Identifying genetic variants that modify the effect size of ApoE alleles on late-onset Alzheimer's disease risk

项目摘要/摘要 研究特定人群和跨祖先对痴呆症风险的遗传贡献 观点对于疾病预测、表征和治疗干预措施的发展至关重要。 迟发性阿尔茨海默病(LOAD)是最常见的痴呆症形式，导致美国和 据估计，相关成本为3050亿美元，影响到全国约600万人，甚至更多 全球超过2400万人。载脂蛋白E(ApoE)是已知的最强的LOAD遗传风险因素。 具体地说，与载脂蛋白E相关的负荷风险是由载脂蛋白E的风险变体(称为ε4或载脂蛋白4)驱动的，而载脂蛋白E- 相关的负荷保护被认为是由该基因的保护性变体(称为ε2或APOE2)驱动的。 这些等位基因的等位基因频率因人群而异，这在一定程度上解释了 携带ApoE4等位基因频率最高的非洲裔人群。与这些发现相反的是， 有证据表明，非洲人后裔的载脂蛋白E4相关负荷风险显著较低 与其他组相比。这种效应的改变在一定程度上是由特定于人口的当地祖先推动的 修改ApoE4的效果大小。然而，这一观察并不能完全解释效应大小的减少。 在非裔美国人身上。我假设遗传变异(局部和全局)改变了载脂蛋白E4和载脂蛋白2效应 大小。这项提案描述了三个目标，以解决对载脂蛋白E基因贡献的调查- 多个不同人群中的相关负荷风险。目标1将记录负荷风险之间的关系 到目前为止要研究的最大和最多样化的数据集中的ApoE4和APOE2等位基因 在几个不同的种群中的每一个的影响大小。目标2将确定与极端载脂蛋白E4相关的SNP 和APOE2效应大小，并测试这些SNP是否定义了特定的生理通路关联。最后， 目标3将评估种族/民族和遗传变异作为影响大小的修饰者在 以及种群之间的差异。作为一名医学博士研究生，我对这个项目充满热情，因为它将带来新的 可用于了解、识别和预测服务不足人群的负载风险 美国，特别是那些经历了更多负荷负担的国家。组合式教育支持 来自人口与定量健康科学部的临床培训 凯斯西储大学的科学家培训计划将使我准备好应对遗传和 这项工作旨在向医疗保健渠道提供信息。在这些来源的支持下，委员会成员 在人口遗传学、统计分析和生物信息学方面的专业知识，我的培训将提供技能 成为一名内科科学家必须精通严格的统计学方法来理解 对复杂疾病的贡献。

PROJECT SUMMARY/ABSTRACT Studying genetic contributions to dementia risk from both the population-specific and trans-ancestral perspectives is vital to disease prediction, characterization, and the development of treatment interventions. Late-onset Alzheimer’s disease (LOAD) is the most common form of dementia, costs the United States an estimated $305 billion in associated costs, and affects approximately 6 million individuals nationally, and more than 24 million people globally. Apolipoprotein E (ApoE) is the strongest known genetic risk factor for LOAD. Specifically, ApoE-associated LOAD risk is driven by a risk variant of ApoE (termed ε4 or ApoE4) while ApoE- associated LOAD protection is thought to be driven by a protective variant of the gene (termed ε2 or ApoE2). The allele frequency of these alleles varies across populations, partially explaining higher LOAD prevalence in populations of African descent who carry the highest ApoE4 allele frequencies. In contrast to these findings, evidence indicates ApoE4-associated LOAD risk is significantly lower in individuals of African descent compared to other groups. This effect modification is partially driven by population-specific local ancestry that modifies the effect size of ApoE4. This observation, however, does not fully explain the reduction in effect size in African Americans. I hypothesize that genetic variants (local and global) modify ApoE4 and ApoE2 effect sizes. This proposal describes three aims to address the investigation into genetic contributions to ApoE- associated LOAD risk in multiple, diverse populations. Aim 1 will document the relationship between LOAD risk and the ApoE4 and ApoE2 alleles in the largest and most diverse dataset to be studied to date by estimating effect sizes in each of several diverse populations. Aim 2 will identify SNPs that associate with extreme ApoE4 and ApoE2 effect sizes and test whether these SNPs define specific physiological pathway association. Finally, aim 3 will evaluate the relative roles of race/ethnicity and genetic variation as modifiers of effect sizes within and between populations. As an MD/PhD candidate, I am passionate about this project as it will lead to new insights that can be used to understand, identify, and predict LOAD risk in underserved populations in the United States, especially those that experience increased LOAD burdens. The combined educational support from the Population and Quantitative Health Sciences Department and clinical training from the Medical Scientist Training Program at Case Western Reserve University will prepare me in tackling the genetic and healthcare avenues this work aims to inform. With support from these sources, and committee members with expertise in population genetics, statistical analysis, and bioinformatics, my training will provide the skills necessary to become a physician scientist versed in rigorous statistical approaches to understanding contributions to complex diseases.