| Literature DB >> 24094743 |
Jian Gong1, Fredrick Schumacher, Unhee Lim, Lucia A Hindorff, Jeff Haessler, Steven Buyske, Christopher S Carlson, Stephanie Rosse, Petra Bůžková, Myriam Fornage, Myron Gross, Nathan Pankratz, James S Pankow, Pamela J Schreiner, Richard Cooper, Georg Ehret, C Charles Gu, Denise Houston, Marguerite R Irvin, Rebecca Jackson, Lew Kuller, Brian Henderson, Iona Cheng, Lynne Wilkens, Mark Leppert, Cora E Lewis, Rongling Li, Khanh-Dung H Nguyen, Robert Goodloe, Eric Farber-Eger, Jonathan Boston, Holli H Dilks, Marylyn D Ritchie, Jay Fowke, Loreall Pooler, Misa Graff, Lindsay Fernandez-Rhodes, Barbara Cochrane, Eric Boerwinkle, Charles Kooperberg, Tara C Matise, Loic Le Marchand, Dana C Crawford, Christopher A Haiman, Kari E North, Ulrike Peters.
Abstract
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.Entities:
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Year: 2013 PMID: 24094743 PMCID: PMC3791273 DOI: 10.1016/j.ajhg.2013.08.012
Source DB: PubMed Journal: Am J Hum Genet ISSN: 0002-9297 Impact factor: 11.025