Disease Model Development and Phenotyping Project

疾病模型开发和表型(DMP)项目摘要 在最初的筹资期间，DMP创建和评估了40多种新车型，包括33种负载- 相关等位基因。这包括一组平台菌株，它们整合了人源化的APOE4、TREM2*R47H和 人性化的Aβ序列。平台菌株通过IU/JAX/PITT模型进行评估，时间从4个月到24个月。 AD表型流水线，包括PET/CT、多组学(转录组学、蛋白质组学和代谢组学)， 神经病理学和体液生物标记物分析。第一个平台菌株LOAD1(APOE4的双纯合子 和TREM2*R47H)主要表现为年龄相关效应，少数表现为基因型特异性效应。为了我们的第二次 平台株，LOAD2(APOE4，TREM2*R47H和HAβ的三重纯合)，我们包括一种高脂肪/高糖 饮食(HFD)组为环境危险因素。与对照组小鼠相比，12个月时，饲喂HFD的LOAD2 小鼠表现出不溶性Aβ42水平升高，下丘脑神经元丢失，长时程增强降低 (LTP)，并降低海马区脊椎密度。除了平台模型，还有24种可能的遗传基因 生物信息学和数据管理核心(BDMC)确定的风险变量被引入LOAD1 或LOAD2，并通过比较脑转录本和加速药物进行评估 AD(AMP-AD)数据中的伙伴关系。假定的风险变量位于先前识别的两个中(例如， ABCA7、CR1、PLCG2、MTHFR和EPHA1)以及新的AD危险基因。通过这项工作，ABCA7*A1527G， PLCG2*M28L和MTHFR*677C&gt；T优先通过我们的表型流水线进行全面鉴定。 总的来说，这些数据支持我们的总体假设，即与负荷相关的基因和/或 环境风险因素，在没有家族性AD(FAD)突变的情况下，将在 并因此创建了用于临床前试验的改进的小鼠模型。在续签中，我们将继续 评估新的负荷模型，更加注重确定临床前测试核心(PTC)的模型。 为了实现这一点，我们的表型管道已经得到了增强，并结合了横截面和 纵向设计、广泛的生物标记物分析、MRI、额外的PET配体(例如，用于神经炎症和 突触丢失)、数字空间侧写以及突触和认知评估。我们将首先完成 三种优先加载应变的特征以及一种新的平台模型LOAD3(三元组 Apo4、HAβ和人源化MAPT等位基因的纯合子)合并和不合并HFD(目标1)。 TAU的过度磷酸化和聚集是LOAD的一个标志性病理，目前在我们的 菌株。因此，我们接下来将评估四个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，预计不会有单一的负荷模型 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和临床前试验协同工作 CORE(PTC)开发更精确的负荷小鼠模型，并启动临床前测试。

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.