Dataset Information

The Next PAGE in understanding complex traits: design for the analysis of Population Architecture Using Genetics and Epidemiology (PAGE) Study.

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's Database of Genotypes and Phenotypes and made available via a custom browser.

SUBMITTER: Matise TC

PROVIDER: S-EPMC3176830 | biostudies-other | 2011 Oct

REPOSITORIES: biostudies-other

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The Next PAGE in understanding complex traits: design for the analysis of Population Architecture Using Genetics and Epidemiology (PAGE) Study.

Matise Tara C TC Ambite Jose Luis JL Buyske Steven S Carlson Christopher S CS Cole Shelley A SA Crawford Dana C DC Haiman Christopher A CA Heiss Gerardo G Kooperberg Charles C Marchand Loic Le LL Manolio Teri A TA North Kari E KE Peters Ulrike U Ritchie Marylyn D MD Hindorff Lucia A LA Haines Jonathan L JL

American journal of epidemiology 20110811 7

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-bas ...[more]

PMID: 21836165

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Project description:By relating hundreds of thousands of genotypes to only a few phenotypes, mostly in individuals of one ancestry, genome-wide association (GWA) studies are identifying a rapidly growing number of associations. The Population Architecture using Genomics and Epidemiology (PAGE) Study is designed to further characterize the most promising variants along an epidemiological dimension that is substantial in its sample size, ethnic diversity, breadth of phenotypes, and exposures. PAGE includes scientists and population samples from large ongoing cohort studies: CALiCo (Causal Variants Across the Life Course, a consortium of ARIC, CARDIA, CHS, HCHS/SOL, Strong Heart Cohort Study, Strong Heart Family Study), EAGLE (Epidemiologic Architecture for Genes Linked to Environment, based on 3 National Health and Nutrition Examination Surveys (NHANES), MEC (Multiethnic Cohort) and WHI (Women's Health Initiative), with logistical and scientific support contributed by a Coordinating Center and the NHGRI Office of Population Genomics. These studies combined include over 270,000 participants, and populations represented include Asian Americans, African Americans, European Americans, Hispanic Americans, Native Hawaiians and American Indians. Health outcomes and traits of interest are prioritized, followed by replication of trait-genotype associations and generalization of their effects across population groups and environmental contexts. The first phase of genotyping focused on 901 high-profile SNPs having replicated associations with phenotypes related to diabetes, obesity, cardiovascular disease, lipids, cancers, menopause/menarche, inflammation and autoimmunity that are being genotyped in over 121,000 participants, as available for trait-specific analyses. SNP genotyping, quality control and population-specific association analyses are performed within each cohort, followed by meta-analyses using harmonized phenotypes and standardized analytic methods. The second phase of genotyping will be done using the Metabochip. The Metabochip is a custom large-scale (~200K SNPs) Illumina chip designed for association testing of several metabolic-related phenotypes. Genotyping will be performed at each study site and centralized analysis will be managed through the coordinating center. PAGE is generating 3 types of data: tier 1 (minimally curated phenotypes and analyses, all SNPs by all available phenotypes, used for Phenome-wide association study (PheWAS analysis)), tier 2 (carefully curated analyses of phenotypes available at only one of the four PAGE sites) and tier 3 (carefully curated phenotypes for multi-site analyses, data specifically generated for manuscripts). All tiers of data are submitted to the CC, where they undergo QC prior to submission to dbGaP.

Dataset Information

The Next PAGE in understanding complex traits: design for the analysis of Population Architecture Using Genetics and Epidemiology (PAGE) Study.

Publications

The Next PAGE in understanding complex traits: design for the analysis of Population Architecture Using Genetics and Epidemiology (PAGE) Study.

Similar Datasets

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