Fine Mapping and Identification of BMI Loci in African Americans. Gong, J., Schumacher, F., Lim, U., Hindorff, L. A., Haessler, J., Buyske, S., Carlson, C. S., Rosse, S., B ̊u ̌zková, P., Fornage, M., Gross, M., Pankratz, N., Pankow, J. S., Schreiner, P. J., Cooper, R., Ehret, G., Gu, C. C., Houston, D., Irvin, M. R., Jackson, R., Kuller, L., Henderson, B., Cheng, I., Wilkens, L., Leppert, M., Lewis, C. E., Li, R., Nguyen, K. H., Goodloe, R., Farber-Eger, E., Boston, J., Dilks, H. H., Ritchie, M. D., Fowke, J., Pooler, L., Graff, M., Fernandez-Rhodes, L., Cochrane, B., Boerwinkle, E., Kooperberg, C., Matise, T. C., Le Marchand, L., Crawford, D. C., Haiman, C. A., North, K. E., & Peters, U. American journal of human genetics, 93:661–671, October, 2013. ![Fine Mapping and Identification of BMI Loci in African Americans. [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex 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.
@article{GongSchumacherLimEtAl2013a,
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.},
author = {Gong, Jian and Schumacher, Fredrick and Lim, Unhee and Hindorff, Lucia A. and Haessler, Jeff and Buyske, Steven and Carlson, Christopher S. and Rosse, Stephanie and B{\r u}{\v z}kov{\'a}, Petra and Fornage, Myriam and Gross, Myron and Pankratz, Nathan and Pankow, James S. and Schreiner, Pamela J. and Cooper, Richard and Ehret, Georg and Gu, C. Charles and Houston, Denise and Irvin, Marguerite R. and Jackson, Rebecca and Kuller, Lew and Henderson, Brian and Cheng, Iona and Wilkens, Lynne and Leppert, Mark and Lewis, Cora E. and Li, Rongling and Nguyen, Khanh-Dung H. and Goodloe, Robert and Farber-Eger, Eric and Boston, Jonathan and Dilks, Holli H. and Ritchie, Marylyn D. and Fowke, Jay and Pooler, Loreall and Graff, Misa and Fernandez-Rhodes, Lindsay and Cochrane, Barbara and Boerwinkle, Eric and Kooperberg, Charles and Matise, Tara C. and Le Marchand, Loic and Crawford, Dana C. and Haiman, Christopher A. and North, Kari E. and Peters, Ulrike},
citation-subset = {IM},
completed = {2014-02-19},
country = {United States},
doi = {10.1016/j.ajhg.2013.08.012},
issn = {1537-6605},
issn-linking = {0002-9297},
issue = {4},
journal = {American journal of human genetics},
keywords = {Adult; African Americans, genetics; Aged; Aged, 80 and over; Body Mass Index; Female; Genetic Loci; Genetic Predisposition to Disease; Genome, Human; Genome-Wide Association Study, methods; Genotype; Humans; Linkage Disequilibrium; Male; Middle Aged; Obesity, ethnology, genetics; Polymorphism, Single Nucleotide; Young Adult},
month = oct,
nlm-id = {0370475},
owner = {NLM},
pages = {661--671},
pii = {S0002-9297(13)00387-X},
pmc = {PMC3791273},
pmid = {24094743},
url = {https://pubmed.ncbi.nlm.nih.gov/24094743/},
pubmodel = {Print},
pubstate = {ppublish},
revised = {2020-08-24},
title = {Fine Mapping and Identification of {BMI} Loci in {African Americans}.},
volume = {93},
year = {2013},
bdsk-url-1 = {https://pubmed.ncbi.nlm.nih.gov/24094743/},
bdsk-url-2 = {https://doi.org/10.1016/j.ajhg.2013.08.012}}
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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. 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