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

项目摘要 晚发性阿尔茨海默病（LOAD）是中老年人痴呆的主要原因。它 其特征在于记忆的逐渐丧失，最终导致认知功能的完全丧失。病理 在脑中的表现包括神经元损失、神经胶质增生、细胞外淀粉样蛋白沉积和神经纤维缠结。 在遗传风险因素中，APOE-ε4是最强的，但基因组关联研究（GWAS）已经确定， 并确认了几个额外的位点。然而，LOAD遗传力的遗传来源的很大一部分， 仍然未知。 阿尔茨海默氏病的大规模测序工作正在进行中，以确定检测罕见的致病性 变异（RV）的关联，可能解释缺失的遗传性。为了检测适度的RV效应，大样本 尺寸是必需的。在这里，我们提出了一个强大的方法来研究RV在大家庭与大数字 受影响的个人，他们可能会聚集在一起，并有更大的影响大小。这个项目的主要目标是 一项建议是协调表型和全基因组和外显子组测序（WGS和WES）数据， 约1000个LOAD系列，并应用现有的和新的基于系列的分析来识别LOAD易感性变体 以及可以作为治疗靶点进行测试的基因座。诸如三到五倍的高发病率等因素 LOAD与一般人群相比，具有毒性有害变体的聚集、近亲繁殖、低水平的 测序伪影和使用族分析设计控制群体亚结构/混合的能力 （与不相关的病例对照相比）使这些家庭成为识别LOAD相关遗传风险的理想选择 保护因素。本建议中的努力将与《2000 - 2001年国际劳工组织关于非洲经济和社会发展的报告》中的分析并行，并与之相辅相成。 对阿尔茨海默病测序项目（ADSP）进行的不相关病例对照分析 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.