Leveraging the Evolutionary History to Improve Identification of Trait-Associated Alleles and Risk Stratification Models in Native Hawaiians

项目总结/摘要 夏威夷原住民是美国研究最少的少数民族之一。相比 与欧洲人或亚裔美国人相比，夏威夷土著人的肥胖、糖尿病 以及其他相关的慢性健康状况，即使在调整了常见的可改变的风险因素之后。但很少 基因研究主要集中在夏威夷土著人身上。基因组资源，如插补参考面板 夏威夷原住民也普遍缺乏，阻止了全面的遗传调查， 对这一人群。因此，与其他大陆人口相比，夏威夷原住民不是 我们将从大规模疾病基因组研究中获益。 虽然越来越多的人认识到需要将更多的非欧洲人纳入基因组研究， 研究中，一个经常被忽视的事实是，一个群体成员的疾病风险与他们的年龄密切相关。 这个群体的进化史。理论和实证研究表明， 群体的历史将以该群体特有的方式影响基因型-表型关系。 因此，更好地纳入进化思想将有助于更好地理解遗传基础， 不同人群之间疾病风险的差异。为此，我们建议制定一项 综合框架，结合了人口遗传学和遗传流行病学的原则， 了解为什么夏威夷原住民在肥胖和2型糖尿病（T2 D）方面表现出过度风险。具体而言，由 利用新生成的全基因组序列（WGS）和现有的阵列基因型数据， 夏威夷原住民，我们将首先描述夏威夷原住民的人口统计历史以及 这一历史的丰富功能等位基因。这些等位基因很可能在自然选择下， 夏威夷原住民的健康，但如果只研究其他大陆人口， 大量存在。其次，通过与萨摩亚现有的WGS相结合，我们将构建第一个 波利尼西亚特定插补参考组。然后，我们将进行最大的关联研究， 迄今为止，在> 10，000名波利尼西亚人和> 2，000名波利尼西亚人中进行了肥胖和T2 D研究。三是 将基于多基因风险评分评估肥胖和T2 D风险分层模型的可转移性 (PRS)在夏威夷原住民中，确定可能促成的群体遗传和非遗传因素 这些模型的预期可移植性差，并评估波利尼西亚特有的汇总统计数据是否 改进风险分层模型。最后，我们会以专题小组的形式进行试验研究， 了解夏威夷原住民社区在未来参与基因组研究方面可能存在的问题。的 这项建议的结果将有助于激励和指导未来基因组研究的设计， 人群，确定影响肥胖和T2 D的人群特异性等位基因，并改善未来的风险分层 夏威夷原住民和其他波利尼西亚人的疾病模型。

Project Summary / Abstract Native Hawaiians are one of the most understudied, ethnic minority population in the United States. Compared to their European or Asian American counterparts, Native Hawaiians exhibit alarming rates of obesity, diabetes, and other related chronic health conditions, even after adjusting for common modifiable risk factors. Yet few genetic research has focused on Native Hawaiians. Genomic resources such as imputation reference panels are also generally lacking for Native Hawaiians, preventing comprehensive genetic investigations to be undertaken with this population. Therefore, compared to other continental populations, Native Hawaiians are not on pace to reap the benefits we have gained from large scale genomic studies of diseases. While there are growing recognitions of the need to include more non-European individuals in genomic studies, an often-ignored fact is that the disease risks for members of a population are intimately tied to the evolutionary history of that population. Theoretical and empirical studies have shown that the demographic history of a population will impact the genotype-phenotype relationship in ways specific to that population. Therefore, a better incorporation of evolutionary thinking will help better understand the genetic basis for differences in disease risk among diverse populations today. To this end, we are proposing to develop an integrative framework that combines principles of both population genetics and genetic epidemiology to understand why Native Hawaiians show excess risk in obesity and type-2 diabetes (T2D). Specifically, by leveraging newly generated whole genome sequences (WGS) and existing array genotype data on >5,600 Native Hawaiians, we will first characterize the demographic history of the Native Hawaiians and the impact of this history to the enrichment of functional alleles. These alleles are likely under natural selection, important for the health of Native Hawaiians, but would be easily missed if one only studies other continental populations that exist in large number. Secondly, by combining with existing WGS from Samoans, we will construct the first Polynesian-specific imputation reference panel. We will then impute and conduct the largest association study to date in >10,000 Polynesian individuals and >2,000 Micronesian individuals for obesity and T2D. Thirdly, we will evaluate the transferability of risk stratification models for obesity and T2D based on polygenic risk scores (PRS) in Native Hawaiians, determine the population genetic and non-genetic factors that may have contributed to the expected poor transferability of these models, and assess if Polynesian-specific summary statistics will improve the risk stratification models. Finally, we will conduct pilot studies in the form of focus groups to understand the concerns Native Hawaiian community may have in future participation of genomic research. The results from this proposal will help motivate and guide the design of future genomic studies in this understudied population, identify population-specific alleles influencing obesity and T2D, and improve future risk stratification models of diseases in Native Hawaiians and other Polynesian populations.