Authors

Jian Gong, Fred Hutchinson Cancer Center
Fredrick Schumacher, Keck School of Medicine of USC
Unhee Lim, University of Hawaiʻi Cancer Center
Lucia A. Hindorff, National Human Genome Research Institute (NHGRI)
Jeff Haessler, Fred Hutchinson Cancer Center
Steven Buyske, Rutgers University–New Brunswick
Christopher S. Carlson, Fred Hutchinson Cancer Center
Stephanie Rosse, Fred Hutchinson Cancer Center
Petra Bůžková, University of Washington
Myriam Fornage, McGovern Medical School
Myron Gross, Masonic Cancer Center
Nathan Pankratz, Masonic Cancer Center
James S. Pankow, School of Public Health
Pamela J. Schreiner, School of Public Health
Richard Cooper, Loyola University Chicago
Georg Ehret, Johns Hopkins University School of Medicine
C. Charles Gu, Washington University in St. Louis
Denise Houston, Wake Forest University School of Medicine
Marguerite R. Irvin, The University of Alabama at Birmingham
Rebecca Jackson, The Ohio State University Wexner Medical Center
Lew Kuller, University of Pittsburgh School of Medicine
Brian Henderson, Keck School of Medicine of USC
Iona Cheng, Cancer Prevention Institute of California
Lynne Wilkens, University of Hawaiʻi Cancer Center
Mark Leppert, University of Utah School of Medicine
Cora E. Lewis, UAB Department of Medicine
Rongling Li, National Human Genome Research Institute (NHGRI)
Khanh Dung H. Nguyen, Johns Hopkins University School of Medicine
Robert Goodloe, Vanderbilt University School of Medicine
Eric Farber-Eger, Vanderbilt University School of Medicine
Jonathan Boston, Vanderbilt University School of Medicine
Holli H. Dilks, Vanderbilt University School of Medicine
Marylyn D. Ritchie, Pennsylvania State University

Document Type

Article

Publication Date

10-3-2013

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 (r2 > 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. © 2013 The American Society of Human Genetics. All rights reserved.

Publication Source (Journal or Book title)

American Journal of Human Genetics

First Page

661

Last Page

671

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