@article {1345,
	title = {A phenomics-based strategy identifies loci on APOC1, BRAP, and PLCG1 associated with metabolic syndrome phenotype domains.},
	journal = {PLoS Genet},
	volume = {7},
	year = {2011},
	month = {2011 Oct},
	pages = {e1002322},
	abstract = {<p>Despite evidence of the clustering of metabolic syndrome components, current approaches for identifying unifying genetic mechanisms typically evaluate clinical categories that do not provide adequate etiological information. Here, we used data from 19,486 European American and 6,287 African American Candidate Gene Association Resource Consortium participants to identify loci associated with the clustering of metabolic phenotypes. Six phenotype domains (atherogenic dyslipidemia, vascular dysfunction, vascular inflammation, pro-thrombotic state, central obesity, and elevated plasma glucose) encompassing 19 quantitative traits were examined. Principal components analysis was used to reduce the dimension of each domain such that >55\% of the trait variance was represented within each domain. We then applied a statistically efficient and computational feasible multivariate approach that related eight principal components from the six domains to 250,000 imputed SNPs using an additive genetic model and including demographic covariates. In European Americans, we identified 606 genome-wide significant SNPs representing 19 loci. Many of these loci were associated with only one trait domain, were consistent with results in African Americans, and overlapped with published findings, for instance central obesity and FTO. However, our approach, which is applicable to any set of interval scale traits that is heritable and exhibits evidence of phenotypic clustering, identified three new loci in or near APOC1, BRAP, and PLCG1, which were associated with multiple phenotype domains. These pleiotropic loci may help characterize metabolic dysregulation and identify targets for intervention.</p>},
	keywords = {African Americans, Apolipoprotein C-I, Blood Glucose, Dyslipidemias, European Continental Ancestry Group, Genetic Association Studies, Genetic Predisposition to Disease, Genome, Human, Humans, Metabolic Syndrome, Obesity, Abdominal, Phenotype, Phospholipase C gamma, Polymorphism, Single Nucleotide, Quantitative Trait, Heritable, Ubiquitin-Protein Ligases, Vascular Diseases},
	issn = {1553-7404},
	doi = {10.1371/journal.pgen.1002322},
	author = {Avery, Christy L and He, Qianchuan and North, Kari E and Ambite, Jos{\'e} L and Boerwinkle, Eric and Fornage, Myriam and Hindorff, Lucia A and Kooperberg, Charles and Meigs, James B and Pankow, James S and Pendergrass, Sarah A and Psaty, Bruce M and Ritchie, Marylyn D and Rotter, Jerome I and Taylor, Kent D and Wilkens, Lynne R and Heiss, Gerardo and Lin, Dan Yu}
}
@article {6626,
	title = {Fine Mapping and Identification of BMI Loci in African Americans.},
	journal = {Am J Hum Genet},
	volume = {93},
	year = {2013},
	month = {2013 Oct 3},
	pages = {661-71},
	abstract = {<p>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~{\texttimes} 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~{\texttimes} 10(-8)) and DHX34 (rs4802349, p = 1.2~{\texttimes} 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.</p>},
	keywords = {Adult, African Americans, Aged, Aged, 80 and over, Body Mass Index, Female, Genetic Loci, Genetic Predisposition to Disease, Genome, Human, Genome-Wide Association Study, Genotype, Humans, Linkage Disequilibrium, Male, Middle Aged, Obesity, Polymorphism, Single Nucleotide, Young Adult},
	issn = {1537-6605},
	doi = {10.1016/j.ajhg.2013.08.012},
	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}zkov{\'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, Lo{\"\i}c and Crawford, Dana C and Haiman, Christopher A and North, Kari E and Peters, Ulrike}
}
