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Pharaoh, Paul

Mayo Clinic

University of Cambridge

Citations 1

Candidate Gene Analysis Using Imputed Genotypes: Cell Cycle Single-Nucleotide Polymorphisms and Ovarian Cancer Risk
Goode, Ellen L. , Vierkant, Robert A. , Cunningham, Julie M. , Phelan, Catherine M., Anderson, S. Keith , Rider, David N., White, Kristin L., Pankratz, V. Shane , Song, Honglin , Høgdall, Estrid , Kjær, Susanne K. , Whittemore, Alice S. , DiCioccio, Richard A., Ramus, Susan J. , Gayther, Simon A. , Schildkraut, Joellen M. , Pharaoh, Paul, Sellers, Thomas A. , Fridley, Brooke L. , Kjaer, Susanne K , Ramus, Susan J , Vierkant, Robert A , Høgdall, Estrid

Cancer Epidemiology, Biomarkers & Prevention | March 9, 2009 | Volume: 18 | Issue: 3 | Pages: 935-944

10.1158/1055-9965.epi-08-0860 Get It

Abstract Polymorphisms in genes critical to cell cycle control are outstanding candidates for association with ovarian cancer risk; numerous genes have been interrogated by multiple research groups using differing tagging single-nucleotide polymorphism (SNP) sets. To maximize information gleaned from existing genotype data, we conducted a combined analysis of five independent studies of invasive epithelial ovarian cancer. Up to 2,120 cases and 3,382 controls were genotyped in the course of two collaborations at a variety of SNPs in 11 cell cycle genes (CDKN2C, CDKN1A, CCND3, CCND1, CCND2, CDKN1B, CDK2, CDK4, RB1, CDKN2D, and CCNE1) and one gene region (CDKN2A-CDKN2B). Because of the semi-overlapping nature of the 123 assayed tagging SNPs, we performed multiple imputation based on fastPHASE using data from White non-Hispanic study participants and participants in the international HapMap Consortium and National Institute of Environmental Health Sciences SNPs Program. Logistic regression assuming a log-additive model was done on combined and imputed data. We observed strengthened signals in imputation-based analyses at several SNPs, particularly CDKN2A-CDKN2B rs3731239; CCND1 rs602652, rs3212879, rs649392, and rs3212891; CDK2 rs2069391, rs2069414, and rs17528736; and CCNE1 rs3218036. These results exemplify the utility of imputation in candidate gene studies and lend evidence to a role of cell cycle genes in ovarian cancer etiology, suggest a reduced set of SNPs to target in additional cases and controls. (Cancer Epidemiol Biomarkers Prev 2009;18(3):935–44)