200 research outputs found

    Offspring sex and risk of epithelial ovarian cancer: a multinational pooled analysis of 12 case-control studies

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    While childbearing protects against risk of epithelial ovarian cancer (EOC), few studies have explored the impact on maternal EOC risk of sex of offspring, which may affect the maternal environment during pregnancy. We performed a pooled analysis among parous participants from 12 case–controls studies comprising 6872 EOC patients and 9101 controls. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated using multivariable logistic regression for case–control associations and polytomous logistic regression for histotype-specific associations, all adjusted for potential confounders. In general, no associations were found between offspring sex and EOC risk. However, compared to bearing only female offspring, bearing one or more male offspring was associated with increased risk of mucinous EOC (OR = 1.45; 95% CI = 1.01-2.07), which appeared to be limited to women reporting menarche before age 13 compared to later menarche (OR = 1.71 vs 0.99; P-interaction = 0.02). Bearing increasing numbers of male offspring was associated with greater risks of mucinous tumors (OR = 1.31, 1.84, 2.31, for 1, 2 and 3 or more male offspring, respectively; trend-p = 0.005). Stratifying by hormonally-associated conditions suggested that compared to bearing all female offspring, bearing a male offspring was associated with lower risk of endometrioid cancer among women with a history of adult acne, hirsutism, or polycystic ovary syndrome (OR = 0.49, 95% CI = 0.28-0.83) but with higher risk among women without any of those conditions (OR = 1.64 95% CI = 1.14–2.34; P-interaction = 0.003). Offspring sex influences the childbearing-EOC risk relationship for specific histotypes and conditions. These findings support the differing etiologic origins of EOC histotypes and highlight the importance of EOC histotype-specific epidemiologic studies. These findings also suggest the need to better understand how pregnancy affects EOC ris

    BRCA2 polymorphic stop codon K3326X and the risk of breast, prostate, and ovarian cancers

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    Background: The K3326X variant in BRCA2 (BRCA2*c.9976A>T; p.Lys3326*; rs11571833) has been found to be associated with small increased risks of breast cancer. However, it is not clear to what extent linkage disequilibrium with fully pathogenic mutations might account for this association. There is scant information about the effect of K3326X in other hormone-related cancers. Methods: Using weighted logistic regression, we analyzed data from the large iCOGS study including 76 637 cancer case patients and 83 796 control patients to estimate odds ratios (ORw) and 95% confidence intervals (CIs) for K3326X variant carriers in relation to breast, ovarian, and prostate cancer risks, with weights defined as probability of not having a pathogenic BRCA2 variant. Using Cox proportional hazards modeling, we also examined the associations of K3326X with breast and ovarian cancer risks among 7183 BRCA1 variant carriers. All statistical tests were two-sided. Results: The K3326X variant was associated with breast (ORw = 1.28, 95% CI = 1.17 to 1.40, P = 5.9x10- 6) and invasive ovarian cancer (ORw = 1.26, 95% CI = 1.10 to 1.43, P = 3.8x10-3). These associations were stronger for serous ovarian cancer and for estrogen receptor–negative breast cancer (ORw = 1.46, 95% CI = 1.2 to 1.70, P = 3.4x10-5 and ORw = 1.50, 95% CI = 1.28 to 1.76, P = 4.1x10-5, respectively). For BRCA1 mutation carriers, there was a statistically significant inverse association of the K3326X variant with risk of ovarian cancer (HR = 0.43, 95% CI = 0.22 to 0.84, P = .013) but no association with breast cancer. No association with prostate cancer was observed. Conclusions: Our study provides evidence that the K3326X variant is associated with risk of developing breast and ovarian cancers independent of other pathogenic variants in BRCA2. Further studies are needed to determine the biological mechanism of action responsible for these associations

    Impact of month of birth on the development of autoimmune thyroid disease in the United Kingdom and Europe

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    CONTEXT: Viral/bacterial infection is proposed as a trigger for the autoimmune thyroid diseases (AITD): Graves' disease (GD) and Hashimoto's thyroiditis (HT). Previous studies in European Caucasian AITD subjects found higher birth rates in the autumn/winter, suggesting those born in the autumn/winter experience increased viral/bacterial exposure after birth, impacting upon immune system development and predisposing to AITD later in life. OBJECTIVE: Month of birth effects were investigated in three independent European Caucasian AITD datasets. DESIGN: Variation in GD and HT onset was compared across months and seasons, with fluctuations across all 12 months analyzed using a Walter-Elwood test. SETTING: The study was conducted at a research laboratory. PATIENTS: National UK Caucasian AITD Case Control Collection (2746 GD and 502 HT compared with 1 423 716 UK births), National UK Caucasian GD Family Collection (239 GD and 227 unaffected siblings), and OXAGEN AITD Caucasian Family Collection (885 GD, 717 HT, and 794 unaffected siblings of European Caucasian decent). MAIN OUTCOME MEASURES: Case-control and family-based association studies were measured. RESULTS: No consistent month of birth effects were detected in GD females or males across all three collections. In HT females from the OXAGEN AITD Caucasian Family Collection, slightly higher birth rates were detected in autumn (Walter's test statistic = 7.47, P = .024) however, this was not seen in the HT females from the case-control cohort. CONCLUSION: Our results suggest in UK/Northern European Caucasian GD subjects, month of birth does not impact on AITD development. Although some month of birth effects for HT females in one collection cannot be excluded, only further work in larger European Caucasian AITD collections can confirm these effects

    Robust Tests for Additive Gene-Environment Interaction in Case-Control Studies Using Gene-Environment Independence

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    There have been recent proposals advocating the use of additive gene-environment interaction instead of the widely used multiplicative scale, as a more relevant public health measure. Using gene-environment independence enhances statistical power for testing multiplicative interaction in case-control studies. However, under departure from this assumption, substantial bias in the estimates and inflated type I error in the corresponding tests can occur. In this paper, we extend the empirical Bayes (EB) approach previously developed for multiplicative interaction, which trades off between bias and efficiency in a data-adaptive way, to the additive scale. An EB estimator of the relative excess risk due to interaction is derived, and the corresponding Wald test is proposed with a general regression setting under a retrospective likelihood framework. We study the impact of gene-environment association on the resultant test with case-control data. Our simulation studies suggest that the EB approach uses the gene-environment independence assumption in a data-adaptive way and provides a gain in power compared with the standard logistic regression analysis and better control of type I error when compared with the analysis assuming gene-environment independence. We illustrate the methods with data from the Ovarian Cancer Association Consortium.Multiple funders listed on paper

    A comprehensive gene-environment interaction analysis in Ovarian Cancer using genome-wide significant common variants.

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    As a follow-up to genome-wide association analysis of common variants associated with ovarian carcinoma (cancer), our study considers seven well-known ovarian cancer risk factors and their interactions with 28 genome-wide significant common genetic variants. The interaction analyses were based on data from 9971 ovarian cancer cases and 15,566 controls from 17 case-control studies. Likelihood ratio and Wald tests for multiplicative interaction and for relative excess risk due to additive interaction were used. The top multiplicative interaction was noted between oral contraceptive pill (OCP) use (ever vs. never) and rs13255292 (p value = 3.48 × 10-4 ). Among women with the TT genotype for this variant, the odds ratio for OCP use was 0.53 (95% CI = 0.46-0.60) compared to 0.71 (95%CI = 0.66-0.77) for women with the CC genotype. When stratified by duration of OCP use, women with 1-5 years of OCP use exhibited differential protective benefit across genotypes. However, no interaction on either the multiplicative or additive scale was found to be statistically significant after multiple testing correction. The results suggest that OCP use may offer increased benefit for women who are carriers of the T allele in rs13255292. On the other hand, for women carrying the C allele in this variant, longer (5+ years) use of OCP may reduce the impact of carrying the risk allele of this SNP. Replication of this finding is needed. The study presents a comprehensive analytic framework for conducting gene-environment analysis in ovarian cancer
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