In the current PAGE study (PAGE 1) we investigated many genetic loci identified through genome-wide association studies (GWAS) in ancestrally diverse populations, and successfully generalized and fine-mapped many GWAS loci from studies of European-descent populations. These successes support extending the genomic search to less frequent and rare variants, which have not been captured in GWAS, but represent the largest fraction of genetic variation in the genome and contribute to the heritabilit of many complex traits. Most GWAS have been conducted in Europeans;yet studies investigating the impact of genetic risk factors, including low frequency variants, on common complex traits in diverse populations are needed including understudied US minorities having high burden of disease. The goal of this project is to comprehensively investigate less frequent and rare non-synonymous variants across the protein coding regions of the genome, i.e. the """"""""exome"""""""", and their associations with common complex traits, such as cardiovascular disease, cancer, body composition, blood lipids, glucose, insulin, and many other outcomes in a multi-ethnic population. Specifically, we propose to use a newly developed ExomeChip genotyping platform, augmented with additional content focused on ancestral diversity and putative regulatory elements in non-coding regions. This platform is highly cost-efficient and will provide genotyping data on about 350,000 variants with allele frequencies as low as 0.1%. Most of these low frequency variants are neither genotyped nor well tagged on existing GWAS arrays. We will use this ExomeChip in an ancestrally diverse population including African Americans (n=7,510), Hispanics (n=5,394) and Native Americans (n=596) from the Women's Health Initiative (WHI). These data will be combined with ExomeChip genotypes and exome sequencing data from 23,303 European Americans and 3,631 African Americans from ongoing WHI studies, for a total of 40,434 WHI participants. This resource will permit us to investigate relationships between low frequency and rare genetic variants with complex diseases of public health importance as well as with well-curated intermediate traits and over 4,800 phenotypic variables available in the WHI. We will develop new methods and apply them in this rich resource to estimate heritability and to identify effects of variants across multiple phenotypes (pleiotropy) and gene-environment interaction which are motivated by our PAGE 1 findings for common variants. Through these efforts, we expect to identify multiple susceptibility loci that may better quantify the proportion of variation in complex diseases explained by genetic variants, identify population-specific loci and provide insights into shared molecular pathways that will more efficiently direct subsequent prevention and treatment strategies in the diverse US population. All genotype and associated phenotypic data will be made publically available through databases, such as dbGaP and as part of the WHI system, building a resource for the scientific community.
The focus of this proposal is to investigate associations between genetic variants from the protein coding regions of the genome, i.e. the exome, and chronic diseases and their risk factors in a multi-ethnic population. Specifically, we propose to use the ExomeChip to identify rare and low frequency genetic variants contributing to variation in traits relevant to chronic diseases in African American, Hispanic and Native American women from the Women's Health Initiative, as part of the PAGE 2 consortium. Findings from this study will improve our understanding of how genetic variation affects the risk of chronic diseases, and may lead to better strategies to prevent these diseases in minority populations and develop effective drug therapies.
|Gong, J; Nishimura, K K; Fernandez-Rhodes, L et al. (2018) Trans-ethnic analysis of metabochip data identifies two new loci associated with BMI. Int J Obes (Lond) 42:384-390|
|Wojcik, Genevieve L; Fuchsberger, Christian; Taliun, Daniel et al. (2018) Imputation-Aware Tag SNP Selection To Improve Power for Large-Scale, Multi-ethnic Association Studies. G3 (Bethesda) 8:3255-3267|
|Kocarnik, Jonathan M; Richard, Melissa; Graff, Misa et al. (2018) Discovery, fine-mapping, and conditional analyses of genetic variants associated with C-reactive protein in multiethnic populations using the Metabochip in the Population Architecture using Genomics and Epidemiology (PAGE) study. Hum Mol Genet 27:2940-2953|
|Justice, Anne E (see original citation for additional authors) (2017) Genome-wide meta-analysis of 241,258 adults accounting for smoking behaviour identifies novel loci for obesity traits. Nat Commun 8:14977|
|Belbin, Gillian Morven; Odgis, Jacqueline; Sorokin, Elena P et al. (2017) Genetic identification of a common collagen disease in puerto ricans via identity-by-descent mapping in a health system. Elife 6:|
|Evans, Daniel S; Avery, Christy L; Nalls, Mike A et al. (2016) Fine-mapping, novel loci identification, and SNP association transferability in a genome-wide association study of QRS duration in African Americans. Hum Mol Genet 25:4350-4368|
|Shungin, Dmitry (see original citation for additional authors) (2015) New genetic loci link adipose and insulin biology to body fat distribution. Nature 518:187-196|
|Locke, Adam E (see original citation for additional authors) (2015) Genetic studies of body mass index yield new insights for obesity biology. Nature 518:197-206|
|Kocarnik, Jonathan M; Park, S Lani; Han, Jiali et al. (2015) Pleiotropic and sex-specific effects of cancer GWAS SNPs on melanoma risk in the population architecture using genomics and epidemiology (PAGE) study. PLoS One 10:e0120491|
|Park, S Lani; Fesinmeyer, Megan D; Timofeeva, Maria et al. (2014) Pleiotropic associations of risk variants identified for other cancers with lung cancer risk: the PAGE and TRICL consortia. J Natl Cancer Inst 106:dju061|
Showing the most recent 10 out of 18 publications