Candidate gene analysis using imputed genotypes: cell cycle single-nucleotide polymorphisms and ovarian cancer risk

Ellen L Goode; Brooke L Fridley; Robert A Vierkant; Julie M Cunningham; Catherine M Phelan; Stephanie Anderson; David N Rider; Kristin L White; V Shane Pankratz; Honglin Song; Estrid Hogdall; Susanne K Kjaer; Alice S Whittemore; Richard DiCioccio; Susan J Ramus; Simon A Gayther; Joellen M Schildkraut; Paul P D Pharaoh; Thomas A Sellers

doi:10.1158/1055-9965.EPI-08-0860

Candidate gene analysis using imputed genotypes: cell cycle single-nucleotide polymorphisms and ovarian cancer risk

Ellen L Goode, Brooke L Fridley, Robert A Vierkant, Julie M Cunningham, Catherine M Phelan, Stephanie Anderson, David N Rider, Kristin L White, V Shane Pankratz, Honglin Song, Estrid Hogdall, Susanne K Kjaer, Alice S Whittemore, Richard DiCioccio, Susan J Ramus, Simon A Gayther, Joellen M Schildkraut, Paul P D Pharaoh, Thomas A Sellers

32 Citations (Scopus)

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.

Original language	English
Journal	Cancer Epidemiology, Biomarkers & Prevention
Volume	18
Issue number	3
Pages (from-to)	935-44
Number of pages	9
ISSN	1055-9965
DOIs	https://doi.org/10.1158/1055-9965.EPI-08-0860
Publication status	Published - 2009

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10.1158/1055-9965.EPI-08-0860

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Goode, E. L., Fridley, B. L., Vierkant, R. A., Cunningham, J. M., Phelan, C. M., Anderson, S., Rider, D. N., White, K. L., Pankratz, V. S., Song, H., Hogdall, E., Kjaer, S. K., Whittemore, A. S., DiCioccio, R., Ramus, S. J., Gayther, S. A., Schildkraut, J. M., Pharaoh, P. P. D., & Sellers, T. A. (2009). Candidate gene analysis using imputed genotypes: cell cycle single-nucleotide polymorphisms and ovarian cancer risk. Cancer Epidemiology, Biomarkers & Prevention, 18(3), 935-44. https://doi.org/10.1158/1055-9965.EPI-08-0860

Goode, EL, Fridley, BL, Vierkant, RA, Cunningham, JM, Phelan, CM, Anderson, S, Rider, DN, White, KL, Pankratz, VS, Song, H, Hogdall, E, Kjaer, SK, Whittemore, AS, DiCioccio, R, Ramus, SJ, Gayther, SA, Schildkraut, JM, Pharaoh, PPD & Sellers, TA 2009, 'Candidate gene analysis using imputed genotypes: cell cycle single-nucleotide polymorphisms and ovarian cancer risk', Cancer Epidemiology, Biomarkers & Prevention, vol. 18, no. 3, pp. 935-44. https://doi.org/10.1158/1055-9965.EPI-08-0860

@article{b1299ab067f011df928f000ea68e967b,

title = "Candidate gene analysis using imputed genotypes: cell cycle single-nucleotide polymorphisms and ovarian cancer risk",

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.",

author = "Goode, {Ellen L} and Fridley, {Brooke L} and Vierkant, {Robert A} and Cunningham, {Julie M} and Phelan, {Catherine M} and Stephanie Anderson and Rider, {David N} and White, {Kristin L} and Pankratz, {V Shane} and Honglin Song and Estrid Hogdall and Kjaer, {Susanne K} and Whittemore, {Alice S} and Richard DiCioccio and Ramus, {Susan J} and Gayther, {Simon A} and Schildkraut, {Joellen M} and Pharaoh, {Paul P D} and Sellers, {Thomas A}",

note = "Keywords: Adult; Aged; Alleles; Case-Control Studies; Cell Cycle; Cyclin D1; Cyclin E; Cyclin-Dependent Kinase 2; Cyclin-Dependent Kinase Inhibitor p15; Cyclin-Dependent Kinase Inhibitor p16; Female; Genotype; Humans; Logistic Models; Markov Chains; Middle Aged; Minnesota; Neoplasm Invasiveness; North Carolina; Oncogene Proteins; Ovarian Neoplasms; Polymorphism, Single Nucleotide; Registries; Risk",

year = "2009",

doi = "10.1158/1055-9965.EPI-08-0860",

language = "English",

volume = "18",

pages = "935--44",

journal = "Cancer Epidemiology, Biomarkers & Prevention",

issn = "1055-9965",

publisher = "American Association for Cancer Research (A A C R)",

number = "3",

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T1 - Candidate gene analysis using imputed genotypes: cell cycle single-nucleotide polymorphisms and ovarian cancer risk

AU - Goode, Ellen L

AU - Fridley, Brooke L

AU - Vierkant, Robert A

AU - Cunningham, Julie M

AU - Phelan, Catherine M

AU - Anderson, Stephanie

AU - Rider, David N

AU - White, Kristin L

AU - Pankratz, V Shane

AU - Song, Honglin

AU - Hogdall, Estrid

AU - Kjaer, Susanne K

AU - Whittemore, Alice S

AU - DiCioccio, Richard

AU - Ramus, Susan J

AU - Gayther, Simon A

AU - Schildkraut, Joellen M

AU - Pharaoh, Paul P D

AU - Sellers, Thomas A

N1 - Keywords: Adult; Aged; Alleles; Case-Control Studies; Cell Cycle; Cyclin D1; Cyclin E; Cyclin-Dependent Kinase 2; Cyclin-Dependent Kinase Inhibitor p15; Cyclin-Dependent Kinase Inhibitor p16; Female; Genotype; Humans; Logistic Models; Markov Chains; Middle Aged; Minnesota; Neoplasm Invasiveness; North Carolina; Oncogene Proteins; Ovarian Neoplasms; Polymorphism, Single Nucleotide; Registries; Risk

PY - 2009

Y1 - 2009

N2 - 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.

AB - 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.

U2 - 10.1158/1055-9965.EPI-08-0860

DO - 10.1158/1055-9965.EPI-08-0860

M3 - Journal article

C2 - 19258477

SN - 1055-9965

VL - 18

SP - 935

EP - 944

JO - Cancer Epidemiology, Biomarkers & Prevention

JF - Cancer Epidemiology, Biomarkers & Prevention

IS - 3

ER -

Candidate gene analysis using imputed genotypes: cell cycle single-nucleotide polymorphisms and ovarian cancer risk

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