@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 {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 {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 {6627, title = {Investigation of gene-by-sex interactions for lipid traits in diverse populations from the population architecture using genomics and epidemiology study.}, journal = {BMC Genet}, volume = {14}, year = {2013}, month = {2013}, pages = {33}, abstract = {

BACKGROUND: High-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and triglyceride (TG) levels are influenced by both genes and the environment. Genome-wide association studies (GWAS) have identified ~100 common genetic variants associated with HDL-C, LDL-C, and/or TG levels, mostly in populations of European descent, but little is known about the modifiers of these associations. Here, we investigated whether GWAS-identified SNPs for lipid traits exhibited heterogeneity by sex in the Population Architecture using Genomics and Epidemiology (PAGE) study.

RESULTS: A sex-stratified meta-analysis was performed for 49 GWAS-identified SNPs for fasting HDL-C, LDL-C, and ln(TG) levels among adults self-identified as European American (25,013). Heterogeneity by sex was established when phet < 0.001. There was evidence for heterogeneity by sex for two SNPs for ln(TG) in the APOA1/C3/A4/A5/BUD13 gene cluster: rs28927680 (p(het) = 7.4 x 10(-7)) and rs3135506 (p(het) = 4.3 x 10(-4)one SNP in PLTP for HDL levels (rs7679; p(het) = 9.9 x 10(-4)), and one in HMGCR for LDL levels (rs12654264; p(het) = 3.1 x 10(-5)). We replicated heterogeneity by sex in five of seventeen loci previously reported by genome-wide studies (binomial p = 0.0009). We also present results for other racial/ethnic groups in the supplementary materials, to provide a resource for future meta-analyses.

CONCLUSIONS: We provide further evidence for sex-specific effects of SNPs in the APOA1/C3/A4/A5/BUD13 gene cluster, PLTP, and HMGCR on fasting triglyceride levels in European Americans from the PAGE study. Our findings emphasize the need for considering context-specific effects when interpreting genetic associations emerging from GWAS, and also highlight the difficulties in replicating interaction effects across studies and across racial/ethnic groups.

}, keywords = {Female, Genetic Heterogeneity, Genome, Human, Genome-Wide Association Study, Humans, Lipids, Male, Polymorphism, Single Nucleotide, Population Groups}, issn = {1471-2156}, doi = {10.1186/1471-2156-14-33}, author = {Taylor, Kira C and Carty, Cara L and Dumitrescu, Logan and B{\r u}zkov{\'a}, Petra and Cole, Shelley A and Hindorff, Lucia and Schumacher, Fred R and Wilkens, Lynne R and Shohet, Ralph V and Quibrera, P Miguel and Johnson, Karen C and Henderson, Brian E and Haessler, Jeff and Franceschini, Nora and Eaton, Charles B and Duggan, David J and Cochran, Barbara and Cheng, Iona and Carlson, Chris S and Brown-Gentry, Kristin and Anderson, Garnet and Ambite, Jose Luis and Haiman, Christopher and Le Marchand, Lo{\"\i}c and Kooperberg, Charles and Crawford, Dana C and Buyske, Steven and North, Kari E and Fornage, Myriam} } @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 {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 {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} }