TY - JOUR
T1 - MicroRNA processing and binding site polymorphisms are not replicated in the Ovarian Cancer Association Consortium
AU - Permuth-Wey, Jennifer
AU - Chen, Zhihua
AU - Tsai, Ya Yu
AU - Lin, Hui Yi
AU - Chen, Y. Ann
AU - Barnholtz-Sloan, Jill
AU - Birrer, Michael J.
AU - Chanock, Stephen J.
AU - Cramer, Daniel W.
AU - Cunningham, Julie M.
AU - Fenstermacher, David
AU - Fridley, Brooke L.
AU - Garcia-Closas, Montserrat
AU - Gayther, Simon A.
AU - Gentry-Maharaj, Aleksandra
AU - Gonzalez-Bosquet, Jesus
AU - Iversen, Edwin
AU - Jim, Heather
AU - McLaughlin, John
AU - Menon, Usha
AU - Narod, Steven A.
AU - Phelan, Catherine M.
AU - Ramus, Susan J.
AU - Risch, Harvey
AU - Song, Honglin
AU - Sutphen, Rebecca
AU - Terry, Kathryn L.
AU - Tyrer, Jonathan
AU - Vierkant, Robert A.
AU - Wentzensen, Nicolas
AU - Lancaster, Johnathan M.
AU - Cheng, Jin Q.
AU - Berchuck, Andrew
AU - Pharoah, Paul D.P.
AU - Schildkraut, Joellen M.
AU - Goode, Ellen L.
AU - Sellers, Thomas A.
PY - 2011/8
Y1 - 2011/8
N2 - Background: Single nucleotide polymorphisms (SNP) in microRNA-related genes have been associated with epithelial ovarian cancer (EOC) risk in two reports, yet associated alleles may be inconsistent across studies. Methods: We conducted a pooled analysis of previously identified SNPs by combining genotype data from 3,973 invasive EOC cases and 3,276 controls from the Ovarian Cancer Association Consortium. We also conducted imputation to obtain dense coverage of genes and comparable genotype data for all studies. In total, 226 SNPs within 15 kb of 4 miRNA biogenesis genes (DDX20, DROSHA, GEMIN4, and XPO5) and 23 SNPs located within putative miRNA binding sites of 6 genes (CAV1, COL18A1, E2F2, IL1R1, KRAS, and UGT2A3) were genotyped or imputed and analyzed in the entire dataset. Results: After adjustment for European ancestry, no overall association was observed between any of the analyzed SNPs and EOC risk. Conclusions: Commonvariants in these evaluated genesdonotseemto be strongly associatedwithEOCrisk. Impact: This analysis suggests earlier associations between EOC risk and SNPs in these genes may have been chance findings, possibly confounded by population admixture. To more adequately evaluate the relationship between genetic variants and cancer risk, large sample sizes are needed, adjustment for population stratification should be carried out, and use of imputed SNP data should be considered.
AB - Background: Single nucleotide polymorphisms (SNP) in microRNA-related genes have been associated with epithelial ovarian cancer (EOC) risk in two reports, yet associated alleles may be inconsistent across studies. Methods: We conducted a pooled analysis of previously identified SNPs by combining genotype data from 3,973 invasive EOC cases and 3,276 controls from the Ovarian Cancer Association Consortium. We also conducted imputation to obtain dense coverage of genes and comparable genotype data for all studies. In total, 226 SNPs within 15 kb of 4 miRNA biogenesis genes (DDX20, DROSHA, GEMIN4, and XPO5) and 23 SNPs located within putative miRNA binding sites of 6 genes (CAV1, COL18A1, E2F2, IL1R1, KRAS, and UGT2A3) were genotyped or imputed and analyzed in the entire dataset. Results: After adjustment for European ancestry, no overall association was observed between any of the analyzed SNPs and EOC risk. Conclusions: Commonvariants in these evaluated genesdonotseemto be strongly associatedwithEOCrisk. Impact: This analysis suggests earlier associations between EOC risk and SNPs in these genes may have been chance findings, possibly confounded by population admixture. To more adequately evaluate the relationship between genetic variants and cancer risk, large sample sizes are needed, adjustment for population stratification should be carried out, and use of imputed SNP data should be considered.
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U2 - 10.1158/1055-9965.EPI-11-0397
DO - 10.1158/1055-9965.EPI-11-0397
M3 - Article
C2 - 21636674
AN - SCOPUS:79961241800
SN - 1055-9965
VL - 20
SP - 1793
EP - 1797
JO - Cancer Epidemiology Biomarkers and Prevention
JF - Cancer Epidemiology Biomarkers and Prevention
IS - 8
ER -