Leveraging ancestral diversity to map adiposity loci in Hispanics

描述(申请人提供)：肥胖是代谢和心血管疾病的主要危险因素，自20世纪80年代以来，肥胖的患病率增加了一倍多，其中少数民族人群负担最大。大规模全基因组关联研究(GWAS)已经确定了70个遗传位点，它们明确地与肥胖相关特征有关，主要是在欧洲血统人群中。到目前为止，还没有对西班牙裔/拉丁裔(HL)人群进行任何与肥胖相关的大规模GWA，尽管他们的肥胖率增加了。虽然被归类在一个“种族标签”下，但HL人群是令人难以置信的多样性和高度混合的基因，最近起源于欧洲，非洲和美洲。因此，全基因组关联将需要大量的合作努力和使用先进的统计方法(远远超出标准的GWAs分析)来解释和利用它们高度的遗传多样性。在这里，我们建议进行第一次大规模的基因组研究，以寻找HL人群中的肥胖易感基因。对于目标1，我们收集了世界上在HL人群中进行的GWAS研究，包括50,000名具有高密度SNP阵列数据的HL男性和女性。将基因组范围归因于1000基因组计划和其他独特的美洲印第安人资源中的多种族参考小组，将允许对HL人群中存在的常见和低频变异进行全面测试，并为解决HL亚群中肥胖相关基因座的遗传风险异质性提供丰富的资源。为了阐明AIM 2中种族/民族的可转移性和精细的关联信号，我们将利用来自大规模GWA的AA和EA人群中肥胖相关特征的数据，这些数据是我们通过与AA(n&>；50,000)和EA(巨型财团，n&>；200,000)联盟合作获得的。在目标3中，我们将使用果蝇的功能分析和生物信息数据挖掘工具来识别和表征目标基因和功能等位基因，并将其与生物途径联系起来。我们有得天独厚的条件和经验来建立一个大规模的合作来研究HLS中肥胖的基因组学。我们的建议也是独一无二的，并具有创新性，可以将GWAS研究带入下一个翻译阶段，并以实验研究为目标，进一步表征肥胖特定的遗传效应。我们的研究可能会提高对肥胖的基因组病因学的理解，这些知识可能被用来减轻服务不足和研究不足的少数民族人群的疾病负担。

DESCRIPTION (provided by applicant): Obesity is a leading risk factor for metabolic and cardiovascular diseases and its prevalence has more than doubled since the 1980's, with the greatest burden carried by minority populations. Large-scale genome-wide associations studies (GWAS) have identified >70 genetic loci that are unequivocally associated with obesity-related traits primarily in European descent populations. So far, no large-scale GWAS for any obesity-related traits have been performed in Hispanic /Latinos (HL) populations, despite their increased prevalence of obesity. Although classified under one 'ethnic label', HL populations are incredibly diverse and genetically highly admixed with recent origins from Europe, Africa and the Americas. Hence, genome-wide association will necessitate a large collaborative effort and the use of advanced statistical methods (that go far beyond standard GWAS analyses) to account for and leverage their high degree of genetic diversity. Here, we propose to perform the first large-scale genomic study in search of obesity-susceptibility loci in HL populations. For aim 1, we have assembled the world's GWAS studies in HL populations, including >50,000 HL men and women with high-density SNP array data. Genome-wide imputation to multiethnic reference panels from the 1000 Genomes Project and other unique Amerindian resources will allow for comprehensive testing of common and low frequency variation present in HL populations as well as provide a rich resource for addressing genetic risk heterogeneity at obesity-related loci across HL sub-populations. To elucidate racial/ethnic transferability and fine-map association signals in aim 2, we will leverage data from large-scale GWAS of obesity-related traits in AA and EA populations that are available to us through our work with AA (n>50,000) and EA (GIANT consortium, n>200,000) consortia. In aim 3, we will employ functional analyses in Drosophila and bioinformatic data-mining tools to identify and characterize the target genes and functional alleles, and link associations with biological pathways. We are uniquely positioned and experienced to establish a large-scale collaboration to study the genomics of obesity in HLs. Our proposal is also unique and innovative for taking a GWAS study to the next translational stage, with an experimental research aim for further characterization of obesity specific genetic effects. Our study may improve the understanding of the genomic etiology of obesity, knowledge which may be used to reduce the burden of disease in underserved and understudied minority populations.