The prevalence of vitamin D inadequacy and breast cancer are both high among women living in Karachi, Pakistan.A matched case control study was conducted in two hospitals of Karachi, Pakistan to evaluate the association of vitamin D (serum 25-hydroxyvitamin D) concentrations, vitamin D supplementation and sun exposure with breast cancer among Pakistani women. A total of 411 newly diagnosed histologically confirmed primary breast cancer cases were enrolled and 784 controls, free of breast and any other cancers, were matched by age (year of birth ± 5 years), residence in the same geographic area and study site. Information was collected on sociodemographic history, history of vitamin D supplementation, past medical and obstetrical history, family history of breast cancer, sun exposure history, histopathology reports and anthropometric measurement and venous blood was collected to measure serum 25-hydroxyvitamin D (25(OH)D) concentration.Compared to patients with sufficient serum vitamin D (>30 ng/ml), women with serum vitamin D deficiency (<20ng/ml), had a higher risk of breast cancer . Women with history of vitamin D supplementation one year prior to enrollment, had significant protective effect against breast cancer .Serum vitamin D deficiency was associated with increased risk of breast cancer, while vitamin D supplementation was associated with decreased risk of breast cancer. In Pakistani women, where vitamin D deficiency is common, raising and maintaining serum vitamin D at population level is a safe and affordable strategy. It may play a role in reducing the incidence of both vitamin D deficiency and breast cancer, particularly among poor women where the breast cancer mortality is highest due to limited resources for early detection, diagnosis, and treatment. The effects of vitamin D with regard to breast cancer risk in Karachi Pakistan should be further evaluated. Cancer rates and the financial burdens of cancer treatments are increasing worldwide in both developed and developing countries , 2. In dThere is substantial evidence supporting the theory that hormonal mechanisms play a vital role in the etiology of breast cancer. Epidemiological studies and laboratory findings indicate that vitamin D has potential anticancer activity . An indiDespite the biological plausibility that vitamin D has an anticancer role, the literature on the relationship between breast cancer and 25(OH)D concentrations remains more controversial. The research findings evaluating the role of vitamin D as a possible preventive agent against breast cancer vary, and the optimal serum 25(OH)D concentration for cancer and other diseases prevention is still unknown . OverallEcological studies on large population living in diverse countries including Europe, China, Australia, France Japan and the USA have also consistently shown the protective association of increased UVB sun exposure and latitude on reducing breast cancer incidence and mortality –19. Howe2D between cases of breast cancer and their matched control subjects [Results from observational studies show a protective association of increased 25(OH)D concentrations against breast cancer which is observed more frequently in case control studies than in cohort studies –26. Prossubjects . These iThere is dearth of well-designed and conducted large randomized controlled trials (RCTs) to assess if vitamin D supplementation can increase serum 25(OH)D concentrations and reduce the incidence of breast cancer. Results vary, with some clinical trials supporting the results of association studies , 39, whiStudies in Asian population of breast cancer and the possible relationship with 25(OH)D concentrations, are limited –54. A stSince Pakistani population was reported to have low concentrations of serum 25(OH)D  and highThis matched case control study was conducted in Karachi, the 5th most populous city in the world with an estimated population of 24 million in 2017. Study participants were sourced from Aga Khan University Hospital (AKUH), which is a private JCIA accredited academic medical center, and the Karachi Institute of Radiation and Nuclear Medicine Hospital (KIRAN) which is a leading referral and cancer treatment public hospital and provides financial assistance for diagnosis and treatment on welfare basis, to more than 75% of its patients, who come from all over Pakistan.All women who were newly diagnosed with a primary histologically confirmed case of breast cancer between February 2015 to July 2018 were eligible as cases. Women who were extremely sick, unable to complete the interview, been living outside Pakistan for more than a year and diagnosis of breast cancer for greater than 6 months before study enrolment were excluded. Women receiving adjuvant or neoadjuvant chemotherapy or radiation, with diagnosis of non-epithelial breast tumor (ICD-O histology code 8800), and women lost to follow up during their metastatic and laboratory work up were also excluded from the study.For each patient two controls free of any cancer diagnosis were matched by age (year of birth ± 5 years), residence in the same geographic area and hospital. The control women were recruited from those attending in- and out-patient services for general medical, and surgical departments of the two participating hospitals and who had no previous diagnosis of breast cancer or any other cancer. The controls enrolled from surgery were those who came for follow up of mammography screening, with benign breast symptoms. Controls sourced from general medicine clinics had a range of medical conditions, for example diabetes, hypertension, headaches and anxiety. All efforts were made to avoid selection bias by proper selection of cases and controls and standardized, and uniform data collection procedures.The number of enrolled cases and controls subjects was decided based on certain assumptions. We assumed the prevalence of deficiency of vitamin D and other risk factors amongst the control group to be in the range of 10–90%. In an audit of blood samples at Aga Khan University, VDD noted was 66.1% . In ordeThe ethical approval was obtained by the Human Research Ethics Committee of the University of Adelaide and the Ethical Review Committees of two hospitals in Karachi Pakistan: Aga Khan University Hospital AKUH & Karachi Institute of Radiation and Nuclear Medicine Hospital KIRAN. Patients who were literate read and signed the informed consent form, and verbal consent was obtained from those who could not read or write.In the first phase, a pilot study was undertaken to pretest the complete questionnaire on a sample of 50 patients attending the outpatient department of Jinah Postgraduate Medical Center JPMC and AKUH between Aug 2014-Jan 2015. Those subjects were not included in the main study. The questionnaire was revised and finalized based on the pretest results, to ensure standardization and reliability of the questionnaire in urdu, the local language.All consenting participants were interviewed using the same structured questionnaire. The questionnaire was divided into different sections of sociodemographic history, history of any vitamin D supplementation, and past medical and obstetrical history, family history of breast cancer or any other cancer, sun exposure history, histopathology reports and anthropometric measurement. Where relevant, clinical notes and pathology reports were assessed. Socio demographic factors included age, ethnicity, education, marital status, place and type of residence, number of dependants and current employment status. Education was treated as an ordinal variable and categorized as <8, 8–12, or > 12 years of full-time study. Socio-economic (SES) factors included education, place and type of residence, crowding index, home ownership, number of rooms, total household members and total household monthly income. Crowding index was also calculated as number of household members divided by number of rooms and was further categorized as <1, 1–2, >2. Factor analysis was used to identify the important variables for socioeconomic status and a composite variable was calculated for socioeconomic status and categorized into upper, middle and poor.Participants self-reported their family history of breast cancer as none (no first-degree family history), or one first degree relative and age at diagnosis of breast cancer, or multiple affected first-degree relatives or second-degree relatives and ages at breast cancer diagnosis. Other variables assessed included reproductive history, body mass index (BMI), and history of benign breast disease. Histopathology and estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor (HER2/ neu) status of breast cancer cases were retrieved from medical records. Tumor characteristics relating to tumor size (T), nodes involved (N), and presence of metastasis (M) were also extracted from pathology reports and cancer staging expressed as stage I (the least advanced stage) to stage IV (the most advanced stage).The STROBE standardised reporting guidelines for case control studies were followed to ensure standardised conduct and reporting of the study .For all enrolled subjects venous blood samples (2.5 ml) were collected in yellow topped gel tubes. For breast cancer patients, collection was within 30 days of diagnosis of cancer and prior to chemotherapy, and from controls, at the end of the questionnaire interview. The collected blood was transported on the same day to the Section of Clinical Chemistry, Department of Pathology & Laboratory Medicine, at AKUH for biochemical analysis. Serum was separated by centrifugation and stored at -80°C until analysis. Serum 25(OH)D concentrations was measured by a kit from DiaMetra S.r.I. Headquarter: Via Garibaldi, 18–20090 SEGRATE (MI) Italy, using solid phase enzyme-linked immunoassay (ELISA) based on the principle of competitive binding. A dose response curve was used to ascertain 25(OH)D concentrations range in unknown specimens by using five human serum-based calibrators from C0 to C5 with concentration range from 0–120 ng/ml. The lowest detectable concentration of 25(OH)D that can be distinguished from the calibrator 0 was 0.3 ng/ml at 95% confidence limit. The assay had intra assay variability and inter assay variability of < 6.4% and <6.955 respectively. Five low and high vitamin D control samples provided with the kit were run with each batch of samples analysed for quality control. The AKUH laboratory participates in the College of American Pathologists CAP proficiency testing. The cut-off used to define VDD is the point where parathyroid hormone (PTH) starts to rise . VitaminThe use of vitamin D supplement , was assessed in relation to the index year, defined as one year prior to breast cancer diagnosis for cases or the interview for controls. Vitamin D supplementation was assessed by asking participants if they had been taking vitamin D supplements regularly, occasionally or not at all in their lifetime, with the mode of administration identified as either injections, oral tablets or ampoules. Similar information was used to assess use of multivitamins, name of the multivitamins, and vitamin D calcium combination supplementation with details about frequency of intake and the brands of tablets (where available) were also determined.The geographic location of Karachi  served as a surrogate measure for ultraviolet B (UVB) exposure. It should be noted that the climate of Karachi provides ample sunlight throughout the year for maintaining adequate 25(OH)D concentrations. To assess sun exposure among cases and controls, the validated long-term sun exposure measurement questionnaire (LT SEM-Q) was used. This questionnaire has been validated against gold standard ultraviolet (UV) dosimeters [Skin tone of the participants was assessed against a shade card by matching shade of the skin on the inner side of the forearm (unexposed part) of the participant and forehead (exposed part) with the shade on the card, according to LT SEM-Q, to match the skin tones of Asian population. Details of weights given to sun exposure variables are shown in Conditional logistic regression with matched sets as strata was used to compute odds ratios (ORs) and 95% confidence intervals (CIs) to evaluate the association of 25(OH)D, sun exposure, and vitamin D supplements with breast cancer. We examined potential confounding by the following covariates as categorical variables: socioeconomic status, education, parity, body mass index (BMI), first-degree family history of breast cancer, breastfeeding, and menopausal status. SPSS 22.0 software  was used where a p-value< 0.05 was accepted as significant for all statistical tests.To enable a more rigorous statistical analysis, cases and controls were categorized into four different concentrations of 25(OH)D, defined as severely deficient (<12 ng/ml), deficient (12–19 ng/ml), insufficient (20-30ng/ml) and sufficient (>30ng/ml) . VDD wasOverall 60.2% of women in Karachi had serum concentrations of 25(OH)D < 20ng/ml, which is considered to indicate vitamin D deficiency. A severe deficiency of serum 25(OH)D <12 ng/ml was reported among 34.8% of women.Those women with VDD and insufficiency on average had higher parity. This is also likely to be related to their lower SES status.The use of different forms of vitamin D and multivitamin supplementation was assessed among cases and controls. For each form of supplementation, the breast cancer group had a significantly lower usage than the control group .There was a significant association between serum 25(OH)D concentrations and intake of vitamin D supplements with 72% of breast cancer cases in the VDD group being non-users of vitamin D supplementation compared to 50.6% of controls. Vitamin D users had higher serum vitamin D sufficiency among both cases and controls .There was no difference in the total sun exposure score between cases and controls and therefore no association with breast cancer risk . HoweverIn this study, unique data for each woman for assessment of all sources of vitamin D, including sunlight exposure and various types of vitamin D supplementation, and their serum concentrations of 25 (OH) D was collected. The major finding was that lower serum 25(OH)D concentration was significantly associated with an increased risk of breast cancer supporting the hypothesis that vitamin D may play a protective role against breast cancer.The median concentration of serum vitamin D in our study among cases was 15.3 (SD 15.6) ng/ml and among controls 16.7 (SD 20.1) ng/ ml. This was on average somewhat lower than the median concentration of serum vitamin D (25(OH)D) of 18.8 ng/ ml reported in a population based study of Pakistani population in Karachi in 2011 . HoweverThe study finding of association of lower serum 25(OH)D concentration with breast cancer is consistent with the results of a prospective observational mediterranean study, where deficient 25(OH)D concentrations were associated with node-positive high grade breast cancer . AnotherThis study results also show the association of vitamin D supplementation with both increased serum concentrations of vitamin D and significantly decreased breast cancer risk. A French Cohort study showed that current use (not past use) of calcium and Vitamin D supplements was associated with a lower risk of developing breast cancer in postmenopausal women, but not in pre-menopausal . In a poAnother cohort study showed that vitamin D was associated with lower incidence of cardiovascular disease, respiratory disease, and fractures but not total incident cancers .According to a review by Feldman et al, in spite of inconsistent epidemiological and clinical trials results, some clinical studies agree with the beneficial effect of vitamin D in preventing cancer and that correcting VDD and usage of vitamin D supplements might have a role to reduce cancer incidence and improve cancer prognosis and outcome .2D may inhibit angiogenesis and down-regulate estrogen receptors [in vitro experiments and in vivo models of mammary tumor cells extracted from mice [Vitamin D has been reported to have anticarcinogenic properties by stimulating apoptosis, inhibiting and slowing cell growth factors and improving cell cycle regulatory factors . Furthereceptors . Activateceptors . Anothereceptors , 92. Vitrom mice , 94. Alsrom mice .In this study, there was no association of total sun exposure score (a proxy measure of 25(OH)D concentrations) with serum 25(OH)D concentrations or breast cancer risk. This is contrary to those studies, particularly conducted at higher latitudes, which have shown a strong positive association between sunlight exposure concentrations and 25(OH)D concentrations and negative association with various cancers including breast . SimilarThis study showed that there was no association of vitamin D with tumor characteristics, ER or PR status or stage of breast cancer which is consistent with similar findings in a Chinese population . It is i2D concentrations may be more relevant due to the enzymatic conversion of 25(OH)D to 1,25(OH)2D, but it was not available in our study. Despite some limitations, the strengths of this study are considerable, including a large sample size with good statistical power, a high response rate and good participation in both cases and controls, best methods of measurement of all the variables using validated questionnaires and excellent laboratory methods for ELISA assay, standardized, sample storage at -80C, blind assessment of laboratory personal testing for 25 OH(D), which ensured comparability of information in both cases and controls, were the strengths of this study. Lastly, measurement of vitamin D from all sources was assessed especially serum concentration of 25(OH)D measurement was carried out which is the gold standard for assessing vitamin D status reflecting integration of cutaneous synthesis, as well as dietary and supplemental vitamin D intake.Some limitations of the study are to be noted. First, measurement of serum 25(OH)D concentrations was done by a single venous blood sample collected at one point in time which may not be necessarily associated with 25(OH)D concentrations at the time of breast cancer initiation or progression. However, findings from an important clinical trial suggest that serum 25(OH)D concentration at a single time point may be representative of long-term vitamin D status over a five-year period . AnotherOverall this study suggests that there may be a potential role of cost- effective vitamin D in reducing breast cancer incidence in a developing and limited resources country like Pakistan, in contrast to more affluent societies. Pakistan has overburdened cancer care services in the health and development systems with an inefficient palliative care which largely remains unknown and neglected area. Cancer treatment facilities are situated in big cities and are beyond the reach of the majority of the population. Pakistan’s ratio of health services to population is one of the highest (1:90 million) .To conclude, in this study, we observed that lower serum 25(OH)D concentration was associated with a higher risk of breast cancer supporting the hypothesis that deficient concentrations of serum vitamin D may contribute to the process of carcinogenesis and its correction may play a role in protection against breast cancer. VDD may be a modifiable risk factor for breast cancer and restoring adequate concentrations of vitamin D may be a safe and affordable approach that could reduce the incidence of VDD and breast cancer. This finding is also supported by the results showing that vitamin D supplementation in Pakistani women was associated with both increased concentrations of vitamin D and reduced incidence of breast cancer. However, further studies, for example a prospective cohort study to confirm our findings in a large prospective study for temporality, or large randomized clinical trials, are needed to draw firmer conclusions and clarify this association in a dose-response relationship. Such large RCTs may confirm the optimal concentrations of serum 25(OH)D for breast cancer prevention, which may be effective and low-cost strategy for women to reduce their risk of breast cancer through preventing VDD and insufficiency.In Pakistani women raising and maintaining serum 25(OH)D concentration at the population concentration can be achieved through public awareness campaigns to improve 25(OH)D concentrations through lifestyle changes that promote sensible sun exposure, consumption of foods that contain vitamin D and are fortified with vitamin D, and use of vitamin D supplements.S1 Data(SAV)Click here for additional data file.S1 Table(DOCX)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.S3 Table(DOCX)Click here for additional data file.


Breast density was assessed as global and localized fibroglandular volume (%). A convolutional neural network characterized H&E composition. In total 37 features were extracted from the network output, describing tissue quantities and morphological structure. A random forest regression model was trained to identify correlates most predictive of fibroglandular volume (n = 588). Correlations between predicted and radiologically quantified fibroglandular volume were assessed in 264 independent patients. A second random forest classifier was trained to predict diagnosis (invasive vs. benign); performance was assessed using area under receiver-operating characteristics curves (AUC). Using extracted features, regression models predicted global (r = 0.94) and localized (r = 0.93) fibroglandular volume, with fat and non-fatty stromal content representing the strongest correlates, followed by epithelial organization rather than quantity. For predicting cancer among high and low fibroglandular volume, the classifier achieved AUCs of 0.92 and 0.84, respectively, with epithelial organizational features ranking most important. These results suggest non-fatty stroma, fat tissue quantities and epithelial region organization predict fibroglandular volume. The model holds promise for identifying histological correlates of cancer risk in patients with high and low density and warrants further evaluation.Breast density, a breast cancer risk factor, is a radiologic feature that reflects fibroglandular tissue content relative to breast area or volume. Its histology is incompletely characterized. Here we use deep learning approaches to identify histologic correlates in radiologically-guided biopsies that may underlie breast density and distinguish cancer among women with elevated and low density. We evaluated hematoxylin and eosin (H&E)-stained digitized images from image-guided breast biopsies ( A recent meta-analysis found that percent density, which reflects the proportion of total breast area comprised of dense fibroglandular tissue, is a stronger predictor of risk than absolute dense area.3 It is estimated that 43% of US women 40–74 years of age have dense breasts,4 but mechanisms accounting for the relationship between elevated density and breast cancer risk remain ill-defined.Among women, invasive breast cancer is the most commonly diagnosed female cancer in most countries worldwide.5 and breast tumors6 are more likely to occur in mammographically dense regions within the breast, suggesting the relevance of localized as well as global density measures in cancer development. The few studies that have examined histological correlates of breast density have suggested that higher breast density is associated with greater epithelial cell content and non-fatty stroma.8 While most studies to date have utilized quantitative microscopy to characterize breast tissue from women undergoing procedures for suspect lesions, one study of non-cancerous autopsy breast tissues also showed positive relationships between epithelial and non-fatty stromal tissue, particularly stromal collagen area, and percent density.9Studies highlight that pre-cancerous lesions11 The recent incorporation of progressive artificial intelligence platforms into digital pathology work systems now allows the utilization and expansion of these approaches to larger scale molecular epidemiological studies. Specifically, deep learning methods such as convolutional neural networks,12 are increasingly being employed for histological image recognition with high accuracy and reproducibility.15 We previously developed a deep learning convolutional neural network model for the assessment of tissue characteristics in hematoxylin and eosin (H&E)-stained whole slide breast tissue images,17 which classified whole slide images as epithelial, stromal and fat tissue. In this current study, we hypothesized that application of this model to whole slide images of H&E-stained fixed tissue specimens collected from diagnostic image-guided breast biopsies might enable identification of specific histologic correlates that underpin breast density, including both global and localized  measures. Secondly, as more than 25 million women in the US have dense breasts,4 and because only a small proportion of these women will develop breast cancer, we also aimed to identify tissue correlates of breast density that may be important for distinguishing malignant from benign biopsy diagnoses separately among women with high and low breast density, to help inform cancer risk stratification among women undergoing a biopsy following an abnormal mammogram.Advancements in automated digital pathology now allow increased opportunities for characterization and quantification of breast tissue organization that can complement traditional microscopic assessments. Moreover, increasingly, studies are utilizing automated digital tools for complex tissue pathology assessment of breast cancer outcomes.n = 588) and testing (n = 264) sets . Benign breast disease diagnoses were categorized according to benign non-proliferative (including non-proliferative fibrocystic change and other benign and discrete entities), proliferative without atypia  and proliferative with atypia . Further, 8.0% of all biopsies yielded in-situ lesions, and 13.8% were invasive carcinoma  and menopausal status on the predictions, and results from these investigations are detailed in Supplementary Table 4 yet only a small proportion will develop invasive breast cancer, we aimed to identify histological correlates that could inform future breast cancer risk stratification among women undergoing diagnostic biopsy with either high or low breast density. The main objective of this exploratory investigation was to examine if the histologic features that were associated with cancer status were similar and/or different among women with low vs. high fibroglandular volume. Thus, using the 37 features, a random forest classifier was trained to predict invasive cancer vs. benign breast disease among women stratified into high or low fibroglandular volume  and localized (40%) fibroglandular volume from the training population). The top-ranked features for predicting invasive cancer status separately among women with high vs. low fibroglandular volume are shown in Table As elevated breast density is common among women,p = 0.24) or localized fibroglandular volume (p = 0.24).The performance of the model for predicting invasive cancer among women with high vs. low global fibroglandular volume in the testing set is shown in Fig. 20We report that we can predict global and local mammographic fibroglandular volume by applying a deep convolutional neural network model to H&E-stained sections of image-guided breast biopsies prompted by an abnormal mammogram. Specifically, we show that greater non-fatty stromal and adipose tissue content and the spatial distribution of epithelial regions in tissues, rather than total epithelial quantities, were the strongest correlates of % fibroglandular volume. The cardinal histopathologic feature of breast cancer on low magnification is ‘invasion’, characterized by irregular epithelial growth with incursion of cells into normal structures. As anticipated, features extracted from the output of the convolutional neural network indicated that epithelial organization is the strongest correlate of invasive cancer irrespective of fibroglandular volume. Thus, we hypothesize that more complex analyses of dense tissue using convolutional neural networks or other imaging technologies may enable radiological recognition of textural patterns that reflect the epithelial disorganization characteristic of breast cancer. Recent preliminary analyses using convolutional neural networks suggest the potential of this approach.9 to understand histological correlates of breast density. Similarly, our findings support prior studies that suggest radiological density is largely non-fatty stroma, with relatively little variation in epithelial content by mammographic density.9 Further, we showed that other quantitative measures of fat tissue were also highly ranked as being important for the prediction of % fibroglandular volume. The heterogeneous nature of the top-ranked histologic features further supports the complexity of quantitative measures of breast density. A novel finding of our study was the identification of the spatial arrangement of epithelial regions as ranking among the top 10 correlates of fibroglandular volume. To define spatial arrangements, we used an area-Voronoi diagram and Delaunay triangulation, which are approaches that would be very difficult to reproduce using visual assessment. Voronoi decomposition is a method whereby an area is partitioned into smaller areas that surround regions that are closest to pre-specified points.21 In essence, our results suggest that tissues that display a high ratio of epithelial area to its corresponding areas of influence are characteristic of cancer in both high and low global fibroglandular volume contexts. The identified Voronoi area along with the area ratio of each epithelial region to its Voronoi region ranked among the top 10 correlates for both global and localized fibroglandular volume measures.Our findings agree with prior literature using quantitative microscopy10 Although prognosis was not the focus of our analyses, using a similar approach, we also found that the quantity of non-fatty breast stromal tissue was among the top-ranked predictors of fibroglandular volume, supporting the contributory role of stroma to fibroglandular volume. This study highlights the importance of examining the tissue microenvironment of dense tissue in more detail, including conducting in-depth analysis of stromal components17 including collagen.23Beck and colleagues were among the first to highlight the potential of digital image analysis for examining histological features of breast cancer. They developed and utilized C-Path , a machine learning tool, which identified features of stromal morphology that were especially important for predicting breast cancer prognosis.20 Findings from our exploratory analysis relating histologic correlates to biopsy diagnosis highlight the interindividual heterogeneity that may be apparent at the histological level despite having comparable radiological densities. Interestingly, we found that irrespective of fibroglandular volume, spatial arrangement of epithelium was the most predictive of a cancer diagnosis, showing that deciphering composition of the mammographic fibroglandular volume is important for identifying abnormalities at the histological level. Of note, the performance of the model was better in detecting cancer status among women with high fibroglandular volume  than among women with low fibroglandular volume, though this difference was not statistically significant. This could be an artifact of the model, i.e., a challenge of recognizing spatial patterns in low density. However, this finding could also support the concept of epithelial-stromal interaction in the progression of invasive cancer. Understanding the heterogeneity24 and significance of the epithelial region spatial arrangement and organization may provide important etiological clues for tumorigenesis, and additional assessment of these features is needed to examine their relationships with other epithelial histological risk markers including terminal duct lobular units.25A major clinical challenge is differentiating between the non-fatty stroma and at-risk epithelium that together constitute the ‘white’ dense areas that appear on a mammogram. Thus, despite similar measures of breast density for a radiologically dense breast, there could be considerable heterogeneity of tissue composition within the dense regions. As density alone may not be capable of defining epithelial organization, other techniques are needed. Potential solutions could be alternative imaging or further classification of density using neural networks.28 The publication of the CAMELYON16 challenge winners showed the ability of deep learning algorithms to detect lymph node metastasis with high accuracy with a comparable AUC to that obtained following pathological assessment (AUC = 0.96).15 While our limited sample size and the cross-sectional nature of the study design prevented detailed investigation of features associated with breast biopsy diagnoses, our preliminary findings also support the need for further investigations of biopsy tissue using deep learning algorithms.Since the publication by Beck and colleagues, there have been substantial advancements in digital pathology methodology, particularly with the advent of deep learning. For example, our investigation complements and expands on existing studies that have highlighted the potential of deep learning for identifying factors associated with breast cancer diagnosis.29 BMI was the highest ranked feature for predicting % fibroglandular volume for models in which it was included. While recognition of clinical and participant characteristics is important, the inclusion of such factors in analytical models may mask lesser associations identified by the random forest approach. Second, clinically relevant histological features of biopsy tissue accompanied with radiological information may be of benefit to integrate into breast cancer risk models,30 which are increasingly being used in clinical practice for determining risk of invasive breast cancer. Our findings are of particular relevance for women with elevated breast density, who have had a prior breast biopsy, and as such are at elevated risk of developing invasive breast cancer. We aim that by identifying validated histological features at the time of clinical biopsy following an abnormal mammogram, we may be able to discriminate women at highest risk. Increased efforts are ongoing to include histological information, as well as mammographic density, in risk prediction tools as evidenced by the BCSC-BBD model.31 However, these current risk models do not yet incorporate detailed histology in risk estimates. The integration of biopsy histological features to current risk models that assess radiological and risk factor information may ultimately improve risk assessment and inform clinical management strategies by providing additional risk information on the increasing number of women undergoing breast biopsies after a mammogram. Furthermore, the application of deep learning models that can utilize histological breast biopsy features to predict future risk of breast cancer among women with dense breasts will be important among the growing population of women who experience an initial benign breast biopsy diagnosis. Future expanded studies will address these questions.This study has many important clinical implications and considerations. Firstly, the ability to make predictions using feature assessment alone and without the inclusion of additional breast cancer risk factor information suggests the utility of deep learning approaches for the clinical setting. However, to investigate potential influences of patient characteristics, we conducted sensitivity analyses. As expected given its well-established strong inverse association with % fibroglandular volume,Our study has many strengths. Firstly, this analysis is one of the largest breast tissue studies to date to apply convolutional neural network models for the identification of tissue correlates of mammographic breast density. Further, from a biological mechanistic perspective, the ability to examine relationships between breast tissue features and localized fibroglandular volume measures allows the additional assessment of characteristics of the microenvironment of the suspect lesion, particularly factors that cannot be quantified by visual assessment but that may be important markers of cancer. Of note, we observed similarities in the top identified histologic correlates of both global and localized % fibroglandular volume, supporting the utility of biopsy tissues in understanding the global breast milieu. Further strengths of this study included the use of deep learning for delineating characteristics of tissue organization as well as for quantification of tissue components. Additionally, the utilization of diagnostic H&E whole slide images supports investigations of samples that are routinely collected during the clinical investigation following a biopsy, which suggests this approach may have clinical applicability and could compliment routine diagnostic assessment. This study related volumetric measures of breast density, determined from FFDM images, to 2D histological images from FFPE tissues, providing an important step toward a novel and complex approach to understanding breast cancer lesions and their relationships with breast density. Additional understanding of volumetric breast density would be gained by examining the 3D architecture of the BBD and breast cancer diagnoses. For example, future studies that incorporate volumetric density measures from 3D imaging modalities along with fresh tissues will provide a complementary extension to these findings.However, this study also has limitations. While random forest approaches are effective in deciphering which histological features contribute most to model prediction, they do not yield easily quantifiable results for strengths of association. Our investigation of deep learning approaches to identify histologic features associated with cancer among women with high versus low breast density, while promising, was hampered by sample size. In our current sample set, the number of cancer cases within the testing dataset was limited in order to maximize the reliability of model training. Thus, additional, larger prospective studies are needed to identify biomarkers for cancer risk stratification among women with high breast density who may be referred to diagnostic biopsy following an abnormal mammogram. While the BREAST-Stamp participants are a representative sample of the population of women undergoing diagnostic investigation after an abnormal breast imaging exam, the women enrolled within the study were primarily white (91.3%), which is reflective of the catchment area of the University of Vermont Cancer Center. Further, detailed information on lifestyle factors including alcohol consumption and smoking were not available for the full study population in this analysis. Thus, additional studies among more diverse populations are warranted to determine the generalizability of study findings and to determine whether tissue correlates of mammographic density vary by race and also by lifestyle breast cancer risk factors. In addition, our analysis was restricted to H&E-stained tissue sections. While using H&E sections is important as they are clinically meaningful and routinely prepared following biopsy, investigation of features associated with complementary histological stains to characterize the breast microenvironment may also be informative. An additional consideration is the applicability of this approach to other populations. This investigation included breast tissue sections from a single cross-sectional study, for which standardized protocols were followed for specimen preparation, tissue sectioning and staining, and were completed in the same laboratory at the University of Vermont Medical Center. While this rigorous methodology reduced potential variability in the tissue samples being assessed, it may limit the generalizability of the findings. The approach applied in this current study used extensive contrast and color augmentation during training. This method increases the robustness of the deep learning model against staining variations, but may not be sufficient when dealing with external datasets with significant staining variations. Therefore, additional validation studies are needed that include tissue sections prepared in multiple laboratories. Such studies would be highly informative for determining the robustness of deep learning within diverse pathological clinical settings.In conclusion, we highlight the potential of applying convolutional neural network models to digital pathology to gain insights into histological correlates that correspond to radiologic measures of breast fibroglandular volume, and to cancer risk. In doing so, in a population of women undergoing diagnostic breast biopsy, we found that epithelial organization was the strongest correlate of invasive cancer irrespective of fibroglandular volume. In addition, we found in agreement with prior studies that fat and non-fatty stromal features were important determinants of radiologic fibroglandular volume. As radiologic density alone may not be capable of defining epithelial organization, these findings suggest opportunities for future efforts using neural networks for enhanced capture of novel histologic as well as breast imaging features that may advance our understanding of breast tumorigenesis.32 Eligible participants were women aged 40–65 years referred for image-guided biopsy who did not have breast implants, had not been diagnosed with breast cancer or received cancer treatments, had not undergone breast surgery within one year and had not received chemoprevention. During the enrollment period, mammography registry data indicated that 1227 patients met these eligibility criteria. Information supplied by the radiology facility included final assessment of the mammogram, in BI-RADS categories: 3, “probably benign finding”; 4, “suspicious abnormality”; and 5, “highly suggestive of malignancy”.33 A standard health history questionnaire which assessed established breast cancer risk factors was collected at the time of the mammogram,34 and upon providing consent to be enrolled in the study, additional detailed breast cancer risk factor information was collected by the research coordinator.29 The distribution of the collected breast cancer risk factor information, including the demographic and lifestyle characteristics of the enrolled BREAST Stamp study population, has been previously described.32 Details of the analytical population included in this current analysis are outlined in more detail below and described in Table This study included women referred for diagnostic image-guided breast biopsy after an abnormal breast imaging exam between October 2007 and June 2010 at the University of Vermont Medical Center, and were enrolled as part of the National Cancer Institute’s (NCI) cross-sectional, molecular epidemiologic Breast Radiology Evaluation and Study of Tissues (BREAST)-Stamp Project. Details of the BREAST Stamp Project and study eligibility characteristics have been described previously.Breast tissues obtained from ultrasound-guided core needle (14-gauge) or stereotactic-guided vacuum-assisted (9-gauge) biopsy, were routinely processed, and representative H&E-stained breast tissue sections were obtained from the formalin-fixed paraffin-embedded target blocks for each biopsy and, when collected during biopsy, from non-target blocks representing surrounding non-target tissue. The diagnosis was confirmed following pathological report review. For women who had ≥ two unilateral biopsy targets, the two targets with the most severe diagnoses were selected. If there were ≥ two bilateral targets, then one target from each breast was selected, sampling the tissues with the most severe diagnoses. H&E-stained breast biopsy tissue sections were digitized at ×20 magnification using the Aperio (47.7%) or Hamamatsu scanning systems (52.3%).36 Briefly, quantitative global29 and localized25 fibroglandular tissue volume (cm3) measures were determined using craniocaudal mammograms of the ipsilateral breast, taken at the time-point prior but nearest to the biopsy date. Percent (%) global fibroglandular volume was estimated using Single X-ray Absorptiometry, which utilized a breast density phantom attached to the compression paddle of the mammography machine.36 For the assessment of % localized peri-lesional fibroglandular volume measurements, the biopsy location and radius were identified on the pre-biopsy mammogram by the study radiologist.25 Localized % fibroglandular volume measurements at a volume ~0–2 mm3 surrounding but excluding the biopsy target location were utilized in this analysis.Assessment of breast density was conducted at the University of California, San Francisco on pre-biopsy raw digital mammograms from full-field digital mammography systems.n = 588; 69%) and a testing dataset . Overall, the 588 women in the training set had 687 biopsies which encompassed 1587 H&E stained sections (667 from the target and 920 from the non-target blocks). For the testing group of 264 women, there were 349 biopsies (454 sections from non-target blocks). An overview of the study design is shown in Fig. Of the women eligible for this study, 882 (69%) had Single X-ray Absorptiometry fibroglandular volume results available for the ipsilateral breast within the year before their breast biopsy. Of these, 852 women had target and non-target H&E slides from 1036 breast biopsies available for assessment. For convolutional neural network model training and assessment, as outlined in more detail below, the study population was randomly subdivided into a training dataset .37 The performance of the convolutional neural network model for generating whole slide image maps of epithelial, stromal and fat tissue has been outlined previously,16 and an example of the classification is shown in Supplementary Fig. 16 Following the generation of the whole slide image maps, features were extracted from the output of the convolutional neural network. These features were grouped into three main categories, describing global tissue quantities, the morphology of the epithelial regions, and spatial arrangements of epithelial regions. To examine spatial arrangements of epithelial regions, region adjacency graphs were used including area-Voronoi diagrams and Delaunay triangulation.19 The area-Voronoi diagram was utilized in the context of spatial distribution analysis to define areas of influence of epithelial regions in the image. Given a set of segmented epithelial regions A1,…,An in a whole slide image, the area-Voronoi of a region Va(Ai) is defined as the set of pixels in the image from which the distance to Ai is less than or equal to any other regions in the image. Overall, 37 features were extracted within these three categories; a description of the 37 features and their distributions in the training and testing sets are shown in Supplementary Table Using the digitized H&E whole slide images from 588 women included in the training set, a deep convolutional neural network was trained to generate maps of tissue composition that classified whole slide images as epithelial, stromal and fat tissue.21 Python method was used for training of the random forest models. These models were then applied to the independent testing set to predict the fibroglandular volume measures. We chose random forests as this approach can account for any non-linear relationships between the features and has been shown to work well even when the number of features exceeds the number of observations.38 The output from the random forest model includes the Gini index plot as a measure of the predictive importance of the features. Supplementary Fig. r ≥ 0.85), one feature was randomly selected to be excluded from the model. We then retrained the random forest models on the remaining 25 features. We also used the 25 features to separately predict each fibroglandular volume measure. When the number of features in the prediction model was reduced to include only one from among highly correlated features, the top selected features for fibroglandular volume prediction were similar; therefore, we present results from random forest analyses including all 37 features.Patient characteristics were compared between the training and testing sets using chi-square or Fisher’s exact tests for categorical variables and Wilcoxon rank sum tests for continuous variables. Using the 37 features extracted from the output of the convolutional neural network, a random forest regression model was used to predict global fibroglandular volume (%) and a separate random forest model was used to predict localized fibroglandular volume (%) . The scikit-learn39 ROC curves of the cancer detection systems among patients with high and low global or localized % fibroglandular volume were compared using the bootstrap method in R package “pROC”, which computes, stores and compares the AUC of each ROC curve.40In an exploratory analysis, we examined the potential of the extracted histologic features for predicting cancer status (benign vs. invasive biopsy diagnosis) among women with high and low fibroglandular volume. Firstly, the patient population was stratified by fibroglandular volume (high vs. low), using the median cut point of global (34.4%) and localized (40%) fibroglandular volume from the training population. For this analysis, all in-situ diagnoses were excluded from both model training and testing. Thus the cancerous group was restricted to biopsy diagnoses of invasive carcinoma and the benign group included diagnoses of non-proliferative and proliferative benign breast disease (with and without atypia). Using the 37 features previously extracted from the convolutional neural network output, a random forest classifier was trained to predict cancer status separately among women with high and low fibroglandular volume. The classifier performance for cancer status prediction was assessed using area under the receiver-operating characteristic (ROC) curve (AUC) analysis on the probabilities generated by the random forest classifier. 95% confidence intervals (CIs) were generated using a patient-stratified percentile bootstrapping method.Supplemental MaterialSupplemental Material


Inflammation contributes to breast cancer development through its effects on cell damage. This damage is usually dealt with by key genes involved in apoptosis and autophagy pathways.We tested 206 single nucleotide polymorphisms (SNPs) in 54 genes related to inflammation, apoptosis and autophagy in a population-based breast cancer study of women of European (658 cases and 795 controls) and East Asian (262 cases and 127 controls) descent. Logistic regression was used to estimate odds ratios for breast cancer risk, and case-only analysis to compare breast cancer subtypes (defined by ER/PR/HER2 status), with adjustment for confounders. We assessed statistical interactions between the SNPs and lifestyle factors .IL-13) and breast cancer risk , which remained statistically significant after multiple testing correction (padj= 0.0350). This association was replicated in a meta-analysis of 4305 cases and 4194 controls in the Shanghai Breast Cancer Genetics Study . Further, we found evidence of an interaction between rs7874234 (TSC1) and physical activity among women of East Asian descent.Although no SNP was associated with breast cancer risk among women of European descent, we found evidence for an association among East Asians for rs1800925 ( Chronic inflammation has been linked to cancer development , and canLifestyle factors such as smoking introduce sources of inflammation to breast tissue. Several studies suggest a causal association between lifestyle factors and breast cancer susceptibility or progression. For example, in premenopausal women, obesity can affect hormone-independent breast cancer through chronic inflammation of the breast adipose tissue . In addiBreast cancers may be classified by pathologists using hormone receptor status (the estrogen receptor [ER] and progesterone receptor [PR]), or HER2 growth receptor status. Some associations of different genes to risk are limited to only certain tumour subtypes ,11, whicThe objective of this study was to replicate previously reported associations of polymorphisms in genes related to inflammation, apoptosis and autophagy with risk of breast cancer in women of European and East Asian descent. Within these three gene categories, we included additional genes previously shown to have an effect on cancer. We also tested for statistical interactions of these genes with lifestyle factors that could affect inflammation, including body mass index (BMI), physical activity and smoking status. Finally, we carried out case-only analyses to examine whether these SNPs may have breast tumour subtype specific effects.This study was approved by the joint Clinical Research Ethics Board of the University of British Columbia and BC Cancer. All participants gave written informed consent.in situ or invasive breast cancer, diagnosed from April 2005 to May 2009 [In brief, the Canadian Breast Cancer Study, a population-based case-control study, invited women with May 2009 . Women wTable 1), eight of which had previously identified tagSNPs [Table 1). Additional SNPs were selected for replication of findings from other studies; this resulted in addition of SNPs for 10 candidate genes, and 7 genes with only replication SNPs (Table 1). Genotyping was done as part of an Illumina Golden Gate Assay  at the Genome Quebec / McGill University Innovation Centre.Fifty-two genes related to apoptosis, autophagy and inflammation were studied ( tagSNPs . Thirty- tagSNPs  in Haplo tagSNPs  with HapS1 Table).Quality control was performed by the authors as described in , using ITable 2). Hormone receptor status  was determined using immunohistochemistry and fluorescence in situ hybridization, as previously described [For this analysis, only individuals of European and East Asian descent were included  and R  . Logistip<0.05 before multiple testing correction were tested for interaction with being overweight/obese at the time of diagnosis (defined as BMI≥25), smoking status (non-smokers vs. pack-years>0) and total lifetime physical activity. Total lifetime physical activity measurements were measured as previously described [SNPs that had escribed ,23 and iescribed , active Table 2. Analysis was only done for SNPs with p<0.05 before multiple testing correction. We did not have samples in each genotype category for the HER2 status case-only analysis in East Asian samples, as the minor allele frequencies were too low. Multiple-testing correction was applied to all SNPs that underwent case-only analysis. Additional analysis to compare the effect of rs7236090 in different hormone receptor status groups in East Asian women was also done using StatPlus:mac.Finally, logistic regression using only the cases was utilized to examine heterogeneity by hormone (ER/PR) receptor status and HER2 status using the categories indicated in Participants in the Shanghai Breast Cancer Genetics Study (SBCGS) are from four population-based studies: the Shanghai Breast Cancer Study (SBCS), the Shanghai Women's Health Study (SWHS), the Shanghai Breast Cancer Survival Study (SBCSS) and the Shanghai Endometrial Cancer Study . Detailed descriptions of these studies have been published elsewhere . Briefly Briefly, quality control measures resulted in data for 922 controls and 920 cases for 206 SNPs (S1 Table). Following logistic regression analysis in Europeans (658 cases and 795 controls), 3 SNPs had p<0.05 before FDR correction and none had p<0.05 after multiple testing correction (S2 Table): (i) rs6676805 (RFWD2) (OR = 0.730 (95% CI: 0.600–0.889) p = 0.00158 and after correction padj = 0.213), (ii) rs617078 (RFWD2) (OR = 0.799 (95% CI: 0.681–0.938) p = 0.00585) and (iii) rs8063461 (TSC2) (OR = 0.823 (95% CI 0.711–0.963) p = 0.00139 and after correction padj = 0.960). There was no evidence for an interaction of any of the three SNPs with excess weight, smoking status, or exercise (S2 Table). There was also no evidence for differential effects depending on the tumour subtype as determined by hormone receptor status (S2 Table).Characteristics of the cases and controls are summarized in p<0.05 before multiple testing correction (Table 3). Following FDR correction, the SNP rs1800925 (IL-13) was associated with breast cancer risk (OR = 2.08 (95% CI: 1.32–3.28) p = 0.000779; after correction padj = 0.0350).Among East Asian women (262 cases and 127 controls), 7 SNPs had TSC1) (OR = 1.81 (95% CI: 1.00–3.28) p = 0.0418; after correction padj = 1.00) interacted with physical activity (p = 0.0281). When separating cases by physical activity totals, the association between rs7874234 and breast cancer risk was only seen in women with an average lifetime weekly exercise of <89.6 MET hrs (OR = 1.24 (95% CI: 1.05–1.46) p = 0.00909), with no association for women with >89.6 MET hrs.Among East Asian women, SNP rs7874234 (BCL2) (OR = 0.713 (95% CI:0.515–0.986) p = 0.0396) was differentially associated in the hormone receptor (ER/PR) classified tumour subtypes in East Asian women , with the strongest association seen for hormone receptor positive tumours.Finally, rs7236090 (IL-13 and TSC1 SNPs for replication of main effects by conducting lookups in genome-wide association study (GWAS) data from the Shanghai Breast Cancer Genetics Study (SBCGS) [p = 0.011) (Table 4), with the same direction of association as in the Canadian data. Because exercise data was not available for the SBCGS, we were not able to test rs7874234 in TSC1 for interaction with exercise in the replication study. No main effect for association with breast cancer risk was observed for this SNP in the SBCGS (Table 4).We tested the  (SBCGS) . Rs18009IL-13) and breast cancer risk among East Asian women, which was not heterogeneous across breast cancer subtypes. IL-13 was associated with breast cancer risk in New Mexico [We report an association between rs1800925   Germany , 2325 ca Germany , and 305ulations  and in aulations . This maulations ,34), or ulations . Alterna-a [MDM2 ).CASP8 with breast cancer depended on BRCA1/BRCA2 mutation carrier status in some studies [TP53 variants are associated with breast cancer only in BRCA2 carriers [Pre-miR-27a polymorphisms were associated with familial, but not sporadic, breast cancer [BRCA1 and BRCA2 mutation status of the women in our study, and such women would likely be a minority of those in our study, we are unlikely to detect associations that only apply to mutation carriers.The association of  studies , but not studies ,39. TP53carriers , not in carriers . Pre-miRt cancer . As we dTSC1) could be attenuated by physical activity, as women with high total physical activity scores (>89.6 MET hrs/wk) no longer had significant association for breast cancer risk. Although obesity and smoking are known to contribute to inflammation, we did not find evidence for an interaction between these factors and genetic influencers of inflammation.We found evidence that, in East Asian women, breast cancer risk conferred by rs7874234  among women of European descent, but neither remained statistically significant after correction for multiple testing. We found one SNP in IL-13 associated with breast cancer among women of East Asian descent that remained statistically significant after multiple testing correction, and this was replicated in the SBCGS. Six other SNPs had evidence for an association in East Asian women before multiple testing correction; of these, one in TSC1 appears to interact with physical activity.Overall, we found evidence for associations with breast cancer risk with single SNPs in 2 genes Click here for additional data file.S2 Table(PDF)Click here for additional data file.


It is plausible that night shift work could affect breast cancer risk, possibly by melatonin suppression or circadian clock disruption, but epidemiological evidence is inconclusive.Using serial questionnaires from the Generations Study cohort, we estimated hazard ratios (HR) and 95% confidence intervals (95%CI) for breast cancer in relation to being a night shift worker within the last 10 years, adjusted for potential confounders.P = 0.035), but no significantly raised risks for hours worked per night, nights worked per week, average hours worked per week, cumulative years of employment, cumulative hours, time since cessation, type of occupation, age starting night shift work, or age starting in relation to first pregnancy.Among 102,869 women recruited in 2003–2014, median follow-up 9.5 years, 2059 developed invasive breast cancer. The HR in relation to night shift work was 1.00 (95%CI: 0.86–1.15). There was a significant trend with average hours of night work per week (The lack of overall association, and no association with all but one measure of dose, duration, and intensity in our data, does not support an increased risk of breast cancer from night shift work in women. Most,25 but not all,15 meta-analyses suggest night shift work may be associated with a modestly raised risk of breast cancer in women.27 But the association is weaker when limited to cohort studies,27 the type of night shift work and exposure definitions have varied from study to study,28 and no clear dose–response relationship has been demonstrated.27Over 30 years ago, it was proposed that suppression of the pineal hormone melatonin by exposure to electric light at night could increase risk of breast cancer.15 but this has been challenged.31 It has been suggested that recent exposure,32 initiating night work at young ages31 or before first pregnancy,34 and risk among pre-menopausal women for oestrogen receptor (ER) positive, progesterone receptor (PR) positive, or human epidermal growth factor-receptor 2 (HER2) positive tumours35 may be relevant, but the evidence is inconclusive. We therefore examined risk of breast cancer in relation to timing of night shift work and receptor status, in a large UK cohort study that has not been included in previous meta-analyses, using detailed questionnaire information at recruitment and during follow-up, with adjustment for potentially confounding factors.The most recent meta-analysis of all prospective studies, including three previously unpublished cohorts concluded that night shift work has little or no effect on breast cancer incidence,36 The first follow-up questionnaire was 2½ years after recruitment was completed by 99% of non-deceased participants, a second 6 years after recruitment by 97%, and a third 9½ years after recruitment by 96% of those recruited long enough ago to have entered this phase of follow-up.The Generations Study (GS) is a cohort study of >113,700 women aged 16 or older from the United Kingdom. Questionnaire information and informed consent was gained at recruitment since 2003.37 Confirmation of diagnosis was obtained from cancer registries in the United Kingdom, NHSCR linkage, pathology reports, and correspondence with patients’ general practitioners.Breast and other cancers occurring in the cohort were identified from recruitment and follow-up questionnaires, and spontaneous reports to the study centre. Spontaneous reports occurred when a woman contacted us and told us about her cancer diagnosis. For those lost to questionnaire follow-up, we ascertained cancers from linkage to National Health Service Central Registers (NHSCR), which provides information on vital status, cancer diagnosis and site.Information on risk factors for breast cancer was obtained from recruitment and follow-up questionnaires. Because we had collected ages or dates at which certain events or changes in lifestyle occurred, we were able to conduct analyses using time-updated alcohol use, parity, oral contraceptive use, menopausal hormone therapy (MHT) use, and menopausal status, at the ages these events or changes occurred through to the second follow-up questionnaire. We also updated post-menopausal body mass index (BMI) at the date of the second follow-up questionnaire.In relation to night shift work, women were asked in the recruitment questionnaire: “Over the last ten years, have you had any jobs that regularly involved work in the late evening or night (between 10 pm and 7 am)”, and we collected information on type of job, year starting and ending, average number of nights per week working at night or late evening, and average number of hours worked between 10 pm and 7 am for each such episode of work. The same information on night work but covering the period from recruitment to the second follow-up questionnaire, was collected at this follow-up 6 years after recruitment. When analysing type of occupation in which night shift work occurred, if a woman reported different types of night work occupation concurrently during a time period, we counted only the type of work that she had done the most, so that we could allocate her to a single occupation at any one time. If the hours per night or nights per week of night work changed during a period of night work, we took an average of these night work intensity measures weighted by the number of years at each intensity. We did not ask about night shift work in the next follow-up questionnaire, 9½ years after recruitment.To analyse breast cancer risk in relation to being a night shift worker in the last 10 years, we updated night shift work status, and cumulative duration and time since cessation in single year increments, through to the 6-year follow-up. After this point, we assumed that women who had never been a night shift worker, or had ceased, did not commence new night work, and that women who were in current night work continued at the same intensity, frequency, and duration through to the end of analytic follow-up. Because our questionnaires only solicited information on night shift work history which, at least in part, had been undertaken in the last 10 years, we did not count information from night shift histories that ended completely >10 years ago  because we deemed this would be incomplete or missing for some women. Therefore, we were able to analyse comprehensive information on night shift exposures more than ten years ago that continued into the last 10 year period, but for exposures based on work history that ended before this 10 year period our analysis would be less complete.38 The recruitment cut-off at December 2014 was selected because at the time of analysis the second follow-up was practically complete for this group of recruits and all women would have in principle been able to reach the minimum follow-up of 2½ years associated with the first follow-up questionnaire. Women entered risk at their date of recruitment and were censored at the earliest date of: invasive or in-situ breast cancer; other malignancy except non-melanoma skin cancer; death; or most recent follow-up questionnaire that was dependent on the date of recruitment. If the most recent follow-up questionnaire was not completed, the censoring date was the date the most recent follow-up questionnaire was due, if cancer and vital status were known after this date from NHSCR linkage. If cancer and vital status were not known at this due date, this was considered a loss to optimum follow-up and the censoring date was the date of the last completed questionnaire. The data for this analysis was extracted and frozen from our live database on 9-Jan-2019.The current analytic cohort is based on all women who were recruited to the study during June 2003–December 2014 without prior invasive or in-situ breast cancer or other malignancy except non-melanoma skin cancer, or prior mastectomy, and who did not report being registered as blind or partially sighted because of the possible association between blindness, melatonin, and breast cancer risk.39 using attained age as the implicit time scale, was used to estimate the hazard ratio (HR) and 95% confidence interval (95%CI) for night shift work and risk of first invasive breast cancer adjusted for potential confounding factors . We stratified by breast cancer risk factors to examine interactions between these risk factors and night shift work, and by ever-use of melatonin supplements (reported at cohort entry). Heterogeneity in HRs by sub-type of breast cancer defined by receptor status, histology, or invasive vs. in-situ breast cancer, was assessed using a data augmentation method41 and Wald test.40 All statistical tests were two-sided and analyses were conducted using Stata/IC version 14.2.42Statistical trends for frequency, intensity, and duration of night work, and time since last night work, were based on discrete time-varying annually updated values. For example, if at the time of recruitment, a woman had been in night shift work for 5 years, her cumulative exposure would be 5 years. If she continued night shift work, then in the next year of follow-up, her cumulative exposure would be updated to 6 years, and so on as long as she continued night shift work. Trends in these time-varying exposures and trend in risk with age starting night work were assessed using the likelihood ratio test.During 2003–2014, a recruitment questionnaire was completed by 102,869 women in the GS who had no previous invasive or in-situ breast cancer or other malignancy except non-melanoma skin cancer. By the censoring date, 1.1% of the women had died. Of the remainder, cancer and vital status was known for 95.3% who had completed the relevant follow-up questionnaire, and a further 3.2% from linkage to the NHSCR. The remaining 0.4% were lost to the follow-up and censored at the date of an earlier returned questionnaire. The last follow-up and censoring date was 27th March 2018.Pheterogeneity < 0.0001, except for pre-menopausal oral contraceptive use, P = 0.13). The proportion reporting ever being a night shift worker in the 10 years before recruitment was greater for women who were younger, pre-menopausal, higher BMI at age 20, did not report family history of breast cancer or personal history of benign breast disease, lived in less affluent neighbourhoods, nulliparous, ex-drinkers of alcohol, current smokers, higher levels of physical activity, higher BMI at post-menopausal ages, current users of MHT, and those not reporting ever use of melatonin supplement.Table n = 18) were self-reported mostly with treatment or other details that implied breast cancer, e.g., information on receptor status. ER status data were available for 96.6%, and of these, 84.3% were ER-positive. Invasive ductal carcinoma accounted for 78.2%, and lobular for 16.4%, of tumours. Further descriptive characteristics of the breast cancer cases are given in Supplementary Table During 880,864 person-years (median 9.5 years) of follow-up 2059 invasive breast cancers occurred, of which 2041 were confirmed through national cancer registration or medical records, and the remainder (P = 0.80) with adjustment only for attained age, and 1.00  with adjustment for additional potentially confounding factors (Table Ptrend = 0.62), nights per week on night shift (Ptrend = 0.066), cumulative years of employment as a night shift worker (Ptrend = 0.51), or cumulative hours of night shift work (Ptrend = 0.51), but there was a significant positive trend with average hours per week, adjusted for age only (Ptrend = 0.038) or fully adjusted (Ptrend = 0.035) . There were no significant associations with age started night shift work (Ptrend = 0.89), whether night shift work started before (P = 0.73) or after (P = 0.90) first pregnancy, or by time since last worked night shifts (Ptrend = 0.38). When we restricted our analyses to women at recruitment who either reported being in a paid or self-employed job , student (n = 3599), unemployed (n = 789), or retired  our results were essentially the same  the adjusted HR for night shift work in the last 10 years was 1.16 , with no significant heterogeneity between invasive and in-situ breast cancer (P = 0.39).We also stratified by menopausal status and examined risk in relation to being a night shift worker in the last 10 years and average hours per week on night shift but found no significant associations, trends, or interactions  between breast cancer risk factors and night shift work in relation to risk of breast cancer, similar to the Million Women Study.i.e. work between 7 pm and 9 am) in the 10 years before diagnosis,32 and raised risk for ≥20 h per week in a pooled case-control analysis,22 whereas in a large record linkage cohort study based on Dutch Labor Force Surveys no significant association was seen with a metric based on contractual night working hours.11 There does not appear to be a strong rationale for hours per week on night shift being a risk factor for breast cancer. We found no significant overall association of risk of breast cancer with being a night shift worker. There was also lack of association with the other measures of dose, duration, and intensity that we analysed. These results from our study and the absence in the literature of an hypothesis for why there should be an association with hours per week but not with other measures of dose, duration, or intensity, and conflicting results from other studies,32 suggesting that it is possible that this is a chance finding in our data. However, unlike traditional carcinogens where cumulative exposure and dose may supersede intensity as a requisite for cause-effect association, it is still unclear which exposure ‘domains’ may be important in relation to night shift work.28The only statistically significant association observed in our main analyses in relation to breast cancer and night shift work was a dose–response trend with average hours per week on night shift. A significant trend has previously been reported in a case-control study for hours per week of ‘graveyard’ shift work  of accrued person-years were after the 6-year follow-up, but 78% of the post 6-year follow-up person-years occurred soon after that, within the first three years after that follow-up. So the scope for potential exposure misclassification was therefore less than in cohort studies that implicitly carry forward exposure status from recruitment for everyone because the studies do not have any updated exposure information. The only other study with updated night shift exposure information using repeat questionnaires, The Nurses’ Health Study-II,31 and as analysed here recent, rather than historic, night shift work may be the most appropriate measure of exposure. However, to the extent that it is longer term or earlier exposures that matter, our analyses would be limited and weaker.Our questions on night shift work only ascertained periods of shift work that took place, or at least ended, during the 10 years before recruitment. We did not collect lifetime history of night shift work because we needed to contain the burden of data collection on the recruits to the study, who at recruitment were completing a 44-page questionnaire covering a wide range of breast cancer related topics. Some have suggested that any increased risk associated with night shift work may diminish soon after exposure ceasesAn advantage of our study is that we were able to examine a wider range of night shift exposures than most other prospective studies, which were often limited to analyses of duration of night shift. There was little scope for bias from unascertained mortality or exits, or erroneous reporting of breast cancer in our study, because follow-up for vital and breast cancer status was obtained for 99% of participants, and confirmation of reported breast cancers for over 99%. Our breast cancer cases were particularly well characterised for histological type and ER status, allowing for analyses by sub-type of breast cancer. Information on PR and HER2 status was less complete because these tests have not been conducted routinely throughout the study period. As breast cancer treatment has advanced, PR testing has become less common and HER2 testing become more common in the UK, but it seems unlikely this would cause major bias in our analyses by sub-type.3 Only this GS cohort47 and a cohort of California teachers48 have examined directly, by prospective questionnaire, exposure to indoor light at night in relation to breast cancer risk, rather than outdoor light at night from ecological geographical correlation with environmental data , and both studies fail to find significant associations with indoor light at night. However, the possible association between night shift work and breast cancer remains a public health concern. A substantial proportion of women in the general population are exposed to night shift work49 and even a modestly increased risk could lead to considerable numbers of breast cancer cases51 if there were a causal association. We did find a statistically significant trend with average hours per week on night shift. But in the absence of an association between breast cancer risk and night shift work overall, or by other measures of dose, duration, or intensity, in our study, and no evidence for association from the most recent and comprehensive meta-analysis (not including the Generations Study) of prospective studies,15 our finding of a significant trend on its own does not provide strong support for a real causal association. Our data overall do not provide evidence for an increased risk of breast cancer with night shift work.The interest in night shift work and risk of breast cancer springs from the hypothesis that exposure to light at night may increase risk of breast cancer.Supplementary Table 1Supplementary Table 2Supplementary Table 3Supplementary Table 4Supplementary Table 5Supplementary Table 6


Objective: Parental inheritance may differentially affect autosomal dominant polycystic kidney disease (ADPKD) severity via genetic imprinting or in utero epigenetic modifications; however, evidence is inconsistent. We conducted a longitudinal retrospective cohort study to assess the association between sex of the affected parent and time to hypertension diagnosis, end-stage renal disease (ESRD), and death in patients with the PKD1 genotype. Materials and methods: 814 individuals who participated in research at the University of Colorado were studied. Kaplan-Meier survival analysis was performed. The predictor was parental sex, and outcomes were diagnosis of hypertension, progression to ESRD, and death. We also examined associations in four strata according to affected parent and participant sex, as previous studies have reported earlier onset of ESRD in males compared to females. Results: The median follow-up for each outcome was as follows: hypertension, 30 (interquartile range (IQR): 18, 37); ESRD, 43 , death 39  years of age. Among affected offspring in the entire cohort, there was no difference in hypertension diagnosis (p = 0.97) or progression to ESRD (p = 0.79) according to affected parent sex; however, participants with an affected mother were more likely to die than participants with an affected father (p < 0.05). In stratified analyses, males were more likely than females to develop hypertension and reach ESRD when the affected parent was the father (p < 0.01) but not when the affected parent was the mother (p ≥ 0.11). Conclusions: Our results are largely in contrast to the hypothesis that severity of ADPKD is worse with maternal inheritance of disease.  PKD1 gene, affecting ~ 70 – 75% of cases, are known to have on average a more severe disease progression than PKD2 mutations [Autosomal dominant polycystic kidney disease (ADPKD) is the most common inherited renal disease, affecting ~ 1 : 500 to 1 : 1,000 live births . It is tutations , 4, 5, tutations . Variability in progression and severity of APDKD may be due in part to type of mutation , polymorGenetic imprinting due to the presence of epigenetic marks in certain regions of the genome may result in differential silencing of certain genes when inherited maternally compared to paternally , 14. ImpPKD1 genotype. We hypothesized that these endpoints would occur earlier, consistent with more severe ADPKD, in participants with maternal inheritance of disease. Accordingly, using a retrospective cohort design, we evaluated the role of parental inheritance of ADPKD upon severity of ADPKD. Specifically, we evaluated the time to endpoints of hypertension, ESRD, and death in participants with the PKD1 genotype, determined by linkage analysis, who were seen between 1985 and 2012 (or provided information about a family member during this period (some events occurred prior to 1985)) and had information available regarding sex of an affected parent. Inclusion was limited to those with a PKD1 genotype as individuals with PKD2 are known to have a slower disease course on average [Since 1985, the University of Colorado has maintained a registry of patients with ADPKD who participated in a longitudinal natural history study of ADPKD. We identified 897 participants with ADPKD and presence of the The study was approved by the Colorado Multiple Institutional Review Board and conforms with the Declaration of Helsinki. The nature, benefits, and risks of the study were explained to all participants, and subject or parental written informed consent was obtained prior to study enrollment. Participants consented to storage of data for future analyses at the time of consent. Children over 7 and under 18 years of age provided an assent. Predictor The predictor variable was sex of an affected parent with a known diagnosis of ADPKD. Further stratification occurred according to sex of the study participant. These data were collected by self-report or by family participation in research. Outcomes Outcomes of interest, defined a priori, were diagnosis of hypertension, progression to ESRD, and death due to any cause. All outcomes were evaluated by clinical evaluation including detailed medical history or questionnaire asking the participant or a family member whether the outcomes had occurred, and if so, in what year . Other measurements Year of birth, sex, age at diagnosis, and very-early onset (VEO) disease were determined either by clinical evaluation or from self-report. VEO status was defined as children diagnosed either in utero or within the first 18 months of life , 18. CauStatistical analyses The longitudinal association between sex of an affected parent and severity of ADPKD , was examined by survival analyses including Kaplan-Meier, the log-rank test, and the Cox proportional hazard regression models. As we were interested in understanding differences in the proposed associations according to participant sex, we also stratified the analyses according to sex of the study participant and tested for multiplicative interactions by sex. However, irrespective of p-values, we planned a priori to explore these associations in four separate strata according to affected parent and participant sex, as previous epidemiological studies have reported earlier onset of ESRD in males compared to females with ADPKD , 20, 21.To better understand the impact of deaths in utero and during infancy upon the survival analysis with death as an endpoint, we performed a post-hoc sensitivity analysis excluding individuals with in-utero/infancy deaths. Survival analyses including Kaplan-Meier, the log-rank test, and the Cox proportional hazard regression models were repeated with these 4 individuals excluded. 2-tests, or Fisher’s exact test. Unadjusted Cox proportional hazards analysis was used to determine the hazard ratio for each outcome of interest. Two-tailed values of p < 0.05 were considered statistically significant. All statistical analyses were performed with SAS version 9.4. Differences in demographics and clinical characteristics between groups were assessed using t-tests, χDemographics and clinical characteristics according to sex of the affected parent are shown in 142 (65%) participants with affected mothers and 145 (70%) participants with affected fathers were diagnosed with hypertension at a known age . However, the four sex * affected parent strata significantly differed in time to diagnosis of hypertension A p < 0.. 131 (34%) participants with affected mothers and 133 (39%) participants with affected fathers reached ESRD at a known age. Progression to ESRD did not differ according to sex of the affected parent  p = 0.7. The hazThe p-value for the participant sex * affected parent sex interaction term was not statistically significant (p = 0.28). However, the four sex * affected parent strata significantly differed in time to ESRD  p < 0.0. 124 (39%) participants with affected mothers and 107 (36%) participants with affected fathers died at a known age. Participants with an affected mother were more likely to die due to any cause than participants with an affected father C p < 0.. The HR The p-value for the participant sex * affected parent sex interaction term was not statistically significant (p = 0.40). However, the four sex * affected parent strata significantly differed in time to death C p = 0.. In this retrospective cohort study, we found no difference in time to diagnosis of hypertension or ESRD in participants with ADPKD according to sex of the affected parent. However, participants with an affected mother were more likely to die than those with an affected father. In contrast, when stratified by participant sex, males were more likely than females to develop hypertension and reach ESRD when the affected parent was the father but not when the affected parent was the mother. PKD1 families found evidence of genetic imprinting of disease progression, with age of ESRD occurring earlier in individuals with an affected mother (51 years) compared to an affected father (65 years) [Previous analyses of the influence of parental sex upon ADPKD severity have been limited and inconsistent in findings. One study of prognosis within 17 5 years) . Similar5 years) , in cont5 years) . To our knowledge, while the effect of parental hypertension status on hypertension in an offspring has previously been evaluated , the effPKD1 genotype; however, complex mutations involving additional genes may have modified the phenotype. A possible explanation of severity of disease is coinheritance of a hypomorphic allele from the nonaffected parent [However, the earlier median age of death in participants with an affected mother compared to an affected father is inconsistent with the ESRD and hypertension endpoints. One previous analysis of changes in mortality ratios across a century-long analysis of five ADPKD families found no evidence of either participant sex or parent sex influences upon mortality . Our find parent . Similard parent , 26, 27,d parent , 28 studWe decided a priori to perform stratified analyses according to participant sex in addition to parental sex due to a large number of studies indicating that median age at ESRD is younger in males compared to females , 20, 21.Our finding that hypertension and ESRD occurred earlier in males with an affected father, but not an affected mother, are in contrast to our hypothesis. However, genetic imprinting may still occur, with an effect from the father rather than the mother. The concept of genetic imprinting proposes that there is differential modification of genetic material (DNA marks) depending on whether inheritance is from the mother or the father . The limPKD1 genotype, determined by linkage analysis, detailed information on mutation type was unavailable in this cohort and represents an important future direction. These findings may differ in individuals with the PKD2 genotype, and future research should follow up on previous research in this population [There are several limitations to this analysis. As the study was retrospective, various biases are introduced including selection bias, loss to follow-up, and missing data. Many endpoints were self-reported, which may have resulted in misclassification bias, and information on all endpoints was missing for some participants. Additionally, due to the nature of self-reported follow-up in many participants, additional outcomes, such as change in estimated glomerular filtration rate, were not available for analysis. As this is an observational study design, it only shows association rather than causation, and the cohort is from a single center. While all participants included had the presence of the pulation . PotentiThe major strength of this analysis is that it included a relatively large number of participants with ADPKD with longitudinal data collected over a nearly 30-year period. While most previous analyses have examined only an ESRD endpoint, we additionally examined the age at diagnosis of hypertension as well as age of death. Additionally, most previous analyses have examined the role of participant rather than parental sex, and little literature is available on the interaction between participant and parental sex. Our results are largely in contrast to the hypothesis that severity of ADPKD is worse with maternal inheritance of disease. With the exception of mortality, which may or may not be ADPKD-related, adverse outcomes (hypertension and ESRD) occurred earlier in males than females, but only with paternal inheritance. However, maternal inheritance was associated with a greater likelihood of VEO disease as well as deaths in utero or during infancy. Overall, these findings support the concept that while genetic imprinting and/or in-utero environment may play a role in disease severity, other factors, including type of mutation  or otherThis work was supported by National Institutes of Health awards . Berenice Gitomer and Michel Chonchol have previously received research funding from Otsuka, which did not support the current study.