No effect of aspirin on mammographic density in a randomized controlled clinical trial.

BACKGROUND: Epidemiologic studies suggest a reduced risk of breast cancer among women who regularly use aspirin; a plausible mechanism is through aspirin effect on mammographic breast density, a breast cancer risk factor, possibly mediated through aspirin interference with estrogen synthesis. METHODS: In a 2-arm randomized placebo-controlled clinical trial, we evaluated the effects of 6-month administration of 325 mg/day aspirin on total mammographic breast dense area and percent of the mammographic breast image occupied by dense areas (% density) in 143 postmenopausal women. Eligible women, recruited from 2005 to 2007, were healthy, not taking hormone therapy, with elevated mammographic breast density (American College of Radiology Breast Imaging Reporting and Data System density category 2, 3, or 4) within 6 months before enrollment. RESULTS: Women were a mean (SD) 59.5 (5.5) years. Geometric mean baseline percent density was 17.6% (95% confidence interval, 14.8-20.9) in women randomized to aspirin and 19.2% (95% confidence interval, 16.3-22.7) in women randomized to placebo. Percent density decreased in women randomized to aspirin by an absolute 0.8% versus an absolute decrease of 1.2% in controls (P = 0.84). Total breast area and dense area decreased to a similar degree in women assigned to aspirin and in those assigned to placebo, with no statistically significant differences between trial arms. CONCLUSIONS: A single daily administration of adult-dose aspirin for 6 months had no effect on mammographic density in postmenopausal women. If aspirin affects breast cancer risk in postmenopausal women, it may do so through alternative pathways than mammographic breast density. (Cancer Epidemiol Biomarkers Prev 2009;18(5):1524-30)

Quantitative iTRAQ-Based Proteomic Identification of Candidate Biomarkers for Diabetic Nephropathy in Plasma of Type 1 Diabetic Patients

# The Author(s) 2010. This article is published with open access at Springerlink.com Introduction As part of a clinical proteomics programme focused on diabetes and its complications, it was our goal to investigate the proteome of plasma in order to find improved candidate biomarkers to predict diabetic nephropathy. Methods Proteins derived from plasma from a crosssectiona

Shared genetics underlying epidemiological association between endometriosis and ovarian cancer

Epidemiological studies have demonstrated associations between endometriosis and certain histotypes of ovarian cancer, including clear cell, low-grade serous and endometrioid carcinomas. We aimed to determine whether the observed associations might be due to shared genetic aetiology. To address this, we used two endometriosis datasets genotyped on common arrays with full-genome coverage (3194 cases and 7060 controls) and a large ovarian cancer dataset genotyped on the customized Illumina Infinium iSelect (iCOGS) arrays (10 065 cases and 21 663 controls). Previous work has suggested that a large number of genetic variants contribute to endometriosis and ovarian cancer (all histotypes combined) susceptibility. Here, using the iCOGS data, we confirmed polygenic architecture for most histotypes of ovarian cancer. This led us to evaluate if the polygenic effects are shared across diseases. We found evidence for shared genetic risks between endometriosis and all histotypes of ovarian cancer, except for the intestinal mucinous type. Clear cell carcinoma showed the strongest genetic correlation with endometriosis (0.51, 95% CI = 0.18-0.84). Endometrioid and low-grade serous carcinomas had similar correlation coefficients (0.48, 95% CI = 0.07-0.89 and 0.40, 95% CI = 0.05-0.75, respectively). High-grade serous carcinoma, which often arises from the fallopian tubes, showed a weaker genetic correlation with endometriosis (0.25, 95% CI = 0.11-0.39), despite the absence of a known epidemiological association. These results suggest that the epidemiological association between endometriosis and ovarian adenocarcinoma may be attributable to shared genetic susceptibility loci

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

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

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

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

Socioeconomic inequalities in mortality, morbidity and diabetes management for adults with type 1 diabetes: A systematic review.

AIMS: To systematically review the evidence of socioeconomic inequalities for adults with type 1 diabetes in relation to mortality, morbidity and diabetes management. METHODS: We carried out a systematic search across six relevant databases and included all studies reporting associations between socioeconomic indicators and mortality, morbidity, or diabetes management for adults with type 1 diabetes. Data extraction and quality assessment was undertaken for all included studies. A narrative synthesis was conducted. RESULTS: A total of 33 studies were identified. Twelve cohort, 19 cross sectional and 2 case control studies met the inclusion criteria. Regardless of healthcare system, low socioeconomic status was associated with poorer outcomes. Following adjustments for other risk factors, socioeconomic status was a statistically significant independent predictor of mortality in 9/10 studies and morbidity in 8/10 studies for adults with type 1 diabetes. There appeared to be an association between low socioeconomic status and some aspects of diabetes management. Although only 3 of 16 studies made adjustments for confounders and other risk factors, poor diabetes management was associated with lower socioeconomic status in 3/3 of these studies. CONCLUSIONS: Low socioeconomic status is associated with higher levels of mortality and morbidity for adults with type 1 diabetes even amongst those with access to a universal healthcare system. The association between low socioeconomic status and diabetes management requires further research given the paucity of evidence and the potential for diabetes management to mitigate the adverse effects of low socioeconomic status

Effect of Adjunct Metformin Treatment in Patients with Type-1 Diabetes and Persistent Inadequate Glycaemic Control. A Randomized Study

Despite intensive insulin treatment, many patients with type-1 diabetes (T1DM) have longstanding inadequate glycaemic control. Metformin is an oral hypoglycaemic agent that improves insulin action in patients with type-2 diabetes. We investigated the effect of a one-year treatment with metformin versus placebo in patients with T1DM and persistent poor glycaemic control.One hundred patients with T1DM, preserved hypoglycaemic awareness and HaemoglobinA(1c) (HbA(1c)) > or = 8.5% during the year before enrolment entered a one-month run-in on placebo treatment. Thereafter, patients were randomized (baseline) to treatment with either metformin (1 g twice daily) or placebo for 12 months (double-masked). Patients continued ongoing insulin therapy and their usual outpatient clinical care. The primary outcome measure was change in HbA(1c) after one year of treatment. At enrolment, mean (standard deviation) HbA(1c) was 9.48% (0.99) for the metformin group (n = 49) and 9.60% (0.86) for the placebo group (n = 51). Mean (95% confidence interval) baseline-adjusted differences after 12 months with metformin (n = 48) versus placebo (n = 50) were: HbA(1c), 0.13% (-0.19; 0.44), p = 0.422; Total daily insulin dose, -5.7 U/day (-8.6; -2.9), p<0.001; body weight, -1.74 kg (-3.32; -0.17), p = 0.030. Minor and overall major hypoglycaemia was not significantly different between treatments. Treatments were well tolerated.In patients with poorly controlled T1DM, adjunct metformin therapy did not provide any improvement of glycaemic control after one year. Nevertheless, adjunct metformin treatment was associated with sustained reductions of insulin dose and body weight. Further investigations into the potential cardiovascular-protective effects of metformin therapy in patients with T1DM are warranted.ClinicalTrials.gov NCT00118937

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

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

Cigarette smoking is associated with adverse survival among women with ovarian cancer: Results from a pooled analysis of 19 studies

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/136359/1/ijc30600_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/136359/2/ijc30600.pd