Exposure to environmental chemicals with hormonal effects, such as organochlorine compounds (OCs), during developmental periods of breast cells may have an impact on the incidence of breast cancer later in life. However, the assessment of exposure to these chemicals that occurred in early life at the time of breast cancer development in adult women is a difficult challenge in epidemiological studies. Plasma levels of the OCs p,p’-dichlorodiphenyl dichloroethene (DDE) and polychlorinated biphenyl congener 153 (PCB153) were measured in 695 cases and 1055 controls of a population-based case-control study conducted in France (CECILE study). Based on these values, we used a physiologically-based pharmacokinetic (PBPK) model to estimate PCB153 levels at age 11–20 years when the women were adolescents. Overall, there was no clear association between breast cancer risk and measured levels of DDE and PCB153 at the time of diagnosis, but there was a trend of decreasing odds ratios of breast cancer with increasing DDE and PCB153 levels in women aged 50 years and over. The PBPK model revealed that PCB153 concentrations estimated during adolescence were highest in the youngest women born after 1960 who reached adolescence at a time when environmental contamination was maximum, and very low in the oldest women who attained adolescence before the contamination peak. Negative associations between breast cancer and PCB153 estimates during adolescence were also found. The negative associations between DDE and PCB153 levels measured at the time of diagnosis or estimated during adolescence in our study were unexplained. Further investigations are needed to clarify whether this finding is real or related to study artifacts. However, this study suggests that using PBPK models in epidemiological studies to back-estimate OC exposures during early life stages may be useful to address critical questions on cancer development.  With approximately 1.7 million new cases each year around the world, breast cancer is the most frequent malignant disease among women . BesidesThere has been increasing interest in the effects of synthetic chemicals with hormonal properties, or endocrine disrupting chemicals, on breast cancer risk. Among them, persistent organic pollutants are mostly lipophilic environmental pollutants that tend to accumulate and biomagnify in food chains, resulting in considerable exposure of living organisms. These compounds include polychlorinated biphenyls (PCBs), which were utilized worldwide in numerous industrial and commercial applications, and organochlorine pesticides like dichlorodiphenyltrichloroethane (DDT), which has been used in agriculture and as a pest control agent . Both ofin utero or puberty, may be crucial for the occurrence of breast cancer later in life. A review of the studies on DDT and DDE was recently conducted. The Working Group classified DDT as “probably carcinogenic to humans” (Group 2A) ,12. No cAssessing exposure during early life periods of adult women is a difficult challenge in breast cancer epidemiology, because the time interval between the relevant exposure period of interest and the disease occurrence spans several decades. This is an important issue, because exposures measured close to diagnosis  may be relevant to tumor promotion , but not to earlier stages of breast cancer development . In a feIn order to assess early exposure to PCB in a population where no long-term follow-up is available, our group tentatively used a physiologically-based pharmacokinetic (PBPK) model based on PCB concentrations measured in adult women. A PBPK model incorporates data on the absorption, distribution, metabolism, and excretion of chemicals, allowing the back-extrapolation of lifetime exposure profiles . We deveIn the present paper, we investigated the association between breast cancer and plasma levels of DDE and PCB153 measured at the time of breast cancer diagnosis in a large case-control study conducted in France. We also estimated PCB153 concentration during adolescence, using a PBPK model, and tentatively explored its association with breast cancer.Côte d’Or and Ille-et-Vilaine, two administrative areas (départements) located in Eastern and Western part of France, respectively.We conducted a population-based case-control study on breast cancer in Cases were breast cancer patients below 75 years of age with invasive or in situ breast carcinoma diagnosed from April 2005 to March 2007, identified from the main cancer treatment centers in each area and from smaller public and private hospitals. The objective was to include all incident cases resident in the study areas during the study period. Among the 1556 eligible cases identified, 163 refused to participate, 151 could not be contacted and 7 died before the interview, leaving 1235 cases included in the study. Among them, 1080 (87%) accepted to have a blood draw. For 385 of these cases, the blood was drawn after a first chemotherapy treatment. To avoid potential influence of chemotherapy on OC measurements, these women were excluded from the statistical analyses, leading to 695 cases included in the present study.Population controls were selected among women residing in the study areas at the time of the case diagnosis and were frequency-matched to the cases by 10-year age group. They were recruited for the study during the same period as the cases in 2005–2007. Quotas by socio-economic status (SES) were set a priori to control for potential selection bias arising from differential participation rates across SES categories . We aimeTo recruit the controls, phone numbers of private homes were selected at random from the telephone directory of each study area. Unlisted numbers were also made available. When a woman living in the residence was reached by phone, she was invited to participate to the study as long as the predefined number of women in her age and SES stratum was not reached. Among the 1731 eligible controls identified by phone, 1317 (76%) accepted to participate to an in-person interview, and 1055 (80%) accepted to have a blood draw and were included in the present study.All subjects signed informed consent before being included in the study. The study was approved under the identification code 04-53 by the French Ethic Committee  Kremlin-Bicêtre) in January 2005. A structured questionnaire was used during in-person interviews by trained nurses to obtain information on socio-demographic characteristics, menstrual and reproductive history, height, weight by decade of adult life starting at age 20, personal medical history, family history of cancer, history of residence, lifetime occupational history and dietary habits. A blood sample (30 mL) was taken after the interview. Blood draws were aliquoted and stored at −80 °C until analysis.Levels of OCs were measured in the toxicology laboratory of the Sart-Tilman University Hospital in Liège, Belgium, in 2 mL plasma samples, using a gas chromatograph coupled to an ion trap mass spectrometer detector, as already described . BrieflyConcentration of triglycerides and cholesterol was also measured in the plasma samples. Total lipids in µg/L were calculated as triglycerides (µg/L) + 2.27 × cholesterol (µg/L) + 0.623 . All conPCB153 was the PCB congener most frequently detected and was chosen for back-extrapolation using the PBPK model. Individualized lifetime PCB153 toxicokinetic profiles were simulated using the PBPK modeling framework developed by Verner et al. ,20, carrThe model incorporated the plasma level of PCB153 measured at the time of diagnosis for the cases and at the time of the interview for the matched controls, which will be referred to hereafter as the ’reference date’. For women with undetectable PCB153 (40%), we imputed random values below the LOD. To do this, we first categorized women with detectable PCB153 by age and weight gain during the last 10 years, which were the strongest predictors of PCB153 levels in our data . Then, aThe model also incorporated information on PCB153 determinants available from the study questionnaire: date of birth, age, height and weight by decade of life, age at pregnancies, and date of start and end of each breastfeeding period. Finally, the model incorporated each subject’s daily dose of PCB153, which was estimated based on environmental and food contamination history from 1930 on, as described by Verner et al.  see App. HistoriWe extracted plasma concentrations from estimated exposure profiles from 11 years of age to age at the reference date. Earlier periods of life were not considered as exposure during infancy is largely dependent on breastfeeding by the mother, which was not known in our study. In the present paper we focused on adolescence, which we broadly defined as the period between 11 and 20 years of age. Therefore, internal levels of PCB153 were calculated from the individual lifetime toxicokinetic profiles as the area under the curve (AUC) of the lipid-adjusted blood concentration in ng/g lipid in the age period 11–20 years .Although it has been suggested that breastfeeding duration can influence PCB levels through adolescence ,24, the In the analyses based on the DDE and PCB153 measurement at reference date, plasma levels of PCB153 (μg/l) were divided in four classes. The LOD was used as a natural cut-off point to define the lower exposure category, and tertiles of the PCB153 distribution among controls with values above the LOD were used to define the three upper categories. We also conducted stratified analyses by age group, used as a proxy for menopausal status .In all analyses, odds ratios (OR) and 95% confidence intervals (CI) were estimated using unconditional logistic regression adjusting for age (5-year age groups), study area reference date, education, parity, age at first full-term pregnancy, body mass index, hormone replacement therapy, family history of breast cancer, history of benign breast disease, breastfeeding, and date of interview. We included these variables in the multivariate model as they are well established breast cancer risk factors or as we found them to be significantly associated with the risk of breast cancer in univariate analyses. Missing covariate data were modeled using missing value indicator categories. Tests for trends were performed by modeling categorical exposures as ordinal variables after assigning median values to each exposure category. Polytomous logistic regression models were used to conduct analyses by receptor status, namely, for estrogen receptor (ER+/ER−), progesterone receptor (PR+/PR−) and human epidermal growth factor receptor 2 HER2 (HER2+/HER2−) and by diagnostic status (in situ and invasive).In the analyses of PCB153 at adolescence, exposure was categorized according to the tertiles of PBPK-derives estimates of PCB153 distribution among controls. Because these estimates varied considerably by birth cohort, the analysis was made separately for women born in 1930–1940, 1941–1950, 1951–1960 and 1961–1981.https://www.R-project.org/); all tests were two-sided, and p < 0.05 was considered statistically significant.Analyses were performed using R software (version 3.3.1. R Core Team (2018). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL The distribution of cases and controls by age, study area and well-established risk factors for breast cancer is shown in Breast cancer risk increased with earlier age at menarche, low parity, low BMI in women before menopause, late age at first full-term pregnancy, current use of menopausal hormone therapy, family history of breast cancer, and history of benign breast disease. Breast cancer incidence also increased with shorter duration of breastfeeding but the association did not reach statistical significance. No association with BMI was apparent among post-menopausal women.p-trend 0.06). Plasma DDE levels were not associated with breast cancer risk, the adjusted OR being 0.93  for women in the highest exposure group compared to women with levels below the LOD . A statip-trend 0.09).Adjusted OR was 0.75  for women in the highest category of PCB153 concentration compared with those with levels below the LOD . In analn = 123) or invasive (n = 572) breast cancer (data not shown).Results were essentially unchanged after stratification by hormonal receptor status  and by in situ (Exposures to PCB153 at adolescence (11–20 years) estimated with the PBPK model varied considerably depending on the calendar year period the women reached adolescence. Back-extrapolated levels during adolescence increased sharply from the oldest birth cohort  to the youngest birth cohort  . The ageOdds ratios associated with PBPK-derived estimates of PCB153 exposure during adolescence were calculated after stratification by birth cohort . AnalysiOverall, plasma levels of DDE and PCB153 measured at the time of breast cancer diagnosis were not clearly associated with risk in our study, but a negative association between concentration of both OCs and breast cancer risk was seen in women above age 50 years. We also estimated PCB153 in the age span 11–20 years using a PBPK model and showed that contamination by PCB153 during adolescence was very low among women born in 1930–1940 and increased several order of magnitude among women born in 1961–1980. We found that PCB153 levels estimated during adolescence were also negatively associated with breast cancer risk, regardless of the birth cohort.It has long been suggested that, due to their hormonal effects, OCs could be causally associated with breast cancer risk . DDT wasin utero, adolescence and pregnancy, and early exposures may alter breast development and increase adult susceptibility to breast cancer [Mammary gland cells are more vulnerable to genotoxic damage from environmental carcinogens during periods of cell growth and differentiation, e.g. during life t cancer . In mostA notable exception is the study by Cohn et al. that reported on a prospective cohort of young pregnant women  who provided blood samples when giving birth in 1959–1967, and who were followed-up for breast cancer incidence during a median time of 17 years. High levels of serum p,p´-DDT predicted a statistically significant 5-fold increased risk of breast cancer among women who were under 14 years of age in 1945, when DDT came into widespread use . In the The CHSD cohort is unique in that it is based on archived serum samples collected from young women at a time when environmental contamination by OCs was elevated, and on extensive follow-up to study breast cancer incidence. Because to our knowledge, no other similar cohort is available to explore breast cancer risk in relation to early exposure to OCs, we used pharmacokinetic modelling as an exploratory approach to estimate PCB153 exposure at adolescence in the women of our case-control study. PCB153 was chosen as it has a long biological half-life, and as it may be seen as a marker of exposure to other OCs . We haveThe negative association with breast cancer observed for PCB153 concentrations at the time of cancer diagnosis in women aged 50 years and over was also observed for PCB153 estimated during adolescence in women born before 1961. Negative associations with breast cancer have been reported in several studies for total PCBs  or for sOur study was designed to minimize potential for selection bias of both cases and controls: we attempted to include all incident cases diagnosed during the study period among women living within well-defined geographical areas, and included age-matched population controls who were representative of the source population by socioeconomic status. Several sources of imprecision may have affected laboratory measurements of OC concentrations and estimates of PCB153 exposure at adolescence. However, exposure was assessed blindly as for the case-control status, and exposure misclassification due to laboratory measurements or inaccuracies in PBPK modeling was non-differential, so it is not likely to account for the observed associations. The limits of detection of OC in plasma samples were relatively high in our study. However, PCB153 and DDE used in the analysis were detected in the majority of women and values below the LOD were imputed as described in PBPK model estimations heavily rely on measured plasma levels at the time of diagnosis and on the daily oral dose of PCB estimated from the 1940s to the date of recruitment in the study using environmental contamination profile derived from literature data see . BecauseWe have shown that breast cancer risk was negatively associated with plasma concentrations of DDE and PCB153 measured at the time of cancer diagnosis in adult women and estimated during adolescence. This negative association was unexplained but it follows similar results in previous studies on OC exposure in hormone-dependent cancers. These findings should be carefully scrutinized to determine whether they are real, or due to study artifacts. The PBPK models were used as an exploratory approach to back-estimate PCB exposures during adolescence. This approach may be useful for assessing exposure to OC in early life periods and should be further developed to address critical questions on cancer etiology in observational studies.


Parity and age at first pregnancy are well-established risk factors for breast cancer, but the effects of other characteristics of pregnancies are uncertain and the literature is inconsistent.In a cohort of 83,451 parous women from the general population of the UK, which collected detailed information on each pregnancy and a wide range of potential confounders, we investigated the associations of length of gestation and birthweight of offspring in a woman’s pregnancies with her breast cancer risk, adjusting for a full range of non-reproductive as well as reproductive risk factors unlike in previous large studies.p trend = 0.03; hazard ratio (HR) for 26–31 compared with 40–41 weeks, the baseline group, = 2.38, 95% confidence interval (CI) 1.26–4.49), and was borderline significantly related to risk of breast cancer overall (p trend = 0.05). Risk was significantly raised in mothers of high birthweight first-born . For gestation and birthweight of most recent birth, there were no clear effects. Analyses without adjustment for confounders (other than age) gave similar results.Gestation of the first-born offspring was significantly inversely related to the risk of pre-menopausal breast cancer  contains supplementary material, which is available to authorized users. It has long been known that a woman’s risk of breast cancer relates to the number of pregnancies she has had and the age at which she first gave birth , 2. SeruWe therefore analysed the relation of offspring’s birthweight and gestation to maternal breast cancer risk in a large UK cohort in which information on birthweight and other characteristics was collected separately for each pregnancy, and in which extensive information was collected on potential confounders and virtually complete information on breast cancer characteristics.The Generations Study is a cohort study of > 113,000 women from the general population of the UK recruited since 2003 at age 16 years and older . At recrFollow-up of the cohort is primarily by questionnaires, which have been completed at approximately 3-year intervals with high completeness: by 99% of non-deceased participants at the first follow-up, 97% at the second, and 95.5% at the third. Follow-up for cancer incidence and mortality of the small proportion who did not respond to questionnaires was by ‘flagging’ at the National Health Service Central Registers (NHSCRs), virtually complete population registers of England and Wales, and of Scotland, in which deaths and cancer registrations are ‘flagged’ and are then reported to authorised medical researchers. The study was approved by the South East Multi-centre Ethics Committee.Cancers occurring in the cohort during follow-up were identified from follow-up questionnaire responses and from spontaneous reports to the investigators, as well as by flagging at the NHSCRs of participants who did not reply to questionnaires. Cancer diagnoses were confirmed by cancer registration data via the NHSCRs, pathology reports, and correspondence with physicians. To facilitate comparison with the great majority of the previous literature , 33, 34,The current analytic cohort consisted of all women who were recruited into the Generations Study from its launch (June 2003) to December 2013, without prior invasive breast cancer or mastectomy. The cut-off date of December 2013 was used because, at the time of analysis, at least second-round follow-up was complete for these recruits .We initially analysed first-birth characteristics in relation to subsequent risk of breast cancer. For this, study subjects entered analytic risk at the date they were recruited to the cohort if already parous, or at the date of first delivery at ≥ 26 weeks gestation if recruited nulliparous, and left at the earliest of first invasive breast cancer diagnosis, death, most recent follow-up questionnaire, or loss to follow-up. Women whose first delivery was of twins or multiple babies were excluded from these analyses since having borne twins has been found to be associated with a reduced risk of breast cancer  and twinWe also conducted separate analyses of follow-up before and after 15 years since delivery, since there is strong evidence that pregnancy has two opposite effects on breast cancer risk: an increase in the short-term, up to about 15 years, followed by a long-term protective effect .p values are two-sided. Analyses were conducted using Stata, version 14.2 [We estimated hazard ratios (HRs) and 95% confidence intervals (CIs) for risk of breast cancer in relation to gestation and birthweight of offspring, by left-truncated right-censored Cox proportional hazards regression  with attion 14.2 .Trends were analysed in the Cox regression model by fitting continuous values of the risk factor, and subjects with missing data for the risk factor were included in the statistical model as a separate categorical term by fitting appropriate interaction terms. Tests for trend were determined by assessing whether the slope parameter in the statistical model differed from zero using the Wald test .Tests for interaction in trends for analyses by menopausal status (to assess effect modification) were assessed by fitting additional interaction terms for menopausal status and the continuous risk factor and testing if the difference in trends differed from zero using the Wald test. For analyses by subtype of breast cancer defined by receptor status (to assess effect heterogeneity) we used a data augmentation method  to test Since pre-eclampsia has been found to be associated with reduced risks of subsequent breast cancer  and ofteThere are 107,480 participants in the Generations Study cohort recruited in 2003–2013 who did not have prior breast cancer or mastectomy at recruitment, of whom 85,069 had had any pregnancies by the time of their second follow-up questionnaire and formed the potential analytic cohort.For analyses of first births, we excluded 1214 women whose first birth was twins or a higher order, and 404 with inadequate or erroneous data, leaving 83,451 for analysis. For analyses of other births there were similar exclusions. The characteristics at recruitment of the analytic cohort are shown in Table During follow-up after first birth, 980 subjects had died, 1767 had developed invasive breast cancer, 80,043 had survived to their end date without breast cancer, and 661 were lost to follow-up (e.g. because of emigration) before their end date. We obtained pathological confirmation of diagnoses for all of the reported breast cancers except 12, which were based on self-report plus a report of appropriate treatment.p = 0.05), which was significant pre-menopausally (p = 0.03), with the greatest risk for those who had given birth at 26–32 weeks . In sensitivity analyses excluding women with diabetes and those with pre-eclampsia in the first pregnancy, results were similar (data not shown). Adjustment of the gestation analyses for birthweight did not substantially alter the results. In separate analyses for in-situ breast cancers  status of the tumour was known for 99.3% of invasive breast cancers. The raised risk in mothers of high birthweight first-borns appeared present for both ER-positive and ER-negative tumours, although it was not significant in either, whereas the raised risk for mothers of low gestation first-borns appeared evident only for ER-positive tumours, although again this was not significant .Analyses of risk in relation to most recent pregnancy rather than first pregnancy gave less marked results Table . Risk waMammary cells in animals proliferate in the first and second trimesters of pregnancy and differentiate in the third trimester , and theThe effect of gestation appeared to be greater for pre-menopausal than for post-menopausal breast cancer. No previous study has published analyses by menopausal status, but in several studies all, or almost all, cases were incident at ages under 50 years , 33, 34,In our data, the effect of short gestation pregnancies was somewhat greater, but not significantly so, in the first 15 years after delivery. A potential reason is the higher oestrogen levels in pre-term than longer pregnancies , 52, whiFewer previous studies have analysed the risk of breast cancer in relation to birthweight of the offspring than have analysed gestation. We found the risk was raised significantly after a high birthweight first-born and to a lesser extent also after the lowest birthweights. Most other studies have also found the risk raised after a high birthweight first-born –21, 23, Women giving birth to heavier offspring tend to have higher oestrogen and free oestrogen levels , 12–14 aThe association of gestation with breast cancer risk was similar for ER-positive tumours to that for breast cancer overall , but an association was not seen for ER-negative cancer. There do not appear to be any previous analyses by hormone receptor status with which to compare this. For high birthweight, the effect was greater, but not significantly so, for ER-negative tumours, in accord with the only previous, also not significant, analysis . The effWhile hormonal and histological explanations for the relation of gestation and birthweight to breast cancer risk seem the most obvious, it is also possible that maternal genetic susceptibility loci affecting offspring birthweight  or gestaOur analyses of risk in relation to gestation and birthweight of most recent birth found no clear relations. This accords with the general tendency for first birth (e.g. age at this birth) to have a much greater impact on breast cancer risk than do subsequent births. The only previous analysis to provide data comparing breast cancer risk in relation to first birth and last birth found no significant effect of birthweight or gestation at either .The previous literature on breast cancer risks in relation to gestation and birthweight of the offspring has, with two exceptions based on small numbers , 53, beeThe quality of birth certificate data on birthweight tends to be high , 58, butOur data add to evidence that a short gestation compared with a longer gestation first pregnancy results in increased breast cancer risk, and suggest that this increase occurs in pre-menopausal but not post-menopausal women. A potential mechanism is that short gestation pregnancies may result in hormonal stimulation and breast proliferation early in pregnancy, without the opportunity for differentiation occurring later in pregnancy. On birthweight, we found a raised risk for mothers of heavier first-borns, in accord with most previous studies, and potentially acting via the association of birthweight with oestrogen and IGF1 levels.Additional file 1:Table S1. In-situ breast cancer risk by birthweight and gestation of first-born singleton offspring by menopausal status. Table S2. Invasive breast cancer risk by birthweight and gestation of first-born by age at first delivery. Table S3. Relative risks of invasive breast cancer in relation to birthweight and gestation of first-born singleton offspring by menopausal status at breast cancer incidence; analyses unadjusted for confounders other than age. Table S4. Relative risks of invasive breast cancer in relation to birthweight and gestation of first-born singleton offspring by oestrogen receptor status of breast cancer; analyses unadjusted for confounders other than age. Table S5. Relative risks of invasive breast cancer in relation to birthweight and gestation of first-born singleton offspring by duration since delivery; analyses unadjusted for confounders other than age. Table S6. Relative risks of invasive breast cancer in relation to birthweight and gestation of most recent singleton birth by menopausal status at breast cancer incidence; analyses unadjusted for confounders other than age. (DOCX 53 kb)


We analysed typical mammographic density (MD) distributions of healthy Taiwanese women to augment existing knowledge, clarify cancer risks, and focus public health efforts. From January 2011 to December 2015, 88,193 digital mammograms were obtained from 69,330 healthy Taiwanese women . MD measurements included dense volume (DV) and volumetric density percentage (VPD) and were quantified by fully automated volumetric density estimation and Box-Cox normalization. Prediction of the declining MD trend was estimated using curve fitting and a rational model. Normalized DV and VPD Lowess curves demonstrated similar but non-identical distributions. In high-density grade participants, the VPD increased from 12.45% in the 35–39-year group to 13.29% in the 65–69-year group but only from 5.21% to 8.47% in low-density participants. Regarding the decreased cumulative VPD percentage, the mean MD declined from 12.79% to 19.31% in the 45–50-year group versus the 50–55-year group. The large MD decrease in the fifth decade in this present study was similar to previous observations of Western women. Obtaining an MD distribution model with age improves the understanding of breast density trends and age variations and provides a reference for future studies on associations between MD and cancer risk. It is natural and accepted that breast density decreases with increasing age because of postmenopausal glandular breast tissue alterations3. The roles of MD are also included in estimations of adjuvant hormone therapy effects after surgery such as tamoxifen4 and the aromatase inhibitors5. Regardless of associations among MD, breast cancer risk, and endocrine therapy responses, it is important to have a realistic density model to improve accuracy in these related studies.Several studies identified mammographic breast density (MD) as an independent risk factor for breast cancer7; it is interesting to evaluate different breast density distribution patterns between Asian and Western women. Prior Asian population-based studies well reported the association between dense mammograms and age10; however, assessments of longitudinal changes in breast density have used the area-based method11 to measure the two-dimensional area of dense breast tissue on digitized mammography based principally on a semi-automated procedure12. This operator-oriented analysis procedure results in unavoidable bias in dense region selection and limits the number of mammograms that can be studied.Prior studies of breast density among diverse age groups were based mainly on Western women14 and volumetric density measurements from FFDM also provide precise estimates of longitudinal changes in breast density16. It provides an objective and transparent method for density measurements and decreases disagreements among radiologists; this method can also handle large numbers of mammograms and would be useful in providing important prognostic information clinically17. In prior MD distribution studies based on Asian populations, the sample sizes of the cohorts usually ranged from 1,000 to 2,000 and the subjects’ ages ranged from 40 to 65 years. This inspired us to perform an MD distribution analysis based on a large number of FFDM examinations from an Asian population dataset  with all cohorts were from a single country (Taiwan). This can provide high-resolution MD analysis for each age range. We aimed to examine relationships and variations between age and breast density in healthy Taiwanese women by utilizing volumetric density measurements from FFDM with the goals of improving age-specific and risk-specific breast cancer screening guidelines.Recently, full-field digital mammography (FFDM) has advanced the development of automated software that measures volumetric breast density in three dimensionsAfter applying the exclusion criteria, there were 69,330 healthy Taiwanese women who underwent mammography screening who did not have an overlapping record in the breast cancer registry from 2011 to 2015. These women were enrolled and data from 88,193 FFDM examinations were analysed. There were 15,269 participants who contributed multiple FFDM examinations during the study period .Table In this dataset, the median age at the time of mammography was 53 years, the median DV was 44.65  and the median VPD was 12.3 . In the group aged 30 to 49 years, the “d” density grade represented 59.06% of the participants. The density grade “c” represented 51.76% of the participants aged 50 to 69 years. The proportion of participants with a density of “a” or “b” only represented 17.9% of all participants. Table Figure Regarding the naturally decreasing trend in MD, the Lowess curves of the mean normalized VPD and DV Fig.  show thaTable 19; this is a reasonable assumption and was used as a reference in this study.Regarding the naturally decreasing MD in healthy Taiwanese women, the DV/VPD Lowess curve in Fig. 11. By comparing the Lowess curve with the fitted model curve, the association between MD and age in the present study was also similar to that of a meta-analysis combining cross-sectional MD data from 22 countries worldwide12 and a recent Australian population-based study1. This means that the previous conclusion also benefits Taiwanese women by having a similar distribution and decreasing MD trend with increasing age. However, Table The large decrease in MD in the fifth decade of life in the present study was similar to previous observations in Western womenIn the present study, the typical MD distribution in healthy Taiwanese women was shown, as were the relationship and declining trend between MD and age. The results of this study improve the understanding of MD trends and variations with age in Taiwanese women and provide a reference for future related studies on associations between MD and cancer risk. Important limitations to the present study include a lack of information such as the BMIs and menopause statuses of the participants; therefore, the effects of menopause and BMI on MD were not estimated or modelled. This is future work that may result in more information to distinguish different MD distributions in the Taiwanese population than those observed in the present study. We hope that this study will provide sufficient information about normal MD distributions in Taiwanese women.This study was based only on raw FFDM data enrolled from an outpatient clinic and mammography screenings during the period from January 2011 to December 2015; 102,094 FFDM examinations from 77,427 women stored at the institute were subsequently analysed. The ages of the participants ranged from 16 to 95 years. All participants underwent the same procedure and all FFDM examinations were performed at the same institute. No further questionnaire or other data were added to assist in obtaining information such as the body mass index (BMI), menopausal status, or family history.The exclusion criteria were participants with breast cancer, those who underwent a mastectomy on either side, FFDM examinations that lacked the information required for the analysis ; and non-four-view mammograms. Participants were permitted to contribute multiple mammograms because this dataset also includes national mammography screening and follow-up data . Each mammogram was compared with the records of the breast cancer registry at the institute to exclude participants with a breast cancer history and to ensure that participants met the inclusion criteria . Detailed exclusion criteria and the workflow for FFDM data pre-processing are shown in Fig. This cross-sectional retrospective study was approved by the Institutional Review Board of Changhua Christian Hospital, Changhua, Taiwan (No. 160814 and No. 171217). The requirement for informed consent was waived by the ethics committee because of the study’s retrospective nature. All experiments were performed in accordance with relevant guidelines and regulations.All mammograms were obtained from the Department of Medical Imaging at Changhua Christian Hospital, Changhua, Taiwan. All standard two-dimensional digital mammograms used in this study were obtained using FFDM systems including Senographe Essential/Senographe DS  , Mammomat Inspiration  , and Selenia Dimensions  . Each FFDM examination was confirmed to be a bilateral four-view examination before analysis.TM software version 1.5.1 . Briefly, through a specific algorithm that models X-ray physics, the total breast volume (in cm3), the overall dense breast volume (DV) (in cm3) and volumetric density percentage (VPD) estimates were produced20. The VPD was obtained from the DV divided by the total breast volume and multiplied by 100. The DV and VPD in the present study were calculated by averaging the left and right sides.The automated measurement of MD and MD grading were performed using Volpara21. The VDG has already been proven to have a good correlation with radiologist-assigned BI-RADS density categories22; therefore, we did not measure the variance between the VDG and the agreement of the radiologists or combined radiologist-assigned BI-RADS score data.MD grades were reported using the Volpara Density Grade (VDG). The VDG classification is based on quantitative volumetric measurements of fibroglandular and fatty tissue to calculate the VPD  and has different thresholds from the Breast Imaging-Reporting and Data System (BI-RADS) fifth edition23 was used to identify and transform the MD measurements by finding an optimal lambda value  so that their residuals were approximately normally distributed. Locally weighted scatterplot smoothing (Lowess) curves were used to fit the normalized DV and VPD to age (bandwidth = 0.5). It was plotted on the basis of the smoothed VD/VPD and age by applying the greatest weight to the point of interest and decreasing weights for points further away based on their x-axis distance to the point of interest in the dataset24. The independent t test was used to test for differences between each age group and p-values less than 0.01 were considered statistically significant.The MD measurements were transformed to meet the assumption of a mixed-effects model in which the residuals have an approximately normal distribution. The Box-Cox transform method2 value. Rational models with a numerator of degree two and denominator of degree four (rat24) had the best fits after comparisons with several regression models such as linear and cubic/polynomial models and thus were chosen to describe the curve . The formula for the rational models is described in equation  was added to the curve-fitting analysis to obtain a more suitable curve to present the MD distribution of younger women (younger than 40 years). The curve-fitting performance is evaluated according to the model with the minimum residual and highest RAll statistical analyses and regression model analyses were performed using Minitab 18 statistical software (2018) . The curve-fitting for rational models was performed using MATLAB and the Statistics Toolbox Release 2017b .


Terminal duct lobular units (TDLUs) are the anatomic sites of breast cancer initiation, and breast tissue involution resulting in lower TDLU counts has been associated with decreased breast cancer risk. The insulin-like growth factor (IGF) pathway plays a role in breast involution, and systemic changes in this developmental pathway occur with hypertensive disorders of pregnancy (HDP), which have also been associated with lower breast cancer risk, especially in women carrying a functional variant of IGF1R SNP rs2016347. We proposed that this breast cancer protective effect might be explained by increased breast tissue involution.  We conducted a retrospective cohort study utilizing the Komen Tissue Bank, which collects breast tissue core biopsies from women without a history of breast cancer. Eighty white non-Hispanic women with a history of HDP were selected along with 120 nonexposed participants, and after genotyping for rs2016347, TDLU parameters were histologically measured blinded to participant characteristics from fixed biopsy sections. p=0.049). Trend analysis demonstrated a multiplicative decrease in counts of 31.6% per T allele (p=0.050). Although no statistically significant interaction was seen between HDP status and T alleles, interaction terms showed increasingly negative values reaching a p value of 0.124 for HDP × 2T alleles.  Stratified models by HDP status demonstrated that among HDP+ participants, those carrying two T alleles of rs2016347 had a decrease in TDLU counts of 53.2% when compared to those with no T alleles ( The observed statistically significant decrease in TDLU counts signifies increased breast epithelial involution in women with prior HDP who inherited the TT genotype of IGF1R SNP rs2016347. The increasing degree of breast involution with greater rs2016347 T allele copy number is consistent with the known progressive reduction in IGF1R expression in breast and other normal tissues. Terminal duct lobular units (TDLUs) are the main structures within the breast that produce milk and are recognized as the anatomic site of development of most breast cancers . Aging ath week of pregnancy. HDP include gestational hypertension  and preeclampsia (hypertension accompanied by proteinuria). These pregnancies are characterized by inadequate cytotrophoblastic invasion of the myometrium and impaired transformation of the spiral arteries resulting in placental ischemia [Hypertensive disorders of pregnancy (HDP) are also associated with systemic changes in the IGF pathway and affect later-life breast cancer risk. HDP impact 5–8% of pregnancies and are characterized by the development of high blood pressure usually after the 20ischemia , 10 and ischemia –15. Manyischemia –18.The breast cancer protective effect of HDP may have been underestimated in subgroups of women in prior studies that did not study inherited gene variants potentially affecting the IGF axis. Recent findings from the California Teachers Study demonstrated that among women with a history of preeclampsia, those carrying the TT genotype of a specific functional IGF1R SNP rs2016347) had a decrease in risk for estrogen receptor-positive breast cancer of 74% when compared to the GG genotype . Similar16347 hadSince the IGF pathway plays an essential role in early mammary gland growth and development as well as later-life breast tissue involution  and overThis retrospective cohort study utilized participants from the Komen Tissue Bank (KTB) at the Indiana University Simon Cancer Center. The KTB is an annotated biobank that collects breast tissue core biopsies, questionnaire data, and blood from women with no prior history of breast cancer and to date has received tissue donations from over 5,000 women. Donors provide written informed consent and are recruited under a protocol approved by the Indiana University Institutional Review Board. KTB participants were asked if they developed hypertension, gestational hypertension, or preeclampsia during a pregnancy and also if they had hypertension prior to pregnancy.Eighty white non-Hispanic women were selected with a history of HDP if they answered yes to any of the questions about pregnancy hypertension and no to having had hypertension prior to pregnancy. One-hundred and twenty nonexposed participants were then selected from white non-Hispanic parous women who answered no to all questions, and these participants were frequency matched for age. The KTB provided digitized slides of the formalin-fixed and hematoxylin and eosin- (H&E-) stained biopsy sections on all participants along with reproductive history details and relevant covariates. Core biopsy tissue acquisition from an upper outer breast quadrant was standardized, and processing details are well described in the KTB standard operating procedures .Upon entry into the study, blood was drawn from participants into an EDTA tube and after plasma separation and removal was stored at −80°C. Buffy coat DNA extraction occurred at the Indiana CTSI Specimen Storage Facility using an AutogenFlex Star instrument and Flexigene AGF3000 kit for DNA extraction. Genotyping for rs2016347 was performed at the Beckman Research Institute of City of Hope using MGB TaqMan Probe Assays from Life Technologies. The overall call rate was 97.0%, and the T allele frequency was 0.53 across the entire cohort.2, and total counts of normal TDLUs were calculated per 100 mm2 and included any TDLU with at least 2 acini associated with a discernable lumen. Ninety-one of our participants had TDLU counts independently determined for another KTB study by Mayo Clinic pathologist M. Sherman, MD; these results were made available to us after our counts were completed and the paired readings showed high correlation, r = 0.89.Histologic evaluation was performed by an experienced cytotechnologist (R. Cora) with specific training and expertise in assessing TDLU parameters and who was blinded to all participant characteristics and genotyping. H&E-stained digital images were reviewed using the Aperio ImageScope software from Leica (version 12.3.3); no samples contained either preneoplastic or malignant cells, and samples without any obvious epithelial component were considered ineligible for review. The mean tissue area scored was 35.26 mmNine of the 200 participants were not included in the final analysis due to lack of detectable epithelium on their biopsy slide (3) or inconclusive rs2016347 genotyping (6), resulting in an analytical dataset of 191.We ran negative binomial generalized linear models (GLM-NB) with a log-link to estimate adjusted count ratios (CRs) per unit of tissue area to assess whether TDLU counts varied with HDP status and whether this association was modified by IGF1R SNP rs2016347 T allele number. Models were adjusted for known confounders including age at first birth, age at time of biopsy, age at menarche, family history of a first-degree relative with breast cancer, body mass index (BMI), and parity. Different genotype parameterizations were used to test for trend and/or threshold effect on the TDLU counts. Multiplicative interaction was assessed via an interaction term in the GLM-NB between genotype and HDP at a significance threshold of 0.10.Although there was a high percentage of zero TDLU counts (10%) despite presence of some epithelium, goodness-of-fit tests did not demonstrate improved fit for a zero-inflated or hurdle model when compared to the GLM-NB via the nested likelihood ratio test and the Vuong test for non-nested models, respectively. Additional nested goodness-of-fit testing compared the GLM-NB to the Poisson-GLM. This test returned evidence of improved model fit in the NB setting, suggesting overdispersion of TDLU counts. The model comparisons are summarized in supplementary https://github.com/sdufault15/tdlu-analysis.All analyses were run using R version 3.5.0 “Joy in Playing” . Estimathttps://bcrisktool.cancer.gov.Gail 5-year risk scores were calculated using the Breast Cancer Risk Assessment Tool located on the NIH website: All participants were parous white non-Hispanic women by study design, and mean age at biopsy was 45.9 years. Characteristics of the major covariates are presented in p < 0.001), with a mean BMI of 32.4 compared to 28.4 for HDP− participants. Obesity has been a frequently reported risk factor for HDP, and 55.2% of HDP+ participants in this study were obese (as defined by BMI >30) compared to 33.1% in the HDP− group [HDP+ participants differed from HDP− participants only in having higher BMI . Both parity and family history of breast cancer were associated with increased TDLU counts, while there was little evidence of an association for age at menarche or age at first birth. In addition, Gail 5-year risk scores demonstrated no significant correlation with TDLU counts, r = −0.144.Relationships of major breast cancer risk factors with TDLU counts (adjusted for other covariates) are presented in p=0.457) and 0.477 (p=0.124) times lower in the HDP+ stratum than in the HDP− stratum.When adjusted for multiple covariates associated with breast cancer risk, there were no statistically significant interactions between the effects of HDP status and the number of rs2016347 T alleles on TDLU count , althougp=0.546) when compared to the HDP− group. For HDP− women, the CRs comparing rs2016347 genotypes of 1 and 2 T alleles to the reference genotype of 0 T alleles show no evidence of association as both CRs hover around the null  with relatively large p values .For women carrying no T alleles of rs2016347, the HDP+ exposure group has a TDLU count that is not significantly increased  decrease in TDLU counts of 53.2% when compared to those with 0 T alleles (GG genotype). Trend analysis in the HDP+ group also demonstrated a significant (p=0.050) linear trend with a multiplicative decrease in TDLU counts of 31.6% per T allele.Covariate adjusted models stratified by HDP status are shown in In the current study, we were able to demonstrate a statistically significant decrease in TDLU counts, signifying increased breast epithelial involution, in women who have experienced HDP and inherited the TT genotype of IGF1R SNP rs2016347, while there was no evidence of an association for women who experienced either the TT genotype or HDP. This association with increased breast involution is very consistent with our prior findings in the California Teachers Study (CTS) where breast cancer incidence was similarly reduced in women with preeclampsia if they also inherited the TT genotype of rs2016347 but not when preeclampsia alone was considered . In bothp=0.124) lower than the CR comparing HDP+ to HDP− exposure groups carrying 0 T alleles of rs2016347, suggesting that the association of HDP with TDLU count is modified by rs2016347 genotype. Failing to achieve significant statistical interaction likely reflected our small number of HDP+ × 2T allele samples  and the extent of variance among sample TDLU counts. Nonetheless, the consistent pattern of association observed between this KTB analysis of normal breast TDLUs and our prior CTS analysis of breast cancer incidence rates strongly suggests that a history of HDP in concert with inheritance of a functionally blunted IGF1R rs2016347 variant manifests as both enhanced mammary gland involution and reduced later-life breast cancer risk, both outcomes impacted by decades of significantly reduced mammary gland IGF axis stimulation.In our formal test for an HDP-genotype interaction, we observed that the CR comparing HDP+ to HDP− exposure groups carrying 2 T alleles of rs2016347 was 52.3% , our findings are similar to what has previously been reported in other KTB cohorts [Many well-established breast cancer risk factors can also independently impact TDLU counts, as shown in  cohorts , 39. As  cohorts .The use of specimens from the KTB provided a number of significant strengths to this study. First and foremost, it enabled assessment of entirely normal breast tissue donated by women without any history of breast cancer or other known breast disorders. Other “normal” breast studies commonly use resected tissue adjacent to breast tumors, biopsies taken for mammographically suspected breast lesions, or reduction mammoplasty samples. Furthermore, asking our participants if they had hypertension prior to pregnancy resulted in the exclusion of women with chronic hypertension, a cause of misclassification in many other HDP studies. In addition, the KTB has extensive data on reproductive history and other breast cancer risk factors, allowing us to account for many potentially confounding variables. Due to the relatively low number of women enrolled in the KTB at the time this study was initiated, we were limited in our ability to observe statistical significance for a moderate effect size, likely explaining the lack of statistical significance when formally testing for interaction between HDP history and rs2016347 genotype. We recognize that participants in the KTB are not completely representative of the general public, potentially limiting the generalizability of our findings. As such, it might be expected that women who volunteer for the KTB are more likely to have a positive family history of breast cancer, and this was noted for 26.7% of our study population, although women with BRCA1/2 positivity were excluded from our study cohort. Inclusion of only white non-Hispanic parous women was dictated by the low number of women of color enrolled by the KTB in its earlier stages.Normal breast biopsy samples along with peripheral blood rs2016347 genotyping of 191 healthy parous female donors confirmed our mechanistic hypothesis that the pronounced breast cancer protective interaction between pregnancy hypertension (HDP) and inheritance of a functionally blunted IGF1R SNP (rs2016347) TT genotype likely results from enhanced breast glandular involution, as determined by fewer terminal duct lobular units (TDLUs).


Some studies have argued that obstructive sleep apnoea (OSA) increases the risk of breast cancer. However, the results are often conflicting. This study aimed to investigate associations between OSA and breast cancer incidence using the Korea National Health Insurance Service (KNHIS) database. This retrospective cohort study analyzed data from the KNHIS database. A total of 45,699 women (≥20 years of age) newly diagnosed with OSA between 2007 and 2014 were included. The control groups were a 5-fold, age-matched women who had not been diagnosed with OSA. Mean follow-up duration was 3.7 ± 2.3 years. The primary endpoint was newly diagnosed breast cancer. The breast cancer hazard ratio  was calculated for patients with OSA and compared with that of the control group. The incidence of breast cancer among patients with OSA was significantly higher than that among the controls (1.20 [1.04–1.39]). In particular, the incidence of breast cancer was higher among patients aged ≥65 years (1.72 [1.10–2.71]). The result suggests that OSA may be a risk factor for breast cancer in women. OSA is a common disorder characterised by repeated respiratory disturbances due to total or partial obstruction of the upper airway during sleep2. The prevalence of OSA in Korea is 4.5% in men and 3.2% in women, similar to that in western countries4. OSA is associated with various harmful mechanisms 5. Eventually, OSA causes many symptoms  and serious consequences 6. Furthermore, recent clinical investigations propose that OSA is associated with diverse cancers8. According to a study by Nieto et al., OSA was associated with total and cancer mortality even after adjusting for age, sex, body mass index, and smoking. Moreover, as the apnea-hypopnea index increased, the association increased. In severe cases, cancer mortality increased 4.8 times compared to the normal group7.According to the American Academy of Sleep Medicine (AASM) guidelines, obstructive sleep apnoea (OSA) is considered a chronic disease, and long-term multidisciplinary management is recommended9. Further, breast cancer is internationally accepted as the fifth most common cause among the total cancer deaths10. Similarly, breast cancer is the second most common cancer diagnosed in women, and the incidence of breast cancer has elevated steadily for decades in Korea11. It is known that hypoxia is strongly involved in oncogenesis, tumour angiogenesis, and metastasis12. Recent basic researches suggest that intermittent hypoxia, but not chronic hypoxia, may be related to the promotion of breast cancer survival and metastatic growth14.Breast cancer is the most common cancer in women and the second most commonly diagnosed malignancy worldwide18. However, other studies suggest that incidence of breast malignancy in OSA patients is not significantly higher than that in control individuals20. Therefore, the purpose of this clinical investigation is to evaluate associations between OSA and the incidence of breast cancer based on the Korea National Health Insurance Service (KNHIS) database.In addition, clinical researches have reported that OSA may be a risk factor for the occurrence of breast cancer in women21. Both outpatient and inpatient claims are reviewed by the KNHIS and include data on diagnoses, procedures, prescription records, demographic information, and direct medical costs. The KNHIS identifies its members by their Korean Resident Registration Number, which removes the potential risk of duplication or omission when accessing the data. The KNHIS database manages claims using the Korean Classification of Disease, sixth edition, a modified version of the International Classification of Diseases, 10th edition (ICD-10), adapted for the Korean healthcare system. Any researcher can use the KNHIS data if the study protocols are approved by the official review committee. The KNHIS data from 2002 to 2017 is available now.The KNHIS covers the entire Korean populationWe defined the OSA group as that including women aged ≥20 years with newly diagnosed OSA (G47.30) between 2007 and 2014. We selected a 5-fold, age-matched control group that had not been diagnosed with OSA. People diagnosed with any types of cancer within five years prior to enrollment were excluded. Therefore, data were available since 2007. In addition, to ensure follow-up of at least 3 years from study participation, only data before 2014 were used. Breast cancer that occurred within one year of enrollment was excluded from the analysis because breast cancer that occurred before or immediately after OSA diagnosis cannot be related to OSA. The primary endpoint of this study was the incidence of newly diagnosed breast cancer. A flowchart showing the enrolment process for this study has been presented.  and income level (four quintiles). Data on comorbidities including diabetes, hypertension, dyslipidaemia, stroke, chronic obstructive pulmonary disease, and ischemic heart disease were also collected. These comorbidities are defined in the Table Data are presented as the mean ± standard deviation (SD) for age and as proportions for the remaining categorical variables. Comparisons between two groups were made using the Student’s t test for continuous variables or Chi-squared test for categorical variables. A Kaplan-Meier plot without covariance correction is presented to analyse the risk of breast cancer according to the presence or absence of OSA. The incidence of breast cancer was calculated by dividing the number of events by the product of number of persons at risk and time. To determine the hazard ratio of OSA on the relative incidence of breast cancer, the Cox proportional hazards model was used after stratifying for covariates including income level and diabetes, hypertension, and dyslipidaemia statuses. Two different models were applied. Model 1 was not adjusted by any covariate. Model 2 was adjusted for income level and diabetes, hypertension, and dyslipidaemia statuses. In addition, differences in the hazard ratio were also analysed according to age groups. The results are presented as the mean, and 95% confidence interval (95% CI). All statistical analyses were performed using SAS version 9.4  and R version 3.2.3 .The study was exempted from the requirement for informed consent by the Institutional Review Board of Soonchunhyang University Hospital because of the use of publicly available data (SCHBC 2019-08-018). All experimental protocols were approved by the same Institutional Review Board. And all methods were carried out in accordance with relevant guidelines and regulations.A total of 49,570,064 subjects enrolled in the KNHIS in 2007. The research data for the first year are available, and the numbers are comparable with that of each subsequent year up to 2014. Between 2007 and 2014, there were 45,699 female patients who were newly diagnosed with OSA. A total of 228,502 subjects were selected as controls , and it was nearly similar after adjusting for various comorbidities in Model 2. The age-related risk was highest at 1.72 (95% CI 1.10–2.71) in the age group of ≥65 years, and lowest at 1.05  compared with the control group after adjusting for potential confounders16. Sillah et al. argued that the overall malignancy incidence of patients with OSA was approximately 26% higher than that of the general population17. More specifically, a significantly increased incidence of breast cancer was shown among patients with OSA, especially the older population17. Brenner et al. confirmed that severe OSA patients aged <45 years have a significantly higher overall cancer incidence compared with the general population 18. All these results of earlier investigations are in close agreement with those of the present study that revealed an association between OSA and breast cancer.Some clinical researches have reported that OSA elevates the risk of cancer, including that of the breast20. Gozal et al. reported that the incidence of breast malignancy  was lower in patients with OSA when compared with control group19. Campos-Rodriguez et al. concluded that there are no associations between OSA and the aggressiveness of breast cancer20.A few studies, however, showed that OSA is not associated with an increase of breast cancer incidenceet al. evaluated the effects of intermittent hypoxia on the proliferation and migration of human breast cancer cells13. Their study suggests that a significant increase in the migration of cancer cells was caused by intermittent hypoxia. Chen et al. documented that intermittent hypoxia leads to some crucial changes  that promote cancer cell survival, colonisation, and metastatic growth14. Sleep fragmentation also plays an important role in the pathogenesis of OSA. Hakim et al. verified the hypothesis that sleep fragmentation facilitates tumour development and invasiveness using tumour cells and model22. Their findings suggested that sleep fragmentation can promote tumour growth and advancement via the recruitment of tumour-associated macrophages and pro-inflammatory TLR4 signalling pathway.It is still unclear how OSA affects the incidence of breast cancer. However, there is a hypothesis that explains the link between OSA and cancer development. As already known, intermittent hypoxia is a very critical mechanism related with the OSA symptoms and complications. Liu 24.In this study, we observed a tendency to increase the risk of breast cancer as the age of OSA patients increased. The exact cause is unknown, but it is presumed that older groups are affected by intermittent hypoxia and sleep disruption for longer periods of time. Additionally, the prevalence and severity of OSA in postmenopausal women were significantly higher than those in premenopausal women, which may also be the reasonThe goal of this study was to appraise the association between OSA and the incidence of breast cancer using a large nationwide (KNHIS) database. However, there are several limitations to this study. (1) The KNHIS data do not include any information about the validity of the diagnosis and OSA severity. The OSA group was defined based only on the diagnostic code of the claim data. Given that the prevalence of OSA is quite high, the control group will also contain a large number of patients with OSA. (2) There were not enough data available on confounders involved in both OSA and breast cancer, including body mass index, lifestyle, family history, exercise, cigarette smoking, alcohol drinking. Without data on these confounders, it is impossible to clearly establish a causal relationship. (3) The results of this study may not be representative of all races because only Korean data were used. (4) The calculation of person-years at risk did not consider death. OSA increases mortality substantially. Therefore, the person-years may have been over-estimated for participants who did not develop breast cancer but died prior to end of follow up.OSA may be a risk factor for breast cancer in women.


BRCA1, BRCA2, PALB2, ATM, and CHEK2 are associated with breast cancer risk. FANCM, which encodes for a DNA translocase, has been proposed as a breast cancer predisposition gene, with greater effects for the ER-negative and triple-negative breast cancer (TNBC) subtypes. We tested the three recurrent protein-truncating variants FANCM:p.Arg658*, p.Gln1701*, and p.Arg1931* for association with breast cancer risk in 67,112 cases, 53,766 controls, and 26,662 carriers of pathogenic variants of BRCA1 or BRCA2. These three variants were also studied functionally by measuring survival and chromosome fragility in FANCM−/− patient-derived immortalized fibroblasts treated with diepoxybutane or olaparib. We observed that FANCM:p.Arg658* was associated with increased risk of ER-negative disease and TNBC . In a country-restricted analysis, we confirmed the associations detected for FANCM:p.Arg658* and found that also FANCM:p.Arg1931* was associated with ER-negative breast cancer risk . The functional results indicated that all three variants were deleterious affecting cell survival and chromosome stability with FANCM:p.Arg658* causing more severe phenotypes. In conclusion, we confirmed that the two rare FANCM deleterious variants p.Arg658* and p.Arg1931* are risk factors for ER-negative and TNBC subtypes. Overall our data suggest that the effect of truncating variants on breast cancer risk may depend on their position in the gene. Cell sensitivity to olaparib exposure, identifies a possible therapeutic option to treat FANCM-associated tumors.Breast cancer is a common disease partially caused by genetic risk factors. Germline pathogenic variants in DNA repair genes  BRCA1 and BRCA2, which are key factors in the DNA double-strand break repair through homologous recombination (HR) and in the inter-strand crosslink (ICL) repair as a part of the Fanconi Anemia (FA) pathway.2 Recently, based on a prospective cohort of families carrying BRCA1 or BRCA2 pathogenic variants, the average cumulative risk by age 80 was estimated to be 72% and 69% for carriers of BRCA1 and BRCA2 pathogenic variants, respectively.3PALB2 has been previously considered a moderate-risk gene, but the latest estimate of about 44% lifetime risk associated with pathogenic variants may raise this gene to the high-risk group.4 Pathogenic variants in moderate-penetrance genes ATM and CHEK2 are also associated with breast cancer, conferring a 20% average lifetime risk.6 Recently, BARD1, RAD51D, BRIP1, and RAD51C have been proposed as risk factors for triple-negative breast cancer (TNBC) with BARD1 and RAD51D conferring high risk, and BRIP1 and RAD51C associated with moderate risk.7 Thus, the risk associated with pathogenic variants in each gene may vary by breast tumor subtype.The genetic architecture of inherited breast cancer is complex and involves germline pathogenic variants in high and moderate-risk genes and polygenetic factors. The major high-penetrance breast cancer risk genes include BRCA/FA pathway genes when altered by biallelic mutations cause FA disease. The FANCM gene  encodes for a translocase, which is a member of the BRCA/FA molecular pathway but has been recently disqualified as a disease-causing factor for FA.9 Some protein-truncating variants in the FANCM gene were described as moderate breast cancer risk factors with a greater risk of TNBC. In the Finnish population, FANCM:c.5101 C > T  is relatively frequent and was reported to be associated with breast cancer with odds ratio (OR) of 1.86 with 95% confidence intervals (CIs) = 1.26–2.75. A larger effect was observed in familial cases , for estrogen receptor-negative (ER-negative) breast cancer  and for TNBC .10 We showed an increased risk  of the FANCM:c.5791 C > T (rs144567652) truncating variant using familial cases and controls. In vitro analysis showed that this variant causes the skipping of the FANCM exon 22 and the creation of a downstream stop codon (p.Gly1906Alafs12*).11 However, in the present study we refer to the FANCM:c.5791 C > T base change as to FANCM:p.Arg1931*, which is the conventional amino acid annotation (consistent with the stop codon creation according to genetic code). The FANCM:p.Arg1931* was also found to be associated with TNBC risk in the Finnish population .12 A burden analysis of truncating variants discovered by a re-sequencing analysis of the entire FANCM coding region in German cases and controls confirmed that FANCM pathogenic variants had a particularly high risk for TNBC .13Many of the FANCM on breast cancer risk further, we tested three recurrent truncating variants FANCM:p.Arg658*, p.Gln1701*, and p.Arg1931*, within the OncoArray Consortium, a collaboration of consortia established to discover germline genetic variants predisposing to different human cancers .14 These three variants were tested for association with breast cancer risk in 67,112 breast cancer cases, 53,766 controls, and 26,662 carriers of pathogenic variants in BRCA1 or BRCA2. We also studied the functional effect of these three variants after their lentiviral transduction into a FANCM−/− patient-derived cell line in which we measured survival and chromosome fragility after exposure to diepoxybutane (DEB) or the poly (ADP-ribose) polymerase inhibitor (PARPi) olaparib.To study the effect of FANCM truncating variants, p.Arg658*, p.Gln1701*, and p.Arg1931*, with breast cancer risk for each variant separately and using a burden analysis. We tested 67,112 invasive breast cancer cases and 53,766 controls collected by the Breast Cancer Association Consortium  and 26,662 carriers of BRCA1 or BRCA2 pathogenic variants collected by the Consortium of Investigators of Modifiers of BRCA1/2 , of whom 13,497 were affected with breast cancer and 13,165 were unaffected.We analyzed the association of three FANCM variants in a primary overall analysis and in a restricted analysis including only countries in which the variant carrier frequencies were higher than the median of the frequencies. In these analyses we tested association with the variants in all available invasive breast cancer cases or in the ER-positive, ER-negative and TNBC subgroups  than in controls (0.035%) with a greater than two-fold increased breast cancer risk . When only TNBC cases were considered, the association was stronger . No association with ER-negative breast cancer or TNBC was seen for p.Gln1701* or p.Arg1931* or for all mutations combined . The restricted set also provided evidence for an association between p.Arg1931* and ER-negative subgroup , though not for TNBC. No significant association was observed for p.Gln1701* with either subgroups  in comparison to the unaffected (0.013%), and in the BRCA2 affected individuals (0.071%) in comparison to the unaffected (0.019%). Consistently, hazard ratios (HRs) above two were estimated for BRCA1  and for BRCA2  pathogenic variant carriers. The frequencies of p.Gln1701* and p.Arg1931* were not increased in affected versus unaffected individuals carrying BRCA1 or BRCA2 pathogenic variants  FANCM cDNA and cDNAs harboring FANCM:p.Gln1701* and p.Arg1931* variants produced, as expected, different C-terminal truncated forms of FANCM. In the EGF280 cells transduced with FANCM:p.Arg658* no visible band was observed on western blot .15 We conducted large case-control studies in 67,112 unselected breast cancer cases, 53,766 controls, and 26,662 carriers of BRCA1 or BRCA2 pathogenic variants. Furthermore, we performed functional analyses based on a patient-derived FANCM−/− cell line transduced with vectors carrying the three FANCM variants and tested for sensitivity to DEB or olaparib. Our genetic data suggest that FANCM:p.Arg658* is a risk factor for ER-negative and TNBC subtypes with statistically significant ORs of 2.44 and 3.79, respectively. These associations were confirmed when we restricted the analyses to countries with higher carrier frequencies. In these restricted analyses we also found that the p.Arg1931* was associated with breast cancer risk in the ER-negative subtype with statistically significant OR = 1.96. , the FANCM protein brings to sites of ICL DNA lesions the FA and the Bloom’s complexes initiating HR repair17  than did p.Gln1701* and p.Arg1931*. This also suggests that in human living cells the FANCM:p.Arg658* variant might impair DNA repair more severely than p.Gln1701* and p.Arg1931*. We have shown that in vitro both the p.Gln1701*- and the p.Arg1931*-derived FANCM proteins are expressed and that the p.Arg658*-mRNA is transcribed ; in addition, one developed several cancers, and the other demonstrated chromosomal fragility.9Previously published genetic and clinical data support our hypothesis of a position effect. https://gnomad.broadinstitute.org/).15 Case-control studies based on the Finnish population showed a strong statistical evidence of association of p.Gln1701* with ER-negative disease, with OR of 2.37 , and with TNBC with ORs of 3.56 ,10 while p.Arg1931* was found associated with TNBC with an OR of 5.14 .12 However, as our 95% CI of risk estimates for TNBC included odds ratios of 2 for both the latter mutations, the published and our results are not mutually exclusive. Risk estimates associated with rare variants may depend on their frequency and the genetic background of the population studied. Hence, pooling the data from multiple outbred and admixed populations as it was done in the present study, may yield different risk estimates than those derived from geographically, ethnically and genetically matched controls, as in the Finnish studies. Indeed, it would have been interesting to test the FANCM variant position effect in the Finnish population, but unfortunately the p.Arg658* is very rare if not absent in this population (https://gnomad.broadinstitute.org/).15Due to the rarity of the studied mutations in most populations, estimation of the risks is challenging. Preferably, the cases should be examined in comparison to geographically, ethnically and genetically matched controls. In the Finnish population, p.Gln1701* and p.Arg1931* are reported with carrier frequency of 1.62% and of 0.92%, respectively ; few were family-clinic-based studies  were collected and included in the CIMBA database.The CIMBA studies contributed 15,679 carriers of a pathogenic FANCM:p.Arg658*, p.Gln1701*, and p.Arg1931* truncating variants was conducted using a custom-designed Illumina genotyping array  at six independent laboratories. To ensure consistency of the genotype data, all laboratories used the same genotype-clustering file and genotyped the same set of reference-samples selected from the HapMap project. Samples with a call rate <95% and those with heterozygosity <5% or >40% were excluded. Further details of the genotype-calling and quality control have been described previously.14 The cluster plots of the three FANCM truncating variants were curated manually to confirm the automatic calls  comparing the model containing the variant carrier status as a covariate to a model without the variant carrier status. The primary analyses were performed including all invasive breast cancer cases and controls and subgrouping cases based on tumor hormonal status. We then performed a country-restricted analysis including the 50% of the countries with the higher variant carrier frequencies. Specifically, we included only countries in which the carrier frequencies in cases and controls combined were higher than the median of the carrier frequencies observed in all countries. Median frequencies were 0.007, 0.114 and 0.163 for p.Arg658*, p.Gln1701* and p.Arg1931* carriers, respectively.The BCAC data were analyzed to test the association between FANCM truncating variant and breast cancer risk in carriers of BRCA1 or BRCA2 pathogenic variant. A survival analyses framework was applied. Briefly, each variant carrier was followed from the age of 18 years until the first breast cancer diagnosis, or censored as unaffected at ovarian cancer diagnosis, bilateral prophylactic mastectomy, or age at last follow-up. The analyses were performed by modelling the retrospective likelihood of the observed genotypes conditional on the disease phenotype as detailed previously.20 All analyses were stratified for country. The per-allele hazard ratio (HR), 95% CIs were estimated separately for each variant. A score test was used to derive P-values for the associations. The analyses of the BCAC data were performed using STATA version 15 . The analyses of the CIMBA data were carried out using custom-written code in Python and Fortran. All statistical tests were two-sided and P-values <0.05 were considered statistically significant.The CIMBA data were analyzed to evaluate the association between each FANCM−/− cell line EGF2808 was transduced with pLenti CMV rtTA3 Blast, a gift from E. Campeau (Addgene plasmid #26429). The doxycycline-inducible lentiviral vector pLVX-TRE3G-FANCM, a gift from N. Ameziane  was mutated by site-directed mutagenesis using the QuickChange II XL Site-Directed Mutagenesis Kit (Agilent Technologies) and the following PAGE purified mutagenic primers. FANCM c.1972C > T primer 1: 5’-GCCTTCTCGGAACTTGCAGTGAAAGTCATCTATCTTTTCC-3’ and primer 2: 5’-GGAAAAGATAGATGACTTTCACTGCAAGTTCCGAGAAGGC-3’ for the p.Arg658*; FANCM c.5101 C > T primer 1: 5’-TTAAACAATGGTCCTATTGTTTGTTCTTCTTAACAGTGCTTGGGT-3’ and primer 2: 5’-ACCCAAGCACTGTTAAGAAGAACAAACAATAGGACCATTGTTTAA-3’ for the p.Gln1701*. Generation of the lentiviral vector containing the FANCM:c.5791 C > T (p.Arg1931*) and transduction of the EGF280 cells were already described.11 Expression of exogenous FANCM protein was achieved supplementing cell culture medium with doxycycline . All the cell lines used in this study were routinely checked for mycoplasma contamination using the MycoAlert™ Mycoplasma Detection Kit (Lonza).The immortalized patient-derived 8 The following primary antibodies were used: mouse monoclonal anti-FANCM antibody, clone CV5.1 diluted 1:100 , mouse monoclonal anti-Vinculin diluted 1:3000 . Western blotting detection was achieved with LuminataTM Classico (Millipore) (Vinculin) and LuminataForteTM (Millipore) (FANCM). We used RT PCR to test the expression of the mutant FANCM:p.Arg658*. Total RNA was extracted (RNeasy Mini Kit Qiagen) from the wtFANCM and FANCM:p.Arg658* transduced EGF280 cell lines. Reverse transcription was performed using High-Capacity RNA-to-cDNA Kit (Thermofisher); a cDNA region corresponding to the FANCM sequence containing the amino acid (AA) position Arg658 was amplified by PCR using the forward: 5’-AGTAACAGGCAGGTCCTTCA-3´and reverse: 5’-TGATCTTGCCACAGTCTCCA-3’ primers. The 386 bp PCR products were then digested with TseI restriction enzyme (New England Biolabs) for two hours at 65 °C and analyzed by standard agarose gel electrophoresis.Cell lysis and western blot assays were performed as previously described.FANCM variants on cell survival was measured with a Sulforhodamine B (SRB) assay.21 One-thousand cells were seeded in 96-well plates and treated constantly with DEB or PARPi olaparib at the indicated concentrations until untreated cells reached confluency. Cell monolayers were fixed overnight at 4 °C with 75 μl of 20% trichloroacetic acid (TCA). TCA was aspirated, and cells washed with tap water. Once dried, 50 μl of SRB was added to the wells and plates were incubated on a shaker at room temperature for 30 min. The excess of SRB dye was removed by washing repeatedly with 1% acetic acid, the plates were dried for 20 min, and the protein-bound dye was dissolved in 10 mM Tris for OD determination at 492 nm using a microplate reader . At least three independent experiments were performed for each cell line and in each experiment, 12 wells were measured per concentration point. These results were statistically analyzed using the Prism (GraphPad) software. Two-Way ANOVA test was used for single comparisons between different cell lines and statistical significance was assessed with the Tukey’s range test. A P-value < 0.05 was considered statistically significant.The effect of the different 11 Twenty-five metaphases were scored for chromosome breakages using the Metafer Slide Scanning Platform from Metasystems. Results were graphed as distributions of metaphases presenting 0, 1, and >1 chromatid break. Statistical analysis was performed applying chi-squared test.Chromosome fragility test was performed as previously described.Further information on research design is available in the Nature Research Reporting SummarySupplementary materialReporting Summary Checklist