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Träfflista för sökning "WFRF:(McCarty Catherine A.) ;pers:(Kolonel Laurence N)"

Sökning: WFRF:(McCarty Catherine A.) > Kolonel Laurence N

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1.
  • Campa, Daniele, et al. (författare)
  • Interactions Between Genetic Variants and Breast Cancer Risk Factors in the Breast and Prostate Cancer Cohort Consortium
  • 2011
  • Ingår i: Journal of the National Cancer Institute. - : Oxford University Press (OUP). - 0027-8874 .- 1460-2105. ; 103:16, s. 1252-1263
  • Tidskriftsartikel (refereegranskat)abstract
    • Background Recently, several genome-wide association studies have identified various genetic susceptibility loci for breast cancer. Relatively little is known about the possible interactions between these loci and the established risk factors for breast cancer. Methods To assess interactions between single-nucleotide polymorphisms (SNPs) and established risk factors, we prospectively collected DNA samples and questionnaire data from 8576 breast cancer case subjects and 11 892 control subjects nested within the National Cancer Institute's Breast and Prostate Cancer Cohort Consortium (BPC3). We genotyped 17 germline SNPs (FGFR2-rs2981582, FGFR2-rs3750817, TNRC9-rs3803662, 2q35-rs13387042, MAP3K1-rs889312, 8q24-rs13281615, CASP8-rs1045485, LSP1-rs3817198, COL1A1-rs2075555, COX11-rs6504950, RNF146-rs2180341, 6q25-rs2046210, SLC4A7-rs4973768, NOTCH2-rs11249433, 5p12-rs4415084, 5p12-rs10941679, RAD51L1-rs999737), and odds ratios were estimated by logistic regression to confirm previously reported associations with breast cancer risk. We performed likelihood ratio test to assess interactions between 17 SNPs and nine established risk factors (age at menarche, parity, age at menopause, use of hormone replacement therapy, family history, height, body mass index, smoking status, and alcohol consumption), and a correction for multiple testing of 153 tests (adjusted P value threshold = .05/153 = 3 x 10(-4)) was done. Casecase comparisons were performed for possible differential associations of polymorphisms by subgroups of tumor stage, estrogen and progesterone receptor status, and age at diagnosis. All statistical tests were two-sided. Results We confirmed the association of 14 SNPs with breast cancer risk (P(trend) = 2.57 x 10(-3) -3.96 x 10(-19)). Three SNPs (LSP1-rs3817198, COL1A1-rs2075555, and RNF146-rs2180341) did not show association with breast cancer risk. After accounting for multiple testing, no statistically significant interactions were detected between the 17 SNPs and the nine risk factors. We also confirmed that SNPs in FGFR2 and TNRC9 were associated with greater risk of estrogen receptor-positive than estrogen receptor-negative breast cancer (P(heterogeneity) = .0016 for FGFR2-rs2981582 and P(heterogeneity) = .0053 for TNRC9-rs3803662). SNP 5p12-rs10941679 was statistically significantly associated with greater risk of progesterone receptor-positive than progesterone receptor-negative breast cancer (P(heterogeneity) = .0028). Conclusion This study does not support the hypothesis that known common breast cancer susceptibility loci strongly modify the associations between established risk factors and breast cancer.
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2.
  • Huesing, Anika, et al. (författare)
  • Prediction of breast cancer risk by genetic risk factors, overall and by hormone receptor status
  • 2012
  • Ingår i: Journal of Medical Genetics. - : BMJ. - 0022-2593 .- 1468-6244. ; 49:9, s. 601-608
  • Tidskriftsartikel (refereegranskat)abstract
    • Objective There is increasing interest in adding common genetic variants identified through genome wide association studies (GWAS) to breast cancer risk prediction models. First results from such models showed modest benefits in terms of risk discrimination. Heterogeneity of breast cancer as defined by hormone-receptor status has not been considered in this context. In this study we investigated the predictive capacity of 32 GWAS-detected common variants for breast cancer risk, alone and in combination with classical risk factors, and for tumours with different hormone receptor status. Material and methods Within the Breast and Prostate Cancer Cohort Consortium, we analysed 6009 invasive breast cancer cases and 7827 matched controls of European ancestry, with data on classical breast cancer risk factors and 32 common gene variants identified through GWAS. Discriminatory ability with respect to breast cancer of specific hormone receptor-status was assessed with the age adjusted and cohort-adjusted concordance statistic (AUROC(a)). Absolute risk scores were calculated with external reference data. Integrated discrimination improvement was used to measure improvements in risk prediction. Results We found a small but steady increase in discriminatory ability with increasing numbers of genetic variants included in the model (difference in AUROC(a) going from 2.7% to 4%). Discriminatory ability for all models varied strongly by hormone receptor status. Discussion and conclusions Adding information on common polymorphisms provides small but statistically significant improvements in the quality of breast cancer risk prediction models. We consistently observed better performance for receptor-positive cases, but the gain in discriminatory quality is not sufficient for clinical application.
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3.
  • Joshi, Amit D., et al. (författare)
  • Additive interactions between susceptibility single-nucleotide polymorphisms identified in genome-wide association studies and breast cancer risk factors in the Breast and Prostate Cancer Cohort Consortium
  • 2014
  • Ingår i: American Journal of Epidemiology. - : Oxford University Press. - 0002-9262 .- 1476-6256. ; 180:10, s. 1018-1027
  • Tidskriftsartikel (refereegranskat)abstract
    • Additive interactions can have public health and etiological implications but are infrequently reported. We assessed departures from additivity on the absolute risk scale between 9 established breast cancer risk factors and 23 susceptibility single-nucleotide polymorphisms (SNPs) identified from genome-wide association studies among 10,146 non-Hispanic white breast cancer cases and 12,760 controls within the National Cancer Institute's Breast and Prostate Cancer Cohort Consortium. We estimated the relative excess risk due to interaction and its 95% confidence interval for each pairwise combination of SNPs and nongenetic risk factors using age- and cohort-adjusted logistic regression models. After correction for multiple comparisons, we identified a statistically significant relative excess risk due to interaction (uncorrected P = 4.51 x 10(-5)) between a SNP in the DNA repair protein RAD51 homolog 2 gene (RAD51L1; rs10483813) and body mass index (weight (kg)/height (m)(2)). We also compared additive and multiplicative polygenic risk prediction models using per-allele odds ratio estimates from previous studies for breast-cancer susceptibility SNPs and observed that the multiplicative model had a substantially better goodness of fit than the additive model.
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4.
  • McKay, James D., et al. (författare)
  • Vitamin D Receptor Polymorphisms and Breast Cancer Risk: Results from the National Cancer Institute Breast and Prostate Cancer Cohort Consortium
  • 2009
  • Ingår i: Cancer Epidemiology Biomarkers & Prevention. - 1538-7755. ; 18:1, s. 297-305
  • Tidskriftsartikel (refereegranskat)abstract
    • Background: Vitamin D is hypothesized to lower the risk of breast cancer by inhibiting cell proliferation via the nuclear vitamin D receptor (VDR). Two common single nucleotide polymorphisms (SNP) in the VDR gene (VDR), rs154441.0 (BsmI), and rs2228570 (FokI), have been inconsistently associated with breast cancer risk. Increased risk has been reported for the FokIff genotype, which encodes a less transcriptionally active isoform of VDR, and reduced risk has been reported for the BsmI BB genotype, a SNP in strong linkage disequilibrium with a 3'-untranslated region, which may influence VDR mRNA stability. Methods: We pooled data from 6 prospective studies in the National Cancer Institute Breast and Prostate Cancer Cohort Consortium to examine associations between these SNPs and breast cancer among >6,300 cases and 8,100 controls for each SNP using conditional logistic regression. Results: The odds ratio (OR) for the rs2228570 (FokI) ff versus FF genotype in the overall population was statistically significantly elevated [OR, 1-1.6; 95% confidence interval (95% CI), 1.04-1.28] but was weaker once data from the cohort with previously published positive findings were removed (OR, 1.1.0; 95% CI, 0.981.24). No association was noted between rs1544410 (Bsm I) BB and breast cancer risk overall (OR, 0.98; 95% CI, 0.89-1.09), but the BB genotype was associated with a significantly lower risk of advanced breast cancer (OR, 0.74; 95% CI, 0.60-0.92). Conclusions: Although the evidence for independent contributions of these variants to breast cancer susceptibility remains equivocal, future large studies should integrate genetic variation in VDR with biomarkers of vitamin D status. (Cancer Epidemiol Biomarkers Prev 2009;18(1):297-305)
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