Methods for Genome-wide Association Studies in Admixed Populations

混合人群全基因组关联研究的方法

基本信息

批准号：
8281417
负责人：
ALKES L PRICE
金额：
$ 51.5万
依托单位：
HARVARD SCHOOL OF PUBLIC HEALTH
依托单位国家：
美国
项目类别：
财政年份：
2011
资助国家：
美国
起止时间：
2011-06-15 至 2016-04-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8281417
关键词：
Accounting Address Admixture Affect African African American Area Asthma Cardiovascular Diseases Cardiovascular system Cohort Studies Collaborations Commit Communities Complex Computer software DNA Resequencing Data Data Set Databases Disease Ensure European Family Family Research Future Genes Genetic Genetic Heterogeneity Genome Genome Scan Genotype Goals Hawaii Heart Hispanics Incidence Individual Inherited Latino Letters Location Maintenance Maps Meta-Analysis Methods Minority Native Americans Phenotype Population Principal Component Analysis Publications Research Research Methodology Research Personnel Risk Running Sampling Scanning Signal Transduction South Africa Statistical Methods Stratification United States Variant Work base computer code disorder risk family structure genetic variant genome wide association study health disparity method development programs software development statistics tool

项目摘要

DESCRIPTION (provided by applicant): Genome-wide association studies (GWAS) have been successful in identifying common genetic variants contributing to disease risk. However, nearly all of these studies have been conducted in populations of European ancestry. It is important to include other populations, because GWAS in Europeans are unlikely to detect risk variants that are common only in non-European populations. In the United States, the majority of individuals of non-European ancestry belong to admixed populations (e.g. African Americans or Latinos) that inherit ancestry from more than one continental population. Existing GWAS methods for admixed populations are inadequate, because they do not incorporate both SNP association and admixture association signals. Thus, if existing methods are applied, analyses will not be fully powered and important variants will be missed. For diseases with known population differences-such as cardiovascular disease in African Americans and asthma in Latinos-the need to develop methods that combine these signals is particularly pressing, because admixture association signals are likely to be particularly important. Here, we propose to develop a complete set of methods and software to combine SNP and admixture association signals in GWAS in admixed populations, while addressing questions such as imputation and choosing SNPs for replication. Our goal is to make fully powered association studies in populations of mixed ancestry as practical as studies in populations of homogeneous ancestry. In addition to African Americans, we will also develop methods for complex admixed populations (e.g. Latinos) that inherit ancestry from three or more continental populations, and for related individuals from admixed populations. Our methods research will be driven by empirical data, including over 10,000 African American samples and 2,400 Latino samples that will be genome-scanned by the CARe consortium, the Jackson Heart Study, and the Multiethnic Cohort Study. Our work will be applicable not only to GWAS in admixed populations, but also to meta-analyses of European and admixed populations, as well as future resequencing-based studies.

描述（由申请人提供）：全基因组关联研究（GWAS）已成功识别出导致疾病风险的常见遗传变异。然而，几乎所有这些研究都是在欧洲血统人群中进行的。包括其他人群很重要，因为欧洲人的 GWAS 不太可能检测到仅在非欧洲人群中常见的风险变异。在美国，大多数非欧洲血统的人属于混合人群（例如非裔美国人或拉丁裔），他们继承了多个大陆人口的血统。现有的混合群体 GWAS 方法是不够的，因为它们没有结合 SNP 关联和混合关联信号。因此，如果应用现有方法，分析将无法充分发挥作用，并且会错过重要的变体。对于具有已知人群差异的疾病，例如非裔美国人的心血管疾病和拉丁美洲人的哮喘，开发结合这些信号的方法的需求尤为迫切，因为混合关联信号可能特别重要。在这里，我们建议开发一套完整的方法和软件，将 SNP 和混合群体中 GWAS 中的混合关联信号结合起来，同时解决插补和选择 SNP 进行复制等问题。我们的目标是对混合血统人群进行充分有力的关联研究，就像对同质血统人群的研究一样实用。除了非裔美国人之外，我们还将开发针对从三个或更多大陆人群继承祖先的复杂混合人群（例如拉丁裔）以及来自混合人群的相关个体的方法。我们的方法研究将由经验数据驱动，包括 10,000 多个非裔美国人样本和 2,400 个拉丁裔样本，这些样本将由 CARe 联盟、杰克逊心脏研究和多种族队列研究进行基因组扫描。我们的工作不仅适用于混合人群的 GWAS，还适用于欧洲和混合人群的荟萃分析，以及未来基于重测序的研究。