Gene discovery in multi-ethnic late-onset Alzheimer's disease families

项目总结 晚发性阿尔茨海默病(LOAD)是中老年人痴呆的主要原因。它 以记忆力的进行性丧失为特征，最终导致认知功能的完全丧失。病理性的 脑部表现为神经元丢失、神经胶质增生、细胞外淀粉样物沉积和神经原纤维缠结。 在遗传风险因素中，载脂蛋白E-ε4是最强的，但基因组关联研究已经确定 并确认了另外几个基因座。然而，很大一部分遗传来源的遗传性的负荷 仍然是未知的。 阿尔茨海默病的大规模测序工作正在进行中，以确定、检测出可能是罕见原因的 可能解释缺失遗传性的变异(RV)关联。要检测适度的RV效果，请使用大样本 尺寸是必填项。在这里，我们提出了一种强有力的方法来研究大家庭中的房车 在受影响的个体中，它们可能聚集在一起，并产生更强的影响大小。这一行动的主要目标是 建议统一表型、全基因组和外显子组测序(WGS和WES)数据 ~1000个载荷族，并应用现有的和新的基于族的分析来确定负荷敏感度变量 以及可以作为治疗靶点进行测试的基因座。因素，如将发病率提高三到五倍 与一般人群相比，有害变异的聚集性，近亲繁殖，低水平的 使用家族分析设计对种群亚结构/混合进行控制的能力和测序伪影 (与不相关的病例对照相比)使这些家系成为识别负荷相关遗传风险的理想选择 和保护性因素。这项提案中的努力将与《公约》中的分析并行并相辅相成 阿尔茨海默病测序项目(ADSP)正在进行的无关病例对照分析 发现、扩展复制和后续数据集。

PROJECT SUMMARY Late onset Alzheimer’s disease (LOAD) is the leading cause of dementia among the middle aged and elderly. It is characterized by progressive loss of memory culminating in complete loss of cognitive function. Pathological manifestations in brain include neuronal loss, gliosis, extracellular amyloid deposits and neurofibrillary tangles. Among genetic risk factors, APOE-ε4 is the strongest, but genome association studies (GWAS) have identified and confirmed several additional loci. However, a substantial portion of the genetic source of heritability of LOAD is still unknown. Large-scale sequencing efforts in Alzheimer’s Disease are underway to identify detect putatively causal rare variant (RV) associations that might explain the missing heritability. To detect modest RV effects, large sample sizes are required. Here we propose a powerful approach to study RVs in extended families with large numbers of affected individuals where they are likely to aggregate and have stronger effect sizes. The major goal of this proposal is to harmonize phenotype and whole genome and exome sequencing (WGS and WES) data from ~1000 LOAD families and apply existing and novel family-based analytics to identify LOAD susceptibility variants and loci that can be tested as therapeutic targets. Factors such as a three to five-fold higher incidence rates of LOAD compared to the general population, clustering of putatively deleterious variants, inbreeding, low level of sequencing artifacts and the ability to control for population substructure/admixture using a family analysis design (compared to unrelated case-controls) make these families ideal for identifying LOAD associated genetic risk and protective factors. The efforts in this proposal will be in parallel with and complementary to analyses in the unrelated case-control analyses being conducted on Alzheimer’s Disease Sequencing Project (ADSP) discovery, extension replication and follow-up datasets.