@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 {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 {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} }