term potentiation (LTP), and reduced spine densities in the hippocampus. In addition to the platform models, 24 putative genetic risk variants identified by the Bioinformatics and Data Management core (BDMC) were introduced into LOAD1 or LOAD2 by CRISPR/Cas9 and evaluated by comparing brain transcriptomes to Accelerated Medicines Partnerships in AD (AMP-AD) data. The putative risk variants were located in both previously identified (e.g., Abca7, CR1, Plcg2, Mthfr and Epha1) as well as novel AD risk genes. Through this work, Abca7*A1527G, Plcg2*M28L and Mthfr*677C>T were prioritized for full characterization through our phenotyping pipeline. Collectively, these data support our overarching hypothesis that combinations of LOAD-relevant genetic and/or environmental risk factors, in the absence of familial AD (fAD) mutations, will induce hallmark AD pathologies in mice and therefore create improved mouse models for preclinical testing. In the renewal we will continue to evaluate novel LOAD models, with an increased focus on identifying models for the preclinical testing core (PTC). To achieve this, our phenotyping pipeline has been enhanced and incorporates a combined cross-sectional and longitudinal design, extensive biomarker analysis, MRI, additional PET ligands (e.g., for neuroinflammation and synapse loss), digital spatial profiling, and synaptic and cognitive assessment. We will first complete characterization of three prioritized LOAD strains as well as characterize a novel platform model LOAD3 (triple homozygous for APOE4, hAβ and a humanized MAPT allele) with and without HFD (Aim 1). Hyperphosphorylation and aggregation of TAU is a hallmark pathology for LOAD and absent in our current strains. Therefore, we will next evaluate four MAPT variants (N279K, P301L, R406W and S320F) that are predicted to increase susceptibility to TAU pathology (Aim 2). Finally, no single LOAD model is expected to represent the heterogeneity of human LOAD and we will therefore evaluate novel LOAD models based on polygenic risk analysis (BDMC, Aim 3). The DMP will continue to synergize with the BDMC and Preclinical Test Core (PTC) to develop more precise mouse models of LOAD and initiate preclinical testing.

项目摘要 疾病模型开发和表型分析 (DMP) 项目 在最初的资助期间，DMP 创建并评估了 40 多个新模型，其中包含 33 个 LOAD- 相关等位基因。这包括一组整合了人源化 APOE4、Trem2*R47H 和 人源化 Aβ 序列。通过 IU/JAX/PITT 模型对平台菌株进行 4 至 24 个月的评估- AD 表型分析流程包括 PET/CT、多组学（转录组学、蛋白质组学和代谢组学）、 神经病理学和液体生物标志物分析。第一个平台菌株 LOAD1（APOE4 双纯合子） 和 Trem2*R47H) 主要表现出年龄依赖性影响，很少有基因型特异性影响。对于我们的第二个 平台菌株 LOAD2（APOE4、Trem2*R47H 和 hAβ 三重纯合子），我们添加了高脂肪/高糖 饮食（HFD）组作为环境危险因素。与对照小鼠相比，12 个月时，HFD 喂养的 LOAD2 小鼠表现出不溶性 Aβ42 水平升高、下托神经元损失、长时程增强降低 （LTP），并降低海马体的棘密度。除了平台模型之外，还有 24 个假定的遗传模型 LOAD1 中引入了生物信息学和数据管理核心 (BDMC) 识别的风险变异 或 LOAD2，通过 CRISPR/Cas9 进行，并通过将大脑转录组与 Accelerated Medicines 进行比较进行评估 AD 合作伙伴关系 (AMP-AD) 数据。假定的风险变体位于先前确定的两个中（例如， Abca7、CR1、Plcg2、Mthfr 和 Epha1）以及新型 AD 风险基因。通过这项工作，Abca7*A1527G， Plcg2*M28L 和 Mthfr*677C>T 优先通过我们的表型分析流程进行全面表征。 总的来说，这些数据支持我们的总体假设，即负荷相关遗传和/或 在没有家族性 AD (fAD) 突变的情况下，环境危险因素将诱发标志性 AD 病理 小鼠，因此创建了用于临床前测试的改进小鼠模型。在更新中我们将继续 评估新颖的 LOAD 模型，更加注重识别临床前测试核心 (PTC) 的模型。 为了实现这一目标，我们的表型分析流程得到了增强，并结合了组合横截面和 纵向设计、广泛的生物标志物分析、MRI、额外的 PET 配体（例如，用于神经炎症和 突触损失）、数字空间分析以及突触和认知评估。我们首先要完成 表征三个优先 LOAD 菌株以及表征新颖的平台模型 LOAD3（三重 APOE4、hAβ 和人源化 MAPT 等位基因的纯合子）有或没有 HFD（目标 1）。 TAU 的过度磷酸化和聚集是 LOAD 的标志性病理学，但在我们目前的研究中不存在。 菌株。因此，我们接下来将评估四种 MAPT 变体（N279K、P301L、R406W 和 S320F），它们是 预计会增加对 TAU 病理的易感性（目标 2）。最后，预计没有任何一个 LOAD 模型能够 代表人类负荷的异质性，因此我们将基于以下因素评估新的负荷模型 多基因风险分析（BDMC，目标 3）。 DMP将继续与BDMC和临床前测试发挥协同作用 Core (PTC) 开发更精确的 LOAD 小鼠模型并启动临床前测试。