@article {1288, title = {Enhanced statistical tests for GWAS in admixed populations: assessment using African Americans from CARe and a Breast Cancer Consortium.}, journal = {PLoS Genet}, volume = {7}, year = {2011}, month = {2011 Apr}, pages = {e1001371}, abstract = {

While genome-wide association studies (GWAS) have primarily examined populations of European ancestry, more recent studies often involve additional populations, including admixed populations such as African Americans and Latinos. In admixed populations, linkage disequilibrium (LD) exists both at a fine scale in ancestral populations and at a coarse scale (admixture-LD) due to chromosomal segments of distinct ancestry. Disease association statistics in admixed populations have previously considered SNP association (LD mapping) or admixture association (mapping by admixture-LD), but not both. Here, we introduce a new statistical framework for combining SNP and admixture association in case-control studies, as well as methods for local ancestry-aware imputation. We illustrate the gain in statistical power achieved by these methods by analyzing data of 6,209 unrelated African Americans from the CARe project genotyped on the Affymetrix 6.0 chip, in conjunction with both simulated and real phenotypes, as well as by analyzing the FGFR2 locus using breast cancer GWAS data from 5,761 African-American women. We show that, at typed SNPs, our method yields an 8\% increase in statistical power for finding disease risk loci compared to the power achieved by standard methods in case-control studies. At imputed SNPs, we observe an 11\% increase in statistical power for mapping disease loci when our local ancestry-aware imputation framework and the new scoring statistic are jointly employed. Finally, we show that our method increases statistical power in regions harboring the causal SNP in the case when the causal SNP is untyped and cannot be imputed. Our methods and our publicly available software are broadly applicable to GWAS in admixed populations.

}, keywords = {African Americans, Algorithms, Breast Neoplasms, Chromosome Mapping, Coronary Disease, Diabetes Mellitus, Type 2, Female, Gene Frequency, Genetic Variation, Genetics, Population, Genome, Human, Genome-Wide Association Study, Genotype, Humans, Linkage Disequilibrium, Male, Odds Ratio, Phenotype, Polymorphism, Single Nucleotide, Principal Component Analysis, Receptor, Fibroblast Growth Factor, Type 2, Software}, issn = {1553-7404}, doi = {10.1371/journal.pgen.1001371}, author = {Pasaniuc, Bogdan and Zaitlen, Noah and Lettre, Guillaume and Chen, Gary K and Tandon, Arti and Kao, W H Linda and Ruczinski, Ingo and Fornage, Myriam and Siscovick, David S and Zhu, Xiaofeng and Larkin, Emma and Lange, Leslie A and Cupples, L Adrienne and Yang, Qiong and Akylbekova, Ermeg L and Musani, Solomon K and Divers, Jasmin and Mychaleckyj, Joe and Li, Mingyao and Papanicolaou, George J and Millikan, Robert C and Ambrosone, Christine B and John, Esther M and Bernstein, Leslie and Zheng, Wei and Hu, Jennifer J and Ziegler, Regina G and Nyante, Sarah J and Bandera, Elisa V and Ingles, Sue A and Press, Michael F and Chanock, Stephen J and Deming, Sandra L and Rodriguez-Gil, Jorge L and Palmer, Cameron D and Buxbaum, Sarah and Ekunwe, Lynette and Hirschhorn, Joel N and Henderson, Brian E and Myers, Simon and Haiman, Christopher A and Reich, David and Patterson, Nick and Wilson, James G and Price, Alkes L} } @article {1303, title = {Genetic determinants of lipid traits in diverse populations from the population architecture using genomics and epidemiology (PAGE) study.}, journal = {PLoS Genet}, volume = {7}, year = {2011}, month = {2011 Jun}, pages = {e1002138}, abstract = {

For the past five years, genome-wide association studies (GWAS) have identified hundreds of common variants associated with human diseases and traits, including high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and triglyceride (TG) levels. Approximately 95 loci associated with lipid levels have been identified primarily among populations of European ancestry. The Population Architecture using Genomics and Epidemiology (PAGE) study was established in 2008 to characterize GWAS-identified variants in diverse population-based studies. We genotyped 49 GWAS-identified SNPs associated with one or more lipid traits in at least two PAGE studies and across six racial/ethnic groups. We performed a meta-analysis testing for SNP associations with fasting HDL-C, LDL-C, and ln(TG) levels in self-identified European American (~20,000), African American (~9,000), American Indian (~6,000), Mexican American/Hispanic (~2,500), Japanese/East Asian (~690), and Pacific Islander/Native Hawaiian (~175) adults, regardless of lipid-lowering medication use. We replicated 55 of 60 (92\%) SNP associations tested in European Americans at p<0.05. Despite sufficient power, we were unable to replicate ABCA1 rs4149268 and rs1883025, CETP rs1864163, and TTC39B rs471364 previously associated with HDL-C and MAFB rs6102059 previously associated with LDL-C. Based on significance (p<0.05) and consistent direction of effect, a majority of replicated genotype-phentoype associations for HDL-C, LDL-C, and ln(TG) in European Americans generalized to African Americans (48\%, 61\%, and 57\%), American Indians (45\%, 64\%, and 77\%), and Mexican Americans/Hispanics (57\%, 56\%, and 86\%). Overall, 16 associations generalized across all three populations. For the associations that did not generalize, differences in effect sizes, allele frequencies, and linkage disequilibrium offer clues to the next generation of association studies for these traits.

}, keywords = {Adolescent, Adult, Aged, Aged, 80 and over, Continental Population Groups, Female, Gene Frequency, Genetics, Population, Genome-Wide Association Study, Humans, Linkage Disequilibrium, Lipid Metabolism, Lipoproteins, HDL, Lipoproteins, LDL, Male, Middle Aged, Molecular Epidemiology, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Risk Factors, Triglycerides, Young Adult}, issn = {1553-7404}, doi = {10.1371/journal.pgen.1002138}, author = {Dumitrescu, Logan and Carty, Cara L and Taylor, Kira and Schumacher, Fredrick R and Hindorff, Lucia A and Ambite, Jos{\'e} L and Anderson, Garnet and Best, Lyle G and Brown-Gentry, Kristin and B{\r u}zkov{\'a}, Petra and Carlson, Christopher S and Cochran, Barbara and Cole, Shelley A and Devereux, Richard B and Duggan, Dave and Eaton, Charles B and Fornage, Myriam and Franceschini, Nora and Haessler, Jeff and Howard, Barbara V and Johnson, Karen C and Laston, Sandra and Kolonel, Laurence N and Lee, Elisa T and MacCluer, Jean W and Manolio, Teri A and Pendergrass, Sarah A and Quibrera, Miguel and Shohet, Ralph V and Wilkens, Lynne R and Haiman, Christopher A and Le Marchand, Lo{\"\i}c and Buyske, Steven and Kooperberg, Charles and North, Kari E and Crawford, Dana C} } @article {1313, title = {The Next PAGE in understanding complex traits: design for the analysis of Population Architecture Using Genetics and Epidemiology (PAGE) Study.}, journal = {Am J Epidemiol}, volume = {174}, year = {2011}, month = {2011 Oct 01}, pages = {849-59}, abstract = {

Genetic studies have identified thousands of variants associated with complex traits. However, most association studies are limited to populations of European descent and a single phenotype. The Population Architecture using Genomics and Epidemiology (PAGE) Study was initiated in 2008 by the National Human Genome Research Institute to investigate the epidemiologic architecture of well-replicated genetic variants associated with complex diseases in several large, ethnically diverse population-based studies. Combining DNA samples and hundreds of phenotypes from multiple cohorts, PAGE is well-suited to address generalization of associations and variability of effects in diverse populations; identify genetic and environmental modifiers; evaluate disease subtypes, intermediate phenotypes, and biomarkers; and investigate associations with novel phenotypes. PAGE investigators harmonize phenotypes across studies where possible and perform coordinated cohort-specific analyses and meta-analyses. PAGE researchers are genotyping thousands of genetic variants in up to 121,000 DNA samples from African-American, white, Hispanic/Latino, Asian/Pacific Islander, and American Indian participants. Initial analyses will focus on single nucleotide polymorphisms (SNPs) associated with obesity, lipids, cardiovascular disease, type 2 diabetes, inflammation, various cancers, and related biomarkers. PAGE SNPs are also assessed for pleiotropy using the "phenome-wide association study" approach, testing each SNP for associations with hundreds of phenotypes. PAGE data will be deposited into the National Center for Biotechnology Information{\textquoteright}s Database of Genotypes and Phenotypes and made available via a custom browser.

}, keywords = {Epidemiologic Methods, Epidemiologic Research Design, Ethnic Groups, Genetic Association Studies, Genetics, Population, Genome-Wide Association Study, Humans, Interinstitutional Relations, Multifactorial Inheritance, National Human Genome Research Institute (U.S.), Phenotype, Pilot Projects, Research Design, Risk Factors, United States}, issn = {1476-6256}, doi = {10.1093/aje/kwr160}, author = {Matise, Tara C and Ambite, Jose Luis and Buyske, Steven and Carlson, Christopher S and Cole, Shelley A and Crawford, Dana C and Haiman, Christopher A and Heiss, Gerardo and Kooperberg, Charles and Marchand, Loic Le and Manolio, Teri A and North, Kari E and Peters, Ulrike and Ritchie, Marylyn D and Hindorff, Lucia A and Haines, Jonathan L} } @article {6633, title = {Consistent directions of effect for established type 2 diabetes risk variants across populations: the population architecture using Genomics and Epidemiology (PAGE) Consortium.}, journal = {Diabetes}, volume = {61}, year = {2012}, month = {2012 Jun}, pages = {1642-7}, abstract = {

Common genetic risk variants for type 2 diabetes (T2D) have primarily been identified in populations of European and Asian ancestry. We tested whether the direction of association with 20 T2D risk variants generalizes across six major racial/ethnic groups in the U.S. as part of the Population Architecture using Genomics and Epidemiology Consortium (16,235 diabetes case and 46,122 control subjects of European American, African American, Hispanic, East Asian, American Indian, and Native Hawaiian ancestry). The percentage of positive (odds ratio [OR] >1 for putative risk allele) associations ranged from 69\% in American Indians to 100\% in European Americans. Of the nine variants where we observed significant heterogeneity of effect by racial/ethnic group (P(heterogeneity) < 0.05), eight were positively associated with risk (OR >1) in at least five groups. The marked directional consistency of association observed for most genetic variants across populations implies a shared functional common variant in each region. Fine-mapping of all loci will be required to reveal markers of risk that are important within and across populations.

}, keywords = {Adult, Aged, Aged, 80 and over, Alleles, Diabetes Mellitus, Type 2, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Genotype, Humans, Male, Metagenomics, Middle Aged, Population Groups, Risk, Risk Factors}, issn = {1939-327X}, doi = {10.2337/db11-1296}, author = {Haiman, Christopher A and Fesinmeyer, Megan D and Spencer, Kylee L and B{\r u}zkov{\'a}, Petra and Voruganti, V Saroja and Wan, Peggy and Haessler, Jeff and Franceschini, Nora and Monroe, Kristine R and Howard, Barbara V and Jackson, Rebecca D and Florez, Jose C and Kolonel, Laurence N and Buyske, Steven and Goodloe, Robert J and Liu, Simin and Manson, JoAnn E and Meigs, James B and Waters, Kevin and Mukamal, Kenneth J and Pendergrass, Sarah A and Shrader, Peter and Wilkens, Lynne R and Hindorff, Lucia A and Ambite, Jose Luis and North, Kari E and Peters, Ulrike and Crawford, Dana C and Le Marchand, Lo{\"\i}c and Pankow, James S} } @article {6634, title = {Evaluation of the metabochip genotyping array in African Americans and implications for fine mapping of GWAS-identified loci: the PAGE study.}, journal = {PLoS One}, volume = {7}, year = {2012}, month = {2012}, pages = {e35651}, abstract = {

The Metabochip is a custom genotyping array designed for replication and fine mapping of metabolic, cardiovascular, and anthropometric trait loci and includes low frequency variation content identified from the 1000 Genomes Project. It has 196,725 SNPs concentrated in 257 genomic regions. We evaluated the Metabochip in 5,863 African Americans; 89\% of all SNPs passed rigorous quality control with a call rate of 99.9\%. Two examples illustrate the value of fine mapping with the Metabochip in African-ancestry populations. At CELSR2/PSRC1/SORT1, we found the strongest associated SNP for LDL-C to be rs12740374 (p = 3.5 {\texttimes} 10(-11)), a SNP indistinguishable from multiple SNPs in European ancestry samples due to high correlation. Its distinct signal supports functional studies elsewhere suggesting a causal role in LDL-C. At CETP we found rs17231520, with risk allele frequency 0.07 in African Americans, to be associated with HDL-C (p = 7.2 {\texttimes} 10(-36)). This variant is very rare in Europeans and not tagged in common GWAS arrays, but was identified as associated with HDL-C in African Americans in a single-gene study. Our results, one narrowing the risk interval and the other revealing an associated variant not found in Europeans, demonstrate the advantages of high-density genotyping of common and rare variation for fine mapping of trait loci in African American samples.

}, keywords = {African Americans, Cardiovascular Diseases, Cholesterol Ester Transfer Proteins, Cholesterol, HDL, Cholesterol, LDL, Chromosomes, Human, Cohort Studies, Gene Frequency, Genome-Wide Association Study, Genotype, Humans, Metabolic Diseases, Polymorphism, Single Nucleotide, Quantitative Trait Loci}, issn = {1932-6203}, doi = {10.1371/journal.pone.0035651}, author = {Buyske, Steven and Wu, Ying and Carty, Cara L and Cheng, Iona and Assimes, Themistocles L and Dumitrescu, Logan and Hindorff, Lucia A and Mitchell, Sabrina and Ambite, Jose Luis and Boerwinkle, Eric and B{\r u}zkov{\'a}, Petra and Carlson, Chris S and Cochran, Barbara and Duggan, David and Eaton, Charles B and Fesinmeyer, Megan D and Franceschini, Nora and Haessler, Jeffrey and Jenny, Nancy and Kang, Hyun Min and Kooperberg, Charles and Lin, Yi and Le Marchand, Lo{\"\i}c and Matise, Tara C and Robinson, Jennifer G and Rodriguez, Carlos and Schumacher, Fredrick R and Voight, Benjamin F and Young, Alicia and Manolio, Teri A and Mohlke, Karen L and Haiman, Christopher A and Peters, Ulrike and Crawford, Dana C and North, Kari E} } @article {6083, title = {Fine-mapping and initial characterization of QT interval loci in African Americans.}, journal = {PLoS Genet}, volume = {8}, year = {2012}, month = {2012}, pages = {e1002870}, abstract = {

The QT interval (QT) is heritable and its prolongation is a risk factor for ventricular tachyarrhythmias and sudden death. Most genetic studies of QT have examined European ancestral populations; however, the increased genetic diversity in African Americans provides opportunities to narrow association signals and identify population-specific variants. We therefore evaluated 6,670 SNPs spanning eleven previously identified QT loci in 8,644 African American participants from two Population Architecture using Genomics and Epidemiology (PAGE) studies: the Atherosclerosis Risk in Communities study and Women{\textquoteright}s Health Initiative Clinical Trial. Of the fifteen known independent QT variants at the eleven previously identified loci, six were significantly associated with QT in African American populations (P<=1.20{\texttimes}10(-4)): ATP1B1, PLN1, KCNQ1, NDRG4, and two NOS1AP independent signals. We also identified three population-specific signals significantly associated with QT in African Americans (P<=1.37{\texttimes}10(-5)): one at NOS1AP and two at ATP1B1. Linkage disequilibrium (LD) patterns in African Americans assisted in narrowing the region likely to contain the functional variants for several loci. For example, African American LD patterns showed that 0 SNPs were in LD with NOS1AP signal rs12143842, compared with European LD patterns that indicated 87 SNPs, which spanned 114.2 Kb, were in LD with rs12143842. Finally, bioinformatic-based characterization of the nine African American signals pointed to functional candidates located exclusively within non-coding regions, including predicted binding sites for transcription factors such as TBX5, which has been implicated in cardiac structure and conductance. In this detailed evaluation of QT loci, we identified several African Americans SNPs that better define the association with QT and successfully narrowed intervals surrounding established loci. These results demonstrate that the same loci influence variation in QT across multiple populations, that novel signals exist in African Americans, and that the SNPs identified as strong candidates for functional evaluation implicate gene regulatory dysfunction in QT prolongation.

}, keywords = {African Americans, Aged, Computational Biology, Electrocardiography, European Continental Ancestry Group, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Linkage Disequilibrium, Male, Metagenomics, Middle Aged, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Quantitative Trait, Heritable, Risk Factors, Tachycardia, United States}, issn = {1553-7404}, doi = {10.1371/journal.pgen.1002870}, author = {Avery, Christy L and Sethupathy, Praveen and Buyske, Steven and He, Qianchuan and Lin, Dan-Yu and Arking, Dan E and Carty, Cara L and Duggan, David and Fesinmeyer, Megan D and Hindorff, Lucia A and Jeff, Janina M and Klein, Liviu and Patton, Kristen K and Peters, Ulrike and Shohet, Ralph V and Sotoodehnia, Nona and Young, Alicia M and Kooperberg, Charles and Haiman, Christopher A and Mohlke, Karen L and Whitsel, Eric A and North, Kari E} } @article {6065, title = {Effects of smoking on the genetic risk of obesity: the population architecture using genomics and epidemiology study.}, journal = {BMC Med Genet}, volume = {14}, year = {2013}, month = {2013 Jan 11}, pages = {6}, abstract = {

BACKGROUND: Although smoking behavior is known to affect body mass index (BMI), the potential for smoking to influence genetic associations with BMI is largely unexplored.

METHODS: As part of the {\textquoteright}Population Architecture using Genomics and Epidemiology (PAGE){\textquoteright} Consortium, we investigated interaction between genetic risk factors associated with BMI and smoking for 10 single nucleotide polymorphisms (SNPs) previously identified in genome-wide association studies. We included 6 studies with a total of 56,466 subjects (16,750 African Americans (AA) and 39,716 European Americans (EA)). We assessed effect modification by testing an interaction term for each SNP and smoking (current vs. former/never) in the linear regression and by stratified analyses.

RESULTS: We did not observe strong evidence for interactions and only observed two interactions with p-values <0.1: for rs6548238/TMEM18, the risk allele (C) was associated with BMI only among AA females who were former/never smokers (β = 0.018, p = 0.002), vs. current smokers (β = 0.001, p = 0.95, p(interaction) = 0.10). For rs9939609/FTO, the A allele was more strongly associated with BMI among current smoker EA females (β = 0.017, p = 3.5 x 10(-5)), vs. former/never smokers (β = 0.006, p = 0.05, p(interaction) = 0.08).

CONCLUSIONS: These analyses provide limited evidence that smoking status may modify genetic effects of previously identified genetic risk factors for BMI. Larger studies are needed to follow up our results.

CLINICAL TRIAL REGISTRATION: NCT00000611.

}, keywords = {Adolescent, Adult, African Americans, Aged, Alpha-Ketoglutarate-Dependent Dioxygenase FTO, Body Mass Index, European Continental Ancestry Group, Female, Genetic Predisposition to Disease, Humans, Male, Membrane Proteins, Middle Aged, Obesity, Polymorphism, Single Nucleotide, Proteins, Risk Factors, Smoking, Young Adult}, issn = {1471-2350}, doi = {10.1186/1471-2350-14-6}, author = {Fesinmeyer, Megan D and North, Kari E and Lim, Unhee and B{\r u}zkov{\'a}, Petra and Crawford, Dana C and Haessler, Jeffrey and Gross, Myron D and Fowke, Jay H and Goodloe, Robert and Love, Shelley-Ann and Graff, Misa and Carlson, Christopher S and Kuller, Lewis H and Matise, Tara C and Hong, Ching-Ping and Henderson, Brian E and Allen, Melissa and Rohde, Rebecca R and Mayo, Ping and Schnetz-Boutaud, Nathalie and Monroe, Kristine R and Ritchie, Marylyn D and Prentice, Ross L and Kolonel, Lawrence N and Manson, JoAnn E and Pankow, James and Hindorff, Lucia A and Franceschini, Nora and Wilkens, Lynne R and Haiman, Christopher A and Le Marchand, Lo{\"\i}c and Peters, Ulrike} } @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 = {

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.

}, 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} } @article {6289, title = {Generalization and dilution of association results from European GWAS in populations of non-European ancestry: the PAGE study.}, journal = {PLoS Biol}, volume = {11}, year = {2013}, month = {2013 Sep}, pages = {e1001661}, abstract = {

The vast majority of genome-wide association study (GWAS) findings reported to date are from populations with European Ancestry (EA), and it is not yet clear how broadly the genetic associations described will generalize to populations of diverse ancestry. The Population Architecture Using Genomics and Epidemiology (PAGE) study is a consortium of multi-ancestry, population-based studies formed with the objective of refining our understanding of the genetic architecture of common traits emerging from GWAS. In the present analysis of five common diseases and traits, including body mass index, type 2 diabetes, and lipid levels, we compare direction and magnitude of effects for GWAS-identified variants in multiple non-EA populations against EA findings. We demonstrate that, in all populations analyzed, a significant majority of GWAS-identified variants have allelic associations in the same direction as in EA, with none showing a statistically significant effect in the opposite direction, after adjustment for multiple testing. However, 25\% of tagSNPs identified in EA GWAS have significantly different effect sizes in at least one non-EA population, and these differential effects were most frequent in African Americans where all differential effects were diluted toward the null. We demonstrate that differential LD between tagSNPs and functional variants within populations contributes significantly to dilute effect sizes in this population. Although most variants identified from GWAS in EA populations generalize to all non-EA populations assessed, genetic models derived from GWAS findings in EA may generate spurious results in non-EA populations due to differential effect sizes. Regardless of the origin of the differential effects, caution should be exercised in applying any genetic risk prediction model based on tagSNPs outside of the ancestry group in which it was derived. Models based directly on functional variation may generalize more robustly, but the identification of functional variants remains challenging.

}, keywords = {African Americans, Asian Americans, Body Mass Index, Diabetes Mellitus, Type 2, European Continental Ancestry Group, Gene Frequency, Genetic Predisposition to Disease, Genetic Variation, Genome-Wide Association Study, Hispanic Americans, Humans, Indians, North American, Lipids, Metagenomics, Oceanic Ancestry Group, Polymorphism, Single Nucleotide}, issn = {1545-7885}, doi = {10.1371/journal.pbio.1001661}, author = {Carlson, Christopher S and Matise, Tara C and North, Kari E and Haiman, Christopher A and Fesinmeyer, Megan D and Buyske, Steven and Schumacher, Fredrick R and Peters, Ulrike and Franceschini, Nora and Ritchie, Marylyn D and Duggan, David J and Spencer, Kylee L and Dumitrescu, Logan and Eaton, Charles B and Thomas, Fridtjof and Young, Alicia and Carty, Cara and Heiss, Gerardo and Le Marchand, Lo{\"\i}c and Crawford, Dana C and Hindorff, Lucia A and Kooperberg, Charles L} } @article {6631, title = {Genetic risk factors for BMI and obesity in an ethnically diverse population: results from the population architecture using genomics and epidemiology (PAGE) study.}, journal = {Obesity (Silver Spring)}, volume = {21}, year = {2013}, month = {2013 Apr}, pages = {835-46}, abstract = {

OBJECTIVE: Several genome-wide association studies (GWAS) have demonstrated that common genetic variants contribute to obesity. However, studies of this complex trait have focused on ancestrally European populations, despite the high prevalence of obesity in some minority groups.

DESIGN AND METHODS: As part of the "Population Architecture using Genomics and Epidemiology (PAGE)" Consortium, we investigated the association between 13 GWAS-identified single-nucleotide polymorphisms (SNPs) and BMI and obesity in 69,775 subjects, including 6,149 American Indians, 15,415 African-Americans, 2,438 East Asians, 7,346 Hispanics, 604 Pacific Islanders, and 37,823 European Americans. For the BMI-increasing allele of each SNP, we calculated β coefficients using linear regression (for BMI) and risk estimates using logistic regression (for obesity defined as BMI >= 30) followed by fixed-effects meta-analysis to combine results across PAGE sites. Analyses stratified by racial/ethnic group assumed an additive genetic model and were adjusted for age, sex, and current smoking. We defined "replicating SNPs" (in European Americans) and "generalizing SNPs" (in other racial/ethnic groups) as those associated with an allele frequency-specific increase in BMI.

RESULTS: By this definition, we replicated 9/13 SNP associations (5 out of 8 loci) in European Americans. We also generalized 8/13 SNP associations (5/8 loci) in East Asians, 7/13 (5/8 loci) in African Americans, 6/13 (4/8 loci) in Hispanics, 5/8 in Pacific Islanders (5/8 loci), and 5/9 (4/8 loci) in American Indians.

CONCLUSION: Linkage disequilibrium patterns suggest that tagSNPs selected for European Americans may not adequately tag causal variants in other ancestry groups. Accordingly, fine-mapping in large samples is needed to comprehensively explore these loci in diverse populations.

}, keywords = {Alleles, Body Mass Index, Ethnic Groups, Gene Frequency, Genetic Loci, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Linkage Disequilibrium, Metagenomics, Obesity, Phenotype, Polymorphism, Single Nucleotide, Risk Factors}, issn = {1930-739X}, doi = {10.1002/oby.20268}, author = {Fesinmeyer, Megan D and North, Kari E and Ritchie, Marylyn D and Lim, Unhee and Franceschini, Nora and Wilkens, Lynne R and Gross, Myron D and B{\r u}zkov{\'a}, Petra and Glenn, Kimberly and Quibrera, P Miguel and Fernandez-Rhodes, Lindsay and Li, Qiong and Fowke, Jay H and Li, Rongling and Carlson, Christopher S and Prentice, Ross L and Kuller, Lewis H and Manson, JoAnn E and Matise, Tara C and Cole, Shelley A and Chen, Christina T L and Howard, Barbara V and Kolonel, Laurence N and Henderson, Brian E and Monroe, Kristine R and Crawford, Dana C and Hindorff, Lucia A and Buyske, Steven and Haiman, Christopher A and Le Marchand, Lo{\"\i}c and Peters, Ulrike} } @article {6290, title = {Genetic variants associated with fasting glucose and insulin concentrations in an ethnically diverse population: results from the Population Architecture using Genomics and Epidemiology (PAGE) study.}, journal = {BMC Med Genet}, volume = {14}, year = {2013}, month = {2013 Sep 25}, pages = {98}, abstract = {

BACKGROUND: Multiple genome-wide association studies (GWAS) within European populations have implicated common genetic variants associated with insulin and glucose concentrations. In contrast, few studies have been conducted within minority groups, which carry the highest burden of impaired glucose homeostasis and type 2 diabetes in the U.S.

METHODS: As part of the {\textquoteright}Population Architecture using Genomics and Epidemiology (PAGE) Consortium, we investigated the association of up to 10 GWAS-identified single nucleotide polymorphisms (SNPs) in 8 genetic regions with glucose or insulin concentrations in up to 36,579 non-diabetic subjects including 23,323 European Americans (EA) and 7,526 African Americans (AA), 3,140 Hispanics, 1,779 American Indians (AI), and 811 Asians. We estimated the association between each SNP and fasting glucose or log-transformed fasting insulin, followed by meta-analysis to combine results across PAGE sites.

RESULTS: Overall, our results show that 9/9 GWAS SNPs are associated with glucose in EA (p = 0.04 to 9 {\texttimes} 10-15), versus 3/9 in AA (p= 0.03 to 6 {\texttimes} 10-5), 3/4 SNPs in Hispanics, 2/4 SNPs in AI, and 1/2 SNPs in Asians. For insulin we observed a significant association with rs780094/GCKR in EA, Hispanics and AI only.

CONCLUSIONS: Generalization of results across multiple racial/ethnic groups helps confirm the relevance of some of these loci for glucose and insulin metabolism. Lack of association in non-EA groups may be due to insufficient power, or to unique patterns of linkage disequilibrium.

}, keywords = {Adaptor Proteins, Signal Transducing, Adult, African Americans, Aged, Alleles, Asian Continental Ancestry Group, Blood Glucose, Diabetes Mellitus, Type 2, European Continental Ancestry Group, Female, Gene Frequency, Genetic Loci, Genome-Wide Association Study, Genomics, Hispanic Americans, Humans, Indians, North American, Insulin, Male, Middle Aged, Polymorphism, Single Nucleotide, Transcription Factor 7-Like 2 Protein}, issn = {1471-2350}, doi = {10.1186/1471-2350-14-98}, author = {Fesinmeyer, Megan D and Meigs, James B and North, Kari E and Schumacher, Fredrick R and B{\r u}zkov{\'a}, Petra and Franceschini, Nora and Haessler, Jeffrey and Goodloe, Robert and Spencer, Kylee L and Voruganti, Venkata Saroja and Howard, Barbara V and Jackson, Rebecca and Kolonel, Laurence N and Liu, Simin and Manson, JoAnn E and Monroe, Kristine R and Mukamal, Kenneth and Dilks, Holli H and Pendergrass, Sarah A and Nato, Andrew and Wan, Peggy and Wilkens, Lynne R and Le Marchand, Lo{\"\i}c and Ambite, Jose Luis and Buyske, Steven and Florez, Jose C and Crawford, Dana C and Hindorff, Lucia A and Haiman, Christopher A and Peters, Ulrike and Pankow, James S} } @article {6287, title = {Genome-wide association of body fat distribution in African ancestry populations suggests new loci.}, journal = {PLoS Genet}, volume = {9}, year = {2013}, month = {2013}, pages = {e1003681}, abstract = {

Central obesity, measured by waist circumference (WC) or waist-hip ratio (WHR), is a marker of body fat distribution. Although obesity disproportionately affects minority populations, few studies have conducted genome-wide association study (GWAS) of fat distribution among those of predominantly African ancestry (AA). We performed GWAS of WC and WHR, adjusted and unadjusted for BMI, in up to 33,591 and 27,350 AA individuals, respectively. We identified loci associated with fat distribution in AA individuals using meta-analyses of GWA results for WC and WHR (stage 1). Overall, 25 SNPs with single genomic control (GC)-corrected p-values<5.0 {\texttimes} 10(-6) were followed-up (stage 2) in AA with WC and with WHR. Additionally, we interrogated genomic regions of previously identified European ancestry (EA) WHR loci among AA. In joint analysis of association results including both Stage 1 and 2 cohorts, 2 SNPs demonstrated association, rs2075064 at LHX2, p = 2.24{\texttimes}10(-8) for WC-adjusted-for-BMI, and rs6931262 at RREB1, p = 2.48{\texttimes}10(-8) for WHR-adjusted-for-BMI. However, neither signal was genome-wide significant after double GC-correction (LHX2: p = 6.5 {\texttimes} 10(-8); RREB1: p = 5.7 {\texttimes} 10(-8)). Six of fourteen previously reported loci for waist in EA populations were significant (p<0.05 divided by the number of independent SNPs within the region) in AA studied here (TBX15-WARS2, GRB14, ADAMTS9, LY86, RSPO3, ITPR2-SSPN). Further, we observed associations with metabolic traits: rs13389219 at GRB14 associated with HDL-cholesterol, triglycerides, and fasting insulin, and rs13060013 at ADAMTS9 with HDL-cholesterol and fasting insulin. Finally, we observed nominal evidence for sexual dimorphism, with stronger results in AA women at the GRB14 locus (p for interaction = 0.02). In conclusion, we identified two suggestive loci associated with fat distribution in AA populations in addition to confirming 6 loci previously identified in populations of EA. These findings reinforce the concept that there are fat distribution loci that are independent of generalized adiposity.

}, keywords = {Adiposity, African Continental Ancestry Group, Body Fat Distribution, European Continental Ancestry Group, Female, Genetic Loci, Genome-Wide Association Study, Humans, Male, Obesity, Polymorphism, Single Nucleotide, Waist-Hip Ratio}, issn = {1553-7404}, doi = {10.1371/journal.pgen.1003681}, author = {Liu, Ching-Ti and Monda, Keri L and Taylor, Kira C and Lange, Leslie and Demerath, Ellen W and Palmas, Walter and Wojczynski, Mary K and Ellis, Jaclyn C and Vitolins, Mara Z and Liu, Simin and Papanicolaou, George J and Irvin, Marguerite R and Xue, Luting and Griffin, Paula J and Nalls, Michael A and Adeyemo, Adebowale and Liu, Jiankang and Li, Guo and Ruiz-Narvaez, Edward A and Chen, Wei-Min and Chen, Fang and Henderson, Brian E and Millikan, Robert C and Ambrosone, Christine B and Strom, Sara S and Guo, Xiuqing and Andrews, Jeanette S and Sun, Yan V and Mosley, Thomas H and Yanek, Lisa R and Shriner, Daniel and Haritunians, Talin and Rotter, Jerome I and Speliotes, Elizabeth K and Smith, Megan and Rosenberg, Lynn and Mychaleckyj, Josyf and Nayak, Uma and Spruill, Ida and Garvey, W Timothy and Pettaway, Curtis and Nyante, Sarah and Bandera, Elisa V and Britton, Angela F and Zonderman, Alan B and Rasmussen-Torvik, Laura J and Chen, Yii-Der Ida and Ding, Jingzhong and Lohman, Kurt and Kritchevsky, Stephen B and Zhao, Wei and Peyser, Patricia A and Kardia, Sharon L R and Kabagambe, Edmond and Broeckel, Ulrich and Chen, Guanjie and Zhou, Jie and Wassertheil-Smoller, Sylvia and Neuhouser, Marian L and Rampersaud, Evadnie and Psaty, Bruce and Kooperberg, Charles and Manson, JoAnn E and Kuller, Lewis H and Ochs-Balcom, Heather M and Johnson, Karen C and Sucheston, Lara and Ordovas, Jose M and Palmer, Julie R and Haiman, Christopher A and McKnight, Barbara and Howard, Barbara V and Becker, Diane M and Bielak, Lawrence F and Liu, Yongmei and Allison, Matthew A and Grant, Struan F A and Burke, Gregory L and Patel, Sanjay R and Schreiner, Pamela J and Borecki, Ingrid B and Evans, Michele K and Taylor, Herman and Sale, Mich{\`e}le M and Howard, Virginia and Carlson, Christopher S and Rotimi, Charles N and Cushman, Mary and Harris, Tamara B and Reiner, Alexander P and Cupples, L Adrienne and North, Kari E and Fox, Caroline S} } @article {6630, title = {The influence of obesity-related single nucleotide polymorphisms on BMI across the life course: the PAGE study.}, journal = {Diabetes}, volume = {62}, year = {2013}, month = {2013 May}, pages = {1763-7}, abstract = {

Evidence is limited as to whether heritable risk of obesity varies throughout adulthood. Among >34,000 European Americans, aged 18-100 years, from multiple U.S. studies in the Population Architecture using Genomics and Epidemiology (PAGE) Consortium, we examined evidence for heterogeneity in the associations of five established obesity risk variants (near FTO, GNPDA2, MTCH2, TMEM18, and NEGR1) with BMI across four distinct epochs of adulthood: 1) young adulthood (ages 18-25 years), adulthood (ages 26-49 years), middle-age adulthood (ages 50-69 years), and older adulthood (ages >=70 years); or 2) by menopausal status in women and stratification by age 50 years in men. Summary-effect estimates from each meta-analysis were compared for heterogeneity across the life epochs. We found heterogeneity in the association of the FTO (rs8050136) variant with BMI across the four adulthood epochs (P = 0.0006), with larger effects in young adults relative to older adults (β [SE] = 1.17 [0.45] vs. 0.09 [0.09] kg/m{\texttwosuperior}, respectively, per A allele) and smaller intermediate effects. We found no evidence for heterogeneity in the association of GNPDA2, MTCH2, TMEM18, and NEGR1 with BMI across adulthood. Genetic predisposition to obesity may have greater effects on body weight in young compared with older adulthood for FTO, suggesting changes by age, generation, or secular trends. Future research should compare and contrast our findings with results using longitudinal data.

}, keywords = {Adolescent, Adult, Aged, Aged, 80 and over, Aging, Body Mass Index, Cohort Studies, Cross-Sectional Studies, European Continental Ancestry Group, Female, Genetic Association Studies, Health Surveys, Humans, Male, Middle Aged, Obesity, Polymorphism, Single Nucleotide, Proteins, United States, Young Adult}, issn = {1939-327X}, doi = {10.2337/db12-0863}, author = {Graff, Mariaelisa and Gordon-Larsen, Penny and Lim, Unhee and Fowke, Jay H and Love, Shelly-Ann and Fesinmeyer, Megan and Wilkens, Lynne R and Vertilus, Shawyntee and Ritchie, Marilyn D and Prentice, Ross L and Pankow, Jim and Monroe, Kristine and Manson, JoAnn E and Le Marchand, Lo{\"\i}c and Kuller, Lewis H and Kolonel, Laurence N and Hong, Ching P and Henderson, Brian E and Haessler, Jeff and Gross, Myron D and Goodloe, Robert and Franceschini, Nora and Carlson, Christopher S and Buyske, Steven and B{\r u}zkov{\'a}, Petra and Hindorff, Lucia A and Matise, Tara C and Crawford, Dana C and Haiman, Christopher A and Peters, Ulrike and North, Kari E} } @article {6078, title = {A meta-analysis identifies new loci associated with body mass index in individuals of African ancestry.}, journal = {Nat Genet}, volume = {45}, year = {2013}, month = {2013 Jun}, pages = {690-6}, abstract = {

Genome-wide association studies (GWAS) have identified 36 loci associated with body mass index (BMI), predominantly in populations of European ancestry. We conducted a meta-analysis to examine the association of >3.2 million SNPs with BMI in 39,144 men and women of African ancestry and followed up the most significant associations in an additional 32,268 individuals of African ancestry. We identified one new locus at 5q33 (GALNT10, rs7708584, P = 3.4 {\texttimes} 10(-11)) and another at 7p15 when we included data from the GIANT consortium (MIR148A-NFE2L3, rs10261878, P = 1.2 {\texttimes} 10(-10)). We also found suggestive evidence of an association at a third locus at 6q16 in the African-ancestry sample (KLHL32, rs974417, P = 6.9 {\texttimes} 10(-8)). Thirty-two of the 36 previously established BMI variants showed directionally consistent effect estimates in our GWAS (binomial P = 9.7 {\texttimes} 10(-7)), five of which reached genome-wide significance. These findings provide strong support for shared BMI loci across populations, as well as for the utility of studying ancestrally diverse populations.

}, keywords = {African Americans, Body Mass Index, Case-Control Studies, Gene Frequency, Genetic Loci, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Linkage Disequilibrium, Obesity, Polymorphism, Single Nucleotide}, issn = {1546-1718}, doi = {10.1038/ng.2608}, author = {Monda, Keri L and Chen, Gary K and Taylor, Kira C and Palmer, Cameron and Edwards, Todd L and Lange, Leslie A and Ng, Maggie C Y and Adeyemo, Adebowale A and Allison, Matthew A and Bielak, Lawrence F and Chen, Guanjie and Graff, Mariaelisa and Irvin, Marguerite R and Rhie, Suhn K and Li, Guo and Liu, Yongmei and Liu, Youfang and Lu, Yingchang and Nalls, Michael A and Sun, Yan V and Wojczynski, Mary K and Yanek, Lisa R and Aldrich, Melinda C and Ademola, Adeyinka and Amos, Christopher I and Bandera, Elisa V and Bock, Cathryn H and Britton, Angela and Broeckel, Ulrich and Cai, Quiyin and Caporaso, Neil E and Carlson, Chris S and Carpten, John and Casey, Graham and Chen, Wei-Min and Chen, Fang and Chen, Yii-der I and Chiang, Charleston W K and Coetzee, Gerhard A and Demerath, Ellen and Deming-Halverson, Sandra L and Driver, Ryan W and Dubbert, Patricia and Feitosa, Mary F and Feng, Ye and Freedman, Barry I and Gillanders, Elizabeth M and Gottesman, Omri and Guo, Xiuqing and Haritunians, Talin and Harris, Tamara and Harris, Curtis C and Hennis, Anselm J M and Hernandez, Dena G and McNeill, Lorna H and Howard, Timothy D and Howard, Barbara V and Howard, Virginia J and Johnson, Karen C and Kang, Sun J and Keating, Brendan J and Kolb, Suzanne and Kuller, Lewis H and Kutlar, Abdullah and Langefeld, Carl D and Lettre, Guillaume and Lohman, Kurt and Lotay, Vaneet and Lyon, Helen and Manson, JoAnn E and Maixner, William and Meng, Yan A and Monroe, Kristine R and Morhason-Bello, Imran and Murphy, Adam B and Mychaleckyj, Josyf C and Nadukuru, Rajiv and Nathanson, Katherine L and Nayak, Uma and N{\textquoteright}diaye, Amidou and Nemesure, Barbara and Wu, Suh-Yuh and Leske, M Cristina and Neslund-Dudas, Christine and Neuhouser, Marian and Nyante, Sarah and Ochs-Balcom, Heather and Ogunniyi, Adesola and Ogundiran, Temidayo O and Ojengbede, Oladosu and Olopade, Olufunmilayo I and Palmer, Julie R and Ruiz-Narvaez, Edward A and Palmer, Nicholette D and Press, Michael F and Rampersaud, Evandine and Rasmussen-Torvik, Laura J and Rodriguez-Gil, Jorge L and Salako, Babatunde and Schadt, Eric E and Schwartz, Ann G and Shriner, Daniel A and Siscovick, David and Smith, Shad B and Wassertheil-Smoller, Sylvia and Speliotes, Elizabeth K and Spitz, Margaret R and Sucheston, Lara and Taylor, Herman and Tayo, Bamidele O and Tucker, Margaret A and Van Den Berg, David J and Edwards, Digna R Velez and Wang, Zhaoming and Wiencke, John K and Winkler, Thomas W and Witte, John S and Wrensch, Margaret and Wu, Xifeng and Yang, James J and Levin, Albert M and Young, Taylor R and Zakai, Neil A and Cushman, Mary and Zanetti, Krista A and Zhao, Jing Hua and Zhao, Wei and Zheng, Yonglan and Zhou, Jie and Ziegler, Regina G and Zmuda, Joseph M and Fernandes, Jyotika K and Gilkeson, Gary S and Kamen, Diane L and Hunt, Kelly J and Spruill, Ida J and Ambrosone, Christine B and Ambs, Stefan and Arnett, Donna K and Atwood, Larry and Becker, Diane M and Berndt, Sonja I and Bernstein, Leslie and Blot, William J and Borecki, Ingrid B and Bottinger, Erwin P and Bowden, Donald W and Burke, Gregory and Chanock, Stephen J and Cooper, Richard S and Ding, Jingzhong and Duggan, David and Evans, Michele K and Fox, Caroline and Garvey, W Timothy and Bradfield, Jonathan P and Hakonarson, Hakon and Grant, Struan F A and Hsing, Ann and Chu, Lisa and Hu, Jennifer J and Huo, Dezheng and Ingles, Sue A and John, Esther M and Jordan, Joanne M and Kabagambe, Edmond K and Kardia, Sharon L R and Kittles, Rick A and Goodman, Phyllis J and Klein, Eric A and Kolonel, Laurence N and Le Marchand, Lo{\"\i}c and Liu, Simin and McKnight, Barbara and Millikan, Robert C and Mosley, Thomas H and Padhukasahasram, Badri and Williams, L Keoki and Patel, Sanjay R and Peters, Ulrike and Pettaway, Curtis A and Peyser, Patricia A and Psaty, Bruce M and Redline, Susan and Rotimi, Charles N and Rybicki, Benjamin A and Sale, Mich{\`e}le M and Schreiner, Pamela J and Signorello, Lisa B and Singleton, Andrew B and Stanford, Janet L and Strom, Sara S and Thun, Michael J and Vitolins, Mara and Zheng, Wei and Moore, Jason H and Williams, Scott M and Ketkar, Shamika and Zhu, Xiaofeng and Zonderman, Alan B and Kooperberg, Charles and Papanicolaou, George J and Henderson, Brian E and Reiner, Alex P and Hirschhorn, Joel N and Loos, Ruth J F and North, Kari E and Haiman, Christopher A} } @article {6292, title = {No evidence of interaction between known lipid-associated genetic variants and smoking in the multi-ethnic PAGE population.}, journal = {Hum Genet}, volume = {132}, year = {2013}, month = {2013 Dec}, pages = {1427-31}, abstract = {

Genome-wide association studies (GWAS) have identified many variants that influence high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and/or triglycerides. However, environmental modifiers, such as smoking, of these known genotype-phenotype associations are just recently emerging in the literature. We have tested for interactions between smoking and 49 GWAS-identified variants in over 41,000 racially/ethnically diverse samples with lipid levels from the Population Architecture Using Genomics and Epidemiology (PAGE) study. Despite their biological plausibility, we were unable to detect significant SNP {\texttimes} smoking interactions.

}, keywords = {Cholesterol, HDL, Cholesterol, LDL, Cohort Studies, Ethnic Groups, Female, Gene Frequency, Gene-Environment Interaction, Genetics, Population, Genome-Wide Association Study, Humans, Lipid Metabolism, Male, Polymorphism, Single Nucleotide, Prevalence, Smoking, Triglycerides, Young Adult}, issn = {1432-1203}, doi = {10.1007/s00439-013-1375-3}, author = {Dumitrescu, Logan and Carty, Cara L and Franceschini, Nora and Hindorff, Lucia A and Cole, Shelley A and B{\r u}zkov{\'a}, Petra and Schumacher, Fredrick R and Eaton, Charles B and Goodloe, Robert J and Duggan, David J and Haessler, Jeff and Cochran, Barbara and Henderson, Brian E and Cheng, Iona and Johnson, Karen C and Carlson, Chris S and Love, Shelly-Anne and Brown-Gentry, Kristin and Nato, Alejandro Q and Quibrera, Miguel and Shohet, Ralph V and Ambite, Jose Luis and Wilkens, Lynne R and Le Marchand, Lo{\"\i}c and Haiman, Christopher A and Buyske, Steven and Kooperberg, Charles and North, Kari E and Fornage, Myriam and Crawford, Dana C} } @article {6111, title = {Post-genome-wide association study challenges for lipid traits: describing age as a modifier of gene-lipid associations in the Population Architecture using Genomics and Epidemiology (PAGE) study.}, journal = {Ann Hum Genet}, volume = {77}, year = {2013}, month = {2013 Sep}, pages = {416-25}, abstract = {

Numerous common genetic variants that influence plasma high-density lipoprotein cholesterol, low-density lipoprotein cholesterol (LDL-C), and triglyceride distributions have been identified via genome-wide association studies (GWAS). However, whether or not these associations are age-dependent has largely been overlooked. We conducted an association study and meta-analysis in more than 22,000 European Americans between 49 previously identified GWAS variants and the three lipid traits, stratified by age (males: <50 or >=50 years of age; females: pre- or postmenopausal). For each variant, a test of heterogeneity was performed between the two age strata and significant Phet values were used as evidence of age-specific genetic effects. We identified seven associations in females and eight in males that displayed suggestive heterogeneity by age (Phet < 0.05). The association between rs174547 (FADS1) and LDL-C in males displayed the most evidence for heterogeneity between age groups (Phet = 1.74E-03, I(2) = 89.8), with a significant association in older males (P = 1.39E-06) but not younger males (P = 0.99). However, none of the suggestive modifying effects survived adjustment for multiple testing, highlighting the challenges of identifying modifiers of modest SNP-trait associations despite large sample sizes.

}, keywords = {Adult, Aged, European Continental Ancestry Group, Female, Genetic Association Studies, Genome-Wide Association Study, Humans, Lipids, Male, Middle Aged, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Quantitative Trait, Heritable, Risk Factors}, issn = {1469-1809}, doi = {10.1111/ahg.12027}, author = {Dumitrescu, Logan and Carty, Cara L and Franceschini, Nora and Hindorff, Lucia A and Cole, Shelley A and B{\r u}zkov{\'a}, Petra and Schumacher, Fredrick R and Eaton, Charles B and Goodloe, Robert J and Duggan, David J and Haessler, Jeff and Cochran, Barbara and Henderson, Brian E and Cheng, Iona and Johnson, Karen C and Carlson, Chris S and Love, Shelly-Ann and Brown-Gentry, Kristin and Nato, Alejandro Q and Quibrera, Miguel and Anderson, Garnet and Shohet, Ralph V and Ambite, Jose Luis and Wilkens, Lynne R and Marchand, Loic Le and Haiman, Christopher A and Buyske, Steven and Kooperberg, Charles and North, Kari E and Fornage, Myriam and Crawford, Dana C} } @article {6628, title = {A systematic mapping approach of 16q12.2/FTO and BMI in more than 20,000 African Americans narrows in on the underlying functional variation: results from the Population Architecture using Genomics and Epidemiology (PAGE) study.}, journal = {PLoS Genet}, volume = {9}, year = {2013}, month = {2013}, pages = {e1003171}, abstract = {

Genetic variants in intron 1 of the fat mass- and obesity-associated (FTO) gene have been consistently associated with body mass index (BMI) in Europeans. However, follow-up studies in African Americans (AA) have shown no support for some of the most consistently BMI-associated FTO index single nucleotide polymorphisms (SNPs). This is most likely explained by different race-specific linkage disequilibrium (LD) patterns and lower correlation overall in AA, which provides the opportunity to fine-map this region and narrow in on the functional variant. To comprehensively explore the 16q12.2/FTO locus and to search for second independent signals in the broader region, we fine-mapped a 646-kb region, encompassing the large FTO gene and the flanking gene RPGRIP1L by investigating a total of 3,756 variants (1,529 genotyped and 2,227 imputed variants) in 20,488 AAs across five studies. We observed associations between BMI and variants in the known FTO intron 1 locus: the SNP with the most significant p-value, rs56137030 (8.3 {\texttimes} 10(-6)) had not been highlighted in previous studies. While rs56137030was correlated at r(2)>0.5 with 103 SNPs in Europeans (including the GWAS index SNPs), this number was reduced to 28 SNPs in AA. Among rs56137030 and the 28 correlated SNPs, six were located within candidate intronic regulatory elements, including rs1421085, for which we predicted allele-specific binding affinity for the transcription factor CUX1, which has recently been implicated in the regulation of FTO. We did not find strong evidence for a second independent signal in the broader region. In summary, this large fine-mapping study in AA has substantially reduced the number of common alleles that are likely to be functional candidates of the known FTO locus. Importantly our study demonstrated that comprehensive fine-mapping in AA provides a powerful approach to narrow in on the functional candidate(s) underlying the initial GWAS findings in European populations.

}, keywords = {Adaptor Proteins, Signal Transducing, Adult, African Americans, Aged, Aged, 80 and over, Alleles, Body Mass Index, Chromosome Mapping, Continental Population Groups, European Continental Ancestry Group, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Linkage Disequilibrium, Male, Metagenomics, Middle Aged, Obesity, Proteins}, issn = {1553-7404}, doi = {10.1371/journal.pgen.1003171}, author = {Peters, Ulrike and North, Kari E and Sethupathy, Praveen and Buyske, Steve and Haessler, Jeff and Jiao, Shuo and Fesinmeyer, Megan D and Jackson, Rebecca D and Kuller, Lew H and Rajkovic, Aleksandar and Lim, Unhee and Cheng, Iona and Schumacher, Fred and Wilkens, Lynne and Li, Rongling and Monda, Keri and Ehret, Georg and Nguyen, Khanh-Dung H and Cooper, Richard and Lewis, Cora E and Leppert, Mark and Irvin, Marguerite R and Gu, C Charles and Houston, Denise and B{\r u}zkov{\'a}, Petra and Ritchie, Marylyn and Matise, Tara C and Le Marchand, Lo{\"\i}c and Hindorff, Lucia A and Crawford, Dana C and Haiman, Christopher A and Kooperberg, Charles} } @article {6629, title = {Trans-ethnic fine-mapping of lipid loci identifies population-specific signals and allelic heterogeneity that increases the trait variance explained.}, journal = {PLoS Genet}, volume = {9}, year = {2013}, month = {2013 Mar}, pages = {e1003379}, abstract = {

Genome-wide association studies (GWAS) have identified ~100 loci associated with blood lipid levels, but much of the trait heritability remains unexplained, and at most loci the identities of the trait-influencing variants remain unknown. We conducted a trans-ethnic fine-mapping study at 18, 22, and 18 GWAS loci on the Metabochip for their association with triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C), respectively, in individuals of African American (n = 6,832), East Asian (n = 9,449), and European (n = 10,829) ancestry. We aimed to identify the variants with strongest association at each locus, identify additional and population-specific signals, refine association signals, and assess the relative significance of previously described functional variants. Among the 58 loci, 33 exhibited evidence of association at P<1 {\texttimes} 10(-4) in at least one ancestry group. Sequential conditional analyses revealed that ten, nine, and four loci in African Americans, Europeans, and East Asians, respectively, exhibited two or more signals. At these loci, accounting for all signals led to a 1.3- to 1.8-fold increase in the explained phenotypic variance compared to the strongest signals. Distinct signals across ancestry groups were identified at PCSK9 and APOA5. Trans-ethnic analyses narrowed the signals to smaller sets of variants at GCKR, PPP1R3B, ABO, LCAT, and ABCA1. Of 27 variants reported previously to have functional effects, 74\% exhibited the strongest association at the respective signal. In conclusion, trans-ethnic high-density genotyping and analysis confirm the presence of allelic heterogeneity, allow the identification of population-specific variants, and limit the number of candidate SNPs for functional studies.

}, keywords = {African Americans, Apolipoproteins A, Cholesterol, HDL, Cholesterol, LDL, European Continental Ancestry Group, Genome-Wide Association Study, Humans, Lipoproteins, HDL, Lipoproteins, LDL, Proprotein Convertases, Serine Endopeptidases, Triglycerides}, issn = {1553-7404}, doi = {10.1371/journal.pgen.1003379}, author = {Wu, Ying and Waite, Lindsay L and Jackson, Anne U and Sheu, Wayne H-H and Buyske, Steven and Absher, Devin and Arnett, Donna K and Boerwinkle, Eric and Bonnycastle, Lori L and Carty, Cara L and Cheng, Iona and Cochran, Barbara and Croteau-Chonka, Damien C and Dumitrescu, Logan and Eaton, Charles B and Franceschini, Nora and Guo, Xiuqing and Henderson, Brian E and Hindorff, Lucia A and Kim, Eric and Kinnunen, Leena and Komulainen, Pirjo and Lee, Wen-Jane and Le Marchand, Lo{\"\i}c and Lin, Yi and Lindstr{\"o}m, Jaana and Lingaas-Holmen, Oddgeir and Mitchell, Sabrina L and Narisu, Narisu and Robinson, Jennifer G and Schumacher, Fred and Stan{\v c}{\'a}kov{\'a}, Alena and Sundvall, Jouko and Sung, Yun-Ju and Swift, Amy J and Wang, Wen-Chang and Wilkens, Lynne and Wilsgaard, Tom and Young, Alicia M and Adair, Linda S and Ballantyne, Christie M and B{\r u}zkov{\'a}, Petra and Chakravarti, Aravinda and Collins, Francis S and Duggan, David and Feranil, Alan B and Ho, Low-Tone and Hung, Yi-Jen and Hunt, Steven C and Hveem, Kristian and Juang, Jyh-Ming J and Kes{\"a}niemi, Antero Y and Kuusisto, Johanna and Laakso, Markku and Lakka, Timo A and Lee, I-Te and Leppert, Mark F and Matise, Tara C and Moilanen, Leena and Nj{\o}lstad, Inger and Peters, Ulrike and Quertermous, Thomas and Rauramaa, Rainer and Rotter, Jerome I and Saramies, Jouko and Tuomilehto, Jaakko and Uusitupa, Matti and Wang, Tzung-Dau and Boehnke, Michael and Haiman, Christopher A and Chen, Yii-der I and Kooperberg, Charles and Assimes, Themistocles L and Crawford, Dana C and Hsiung, Chao A and North, Kari E and Mohlke, Karen L} } @article {6360, title = {Multiancestral analysis of inflammation-related genetic variants and C-reactive protein in the population architecture using genomics and epidemiology study.}, journal = {Circ Cardiovasc Genet}, volume = {7}, year = {2014}, month = {2014 Apr}, pages = {178-88}, abstract = {

BACKGROUND: C-reactive protein (CRP) is a biomarker of inflammation. Genome-wide association studies (GWAS) have identified single-nucleotide polymorphisms (SNPs) associated with CRP concentrations and inflammation-related traits such as cardiovascular disease, type 2 diabetes mellitus, and obesity. We aimed to replicate previous CRP-SNP associations, assess whether these associations generalize to additional race/ethnicity groups, and evaluate inflammation-related SNPs for a potentially pleiotropic association with CRP.

METHODS AND RESULTS: We selected and analyzed 16 CRP-associated and 250 inflammation-related GWAS SNPs among 40 473 African American, American Indian, Asian/Pacific Islander, European American, and Hispanic participants from 7 studies collaborating in the Population Architecture using Genomics and Epidemiology (PAGE) study. Fixed-effect meta-analyses combined study-specific race/ethnicity-stratified linear regression estimates to evaluate the association between each SNP and high-sensitivity CRP. Overall, 18 SNPs in 8 loci were significantly associated with CRP (Bonferroni-corrected P<3.1{\texttimes}10(-3) for replication, P<2.0{\texttimes}10(-4) for pleiotropy): Seven of these were specific to European Americans, while 9 additionally generalized to African Americans (1), Hispanics (5), or both (3); 1 SNP was seen only in African Americans and Hispanics. Two SNPs in the CELSR2/PSRC1/SORT1 locus showed a potentially novel association with CRP: rs599839 (P=2.0{\texttimes}10(-6)) and rs646776 (P=3.1{\texttimes}10(-5)).

CONCLUSIONS: We replicated 16 SNP-CRP associations, 10 of which generalized to African Americans and/or Hispanics. We also identified potentially novel pleiotropic associations with CRP for two SNPs previously associated with coronary artery disease and/or low-density lipoprotein-cholesterol. These findings demonstrate the benefit of evaluating genotype-phenotype associations in multiple race/ethnicity groups and looking for pleiotropic relationships among SNPs previously associated with related phenotypes.

}, keywords = {Adult, African Continental Ancestry Group, Aged, Asian Continental Ancestry Group, C-Reactive Protein, Female, Genetic Variation, Genome-Wide Association Study, Hispanic Americans, Humans, Indians, North American, Inflammation, Male, Middle Aged, Polymorphism, Single Nucleotide, United States, Young Adult}, issn = {1942-3268}, doi = {10.1161/CIRCGENETICS.113.000173}, author = {Kocarnik, Jonathan M and Pendergrass, Sarah A and Carty, Cara L and Pankow, James S and Schumacher, Fredrick R and Cheng, Iona and Durda, Peter and Ambite, Jose Luis and Deelman, Ewa and Cook, Nancy R and Liu, Simin and Wactawski-Wende, Jean and Hutter, Carolyn and Brown-Gentry, Kristin and Wilson, Sarah and Best, Lyle G and Pankratz, Nathan and Hong, Ching-Ping and Cole, Shelley A and Voruganti, V Saroja and B{\r u}zkov{\'a}, Petra and Jorgensen, Neal W and Jenny, Nancy S and Wilkens, Lynne R and Haiman, Christopher A and Kolonel, Laurence N and LaCroix, Andrea and North, Kari and Jackson, Rebecca and Le Marchand, Lo{\"\i}c and Hindorff, Lucia A and Crawford, Dana C and Gross, Myron and Peters, Ulrike} } @article {7465, title = {Trans-ethnic fine-mapping of genetic loci for body mass index in the diverse ancestral populations of the Population Architecture using Genomics and Epidemiology (PAGE) Study reveals evidence for multiple signals at established loci.}, journal = {Hum Genet}, volume = {136}, year = {2017}, month = {2017 Jun}, pages = {771-800}, abstract = {

Most body mass index (BMI) genetic loci have been identified in studies of primarily European ancestries. The effect of these loci in other racial/ethnic groups is less clear. Thus, we aimed to characterize the generalizability of 170 established BMI variants, or their proxies, to diverse US populations and trans-ethnically fine-map 36 BMI loci using a sample of >102,000 adults of African, Hispanic/Latino, Asian, European and American Indian/Alaskan Native descent from the Population Architecture using Genomics and Epidemiology Study. We performed linear regression of the natural log of BMI (18.5-70~kg/m(2)) on the additive single nucleotide polymorphisms (SNPs) at BMI loci on the MetaboChip (Illumina, Inc.), adjusting for age, sex, population stratification, study site, or relatedness. We then performed fixed-effect meta-analyses and a Bayesian trans-ethnic meta-analysis to empirically cluster by allele frequency differences. Finally, we approximated conditional and joint associations to test for the presence of secondary signals. We noted directional consistency with the previously reported risk alleles beyond what would have been expected by chance (binomial p~<~0.05). Nearly, a quarter of the previously described BMI index SNPs and 29 of 36 densely-genotyped BMI loci on the MetaboChip replicated/generalized in trans-ethnic analyses. We observed multiple signals at nine loci, including the description of seven loci with novel multiple signals. This study supports the generalization of most common genetic loci to diverse ancestral populations and emphasizes the importance of dense multiethnic genomic data in refining the functional variation at genetic loci of interest and describing several loci with multiple underlying genetic variants.

}, keywords = {Body Mass Index, Ethnic Groups, Genetics, Population, Humans, Obesity}, issn = {1432-1203}, doi = {10.1007/s00439-017-1787-6}, author = {Fernandez-Rhodes, Lindsay and Gong, Jian and Haessler, Jeffrey and Franceschini, Nora and Graff, Mariaelisa and Nishimura, Katherine K and Wang, Yujie and Highland, Heather M and Yoneyama, Sachiko and Bush, William S and Goodloe, Robert and Ritchie, Marylyn D and Crawford, Dana and Gross, Myron and Fornage, Myriam and B{\r u}zkov{\'a}, Petra and Tao, Ran and Isasi, Carmen and Avil{\'e}s-Santa, Larissa and Daviglus, Martha and Mackey, Rachel H and Houston, Denise and Gu, C Charles and Ehret, Georg and Nguyen, Khanh-Dung H and Lewis, Cora E and Leppert, Mark and Irvin, Marguerite R and Lim, Unhee and Haiman, Christopher A and Le Marchand, Lo{\"\i}c and Schumacher, Fredrick and Wilkens, Lynne and Lu, Yingchang and Bottinger, Erwin P and Loos, Ruth J L and Sheu, Wayne H-H and Guo, Xiuqing and Lee, Wen-Jane and Hai, Yang and Hung, Yi-Jen and Absher, Devin and Wu, I-Chien and Taylor, Kent D and Lee, I-Te and Liu, Yeheng and Wang, Tzung-Dau and Quertermous, Thomas and Juang, Jyh-Ming J and Rotter, Jerome I and Assimes, Themistocles and Hsiung, Chao A and Chen, Yii-Der Ida and Prentice, Ross and Kuller, Lewis H and Manson, JoAnn E and Kooperberg, Charles and Smokowski, Paul and Robinson, Whitney R and Gordon-Larsen, Penny and Li, Rongling and Hindorff, Lucia and Buyske, Steven and Matise, Tara C and Peters, Ulrike and North, Kari E} } @article {9176, title = {Large-scale genome-wide association study of coronary artery disease in genetically diverse populations.}, journal = {Nat Med}, volume = {28}, year = {2022}, month = {2022 08}, pages = {1679-1692}, abstract = {

We report a genome-wide association study (GWAS) of coronary artery disease (CAD) incorporating nearly a quarter of a million cases, in which existing studies are integrated with data from cohorts of white, Black and Hispanic individuals from the Million Veteran Program. We document near equivalent heritability of CAD across multiple ancestral groups, identify 95 novel loci, including nine on the X chromosome, detect eight loci of genome-wide significance in Black and Hispanic individuals, and demonstrate that two common haplotypes at the 9p21 locus are responsible for risk stratification in all populations except those of African origin, in which these haplotypes are virtually absent. Moreover, in the largest GWAS for angiographically derived coronary atherosclerosis performed to date, we find 15 loci of genome-wide significance that robustly overlap with established loci for clinical CAD. Phenome-wide association analyses of novel loci and polygenic risk scores (PRSs) augment signals related to insulin resistance, extend pleiotropic associations of these loci to include smoking and family history, and precisely document the markedly reduced transferability of existing PRSs to Black individuals. Downstream integrative analyses reinforce the critical roles of vascular endothelial, fibroblast, and smooth muscle cells in CAD susceptibility, but also point to a shared biology between atherosclerosis and oncogenesis. This study highlights the value of diverse populations in further characterizing the genetic architecture of CAD.

}, keywords = {Coronary Artery Disease, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Polymorphism, Single Nucleotide, Risk Factors}, issn = {1546-170X}, doi = {10.1038/s41591-022-01891-3}, author = {Tcheandjieu, Catherine and Zhu, Xiang and Hilliard, Austin T and Clarke, Shoa L and Napolioni, Valerio and Ma, Shining and Lee, Kyung Min and Fang, Huaying and Chen, Fei and Lu, Yingchang and Tsao, Noah L and Raghavan, Sridharan and Koyama, Satoshi and Gorman, Bryan R and Vujkovic, Marijana and Klarin, Derek and Levin, Michael G and Sinnott-Armstrong, Nasa and Wojcik, Genevieve L and Plomondon, Mary E and Maddox, Thomas M and Waldo, Stephen W and Bick, Alexander G and Pyarajan, Saiju and Huang, Jie and Song, Rebecca and Ho, Yuk-Lam and Buyske, Steven and Kooperberg, Charles and Haessler, Jeffrey and Loos, Ruth J F and Do, Ron and Verbanck, Marie and Chaudhary, Kumardeep and North, Kari E and Avery, Christy L and Graff, Mariaelisa and Haiman, Christopher A and Le Marchand, Lo{\"\i}c and Wilkens, Lynne R and Bis, Joshua C and Leonard, Hampton and Shen, Botong and Lange, Leslie A and Giri, Ayush and Dikilitas, Ozan and Kullo, Iftikhar J and Stanaway, Ian B and Jarvik, Gail P and Gordon, Adam S and Hebbring, Scott and Namjou, Bahram and Kaufman, Kenneth M and Ito, Kaoru and Ishigaki, Kazuyoshi and Kamatani, Yoichiro and Verma, Shefali S and Ritchie, Marylyn D and Kember, Rachel L and Baras, Aris and Lotta, Luca A and Kathiresan, Sekar and Hauser, Elizabeth R and Miller, Donald R and Lee, Jennifer S and Saleheen, Danish and Reaven, Peter D and Cho, Kelly and Gaziano, J Michael and Natarajan, Pradeep and Huffman, Jennifer E and Voight, Benjamin F and Rader, Daniel J and Chang, Kyong-Mi and Lynch, Julie A and Damrauer, Scott M and Wilson, Peter W F and Tang, Hua and Sun, Yan V and Tsao, Philip S and O{\textquoteright}Donnell, Christopher J and Assimes, Themistocles L} } @article {9104, title = {Multi-ancestry genetic study of type 2 diabetes highlights the power of diverse populations for discovery and translation.}, journal = {Nat Genet}, volume = {54}, year = {2022}, month = {2022 May}, pages = {560-572}, abstract = {

We assembled an ancestrally diverse collection of genome-wide association studies (GWAS) of type 2 diabetes (T2D) in 180,834 affected individuals and 1,159,055 controls (48.9\% non-European descent) through the Diabetes Meta-Analysis of Trans-Ethnic association studies (DIAMANTE) Consortium. Multi-ancestry GWAS meta-analysis identified 237 loci attaining stringent genome-wide significance (P < 5 {\texttimes} 10), which were delineated to 338 distinct association signals. Fine-mapping of these signals was enhanced by the increased sample size and expanded population diversity of the multi-ancestry meta-analysis, which localized 54.4\% of T2D associations to a single variant with >50\% posterior probability. This improved fine-mapping enabled systematic assessment of candidate causal genes and molecular mechanisms through which T2D associations are mediated, laying the foundations for functional investigations. Multi-ancestry genetic risk scores enhanced transferability of T2D prediction across diverse populations. Our study provides a step toward more effective clinical translation of T2D GWAS to improve global health for all, irrespective of genetic background.

}, keywords = {Diabetes Mellitus, Type 2, Ethnicity, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Polymorphism, Single Nucleotide, Risk Factors}, issn = {1546-1718}, doi = {10.1038/s41588-022-01058-3}, author = {Mahajan, Anubha and Spracklen, Cassandra N and Zhang, Weihua and Ng, Maggie C Y and Petty, Lauren E and Kitajima, Hidetoshi and Yu, Grace Z and R{\"u}eger, Sina and Speidel, Leo and Kim, Young Jin and Horikoshi, Momoko and Mercader, Josep M and Taliun, Daniel and Moon, Sanghoon and Kwak, Soo-Heon and Robertson, Neil R and Rayner, Nigel W and Loh, Marie and Kim, Bong-Jo and Chiou, Joshua and Miguel-Escalada, Irene and Della Briotta Parolo, Pietro and Lin, Kuang and Bragg, Fiona and Preuss, Michael H and Takeuchi, Fumihiko and Nano, Jana and Guo, Xiuqing and Lamri, Amel and Nakatochi, Masahiro and Scott, Robert A and Lee, Jung-Jin and Huerta-Chagoya, Alicia and Graff, Mariaelisa and Chai, Jin-Fang and Parra, Esteban J and Yao, Jie and Bielak, Lawrence F and Tabara, Yasuharu and Hai, Yang and Steinthorsdottir, Valgerdur and Cook, James P and Kals, Mart and Grarup, Niels and Schmidt, Ellen M and Pan, Ian and Sofer, Tamar and Wuttke, Matthias and Sarnowski, Chloe and Gieger, Christian and Nousome, Darryl and Trompet, Stella and Long, Jirong and Sun, Meng and Tong, Lin and Chen, Wei-Min and Ahmad, Meraj and Noordam, Raymond and Lim, Victor J Y and Tam, Claudia H T and Joo, Yoonjung Yoonie and Chen, Chien-Hsiun and Raffield, Laura M and Lecoeur, C{\'e}cile and Prins, Bram Peter and Nicolas, Aude and Yanek, Lisa R and Chen, Guanjie and Jensen, Richard A and Tajuddin, Salman and Kabagambe, Edmond K and An, Ping and Xiang, Anny H and Choi, Hyeok Sun and Cade, Brian E and Tan, Jingyi and Flanagan, Jack and Abaitua, Fernando and Adair, Linda S and Adeyemo, Adebowale and Aguilar-Salinas, Carlos A and Akiyama, Masato and Anand, Sonia S and Bertoni, Alain and Bian, Zheng and Bork-Jensen, Jette and Brandslund, Ivan and Brody, Jennifer A and Brummett, Chad M and Buchanan, Thomas A and Canouil, Micka{\"e}l and Chan, Juliana C N and Chang, Li-Ching and Chee, Miao-Li and Chen, Ji and Chen, Shyh-Huei and Chen, Yuan-Tsong and Chen, Zhengming and Chuang, Lee-Ming and Cushman, Mary and Das, Swapan K and de Silva, H Janaka and Dedoussis, George and Dimitrov, Latchezar and Doumatey, Ayo P and Du, Shufa and Duan, Qing and Eckardt, Kai-Uwe and Emery, Leslie S and Evans, Daniel S and Evans, Michele K and Fischer, Krista and Floyd, James S and Ford, Ian and Fornage, Myriam and Franco, Oscar H and Frayling, Timothy M and Freedman, Barry I and Fuchsberger, Christian and Genter, Pauline and Gerstein, Hertzel C and Giedraitis, Vilmantas and Gonz{\'a}lez-Villalpando, Clicerio and Gonzalez-Villalpando, Maria Elena and Goodarzi, Mark O and Gordon-Larsen, Penny and Gorkin, David and Gross, Myron and Guo, Yu and Hackinger, Sophie and Han, Sohee and Hattersley, Andrew T and Herder, Christian and Howard, Annie-Green and Hsueh, Willa and Huang, Mengna and Huang, Wei and Hung, Yi-Jen and Hwang, Mi Yeong and Hwu, Chii-Min and Ichihara, Sahoko and Ikram, Mohammad Arfan and Ingelsson, Martin and Islam, Md Tariqul and Isono, Masato and Jang, Hye-Mi and Jasmine, Farzana and Jiang, Guozhi and Jonas, Jost B and J{\o}rgensen, Marit E and J{\o}rgensen, Torben and Kamatani, Yoichiro and Kandeel, Fouad R and Kasturiratne, Anuradhani and Katsuya, Tomohiro and Kaur, Varinderpal and Kawaguchi, Takahisa and Keaton, Jacob M and Kho, Abel N and Khor, Chiea-Chuen and Kibriya, Muhammad G and Kim, Duk-Hwan and Kohara, Katsuhiko and Kriebel, Jennifer and Kronenberg, Florian and Kuusisto, Johanna and L{\"a}ll, Kristi and Lange, Leslie A and Lee, Myung-Shik and Lee, Nanette R and Leong, Aaron and Li, Liming and Li, Yun and Li-Gao, Ruifang and Ligthart, Symen and Lindgren, Cecilia M and Linneberg, Allan and Liu, Ching-Ti and Liu, Jianjun and Locke, Adam E and Louie, Tin and Luan, Jian{\textquoteright}an and Luk, Andrea O and Luo, Xi and Lv, Jun and Lyssenko, Valeriya and Mamakou, Vasiliki and Mani, K Radha and Meitinger, Thomas and Metspalu, Andres and Morris, Andrew D and Nadkarni, Girish N and Nadler, Jerry L and Nalls, Michael A and Nayak, Uma and Nongmaithem, Suraj S and Ntalla, Ioanna and Okada, Yukinori and Orozco, Lorena and Patel, Sanjay R and Pereira, Mark A and Peters, Annette and Pirie, Fraser J and Porneala, Bianca and Prasad, Gauri and Preissl, Sebastian and Rasmussen-Torvik, Laura J and Reiner, Alexander P and Roden, Michael and Rohde, Rebecca and Roll, Kathryn and Sabanayagam, Charumathi and Sander, Maike and Sandow, Kevin and Sattar, Naveed and Sch{\"o}nherr, Sebastian and Schurmann, Claudia and Shahriar, Mohammad and Shi, Jinxiu and Shin, Dong Mun and Shriner, Daniel and Smith, Jennifer A and So, Wing Yee and Stan{\v c}{\'a}kov{\'a}, Alena and Stilp, Adrienne M and Strauch, Konstantin and Suzuki, Ken and Takahashi, Atsushi and Taylor, Kent D and Thorand, Barbara and Thorleifsson, Gudmar and Thorsteinsdottir, Unnur and Tomlinson, Brian and Torres, Jason M and Tsai, Fuu-Jen and Tuomilehto, Jaakko and Tusi{\'e}-Luna, Teresa and Udler, Miriam S and Valladares-Salgado, Adan and van Dam, Rob M and van Klinken, Jan B and Varma, Rohit and Vujkovic, Marijana and Wacher-Rodarte, Niels and Wheeler, Eleanor and Whitsel, Eric A and Wickremasinghe, Ananda R and van Dijk, Ko Willems and Witte, Daniel R and Yajnik, Chittaranjan S and Yamamoto, Ken and Yamauchi, Toshimasa and Yengo, Loic and Yoon, Kyungheon and Yu, Canqing and Yuan, Jian-Min and Yusuf, Salim and Zhang, Liang and Zheng, Wei and Raffel, Leslie J and Igase, Michiya and Ipp, Eli and Redline, Susan and Cho, Yoon Shin and Lind, Lars and Province, Michael A and Hanis, Craig L and Peyser, Patricia A and Ingelsson, Erik and Zonderman, Alan B and Psaty, Bruce M and Wang, Ya-Xing and Rotimi, Charles N and Becker, Diane M and Matsuda, Fumihiko and Liu, Yongmei and Zeggini, Eleftheria and Yokota, Mitsuhiro and Rich, Stephen S and Kooperberg, Charles and Pankow, James S and Engert, James C and Chen, Yii-Der Ida and Froguel, Philippe and Wilson, James G and Sheu, Wayne H H and Kardia, Sharon L R and Wu, Jer-Yuarn and Hayes, M Geoffrey and Ma, Ronald C W and Wong, Tien-Yin and Groop, Leif and Mook-Kanamori, Dennis O and Chandak, Giriraj R and Collins, Francis S and Bharadwaj, Dwaipayan and Par{\'e}, Guillaume and Sale, Mich{\`e}le M and Ahsan, Habibul and Motala, Ayesha A and Shu, Xiao-Ou and Park, Kyong-Soo and Jukema, J Wouter and Cruz, Miguel and McKean-Cowdin, Roberta and Grallert, Harald and Cheng, Ching-Yu and Bottinger, Erwin P and Dehghan, Abbas and Tai, E-Shyong and Dupuis, Jos{\'e}e and Kato, Norihiro and Laakso, Markku and K{\"o}ttgen, Anna and Koh, Woon-Puay and Palmer, Colin N A and Liu, Simin and Abecasis, Goncalo and Kooner, Jaspal S and Loos, Ruth J F and North, Kari E and Haiman, Christopher A and Florez, Jose C and Saleheen, Danish and Hansen, Torben and Pedersen, Oluf and M{\"a}gi, Reedik and Langenberg, Claudia and Wareham, Nicholas J and Maeda, Shiro and Kadowaki, Takashi and Lee, Juyoung and Millwood, Iona Y and Walters, Robin G and Stefansson, Kari and Myers, Simon R and Ferrer, Jorge and Gaulton, Kyle J and Meigs, James B and Mohlke, Karen L and Gloyn, Anna L and Bowden, Donald W and Below, Jennifer E and Chambers, John C and Sim, Xueling and Boehnke, Michael and Rotter, Jerome I and McCarthy, Mark I and Morris, Andrew P} }