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Fine Mapping and Identification of BMI Loci in African Americans

机译:非洲裔美国人BMI基因座的精细定位和鉴定

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摘要

Genome-wide association studies (GWASs) primarily performed in European-ancestry (EA) populations have identified numerous loci associated with body mass index (BMI). However, it is still unclear whether these GWAS loci can be generalized to other ethnic groups, such as African Americans (AAs). Furthermore, the putative functional variant or variants in these loci mostly remain under investigation. The overall lower linkage disequilibrium in AA compared to EA populations provides the opportunity to narrow in or fine-map these BMI-related loci. Therefore, we used the Metabochip to densely genotype and evaluate 21 BMI GWAS loci identified in EA studies in 29,151 AAs from the Population Architecture using Genomics and Epidemiology (PAGE) study. Eight of the 21 loci (SEC16B, TMEM18, ETV5, GNPDA2, TFAP2B, BDNF, FTO, and MC4R) were found to be associated with BMI in AAs at 5.8 × 10(-5). Within seven out of these eight loci, we found that, on average, a substantially smaller number of variants was correlated (r(2) > 0.5) with the most significant SNP in AA than in EA populations (16 versus 55). Conditional analyses revealed GNPDA2 harboring a potential additional independent signal. Moreover, Metabochip-wide discovery analyses revealed two BMI-related loci, BRE (rs116612809, p = 3.6 × 10(-8)) and DHX34 (rs4802349, p = 1.2 × 10(-7)), which were significant when adjustment was made for the total number of SNPs tested across the chip. These results demonstrate that fine mapping in AAs is a powerful approach for both narrowing in on the underlying causal variants in known loci and discovering BMI-related loci.
机译:主要在欧洲血统(EA)人群中进行的全基因组关联研究(GWAS)已经确定了许多与体重指数(BMI)相关的基因座。但是,尚不清楚这些GWAS基因座是否可以推广到其他种族,例如非裔美国人(AAs)。此外,这些基因座中的一个或多个推定功能变体大部分仍在研究中。与EA群体相比,AA总体上较低的连锁不平衡性提供了缩小这些BMI相关基因座或对其进行精细定位的机会。因此,我们使用Metabochip进行密集的基因分型,并评估了使用基因组学和流行病学(PAGE)研究从29 151个AA中的EA研究中鉴定出的21个BMI GWAS基因座。发现21个基因座中的八个(SEC16B,TMEM18,ETV5,GNPDA2,TFAP2B,BDNF,FTO和MC4R)与5.8×10(-5)的AA中的BMI相关。在这八个基因座中的七个中,我们发现,与EA人群相比,AA中具有最高显着SNP的变体的数量要少得多(r(2)> 0.5)(16对55)。条件分析表明,GNPDA2具有潜在的附加独立信号。此外,在Metabochip范围内的发现分析中发现了两个与BMI相关的基因座BRE(rs116612809,p = 3.6×10(-8))和DHX34(rs4802349,p = 1.2×10(-7)),在进行调整时很重要表示整个芯片上测试的SNP总数。这些结果表明,AA中的精细定位对于缩小已知基因座中潜在的因果变体以及发现BMI相关基因座都是一种有效的方法。

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