An evolutionary framework to elucidate and interpret the genetic architecture of complex traits in diverse populations

阐明和解释不同人群复杂性状遗传结构的进化框架

• 批准号: 10458746
• 负责人: Charleston Chiang
• 金额: $ 40.98万
• 依托单位: UNIVERSITY OF SOUTHERN CALIFORNIA
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-08-01 至 2026-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10458746
• 关键词: Address; Alleles; Childhood Leukemia; Collaborations; Communities; Complex; Data Analyses; Development; Disease; Etiology; European; Future; Genealogical Tree; Genetic; Genetic Research; Genomics; Goals; Heritability; Human; Individual; Latino Population; Medical Genetics; Meta-Analysis; Modernization; Native Hawaiian; Non-Insulin-Dependent Diabetes Mellitus; Obesity; Performance; Persons; Phenotype; Polynesian; Population; Population Genetics; Population Heterogeneity; Positioning Attribute; Recording of previous events; Research; Resources; Risk; Thinking; Variant; clinical practice; disorder risk; ethnic minority; experience; genetic analysis; genetic architecture; genetic epidemiology; genetic evolution; health disparity; improved; method development; personalized care; phenome; pressure; programs; trait

Project Summary / Abstract Both environmental and genetic factors contribute to disparity in disease risks between populations. The genetic causes of differences between populations are intimately tied to the evolutionary histories of these populations. Therefore, a better incorporation of evolutionary thinking will help explain the disparity among diverse populations today and improve clinical practices and personalized care. To this end, the Chiang Lab will continue to develop an integrative framework combining evolutionary population genetics with genetic epidemiology in humans, utilizing both empirical data analysis and quantitative methods development to better probe into the genetic architecture of complex traits within and between populations. This integrative framework consists of three main foci: (1) the genetic architecture of human complex traits, (2) the demographic history, and (3) the adaptive history of human populations. Research in the first topic informs the genetic consequences on our phenome today, while research in the latter two explains the evolutionary mechanisms through which variation arise within and between human populations. More importantly, research from the Chiang Lab focuses not solely on these topics, but also leverages information on one to inform the other. Within this paradigm, the Chiang Lab will focus on the following three goals over the next five years. First, we will execute a comprehensive genetic research program to address the health disparities in Native Hawaiians. Specifically, we will generate the genomic resources necessary to accelerate genetic research in this population. We will then characterize the demographic history of the Native Hawaiians to illustrate the benefit of conducting genomic studies in understudied populations, perform large-scale meta-analysis in Polynesian populations to identify population- specific alleles associated with diseases prevalent in Native Hawaiians, and engage the Native Hawaiian community for future partnership and collaborations. Second, we will investigate the evolutionary etiology for elevated risk in present-day populations. Using Latino population as an example, we will examine if the elevated risk in childhood leukemia in this population is due to the selective pressure introduced during European contact in the 16th century. Third, we will revolutionize the current concept of genetic relatedness by introducing a new genetic similarity matrix among individuals that incorporates information from the genealogical tree of the population. This matrix will improve the performance of a number of statistical genetic applications, such as heritability estimation and phenotype imputation. While we used Native Hawaiians and Latinos as example populations in this proposal, this integrated framework of genetic epidemiology and evolution will also benefit future research in other understudied ethnic minorities. We are uniquely positioned to achieve these goals because of our expertise in combining population genetic principles with medical genetic analysis and statistical genetic development.

项目总结/摘要 环境和遗传因素都造成了人群之间疾病风险的差异。遗传 种群间差异的原因与这些种群的进化历史密切相关。 因此，更好地纳入进化思想将有助于解释不同人群之间的差异 并改善临床实践和个性化护理。为此，Chiang Lab将继续发展 结合进化群体遗传学和遗传流行病学的综合框架， 人类，利用经验数据分析和定量方法的发展，以更好地探讨 复杂性状在种群内和种群间的遗传结构。这一综合框架包括： 三个主要焦点：（1）人类复杂性状的遗传结构，（2）人口统计学史，（3） 人类的适应史第一个主题中的研究告知了我们的遗传后果， 后两者的研究解释了变异的进化机制， 发生在人类内部和人类之间。更重要的是，Chiang Lab的研究不仅关注 在这些主题上，而且还利用一个方面的信息来通知另一个方面。在这种模式下，Chiang Lab 在今后五年中，将重点实现以下三个目标。首先，我们将执行全面的遗传 研究计划，以解决夏威夷土著人的健康差距。具体来说，我们将生成 基因组资源，以加速在这一人群中的遗传研究。然后我们将描述 夏威夷原住民的人口历史，以说明在夏威夷进行基因组研究的好处。 研究不足的人群，在波利尼西亚人群中进行大规模荟萃分析，以确定人群- 与夏威夷原住民中流行的疾病相关的特定等位基因，并使夏威夷原住民 未来的合作与合作。第二，我们将研究进化的病因， 在当今的人群中，风险更高。以拉丁裔人口为例，我们将研究 这一人群中儿童白血病的风险升高是由于欧洲癌症研究期间引入的选择性压力。 世纪的接触。第三，我们将彻底改变目前的遗传相关性的概念， 在个体之间引入新的遗传相似性矩阵，该矩阵包含来自系谱的信息， 人口的树。该矩阵将提高许多统计遗传应用程序的性能， 例如遗传力估计和表型插补。当我们用夏威夷土著和拉丁美洲人作为 在这个建议中，这个遗传流行病学和进化的综合框架也将 有利于未来在其他未充分研究的少数民族的研究。我们处于独特的地位，以实现这些目标 目标，因为我们的专业知识相结合的人口遗传学原则与医学遗传分析， 统计遗传学发展。