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: 10275367
• 负责人: Charleston Chiang
• 金额: $ 39.35万
• 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/10275367
• 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; Hispanics; Human; Individual; Latino; Medical Genetics; Meta-Analysis; Modernization; Native Hawaiian; Non-Insulin-Dependent Diabetes Mellitus; Obesity; Performance; Phenotype; Polynesian; Population; Population Genetics; Population Heterogeneity; Positioning Attribute; Recording of previous events; Research; Resources; Risk; Thinking; Variant; clinical practice; disorder risk; ethnic minority population; 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.

项目摘要 /摘要 环境和遗传因素都导致人口之间疾病风险的差异。遗传 人群之间差异的原因与这些人群的进化历史密切相关。 因此，更好地纳入进化思维将有助于解释不同人群之间的差异 今天并改善临床实践和个性化护理。为此，清学实验室将继续发展 将进化人群遗传学与遗传流行病学相结合的综合框架 人类，利用经验数据分析和定量方法的发展来更好地探究 人口内和人群之间的复杂特征的遗传结构。这个综合框架包括 三个主要焦点：（1）人类复杂性状的遗传结构，（2）人口统计记录，（3） 人口的适应性历史。第一个主题中的研究介绍了对我们的遗传后果 今天的现象，而后两个研究解释了变化的进化机制 在人口内和人口之间出现。更重要的是，Chiang Lab的研究不仅仅关注 在这些主题上，但也利用一个信息来告知另一个。在这个范式中，朝安实验室 将在未来五年内关注以下三个目标。首先，我们将执行全面的遗传 研究计划，以解决夏威夷原住民的健康差异。具体来说，我们将生成 在该人群中加速遗传研究所必需的基因组资源。然后，我们将表征 夏威夷原住民的人口统计历史说明进行基因组研究的好处 研究的人群，对波利尼西亚人群进行大规模荟萃分析，以识别人口 与夏威夷原住民的疾病相关的特定等位基因，并与夏威夷当地人接触 社区未来的合作伙伴关系和合作。其次，我们将研究用于进化的病因 当今人口的风险升高。以拉丁裔人口为例，我们将检查是否 该人群中儿童白血病的风险升高是由于欧洲期间引入的选择性压力 16世纪的接触。第三，我们将通过 在个体中引入一个新的遗传相似性矩阵，该矩阵结合了家谱中的信息 人口树。该矩阵将改善许多统计遗传应用的性能， 例如遗传力估计和表型推出。当我们使用夏威夷原住民和拉丁美洲人 该提案中的人群示例，这种遗传流行病学和进化的综合框架也将 受益于其他研究少数族裔的未来研究。我们在实现这些方面有独特的位置 目标是因为我们在将人口遗传原理与医学遗传分析相结合的专业知识和 统计遗传发展。