Background

Reproductive factors provide an early window into a woman's coronary heart disease (CHD) risk; however, their contribution to CHD risk stratification is uncertain.

Methods and results

In the Women's Health Initiative Observational Study, we constructed Cox proportional hazards models for CHD including age, pregnancy status, number of live births, age at menarche, menstrual irregularity, age at first birth, stillbirths, miscarriages, infertility ≥1 year, infertility cause, and breastfeeding. We next added each candidate reproductive factor to an established CHD risk factor model. A final model was then constructed with significant reproductive factors added to established CHD risk factors. Improvement in C statistic, net reclassification index (or net reclassification index with risk categories of <5%, 5 to <10%, and ≥10% 10-year risk of CHD), and integrated discriminatory index were assessed. Among 72 982 women (CHD events, n=4607; median follow-up,12.0 [interquartile range, 8.3-13.7] years; mean [standard deviation] age, 63.2 [7.2] years), an age-adjusted reproductive risk factor model had a C statistic of 0.675 for CHD. In a model adjusted for established CHD risk factors, younger age at first birth, number of still births, number of miscarriages, and lack of breastfeeding were positively associated with CHD. Reproductive factors modestly improved model discrimination (C statistic increased from 0.726 to 0.730; integrated discriminatory index, 0.0013; P<0.0001). Net reclassification for women with events was not improved (net reclassification index events, 0.007; P=0.18); and, for women without events, net reclassification was marginally improved (net reclassification index nonevents, 0.002; P=0.04) CONCLUSIONS: Key reproductive factors are associated with CHD independently of established CHD risk factors, very modestly improve model discrimination, and do not materially improve net reclassification.

Candidate gene and genome-wide association studies (GWAS) have identified 15 independent genomic regions associated with bladder cancer risk. In search for additional susceptibility variants, we followed up on four promising single-nucleotide polymorphisms (SNPs) that had not achieved genome-wide significance in 6911 cases and 11 814 controls (rs6104690, rs4510656, rs5003154 and rs4907479, P < 1 × 10(-6)), using additional data from existing GWAS datasets and targeted genotyping for studies that did not have GWAS data. In a combined analysis, which included data on up to 15 058 cases and 286 270 controls, two SNPs achieved genome-wide statistical significance: rs6104690 in a gene desert at 20p12.2 (P = 2.19 × 10(-11)) and rs4907479 within the MCF2L gene at 13q34 (P = 3.3 × 10(-10)). Imputation and fine-mapping analyses were performed in these two regions for a subset of 5551 bladder cancer cases and 10 242 controls. Analyses at the 13q34 region suggest a single signal marked by rs4907479. In contrast, we detected two signals in the 20p12.2 region-the first signal is marked by rs6104690, and the second signal is marked by two moderately correlated SNPs (r(2) = 0.53), rs6108803 and the previously reported rs62185668. The second 20p12.2 signal is more strongly associated with the risk of muscle-invasive (T2-T4 stage) compared with non-muscle-invasive (Ta, T1 stage) bladder cancer (case-case P ≤ 0.02 for both rs62185668 and rs6108803). Functional analyses are needed to explore the biological mechanisms underlying these novel genetic associations with risk for bladder cancer.