INTRODUCTIONGenome‐wide association studies have identified over 70 genetic loci associated with late‐onset Alzheimer's disease (LOAD), but few candidate polymorphisms have been functionally assessed for disease relevance and mechanism of action.METHODSCandidate genetic risk variants were informatically prioritized and individually engineered into a LOAD‐sensitized mouse model that carries the AD risk variants APOE ε4/ε4 and Trem2*R47H. The potential disease relevance of each model was assessed by comparing brain transcriptomes measured with the Nanostring Mouse AD Panel at 4 and 12 months of age with human study cohorts.RESULTSWe created new models for 11 coding and loss‐of‐function risk variants. Transcriptomic effects from multiple genetic variants recapitulated a variety of human gene expression patterns observed in LOAD study cohorts. Specific models matched to emerging molecular LOAD subtypes.DISCUSSIONThese results provide an initial functionalization of 11 candidate risk variants and identify potential preclinical models for testing targeted therapeutics.Highlights A novel approach to validate genetic risk factors for late‐onset AD (LOAD) is presented. LOAD risk variants were knocked in to conserved mouse loci. Variant effects were assayed by transcriptional analysis. Risk variants in Abca7, Mthfr, Plcg2, and Sorl1 loci modeled molecular signatures of clinical disease. This approach should generate more translationally relevant animal models.

中文翻译：

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晚发性阿尔茨海默病遗传危险因素的体内验证

简介 全基因组关联研究已确定了 70 多个与迟发性阿尔茨海默氏病 (LOAD) 相关的遗传位点，但很少对候选多态性进行了疾病相关性和作用机制的功能评估。方法对候选遗传风险变异进行信息优先级排序，并单独设计成携带 AD 风险变异的 LOAD 敏感小鼠模型APOEε4/ε4 和 Trem2*R47H。通过将 4 月龄和 12 月龄时 Nanostring 小鼠 AD Panel 测量的脑转录组与人类研究队列进行比较，评估每个模型的潜在疾病相关性。结果我们为 11 种编码和功能丧失风险变异创建了新模型。多种遗传变异的转录组效应概括了 LOAD 研究队列中观察到的各种人类基因表达模式。与新兴分子负荷亚型相匹配的特定模型。讨论这些结果提供了 11 种候选风险变异的初步功能化，并确定了用于测试靶向治疗的潜在临床前模型。亮点 提出了一种验证迟发性 AD (LOAD) 遗传风险因素的新方法。 LOAD 风险变异被敲入保守的小鼠位点。 通过转录分析来测定变异效应。 风险变体ABCA7,甲基四氢呋喃,Plcg2 和 Sorl1位点模拟临床疾病的分子特征。 这种方法应该产生更多翻译相关的动物模型。