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We aimed to examine the association between the use of metformin and other anti‐diabetic medications and breast cancer incidence within two large prospective cohort studies. We followed 185,181 women who participated in the Nurses' Health Study (NHS; 1994–2016) and the NHSII (1995–2017), with baseline corresponding to the date metformin was approved for type 2 diabetes (T2D) treatment in the US Information on T2D diagnosis, anti‐diabetes medications, and other covariates was self‐reported at baseline and repeatedly assessed by follow‐up questionnaires every 2 years. Breast cancer cases were self‐reported and confirmed by medical record review. Hazard ratios (HRs) and 95% confidence intervals (CIs) for the association between medication use and breast cancer were estimated using Cox proportional hazards regression models, adjusting for breast cancer risk factors. During 3,324,881 person‐years of follow‐up, we ascertained 9,192 incident invasive breast cancer cases, of which 451 were among women with T2D. Compared with women without T2D (n = 169,263), neither metformin use (HR = 0.97; 95% CI = 0.81–1.15) nor other anti‐diabetic medications use (HR = 1.11; 95% CI = 0.90–1.36) associated with significantly lower breast cancer incidence. Among women with T2D (n = 15,918), compared with metformin never users, metformin ever use was not significantly inversely associated with breast cancer (HR = 0.92; 95% CI = 0.74–1.15). Although we observed that past use of metformin was inversely associated with breast cancer in the T2D population (HR = 0.67; 95% CI = 0.48–0.94), current use (HR = 1.01; 95% CI = 0.80–1.27) and longer duration of metformin use were not associated with breast cancer (each 2‐year interval: HR = 1.01; 95% CI = 0.95–1.07). Overall, metformin use was not associated with the risk of developing breast cancer among the overall cohort population or among women with T2D. [ABSTRACT FROM AUTHOR]

Background: According to the stem cell hypothesis, breast carcinogenesis may be related to the breast stem cell pool size. However, little is known about associations of breast cancer risk factors, such as anthropometric measures, with the expression of stem cell markers in noncancerous breast tissue. Methods: The analysis included 414 women with biopsy-confirmed benign breast disease in the Nurses' Health Study and Nurses' Health Study II. Birthweight, weight at age 18, current weight, and current height were reported via self-administered questionnaires. IHC staining of stem cell markers (CD44, CD24, and aldehyde dehydrogenase family 1 member A1) in histopathologically normal epithelial and stromal breast tissue was quantified using an automated computational image analysis system. Linear regression was used to examine the associations of early-life and adult anthropometric measures with log-transformed stem cell marker expression, adjusting for potential confounders. Results: Birthweight [=10.0 vs. <5.5 lbs: ß (95% confidence interval) = 4.29 (1.02, 7.56); P trend = 0.001 in the stroma] and adult height [=67.0 vs. <63.0 inch: 0.86 (0.14, 1.58); P trend = 0.02 in the epithelium and stroma combined] were positively associated with CD44 expression. Childhood body fatness was inversely associated (P trend = 0.03) whereas adult height was positively associated with CD24 expression in combined stroma and epithelium (P trend = 0.03). Conclusions: Our data suggest that anthropometric measures, such as birthweight, adult height, and childhood body fatness, may be associated with the stem cell expression among women with benign breast disease. Impact: Anthropometric measures, such as birthweight, height, and childhood body fatness, may have long-term impacts on stem cell population in the breast. [ABSTRACT FROM AUTHOR]

Background: We investigated the associations between several reproductive factors related to childbearing and the variation (V) measure (a novel, objective, single summary measure of breast image intensity) by menopausal status. Methods: Our study included 3,814 cancer-free women within the Nurses' Health Study (NHS) and NHSII cohorts. The data on reproductive variables and covariates were obtained from biennial questionnaires closest to the mammogram date. V-measures were obtained from mammographic images using a previously developed algorithm capturing the standard deviation of pixel values. We used multivariate linear regression to examine the associations of parity, age at first birth, time between menarche and first birth, time since last pregnancy, and lifetime breastfeeding duration with V-measure, adjusting for breast cancer risk factors, including the percentage of mammographic density (PMD). We further examined whether these associations were statistically accounted for (mediated) by PMD. Results: Among premenopausal women, none of the reproductive factors were associated with V. Among postmenopausal women, inverse associations of parity and positive associations of age at first birth with V were mediated by PMD (percent mediated: nulliparity: 66.7%, P < 0.0001; parity: 50.5%, P < 0.01; age at first birth 76.1%, P < 0.001) and were no longer significant in PMD-adjusted models. Lifetime duration of breastfeeding was positively associated with V [>36 vs. 0 ≤1 months β = 0.29; 95% confidence interval (CI) 0.07; 0.52, Ptrend < 0.01], independent of PMD. Conclusions: Parity, age at first birth, and breastfeeding were associated with postmenopausal V. [ABSTRACT FROM AUTHOR]

Purpose:Sex hormones may be associated with primary open-angle glaucoma (POAG), although the mechanisms are unclear. We previously observed that gene variants involved with estrogen metabolism were collectively associated with POAG in women but not men; here we assessed gene variants related to testosterone metabolism collectively and POAG risk. Methods:We used two datasets: one from the United States (3853 cases and 33,480 controls) and another from Australia (1155 cases and 1992 controls). Both datasets contained densely called genotypes imputed to the 1000 Genomes reference panel. We used pathway- and gene-based approaches with Pathway Analysis by Randomization Incorporating Structure (PARIS) software to assess the overall association between a panel of single nucleotide polymorphisms (SNPs) in testosterone metabolism genes and POAG. In sex-stratified analyses, we evaluated POAG overall and POAG subtypes defined by maximum IOP (high-tension [HTG] or normal tension glaucoma [NTG]). Results:In the US dataset, the SNP panel was not associated with POAG (permuted P = 0.77), although there was an association in the Australian sample (permuted P = 0.018). In both datasets, the SNP panel was associated with POAG in men (permuted P ≤ 0.033) and not women (permuted P ≥ 0.42), but in gene-based analyses, there was no consistency on the main genes responsible for these findings. In both datasets, the testosterone pathway association with HTG was significant (permuted P ≤ 0.011), but again, gene-based analyses showed no consistent driver gene associations. Conclusions:Collectively, testosterone metabolism pathway SNPs were consistently associated with the high-tension subtype of POAG in two datasets.

Purpose:Sex hormones may be associated with primary open-angle glaucoma (POAG), although the mechanisms are unclear. We previously observed that gene variants involved with estrogen metabolism were collectively associated with POAG in women but not men; here we assessed gene variants related to testosterone metabolism collectively and POAG risk. Methods:We used two datasets: one from the United States (3853 cases and 33,480 controls) and another from Australia (1155 cases and 1992 controls). Both datasets contained densely called genotypes imputed to the 1000 Genomes reference panel. We used pathway- and gene-based approaches with Pathway Analysis by Randomization Incorporating Structure (PARIS) software to assess the overall association between a panel of single nucleotide polymorphisms (SNPs) in testosterone metabolism genes and POAG. In sex-stratified analyses, we evaluated POAG overall and POAG subtypes defined by maximum IOP (high-tension [HTG] or normal tension glaucoma [NTG]). Results:In the US dataset, the SNP panel was not associated with POAG (permuted P = 0.77), although there was an association in the Australian sample (permuted P = 0.018). In both datasets, the SNP panel was associated with POAG in men (permuted P ≤ 0.033) and not women (permuted P ≥ 0.42), but in gene-based analyses, there was no consistency on the main genes responsible for these findings. In both datasets, the testosterone pathway association with HTG was significant (permuted P ≤ 0.011), but again, gene-based analyses showed no consistent driver gene associations. Conclusions:Collectively, testosterone metabolism pathway SNPs were consistently associated with the high-tension subtype of POAG in two datasets.

Primary open-angle glaucoma (POAG) is the most common chronic optic neuropathy worldwide. Epidemiological studies show a robust positive relation between intraocular pressure (IOP) and POAG and modest positive association between IOP and blood pressure (BP), while the relation between BP and POAG is controversial. The International Glaucoma Genetics Consortium (n=27 558), the International Consortium on Blood Pressure (n=69 395), and the National Eye Institute Glaucoma Human Genetics Collaboration Heritable Overall Operational Database (n=37 333), represent genome-wide data sets for IOP, BP traits and POAG, respectively. We formed genome-wide significant variant panels for IOP and diastolic BP and found a strong relation with POAG (odds ratio and 95% confidence interval: 1.18 (1.14-1.21), P=1.8 × 10-27) for the former trait but no association for the latter (P=0.93). Next, we used linkage disequilibrium (LD) score regression, to provide genome-wide estimates of correlation between traits without the need for additional phenotyping. We also compared our genome-wide estimate of heritability between IOP and BP to an estimate based solely on direct measures of these traits in the Erasmus Rucphen Family (ERF; n=2519) study using Sequential Oligogenic Linkage Analysis Routines (SOLAR). LD score regression revealed high genetic correlation between IOP and POAG (48.5%, P=2.1 × 10-5); however, genetic correlation between IOP and diastolic BP (P=0.86) and between diastolic BP and POAG (P=0.42) were negligible. Using SOLAR in the ERF study, we confirmed the minimal heritability between IOP and diastolic BP (P=0.63). Overall, IOP shares genetic basis with POAG, whereas BP has limited shared genetic correlation with IOP or POAG.

ObjectiveSeveral attributes of female reproductive history, including age at natural menopause (ANM), have been related to primary open-angle glaucoma (POAG). We assembled 18 previously reported common genetic variants that predict ANM to determine their association with ANM or POAG.MethodsUsing data from the Nurses' Health Study (7,143 women), we validated the ANM weighted genetic risk score in relation to self-reported ANM. Subsequently, to assess the relation with POAG, we used data from 2,160 female POAG cases and 29,110 controls in the National Eye Institute Glaucoma Human Genetics Collaboration Heritable Overall Operational Database (NEIGHBORHOOD), which consists of 8 datasets with imputed genotypes to 5.6+ million markers. Associations with POAG were assessed in each dataset, and site-specific results were meta-analyzed using the inverse weighted variance method.ResultsThe genetic risk score was associated with self-reported ANM (P = 2.2 × 10) and predicted 4.8% of the variance in ANM. The ANM genetic risk score was not associated with POAG (Odds Ratio (OR) = 1.002; 95% Confidence Interval (CI): 0.998, 1.007; P = 0.28). No single genetic variant in the panel achieved nominal association with POAG (P ≥0.20). Compared to the middle 80 percent, there was also no association with the lowest 10 percentile or highest 90 percentile of genetic risk score with POAG (OR = 0.75; 95% CI: 0.47, 1.21; P = 0.23 and OR = 1.10; 95% CI: 0.72, 1.69; P = 0.65, respectively).ConclusionsA genetic risk score predicting 4.8% of ANM variation was not related to POAG; thus, genetic determinants of ANM are unlikely to explain the previously reported association between the two phenotypes.

PurposeAccurate risk assessment is necessary for decision-making around breast cancer prevention. We aimed to develop a breast cancer prediction model for postmenopausal women that would take into account their individualized competing risk of non-breast cancer death.MethodsWe included 73,066 women who completed the 2004 Nurses' Health Study (NHS) questionnaire (all ≥57 years) and followed participants until May 2014. We considered 17 breast cancer risk factors (health behaviors, demographics, family history, reproductive factors) and 7 risk factors for non-breast cancer death (comorbidities, functional dependency) and mammography use. We used competing risk regression to identify factors independently associated with breast cancer. We validated the final model by examining calibration (expected-to-observed ratio of breast cancer incidence, E/O) and discrimination (c-statistic) using 74,887 subjects from the Women's Health Initiative Extension Study (WHI-ES; all were ≥55 years and followed for 5 years).ResultsWithin 5 years, 1.8 % of NHS participants were diagnosed with breast cancer (vs. 2.0 % in WHI-ES, p = 0.02), and 6.6 % experienced non-breast cancer death (vs. 5.2 % in WHI-ES, p