Recent studies indicate that lifestyle factors in early life affect breast cancer risk. We therefore explored the association of high consumption of meat, milk, and whole grain products in adolescence and midlife, on breast cancer risk. We used data from the population based AGES-Reykjavik cohort (2002–2006), where 3,326 women with a mean age of 77 years (SD 6.0) participated. For food items and principal component derived dietary patterns we used Cox proportional models to calculate multivariate hazard ratios (HR) with 95% confidence intervals (95% CI). During a mean follow-up of 8.8 years, 97 women were diagnosed with breast cancer. For both adolescence and midlife, daily consumption of rye bread was positively associated with breast cancer . In contrast, persistent high consumption of oatmeal was negatively associated with breast cancer . No association was found for other food items or dietary patterns that included rye bread. High rye bread consumption in adolescence and midlife may increase risk of late-life breast cancer whilst persistent consumption of oatmeal may reduce the risk. This variation was observed to be strongest for the most common food items consumed at that time, or meat, rye, milk products, fish and fish oil [During adolescence the female mammary tissue undergoes extensive modeling or re-modeling. Consequently, researchers have hypothesized that breast tissue may be particularly susceptible for initiation of breast tumors during this period , 2. Therfish oil . These pfish oil , 7 as weIn the Nurses' Health Study, women in the highest quintile of red meat consumption in adolescence had significantly higher risk of breast cancer than women in the lowest quintile –10. A reFor this study we used data from the population based AGES-Reykjavik Study, which is derived from a population with considerable variation in dietary habits in adolescence. Using the same cohort, we have previously observed a preventive role of very high fish intake in adolescence and midlife for breast cancer  and alsoWe used data from the Age Gene Environment Susceptibility (AGES)—Reykjavik Cohort Study of the Icelandic Heart Association, a sub-cohort of the population based Reykjavik Study initiated in 1967 . The AGEAt study entry, the participants completed a food frequency questionnaire (FFQ) on diet in adolescence (between the ages of 14 to 19 years), in midlife (between the ages 40 to 50 years), and at study entry (late life). For this analysis we only use questions from the adolescent and midlife period.The FFQ was especially designed for this project and provides information on frequency of intake of 10 common foods and food groups consumed in adolescence and 11 in midlife. For both adolescence and midlife, these food groups were meat , fish , fish liver oil, blood or liver sausage, rye bread, oatmeal, potatoes, milk and milk products, fruits and vegetables . An addiTwo separate questions were asked regarding meat consumption. One included total consumption of meat and ground meat as a meal (hereafter referred to as meat). The other question  concerned intake of corned meat, corned meat sausage, or any kind of salted/smoked meat . Information on milk consumption included frequency of intake of milk and milk products (hereafter referred to as milk). Rye bread consumption was assessed by one question on intake of rye bread and flatbread made of rye (hereafter referred to as rye bread). For midlife, the question on oatmeal also included muesli, but will be referred to as oatmeal in both periods.For meat, milk, rye bread, oatmeal, and whole wheat bread, the frequency of consumption was classified into; 1) never, 2) less than once a week, 3) 1–2 times a week, 4) 3–4 times a week, 5) 5–6 times a week, 6) daily, and 7) more than once a day. For salted or smoked meat, the following response categories were: 1) never, 2) less than once a month, 3) 1–3 times a month, 4) 1–2 times a week 5) 3–6 times a week 6) daily or more often.For both adolescence and midlife, meat consumption was divided into two categories. low (2 times or less per week) and high (3 times or more per week). Consumption of salted or smoked meat was also divided into two categories, with low intake defined as 3 times per month or less and high as once per week or more. Consumption of milk, rye bread and whole wheat bread (midlife only) was divided into two categories (less than daily and daily or more). Consumption of oatmeal was divided into low (4 times a week or less) and high (5 times a week or more).The FFQ has been validated for midlife and late life , 34. In Information on potential confounders was mainly retrieved from a lifestyle questionnaire, completed at entry to the AGES-Reykjavik Study. We collected information on age at entry to the study (continuous), age at menarche (continuous), family history of breast cancer , education , use of hormonal replacement therapy , oral contraceptive , use of alcohol in midlife , and physical activity in adolescence and midlife . We also retrieved information on ever being pregnant (y/n) and age at first birth (continuous), and combined this information into one variable . From the Reykjavik Study we retrieved values on body mass index (BMI) and height from the midlife period (both continuous). Information on dietary covariates was retrieved from the AGES-FFQ .Selected dietary covariates on concurrent consumption included, milk, meat, salted and smoked meat, oatmeal, and rye bread, depending on the exposure (see cut offs above). We also used information on fish consumption, (≤ 2 portions p/w vs. >2–4 portions p/w vs. > 4portions p/w) and on salted and smoked fish (3 times a month or less vs. once a week or more).As residence dependent variance in food consumption existed during the adolescence period  we also We ascertained breast cancer diagnosis through the nationwide Icelandic Cancer Registry . Informacovariates assessment). Further adjustments were then made for education (3 categories), BMI (continuous) in midlife, age at first child birth (3 categories) and age at menarche (continuous).For both adolescence and midlife, Cox proportional hazard regression models were used to calculate hazard ratio (HR) and 95% confidence interval (95% CI) for incident breast cancer. For all exposures in the adolescent period the first model was adjusted for age (as a continuous variable) at entry. Depending on exposure, all other food items under study  plus information on fish and salted and smoked fish were then added simultaneously to the second model  and were therefore not included in our final statistical models.To assess the potential effects of longitudinal dietary habits on breast cancer risk we pooled consumption of each food item in adolescence and midlife into one variable with four categories; 1) low in both adolescence and midlife; 2) low in adolescence and high in midlife; 3) high in adolescence and low in midlife; and 4) high in both adolescence and midlife. For this analysis, the first category (low consumption in both periods) was used as a reference. Adjustments were made for same factors as described for the adolescent period. We also performed Spearman´s correlation test between consumption on food items under study in adolescence and midlife.To further examine whether the association observed for rye bread and oatmeal persisted when other food items commonly consumed were included we also used principal component analysis to identify dietary patterns from the AGES-FFQ, including all dietary data available. This method is data driven and forms new linear factors (dietary patterns) by reducing data dimension and grouping correlated variables (food intake). For each pattern, a new variable is created, ranking participants on their adherence to that particular pattern . Each vawww.spss.com) and R Core Team (2014). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria; (http://www.R-project.org/).For all statistical analysis we used SPSS software, version 24.0 .The mean age at study entry was 77.0 years and standard deviation (SD) 6.0. The mean follow-up time was 8.8 years (SD = 3.1). During that time, 97 women were diagnosed with breast cancer, with mean age at diagnosis 81.4 years (SD = 6.5). The dietary analyses were based on participants who provided information on diet in midlife and adolescence when entering the AGES-Reykjavik cohort and were free of breast cancer.trend = 0.043).We further divided rye bread consumption into three groups  and explored the association with breast cancer risk, where we found a significant trend across the groups, HR 1.0 (95% CI 0.5–2.0) and HR 1.7 (95% CI 0.9–3.2), respectively .Rye bread consumption in midlife was further divided into three groups . Compared with the group with the lowest consumption, the risk estimates for 3–6 times per week and daily or more were 1.4 (95% CI 0.8–2.4) and 2.3 (95% CI 1.3–4.1), respectively (PP = 0.001) and the lowest for meat consumption .trend = 0.07). No association was observed between breast cancer and meat, salted or smoked meat and milk.th century. High adherence to this pattern was not significantly associated with breast cancer risk (HR 1.3 95% CI 0.7–2.1). Borderline inverse association was observed for the highest adherence to a pattern high in consumption of fish, blood/liver sausage, oatmeal, fish oil, and milk in adolescence  (Ptrend = 0.049) (Four dietary patterns were extracted for the adolescent period. Factor loading coefficients for those patterns are presented in = 0.049) .Four dietary patterns were also extracted for the midlife period. No association was observed for any of those patterns, including the dietary pattern including rye bread consumption (data not shown).In this population based cohort, daily consumption of rye bread during both adolescence and midlife was positively associated with breast cancer. Conversely, we found reduced risk for breast cancer among women who consumed oatmeal persistently both in adolescence and midlife. However, no dietary pattern in either adolescence or midlife that included rye bread was significantly associated with breast cancer while a pattern in adolescence that represented fish, blood/liver sausage, oatmeal, fish oil, and milk seemed to be protective for breast cancer. We also observed borderline risk of breast cancer with high midlife consumption of salted or smoked meat. No association was found between high milk intake and breast cancer risk in either period.To the best of our knowledge, no study has specifically addressed adolescent consumption of rye bread, a common whole grain product in the Nordic countries, in relation to late-life breast cancer. A few studies have analyzed total adolescent consumption of lignans, a common phytoestrogen in whole grain cereals—such as rye, wheat, oats, and barley—but also in legumes, oilseeds, and various fruits and vegetables . A CanadThe few studies on total whole grain consumption in adults and breast cancer have either suggested a protective , 24 or nA Danish study  reportedProlonged exposure to rye bread might therefore possibly explain the observed risk found in our cohort. Rye bread is rich in lignans, which can be converted into enterolignans by the gut microbiome. Enterolignans have been suggested to enhance breast cancer risk reduction , 39, 40.In contrast to our results on rye bread, frequent long-term consumption of oatmeal was found to be protective against breast cancer. Similar to rye, yet containing only half the amount of phytoestrogen , oatmealA major strength of our study is the prospective design and the well-established population-based AGES cohort with its extensive covariate information. The record linkage to the nationwide Cancer Registry of Iceland ensures detailed and valid assessment of the outcome with a virtually complete follow-up , where aIn conclusion, our results suggest that rye bread consumption in both adolescence and midlife is associated with increased risk of breast cancer diagnosed late in life. Conversely, persistent high consumption of oatmeal in adolescence and midlife was associated with decreased risk. Collectively, these data suggest that dietary exposure during both adolescence and midlife period might be critical for breast cancer development in older women. These associations need to be confirmed in future studies, and our findings also call for further studies on potential mechanisms involved.S1 Table(DOCX)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.


MDM4 amplification has been observed in several tumor forms. A polymorphism  in the MDM4 3′ untranslated region has been reported to create a target site for hsa‐miR‐191, resulting in decreased MDM4 mRNA levels. In this population‐based case–control study, we examined the potential association between MDM4 SNP34091, alone and in combination with the MDM2 SNP309T>G (rs2279744), and the risk of breast‐, colon‐, lung‐, and prostate cancer in Norway. SNP34091 was genotyped in 7,079 cancer patients as well as in 3,747 gender‐ and age‐matched healthy controls. MDM4 SNP34091C was not associated with risk for any of the tumor forms examined, except for a marginally significant association with reduced risk for breast cancer in a recessive model (OR = 0.77: 95% CI = 0.59–0.99). Stratifying according to MDM2 SNP309 status, we observed a reduced risk for breast cancer related to MDM4 SNP34091CC among individuals harboring the MDM2 SNP309GG genotype . We conclude, MDM4 SNP34091 status to be associated with reduced risk of breast cancer, in particular in individuals carrying the MDM2 SNP309GG genotype, but not to be associated with either lung‐, colon‐ or prostate cancer.The MDM4 protein plays an important part in the negative regulation of the tumor suppressor p53 through its interaction with MDM2. In line with this,  MDM2, and its homolog MDM4, acting in concert MDM2 and MDM2 downregulates p53 MDM4 gene has been found amplified in malignant gliomas with no TP53 mutations or MDM2 amplifications The tumor suppressor p53 plays a pivotal role in many physiological processes, including metabolism and maintenance of genomic stability. In order to allow normal cell proliferation and to maintain cell viability during absence of stress signals, the activity of p53 is kept under strict control, predominantly by the protein product of the murine double minute 2 gene, MDM2 SNP309T>G (rs2279744) and SNP285G>C (rs117039649) both affect MDM2 transcription, MDM4 SNP34091A>C (rs4245739) has been found to affect MDM4 mRNA stability and protein levels MDM4, and was found to create a functional target site for hsa‐miR‐191 and hsa‐miR‐887. Both miRs bind to the MDM4 SNP34091 C‐allele with higher affinity than to the MDM4 SNP34091 A‐allele, leading to miR‐mediated decrease in MDM4 protein levels in cells carrying the MDM4 SNP34091C variant Single‐nucleotide polymorphisms (SNP) affecting the levels of both MDM2 and MDM4 have been reported 85G>C rs1039649 bo85G>C rs1039649 bo309T>G rs79744 andincreased risk for estrogen receptor negative, and in particular, triple negative breast cancer Contrasting these results, genome wide association studies (GWAS) reported the C allele to be associated with an MDM4 SNP34091 status on the risk of cancer of the breast, lung, prostate, and colon in a large population‐based cohort of Caucasian descent.In this study, we assessed the impact of MDM4 SNP34091A>C by analyzing the four major cancer forms; breast , lung , colon , and prostate . On the basis of previously published allele frequencies in healthy controls and breast cancer cases From the population‐based Cohort of Norway (CONOR) study MDM4 SNP34091 status using a custom LightSNiP assay  on a LightCycler 480 II instrument . The reactions were performed in a final reaction volume of 10 μL, containing 1 μL LightCycler®FastStart DNA Master HybProbe mix (Roche Diagnostics), 0.5 μL LightSNiP mix (TIB MOLBIOL), 3 mmol/L MgCl2 and 10–50 ng DNA. The thermocycling and melting curve conditions were as follows: 10 min initial denaturation/activation at 95°C, followed by 45 cycles of denaturation at 95°C for 10 sec, annealing for 10 sec at 60°C and elongation at 72°C for 15 sec. Subsequent to the thermocycling amplification the high‐resolution melting (HRM) step was initiated with a denaturation step at 95°C for 30 sec, followed by melting from 40°C to 75°C with a ramp rate of 0.19°C/sec and finally a cooling step at 40°C for 30 sec. The HRM curve profiles were analyzed by the Melt Curve Genotyping software (version 1.5) on the LightCycler® 480 II instrument (Roche Diagnostics).All samples were genotyped for Potential deviations from Hardy–Weinberg equilibrium were assessed by calculating the expected genotype distribution based on the observed allele frequencies and comparing the output with the observed genotype distribution using Chi‐square tests.MDM4 SNP34091 and the risk of any of the cancer types tested as well as cancer risk within different subgroups were estimated by calculating Odds Ratios (OR) with 95% confidence intervals (CI) and logistic regression adjusting for sex and age. In addition, for colon‐ and lung cancer, overall calculations were performed including both genders using the Mantel–Haenszel test (sex adjusted).Potential associations between P‐values are given as two‐sided.All statistical analyses were performed using the IBM SPSS 22 software package  and Stata 13.0 for Windows . All MDM4 SNP34091 status. Among the healthy individuals, the percentages harboring the three different genotypes  were recorded to be 54.5%, 38.4%, and 7.1%, respectively. The genotype frequencies were found to be in Hardy–Weinberg equilibrium (P > 0.9). A comprehensive overview of the MDM4 SNP34091 distribution in the healthy controls as well as the four cancer types analyzed is given in Table P = 0.193).In this study, 7,079 cancer cases and 3,747 healthy controls were analyzed for MDM4 SNP34091 status on cancer risk, we compared the frequency of the MDM4 SNP34091 genotypes among breast‐ , lung‐ , colon‐ , and prostate cancer  patients to healthy controls . We observed no significant correlation between MDM4 SNP34091 status and the risk of either cancer in the colon, lung, or prostate, either in a dominant or a recessive model . Furthermore, analyzing tumors of the right or the left side of the colon separately, revealed no significant effect of MDM4 SNP34091 status and cancer risk in either of the two groups (Table S1). We observed, however, a marginally significant association with reduced risk for breast cancer among individuals harboring the SNP34091CC genotype  were smokers, excluding nonsmokers from the analysis had no impact on the estimates (Table S2).MDM2 SNP309GG genotype has been associated with a nonsignificantly increased risk for breast cancer, breast cancer patients carrying the SNP309GG genotype have been found particularly sensitive to cancer risk reduction by a second MDM2 SNP (SNP285G>C) Previously, we assessed SNP status of the MDM4 partner MDM2 across the same population of cancer patients and healthy controls MDM4 SNP34091 and MDM2 SNPs with respect to cancer risk. Stratifying according to MDM2 SNP309 status  we found the MDM4 SNP34091CC genotype (recessive model) to be significantly associated with reduced risk of breast cancer among patients carrying the SNP309GG genotype , data not shown).In addition to assessing the effect of MDM4 SNP34091 status within the different MDM2 genotypes, either when stratifying cancer of the colon according to tumors of the right or left side, or when excluding the nonsmokers in lung cancer, was recorded.No effect on the risk of any of the other cancer forms with respect to MDM4 SNP34091 status and the risk for colon‐, prostate‐, or lung cancer, while a marginally significant association with reduced risk of breast cancer was observed. Our observation in breast cancer is similar to, but weaker than the observations of Liu and colleagues, who found the SNP34091 AC and CC genotypes to be significantly associated with reduced breast cancer risk compared with the AA genotype in two different Chinese populations MDM4 SNP34091C and reduced risk in the dominant model. This is in line with data from the majority of individual datasets from European populations, included in a recent large GWAS In this study, we observed no association between MDM4 SNP34091 on cancer risk in lung‐ and colon cancer. Previous case–control studies assessing this variant in other cancer forms , including breast cancer, have found the SNP34091C allele to be associated with reduced risk, but have all been performed in Chinese populations This study is, to our knowledge, the first population‐based case–control study assessing the impact of MDM4 SNP34091 between Europeans and Asians with a MAF of 0.26 and 0.05, respectively [MDM2 SNPs; SNP309 and SNP285 [Regarding the variations in the results between studies of different ethnic groups, notably, there is a large difference in the distribution of ectively , possibld SNP285 , 32, 33.MDM2 SNP309 status, we found a reduced risk for breast cancer among individuals harboring the MDM4 SNP34091CC/MDM2 SNP309GG genotype, and this association was stronger after removing individuals harboring the MDM2 SNP285C allele, previously shown to antagonize SNP309G‐induced transcription elevation MDM4 SNP34091C allele, similar to SNP285G>C seems to execute their effects on breast cancer risk among individuals carrying the SNP309GG genotype only After stratifying according to MDM4 SNP34091 status and risk for lung‐, prostate‐, or colon cancer, and a weak association with breast cancer, applying the candidate gene approach. The latter finding was substantiated by the observation of a seemingly synergistic effect between the MDM2 SNP309GG and MDM4 SNP34091AA genotypes on increased risk for breast cancer.In conclusion, we found no association between the None declared.Table S1.MDM4 SNP34091 distribution and left versus right colon cancer risk.Table S2.MDM4 SNP34091 distribution and lung cancer risk in smokers.Table S3.MDM4 SNP34091 among MDM2 SNP309GG without MDM2 SNP285C.Click here for additional data file.


Clustering of breast and colorectal cancer has been observed within some families and cannot be explained by chance or known high-risk mutations in major susceptibility genes. Potential shared genetic susceptibility between breast and colorectal cancer, not explained by high-penetrance genes, has been postulated. We hypothesized that yet undiscovered genetic variants predispose to a breast-colorectal cancer phenotype.P<5.0E-04  were analyzed for replication .To identify variants associated with a breast-colorectal cancer phenotype, we analyzed genome-wide association study (GWAS) data from cases and controls that met the following criteria: cases (n = 985) were women with breast cancer who had one or more first- or second-degree relatives with colorectal cancer, men/women with colorectal cancer who had one or more first- or second-degree relatives with breast cancer, and women diagnosed with both breast and colorectal cancer. Controls (n = 1769), were unrelated, breast and colorectal cancer-free, and age- and sex- frequency-matched to cases. After imputation, 6,220,060 variants were analyzed using the discovery set and variants associated with the breast-colorectal cancer phenotype at ROBO1 gene were suggestively associated with the breast-colorectal cancer phenotype in the discovery and replication data . In meta-analysis of the discovery and replication data, the most significant association remained at rs7429100 (P = 1.84E-06).Multiple correlated SNPs in intron 1 of the ROBO1, a potential tumor suppressor gene, merits further investigation.The results of this exploratory analysis did not find clear evidence for a susceptibility locus with a pleiotropic effect on hereditary breast and colorectal cancer risk, although the suggestive association of genetic variation in the region of  BRCA1, BRCA2 and CHEK2 genes (which are associated with breast cancer) are also at moderately increased risk of colorectal cancer  . We examEncyclopedia of DNA Elements data were queried to assess overlap with potentially functional genomic characteristics such as DNase I hypersensitivity sites, transcription factor regulatory regions and enhancer elements. Similarly, RegulomeDB  and HaplData for 985 cases and 1769 controls from 5 CCFR sites and 3 BCFR sites were analyzed in the Discovery Phase . The CCFP = 2.5E-07), an intronic SNP in BAALC (P<5.0E-08). Using a lower threshold (P<5.0E-04), we identified 60 suggestive regions/loci across the genome, on multiple chromosomes (chromosomes 1–12 and 16–20). The most significant SNP associations at each locus are listed in P<5.0E-04 are provided in The most significant association signal from the genome-wide association analysis was for rs12548629 on chromosome 8q22.3  along with three independent SNPs on 5p13.3, 9p22.2 and 20p11.23 (BAALC gene did not replicate (P = 0.54).Replication of the most significant SNP associations (n = 549 SNPs) in 60 regions on 18 chromosomes was performed using 293 cases and 2,103 controls, from 3 studies in GECCO. All cases and controls were women and the mean ages were 66.4 and 67.7 years, respectively . The rep20p11.23 . The sigP was for rs7429100 on chromosome 3p12.3, P = 1.84E-06; ROBO1  in intron 1.The meta-analysis of discovery and replication results did not identify a genome-wide significant signal , but no breast or colorectal tissue specific expression quantitative trait loci (eQTL) were associated with any of the ROBO1 SNPs , which coupled with their cancer family histories, favors the likelihood of a genetic predisposition. Our main findings include a suggestive association of a cluster of SNPs in et al. who found that some families where many members had breast cancer also had a high predisposition to colorectal cancer [CHEK2 1100delC mutation with HBCC using a subset of familial breast cancer families that did not carry the BRCA1 or BRCA2 mutations [CHEK2 1100delC mutation, suggesting that HBCC could be due to chance or yet undiscovered genes [There has been long interest and debate around possible genetic susceptibility to a distinct breast-colorectal cancer phenotype. The clustering of breast and colorectal cancer in families was described as early as in 1972 by Lynch l cancer . Subsequed genes . A similed genes . GWAS daBAALC gene. However, of the 549 SNPs at 60 loci tested for replication, BAALC SNPs did not replicate but P-values <5.0E-03 were found for several correlated SNPs in the region of chromosome 3p12.3; the ROBO1 gene. Although suggestive, the association signal did not meet the Bonferroni multiple testing threshold,  but the cluster of SNPs in intron 1 of the ROBO1 gene also had the smallest P-values from meta-analysis of the discovery and replication datasets .In the present study, no genome-wide significant loci were detected in the Discovery Phase but we found some suggestive associations, across multiple chromosomes, the most promising on chromosome 8q22.3, overlying the ROBO1 merits follow-up as it may have a potential functional role in breast-colorectal carcinogenesis. A transmembrane receptor of the immunoglobulin family, ROBO1interacts with SLIT2 (Slit Guidance Ligand 2) to regulate many biological functions, is differentially expressed in human cancers, and has a possible role as a tumor suppressor gene [sor gene . Studiessor gene , 32 and sor gene .ROBO1 as a susceptibility gene for a hereditary breast-colorectal cancer (HBCC) phenotype comes from a study by Villacis and colleagues [ROBO1 germline deletion in intron 4, spanning 37.470 kb , in three unrelated cases out of 113 HBCC patients. Pathogenicity of the deletion was supported by familial co-segregation with disease, its rarity in public CNV databases, and in silico evidence of the deletion having a functional role due to the presence of several enhancers and a histone marker in the deleted region. Notably, the authors reported that direct sequencing did not reveal any pathogenic point mutations in ROBO1. From our data and analyses, the association signal for ROBO1, comprised a cluster of 53 SNPs in intron 1, spanning 87.866 kb  and the SNP closest to the deletion was located 675.51 kb away from the deletion. Furthermore, unlike the rare deletion identified by Villacis and colleagues [Evidence in support of lleagues . The aimlleagues ). The aulleagues , these wP<0.05. The SMAD7 SNP rs4939827, identified as a colorectal cancer risk SNP [P = 1.85E-04) with a consistent direction of association for the risk allele (T). To our knowledge, there is no published evidence of association of this SNP with breast cancer risk, although a role of SMAD7 in the modulation of cancer growth and progression has been suggested for many cancers, including breast cancer [FGFR2 SNPs (rs298175 and rs2981582) [FGFR2 have been found to be associated with cancers other than breast but we have not found any association of FGFR2 SNPs with colorectal cancer in the published literature.Of the published GWAS SNPs associated with colorectal cancer risk and breast cancer risk, our analysis of the combined breast-colorectal dataset found that only a few SNPs were nominally significant at risk SNP  was the t cancer . Among t2981582) , 38 thatSH2B3 gene and rs12970291 near the TSHZ1 gene with evidence for a shared colorectal and endometrial cancer predisposition [SH2B3 SNP on chr12q24 was associated with lung, colorectal and breast cancer [Unlike the present study, which used a familial clustering approach used to identify cases, other studies have applied a meta-analysis approach to large GWAS datasets to identify common genetic susceptibility variants across multiple cancers. For example, using colorectal cancer and endometrial cancer genome-wide data for ~13,000 cases unselected for age of disease onset or family history, and ~40,000 controls, Cheng and colleagues identified two novel polymorphisms, rs3184504 in the position . Anothert cancer , which sBRCA1 or BRCA2 or known colorectal cancer susceptibility gene mutations were excluded from the GWAS. Despite this, our study could have had limited statistical power to detect alleles with small true effect sizes especially if they are rare. Our study was powered to detect risk alleles with a frequency greater than 10% and a per-allele odds ratio of 1.7. Although this detectable odds ratio is high for a GWAS, we reasoned that because the cases had a family history, the frequency of the risk allele could be higher than it would be for unselected cases [The strengths of the present study include using an agnostic approach to identify genetic susceptibility loci, and its enrichment for genetic susceptibility through the incorporation of early cancer onset (for breast cancer) and family history to define the breast-colorectal cancer phenotype. Furthermore, any breast-colorectal GWAS signal was less likely to be due to syndromic cases since all cases carrying ed cases . Study ped cases . We usedROBO1 was suggestive of an association with breast-colorectal cancer risk, and given mounting evidence for the role of ROBO1 as a tumor suppressor gene, further investigation of this association may be warranted.This analysis, aimed at elucidating genes/regions associated with a pleiotropic effect for breast and colorectal cancer risk, did not show a clear susceptibility locus for this phenotype. This raises the possibility that aggregation of these cancers within families may be due to chance co-occurrence of two common cancers. However, since germline variation in the region of S1 Fig(DOCX)Click here for additional data file.S2 Fig(DOCX)Click here for additional data file.S3 Fig(DOCX)Click here for additional data file.S4 Fig(DOCX)Click here for additional data file.S1 Table(DOCX)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.S3 Table(DOCX)Click here for additional data file.S4 Table(DOCX)Click here for additional data file.


PMD) is one of the most important risk factors for breast cancer (BC). Calcium, vitamin D, bisphosphonates, and denosumab have been considered and partly confirmed as factors potentially influencing the risk of BC. This retrospective observational study investigated the association between serum calcium level and PMD. A total of 982 BC patients identified in the research database at the University Breast Center for Franconia with unilateral BC, calcium and albumin values, and mammogram at the time of first diagnosis were included. PMD was assessed, using a semiautomated method by two readers. Linear regression analyses were conducted to investigate the impact on PMD of the parameters of serum calcium level adjusted for albumin level, and well‐known clinical predictors such as age, body mass index (BMI), menopausal status and confounder for serum calcium like season in which the BC was diagnosed. Increased calcium levels were associated with reduced PMD (P = 0.024). Furthermore, PMD was inversely associated with BMI (P < 0.001) and age (P < 0.001). There was also an association between PMD and menopausal status (P < 0.001). The goodness‐of‐fit of the regression model was moderate. This is the first study assessing the association between serum calcium level and PMD. An inverse association with adjusted serum calcium levels was observed. These findings add to previously published data relating to vitamin D, bisphosphonates, denosumab, and the RANK/RANKL signaling pathway in breast cancer risk and prevention.Percentage mammographic breast density ( BRCA mutation status have a higher relative risk for developing breast cancer than a PMD over 50% compared with a PMD lower than 10% Percentage mammographic breast density (PMD) is one of the most important risk factors for breast cancer (BC) Fibroglandular breast tissue appears radiopaque on mammography, whereas adipose breast tissue appears transparent or nondense A positive key feature of PMD in comparison with other established risk factors for breast cancer is its modifiability and dynamics. To date, several factors influencing PMD have been identified. PMD typically decreases with age, body mass index (BMI), which are independent risk factors for BC themselves Calcium, vitamin D, bisphosphonates, and denosumab have also been considered and partly confirmed as influencing factors for the risk of BC. An inverse dose–‐response association between calcium intake and breast cancer risk was described. A large meta‐analysis of eleven prospective studies showed that the overall risk reduction in breast cancer for high versus low intake of calcium was 0.92  Recent studies have provided a strong rationale that the RANK/RANKL signaling pathway, which controls amongst other things the regulation of calcium metabolism There are limited data concerning vitamin D and calcium in connection with reducing BC risk. Some studies have reported that calcium and vitamin D intake reduces PMD in premenopausal women, but not in postmenopausal women The aim of this study was to examine the association between PMD and the serum calcium level in a large retrospective study of primary BC patients with high‐quality PMD measurements — specifically, whether serum calcium can be used to predict the PMD in addition to other, previously reported modifiers of PMD that correlate with a lower PMD, such as age, menopausal status, and BMI.This study is a retrospective, single‐center, observational study in which the association of PMD and serum calcium levels was evaluated in patients with unilateral primary BC. It was conducted in accordance with the World Medical Association Declaration of Helsinki. Approval for the study was obtained from the ethical review committee in the Faculty of Medicine at Friedrich Alexander University of Erlangen–Nuremberg. All patients provided written informed consent after receiving detailed instructions and before inclusion in the NIS.The patients were selected from the BC database at the University Breast Center Franconia (Germany). All patients with invasive BC diagnosed between 2002 and 2010 at the University Breast Center Franconia were initially included in the database. A total of 5110 patients with invasive BC were documented in the database for the period 2002–2010. For the analysis presented here, patient datasets were excluded in the following order: missing calcium and albumin values around the date of the first diagnosis of breast cancer ; and no mammograms taken and digitally stored around the time of diagnosis . The final dataset consisted of 982 patients at the University Breast Center Franconia with unilateral breast cancer and with calcium and albumin values and mammograms available from the time of first diagnosis. The patient characteristics of included and excluded patients are shown in Table S1. Both groups are similar.Deutsche Krebsgesellschaft) and by the German Society for Breast Diseases (Deutsche Gesellschaft für Senologie) All patient characteristics and tumor characteristics were documented as part of the certification processes required by the German Cancer Society  of the examination parameters of serum calcium level adjusted for albumin level (continuous), as well as several well‐known clinical predictors, such as age, continuous; body mass index (BMI), continuous and menopausal status, categorical. Season of diagnosis was included in the model because it could be a confounder for vitamin D and calcium levels.final regression model). The predictor serum calcium level was kept because it is the predictor of interest, the predictors age and BMI were kept because it is known that they are associated with PMD. The regression coefficients and P values for the predictor variables were estimated. The coefficient of determination, R2, was calculated to measure the goodness of fit.Initially, a full linear regression model was set up with all of the predictors mentioned above and PMD as outcome variable. Then, backward stepwise variable selection in which serum calcium level, age, and BMI were kept was carried out to obtain the best model in accordance with the Akaike information criterion .All of the tests were two‐sided, and a n = 242) of the patients were premenopausal and 75.36% (n = 740) were perimenopausal or postmenopausal. Excluded and included patients were similar (Table S1).The analysis was conducted with complete datasets for 982 breast cancer patients, 2134 patients were excluded because of missing values, either calcium or albumin and 1994 patients were excluded due to missing mammograms. The PMD of included patients ranged from 3% to 93%. The patients’ average age was 59.2 (±12.3) years and their average BMI was 26.5 (±5.2); 24.6% , and serum albumin levels from 14.4 to 54.5 g/L (reference range 33–55 g/L). The frequency of diagnosis did not depend on season. The patients’ and tumor characteristics are listed in Table P values of the final linear model are shown in Table The final linear regression model for predicting the impact of clinical predictors and serum calcium on the percentage mammographic density consisted of the predictors albumin adjusted serum calcium level, BMI, age, and menopausal status. Season of diagnosis did not remain in this model. The coefficients and P < 0.001) as well as postmenopausal women (P < 0.001). A higher BMI was associated with a lower PMD as well (P < 0.001).Age and BMI were both significantly and inversely associated with PMD. There was also an association between PMD and menopausal status. Older women had lower mammographic densities (P = 0.024). Every increase in calcium serum levels by 0.1 mmol/L would decrease the predicted PMD in the linear regression model by 1.1%.With regard to calcium a higher calcium was significantly associated with lower PMD (R2: 0.39).A “high‐density patient” can thus be defined by this linear regression model as a young, slim woman with a low calcium level, while a “low‐density patient” is an elderly, obese woman with a high calcium level. Goodness of fit of the regression model was moderate D) levels and/or serum calcium level and PMD, most previous studies have only taken into account the 25‐hydroxyvitamin D (25(OH)D) level, without the serum calcium level. The 25(OH)D level has been associated with breast cancer risk Some evidence has recently been found that RANKL mediates progestin‐induced mammary epithelial proliferation, carcinogenesis and BC development Against this background, the present results are of particular interest. The exact mechanism through which low serum calcium levels lead to a higher PMD, which is associated with an increased risk for BC, is not yet known. However, in view of recent research on RANKL and BC development, as well as the regulation of the calcium metabolism by RANKL, it may be hypothesized that the RANK/RANKL signaling pathway plays a special role in the complex correlation between serum calcium levels and PMD. This study might therefore support a rationale for establishing denosumab as a preventive treatment against BC.The study has several strengths and limitations. The BC patients included were hospital‐based and were not recruited from a population‐based screening program. Breast density is thought to contribute to a higher likelihood of tumors being missed during early detection methods for BC. It might therefore be possible that the patients had a higher PMD than that in the general population. The large amount of missing values could lead to a selection bias. But on the other hand, the collective was well characterized and published in others studies before. Another study limitation is the lack of information on the correlation between serum calcium and PMD in healthy women not diagnosed with breast cancer. It could be that the presence of breast cancer has influenced the association of serum calcium and PMD. Not all well‐known predictors  of PMD are included in the model. The correlation between a higher calcium and lower PMD was significant, but the goodness of fit of the regression model was moderate. Our regression analyses showed that age, BMI, menopausal status, and calcium levels are associated with PMD. A precise quantification of the association, however, was not possible due to moderate goodness of fit of the regression model.The strengths of the study are the semiautomated method of quantifying mammographic density, with two readers for all images and a mean value for PMD being used. This may reduce measurement inaccuracies. Both semiautomated assessments and automated volumetric density showed similar results An inverse association was observed between serum calcium levels, adjusted to serum albumin levels, and percentage mammographic density in patients with primary breast cancer. These findings, along with previously published research results, provide a strong rationale suggesting that the calcium metabolism and related pathways, including the RANK/RANKL signaling pathway, may play a role in the mechanism involved. Future research investigating BC prevention should specifically address the calcium and RANK/RANKL pathway.PAF has carried out research for Novartis and Amgen. All of the other authors declare that they do not have any conflicts of interest.Table S1. Patient characteristics and tumor characteristics of included and excluded patients, showing means for continuous characteristics and percentages for categorical characteristics.Click here for additional data file.


We evaluated serum concentrations of sRAGE, adiponectin, leptin, monocyte chemotactic protein 1 (MCP1), and plasminogen activator inhibitor‐1 (PAI1) using immunoassay. We used conditional logistic regression model to estimate adjusted odds ratios (aORs) and 95% confidence intervals (CIs) for pancreatic cancer over biomarker quartiles (Q1–Q4). We used principal component analysis to create two composite biomarkers and performed a confirmatory factor analysis to examine the association between composite biomarker scores (CBS) and pancreatic cancer risk. Baseline serum sRAGE concentrations were inversely associated with pancreatic cancer risk . High MCP1  and the higher CBS including MCP1, PAI1, and leptin  were also associated with increased pancreatic cancer risk among women with BMI <25 kg/m2 . We found an inverse association between prediagnostic sRAGE concentrations and risk of incident pancreatic cancer in postmenopausal women. A proinflammatory CBS was associated with increased risk only in women with normal BMI. MCP1 was not modulated by sRAGE.Advanced glycation end products (AGEs) dysregulate adipokines and induce inflammation by binding to their adipocyte receptor (RAGE). Soluble RAGE (sRAGE) prevents AGEs/RAGE signaling. We performed a nested case–control study of the association between sRAGE, adipokines, and incident pancreatic cancer risk in the prospective Women's Health Initiative Study. We individually matched controls ( It is estimated that about 53,670 individuals will be diagnosed with pancreatic cancer in the United States in 2017, and it is the deadliest type of cancer Chronic inflammation triggered by the proinflammatory advanced glycation end products (AGEs) and their receptor (RAGE) has been associated with pancreatic carcinogenesis in experimental studies SERPINE1 and is the principal component of the plasminogen system, which is upregulated in inflammation and cancer In addition to affecting sRAGE levels, AGE accumulation in adipocytes dysregulates production of adipokines, such as adiponectin, leptin, monocyte chemoattractant protein 1 (MCP‐1), and plasminogen activator inhibitor type I (PAI‐1), through binding to RAGE Therefore, we performed a nested case–control study within the prospective Women's Health Initiative Study (WHI) to investigate the association between baseline serum concentrations of sRAGE and adiponectin, leptin, MCP1, and PAI1 and incident pancreatic cancer risk. We hypothesized that sRAGE concentrations would be inverse while proinflammatory adipokines would be positively associated with pancreatic cancer risk, and the concentrations of sRAGE and adipokines were correlated. Furthermore, we evaluated whether the associations were modified by body mass index (BMI). Finally, we used a principal component analysis (PCA) and confirmatory factorial analysis to elucidate the association between sRAGE, adipokines, and pancreatic cancer risk.Detailed information on the WHI Study including study population, recruitment methods, and measurement protocols has been described previously The WHI maintains ongoing follow‐up for health outcomes; for this analysis, we used data through December 2013. Cases of incident pancreatic cancer were ascertained from annual self‐administered questionnaires. The diagnosis was further verified via a centralized review of medical records including clinical notes, pathology, operative and radiology reports, and tumor registry abstracts and eventually adjudicated according to the International Classification of Diseases for Oncology site codes C25.0–C25.4, C25.7–C25.9 n = 57 cases and n = 14,792 controls) prior to baseline, who had missing matching variable data or follow‐up time (n = 1 cases and n = 719 controls), who were in DM active intervention arm , or who had inadequate serum (n = 2 cases and n = 979 controls). Thus, we identified 494 cases and 114,310 potential controls . However, in the main analysis, we excluded 186 controls and 22 orphaned cases (without matching controls) because they developed breast, colorectal, or lung cancers after the index diagnosis date of the matched pancreatic cancer case. Thus, our final analytic cohort included 142 and 330 cases matched 1:1 and 1:2 to controls, respectively, yielding a total of 472 cases and 802 matched controls.Detailed information including sociodemographic characteristics, personal medical history, reproductive history, and lifestyle including smoking and alcohol use was obtained at baseline using interviewer‐administered structured questionnaires Blood samples obtained at baseline following an overnight fast of at least 12 h were stored at −70°C. Because serum samples have been used to test biomarkers previously, all samples have gone through the same freeze‐thaw cycles (less than two cycles).We used human sRAGE Quantikine ELISA kit  to measure sRAGE concentrations. We used the R&D Human Obesity MultiAnalyte Profiling Kit (R&D System Inc.) to concomitantly measure concentrations of adiponectin, leptin, MCP1, and PAI1. All kits had the same lot number. All the biomarkers were measured at Baylor College of Medicine. Randomly ordered case and matched control samples were run side by side in the same batch (96‐well plate). A 10% quality control (QC) sample provided by the WHI clinical coordinating center was also randomly placed on each plate. Laboratory personnel who performed the ELISA assay were blinded to QC samples and case–control status. All samples were assayed in duplicate. The QC samples showed that all inter‐ and intra‐assay CVs varied from 2% to 5% for all biomarkers indicating excellent laboratory performance.The study protocol was approved by Institutional Review Board (IRB) of the WHI and by the combined IRB of Baylor College of Medicine and the Michael E. DeBakey VA Medical Center in Houston, TX.We compared the distribution of sociodemographic factors, anthropometric characteristics ), medical history , lifestyle factors , food consumption , medication use ), and baseline concentrations of circulating biomarkers  in pancreatic cancer cases and matched controls using paired t‐tests or Wilcoxon signed‐rank tests for normal or non‐normal distributed continuous variables, respectively, and McNemar's or Cochran's Q test for categorical variables for two or more than two categories, respectively.2) was further adjusted in the model to evaluate its mediate effect on sRAGE and risk of pancreatic cancer. All other variables evaluated in Table We used the distribution of each circulating biomarker in controls to define quartile (Q) thresholds. We investigated the association between our primary biomarker of interest, sRAGE, and all other biomarkers  as well as the ratio of adiponectin to leptin (adiponectin/leptin) and risk of incident pancreatic cancer using conditional logistic regression models. We performed staged multivariable analysis with the minimal multivariable model adjusting for history of type 2 diabetes and smoking (current/former vs. never) as they are established risk factors for pancreatic cancer. BMI  and follow‐up time (<10 years vs. ≥10 years). The score test was used to assess for trend across increasing quartiles by treating the quartile levels as a continuous variable with significance of interaction terms evaluated by a Wald test. In the stratified analysis, the case–control match was broken. The primary matching factors age and race/ethnicity were adjusted for in the unconditional logistic regression models. Sensitivity analyses were performed by excluding study participants who had <1 year of follow‐up (450 cases and 801 controls retained) or including controls who later developed cancers of breast, colon‐rectum, and lung and their matched pancreatic cancer cases (494 cases and 986 controls).We performed stratified analyses to further assess for potential effect modification by two variables P values for all the biomarkers with BMI. We further conducted PCA that showed a strong two‐dimensional structure. Oblique rotations were applied to the two principal components to ascertain a structure that would eliminate low correlations between these two factors. This structure was then used in specifying a confirmatory factor analytic (CFA) model (a multiple regression of the biomarkers on the two factors as latent variables). The scores from the two factors obtained from these CFA regressions were then used as composite biomarker scores to serve as surrogates for the original biomarkers in multivariate conditional logistic regression analysis assessing pancreatic cancer risk.We used log transformations to normalize the distributions of sRAGE, adiponectin, leptin, MCP1, and PAI1 and calculated the Pearson correlation coefficients and associated P values considered significant at P < 0.05 because sRAGE was the main biomarker of interest, and with all analyses performed using SAS version 13 .All statistical tests were two‐sided with P = 0.04).Table Q4 vs. Q1 = 0.70, 95% CI: 0.50–0.99; P trend = 0.03). The association was slightly attenuated with further inclusion of BMI in the model. There was a suggestive inverse association with adiponectin . There were no significant associations between concentrations of leptin, MCP1, and PAI1 and pancreatic cancer risk. In a sensitivity analysis where we excluded participants with <1 year of follow‐up, the association was essentially unchanged for sRAGE. There was a nonsignificant inverse association between adiponectin and pancreatic cancer risk  with the positive association seen only among women with BMI <25 kg/m2 .Table Table 2 , but not in women with BMI ≥25 kg/m2. The composite biomarker A showed no association with risk of incident pancreatic cancer . Composite biomarker A (anti‐inflammatory) was positively significantly correlated with sRAGE and adiponectin, negatively correlated with leptin, but not correlated with MCP1 or PAI1. Composite biomarker B (proinflammatory) was positively correlated with MCP1, PAI1, and leptin, but not correlated with sRAGE and adiponectin. These two components yielded well‐defined exploratory factors that tracked the syndemic behavior of the five biomarkers. We found, like results for the individual biomarkers, a suggestion of potential significant effect modification by BMI for composite biomarker score B, which was associated with increased risk of pancreatic cancer only in women with BMI <25 kg/mIn a sensitivity analysis where we included controls who later developed cancers of breast, colon–rectum, and lung during follow‐up and their matched pancreatic cancer cases, the association between sRAGE and pancreatic cancer was only moderately attenuated and became nonsignificant, while risk estimates for PAI1 were attenuated more than 10%. The observed interaction between MCP1 and BMI remained the same Tables  and S4.2) with higher MCP1 had increased risk of pancreatic cancer. Furthermore, lean women with a higher proinflammatory composite biomarker score comprised of MCP1, PAI1, and leptin had an increased risk of pancreatic cancer.In this nested case–control study in the WHI Study, we prospectively examined the association between baseline serum concentrations of sRAGE and multiple adipokines/chemokines and the risk of incident pancreatic cancer. We found that sRAGE was inversely associated with pancreatic cancer risk in postmenopausal women regardless of BMI, smoking status or follow‐up time. We also found that lean women  and CCL5, are major attractants of monocyte and macrophage precursors to the tumor microenvironment. Pancreatic cancer uses the CCL2/CCL2 receptor (CCR2) axis to favor the mobilization and recruitment of inflammatory monocytes from the bone marrow to the tumor site to facilitate tumor growth Because inflamed adipose tissue in obese persons has been associated with various cancers, we originally hypothesized that proinflammatory adipokines/chemokines would be associated with increased risk of pancreatic cancer particularly in obese women. However, we observed a positive association between prediagnostic concentrations of MCP1 and pancreatic cancer only in lean women. It is well known that MCP1 is expressed by a wide range of cells including endothelial, epithelial, myeloid and smooth muscle cells, and fibroblasts, either constitutively or after induction, and is a potent chemoattractant for monocytes, basophils, T lymphocytes, and NK cells Our study has novelty and multiple strengths. First, this study was the first to evaluate sRAGE as a risk marker for pancreatic cancer in women and to evaluate chemokines MCP1 and PAI‐1 and pancreatic cancer risk in any cohort. Second, the use of PCA to generate composite biomarker score which was interrogated in exploratory multivariable analysis was novel. Third, it was performed in the large, well‐phenotyped, and prospectively followed WHI cohort. Collection of baseline samples in women followed for an average of 14 years helped reduce concern about potential reverse causation bias, with results from our lag analysis suggesting that only the biomarker leptin may be differentially associated with disease risk over time. Finally, we evaluated multiple established and potential confounders. Methodologically, we found risk set sampling of controls in the nested case–control study may attenuate the association if matched controls had undiagnosed cancers because the biomarker abnormality may have occurred in undiagnosed controls.There are several limitations of our study. First, the generalizability of our findings on MCP1 is limited because the postmenopausal women in our study were largely non‐Hispanic White and never or former smokers. In addition, given the tumor microenvironment may be organ‐specific, these study findings may not be generalizable to other types of cancer. Second, given the rarity of pancreatic cancer, study power was limited in stratified analyses. Our results were not adjusted for multiple testing in considering sRAGE was the major biomarker of interest. Finally, our findings on the composite biomarker suggesting excess risk in lean women only were qualified as suggestive and provisional until replicated in other cohorts.In summary, together with our previous study RAGE expressed on adipocytes may modulate adipokine production. Serum concentrations of anti‐inflammatory soluble RAGE were inversely associated with risk of incident pancreatic cancer in postmenopausal women. Chemokine MCP1 and a proinflammatory biomarker score including MCP1, leptin, and PAI1 were associated with increased risk of incident pancreatic cancer among lean women. However, sRAGE was not correlated with MCP1. This research provides novel insight into obesity‐related pancreatic cancer in the context of RAGE signaling pathway and adipokine/chemokines.None delared.Table S1. Association between baseline serum levels of biomarkers and risk of incident pancreatic cancer in the WHI Study, follow up no less than 1 year, 1993–2013 (450 cases and 801 controls).Table S2. Association between sRAGE, adiponectin, leptin, MCP1 And PAI 1 and risk of pancreatic cancer by follow‐up years (472 cases and 802 controls).Table S3. Association between baseline serum levels of biomarkers and risk of incident pancreatic cancer from the WHI Study, 1993–2013 (494 cases and 986 controls).Table S4. Association between MCP1 and risk of pancreatic cancer by BMI status (494 cases and 986 controls).Click here for additional data file.


The role of diet in breast cancer aetiology is unclear; recent studies have suggested associations may differ by estrogen receptor status.P-values allowed for multiple testing.Baseline diet was assessed in 2000–04 using a validated questionnaire in 691 571 postmenopausal UK women without previous cancer, who had not changed their diet recently. They were followed by record linkage to national cancer and death databases. Cox regression yielded adjusted relative risks for breast cancer for 10 food items and eight macronutrients, subdivided mostly into five categories of baseline intake. Trends in risk across the baseline categories were calculated, assigning re-measured intakes to allow for measurement error and changes in intake over time; P = 5.8 × 10−14. There were inverse associations with fruit: RR 0.94 (99% CI 0.92–0.97) per 100 g/day higher intake, P = 1.1 × 10−6, and dietary fibre: RR 0.91 (99% CI 0.87–0.96) per 5 g/day increase, P = 1.1 × 10−4. Fruit and fibre intakes were correlated (ρ = 0.62) and were greater among women who were not overweight, so residual confounding cannot be excluded. There was no heterogeneity for any association by estrogen receptor status.Women aged 59.9 (standard deviation (SD 4.9)) years at baseline were followed for 12 (SD 3) years; 29 005 were diagnosed with invasive breast cancer. Alcohol intake had the strongest association with breast cancer incidence: relative risk (RR) 1.08 [99% confidence interval (CI) 1.05–1.11] per 10 g/day higher intake, By far the strongest association was between alcohol intake and an increased risk of breast cancer. Of the other 17 intakes examined, higher intakes of fruit and fibre were associated with lower risks of breast cancer, but it is unclear whether or not these associations are causal. In this large prospective study, we systematically examined associations of 10 foods and eight macronutrients with breast cancer risk, overall and by estrogen receptor status.The strongest finding was a positive association of alcohol consumption with breast cancer risk, in line with previous evidence.None of the 17 other foods and macronutrients examined was strongly associated with breast cancer risk; both fruit and fibre intakes, which are correlated, showed inverse associations with risk, but it is unclear if these associations are causal.For none of the dietary items examined was there evidence of heterogeneity by estrogen receptor status. ,,Breast cancer incidence is generally greater in high-income than low-income countries.We report here results from an analysis of the relation between intakes of a wide range of foods and macronutrients and breast cancer incidence among postmenopausal women in the Million Women Study, a large prospective study in the UK. To cover the most prominent hypotheses for effects of diet on breast cancer risk,,Participants in the Million Women Study were recruited from women invited to the National Health Service (NHS) Breast Screening Programme in England and Scotland between 1996 and 2001. A total of 1.3 million women aged 56 years [standard deviation (SD) 6] on average joined the study by completing the recruitment questionnaire, which asked about social, demographic and lifestyle factors. Postal re-surveys have been done every 3–5 years and online questionnaires about dietary intake have been administered since 2010. The study was approved by the Oxford and Anglia Multi-Centre Research Ethics Committee, and all women gave written consent. Further details are on the study website.http://www.millionwomenstudy.org/files/mws-web2.pdf). Nutrient intakes were calculated by multiplying the frequency of consumption of each food by the specified portion size and the nutrient composition of that item. The short-term repeatability of most of the diet questions was good, and in comparison with intakes of nine macronutrients estimated from 7-day food diaries (with portion sizes weighed or assessed by comparison with photographs), the median energy-adjusted correlation coefficient was 0.55 .An average of 3.3 years after recruitment, women were sent a questionnaire which updated information collected at recruitment and collected new information on diet. This 3-year re-survey, which asked for the first time about dietary intakes, was completed in 2000–04 and is the baseline for the analyses reported here. Participants were asked about their usual diet during a typical week, including about 130 quantitative or semi-quantitative questions . For meat, the five categories were of the type of meat consumed: never ate meat; ate poultry but no red meat ; consumers of red meat but no processed meat; consumers of red meat and at least one type of processed meat ; and consumers of red meat and at least two types of processed meat. For other foods the categories were selected to provide substantial numbers in each of the five groups, while respecting the integer nature of some of the data (e.g. items of fruit consumed per day). Vegetables comprised cooked vegetables (except potatoes) and salad items/raw vegetables; and fruit comprised fresh fruit, dried fruit and stewed or tinned fruit. For the eight macronutrients studied here, the cut-points for the five groups were quintiles of intake. In Repeat measures of intake in each baseline category were derived from a web-based 24-h dietary assessment tool, the Oxford WebQ,n = 7647) of the cohort has been lost to follow-up. and individuals contributed person-years until they were lost. Diagnoses were coded to the International Classification of Diseases, 10th Revision (ICD-10). The endpoint for this study was incident invasive breast cancer (ICD-10 C50).Participants were followed by record linkage to the UK NHS databases on cancer registrations and deaths. Data for England were provided by NHS Digital and the Office for National Statistics, and for Scotland by the Information Services Division, NHS Scotland. Information on estrogen receptor (ER) status of the incident breast tumours was provided by Public Health England/National Cancer Registration and Analysis Service; this information is incomplete, particularly during the early years of follow-up. Overall 1% . This non-parametric approach reduces the impact of regression dilution bias and other forms of measurement error.2), height , alcohol consumption , smoking , age at menarche , strenuous exercise , parity and age at first birth , highest education  and ever use of hormonal therapy for menopause . The non-dietary data were from the 3-year re-survey, except for socioeconomic group, strenuous exercise and height, which were from the recruitment questionnaire. To ensure that the same women were being compared in all analyses, the small number with a missing value for each particular variable were assigned to a separate category for that variable.Woman-years were calculated from the date the baseline dietary questionnaire was completed up to whichever came first: diagnosis of cancer, emigration, death, loss to follow-up or the last date when cancer incidence data were complete. The last date of follow-up was 31 December 2014. Cox regression models with time in study as the underlying time variable were used to estimate rate ratios (RRs) and 99% confidence intervals (99% CIs) of breast cancer by dietary factors. Analyses were stratified by year of birth, region of residence  and calendar year of completion of the dietary questionnaire, and adjusted for dietary energy intake (fifths), socioeconomic group  at baseline and 123 099 who reported at baseline that they had changed their diet in the previous 5 years due to illness. Women with energy intakes <2100 kJ/day (d)  or more than 14 700 kJ/d  were excluded. After these exclusions, 691 571 women were eligible for these analyses. 12 for trend = 62.1; P = 5.8 × 10−14) per 10 g/d higher intake (trend in drinkers only). There was also an inverse association of risk with fruit intake, with a RR of 0.94  per 100 g/d higher intake (further results for 12 for trend = 19.5] and dried fruit , but not with tinned/stewed fruit or fruit juice (After 12 (SD 3) years of follow-up, 29 005 women were diagnosed with incident invasive breast cancer, among whom information on ER status was available for 10 838 ER+ve and 1658 ER-ve breast cancers. 12 for trend = 20.5; P = 1.1 × 10−4) per 5 g/d higher intake  is expected, given that alcohol is an established cause of breast cancer.P = 1.1 × 10−6 and 1.1 × 10−4, respectively, after correction for multiple testing). Intakes of fruit and dietary fibre were strongly correlated with each other (correlation coefficient 0.62), therefore the associations of these two dietary items with breast cancer risk are not independent. In a recent meta-analysis,We report the results from systematic analyses in a large prospective study of the associations between intakes of 18 dietary factors and the incidence of breast cancer. The positive association with alcohol consumption , the UK Medical Research Council (grant no. MR/K02700X/1) and the Wellcome Trust, Our Planet Our Health . K.E.B. is supported by the Girdlers' New Zealand Health Research Council Fellowship. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript. The authors had full access to the data and analyses, and were solely responsible for the decision to submit for publication.Supplementary DataClick here for additional data file.


Optimune, a novel Internet intervention we developed for that purpose, leads to improvements in quality of life and relevant lifestyle habits over the course of 3 to 6 months.Depression and fatigue are common in breast cancer survivors, and their presence is associated with personal suffering and worse prognosis. While many women receive short-term psychological support in the acute treatment phase, this is rarely available in subsequent phases. Internet interventions for breast cancer survivors could provide additional psychological support, as they are easily accessible and may be effective. However, no trial has yet examined the effectiveness of an Internet intervention that provides cognitive behavioural therapy techniques plus lifestyle advice for this population. This trial aims to test whether Optimune after a delay of 3 months (CAU/wait list control), or (2) a treatment group that may also use CAU and will receive 12-month access to Optimune immediately after randomization. The three primary endpoints are quality of life, physical activity and diet quality, assessed with the World Health Organization Quality of Life Questionnaire, the International Physical Activity Questionnaire and the Food Quality Questionnaire, at 3 months post-baseline; secondary outcomes include cancer-related fatigue, emotional stress, depression, anxiety, fear of progression, insomnia, usefulness of the programme and negative treatment effects. Online assessments are conducted at baseline (T0), 3 months (T1) and 6 months (T2).This randomized controlled trial (RCT) will include 360 female breast cancer survivors who have completed the active tumour eradication phase. Participants will be recruited from various settings, including web-based advertisements and Internet forums in German-speaking countries. The main inclusion criteria are a breast cancer diagnosis less than 5 years ago and completion of acute treatment at least 1 month ago, as verified by discharge letter from an oncology treatment centre. Participants will be randomly assigned to either (1) a control group, in which they receive care as usual (CAU) and are given access to Results of this RCT are expected to extend the body of knowledge with regard to the effectiveness of CBT-based Internet interventions for female breast cancer survivors.NCT03643640. Registered on 23 August 2018.ClinicalTrials.gov,  Approximately 70,000 women are diagnosed with breast cancer in Germany annually . Breast While many women receive short-term psychological support in the phase of acute treatment, this is rarely the case in subsequent phases. Although women successfully treated for breast cancer often do not experience cancer recurrence during the monitoring phase, they frequently experience other symptoms. For example, an average of 27% of breast cancer survivors experience clinically significant fatigue following treatment , 5. FurtSeveral pharmacological depression treatments have been shown to be effective among breast cancer survivors. A systematic review reported that the prescription of antidepressants is more common among breast cancer survivors (average rate of 23%) compared to other cancer types, even though some controversy persists as to whether selective serotonin re-uptake inhibitors interact with tamoxifen , 13. CerCertain psychological interventions for depression, including mindfulness-based stress reduction (MBSR), cognitive behavioural therapy (CBT) and supportive-expressive dynamic psychotherapy have also been shown to have an impact on inflammatory markers  in several psychiatric and somatic diseases with comorbid depression –19. A reEven though CBT and perhaps other forms of psychotherapy are promising treatments for depression among breast cancer survivors, these psychological treatments are not always available . Psycho-A potential barrier to pharmacological depression treatment is that physicians are often reluctant to prescribe antidepressants because of concerns over side effects or drug-drug interactions . AccordiOptimune. This individually tailored Internet intervention targets female breast cancer survivors and was developed by Gaia, a German research-focused small-to-medium enterprise (SME) with more than 10 years of experience in the development of similar interventions. For example, 12 RCTs have demonstrated the efficacy of Deprexis, an Internet intervention for depression developed by the same team with the same technology ) questionnaire [Fear of progression using the standardized ionnaire , 70Insomnia Severity Index (ISI) [Insomnia using the standardized ex (ISI) NPS [Subjective usefulness of the programme using the NPS  and seveThe following secondary outcomes will be assessed using self-report. Each instrument will be administered at T0, T1 and T2, except for the Additionally, participants will be asked about specific illness-related parameters including recurrence of breast cancer , frequency of common cold or virus flu, frequency of unscheduled medical encounters, body mass index and the parallel use of psychotherapy at T0, T1 and T2. Furthermore, participants will be asked for open feedback on the programme 15 days after access has been granted.d = 0.35), a total sample size of 346 participants will be required to achieve a power of 0.80 with an adjusted alpha level of 0.0167 . An effect of d = 0.35 has been shown in previous reviews on psychosocial outcomes in patients with cancer [N = 360). Because missing data will be replaced by multiple imputation, the target sample size is not adjusted for anticipated attrition.To estimate the target sample size, an a priori power analysis was performed with g*power (Version 3.1.9.2) . In ordeh cancer –76. TherIn line with recommendations of the CONSORT eHealth statement, we will conduct both intention-to-treat (ITT) and per-protocol (PP) analyses using appropriate statistical procedures such as analysis of covariance (ANCOVA) for primary and secondary outcome measures , 77. MisThe reasons that lead to the exclusion of participants will be reported and analysed for patterns , that isOptimune is the first Internet intervention for breast cancer survivors that uses an extensive tailoring approach to convey CBT content to users. It has been specifically designed to address the needs of breast cancer survivors and uses a responsive web-design approach to maximize personal relevance and ensure easy usability.The present study aims to make a contribution to the literature on Internet interventions for breast cancer survivors, and to test the effectiveness of a potential new treatment option that may help improve the quality of care for this group. There is a need for innovative interventions in this area, given that depression and fatigue are exceedingly common in women after the acute treatment phase, and psycho-oncological treatment provision is often insufficient, particularly in rural areas. To our knowledge, An advantage of this trial is that diagnoses will be verified by a clinician, which is rare in studies of Internet interventions. Additional methodological strengths include follow-up assessments and the inclusion of an array of validated measures for the primary and secondary outcomes. Of note, potential negative treatment effects will also be assessed, which is rarely done but required to establish the safety of novel Internet interventions. Another strength is that participants will be asked to provide open feedback about the programme.Several limitations must also be acknowledged. First, the trial does not include an active control condition, but comparisons with CAU are regarded as common and appropriate features of pragmatic RCTs. Second, because we could not identify a brief and previously validated food questionnaire that adequately covers the food groups targeted by our intervention, we included a new questionnaire that was developed for this study. We regard this study as a first step towards examining this questionnaire’s psychometric properties, but we acknowledge the limitation that further research will be required to establish its reliability and validity. Third, the target sample size may yield insufficient statistical power for the detection of small effects, especially if attrition rates are high. As recommended by the CONSORT statement, we plan to replace missing data by appropriate procedures (e.g. multiple imputation), and we expect that the sample size will allow us to detect effects of medium magnitude, which could be considered clinically relevant. Due to resource limitations, recruitment of a large sample is not possible in this trial. Fourth, the inclusion of three primary outcome variables is unusual. However, given that the intervention aims to improve quality of life as well as change dietary and exercise habits, we regarded all three as equally important outcomes, each of which deserves equal consideration. To reduce the familywise error rate, the Bonferroni correction will be applied. The fifth limitation concerns the lack of clinician outcome ratings. Self-report questionnaires will be used, which are efficient and validated but also carry the risk of introducing biases such as social desirability. An additional limitation is that the developers of the intervention that is being tested are involved in this trial. We note, however, that this is not unusual and that several steps are taken to ensure the scientific integrity of data collection and analysis. To avoid potential developer bias, data monitoring will be performed by the Principal Investigator (CW), who is an established independent researcher in immunology with no financial ties to the developers or other relevant conflicts of interest. The trial has been registered, and results will be published regardless of study outcome.Optimune, which will be offered as an adjunct to care as usual. If the results from this trial demonstrate the effectiveness of the Optimune programme, this would suggest that this Internet intervention could serve as a useful treatment tool with the potential to enhance the overall quality of care for breast cancer survivors.In conclusion, the present study will test the effectiveness of the new self-management intervention The protocol version number is OPT 01, issued 13 November 2019. Participant recruitment began on 1 September 2018, and was completed on 1 October 2019. Collection of follow-up data will continue until 1 April 2020.Additional file 1. Exemplary screenshots of the Optimune programme, showing exemplary content of the four domains covered in Optimune.Additional file 2. SPIRIT 2013 checklist: recommended items to address in a clinical trial protocol and related documents.


Dear Editor,Recently, Punzi and colleagues published a study about the role of WDR5 in breast cancer metastasis . WDR5 i


To estimate the potential effect of schizophrenia on breast cancer risk in women, we performed a two-sample Mendelian randomization (MR) study.http://www.med.unc.edu/pgc/) and the United Kingdom Clozapine Clinic. The association between these SNPs determined schizophrenia and breast cancer risk was estimated in approximately 229,000 European descent females from the Breast Cancer Association Consortium using the inverse-variance weighted and the weighted median MR methods.The instrumental variables comprised 170 uncorrelated and non-pleiotropic single nucleotide polymorphisms (SNPs) that are significantly associated with schizophrenia risk in genome-wide association studies in 105,000 European descent individuals of the Psychiatric Genomics Consortium (p = 5.6 × 10−5). Similar significant associations were observed in analyses using a weighted median model and sensitivity analysis excluding six SNPs with genotype imputation score of less than 0.8, as well as analyses stratified by estrogen receptor status of breast cancer.We found that the genetically-predicted risk of schizophrenia was associated with increased breast cancer risk (under a random-effects model: odds ratio per 1 unit increase in log odds of schizophrenia = 1.04, 95% confidence interval: 1.02–1.06, Our findings implicate a modest increased risk for breast cancer in genetically determined schizophrenic females. Antipsychotic-induced hyperprolactinemia has been suggested as a risk factor for increased breast cancer risk in SCZ women, while other known breast cancer risk factors, including nulliparity, obesity, type-2 diabetes, alcohol dependence, smoking, and low physical activity, are more likely to be the cause of comorbidity . However, it is unknown whether there is a genetic effect of SCZ on breast cancer risk.Observational studies have suggested an increased breast cancer risk in female subjects with schizophrenia (SCZ) . Compared to traditional epidemiologic methods, MR is less prone to confounding effects due to the random assortment of alleles at conception. Recent large-scale genome-wide association studies (GWAS) have identified multiple genetic variants associated with complex human traits or diseases including SCZ ,7 and breast cancer –10, which enable MR analysis by using such genetic variants as IVs with an increased statistical power to detect potential causal associations of exposure with an outcome –13. Two-sample MR has become popular, as it exploits publicly available summary data of genetic instrument-exposure association and genetic instrument-outcome association in GWAS consortia from different samples of participants ,15.Mendelian randomization (MR), a design that utilizes genetic variants as instrumental variables (IVs), could potentially be used to estimate the unconfounded effect of an exposure/risk factor on an outcome  and the United Kingdom Clozapine Clinic (CLOZUK) , and one breast cancer GWAS data set from the Breast Cancer Association Consortium . These studies represent the largest sample size GWAS to date for each of the diseases in European descendants. The genetic effect of SCZ on breast cancer was further evaluated by estrogen receptor (ER) status of the cancer tissues.To address potentially biased association between SCZ and breast cancer risk due to unmeasured confounders, we conducted a two-sample MR study by analyzing publicly accessible summary meta-analysis results of two SCZ GWAS data sets, the Psychiatric Genomics Consortium (PGC2) 22.1,7. Summary associations of these SNPs with breast cancer risk were obtained from the latest GWAS by the BCAC .Single nucleotide polymorphisms (SNPs) significantly associated with SCZ risk were identified from the most recent largest-scale GWAS combing association results of PGC2 and CLOZUK p < 5 × 10−8) . The summary association data for each of the 179 SNPs were downloaded from the Data Repository website  of the Walters Group at the Cardiff University MRC Centre for Neuropsychiatric Genetics and Genomics. The sex-combined association summary statistics was selected as few sex-specific associated genetic variants have been reported , and there are no suggested sex differences in SCZ prevalence . To reduce potential violation of MR assumptions due to linkage disequilibrium (LD) of SNPs at a single locus , independent SNPs with LD r2 of less than 0.1 were selected based on the genotypic data of 503 individuals of European ancestry from the 1000 Genomes Project phase 3 dataset. A total of 176 SNPs remained after removing three SNPs  with r2 > 0.1 with another more significant index SNP located nearby  > 0.01) at 145 distinct genomic loci were identified to be significantly associated with disease risk (d nearby .http://bcac.ccge.medschl.cam.ac.uk/bcacdata/oncoarray/): 61,282 cases and 45,494 controls; the Collaborative Oncological Gene-Environment Study : 46,785 cases and 42,892 controls; and 11 other breast cancer GWAS: 14,910 cases and 17,588 controls) . For the 176 uncorrelated SCZ associated SNPs, summary breast cancer association data were retrieved from combined samples from the BCAC database (http://bcac.ccge.medschl.cam.ac.uk/bcacdata/oncoarray/gwas-icogs-and-oncoarray-summary-results/ ). To reduce distorted effects of genetic IVs, six horizontally pleiotropic SNPs  identified from the Mendelian randomization pleiotropy residual sum and outlier  test  were further removed. Finally, a total of 170 SNPs were selected to estimate the effect of genetically determined SCZ on breast cancer risk. MR was also performed after excluding six SNPs with imputation quality score r2 of less than 0.8 in the BACA controls. Characteristics and the summary association statistics of each of the SNPs are provided in The latest BCAC GWAS included 122,977 breast cancer cases and 105,974 controls of European ancestry from three datasets with different study designs and genotyping platforms  method , let x and y denote the exposure and outcome, respectively. The parameter α was used to quantify the causal effect of x on y. Let γi and βi denote effect-size estimates of the ith SNP on x and y, respectively, and let se (ßi) denote the standard error (s.e) of βi. Then the MR estimate associated with the ith SNP is αi = βi∕γi, and the corresponding variance of this estimate is1 . The weight of the ith MR estimate of α is defined as s.e. of the estimate is given by Q statistical analysis was used to test heterogeneity and the I2 statistic was used to estimate the amount of heterogeneity .As previously described for the IVW method . Finally, further MR was conducted to test the effect of SCZ on risk of ER-positive and ER-negative breast cancer.SCZ-breast cancer effect was also estimated using a weighted median method which allows up to 50% of genetic instruments to be invalid p < 0.05 was used to define statistical significance. All the MR analyses were conducted using the MR-PRESSO and MR-Base (http://www.mrbase.org/) “TwoSampleMR” packages  in R version 3.4.3 (http://www.r-project.org/).The effect-sizes for each meta-analysis are reported as the odds ratios (ORs) describing the effect of SCZ on breast cancer risk . A 3p = 5.6 × 10−5)  . Similar × 10−5) , as wellr2 < 0.8 .r2 of < 0.8 were excluded, the identified associations remained for both ER-positive  and ER-negative breast cancer   .4In this large-scale MR study in European female descendants, we estimated genetic influence of 170 independent non-pleiotropic SCZ-associated SNPs on breast cancer risk. Results from both the standard IVW random-effects and the weighted median models suggest a positive association between genetically determined SCZ and breast cancer risk. The association was also detected in both ER-positive and ER-negative breast cancer.. The most recent meta-analysis of 12 cohort studies with 125,760 female SCZ patients revealed a 31% increased breast cancer risk, although significant heterogeneity between studies existed . Antipsychotic-induced hyperprolactinemia, nulliparity, obesity, type-2 diabetes and unhealthy lifestyle behaviors  have been proposed for breast cancer risk factors in female patients with SCZ ; however, it is unknown what proportion of breast cancer risk variation is explained by these non-genetic factors. On the other hand, two recent studies suggested a nominally significant positive genetic correlation between SCZ and breast cancer (r = 0.14–0.16) 25. The horizontal pleiotropy of some genetic variants may account for this genetic association . In this study, we excluded six pleiotropic SNPs through MR-PRESSO outlier tests and still detected a significant weak genetic association. The modest effect from our analyses may be true, due to the low incidence of breast cancer in schizophrenic females , the low genetic correlation between these two diseases ,25, and the low proportion (29%) of genetic component of SCZ influencing breast cancer risk .A meta-analysis of 16 observational studies in 427,843 patients with SCZ showed a 25% increased co-occurrence of breast cancer  and breast cancer GWAS , found a significant genetic influence of SCZ on breast cancer risk. Second, the influence of SCZ on breast cancer risk was observed for both ER-positive and ER-negative diseases  in each of the GWAS was controlled using principal components during SNP-SCZ association analyses ,7. Third, the underlying biological mechanisms of increased breast cancer risk in female SCZ patients remain unclear. A previously proposed hypothesis of antipsychotic-induced hyperprolactinemia as the cause for breast cancer has been shown to be inconclusive since hyperprolactinemia has also been observed in antipsychotic-naïve first-episode patients and even in prodromal stages, and several prolactin-elevating antipsychotics have been shown to have cancer-protection mechanisms . On the other hand, enrichment of cell and tissue type-specific enhancers of SCZ-associated SNPs support a role for immune dysregulation , while a similar dysfunctional immune system hypothesis has been proposed for the pathogenesis of breast cancer . Further studies are warranted to clarify whether the SCZ-related immune system  or other biological mechanism(s) contribute to the development of breast cancer. Fourth, invalid or weak genetic instrumental variables may introduce biased effect in MR analyses since many of the SCZ GWAS-identified SNPs with association p < 5 × 10−8 from GWAS need to be further replicated in independent samples to avoid the winner’s curse bias or inflated effect sizes. For example, among 108 SCZ-associated loci from PGC2, 15 have not reached genome-wide significance in the combined PGC2 and CLOZUK samples . Fifth, results from the heterogeneity tests suggest a possible horizontal/ pleiotropic effect of the SCZ-associated SNPs, which could influence the effect size estimate. However, we excluded SNPs that are pleiotropic outlier SNPs using MR-PRESSO. In addition, LD score regression  with approximately 1,700 uncorrelated SNPs (r2 < 0.1) across the genome that were associated with SCZ at p < 1.0 × 10−4 in the PGC2 European participants ruled out a global pleiotropism between SCZ and breast cancer (posterior probability < 1%). Sixth, clinically observed increased incidence of breast cancer in female SCZ patients may be a result of surveillance bias. In other words, a closer clinical care of SCZ patients than other patients would possibly lead to an earlier diagnosis of breast cancer. MR approaches may not be able to deal with such bias. Seventh, it is unknown whether the MR detected SCZ-breast cancer association in European descendants could be generalizable to population of other ancestry. Lastly, MR analyses using genetic risk score method with individual genotype data and detailed breast cancer risk factors, such as nulliparity, obesity, type-2 diabetes, smoking, alcohol dependence, and low physical activity, are needed to clarify the genetic effect of SCZ on breast cancer.There are also some potential limitations in the present study. First, as SCZ is a binary exposure, the estimated effect on breast cancer risk from the random-effects IVW MR may still be biased 5Genetically determined schizophrenic females may have a modest increased risk for breast cancer.supplemental file