Beta blockers (BB) have been associated with improved, worsened, or unchanged breast cancer outcomes in previous studies. This study examines the association between the post-diagnostic use of BBs and death from breast cancer in a large, representative sample of New Zealand (NZ) women with breast cancer.Women diagnosed with a first primary breast cancer between 2007 and 2016 were identified from four population-based regional NZ breast cancer registries and linked to national pharmaceutical data, hospital discharges, and death records. The median follow-up time was 4.51 years. Cox proportional hazard models were used to estimate the hazard of breast cancer-specific death (BCD) associated with any post-diagnostic BB use.Of the 14,976 women included in analyses, 21% used a BB after diagnosis. BB use (vs non-use) was associated with a small and nonstatistically significant increased risk of BCD . A statistically significant increased risk confined to short-term use (0–3 months) was seen , and this risk steadily decreased with increasing duration of use and became a statistically significant protective effect at 3 + years of use .Our findings suggest that any increased risk associated with BB use may be driven by risk in the initial few months of use. Long-term BB use may be associated with a reduction in BCD.The online version contains supplementary material available at 10.1007/s10549-022-06528-0. Breast cancer is the most common cancer in women and the leading cause of female cancer mortality worldwide . ComorbiHuman breast cancer cells have beta-adrenergic receptors . ResponsThere have been several methodological limitations in previous studies examining the association between BB use and BCD. For example, some studies fail to account for the time-varying nature of medication use . Moreoven = 14) or if their date of death was on or before their recorded date of breast cancer diagnosis (n = 3). The final cohort for analyses was composed of 14,976 women.Eligible women were all those with a first primary breast cancer diagnosed and recorded in any of four population-based regional breast cancer registries   in New ZIn the PHARMS database, medications dispensed any time after breast cancer diagnosis were determined using the therapeutic group ID, a PHARMAC identifier for each group of Anatomical, Therapeutic, and Chemical properties . All BBsDeaths were determined from the underlying cause of death in the regional breast cancer registries and National Mortality Collection, with ICD codes C50.0 to C50.9 classified as deaths from breast cancer.Demographic and clinical information came from the regional breast cancer registries, and covariates considered included date of diagnosis, age, ethnic group , 34, socComparisons by BB use at baseline (date of diagnosis of breast cancer) were conducted using the chi-square test. We used Cox proportional hazard models to assess hazard ratios (HRs) of breast cancer-specific mortality associated with any post-diagnostic BB use vs non-use. Death registrations and Pharmaceutical Collection coverage were complete to the end of 2017, so we followed patients from their breast cancer diagnosis until death or 31 December 2017. Women with no death recorded prior to 31 December 2017 were assumed to be alive as at 31 December 2017. Medication use was conceptualised as a time-varying covariate, such that time before the first dispensing was counted as ‘nonuser’ time, and time from the first dispensing to end of followup was counted as ‘user’ time . Models Analyses were conducted considering BB use as a binary variable (user/nonuser), and also by splitting BB use into seven categories based on the number of daily defined doses . Dose analyses were conducted using a time-varying. Approach, such that women spent time in the lowest category before moving into the next dose category. In order to compare patterns of risk observed for BBs to those of another cardiovascular medication with similar indications , the samTo examine the effect of BB use in early-stage patients only, an analysis was carried out restricted to patients with stage 1, stage 2, or stage 3a cancers. In this analysis, patients with an ‘unknown’ stage were excluded.To evaluate the effect of the competing risk of death from other causes, the proportional subhazards model was also used . For thiAs dispensings towards the end of life may reflect changes in morbidity (including cancer recurrence/progression) or in health care related to end-of-life care , 44, we In order to compare BB users to patients using other medications for a similar indication, a further analysis was carried out comparing BB users to BB nonusers who used another antihypertensive medication. For this comparison, other antihypertensives included ‘Potassium Sparing Combination Diuretics’, ‘Thiazide and Related Diuretics’, ‘ACE Inhibitors’, ‘ACE Inhibitors with Diuretics’, ‘Angiotensin II Antagonists’, ‘Angiotensin II Antagonists with Diuretics’, ‘Dihydropyridine Calcium Channel Blockers’, ‘Other Calcium Channel Blockers’, ‘Alpha Adrenoceptor Blockers’, and ‘Centrally Acting Agents’. In this analysis, BB nonusers who used another antihypertensive were followed from their first post-diagnostic antihypertensive dispensing until death or 31 December 2017.We also conducted an analysis with breast cancer recurrence (BCR) as the outcome. In this analysis, we defined a BCR as either a local/regional recurrence or distant metastasis and restricted the cohort to patients with early-stage breast cancer as above. Recurrences were determined from the breast cancer registry data through patient’s routine clinical records, and women were followed from their breast cancer diagnosis until BCR, death, last follow-up date, or end of Pharmaceutical Collection coverage (31 December 2017), whichever came first. These analyses examined the risk of BCR associated with BB use vs non-use, as well as the risk associated with different doses of BB use vs non-use.Results are reported as HRs and their 95% confidence intervals (CIs), with the two-sided significance level set at 0.05. Statistical analyses were conducted in STATA 13.1 .p < 0.05).Median follow-up for our cohort of 14,976 women was 4.51 years (range 0.01–10.99 years), with 1341 dying of breast cancer, and 884 dying from other causes. Of these 14,976 women, 21% were dispensed a BB after diagnosis (Table We compared the risk of BCD associated with BB use (vs non-use) after diagnosis Table . In the p value for linear trend was 0.0005. In the same analysis with calcium channel blockers as the exposure of interest (Table p for trend = 0.2).In the dose analysis, the highest risk was observed during the initial 0–3 months of BB use , with a HR of 1.40 (1.14–1.73) for the initial 0 to 3 months of use, and a HR of 0.55 (0.34–0.88) for 3 or more years of use. After the equivalent of a year’s use, the risk was decreased with increasing duration of use, which may be suggestive of a protective effective associated with long-term BB use. Previous literature investigating dose–response effects of BBs has been sparse; however, our results are in contrast to two previous papers  [We found the risk of BCD to decrease with increasing doses of BBs ( effect) , 22, whi effect) , and one effect) . To our  effect) , whereby 1.14–1.7 for the The hypothesis that increased risk associated with the first few months of use is driven by short-term use towards the end of life is supported by an amalgamation of evidence. Firstly, there was a clear pattern in women’s median time to death/last follow-up from their first BB dispensing by dose category: those who took BBs in lower doses consistently had a shorter time interval between their first dispensing and death/last follow-up than those who took BBs for longer (Supplementary Table S3). Secondly, there was no longer a statistically significant increased risk in short-term users when considering BCR as the outcome Table . This suIt has been suggested that breast cancer and CVD deaths are sometimes misclassified, with one study suggesting that women’s cancer diagnosis is often perceived as the overriding medical priority in patients with both cancer and CVD . HoweverWhen BB users were compared with a more similar comparison group (BB nonusers who used another antihypertensive), we observed a 24% increased risk of BCD after adjustment for confounding variables. This result may be explained by BB dispensings towards the end of life, as the HR decreased from 1.24 (1.05–1.47) to 0.98 (0.77–1.25) when lagging medication times by 2 years. Therefore, it appears that any differences in the HRs between different comparison groups can mostly be attributed to differences in end-of-life care between the two groups, rather than any fundamental differences in their underlying characteristics.Finally, adjusting for the competing risk of death from other causes or analysing early-stage patients only did not substantially affect the HR. Moreover, when we applied these types of analyses to our other results, the HR did not change to a degree that would alter the interpretation of our results.The primary strength of our study is that we had a large cohort of patients with breast cancer followed up over a relatively long time period sourced from four population-based databases. The Auckland and Waikato databases have been checked against the National Cancer Registry and found to be at least 99% complete, and the registry data we used contains more comprehensive and accurate information than the national data sources –53. Our Our study also has limitations. We did not have access to primary care data, which meant that our comorbidity data were restricted to hospital admissions in the relevant timeframe. Furthermore, this limited access to a range of potential confounders such as body mass index, alcohol intake, and smoking status, all of which would generally be available through general practitioner records. However, these limitations in residual confounders were somewhat mitigated by the use of a more balanced comparison group. The most commonly prescribed BB in New Zealand is a selective BB, metoprolol , which wIn conclusion, there was only a weak and non-significant association between post-diagnostic BB use and BCD in this large population-based study of NZ patients with breast cancer. Further analyses showed an increased risk associated with the first few months of use, likely to be due to use towards the end of life. For longer-term use, risk of death decreased with increasing duration of use, suggesting that long-term BB use may confer a protective effect on BCD. Further research is warranted to assess if this relationship is replicated in other clinical settings.Supplementary file1 (DOC 59 kb)Below is the link to the electronic supplementary material.


BRCA1, we reported that increased blood arsenic levels are significantly associated with high breast-cancer risk. The aim of this study was to assess if an association between As levels and cancer risk also exists among women harboring mutations in BRCA1. We found that women with As blood levels above the median (0.85 µg/L) had a significant 2-fold increased risk of developing breast cancer. This raises the possibility that lowering the blood arsenic level by dietary means might reduce cancer risk for BRCA1 mutation carriers. Arsenic (As) is recognized by the International Agency for Research on Cancer (IARC) as a potent carcinogen. Numerous studies are focused on endemic regions of high exposure, and its effect on human health. Several authors suggest that As may be an important endocrine disruptor, mainly through estrogen-like activity. In our previous study on subjects without germline mutations in BRCA1 have a lifetime cancer risk of 70%. As part of a larger prospective study on heavy metals, our aim was to investigate if blood arsenic levels are associated with breast cancer risk among women with inherited BRCA1 mutations. A total of 1084 participants with pathogenic variants in BRCA1 were enrolled in this study. Subjects were followed from 2011 to 2020 (mean follow-up time: 3.75 years). During that time, 90 cancers were diagnosed, including 67 breast and 10 ovarian cancers. The group was stratified into two categories (lower and higher blood As levels), divided at the median (<0.85 µg/L and ≥0.85 µg/L) As level among all unaffected participants. Cox proportional hazards models were used to model the association between As levels and cancer incidence. A high blood As level (≥0.85 µg/L) was associated with a significantly increased risk of developing breast cancer  and of any cancer . These findings suggest a possible role of environmental arsenic in the development of cancers among women with germline pathogenic variants in BRCA1.An important group of breast cancers is those associated with inherited susceptibility. In women, several predisposing mutations in genes involved in DNA repair have been discovered. Women with a germline pathogenic variant in  BRCA1 mutation have a lifetime risk of developing breast cancer of approximately 70% [BRCA1 mutation carriers [Women with an inherited tely 70% ,3. Variotely 70% . Over thtely 70% ,5,6,7. Hcarriers ,9.Arsenic is a metalloid that is widely distributed throughout the environment and can be found in water, soil and air . ArsenicBRCA1 mutation. We reported that women in the highest quartile of total blood arsenic had a 13-fold increased risk of breast cancer, compared to women in the reference group [BRCA1.We have recently demonstrated a significant association between total blood arsenic levels and the risk of breast cancer in a population of Polish women who did not carry a ce group . To datece group . In the The study subjects were women aged 25 years and above, who received genetic counselling and testing between January 2011 and August 2020. All participants had no prior history of breast, or other, cancers at the time of enrollment in the study. All participants provided informed, written consent to participate in the study, and agreed to provide a blood sample to be used for research purposes . The stuBRCA1 mutations. Additionally, a second aliquot of 2 cc of whole blood was collected for research purposes. All blood samples were collected between 8 a.m. and 2 p.m. and stored at −80 ℃ until analysis. Participants were included in the study if a deleterious BRCA1 variant was detected.At the first study visit, a fasting blood sample was collected from each study participant to be used for genetic testing for BRCA1 deleterious mutations were excluded from this study, and results from that sub-cohort have been reported in a prior publication [Women without lication .Study participants also completed a detailed questionnaire regarding their age, prior contraceptive and hormone replacement therapy use, smoking habits, personal medical history, including ovary removal surgery (oophorectomy), use of dietary supplements, diabetes, and body mass index (BMI).2 purity > 0.9999, Messer). Samples were diluted 30 times using an alkali buffer. For best accuracy, matrix-matched technique was used for calibration. The calibration curve consisted of 0.0 µg/L; 0.48 µg/L; 0.96 µg/L; 1.98 µg/L and 2.0 µg/L calibration points, for which the linear coefficient was always greater than >0.999. Rhodium was set as an internal standard to compensate instrument drift and matrix effects. Parameters of the method were confirmed by using several available certified materials: NIST 955C , Plasmonorm Whole Blood Level 1 .Total blood arsenic was quantitatively measured using inductively coupled plasma mass spectrometry, using the ELAN DRC-e instrument . Arsenic was measured under the DRC (Dynamic Reaction Cell) conditions with oxygen as a reaction gas  to the date of first breast cancer diagnosis, death from another cause, or 18 August 2020.There were 1084 women enrolled in this study. All were free of cancer at baseline and carried a mutation in the Information on diagnosed cancers was extracted from the medical records and manual review of pathology records from the treating hospitals in Szczecin (Poland), Bari  and Riga (Latvia). Study participants were assigned to one of two categories (lower and higher blood As levels) divided by the median (<0.85 µg/L and ≥0.85 µg/L) As level among all unaffected participants. In order to estimate the hazard ratio (HR) for breast cancer risk, univariable and multivariable Cox proportional hazards regression models were calculated. In multivariable models, the following factors were taken into analysis: arsenic median, age at blood draw (≤50 vs. >50), oral contraceptive use (ever/never), hormone replacement therapy use (ever/never), smoking history (yes/no), oophorectomy (yes/no), dietary supplement use (ever/never), diabetes (yes/no), BMI . BMI was stratified to four categories: <18.5 as underweight, 18.5–24.9 as normal weight; 25.0–29.9 as pre-obesity; ≥30.00 as obesity. To exclude the potential influence of other toxic metals on breast cancer risk, levels of lead and cadmium were included in the multivariable analysis. Subjects were assigned to one of two categories (lower and higher) divided by the median (11.75 µg/L for Pb and 0.42 µg/L for Cd) level among all unaffected participants.Cancer-free observation time (or time to diagnosis) varied between 0 and 8 years. Crude differences in cumulative rate incidence by the As level were tested for statistical significance using the log-rank test. A secondary analysis was conducted using the diagnosis of any cancer as the outcome. For this analysis, all patients were followed from date of blood draw or age 25 years (whichever came last) to the date of the first cancer diagnosis, death from another cause or 18 August 2020.All statistical analyses were performed using R statistical environment (R version 4.0.3 (2020-10-10); Copyright (C) 2020 The R Foundation for Statistical Computing).BRCA1. A total of 46 different BRCA1 deleterious variants were detected in this cohort, and three founder mutations  contributed 89.39% of all detected variants. All study participants had no prior history of cancer at the time of enrollment in the study. Total blood arsenic levels for all women in the cohort are presented in This study included 1084 women . All were positive for a deleterious variant in The women were followed for an average 3.75 years (range 0–8 years) from the blood draw. Over the follow-up period, 90 incident cases of cancers were diagnosed in the study cohort .This included 67 cases of breast cancer, 10 cases of ovarian cancer, and 13 cancers at other sites. One study participant was affected by both breast and ovarian cancer during the follow-up period. For analysis, the date and type of the first cancer was used.The 1084 study participants were assigned to one of two categories (lower and higher blood As levels) divided by the median (<0.85 µg/L and ≥0.85 µg/L) As level among all unaffected participants. The univariate and multivariate hazard ratios (HR) for developing breast cancer, stratified by median blood arsenic levels, are presented in p = 0.011). The effect was similar after adjusting for age at blood draw (≤50 vs. >50), oral contraceptive use (ever/never), hormone replacement therapy use (ever/never), smoking history (yes/no), oophorectomy (yes/no), dietary supplement use (ever/never), diabetes (yes/no), BMI , levels of other toxic metals, such as lead and cadmium .In the crude analysis, a higher level of total blood arsenic (≥0.85 µg/L) was associated with a significantly increased risk of developing breast cancer  and 10% for the high blood arsenic group (≥0.85 µg/L) .n = 90). Similar to the previous analysis, women were assigned to one of two categories (lower and higher blood As levels) divided by the median (<0.85 µg/L and ≥0.85 µg/L) As level among all unaffected participants. The univariate and multivariate hazard ratios are presented in In a secondary analysis, the diagnosis of any cancer was considered as the endpoint (p = 0.02).Overall, women who had higher total blood arsenic levels (≥0.85 µg/L) had a 1.7 increased risk of developing any cancer, compared to the lower blood arsenic reference group  and 13% for the high total blood arsenic group (≥0.85 µg/L) .BRCA1 gene. The findings of this study revealed a statistically significant association between baseline blood arsenic levels and subsequent risk of breast cancer, and with all cancers combined. Women with a higher total blood arsenic level (≥0.85 µg/L) had a 2.05 increased risk of developing breast cancer, compared to the lower blood arsenic reference group (p = 0.011). The risk ratio was not modified by adjusting for potential confounders.In this prospective study of 1084 European women, we evaluated the impact of arsenic exposure on individuals who have inherited susceptibility to breast cancer because of mutations in the p = 0.02). When comparing these findings to those of our previous study in women who did not have a BRCA1 mutation [Similarly, in an analysis of all cancers combined, the HR comparing women in the higher blood arsenic group to the lower reference group was 1.73  in the body [The methylation of arsenic is thought to be one of the primary aspects of the element’s carcinogenicity. Currently accepted mechanisms suggest that incomplete methylation of inorganic arsenic to dimethylarsinic acid leads to the bioaccumulation of toxic arsenic species , as well as genome methylation. Validation studies on additional cohorts and from different populations are also needed.BRCA1 mutation carriers. This correlation is attractive as it creates the perspective that lowering blood arsenic level by control of diet can significantly improve the situation of carriers. Blood arsenic level is the marker of cancer risk among


Adolescence and early adulthood has been identified as a critical time window for establishing breast cancer risk. Mammographic density is an independent risk factor for breast cancer that may be influenced by diet, but there has been limited research conducted on the impact of diet on mammographic density. Thus, we sought to examine the association between adolescent and early adulthood inflammatory dietary patterns, which have previously been associated with breast cancer risk, and premenopausal mammographic density among women in the Nurses’ Health Study II (NHSII).This study included control participants with premenopausal mammograms from an existing breast cancer case-control study nested within the NHSII who completed a Food Frequency Questionnaire in 1998 about their diet during high school (HS-FFQ) (n = 685) and/or a Food Frequency Questionnaire in 1991 (Adult-FFQ) when they were 27–44 years old (n = 1068). Digitized analog film mammograms were used to calculate the percent density, absolute dense, and non-dense areas. Generalized linear models were fit to evaluate the associations of a pro-inflammatory dietary pattern and the Alternative Healthy Eating Index  with each breast density measure.Significant associations were observed between an adolescent pro-inflammatory dietary pattern and mammographic density in some age-adjusted models; however, these associations did not remain after adjustment for BMI and other breast cancer risk factors. No associations were observed with the pro-inflammatory pattern or with the AHEI pattern in adolescence or early adulthood in fully adjusted models.To our knowledge, this is the first study to evaluate the dietary patterns during adolescence and early adulthood in relation to mammographic density phenotypes. Our findings do not support an association between adolescent and early adulthood diet and breast density in mid-adulthood that is independent of BMI or other breast cancer risk factors.The online version contains supplementary material available at 10.1186/s13058-021-01449-0. Mid- and later life adult diet and breast cancer risk have been extensively studied, but few associations have emerged . Prior rThe aim of this study was to examine the association between adolescent and early adulthood dietary patterns and premenopausal mammographic density. Two different inflammatory-associated dietary patterns were examined: pro-inflammatory and the Alternative Healthy Eating Index (an anti-inflammatory dietary pattern). We also examined whether the associations between these dietary patterns differed by body mass index (BMI), an established risk factor for breast cancer that is also associated with mammographic density.The NHSII is an ongoing prospective cohort that began in 1989 with 116,429 female registered nurses aged 25–42 years at baseline. Questionnaires are sent biennial to collect follow-up information on medical conditions, health, family history, and lifestyle factors . AdditioThe study population for this analysis was restricted to control participants from an existing breast cancer case-control study nested within the NHSII. Details on this study have been provided previously . In brieIn 1997, participants were asked if they would be willing to complete a supplemental FFQ about diet during high school (HS-FFQ). The HS-FFQ was completed by 83%  of women sent this questionnaire in 1998 when they were between 33 and 52 years old . This 12Early adulthood diet was assessed with the 1991 FFQ (Adult-FFQ) which collected dietary information on more than 130 food items, with nine responses possible ranging from never to six or more times per day. The reproducibility and validity of the FFQ questionnaire have been extensively assessed , 25, 26.The pro-inflammatory dietary pattern was previously developed using reduced rank regression (RRR) to identify foods strongly related to inflammatory biomarkers  in a subset of primarily postmenopausal women in the Nurses’ Health Study (NHS) –29. ThisAn anti-inflammatory diet was defined based on the Alternative Healthy Eating Index (AHEI), for which the details of this scoring method can be found elsewhere , 31. In 2), absolute non-dense area (in cm2), and percent mammographic density area were calculated. Since density for the left and right breast have shown to be strongly correlated [Mammographic density was calculated using digitized analog film mammograms. Details have been described previously . Mammogrrrelated , the aveInformation on breast cancer risk factors was collected from baseline and biennial questionnaires. The baseline questionnaire (1989) was used to determine BMI at 18 years old, age at menarche, and high school physical activity. The biennial questionnaire directly preceding the mammogram date was used to determine the covariates at the time of mammogram: age, current BMI, age at first birth, parity, biopsy-confirmed benign breast disease, and first-degree family history of breast cancer.Primary analyses were restricted to controls with premenopausal mammographic density measurements who completed the HS-FFQ n = 812) and/or Adult-FFQ (n = 1257), as shown in Fig. 2 and/or Generalized linear models were fit to evaluate the association between each quintile of each dietary pattern (pro-inflammatory and AHEI) and mammographic density phenotype . Dietary intake was examined at three time points: adolescence, early adulthood, and average of adolescence/early adulthood. Since controls were matched to each case in the original nested case-control data , generalmodel 1 was adjusted for age at mammogram and total caloric intake at the time of dietary assessment (high school and/or early adulthood), model 2 was additionally adjusted for BMI at mammogram, and model 3 was additionally adjusted for BMI at age 18, physical activity at the time of dietary assessment, alcohol intake at the time of dietary assessment, age at menarche, age at first birth, parity, history of benign breast disease, and first-degree family history of breast cancer. For the averaged analysis, physical activity and alcohol intake were adjusted using adolescent-level variables only. In addition, as BMI is strongly correlated with percent mammographic density [For each time point of dietary assessment , three models were examined:  density –36, we c density .The median age at the time of mammogram was 44 years old (range 30–55 years) with a mean percent mammographic density of 41%. The greatest overall mean caloric intakes  were observed among women whose dietary patterns were strongly pro-inflammatory in adolescence (Table trend = 0.005) and non-dense area increased (ptrend < 0.0001)  Table . However1) Table . No asso1) Table  and 3.TUpon examination of individual covariates, we observed the greatest attenuation of the effect estimates occurred with adjustment for BMI at the time of mammogram. To more fully examine the impact of BMI on the dietary pattern-mammographic density association, we stratified the percent mammographic density analyses by BMI at the time of mammogram (< 25 vs. ≥ 25) Table . The meaIn this study, we did not observe significant associations between inflammation-associated dietary patterns in adolescence or early adulthood and mammographic density in models fully adjusted for breast cancer risk factors. Although significant associations were observed between an adolescent pro-inflammatory dietary pattern and mammographic density in some age-adjusted models, with a similar but non-significant pattern for the early adulthood pro-inflammatory dietary pattern, these associations did not remain after adjustment for BMI and other breast cancer risk factors. While, as expected, the distribution of percent mammographic density varied by BMI, no associations were observed between dietary patterns and mammographic density within the strata of BMI .To our knowledge, this is the first study to evaluate the relation between adolescent dietary patterns and mammographic density as prior studies have focused on individual foods/food groups and sources of macronutrients . In previous work in the NHSII cohort, Bertrand et al. observed that adolescent animal fat intake was positively associated with premenopausal mammographic density, an association that remained after adjustment for red meat intake and adult intake of animal fat. In addition, adolescent red meat intake had a non-significant positive association with mammographic density . ConsistA limited number of studies have examined the dietary patterns in relation to mammographic density, with a focus on mid-life dietary patterns. In the Minnesota Breast Cancer Family Study (n = 1286), the association between a Mediterranean dietary pattern  and mammographic density was examined among a sample of predominantly postmenopausal women . No overThere are some important limitations of this study to be considered. First, measurement error could have impacted the adolescent diet assessment, since participants were asked to recall diet as much as 2 to 3 decades in the past , 32. HowA further limitation is related to the timing of the breast density assessment. Breast density measured through a screening mammogram may not capture the most relevant breast density measurement in regard to the impact of adolescent dietary exposures. Studies have shown that breast density declines with age , but theAn important strength of this study was the access to digitized mammograms, and the ability to measure dietary patterns at two different time points among the study population, adolescence and early adulthood. Information on the risk factors was also available for both time points, which allowed for necessary adjustments in multivariable analyses.In conclusion, we observed that, after adjusting for covariates including BMI at mammogram, consuming a pro-inflammatory or AHEI dietary pattern during adolescence or early adulthood was not associated with premenopausal mammographic density. More research is needed to investigate early life diet in relation to breast density using prospectively collected dietary data and breast density measured prior to the age of most mammograms.Additional file 1: Table S1. Food Components of the Pro-Inflammatory and Alternative Healthy Eating Index (AHEI) Dietary PatternsAdditional file 2: Table S2. Adolescent and adult characteristics by early adulthood dietary patterns among 1,117 premenopausal women in NHSIIAdditional file 3: Table S3. Mean mammographic density phenotypes  by quintile of averaged dietary patterns (n=677)


Among different molecular subtypes, ORPS was positively correlated with Luminal breast cancer, with additionally positive association with triple-negative breast cancer in premenopausal women. The ORPS might be a potential marker of breast cancer risk among Chinese women.There is strong evidence to suggest that obesity-related proteins play a key role in pathways that are related to breast cancer. In this study, we aimed to establish a robust obesity-related protein score (ORPS) that could be used to assess breast cancer risk. Based on evidence from high-quality systematic reviews and population studies, we selected nine such proteins that are stable in vitro, and measured their circulating concentrations by ELISA in a case–control study conducted in Chengdu, Sichuan, China, with 279 breast cancer cases and 260 healthy controls. Two obesity-related protein scores (ORPS) were calculated using a three-step method, with linear-weighted summation, and the one with a larger area under the curve was chosen for further evaluation. As a result, ORPS (PS Breast cancer was also the first common cancer in Chinese women, with its age-standardized incidence rate increased by 94.73% from 1990 to 2017 and the age-standardized death rate increased by 2.46%2. General and central obesity are modifiable risk factors for many chronic diseases4, and are often defined by body mass index (BMI) or waist-hip ratio (WHR)6. A meta-analysis of data from 7 cohort studies showed positive associations between BMI and WHR with obesity-related cancers, including postmenopausal breast cancer7.Breast cancer constitutes the most commonly-diagnosed cancer and the leading cause of cancer death in women, worldwide, according to the International Agency for Research on Cancer (IARC) World Cancer Reports in 20204. Ten proteins are involved in the former two pathways, namely adiponectin (ADP), leptin (LEP), resistin (RES), visfatin (VF), interleukin-6 (IL-6), tumor necrosis factor-α (TNF-α), C-reactive protein (CRP) and interleukin-8 (IL-8), etc8. Nine common circulating sex hormones are involved in the sex hormones biosynthesis pathway, including estrone (E1), estradiol (E2), progesterone (P), estrone sulfate (ES), androstenedione (A), dehydroepiandrosterone (DHA), dehydroepiandrosterone sulfate (DHAS), sex hormone-binding globulin (SHBG) and testosterone (T)8. Four proteins including C-peptide, insulin (INS), insulin-like growth factors (IGFs) and IGF-binding proteins (IGFBPs) are taken multiple biological roles in the insulin-IGF-1 axis, one of the potential biological mechanisms underlying the obesity-breast cancer connections9. Abnormal regulations in the blood levels of these proteins caused by adipose tissue may contribute to breast cancer initiation and progression through the activation of multiple signaling pathways10.Several interlinked biological pathways have been recognized which may explain the correlation between obesity and breast cancer: (1) alterations in adipocytokine pathophysiology; (2) subclinical chronic low-grade inflammation and oxidative stress; (3) sex hormones bio-synthesis pathway and (4) abnormal system and signaling of insulin-like growth factor (IGF)-1 and insulin resistance11. Moreover, the increase in the prevalence of obesity in China has been lower to date than that in Western countries12, therefore it is uncertain whether obesity-related proteins might represent equally useful markers of breast cancer risk in Chinese women.Although it has been suggested that obesity-related proteins might be suitable for use as markers of breast cancer risk, there are some serious challenges that need to be overcome. For instance, the evidence obtained to date suggests that it is unreliable to use a single obesity-related protein as a risk marker of breast cancer, and it is hard to obtain a comprehensive evaluation especially when the associations between several obesity-related proteins and breast cancer are inconsistent. Using leptin and adiponectin as examples, a meta-analysis of data from 119 studies showed that leptin concentration is positively associated with breast cancer risk, whereas adiponectin is negatively associatedIn the present study, we aimed to identify obesity-related proteins that are associated with breast cancer risk using evidence from systematic reviews, and to use this information to establish a robust obesity-related protein score (ORPS) that could be used to assess breast cancer risk.An age-matched case–control study was conducted. Two hundred and seventy-nine women newly diagnosed with primary breast cancer by histopathology were enrolled from three hospitals in Chengdu, Sichuan Province, China, from April 2014 to April 2015. The inclusion criteria were Han nationality, living in Sichuan province, not receiving anti-infective treatment, no mental disorder and other malignant tumors. We also excluded patients with metastatic breast cancer. Meanwhile, 260 healthy women of urban and rural screening cohorts from two hospitals in Chengdu, Sichuan Province, China, were recruited from March 2015 to June 2015. The inclusion criteria were Han nationality, living in Sichuan province, and being confirmed to be free of breast cancer via ultrasound or mammography. Women who were receiving anti-infection treatments or had a mental disorder or any malignant tumors were excluded. In both cases and controls, women who had previously undergone abdominoplasty surgery, were receiving neoadjuvant therapy currently or received it in the last 12 months, were receiving or had received any hormonal therapy (HT) during the last 12 months, had gone on a strictly restricted diet in the last 12 months or had lost > 3 kg in the last year were all excluded.13 to collect information on demographic characteristics and breast cancer risk factors of participants. Women aged 50 or older, or had undergone bilateral oophorectomy or surgical sterilization, or younger than 50 years old but had their menstrual periods been absent for at least 12 months were considered to be postmenopausal. The pathological characteristics of cases, such as the levels of ER (estrogen receptor), PR (progesterone receptor), HER-2 , and Ki-67 (a protein that in humans is encoded by the MKI67 gene) were derived from the hospital information system. The study protocol was approved by the ethics committee of West China School of Public Health and West China Fourth Hospital, Sichuan University. Written informed consents were obtained prior to questionnaires and blood samples donation.A structured questionnaire was designed based on previous study14, electronic databases including PubMed, Embase, CNKI, VIP and Wanfang were assessed to search for original researches or systematic reviews on obesity-related proteins and breast cancer risk. Protocol of this has been registered on the International Prospective Register of Systematic Reviews (PROSPERO no. CRD42019127767). Proteins included in this study should meet the following inclusion criteria: (1) significantly correlated with breast cancer risk; (2) serum or plasma level was relatively stable in vitro with the degradation rate less than 10% or has been detected by previous studies using blood samples stored in the refrigerator for years.Based on the above-mentioned biological pathways15. Proteins with unclear associations with breast cancer risk were excluded . Proteins degrading > 10% in vitro were excluded .Nine proteins were selected ultimately, namely E2 (estradiol), LEP (leptin), sOB-R (soluble leptin receptor), ADP (adiponectin), RETN (resistin), VF (visfatin), IGF-1 (insulin-like growth factor-1), IGFBP-3 (IGF-binding protein-3) and CRP (C-reactive protein) . The standard sample was detected through double-holes and the average value was calculated. Absorbance was detected by the enzyme labeling instrument . We used Origin software (version 9.0) to obtain the standard curve and calculate the circulating concentrations. To avoid human and instrument errors, each candidate protein was detected by the same researcher using the same batch of ELISA kit.sd) and t test or variance test to describe and compare the demographic characteristics between cases and controls. Otherwise, median (quartile) and rank-sum test would be used. For categorical variables, we used frequency (composition ratio) and chi-square test. To consider as statistically significant, a p < 0.05 is required.All analyses were stratified by menopausal status. To avoid the influence of units of proteins, plasma levels were standardized before analyses by dividing the original level by the mean. For continuous variables, if normally distributed, we used mean ± standard deviation . We standardized the scores to 0–100, and the formula for standardization was as follows , R 3.5.1 software (R Core Team (2018), Vienna, Austria. https://www.R-project.org/) and Microsoft EXCEL software (Microsoft (2016), USA. https://www.microsoft.com/zh-cn/microsoft-365/excel). An overview of the analysis process was shown in Supplementary Fig. All the statistical analyses were conducted using SPSS 24 software . Additionally, premenopausal cases had an earlier age at menarche and exercised less, and postmenopausal cases were more likely to be passive smokers and have more estrogen diseases  and fewer proteins compared to that of PS8pre        . However, PS4post was positively correlated with the risk in obese women  . As a result, the PS18. It could inhibit the hypoglycemic reactivity and sensitivity of insulin, resulting in hyperinsulinemia and other chronic diseases20. RETN is also involved in tumor progression through the activation of inflammation and the expression of adhesion molecules, promoting the proliferation, metabolism and invasion of tumor cells22. A meta-analysis of data from eight previous studies found that RETN concentration positively correlated with breast cancer risk23, which is consistent with our findings.RETN concentration is associated with obesity and insulin resistance24 and chronic inflammation. Previous studies have suggested that chronic inflammation often coexists in tissues that are affected by malignant tumors. Besides, cancer cells could aggravate chronic inflammation response and impart tumor micro-environment, contributing to the proliferation and survival of malignant cells, angiogenesis and metastasis, destruction of adaptive immunity, and decreasing responses to hormones and chemotherapy27. Similar to the present findings, a systematic review of 15 cohort and case–control studies suggested a positive association between CRP and breast cancer risk28.CRP is one kind of acute-phase response proteins related to obesity18 and risk of breast cancer by activating an anti-proliferative process on cancer cells, controlling cell cycle, regulating cell migration and inhibiting DNA synthesis, as well as anti-tumor immunity30. The protective effect on breast cancer, that in line with our study, was also observed in a systematic review consisting of 60 observational studies31.ADP is negatively correlated with obesity18 and tumor progression by inhibiting the apoptosis of tumor cells and promoting the expression of oncogenes. Circulating sOB-R binds LEP, which results in a low concentration of free LEP and the inhibition of its biological function32. A previous case–control study found that the sOB-R concentration in normal individuals was higher than that in breast cancer cases33.sOB-R binds another adipocytokine, namely LEP. LEP is mainly involved in obesity, appetite control, energy metabolism34. And it promotes mitosis, proliferation, and differentiation, and inhibits apoptosis, but these are inhibited when IGF-1 binds to IGFBP-3, one of its specific binding proteins36. The carcinogenic mechanism of IGFBP-3 was suggested to be bidirectional37. A systematic review showed that high levels of IGF-1 and IGFBP-3 were positively correlated with premenopausal breast cancer risk38, while IGFBP-3 was found to have a protective effect in our study, which might be due to the bidirectional carcinogenic mechanism of IGFBP-3. Additionally, the above association was found only in premenopausal women. The possible explanation is: since each of these molecules may be regulated by estrogen, which may increase membrane IGF-1 receptors, which would increase the effects of IGF-1, and downregulate IGFBP-3, such that the high estrogen concentrations in premenopausal women would amplify the biological effect of IGF-135.IGF-1 may contribute to the development of obesity5pre and PS4post was positively associated with Luminal breast cancer risk, which may be related to the potential interactions among proteins and hormone receptors. In vitro, the pro-apoptotic effect of ADP was found only in ER+ cell lines39. The signal axis of leptin interacts with ER to enhance the occurrence and metastasis of tumors40. In addition, we have shown that there are lower ADP concentrations in Luminal breast cancer41. Cho et al.42 suggested that a higher concentration of LEP results in a poorer prognosis in ER or PR-positive patients only, whereas Lee et al.43 found that ER-positive patients have a higher concentration of RETN than ER-negative patients. Furthermore, Raman et al.44 showed that high CRP concentrations are associated with PR or ER. Therefore, the proteins that comprised PS5pre and PS4post all interacted with ER or PR.Additionally, we also found that PS5pre had shown a stronger relevance to triple-negative breast cancer than that of luminal breast cancer in premenopausal women. The association between PS5pre and triple-negative breast cancer could be mediated via IGFBP-3 by two ways. First, IGFBP-3 and IGF-1 are regulated by estrogen35, resulting in low concentrations of IGFBP-3 in premenopausal women, which is consistent with our finding. Second, via the epidermal growth factor receptor signaling pathway45, the over-expressed IGFBP-3 may promote triple-negative breast cancer development47. Therefore, in ER-negative breast cancer, high concentrations of IGFBP-3 would result in more rapid recurrence, and therefore a poorer prognosis48. Thus, IGFBP-3 may represent a novel predictor of and potential therapeutic target for triple-negative premenopuasal breast cancer.Moreover, it was interesting to note that the PSThis study is the first to construct the ORPS for breast cancer. We selected our candidate proteins based on high-quality evidence, and constructed the ORPS with an innovative three-step method. Our study also had several weaknesses. As a case–control study, the association between ORPS and breast cancer risk could not been confirmed. The applicability and authenticity need to be further verified by future longitudinal studies. Additionally, due to a small sample size, the statistical power might be low and the associations might not be estimated correctly, and we did not further subdivide Luminal breast cancers into Luminal-A and Luminal-B subtypes. Finally, complex interactions between the investigated proteins should be further considered. Despite all these, the associations of proteins and breast cancer risk we observed were consistent with the previous studies, and a significant association was found between the ORPS and breast cancer risk.5pre or PS4post) was positively correlated with breast cancer risk and represented a better risk predictor among obese women compared to non-obese in pre- and postmenopausal women. Among different molecular subtypes, ORPS was positively correlated with Luminal breast cancer with additionally positive association with triple-negative breast cancer in premenopausal women. The ORPS might be a potential marker of breast cancer risk among Chinese women. Future studies should focused on the development of rapid detection methods of obesity-related proteins and some of their components in isolation, so as to promote the application of ORPS in clinical practice.ORPS (PSSupplementary Information.


Breast cancer (BC) represents the most common cancer in women, while overweight and obesity are the second preventable cause of cancer. Weight gain and fat accumulation are common after BC diagnosis; moreover, weight gain during the treatment decreases the survival rate and increases the risk of recurrence in breast cancer survivors (BCS). To reduce the risk of second primary cancer or BC recurrence, and all-cause mortality in BCS, multiple interventions have been investigated to obtain reduction in weight, BMI and/or waist circumference. The aim of this narrative review is to analyze evidence on BCS for their risk of recurrence or mortality related to increased weight or fat deposition, and the effects of interventions with healthy dietary patterns to achieve a proper weight and to reduce fat-related risk. The primary focus was on dietary patterns instead of single nutrients and supplements, as the purpose was to investigate on secondary prevention in women free from disease at the end of their cancer treatment. In addition, BC relation with insulin resistance, dietary carbohydrate, and glycemic index/glycemic load is discussed. In conclusion, obesity and overweight, low rates of physical activity, and hormone receptor-status are associated with poorer BC-treatment outcomes. To date, there is a lack of evidence to suggest which dietary pattern is the best approach for weight management in BCS. In the future, multimodal lifestyle interventions with dietary, physical activity and psychological support after BC diagnosis should be studied with the aim of reducing the risk of BC recurrence or mortality. Breast cancer (BC) represents the most common cancer in women, while overweight or obesity are the second preventable cause of cancer, related to 33% of postmenopausal breast cancers that could be prevented by lifestyle modification .Excessive body fat deposition and weight gain promote a pro-oxidative microenvironment with chronic low-grade systemic inflammation, posing breast cancer survivors (BCS) at high risk of second primary cancer or BC recurrence, and all-cause mortality . HealthyThe third expert report on “Diet, nutrition, physical activity and breast cancer” of the World Cancer Research Fund/American Institute for Cancer Research (WCRF/AICR) [dietandcancerreport.org] for preventing cancer generally recommends maintaining a healthy lifestyle by being physically active and eating a healthy diet for proper weight management . Therefore, body weight management is crucial not only for primary prevention of cancer in general, but also for secondary cancer prevention in breast-specific sites. All women after a BC diagnosis undergo treatments for such a life-changing diagnosis and should be counselled to prevent excessive fat mass deposition, that is often a common event .The relation between overweight/obesity and cancer is still not fully clarified; the tumor environment could be metabolically stimulated by the excess of adipose tissue, with elevated levels of free fatty acids (FFA) and triglycerides, increased blood glucose, and insulin resistance. Increased production of adipokines, especially leptin, and inflammatory cytokines, such as tumor necrosis factor alpha (TNF-α), interleukin-6 (IL-6), interleukin-1 beta (IL-1β), TGF-β could exert local and systemic functions . Breast With this purpose, multiple interventions on breast cancer survivors (BCS) have been investigated especially in patients with overweight or obesity to obtain weight loss and reduce BMI and/or waist circumference as a proxy for proinflammatory fat accumulation. To date, there is still a lack of evidence to suggest which dietary strategy is the best among those available after BC diagnosis.The aim of this review is to collect evidence on the risk of recurrence or mortality in BCS related to increased weight or fat deposition and the effects of interventions with healthy dietary patterns aiming to achieve a proper weight, improve waist circumference, or reduce obesity-related risk factors.A search was conducted using keywords: “breast cancer” OR “breast cancer survivors” OR “breast cancer prevention” AND “nutritional therapy” OR “dietary therapy” OR “diet”, applying “humans” as a filter, and selecting articles published between 2015 and March 2021 on such databases as PubMed, Google Scholar, MEDLINE, EMBASE, and Scopus. Among 3640 results, 525 were included in the first selection after screening by title and abstract, 61 of which reported data on BCS. Among the latter, full texts of original studies and reviews were screened after exclusion of reports on “cancer” in general, thus only selecting those referring to site-specific “breast cancer”. In this narrative review, we assess the effect of dietary patterns to investigate secondary preventions in women free from BC or at the end of treatment. Studies were excluded if carried out on a BC patient on chemotherapy-active treatment, if reporting only single nutrients and/or supplement treatments, and if reporting only adherence to dietary recommendations/guidelines  or healthy patterns but not data on recurrence or mortality risk from BC. When included, “healthy patterns” were specifically described or specified . Studies reporting outcomes other than recurrence or mortality risk  were excluded. Eventually, duplicates, abstract without the full text available, reports on mice or basic science, and study protocols were excluded .Among 61 selected papers, only 32 address a specific dietary pattern implemented in BCS not undergoing chemotherapy or any active treatment other than hormonal or immune therapy, aimed at the prevention of recurrence. In Women with BC show a 30% excess risk for second malignancies, even higher if considering contralateral breast cancers . Weight In the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort the risk for second malignancies after invasive BC was particularly elevated for colorectal cancer (OR 1.71), lymphoma (OR 1.80), melanoma (OR 2.12), endometrium (OR 2.18), and kidney cancers (OR 2.40), and positively associated with age at first cancer, BMI, and smoking status . Another review investigating the best approach to recommend to overweight or obese BCS found that multimodal weight-loss interventions, including diet, exercise, and psychosocial support, achieved greater reduction in body weight, BMI, and waist circumference and improved overall quality of life more than dietary change alone . UnfortuInterestingly, a review has analyzed the association between dietary patterns and/or main food groups with mortality and cancer recurrence in survivors of common cancers, including BC, prior to or after cancer diagnosis. Their findings suggest that reducing the amount of body fat after diagnosis decreases the risk of breast cancer recurrence, and adherence to a high-quality diet, low-fat diet, or prudent diet after diagnosis is associated with a decreased risk of all-cause mortality in BCS. Conversely, adherence to a Western diet before and after diagnosis, is detrimental in terms of overall mortality risk and death from other causes among BCS . FollowiAccordingly, a large prospective cohort study including 2295 postmenopausal women, the Women’s Health Initiative (WHI), with over 12 years of follow-up showed that adherence to a lower quality diet after BC diagnosis, as assessed through the Healthy Eating Index (HEI)-2010 score, increased the risk of death from BC . Instead, a better quality diet (≥15% increase in HEI-2010 score) was non-significantly associated with a lower risk of death, irrespective of change in BMI . p for trend = 0.004, and HR 0.84; 95% CI, 0.72–0.97; p for trend = 0.001, respectively], but not related to BC-specific mortality. Total fruit consumption was not related to BC-specific or all-cause mortality. Greater intake of green leafy and cruciferous vegetables was associated with lower all-cause mortality, while higher fruit juice consumption, except for orange juice, which was associated with poorer BC-specific and all-cause survival [Another large-scale study enrolled 8927 women with stage I–III breast cancer in the Nurses’ Health Study  and NHSII (1991–2011 follow-up) and assessed the associations of post-diagnostic fruit and vegetable consumption with BC-specific and all-cause mortality. The total fruit and vegetable and total vegetable consumption was related to lower all-cause [highest vs. lower quintile HR 0.82; 95% confidence interval (CI), 0.71–0.94; In addition, higher adherence to healthy and anti-inflammatory dietary patterns, such as a Mediterranean diet, is associated to a higher quality of life ; howeverp for trend <0.0001) than in the lowest tertile. Higher DII scores increased risk of (ER)+/(PR)+ breast cancer regardless of menopausal status , but the risk was not increased for ER-/PR- status [To provide insight into the dietary inflammatory index (DII), a study assessed the risk for cancer recurrence and overall mortality after surgery for invasive BC finding significantly higher recurrence  and higher overall mortality  in patients with higher DII scores after adjusting for confounding factors, such as age (<50 years), premenopausal status, BMI (≥25 kg/m²), hormone receptor HR+, tumor size (>2 cm), and presence of lymph node metastasis . A Korea- status . A low-fat dietary pattern  implemented on a long-term follow-up of 16.1 years was also able to reduce the incidence of deaths after BC in the intervention group compared to the usual diet . A Danish study following up 1965 women for 7 years after BC diagnosis found that pre-diagnostic wholegrain intake of oatmeal/muesli was associated with lower all-cause mortality, while post-diagnostic intake of rye bread was associated with higher breast cancer specific mortality; moreover, a high intake of cheese was associated with a higher recurrence rate . Another study observed the food intake trajectory for 2 years after BC diagnosis. Findings showed only a slight increase in fruit and vegetables and decreased alcohol intake, while total fat intake did not change post-diagnosis, with 45% of survivors maintaining a high-fat diet  . DietaryDietary patterns characterized by lower post-prandial glucose and insulin responses, those with low glycemic index (GI) and low glycemic load (GL), reflecting quality and quantity of carbohydrate intake, could help explain the reduction of mortality and recurrence risk in BCS. Mechanisms influencing BC development and recurrence include hyperglycemia, hyperinsulinemia, high insulin-like growth factor (IGF)-1, high circulating estrogen, inflammation, and impaired cellular differentiation/apoptosis . VisceraOne meta-analysis of prospective cohort studies showed only a modest association between a dietary pattern with high GI or GL and the risk of breast cancer, even after adjustment for BMI, physical activity, and other lifestyle factors and for menopausal status and estrogen receptor status of the tumor . Anotherp trend = 0.03) with a positive association only among overweight women , but no association in women with BMI < 25 kg/m2 [A study on Mexican women concluded that total carbohydrate intake was associated with an increased risk of breast cancer among premenopausal women , whereas in contrast, the risk of postmenopausal BC is increased for those with a body weight that is heavier than normal and those who gain weight in adulthood [In postmenopausal women with obesity, the higher risk of estrogen receptor (ER)-positive BC is known, but similarly, increased adiposity in postmenopausal women with a normal body mass index also pose them at double risk of invasive BC . The group in the highest quartiles of trunk fat mass showed higher circulating levels of insulin, C-reactive protein, interleukin-6, leptin, and triglycerides, whereas levels of high-density lipoprotein cholesterol and sex hormone-binding globulin were lower ,40,41,42Nevertheless, overweight and obesity are considered a risk factor for BC development, recurrence, and mortality, irrespective of hormone-receptor (HR) status. Women with obesity have a higher risk of developing triple-negative breast cancer (TNBC) anyway , a subtyA critical review suggests that nutritional therapy in BC patients should be based on the patients’ nutritional status, dietary habits, schedule, activities, and cultural preferences, to meet compliance and dietary adequacy for the improvement of overall health and prognosis . IncreasCirculating levels of IGFs and their binding proteins have been associated with BC risk, but evidence related to BC prognosis is still limited and inconsistent . The IGFAlthough the presence of obesity increases the risk of cancer recurrence and death, its causative role is still not clear, and weight loss interventions deserve more research to clarify if benefits can be achieved through a combination of dietary intervention and aerobic exercise or by one intervention alone. A clinical study analyzing tumor markers , gene expression on surgical specimens, blood cytokines, growth and metabolic factors found unclear benefits on tumor biology after pre-surgical caloric restriction in women undergoing a two-arm, single-blinded, randomized controlled and successful weight-loss trial . The samIn order to shed some light on the link between BC and excess fat, in women with overweight or obesity, a study identified novel microRNAs associated to BMI and weight loss that could contribute to the development of cancer, identifying multiple pathways associated with cancer, and highlighting potential mechanisms explaining the link between BMI and increased cancer risk . Among ap-value 0.01, and 2.31 CI 1.42–3.74 for net endogenous acid production NEAP, p-value 0.05) [Another study worth mentioning is that which investigated the association between dietary acid load and inflammation as well as hyperglycemia in BCS, where a positive association was found in women with highest intakes of dietary acid load who showed a 30–33% increase in CRP and a 6–9% increase in HbA1c levels. This finding could provide a possible link explaining how dietary habits affect both systemic inflammation and hyperglycemia, a well-known risk factor for recurrence and reduction in both overall and disease-free survival in BCS . The samue 0.05) .Weight gain is common after BC diagnosis, and weight gain during treatment decreases the survival rate and increases the risk of recurrence ,32. MultWeight management programs in BCS have been effective in reducing weight, body fat, waist, and hip circumference ,19,20, aAlthough the purpose of this review was to focus on dietary patterns, WCRF underscores the importance of a healthy lifestyle comprised of behavioral components such as physical activity and smoking . AccordiPrograms to induce weight loss in women after BC diagnosis have been proven to be efficient and feasible in improving anthropometric parameters, quality of life outcomes, and circulating biomarkers ,20,50. STogether with metabolic risk and insulin resistance improvements, leptin and adiponectin decrease were correlated with a decrease in BMI and increase in cardiorespiratory fitness . p < 0.01) and have increased total energy [Interestingly, a longitudinal study followed BCS in five survivorship periods since diagnosis  and found that non-drinker and non-smoker BCS slightly increased after diagnosis, and only in the recent survivorship period were BCS significantly more physically active and they consumed more fruit, but were less likely to be classified in the healthy weight range  patients undergoing hormonal or immune therapy to prevent cancer recurrence, while TNBC patients are not always eligible for such protocols. Therefore, this may cause another interpretation bias, and may explain, at least in part, the worse outcomes in patients with TNBC. In the end, the small amount of reports included in the review does not allow to clearly select a specific diet to recommend in BCS and to respond to the main aim of the study. Nevertheless, this limit underlies the importance of the work itself as a trigger for more specific research on nutritional therapy for the prevention of recurrence in BCS, as well as in other cancer sites.To date, studies on BCS are not enough to suggest which is the best diet to prevent recurrence of cancers of the breast and other sites after a cancer diagnosis. Nevertheless, Mediterranean  and otheObesity and overweight, lower rates of physical activity, and hormone receptor-status subtype are associated with poorer BC treatment outcomes. To date, there is a lack of evidence to suggest which dietary pattern is the best approach for weight management in BCS . In the


We conducted a retrospective cohort study to evaluate the temporal pattern of incidence of chronic conditions after developing breast cancer using a population-based national registry. We selected 84,969 women with newly diagnosed breast cancer between 2002 and 2016 and a 1:10 sample of age-matched non-breast cancer controls . The main study exposure was incident breast cancer, considered as a time-varying exposure. The outcomes were incident cases of leukemia, endometrial cancer, myeloma, cardiomyopathy, osteoporosis, end stage renal disease (ESRD), pulmonary fibrosis, hypothyroidism, type 2 diabetes, hypertension and hyperlipidemia. The development of breast cancer was associated with a significantly increased risk of all outcomes analyzed except for ESRD and hypertension. The fully-adjusted risks of leukemia , cardiomyopathy , endometrial cancer , hypothyroidism , pulmonary fibrosis , and hyperlipidemia  remained significantly elevated after more than 5 years since diagnosis. Optimal care for breast cancer survivors requires close collaboration between oncologists and allied health care professionals to identify and manage the long-term morbidity and mortality associated with these chronic conditions. Thanks to early diagnosis and medical advances, the 5-year survival of breast cancer patients has increased from 79.2% in 1993–1995 to 93.2% in 2013–20172. Due to the high incidence and high survival, breast cancer survivors represent one of the largest groups of cancer survivors. Breast cancer survivors, however, are at increased risk of developing new chronic conditions. Women with breast cancer had a higher risk of developing cardiovascular disease3, osteopenia, osteoporosis, and bone fractures4, hypothyroidism5 and second primary malignancies including acute myeloid leukemia, multiple myeloma, and acute lymphoblastic leukemia or lymphocytic lymphoma7.Breast cancer is the most common malignancy in women, with an average lifetime risk of 1 in 88.Previous studies have not provided detailed descriptions of the temporal pattern of chronic disease incidence after breast cancer, partly due to limited sample sizes and to limited follow up times. Furthermore, prior studies were usually limited by a lack of information on risk factor levels prior to the development of breast cancer, making it difficult to separate the specific contribution of breast cancer or breast cancer-related therapies to the development of chronic diseaseUnderstanding the pattern of chronic disease incidence after breast cancer can help plan preventive services and clinical management of cancer survivors, and may provide leads into the etiology of chronic disease in this patient group. We thus studied a large cohort of women without a history of cancer at baseline to evaluate the temporal pattern of incidence of chronic diseases after developing breast cancer.Compared to participants who developed breast cancer , non-breast cancer controls  had similar characteristics at the time of the baseline health screening exam , cardiomyopathy , endometrial cancer , hypothyroidism , pulmonary fibrosis , and hyperlipidemia  remained significantly elevated , radiotherapy , and radiotherapy, chemotherapy, and hormone therapy   have also been reported in early-stage breast cancer patients treated with chemotherapy and radiation therapy17. In fact, breast cancer is the most frequent solid tumor linked to t-MNs, accounting for 70% of t-MNs among women18.In our study, breast cancer patients had increased risk of leukemia and multiple myeloma compared to women without breast cancer. The increased risk for leukemia was evident shortly after breast cancer development and remained elevated even 5 years after diagnosis. Genetic studies have identified somatic mutations in leukemia-related genes present in tumor-infiltrating leukocytes (TILeuks) in cases of early breast cancer who underwent chemotherapy20, and generating reactive oxygen species, which damage DNA, proteins, and lipids, including the mitochondrial membrane21. Besides chemotherapy, radiation therapy could also affect the incidence of cardiomyopathy. Although more modern radiation therapy techniques may have attenuated the risk or cardiac toxicity, the long-term safety of radiation therapy for breast cancer remains uncertain22.The increased risk of cardiomyopathy was also evident shortly after breast cancer development and remained elevated throughout the rest of follow-up. Cardiomyopathy is a well-known side effect of anthracyclines. Anthracyclines induce cardiomyocyte death by interacting with DNA, binding to topoisomerase IIβ23. For example, tamoxifen promotes cell proliferation in the endometrium and migration and invasion of endometrial cancer cells24, which may explain an increased risk of endometrial lesions, including hyperplasia, polyps, carcinomas, and sarcoma25. In fact, in a meta-analysis of 20 trials of 21,457 early breast cancer patients, the risk of endometrial cancer increased by 2.4 times in the tamoxifen group compared to the control group26. Considering the increased risk over time, breast cancer survivors may need to be referred for endometrial cancer screening, especially patients who received hormone therapy.Incident breast cancer patients had about 2 times higher risk of developing endometrial cancer during early survivorship (< 3 years after diagnosis), and this risk increased in later survivorship (> 3 year). Endometrial cancer and breast cancer share common lifestyle risk factors such as smoking, obesity, diabetes, physical inactivity, and reproductive factors such as early age at menarche, late-onset menopause, and nulliparity. The increase in risk during survivorship may be also due to long-term exposure to unopposed estrogens27. The thyroid gland is highly sensitive to radiation, which may damage its blood vessels and parenchymal cells, trigger autoimmune reactions, and cause fibrosis28. Radiation-induced thyroid disease most commonly presents as hypothyroidism28. However, chemotherapy or hormone therapy-related hypothyroidism in breast cancer patients, is less well understood. Further studies are needed to understand the impact of chemotherapy and hormone on the incidence of thyroid disorders in breast cancer survivors.The risk of hypothyroidism was evident right after development of breast cancer and the remained significantly elevated even 5 years after diagnosis regardless of treatment. In previous studies, breast cancer patients who received radiation therapy were at higher risk of developing hypothyroidism compared to individuals without cancer29, and the changes in lipid levels after breast cancer correlate with changes in menstruation29 due to chemotherapy or hormone therapy. Also, adjuvant chemotherapy was associated with significant changes in the lipid profile30. Aromatase inhibitors, for instance, block the conversion of androgens to estrogen and affect the lipid profile31. An analysis of pooled data from seven clinical trials  demonstrated that longer duration of aromatase inhibitor use was associated with a statistically significant increase in the odds of hypercholesterolemia as compared with tamoxifen31.We also observed a sustained risk of hyperlipidemia in breast cancer survivors over time. Lipid metabolism is associated with sex hormonesSeveral limitations need to be considered in the interpretation of our findings. First, due to the nature of the data, we did not have information on cancer stage, and we had only limited information on breast cancer treatments and disease management based on claims. As a consequence, we could not establish the precise mechanisms responsible for increased chronic disease risk. Second, patients who develop cancer have more contact with the health care system which may induce surveillance bias. However, we excluded participants with comorbidities after a baseline screening, as well as comorbidities that were identified very early after cancer development. Lastly, we were not able to evaluate the independent contribution of each treatment modality as patients commonly received treatment combinations.32, incorporation of surveillance and prevention strategies would be necessary to manage the long-term morbidity and mortality associated with these chronic conditions in breast cancer patients. Further research also is required to define optimal strategies for prevention, early detection, and management of chronic conditions after breast cancer.In conclusion, breast cancer development was associated with an increased risk of subsequent development of multiple chronic conditions, and the risk remained significantly elevated after more than 5 years since diagnosis. Considering that these chronic diseases may have a substantial impact on the quality of life and survival of breast cancer survivorsWe conducted a retrospective cohort study using a population-based national registry. Korea has a universal single-payer national health system, and the National Health Insurance Service (NHIS) maintains national records of all covered inpatient and outpatient visits, procedures, and prescriptions. The NHIS also includes information on risk factor levels for common chronic conditions collected in routine health screening exams supported by the national health system.Among all Korean women age 20 and older between 2002 and 2016 and without a prior history of cancer  as of 2002, we selected all women with an incident case of breast cancer (ICD-10 code C50) between January 1st 2003 and December 31st, 2016 . Among the eligible participants, we excluded 203,323 participants who had any cancer (ICD-10 code C) prior to the health screening exam as the health screening exam constitutes the baseline for the current study. The final sample size was 1,142,643 . The Institutional Review Board (IRB) of the Samsung Medical Center approved (SMC-201912064) this study and waived the requirement for informed consent as we used only de-identified data. This study was performed in accordance with relevant guidelines/regulations of our institutions.In Korea, the Industrial Safety and Health Law also requires annual or biennial health screening exams of all employees that include assessment of cardiovascular and diabetes risk factors. These exams are covered by the NHIS and provided free of charge. Approximately 72% of eligible beneficiaries receive the screening exams34. Thus, potential strengths of this data set were that we had almost all the patient with cancer as well as their follow up until they death or end date of the data set. NHIS claims for inpatient and outpatient visits, procedures, and prescriptions were coded using ICD-10 and the Korean Drug and Anatomical Therapeutic Chemical codes35. NHIS routinely audits the claims, and the data are considered reliable and have used in numerous peer-reviewed publications36. According to a recent study, definitions of cancer diagnosis in our study is an accurate and valid method to identify cancer incidence using health insurance claim data37. Definitions showed over 90% sensitivity in identifying patients with central cancer registration. For breast cancer, it had 97.9% sensitivity .The NHIS data comprises five databases on insurance eligibility, medical treatments, medical care institutions, general health screening exams and cancer screening exam. The medical treatments database contains information on all claims on inpatient hospitalizations, outpatient visits, treatments and procedures in all clinical care use from primary care clinics to tertiary hospitals reimbursed by the NHIS, including details of diseases and prescriptionsThe main study exposure was the development of incident breast cancer (ICD-10 code C50) considered as a time-varying exposure. Breast cancer was confirmed after the presence of a C50 code in more than 3 claims within a year or in an inpatient hospitalization claim. Treatments for breast cancer were identified from claims filled within 1 year after breast cancer diagnosis and used to classify patients as receiving only surgery or surgery plus chemotherapy, radiation therapy, or hormone treatment.38. According to a recent systematic review, cure or control of cancer leads to a higher risk and earlier onset of multiple ageing-associated health problems resulting in chronic diseases12. Cancer treatment contribute to the ageing phenotypes of decreased resilience, geriatric syndromes and predisposition to age-related chronic diseases, including telomere attrition, cellular senescence, stem and progenitor cell dysfunction, macromolecular DNA damage and epigenetic alterations12. For this study, we initially included leukemia, endometrial cancer, myeloma, cardiomyopathy, osteoporosis, end stage renal disease (ESRD), pulmonary fibrosis, hair loss, muscular weakness, frailty, attention deficits, infertility, and hypothyroidism that breast cancer patients would experience due to premature of ageing due to breast cancer treatment. We then added hypertension, hyperlipidemia, and diabetes which could be important mediator or shared risk factors for the chronic diseases. However, we had to exclude hair loss, muscular weakness, frailty, attention deficits, and infertility as these conditions are difficult to define or to identify using claims data. Finally, we included leukemia, endometrial cancer, myeloma, cardiomyopathy, osteoporosis, end stage renal disease (ESRD), pulmonary fibrosis, hypothyroidism, type 2 diabetes, hypertension and hyperlipidemia. Leukemia (ICD-10 codes C91-C95), endometrial cancer (C54.1) and myeloma (C90) were confirmed after the presence of the same C code in more than 3 claims within a year or in an inpatient hospitalization claim39. Cardiomyopathy was defined as an inpatient hospitalization with a code I40-I4340. Osteoporosis was defined as the presence of codes M80-M82 in at least 2 claims with a bone mineral density examination code (HC341-HC345) within a year39. Hypothyroidism was defined as the presence of code E03 in 3 claims within a year or in an inpatient hospitalization claim41. Pulmonary fibrosis was defined as the presence of code E03 in more than 2 claims within a year42. ESRD was defined as a code N18, N19, Z49, Z940, Z992, or code V001, V003 with a hemodialysis code O7020, O9991, peritoneal dialysis code O7075, or kidney transplantation code R3280 in a claim43. Hypertension , type 2 diabetes (E11–E14) and hyperlipidemia (E78) were defined as the presence of identical disease codes in at least two claims within a year, or the presence of a disease code claim and a code for a medication to control the disease in a prescription claim within a year. Outcomes were consider to occur at the time of the first claim with the diagnostic or medication code12.The study outcomes were the development of chronic diseases for which prior research indicates that breast cancer patients may be at increased risk, including common consequences of cancer treatments2), normal (18.5–< 23 kg/m2), overweight (23–< 25 kg/m2), obese (≥ 25 kg/m2), and unknown. In addition, age at menarche and menopause status were obtained from the cancer screening exam. In terms of menopause status, we used menopause age from all of the screening during the study period and then coded whether the patients were pre- or post-menopause at the initial breast cancer screening comparing the current age and menopause age.Age and income level were obtained from the insurance eligibility database. Smoking habits , drinking habit s, physical activity, height, and weight were obtained from the health screening exam database. Body mass index (BMI) was calculated and categorized as underweight  and were followed-up until the development of a study endpoint, death, or the end of the study period . The study endpoints were the development of leukemia, endometrial cancer, myeloma, cardiomyopathy, osteoporosis, hypothyroidism, pulmonary fibrosis, ESRD, type 2 diabetes, hypertension, and hyperlipidemia. Each endpoint was analyzed separately, and for each end point analysis we included only participants who had not experienced the endpoint prior to the first screening exam. The number of participants included in the analysis will thus be different for each endpoint.44. Since patients would receive various exam prior to surgery, to reduce the potential impact of surveillance bias, we considered that outcomes occurring in the first 31 days after a diagnosis of breast cancer corresponded to unexposed person-time.The study exposure was breast cancer development, considered as a time-varying variable. Participants who developed breast cancer contributed person-time to the exposed group from the time of breast cancer development. Unexposed person-time was contributed by participants who did not develop breast cancer and by participants who developed event prior to breast cancer development  with 95% confidence intervals (CI) for developing each chronic disease using a proportional hazards regression model with age as the time scale. To estimate age-dependent effects, we conducted time-varying analyses according to the split-age interval. Participants were assigned to the < 50 years age group until they reached the age of 50 years and to the age ≥ 50 years age group.Follow-up time was classified as < 1, 1–< 3, 3–< 5, and ≥ 5 years from the time of breast cancer diagnosis. Because of the substantial overlap of treatment modalities , we used non-exclusive categories in the analysis of treatment modalities .To account for potential confounding factors at the health screening exam (baseline), we adjusted for body mass index, alcohol intake, moderate-vigorous physical activity, smoking status, income percentile, and for the presence of other comorbid conditions included in this study at the time of the health screening exam. When the variable had missing value, we considered as “none” for variables from the claim. On the other hand, for the variables from questionnaire in health screening data, we coded as missing category. Thus we adjusted for BMI, alcohol intake, physical activity, smoking status, income percentile, as well as for the baseline presence of comorbid conditions other than the corresponding outcome.45, with similar findings (not shown). We examined the proportional hazards assumption. All analyses were performed using STATA version 14 .To account for competing risks due to mortality, we fitted a proportional subdistribution hazards regression model with death as the competing eventThe Institutional Review Board (IRB) of the Samsung Medical Center approved this study (SMC-201912064) and waived the requirement for informed consent as we used only de-identified data.Supplementary Figure 1.Supplementary Figure 2.Supplementary Tables.


Despite a modest association between tobacco smoking and breast cancer risk reported by recent epidemiological studies, it is still equivocal whether smoking is causally related to breast cancer risk.We applied Mendelian randomisation (MR) to evaluate a potential causal effect of cigarette smoking on breast cancer risk. Both individual-level data as well as summary statistics for 164 single-nucleotide polymorphisms (SNPs) reported in genome-wide association studies of lifetime smoking index (LSI) or cigarette per day (CPD) were used to obtain MR effect estimates. Data from 108,420 invasive breast cancer cases and 87,681 controls were used for the LSI analysis and for the CPD analysis conducted among ever-smokers from 26,147 cancer cases and 26,072 controls. Sensitivity analyses were conducted to address pleiotropy.P = 0.11 × 10–2), but there was no evidence of association for genetically predicted CPD . The sensitivity analyses yielded similar results and showed no strong evidence of pleiotropic effect.Genetically predicted LSI was associated with increased breast cancer risk (OR 1.18 per SD, 95% CI: 1.07–1.30, Our MR study provides supportive evidence for a potential causal association with breast cancer risk for lifetime smoking exposure but not cigarettes per day among smokers. It is however difficult to establish causation based on these observational studies.Based on the experimental and epidemiologic findings, evidence is insufficient to establish a causal relationship between tobacco smoking and breast cancer risk.14 MR uses genetic variants such as single-nucleotide polymorphisms (SNPs) associated with an exposure of interest as an instrumental variable (IV), which is robust if three assumptions are met: (1) the genetic variants are casually associated with the exposure, (2) the variants are not associated with known or potential confounders for the exposure–outcome relationships and (3) the variants are associated with outcome only via the exposure of interest and not through other pathways.16 Given the unclear causal nature of the findings in observational studies, we conducted a MR analysis to investigate the association between smoking traits and breast cancer risk.Mendelian randomisation (MR) has been increasingly used to strengthen causal inference in observational studies and under certain assumptions is less vulnerable to residual confounding, reverse causation and selection bias.https://epi.grants.cancer.gov/oncoarray/)17 and iCOGS arrays in 40,178 cases and 35,314 controls (http://ccge.medschl.cam.ac.uk/research/consortia/icogs/).18 Genotype data were imputed based on the 1000 Genomes project Phase 3 as the reference panel using the programme IMPUTE2.19 SNPs with high imputation quality (imputation r2 > 0.5) were included. Overlapping participants between datasets were excluded from the iCOGS dataset as the OncoArray provides a better genomic coverage than the iCOGS array. Demographic and epidemiologic data were harmonised across BCAC sites based on a standardised protocol and derived with respect to a reference date, which was date at diagnosis for cases and date at interview for controls. For controls and cases from the nested case-control studies, data from the baseline interview were considered, or if available, follow-up information. Chosen characteristics of the two datasets, including self-reported smoking behaviours  are shown in Supplementary Table We used data from 81 studies participating in the Breast Cancer Association Consortium (BCAC), including 108,420 cases and 87,681 controls of European ancestry. Genotyping was performed using two custom-made genotyping arrays: OncoArray in 68,242 invasive breast cancer cases and 52,367 controls  of European ancestry from the UK biobank.20 The genetic scores of the two smoking behaviour-related traits were reported to be associated with significantly higher risks of lung cancer.22Exposure variables were selected based on the availability of associated genetic variants to reflect smoking exposure. We included two quantitative smoking behaviour-related traits, cigarettes per day  and lifetime smoking index .P ≤ 5 × 10−8) and had a minor allele frequency (MAF) above or equal 1%. For each behaviour phenotype, we filtered the list of behaviour-associated SNPs so that the remaining SNPs were not in linkage disequilibrium (LD) (r2 > 0.1). For CPD, the SNP with lowest P value (rs10519203) of the correlated SNPs  was retained. One SNP (rs4886550) was not available in our data and without any proxy SNPs . Given that alcohol consumption is a recognised confounder of the association between smoking and breast cancer risk,25 we excluded nine SNPs  correlated with any alcohol consumption-associated SNPs (r2 > 0.1) from recent large-scale GWAS .21 After exclusions, we included a total of 164 variants associated with one of the smoking traits; 44 and 120 variants, respectively, for CPD and LSI  r > 0.1. FR2 of 0.0109 for CPD and R2 of 0.0036 for LSI, which correspond to the variance in each smoking behaviour explained by the SNPs used for this analysis. Power calculations were performed using an online tool available at http://cnsgenomics.com/shiny/mRnd/.26 Detailed power calculations for all outcomes  to detect different odd ratios are shown in Supplementary Table Power calculations were conducted to estimate the magnitude of effects detectable with our study size assuming 5% α level and an i) (ranging from 0 to 2) for each SNP weighted by the β-coefficient βgx for the effect of the genetic variant (g) related to the smoking quality or/and duration  (x) (Supplementary Table 21 The wPGSs of LSI was weakly correlated with wPGSs of CPD (0.17 in iCOGS and 0.03 in OncoArray) in ever-smokers. Analysis of LSI was conducted using all participants (including ever- and never-smokers), whereas that of CPD was performed solely in ever-smokers, and based on 26,147 cases  and 26,072 controls . These inclusion criteria correspond to those used in the GWAS studies that identified the SNPs for the smoking traits.21For our primary analysis, we generated weighted polygenic scores (wPGSs) using individual-level data of BCAC participants as follow: wPGS =entclass1pt{minima27 In order to assess if the genetic instrument is independent of established risk factors for breast cancer, associations of wPGSs with selected breast cancer risk factors were assessed by linear regression for continuous variables and logistic regression for categorical variables  was adjusted for age (continuous), principal components (PCs) of genetic ancestry  and study site, as previously described.Stratified analysis was performed to assess potential differences in associations with breast cancer risk by menopausal status  adjusting for age, study site and top ten PCs. Heterogeneity was tested employing the likelihood ratio test (LRT) for evaluating the multiplicative interaction terms in nested models. Polytomous regression was used to estimate the association according to oestrogen receptor (ER) status.Scaling was applied to convert the wPGSs for CPD into meaningful units through dividing them by linear regression coefficients of self-reported CPD (0.35 per pack of cigarettes per day). The regression coefficient of CPD was derived from a meta-analysis of iCOGS and OncoArray data on smoking behaviours among 26,072 among ever-smoker controls .28 MR Egger,29 weighted median,30 weighted mode,31 and robust adjusted profile score (RAPS).32 Each of these methods makes slightly different assumptions about the nature of pleiotropy and therefore a roughly consistent point estimate across the multiple methods provides the strongest evidence of causal inference.28 The IVW method was implemented since the instruments consisted of multiple SNPs.33 Multivariable MR methods34 were conducted also using summary association data from GWASs of alcohol consumption (drinks per week),21 body mass index (BMI) among females35 and education attainment.36 To produce valid results, the IVW method requires that all instruments are associated with the exposure of interest (relevance assumption), but neither directly with the outcome of interest  nor any confounders of the relationship between the exposure and the outcome (independence assumption).37 The intercept from MR-Egger regression is a statistical test for horizontal pleiotropy, whereas the slope can be interpreted as the smoking behaviour effect on breast cancer adjusted for horizontal pleiotropy.29 This method assumes however that the pleiotropic effects are independent of the instrument strength (InSIDE assumption). The weighted median estimator provides a valid causal estimate when at least half of the instruments are valid.30 The estimate from the weighted-mode analysis is valid when the largest group of instruments with consistent MR estimates is valid.31 MR-RAPS test extends the basic IVW random-effects approach by making the weight each variant receives in the analysis a function of the causal effect and the precision of the SNP-exposure association.32 The MR pleiotropy residual sum and outlier test (MR-PRESSO) was also implemented to identify outlying genetic variants and analyses were re-run after excluding these variants.38Five different two-sample MR methods using summary association data were applied: inverse-variance weighted (IVW),All two-sample MR analyses using summary association data were performed with respect to three cancer susceptibility phenotypes: overall breast cancer  as well as oestrogen receptor (ER)-positive  and ER-negative tumours . Due to the nature of summary-level data, the analyses of both LSI and CPD were conducted using all samples regardless of smoking status.R version 3.4.3 was used to conduct analyses. R package “Mendelian randomisation”, “mr_raps” and “MR-PRESSO” were used for two-sample MR analysis. All tests were considered at the 0.05 level of significance.P = 0.11 × 10–2) whereas little evidence was found for an association between wPGSs for CPD and invasive breast cancer  after adjustment for age and study (Model 1) (Table P = 0.60 × 10−2) (Table P = 0.39). The association between wPGSs for CPD and invasive breast cancer did not change after adjustments.There was an association of wPGS for LSI with increased invasive breast cancer risk  Table . AdjustmThere was no evidence for effect heterogeneity of the associations of LSI and CPD with breast cancer risk according to ER status or menopausal status  and breast cancers according to ER status  .39 We conducted association analyses of wPGS of smoking initiation and smoking cessation with breast cancer risk (see Supplementary Note) and found no statically significant association for either smoking initiation  or smoking cessation  ,.02,13 a P = 0.84)  status, potential confounding by alcohol consumption. We conducted an association analysis between wPGS of age at smoking initiation and invasive breast cancer (see Supplementary Note). The result showed an inverse association but statistically nonsignificant with low precision . We found no clear evidence of association between genetically predicted alcohol consumption and invasive breast cancer . The association remained unchanged after adjusting for LSI .Despite epidemiological evidence indicating alcohol consumption as an established risk factor for breast cancer risk,13 we cannot exclude that the lack of association observed in the MR analysis particularly regarding CPD may be due to limited power. The unit for LSI is not scaled due to the nature of the phenotype. The reported order of magnitude for associations with LSI can therefore not be directly compared with the relative risk estimates for smoking from observational studies.Despite the relatively large sample size used for our analyses, weak statistical power to detect modest associations should be considered when interpreting the results. The power calculation shows that our study had 68% power to detect an OR of 1.20 per SD change in LSI but only around 9% power for an OR of 1.05 in combined dataset (iCOGS and OncoArray)  to outcome (breast cancer risk). It can make the association between smoking and breast cancer risk appear weaker by removing a part of the association that is attributable to smoking initiation.The genetic instrument for LSI allows for the use of the large entire sample to conduct MR analysis without stratifying on smoking status. The analyses for CPD were restricted to smokers by reason that the CPD-associated SNPs were identified among ever-smokers in the GWAS study,Another limitation is that our analysis was restricted to participants of European ancestry; therefore, our results may not apply to populations of other ethnicities. However, it reduces the potential bias caused by population stratification.In conclusion, this Mendelian randomisation analysis using both individual-level data and summary statistics supports a causal association between lifetime smoking exposure and breast cancer risk. Larger studies for MR analysis are warranted to address additional aspects of smoking behaviour.Supplementary Materials