Genetic insights into biological mechanisms governing human ovarian ageing.

Reproductive longevity is essential for fertility and influences healthy ageing in women1,2, but insights into its underlying biological mechanisms and treatments to preserve it are limited. Here we identify 290 genetic determinants of ovarian ageing, assessed using normal variation in age at natural menopause (ANM) in about 200,000 women of European ancestry. These common alleles were associated with clinical extremes of ANM; women in the top 1% of genetic susceptibility have an equivalent risk of premature ovarian insufficiency to those carrying monogenic FMR1 premutations3. The identified loci implicate a broad range of DNA damage response (DDR) processes and include loss-of-function variants in key DDR-associated genes. Integration with experimental models demonstrates that these DDR processes act across the life-course to shape the ovarian reserve and its rate of depletion. Furthermore, we demonstrate that experimental manipulation of DDR pathways highlighted by human genetics increases fertility and extends reproductive life in mice. Causal inference analyses using the identified genetic variants indicate that extending reproductive life in women improves bone health and reduces risk of type 2 diabetes, but increases the risk of hormone-sensitive cancers. These findings provide insight into the mechanisms that govern ovarian ageing, when they act, and how they might be targeted by therapeutic approaches to extend fertility and prevent disease.

Genome- and transcriptome-wide association studies of 386,000 Asian and European-ancestry women provide new insights into breast cancer genetics.

By combining data from 160,500 individuals with breast cancer and 226,196 controls of Asian and European ancestry, we conducted genome- and transcriptome-wide association studies of breast cancer. We identified 222 genetic risk loci and 137 genes that were associated with breast cancer risk at a p < 5.0 × 10-8 and a Bonferroni-corrected p < 4.6 × 10-6, respectively. Of them, 32 loci and 15 genes showed a significantly different association between ER-positive and ER-negative breast cancer after Bonferroni correction. Significant ancestral differences in risk variant allele frequencies and their association strengths with breast cancer risk were identified. Of the significant associations identified in this study, 17 loci and 14 genes are located 1Mb away from any of the previously reported breast cancer risk variants. Pathways analyses including 221 putative risk genes identified multiple signaling pathways that may play a significant role in the development of breast cancer. Our study provides a comprehensive understanding of and new biological insights into the genetics of this common malignancy.

Functional annotation of the 2q35 breast cancer risk locus implicates a structural variant in influencing activity of a long-range enhancer element.

A combination of genetic and functional approaches has identified three independent breast cancer risk loci at 2q35. A recent fine-scale mapping analysis to refine these associations resulted in 1 (signal 1), 5 (signal 2), and 42 (signal 3) credible causal variants at these loci. We used publicly available in silico DNase I and ChIP-seq data with in vitro reporter gene and CRISPR assays to annotate signals 2 and 3. We identified putative regulatory elements that enhanced cell-type-specific transcription from the IGFBP5 promoter at both signals (30- to 40-fold increased expression by the putative regulatory element at signal 2, 2- to 3-fold by the putative regulatory element at signal 3). We further identified one of the five credible causal variants at signal 2, a 1.4 kb deletion (esv3594306), as the likely causal variant; the deletion allele of this variant was associated with an average additional increase in IGFBP5 expression of 1.3-fold (MCF-7) and 2.2-fold (T-47D). We propose a model in which the deletion allele of esv3594306 juxtaposes two transcription factor binding regions (annotated by estrogen receptor alpha ChIP-seq peaks) to generate a single extended regulatory element. This regulatory element increases cell-type-specific expression of the tumor suppressor gene IGFBP5 and, thereby, reduces risk of estrogen receptor-positive breast cancer (odds ratio = 0.77, 95% CI 0.74-0.81, p = 3.1 × 10-31).

Disentangling the relationships of body mass index and circulating sex hormone concentrations in mammographic density using Mendelian randomization.

PURPOSE: Mammographic density phenotypes, adjusted for age and body mass index (BMI), are strong predictors of breast cancer risk. BMI is associated with mammographic density measures, but the role of circulating sex hormone concentrations is less clear. We investigated the relationship between BMI, circulating sex hormone concentrations, and mammographic density phenotypes using Mendelian randomization (MR). METHODS: We applied two-sample MR approaches to assess the association between genetically predicted circulating concentrations of sex hormones [estradiol, testosterone, sex hormone-binding globulin (SHBG)], BMI, and mammographic density phenotypes (dense and non-dense area). We created instrumental variables from large European ancestry-based genome-wide association studies and applied estimates to mammographic density phenotypes in up to 14,000 women of European ancestry. We performed analyses overall and by menopausal status. RESULTS: Genetically predicted BMI was positively associated with non-dense area (IVW: ß = 1.79; 95% CI = 1.58, 2.00; p = 9.57 × 10-63) and inversely associated with dense area (IVW: ß = - 0.37; 95% CI = - 0.51,- 0.23; p = 4.7 × 10-7). We observed weak evidence for an association of circulating sex hormone concentrations with mammographic density phenotypes, specifically inverse associations between genetically predicted testosterone concentration and dense area (ß = - 0.22; 95% CI = - 0.38, - 0.053; p = 0.009) and between genetically predicted estradiol concentration and non-dense area (ß = - 3.32; 95% CI = - 5.83, - 0.82; p = 0.009), although results were not consistent across a range of MR approaches. CONCLUSION: Our findings support a positive causal association between BMI and mammographic non-dense area and an inverse association between BMI and dense area. Evidence was weaker and inconsistent for a causal effect of circulating sex hormone concentrations on mammographic density phenotypes. Based on our findings, associations between circulating sex hormone concentrations and mammographic density phenotypes are weak at best.

A likelihood ratio approach for utilizing case-control data in the clinical classification of rare sequence variants: application to BRCA1 and BRCA2.

A large number of variants identified through clinical genetic testing in disease susceptibility genes, are of uncertain significance (VUS). Following the recommendations of the American College of Medical Genetics and Genomics (ACMG) and Association for Molecular Pathology (AMP), the frequency in case-control datasets (PS4 criterion), can inform their interpretation. We present a novel case-control likelihood ratio-based method that incorporates gene-specific age-related penetrance. We demonstrate the utility of this method in the analysis of simulated and real datasets. In the analyses of simulated data, the likelihood ratio method was more powerful compared to other methods. Likelihood ratios were calculated for a case-control dataset of BRCA1 and BRCA2 variants from the Breast Cancer Association Consortium (BCAC), and compared with logistic regression results. A larger number of variants reached evidence in favor of pathogenicity, and a substantial number of variants had evidence against pathogenicity - findings that would not have been reached using other case-control analysis methods. Our novel method provides greater power to classify rare variants compared to classical case-control methods. As an initiative from the ENIGMA Analytical Working Group, we provide user-friendly scripts and pre-formatted excel calculators for implementation of the method for rare variants in BRCA1, BRCA2 and other high-risk genes with known penetrance.

A genome-wide gene-environment interaction study of breast cancer risk for women of European ancestry.

BACKGROUND: Genome-wide studies of gene-environment interactions (G×E) may identify variants associated with disease risk in conjunction with lifestyle/environmental exposures. We conducted a genome-wide G×E analysis of ~ 7.6 million common variants and seven lifestyle/environmental risk factors for breast cancer risk overall and for estrogen receptor positive (ER +) breast cancer. METHODS: Analyses were conducted using 72,285 breast cancer cases and 80,354 controls of European ancestry from the Breast Cancer Association Consortium. Gene-environment interactions were evaluated using standard unconditional logistic regression models and likelihood ratio tests for breast cancer risk overall and for ER + breast cancer. Bayesian False Discovery Probability was employed to assess the noteworthiness of each SNP-risk factor pairs. RESULTS: Assuming a 1 × 10-5 prior probability of a true association for each SNP-risk factor pairs and a Bayesian False Discovery Probability < 15%, we identified two independent SNP-risk factor pairs: rs80018847(9p13)-LINGO2 and adult height in association with overall breast cancer risk (ORint = 0.94, 95% CI 0.92-0.96), and rs4770552(13q12)-SPATA13 and age at menarche for ER + breast cancer risk (ORint = 0.91, 95% CI 0.88-0.94). CONCLUSIONS: Overall, the contribution of G×E interactions to the heritability of breast cancer is very small. At the population level, multiplicative G×E interactions do not make an important contribution to risk prediction in breast cancer.

Breast Cancer Polygenic Risk Score and Contralateral Breast Cancer Risk.

Previous research has shown that polygenic risk scores (PRSs) can be used to stratify women according to their risk of developing primary invasive breast cancer. This study aimed to evaluate the association between a recently validated PRS of 313 germline variants (PRS313) and contralateral breast cancer (CBC) risk. We included 56,068 women of European ancestry diagnosed with first invasive breast cancer from 1990 onward with follow-up from the Breast Cancer Association Consortium. Metachronous CBC risk (N = 1,027) according to the distribution of PRS313 was quantified using Cox regression analyses. We assessed PRS313 interaction with age at first diagnosis, family history, morphology, ER status, PR status, and HER2 status, and (neo)adjuvant therapy. In studies of Asian women, with limited follow-up, CBC risk associated with PRS313 was assessed using logistic regression for 340 women with CBC compared with 12,133 women with unilateral breast cancer. Higher PRS313 was associated with increased CBC risk: hazard ratio per standard deviation (SD) = 1.25 (95%CI = 1.18-1.33) for Europeans, and an OR per SD = 1.15 (95%CI = 1.02-1.29) for Asians. The absolute lifetime risks of CBC, accounting for death as competing risk, were 12.4% for European women at the 10th percentile and 20.5% at the 90th percentile of PRS313. We found no evidence of confounding by or interaction with individual characteristics, characteristics of the primary tumor, or treatment. The C-index for the PRS313 alone was 0.563 (95%CI = 0.547-0.586). In conclusion, PRS313 is an independent factor associated with CBC risk and can be incorporated into CBC risk prediction models to help improve stratification and optimize surveillance and treatment strategies.

Association analysis identifies 65 new breast cancer risk loci.

Breast cancer risk is influenced by rare coding variants in susceptibility genes, such as BRCA1, and many common, mostly non-coding variants. However, much of the genetic contribution to breast cancer risk remains unknown. Here we report the results of a genome-wide association study of breast cancer in 122,977 cases and 105,974 controls of European ancestry and 14,068 cases and 13,104 controls of East Asian ancestry. We identified 65 new loci that are associated with overall breast cancer risk at P < 5 × 10-8. The majority of credible risk single-nucleotide polymorphisms in these loci fall in distal regulatory elements, and by integrating in silico data to predict target genes in breast cells at each locus, we demonstrate a strong overlap between candidate target genes and somatic driver genes in breast tumours. We also find that heritability of breast cancer due to all single-nucleotide polymorphisms in regulatory features was 2-5-fold enriched relative to the genome-wide average, with strong enrichment for particular transcription factor binding sites. These results provide further insight into genetic susceptibility to breast cancer and will improve the use of genetic risk scores for individualized screening and prevention.

Common variants in breast cancer risk loci predispose to distinct tumor subtypes.

BACKGROUND: Genome-wide association studies (GWAS) have identified multiple common breast cancer susceptibility variants. Many of these variants have differential associations by estrogen receptor (ER) status, but how these variants relate with other tumor features and intrinsic molecular subtypes is unclear. METHODS: Among 106,571 invasive breast cancer cases and 95,762 controls of European ancestry with data on 173 breast cancer variants identified in previous GWAS, we used novel two-stage polytomous logistic regression models to evaluate variants in relation to multiple tumor features (ER, progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2) and grade) adjusting for each other, and to intrinsic-like subtypes. RESULTS: Eighty-five of 173 variants were associated with at least one tumor feature (false discovery rate < 5%), most commonly ER and grade, followed by PR and HER2. Models for intrinsic-like subtypes found nearly all of these variants (83 of 85) associated at p < 0.05 with risk for at least one luminal-like subtype, and approximately half (41 of 85) of the variants were associated with risk of at least one non-luminal subtype, including 32 variants associated with triple-negative (TN) disease. Ten variants were associated with risk of all subtypes in different magnitude. Five variants were associated with risk of luminal A-like and TN subtypes in opposite directions. CONCLUSION: This report demonstrates a high level of complexity in the etiology heterogeneity of breast cancer susceptibility variants and can inform investigations of subtype-specific risk prediction.

Polygenic Risk Scores for Prediction of Breast Cancer and Breast Cancer Subtypes.

Stratification of women according to their risk of breast cancer based on polygenic risk scores (PRSs) could improve screening and prevention strategies. Our aim was to develop PRSs, optimized for prediction of estrogen receptor (ER)-specific disease, from the largest available genome-wide association dataset and to empirically validate the PRSs in prospective studies. The development dataset comprised 94,075 case subjects and 75,017 control subjects of European ancestry from 69 studies, divided into training and validation sets. Samples were genotyped using genome-wide arrays, and single-nucleotide polymorphisms (SNPs) were selected by stepwise regression or lasso penalized regression. The best performing PRSs were validated in an independent test set comprising 11,428 case subjects and 18,323 control subjects from 10 prospective studies and 190,040 women from UK Biobank (3,215 incident breast cancers). For the best PRSs (313 SNPs), the odds ratio for overall disease per 1 standard deviation in ten prospective studies was 1.61 (95%CI: 1.57-1.65) with area under receiver-operator curve (AUC) = 0.630 (95%CI: 0.628-0.651). The lifetime risk of overall breast cancer in the top centile of the PRSs was 32.6%. Compared with women in the middle quintile, those in the highest 1% of risk had 4.37- and 2.78-fold risks, and those in the lowest 1% of risk had 0.16- and 0.27-fold risks, of developing ER-positive and ER-negative disease, respectively. Goodness-of-fit tests indicated that this PRS was well calibrated and predicts disease risk accurately in the tails of the distribution. This PRS is a powerful and reliable predictor of breast cancer risk that may improve breast cancer prevention programs.

Investigating the relationship between melatonin patterns and methylation in circadian genes among day shift and night shift workers.

OBJECTIVES: Mechanisms underlying the carcinogenicity of night shift work remain uncertain. One compelling yet understudied cancer mechanism may involve altered DNA methylation in circadian genes due to melatonin secretion patterns. The objective of this study was to explore the relationship between melatonin secretion patterns and circadian gene methylation among day and night shift workers. METHODS: Female healthcare employees (n=38 day workers, n=36 night shift workers) for whom we had urinary 6-sulfatoxymelatonin secretion data from a previous study were recontacted. New blood samples were collected and used to measure methylation levels at 1150 CpG loci across 22 circadian genes using the Illumina Infinium MethylationEPIC beadchip. Linear regression was used to examine the association between melatonin (acrophase and mesor) and M values for each CpG site (false discovery rate, q=0.2), while testing for effect modification by shift work status. RESULTS: Among night shift workers, a higher mesor (24 hours of mean production of melatonin) was associated with increased methylation in the body of RORA (q=0.02) and decreased methylation in the putative promoter region of MTNR1A (q=0.03). Later acrophase (ie, time of peak concentration) was associated with increased methylation in the putative promoter region of MTNR1A (q=0.20) and decreased methylation in the body of PER3 (q=0.20). No associations were identified among day workers. CONCLUSIONS: In conclusion, patterns in melatonin secretion were associated with differential circadian gene methylation among night shift workers. Melatonin and alteration of DNA methylation in circadian genes may be one pathway towards increased cancer risk, although larger-scale studies examining multiple time points are needed.

Physical activity, sedentary time and breast cancer risk: a Mendelian randomisation study.

OBJECTIVES: Physical inactivity and sedentary behaviour are associated with higher breast cancer risk in observational studies, but ascribing causality is difficult. Mendelian randomisation (MR) assesses causality by simulating randomised trial groups using genotype. We assessed whether lifelong physical activity or sedentary time, assessed using genotype, may be causally associated with breast cancer risk overall, pre/post-menopause, and by case-groups defined by tumour characteristics. METHODS: We performed two-sample inverse-variance-weighted MR using individual-level Breast Cancer Association Consortium case-control data from 130 957 European-ancestry women (69 838 invasive cases), and published UK Biobank data (n=91 105-377 234). Genetic instruments were single nucleotide polymorphisms (SNPs) associated in UK Biobank with wrist-worn accelerometer-measured overall physical activity (nsnps=5) or sedentary time (nsnps=6), or accelerometer-measured (nsnps=1) or self-reported (nsnps=5) vigorous physical activity. RESULTS: Greater genetically-predicted overall activity was associated with lower breast cancer overall risk (OR=0.59; 95% confidence interval (CI) 0.42 to 0.83 per-standard deviation (SD;~8 milligravities acceleration)) and for most case-groups. Genetically-predicted vigorous activity was associated with lower risk of pre/perimenopausal breast cancer (OR=0.62; 95% CI 0.45 to 0.87,≥3 vs. 0 self-reported days/week), with consistent estimates for most case-groups. Greater genetically-predicted sedentary time was associated with higher hormone-receptor-negative tumour risk (OR=1.77; 95% CI 1.07 to 2.92 per-SD (~7% time spent sedentary)), with elevated estimates for most case-groups. Results were robust to sensitivity analyses examining pleiotropy (including weighted-median-MR, MR-Egger). CONCLUSION: Our study provides strong evidence that greater overall physical activity, greater vigorous activity, and lower sedentary time are likely to reduce breast cancer risk. More widespread adoption of active lifestyles may reduce the burden from the most common cancer in women.

Transcriptome-wide association study of breast cancer risk by estrogen-receptor status.

Previous transcriptome-wide association studies (TWAS) have identified breast cancer risk genes by integrating data from expression quantitative loci and genome-wide association studies (GWAS), but analyses of breast cancer subtype-specific associations have been limited. In this study, we conducted a TWAS using gene expression data from GTEx and summary statistics from the hitherto largest GWAS meta-analysis conducted for breast cancer overall, and by estrogen receptor subtypes (ER+ and ER-). We further compared associations with ER+ and ER- subtypes, using a case-only TWAS approach. We also conducted multigene conditional analyses in regions with multiple TWAS associations. Two genes, STXBP4 and HIST2H2BA, were specifically associated with ER+ but not with ER- breast cancer. We further identified 30 TWAS-significant genes associated with overall breast cancer risk, including four that were not identified in previous studies. Conditional analyses identified single independent breast-cancer gene in three of six regions harboring multiple TWAS-significant genes. Our study provides new information on breast cancer genetics and biology, particularly about genomic differences between ER+ and ER- breast cancer.

CYP3A7*1C allele: linking premenopausal oestrone and progesterone levels with risk of hormone receptor-positive breast cancers.

BACKGROUND: Epidemiological studies provide strong evidence for a role of endogenous sex hormones in the aetiology of breast cancer. The aim of this analysis was to identify genetic variants that are associated with urinary sex-hormone levels and breast cancer risk. METHODS: We carried out a genome-wide association study of urinary oestrone-3-glucuronide and pregnanediol-3-glucuronide levels in 560 premenopausal women, with additional analysis of progesterone levels in 298 premenopausal women. To test for the association with breast cancer risk, we carried out follow-up genotyping in 90,916 cases and 89,893 controls from the Breast Cancer Association Consortium. All women were of European ancestry. RESULTS: For pregnanediol-3-glucuronide, there were no genome-wide significant associations; for oestrone-3-glucuronide, we identified a single peak mapping to the CYP3A locus, annotated by rs45446698. The minor rs45446698-C allele was associated with lower oestrone-3-glucuronide (-49.2%, 95% CI -56.1% to -41.1%, P = 3.1 × 10-18); in follow-up analyses, rs45446698-C was also associated with lower progesterone (-26.7%, 95% CI -39.4% to -11.6%, P = 0.001) and reduced risk of oestrogen and progesterone receptor-positive breast cancer (OR = 0.86, 95% CI 0.82-0.91, P = 6.9 × 10-8). CONCLUSIONS: The CYP3A7*1C allele is associated with reduced risk of hormone receptor-positive breast cancer possibly mediated via an effect on the metabolism of endogenous sex hormones in premenopausal women.

Mendelian randomisation study of smoking exposure in relation to breast cancer risk.

BACKGROUND: Despite a modest association between tobacco smoking and breast cancer risk reported by recent epidemiological studies, it is still equivocal whether smoking is causally related to breast cancer risk. METHODS: We applied Mendelian randomisation (MR) to evaluate a potential causal effect of cigarette smoking on breast cancer risk. Both individual-level data as well as summary statistics for 164 single-nucleotide polymorphisms (SNPs) reported in genome-wide association studies of lifetime smoking index (LSI) or cigarette per day (CPD) were used to obtain MR effect estimates. Data from 108,420 invasive breast cancer cases and 87,681 controls were used for the LSI analysis and for the CPD analysis conducted among ever-smokers from 26,147 cancer cases and 26,072 controls. Sensitivity analyses were conducted to address pleiotropy. RESULTS: Genetically predicted LSI was associated with increased breast cancer risk (OR 1.18 per SD, 95% CI: 1.07-1.30, P = 0.11 × 10-2), but there was no evidence of association for genetically predicted CPD (OR 1.02, 95% CI: 0.78-1.19, P = 0.85). The sensitivity analyses yielded similar results and showed no strong evidence of pleiotropic effect. CONCLUSION: Our MR study provides supportive evidence for a potential causal association with breast cancer risk for lifetime smoking exposure but not cigarettes per day among smokers.

Outdoor light at night at residences and breast cancer risk in Canada.

Experimental and epidemiologic studies suggest that light at night (LAN) exposure disrupts circadian rhythm, and this disruption may increase breast cancer risk. We investigated the potential association between residential outdoor LAN and breast cancer risk. A population-based case-control study was conducted in Vancouver, British Columbia and Kingston, Ontario, Canada with incident breast cancer cases, and controls frequency matched by age in the same region. This analysis was restricted to 844 cases and 905 controls who provided lifetime residential histories. Using time-weighted average duration at each home 5-20 years prior to study entry, two measures of cumulative average outdoor LAN were calculated using two satellite data sources. Logistic regression was used to estimate the relationship between outdoor LAN and breast cancer risk, considering interactions for menopausal status and night shift work. We found no association between residential outdoor LAN and breast cancer for either measure of LAN [OR comparing highest vs. lowest tertile (DNB) = 0.95, 95% CI 0.70-1.27]. We also found no association when considering interactions for menopausal status and past/current night work status. These findings were robust to changes to years of residential data considered, residential mobility, and longer exposure windows. Our findings are consistent with studies reporting that outdoor LAN has a small effect or no effect on breast cancer risk.

Women's occupational exposure to polycyclic aromatic hydrocarbons and risk of breast cancer.

OBJECTIVE: To estimate the association between occupational polycyclic aromatic hydrocarbon (PAH) exposure and female breast cancer. METHODS: Lifetime work histories for 1130 cases and 1169 controls from British Columbia and Ontario (Canada) were assessed for PAH exposure using a job-exposure matrix based on compliance measurements obtained during US Occupational Safety and Health Administration workplace safety inspections. RESULTS: Exposure to any level of PAHs was associated with an increased risk of breast cancer (OR=1.32, 95% CI: 1.10 to 1.59), as was duration at high PAH exposure (for >7.4 years: OR=1.45, 95% CI: 1.10 to 1.91; ptrend=0.01), compared with women who were never exposed. Increased risk of breast cancer was most strongly associated with prolonged duration at high occupational PAH exposure among women with a family history of breast cancer (for >7.4 years: OR=2.79, 95% CI: 1.25 to 6.24; ptrend<0.01). CONCLUSIONS: Our study suggests that prolonged occupational exposure to PAH may increase breast cancer risk, especially among women with a family history of breast cancer.

Mammographic non-dense area and breast cancer risk in postmenopausal women: a causal inference approach in a case-control study.

PURPOSE: The association between high mammographic density (MD) and elevated breast cancer risk is well established. However, the role of absolute non-dense area remains unclear. We estimated the effect of the mammographic non-dense area and other density parameters on the risk of breast cancer. METHODS: This study utilizes data from a population-based case-control study conducted in Greater Vancouver, British Columbia, with 477 female postmenopausal breast cancer cases and 588 female postmenopausal controls. MD measures were determined from digitized screening mammograms using computer-assisted software (Cumulus). Marginal odds ratios were estimated by inverse-probability weighting using a causal diagram for confounder selection. Akaike information criteria and receiver operating characteristic curves were used to assess the goodness of fit and predictive power of unconditional logistic models containing MD parameters. RESULTS: The risk of breast cancer is 60% lower for the highest quartile compared to the lowest quartile of mammographic non-dense area (marginal OR 0.40, 95% CI 0.26-0.61, p-trend < 0.001). The cancer risk almost doubles for the highest quartile compared to the lowest quartile of dense area (marginal OR 1.81, 95% CI 1.19-2.43, p-trend < 0.001). For the highest quartile of percent density, breast cancer risk was more than three times higher than for the lowest quartile (marginal OR 3.15, 95% CI 1.90-4.40, p-trend < 0.001). No difference was seen in predictive accuracy between models using percent density alone, dense area alone, or non-dense area plus dense area. CONCLUSIONS: In this study, non-dense area is an independent risk factor after adjustment for dense area and other covariates, inversely related with the risk of breast cancer. However, non-dense area does not improve prediction over that offered by percent density or dense area alone.

Actigraph measures of sleep among female hospital employees working day or alternating day and night shifts.

Sleep disturbance is common among shift workers, and may be an important factor in the effect of shift work on chronic disease development. In this cross-sectional study, we described sleep patterns of 294 female hospital workers (142 alternating day-night shift workers, 152 day workers) and determined associations between shift work and sleep duration. Rest-activity cycles were recorded with the ActiGraph GT3X+ for 1 week. Analyses were stratified by chronotype of shift workers. Using all study days to calculate average sleep duration, shift workers slept approximately 13 min less than day workers during main sleep periods, while 24-h sleep duration did not differ between day workers and shift workers. Results from age-adjusted models demonstrated that all shift workers, regardless of chronotype, slept 20-30 min less than day workers on day shifts during main and total sleep. Early and intermediate chronotypes working night shifts slept between 114 and 125 min less than day workers, both with regard to the main sleep episode and 24-h sleep duration, while the difference was less pronounced among late chronotypes. When sleep duration on free days was compared between shift workers and day workers, only shift workers with late chronotypes slept less, by approximately 50 min, than day workers during main sleep. Results from this study demonstrate how an alternating day-night shift work schedule impacts sleep negatively among female hospital workers, and the importance of considering chronotype in sleep research among shift workers.

Night shift work and breast cancer: a pooled analysis of population-based case-control studies with complete work history.

Night shift work has been suspected to increase breast cancer risk but epidemiological studies have been inconsistent due to heterogeneous assessment of exposure to night work. To overcome this limitation, we pooled data of five population-based case-control studies from Australia, Canada, France, Germany, and Spain into a single harmonized dataset using a common definition of night work including 6093 breast cancer cases and 6933 population controls. The odds ratio for breast cancer in women who ever worked at night for at least 3 h between midnight and 5 a.m. as compared to never night workers was 1.12 (95% CI 1.00-1.25). Among pre-menopausal women, this odds ratio was 1.26 [1.06-1.51], increasing to 1.36 [1.07-1.74] for night shifts ≥ 10 h, 1.80 [1.20-2.71] for work ≥ 3 nights/week, and 2.55 [1.03-6.30] for both duration of night work ≥ 10 years and exposure intensity ≥ 3 nights/week. Breast cancer risk in pre-menopausal women was higher in current or recent night workers (OR = 1.41 [1.06-1.88]) than in those who had stopped night work more than 2 years ago. Breast cancer in post-menopausal women was not associated with night work whatever the exposure metric. The increase in risk was restricted to ER+ tumors, particularly those who were both ER+ and HER2+ . These results support the hypothesis that night shift work increases the risk of breast cancer in pre-menopausal women, particularly those with high intensity and long duration of exposure. Risk difference between pre- and post-menopausal women deserves further scrutiny.