Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA.
Am J Hum Genet. 2013 Oct 3;93(4):661-71. doi: 10.1016/j.ajhg.2013.08.012.
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.
全基因组关联研究(GWAS)主要在欧洲血统(EA)人群中进行,已确定了许多与体重指数(BMI)相关的基因座。然而,这些 GWAS 基因座是否可以推广到其他族群,如非裔美国人(AA),仍然不清楚。此外,这些基因座中的假定功能变体或变体大多仍在研究中。与 EA 人群相比,AA 人群中的整体连锁不平衡程度较低,这为缩小或精细定位这些与 BMI 相关的基因座提供了机会。因此,我们使用 Metabochip 对来自基因与流行病学人群结构研究(PAGE)的 29151 名 AA 个体中的 21 个在 EA 研究中确定的与 BMI 相关的 GWAS 基因座进行高密度基因分型和评估。在 AA 中,21 个基因座中的 8 个(SEC16B、TMEM18、ETV5、GNPDA2、TFAP2B、BDNF、FTO 和 MC4R)在 5.8×10(-5)的水平下与 BMI 相关。在这 8 个基因座中的 7 个中,我们发现,平均而言,与 AA 人群中最显著 SNP 相关的变异数量要少得多(r(2) > 0.5),而在 EA 人群中则要多得多(16 个对 55 个)。条件分析显示 GNPDA2 可能含有一个额外的独立信号。此外,Metabochip 全基因组发现分析揭示了两个与 BMI 相关的基因座,BRE(rs116612809,p = 3.6×10(-8))和 DHX34(rs4802349,p = 1.2×10(-7)),当对芯片上测试的总 SNP 数量进行调整时,这两个基因座都具有显著性。这些结果表明,在 AA 中进行精细定位是一种有效的方法,既可以缩小已知基因座中潜在的因果变异,也可以发现与 BMI 相关的基因座。