@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 {1371, title = {Associations between incident ischemic stroke events and stroke and cardiovascular disease-related genome-wide association studies single nucleotide polymorphisms in the Population Architecture Using Genomics and Epidemiology study.}, journal = {Circ Cardiovasc Genet}, volume = {5}, year = {2012}, month = {2012 Apr 01}, pages = {210-6}, abstract = {

BACKGROUND: Genome-wide association studies (GWAS) have identified loci associated with ischemic stroke (IS) and cardiovascular disease (CVD) in European-descent individuals, but their replication in different populations has been largely unexplored.

METHODS AND RESULTS: Nine single nucleotide polymorphisms (SNPs) selected from GWAS and meta-analyses of stroke, and 86 SNPs previously associated with myocardial infarction and CVD risk factors, including blood lipids (high density lipoprotein [HDL], low density lipoprotein [LDL], and triglycerides), type 2 diabetes, and body mass index (BMI), were investigated for associations with incident IS in European Americans (EA) N=26 276, African-Americans (AA) N=8970, and American Indians (AI) N=3570 from the Population Architecture using Genomics and Epidemiology Study. Ancestry-specific fixed effects meta-analysis with inverse variance weighting was used to combine study-specific log hazard ratios from Cox proportional hazards models. Two of 9 stroke SNPs (rs783396 and rs1804689) were significantly associated with [corrected] IS hazard in AA; none were significant in this large EA cohort. Of 73 CVD risk factor SNPs tested in EA, 2 (HDL and triglycerides SNPs) were associated with IS. In AA, SNPs associated with LDL, HDL, and BMI were significantly associated with IS (3 of 86 SNPs tested). Out of 58 SNPs tested in AI, 1 LDL SNP was significantly associated with IS.

CONCLUSIONS: Our analyses showing lack of replication in spite of reasonable power for many stroke SNPs and differing results by ancestry highlight the need to follow up on GWAS findings and conduct genetic association studies in diverse populations. We found modest IS associations with BMI and lipids SNPs, though these findings require confirmation.

}, keywords = {Aged, Aged, 80 and over, Cardiovascular Diseases, Cholesterol, HDL, Cholesterol, LDL, European Continental Ancestry Group, Female, Genetics, Population, Genome-Wide Association Study, Genomics, Humans, Male, Middle Aged, Polymorphism, Single Nucleotide, Risk Factors, Stroke, Triglycerides}, issn = {1942-3268}, doi = {10.1161/CIRCGENETICS.111.962191}, author = {Carty, Cara L and B{\r u}zkov{\'a}, Petra and Fornage, Myriam and Franceschini, Nora and Cole, Shelley and Heiss, Gerardo and Hindorff, Lucia A and Howard, Barbara V and Mann, Sue and Martin, Lisa W and Zhang, Ying and Matise, Tara C and Prentice, Ross and Reiner, Alexander P and Kooperberg, Charles} } @article {6827, title = {Association of functional polymorphism rs2231142 (Q141K) in the ABCG2 gene with serum uric acid and gout in 4 US populations: the PAGE Study.}, journal = {Am J Epidemiol}, volume = {177}, year = {2013}, month = {2013 May 1}, pages = {923-32}, abstract = {

A loss-of-function mutation (Q141K, rs2231142) in the ATP-binding cassette, subfamily G, member 2 gene (ABCG2) has been shown to be associated with serum uric acid levels and gout in Asians, Europeans, and European and African Americans; however, less is known about these associations in other populations. Rs2231142 was genotyped in 22,734 European Americans, 9,720 African Americans, 3,849 Mexican Americans, and 3,550 American Indians in the Population Architecture using Genomics and Epidemiology (PAGE) Study (2008-2012). Rs2231142 was significantly associated with serum uric acid levels (P = 2.37 {\texttimes} 10(-67), P = 3.98 {\texttimes} 10(-5), P = 6.97 {\texttimes} 10(-9), and P = 5.33 {\texttimes} 10(-4) in European Americans, African Americans, Mexican Americans, and American Indians, respectively) and gout (P = 2.83 {\texttimes} 10(-10), P = 0.01, and P = 0.01 in European Americans, African Americans, and Mexican Americans, respectively). Overall, the T allele was associated with a 0.24-mg/dL increase in serum uric acid level (P = 1.37 {\texttimes} 10(-80)) and a 1.75-fold increase in the odds of gout (P = 1.09 {\texttimes} 10(-12)). The association between rs2231142 and serum uric acid was significantly stronger in men, postmenopausal women, and hormone therapy users compared with their counterparts. The association with gout was also significantly stronger in men than in women. These results highlight a possible role of sex hormones in the regulation of ABCG2 urate transporter and its potential implications for the prevention, diagnosis, and treatment of hyperuricemia and gout.

}, keywords = {Adult, African Americans, Age Distribution, ATP-Binding Cassette Transporters, Comorbidity, European Continental Ancestry Group, Female, Genetic Predisposition to Disease, Genetics, Population, Genome-Wide Association Study, Gout, Hormone Replacement Therapy, Humans, Indians, North American, Male, Mexican Americans, Middle Aged, Neoplasm Proteins, Polymorphism, Genetic, Postmenopause, Sex Distribution, United States, Uric Acid}, issn = {1476-6256}, doi = {10.1093/aje/kws330}, author = {Zhang, Lili and Spencer, Kylee L and Voruganti, V Saroja and Jorgensen, Neal W and Fornage, Myriam and Best, Lyle G and Brown-Gentry, Kristin D and Cole, Shelley A and Crawford, Dana C and Deelman, Ewa and Franceschini, Nora and Gaffo, Angelo L and Glenn, Kimberly R and Heiss, Gerardo and Jenny, Nancy S and K{\"o}ttgen, Anna and Li, Qiong and Liu, Kiang and Matise, Tara C and North, Kari E and Umans, Jason G and Kao, W H Linda} } @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} }