Breast cancer is the most common cause of cancer—related death among women. In this paper, we studied the variations in the trends of Chinese female breast cancer mortality by age, period and cohort from 1990 to 2009.The mortality data were collected from the Institute for Health Metrics and Evaluation. An age-period-cohort model and Intrinsic Estimator were used to estimate the age effect, period effect and cohort effect on the Chinese adult female breast cancer mortality risk.The age effect on Chinese female breast cancer mortality initially increased, but then declined, and showed a reversed “J” shape with age. The period effect of breast cancer mortality continued to rise with the time period and increased by 59 % from 1990–1994 to 2005–2009. The cohort effect showed that the mortality risk of Chinese females born after 1911 was on the decline and decreased by 2.2336 from 1911 to 1989. The change rate of the cohort effect on breast cancer mortality fluctuated regularly. Three accelerating decreases and three decelerating decreases were noted in the variation law of the change rate.The results of study show the increasing mortality trend of breast cancer in Chinese female from 1990 to 2009, and the breast cancer mortality risk decreased with birth cohort.The online version of this article (doi:10.1186/s12939-015-0211-x) contains supplementary material, which is available to authorized users. Cancer has become a serious public health challenge worldwide. As the most common cancer in females, breast cancer has an impact on the everyday lives of women and is a common cause of death. According to the Globocan  data pubMortality rate is one of the most important indicators for monitoring the health status of breast cancer patients. Breast cancer has been the main cause of death in many regions worldwide, and the mortality rates of breast cancer have increased among Chinese females. According to the results of three death cause surveys, the breast cancer mortality of female showed an upward tendency. The standard mortality for Chinese female increased 36.1 % from 1970s to 2005, while it decreased obviously in Europe and America developed countries.With the increasing breast cancer burden in China, the study on the trend of breast cancer mortality has become more and more. However, there are many studies failed to analysis the cohort effect or apply the flawed methods about the parameter estimation of Age-period-Cohort Model. For instance, Zheng Y  and Ma SIn this paper, we examined the trends in Chinese female breast cancer mortality by age, period and cohort. A statistical analysis of the breast cancer mortality of 20–79-year-old Chinese females from 1990 to 2009 was performed. The age effect, period effect and cohort effect were estimated by an Age-Period-Cohort (APC) model combined with the Intrinsic Estimator algorithm. APC modeling allowed us to use the present mortality rates to analyze the variations in the tendencies and the regular patterns of mortality in the past few decades or over the past century, even when data were missing or inaccurate.Studying the trends in Chinese female breast cancer mortality may reveal new information about the risk factors for breast cancer. The results of the period effect and cohort effect could reveal the relationship between social development and breast cancer burden.http://ghdx.healthdata.org/). The IHME is an independent global health research center at the University of Washington in the US. The IHME Global Health Data Exchange combines registry data, surveys, censuses and other health-related data to produce mortality estimates. The IHME includes many scientists from dozens of countries in publishing the Global Burden of Diseases, Injuries and Risk Factor Study. With reference to China, the data were collected from Vital Registration, the Ministry of Health, China Vital Statistics-Deaths, the Cancer Registry, and the WHO Mortality Database, among other sources. The Gaussian process regression (GPR) was used to adjust the raw data and derive trend estimates by the IHME. Therefore, the data are highly reliable.The national female breast cancer (coded in the ICD-10) mortality rates were extracted from the Institute for Health Metrics and Evaluation . The age-specific and period mortality rates were computed.The APC model represents a classic epidemiological method that can be used to extract information from cross-sectional data regarding historical changes in the morbidity and mortality risk, termed the cohort effect . As therFu  applied In this paper, all analyses were implemented using the Stata version 12.0 software program . Fitting deviance, the Akaike Information Criterion (AIC) and the Bayesian Information Criterion (BIC) were used to evaluate the model.The variation trends in the age-specific breast cancer mortality among Chinese females aged 20–79 during 1990–2009 are shown in Fig. The variations in the breast cancer mortality rates of different age groups during the decades from 1990–2009 are shown in Fig. The APC model was used to analyze the age-specific breast cancer mortality, and the age effect, period effect and cohort effect were calculated by the IE algorithm. The results of the analysis of breast cancer mortality are shown in Table RR = e[0.9254 − (−3.20)]) and 1.61 (RR = e[0.9254 − 0.4461]) compared with the groups of subjects 20–24 years old and 40–44 years old, respectively.According to the analysis of the age effect Table , the ageRR = e[0.3013 − (−0.1659)]), 1.53 (RR = e[0.3013 − (−0.1219)]) and 1.37 (RR = e[0.3013 − (−0.0136)]) compared with period group 1990–1994, 1995–1999 and 2000–2004, respectively. The period effect alone increased the breast cancer mortality risk by 59.55 % over a period of 20 years, indicating an annual average growth of 2.98 %.The period effect of breast cancer mortality showed a net increase of 0.4672 = [0.3013-(−0.1659)] from the period of 1990–1994 to the period of 2005–2009 (Table RR = e[−1.235 − 0.9986]) compared with the oldest birth cohort 1911–1919.The cohort effect of breast cancer mortality in Table According to the mathematical meaning of numerical differentiation, we calculated the change speed of the cohort effect by numerical differentiation. The differential value is positive if the mortality risk is increased, negative if the mortality risk is decreased and 0 if the mortality risk remains the same.As shown in Fig. As shown in Fig. The APC model and the Intrinsic Estimator algorithm were used to analyze the variation trends of breast cancer mortality among Chinese females aged 20–79 years during the period from 1990–2009 in this study. Because of the collinearity of three factors  and the un-identification problem, there are many statistical methods used to solve this problem, e.g., Constrained Generalized Linear Models, Two Factor Models, Nonlinear Models, Penalty Function Approach and Estimation Function, et.al. Compared with these methods, the IE algorithm could obtain the unique solution of parameters without any constrained conditions or new variable. In addition, the estimated values are interpreted more intuitively and unbiased. To verify the validation of IE estimates, Monte Carlo simulations are conducted for the IE and other conventional coefficients constrained approaches. It is proved that the MSEs of the IE estimates are much smaller and close to zero.The age effect of breast cancer mortality among Chinese females aged 20–79 years old essentially showed a reversed “J” shape with age. This trend indicated that the older the age, the higher the breast cancer mortality. Compared to the subjects 20–24 years old, the mortality risk of subjects 50–54 years old increased by 61.86 %, while the mortality risk of the patients 75–79 years old increased by 43.62 %.According to the analysis of the period effect on breast cancer mortality, there was a net increase of 0.4672 from the period from 1990–1994 to that from 2005–2009, indicating an annual average growth of 2.98 %. Such rapid growth may suggest that environmental deterioration and unhealthy lifestyle behaviors such as increased alcohol consumption, obesity, and a lack of physical exercise, increase the period effect of breast cancer mortality risk during these time periods , 16. In Although the cohort effect on the breast cancer mortality of Chinese females born after 1911 was on the decline, the change rate of the mortality risk fluctuated regularly. Three accelerating decreases and three decelerating decreases were noted for the change rate of the mortality risk. The accelerating decreases in the change rate represent improvements in the breast cancer mortality, while the decelerating decreases in the change rate represent a relative deterioration of breast cancer mortality. The three accelerating decrease started from 1926–1934 to 1931–1939, 1946–1954 to 1956–1964 and 1976–1984 to 1981–1989, respectively. The three decelerating decreases were from 1916–1924 to 1926–1934, 1936–1944 to 1941–1949 and 1961–1969 to 1971–1979, respectively.Changes in lifestyle and dietary habits may have led to the increasing trends in breast cancer mortality. Kaizer  analyzedOn the other hand, many pathological and epidemiological studies have found that benign breast lesions (BBL) also have a relationship with breast cancer . Liu repAdditionally, many studies have indicated that an early age at menarche, late menopause age and fertility are associated with breast cancer risk –28, and Thus, breast cancer screening, detection, and changes in dietary habits are associated with breast cancer risk , 33. In A major limitation of the present study was lack of analysis on incidence of breast cancer Chinese female. The incidence is one of the important factors which influenced the trend of breast cancer death. According to the Cancer Registry, the crude incidence of breast cancer for Chinese female increased 1.2–2.8 times, and the standardization incidence increased 4.0–7.3 times during 1988–2007 . Thus, aIn summary, although the cohort effect of breast cancer decreased, the mortality rate of breast cancer increased during the period from 1990–2009. The morality pattern of breast cancer in China can be explained by the period effect. The imperfect breast cancer screening, low detection rate and unhealthy dietary habits have likely all played an important role on the period effect of breast cancer mortality among Chinese females.


Breast MRI added to mammography increases screening sensitivity for high-risk women but false-positive (FP) rates are higher and the optimal screening schedule for coordination with mammography is unclear. We compare rates of FP MRI when studies were performed on two different schedules.High-risk women at the University of Vermont who had at least 1 MRI and 1 mammogram performed within one year between 2004–2012 were eligible for inclusion in this study. Screening was considered stacked if both studies were performed within 90 days and alternating if studies were 4–8 months apart. False positive was defined in one of three ways.137 women had screening which met inclusion criteria and 371 MRIs were reviewed. The FP rates were similar for the two schedules when considering BI-RAD 4, 5, 0 or biopsy as a positive test. FP rates were significantly higher for the stacked schedule  when considering BI-RADS 3-4-5-0 as positive test, due to the elevated rate of BI-RADS 3 assessments among stacked exams.False positive rates differ based on the type of exam (baseline or subsequent) and definition of positive but do not differ based on imaging schedule ; suggesting that women and their providers may choose the imaging schedule they prefer. This is significant as a randomized clinical trial comparing the two schedules is not likely to be performed, given the high cost and large number of women needed for such a study. The implementation of screening mammography was a major step in the fight against breast cancer, but several studies have demonstrated lower sensitivity of mammography in younger women  published recommendations for screening breast MRI in addition to mammography for high risk women which include; all women with a lifetime risk of more than 20% to 25% based on family history, women with BRCA mutation, first-degree untested relative of BRCA carrier, women with Li-Fraumeni syndrome and first-degree relatives, women with Cowden syndrome and first-degree untested relatives, and women who had radiation to chest wall between ages 10 and 30  has not been addressed. The above mentioned studies demonstrating the increased sensitivity when MRI is added to mammogram specified that imaging studies were done within a short period of time (on the same day or less than 90 days apart). There have been no studies comparing the two screening schedules directly. Identifying the optimal screening schedule may reduce the false positive rates and reduce unnecessary biopsies and imaging. The current study was undertaken to compare the false positive rates for screening breast MRI when imaging is done at the same time each year (a stacked schedule) compared to an every six month imaging  schedule.a. Two or more first-degree relatives with breast cancer or ovarian cancer. b. One first-degree relative and two or more second- or third degree relatives with breast cancer. c. One first-degree relative with breast cancer or ovarian cancer before the age of 50 years. d. One first-degree relative with breast cancer and one or more relatives with ovarian cancer. e. Two second- or third-degree relatives with breast cancer and one or more with ovarian cancer. f. One second- or third-degree relative with breast cancer and two or more with ovarian cancer. g. Three or more second- or third-degree relatives with breast cancer. h. One first-degree relative with bilateral breast cancer. Individuals with a known genetic abnormality of a breast cancer causing gene in themselves or a family member. Individuals with a prior breast biopsy showing atypical ductal hyperplasia or lobular neoplasia . Individuals with a Gail Model breast cancer risk of greater than or equal to 1.66% over the next 5 years or greater than 20% lifetime risk.Women enrolled in an Institutional Review Board (IRB) approved prospective study of women at moderate and high risk for breast cancer between 2004 and 2012 at the University of Vermont were the subject of this current study. To be eligible to participate in the IRB approved database participants must have an increased risk for developing breast cancer. Patients are identified as having an increased risk for developing breast cancer if they meet any one of the following criteria: A strong family history of breast  and/or ovarian cancer. Strong family history is defined as one of the following: To be included in the current study women must have had at least 1 screening breast MRI and 1 mammogram performed within 1 year. Women were excluded if they had a personal history of invasive breast cancer, had a diagnostic screening breast MRI  or were using chemoprevention. Medical records were abstracted for clinical, radiological, and biopsy data. One cycle of surveillance was defined as 1 MRI and 1 mammogram done within 1 year. Screening was considered stacked if both studies were performed within 90 days and alternating if studies were 4–8 months apart. Three definitions of a false-positive MRI were considered: 1) MRI result of BI-RADS 4, 5, 0 with no cancer diagnosis within 365 days; 2) BI-RADS 3, 4, 5, 0 with no cancer diagnosis within 365 days; and 3) benign breast biopsy after an MRI-based recommendation.Dynamic contrast enhanced MRI was performed according to standard techniques (which varied over the time course of the study) and interpreted by breast imaging radiologists with 1–12 years’ experience interpreting breast MRI. The original clinical reports were used in this study. The images were not re-analyzed for research purposes.The analyses were restricted to the 371 MRIs among 137 women which met the above inclusion criteria. Chi-square tests and Fisher’s exact tests were used to compare differences in assessments and false-positive rates between stacked and alternating MRI screens. All statistical analyses were performed using SAS Statistical Software .st, 2004 to March 31st, 2012 were reviewed. 440 women did not have a breast MRI as part of their screening, 16 women who had breast MRI performed to evaluate mammographic findings were excluded; an additional 6 women were excluded because they did not have an MRI and mammogram performed within one year. Therefore, 137 women met the inclusion criteria and are the subject of this analysis. See Figure The records of 599 women at increased risk of developing breast cancer and enrolled in the parent database at the University of Vermont from May 1Forty-five women had all screening cycles done on a stacked schedule, 52 women had all cycles done on an alternating schedule, while 40 women had cycles that were mixed with some on a stacked schedule and others on an alternating schedule. 371 screening breast MRIs were reviewed; 165 performed on a stacked and 206 on an alternating schedule. Table The false positive rate was first calculated for MRIs with BI-RADS 4,5,0 interpretations demonstrating a non-significant difference between screening on a stacked or alternating schedule   a rate of 6.1% (10/165) for the stacked group and 5.8% (12/206) for the alternating group. There was not a significant difference between false-positive rates based on having a benign biopsy for the stacked compared to alternating group (p = 0.92).Four breast cancers were detected in 137 women included in this cohort. Three were identified by MRI . There was 1 interval cancer in this cohort. Table In this retrospective evaluation of a prospectively gathered cohort we have shown similar rates of false positive studies regardless of the screening schedule or definition of a positive study. To our knowledge, this is one of the first studies to compare the two styles of screening in a prospectively gathered cohort and one of the largest series to examine the alternating schedule of mammogram and screening breast MRI. Le-Petross et al. reported their institutional practice of alternating studies and found a sensitivity of 92% and a specificity of 79%; similar to published series with studies performed annually  as highlighted in Table We did observe a significant difference in false-positive rates depending on the definition of a positive study . We found the highest false-positive rate when considering BI-RADS 3, 4, 5, 0 as a positive study (13.7%), with much lower rates of false-positive studies for BI-RADS 4, 5, 0 (7.8%) and for benign biopsy (5.9%). The higher rate when calling BI-RADS 3, 4, 5, 0 positive can be explained by BI-RADS 3 interpretations. In our cohort there were no cancers identified within one year of any BI-RADS 3 MRI. Others have shown similarly high rates of false positive screening breast MRI when including BI-RADS 3 interpretations as positive, with a range between 6.3 – 27% in published studies  screening only (Le-Petross et al. In conclusion, we have shown that the false-positive rates are similar for studies performed on either a stacked or alternating schedules regardless of the definition of a false-positive study. This finding and information from prior studies (Le-Petross et al.


Current understanding of cancer genomes is mainly “gene centric.” However, GWAS have identified some nongenic breast cancer susceptibility loci. Validation studies showed inconsistent results among different populations. To further explore this inconsistency and to investigate associations by intrinsic subtype  among Southern Han Chinese women, we genotyped five nongenic polymorphisms  using MassARRAY IPLEX platform in 609 patients and 882 controls. Significant associations with breast cancer were observed for rs13387042 and rs4415084 with OR (95% CI) per-allele 1.29 (1.00–1.66) and 0.83 (0.71–0.97), respectively. In subtype specific analysis, rs13387042  and rs4415084  showed slightly significant association with Luminal-A subtype; however, only rs13387042 was associated with ER−&PR−&HER2+ tumors , and none of them were linked to Luminal-B and triple negative subtype. Collectively, nongenic SNPs were heterogeneous according to the intrinsic subtype. Further studies with larger datasets along with intrinsic subtype categorization should explore and confirm the role of these variants in increasing breast cancer risk. Detection and characterization of the genetic diversity of disease-associated loci are a major emphasis of current scientific inquiry in cancer. Rapid technological advances have enabled us to explore the increasingly complex genetic architectures and their relationship to cancer. However, current understanding of cancer genomes is primarily a “gene centric” view . BecauseFocusing only on genic variants is obviously not a comprehensive strategy for research into the genetics of cancer, due to the fact that the majority lie in nongenic regions . ConsistAssociations between three nongenic loci SNPs and breast cancer risk have been independently replicated by subsequent studies in recent years among East Asians, Africans, and some other ethnic populations; however, a proportion of them have yielded conflicting or inconclusive results –9. The rIn addition, all four GWAS were conducted in European ancestry (EA) populations, who differ from women of other ethnic groups in certain aspects of their genetic architecture. In this regard, it is important to validate these findings in other ethnic populations and perhaps use the different linkage disequilibrium (LD) patterns observed in non-European ancestral population to refine associated genomic regions. In our previous studies –13, mostHerein, we evaluated the association of three nongenic loci with breast cancer risk in Southern Han Chinese women. Furthermore, the associations of these loci with four breast cancer subtypes defined by four markers (estrogen receptor (ER) status, progestin receptor (PR) status, human epidermal growth factor receptor-2 (HER-2) status, and Ki-67 expression status) were also evaluated. Without a doubt, this paper will expand and refine our previous reports on analyses mainly focusing on genic loci and thus make more definite conclusions than previous reports.Individuals included in the current analysis were Han Chinese women who participated in the Southern China Breast Cancer Genetics Study (SCBCGS) . The SCBOur previous study has shown the specific characteristics of the controls and cases by the intrinsic subtype . BrieflyFrom 2009 to 2013, we collaborated with other two research groups to start validating breast cancer susceptibility genes (including nongenic loci) in Chinese cohorts. As far, recent GWAS have identified more than 20 different intergenic loci associated with breast cancer risk, which can be viewed in the NHGRI GWAS Catalog. However, seven GWAS , 16–20 phigh), and (iv) Luminal-A (ER+ and/or PR+ and not HER2+ or Ki67high). The number of cases with above-mentioned tumor marker data available, the classification scheme we used based on combinations of the marker, and specific characteristics of the controls and cases classified according to the intrinsic subtype have been described in our previous reports [Four subtypes were constructed based on the receptor status of the primary tumor, specifically, (i) triple negative , (ii) ER−&PR−&HER2+ , (iii) Luminal-B  and 95% confidence intervals (95% CIs), based on unconditional logistic regression and adjusted for potential confounders including age, age at first full-term pregnancy, menopausal status, and hormonal therapy use [For each SNP, deviation of genotype frequencies in controls from the Hardy Weinberg Equilibrium (HWE) was assessed by a goodness-of-fit rapy use . AnalyseP < 0.05 was considered statistically significant. Statistical analysis was performed using SPSS version 19.0  unless otherwise specified.Stratified analysis according to the 4 breast cancer subtypes was additionally conducted. To correct multiple testing, we estimated the adjusted significance by applying the Bonferroni correction for all the SNPs tested in the analysis. All statistical tests were two-sided, and P < 1 × 10−4) and thus was excluded from the subsequent analyses  and JPT (Japanese) population. All the observed genotype frequencies were found to be in agreement with HWE in the controls except for rs13281615, which deviates from HWE  was found for rs13387042-A variant. Significant results were also observed using recessive  and codominant genetic model . After adjusting for potential cofounders including age, age at first full-term pregnancy, menopausal status, and hormonal therapy use, these findings persisted   . FurtherP = 0.03), dominant , and overdominant models  with an A-allelic trend of OR = 1.55 (95% CI = 1.00–2.40) after adjusting for potential cofounders  of rs13387042 significantly increased breast cancer risk under the codominant  .For Luminal-B and triple negative breast cancer cases, however, no significant associations were found with the four nongenic variants under all five genetic models , suggesting that the search for functional polymorphisms should extend beyond genic regions .Furthermore, studies trying to investigate the association between common nongenic polymorphisms with breast cancer susceptibility have yielded inconsistent results . There aThus, present study investigated whether 5 common nongenic SNPs located in “gene desert” regions were associated with specific tumor subtypes defined by four markers . This will be the first Chinese study to validate and provide convincing evidence for heterogeneity in the strength of the associations of nongenic susceptibility loci with respect to the risk of tumor subtypes. Furthermore, stratification of tumors also provided further insights into etiological heterogeneity.First, this study confirmed that two nongenic SNPs (rs13387042 and rs4415084) were significantly associated with increased risk of breast cancer. Rs13387042 was first identified as a breast cancer susceptibility SNP in two GWAS conducted among Europeans . SignifiFor rs4415084, the association with breast cancer has been evaluated by three studies in Chinese since it was first identified through GWAS approach ; howeverFurther subtype stratification analyses showed that rs13387042 and rs4415084 marginally associated with Luminal-A breast cancer even after adjusting for potential cofounders including age, age at first full-term pregnancy, menopausal status, and hormonal therapy use . HoweverFinding the potential biological functions of such SNPs can be an important step towards further study. However, we identified that 2q35-rs13387042 and 5p12-rs4415084 are located in a 90-kb and a 100 kb LD block containing neither known genes nor noncoding RNAs, respectively. Furthermore, both SNPs are located more than 100 kb from the nearest gene: TNP1 and MRPS30, respectively. The causal variant in this region has not been determined. Thus, functional studies in these regions are likely to lead to a better understanding of mechanisms of carcinogenesis and progression of breast cancer. In addition, the ORs we obtained were small with narrow CIs indicating that when considered alone as a genetic factor, both polymorphisms have a very small effect on susceptibility to breast cancer.P > 0.05). Thus, larger sample sizes could help improve the power and ensure the correct conclusion regarding whether these SNPs are associated with specific breast cancer subtypes.A strength of our study was that ER, PR, HER-2, and ki-67 status were all assessed using the same processing protocols and criteria for pathology review for all cases. However, three important limitations of this study must be considered. First, we could not confirm that other SNPs lacked an association with specific breast cancer subtypes because we had limited samples and a lack of power to detect a true association. For example, though current study has sufficient power (>90%) to detect a log-additive OR of 1.30 with allele frequencies >27%, the exact powers to detect a log-additive OR of 1.30 of four selected SNPs  with Luminal-B subtypes using the MAF in Additionally, we cannot rule out that other nongenic loci may be risk factors for breast cancer and specific subtypes because there may be different functional variants among different populations and specific subtypes. For example, one GWAS among Chinese women by Zheng et al. in 2010 identified a novel SNP rs2046210 at a nongenic loci of 6q25.1 exhibiting strong and consistent significant association with breast cancer across all three stages in Chinese women only . DiffereThird, misclassification of breast cancer subtypes is likely to be independent of susceptibly loci and thus would tend to underestimate association strengths rather than create spurious associations . For exaCollectively, our study demonstrated a marginally significant association of nongenic SNPs with breast cancer risk in Southern Chinese Han population and added evidences for differential susceptibility according to intrinsic subtype. Moreover, further investigation of larger data sets along with intrinsic subtype categorization and functional studies are required to determine how and to what degree these variant gene forms are influencing breast cancer pathogenesis.Supplementary materials included two tables showing the results from both the univariate and multivariate logistic regression analyses on the association between four nongenic polymorphisms and Luminal-B/triple negative subtypes.


Role of hair dyes in the etiology of breast cancer has occasionally raised concern but previous research has concluded with mixed results. Remnants of prohibited aromatic amines have been found in many hair dye products, and elevated levels of DNA-adducts of these amines have been detected from breast epithelial cells of hair dye users. However, the IARC working group has concluded that there is inadequate evidence for carcinogenicity of personal hair dye use and limited evidence in experimental animals for carcinogenicity of hair colorants.We investigated whether the use of hair dyes is associated with breast cancer risk in women. The study design was a retrospective population-based case-control study in Finland, with a self-administered questionnaire from 6,567 breast cancer patients, aged 22–60 years and diagnosed in 2000–2007, and their 21,598 matched controls. We report odds ratios (OR) with 95% confidence interval (95% CI) from a conditional logistic regression model applied to the frequency matched sets of cases and controls. Bias-adjusted odds ratios from the sensitivity analysis are also presented.P: 0.005). Bias-adjusted odds ratios varied between 1.04 and 2.50.After adjusting for potential confounders, the odds of breast cancer increased by 23%  among women who used hair dyes compared to those who did not. In women born before 1950 an increase of 28% was noted . We also observed a significant trend between the OR and cumulative use of hair dyes (Our results suggest that use of hair dyes is associated with breast cancer incidence. The impact on public health may be substantial due to vast popularity of hair coloring in modern societies. It should be noted that regardless of all efforts, a possibility of bias cannot definitively be ruled out and use of a prospective design is warranted. Based on the present results, it may be concluded however that safety of hair dyes in relation to breast cancer cannot yet be fully acknowledged and lack of external safety assessment within the cosmetics industry is of major concern. It has been suggested that certain chemical compounds, especially aromatic amines that are often present in commercial hair dyes and bleaches, may play a role in the etiology of some human cancers. Research results have though been inconclusive. Accordinth century, before which natural dyes, such as henna dominated. In the 1970 and 1980’s, a variety of new hair dye substances were brought to the market, while at the same time concerns were raised on the safety of certain dyeing chemicals. This led to banning of several potential carcinogenic substances in the EU, but not in the US [Hair dyes can roughly be categorized as permanent, oxidative hair dyes and semi-permanent and temporary dyes, the latter two being mainly non-oxidative. Permanen the US .P-Phenylenediamine (PPD) is among the most commonly used hair dye compounds . It is hThe mechanism of a possible association between hair dye use and breast cancer, and most specifically of the potential tumorigenesis induced by 4-ABP, is not clear. 4-ABP has been suggested to have an ability to produce mutations in the human genome. KnowingWe investigated the relationship of personal hair dye use and occurrence of breast cancer in a population-based series of some 6 800 breast cancer cases and 21 600 controls. The main objective was to determine whether the use of hair dyes is associated with the risk of breast cancer.st January 2000 and 31st December 2007 were considered eligible (N = 14 815). Age-matched controls were sampled from the central population register (N = 64 353). For the purpose of this study, re-matching by birth year was conducted to match the cases and controls in an exact ratio of 1:4 and the surplus of controls and cases were randomly excluded from the appropriate birth year cohorts.The study design was a retrospective, frequency matched population-based case-control study with a questionnaire conducted in 2009. Case ascertainment was done in December 2008 from the population-based, nationwide cancer registry, covering close to 100% of solid tumors . All womOf the 14 815 breast cancer cases identified from the cancer registry, 1550 had died before the start of the study, leaving 13 265 cases in the sample. After re-matching the cases and controls by birth year, 10 448 women with breast cancer were left in the data. Of these, 951 were excluded due to any previous malignancy, leaving 9 537 cancer cases for the study, out of which 6567 responded to the questionnaire (69%). With respect to morphology of the cancers, 5248 (80%) were ductal carcinomas, of which 4758 (91%) invasive and 1022 (16%) lobular carcinomas, of which 1002 (98%) invasive. The remaining 4% (N = 297) included cases of medullary, mucinous, tubular, and other infrequent types of breast cancer, or cases where morphology could not be clearly specified. From all breast cancer cases in the study, 99% were based on histological confirmation.The questionnaire Women’s Health and Use of Hormones was initially developed to address the association between the use of hormonal intrauterine device and breast cancer  and it aThe exposure of primary interest in this study was the use of hair dyes. The respondents were asked to estimate the cumulative number of hair dye episodes during life, age at first use and the types of dyes used. Regarding the total number of hair dye episodes during life, the response options were categorized as: Never, 1–2 times, 3–9 times, 10–34 times, 35–89 times or 90 times or more. In a pooled analysis, women reporting using hair dyes ‘Never’ or ‘1–2 times’ in their lifetime were classified as never-users, all other categories counting as ever-users. Age at first dye was categorized as: Under 20 years of age, 20–29 years, 30–39 years, and 40 years or older. The different dye types were defined as: ‘Temporary’ = a color that rinses off at first or few washes, ‘Semi-permanent’ = a color that rinses off after several washes, ‘Permanent’ = a color that does not wash off, ‘Bleach’ = the hair was bleached before coloring and ‘Partial’ = the hair was only partially dyed, e.g. highlighted. The frequency of dyeings in each of the type-specific categories was classified as Never, Rarely, Quite Often, Often.We report odds ratios (OR), with their 95% confidence intervals (CI) from the conditional logistic regression model applied to frequency matched study design. Potential confounding factors, including parity, age at first birth, family history of breast cancer, menarche age, use of hormonal contraceptives, physical activity, alcohol use, BMI and education were included in the multivariate adjusted model, as suggested by the step wise model search. We tested the trend in the log-ORs (dose-response) of the number of hair dye episodes and the odds of breast cancer by treating the number of episodes as a continuous variable in the logistic regression. Attributable fraction in the exposed represents the magnitude of the role of hair dye use in breast cancer risk in the exposed and was calculated with a formula presented by Greenland ((OR-1)/OR) x 100) . To idenOwing to comprehensive cancer information from the population based cancer registry in Finland, the coverage of cancer diagnoses was close to complete  and the The data was analyzed using R, version 3.1.1., with packages Epi (1.1.67), car (2.0–22) and Survival (2.37–7). The sensitivity analysis was performed with Stata version 12, using the Episensi-command, as introduced by Orsini and colleagues .The study was approved by the ethical committee of HUS  and permission for data linkage was obtained from the National Institute of Health and Welfare . Permission to contact the patients was issued by the senior physician of the appropriate hospital. The aims and objectives of the study were explained at the cover letter of the questionnaire, and returning of the filled questionnaire was considered as an informed consent.As of the controls, 41 978 subjects remained in the sample after the re-matching, out of the 64 353 originally sampled. Of these 23 114 responded to the questionnaire (55%). A previous malignancy was reported by 1516 controls and these were excluded, leaving 21 598 controls in the analytical data set.Distribution of the diagnostic age did not differ between the cases who answered to the questionnaire and those who did not, being 52 years in both groups. Median age at the time of the questionnaire was 57.5 years among the responded cases as well as controls. As expected, cases had a higher response rate (69%) than the controls (55%). Age distributions are presented in Prevalence of other breast cancer risk factors according to hair dye use (24 479 users and 3 316 non-users) are shown in P = 0.005). Early age at first dye (20–29) was associated with higher odds of breast cancer when compared to those started at 40 years of age or later . The association was not, however, seen in those with a first dye episode before the age 20 . In a pooled estimate (starting age <30 vs. ≥30), an increase of 7% was observed  among women who had started using hair dyes before the age 30.The odds of breast cancer was significantly increased , when comparing ever vs. never users of hair dyes after adjusting for other risk factors . ConsideRegarding the different types of hair dyes, the odds ratios were increased with all types, when compared to non-hair dye users. The highest estimates were obtained for women who reported to have used temporary and/or semi-permanent dyes, with 32% and 31% increase in the odds of breast cancer , respectively.When including only invasive breast cancers in the analysis, a 21% increase in the estimated odds ratio was noted . In age group specific analysis, the odds ratio regarding ever vs. never use of hair dyes was the most increased in women born before 1950 . Furthermore, a substantial amount (19%) of the new breast cancer cases in women 60 years of age or less can potentially be attributable to the use of hair dye products.The estimates did not significantly vary between different types of dyes. Most interestingly, temporary and semi-permanent dyes seemed to have greatest impact in the odds of breast cancer. Permanent hair colours containing higher concentrations of intermediates and oxidative agents have previously been thought to possess the most potentially hazardous effects. Nevertheless, many of the modern semi-permanent dyes contain a peroxidising agent and may thus be considered to act as permanent dyes with lower oxidative agent concentrations. Also, semi-permanent colours may contain potentially carcinogenic substances, as many of them contain an azo bond that after cleavage may result into the release of aromatic amines . Even thP = 0.024) also suggests that exposure over a long period of time carries a greater risk than short exposure.In a pooled analysis comparing ever and never-users of hair dyes, the odds ratio was the highest in women born before 1950. This appears logical as they have had a possibility to cumulate more hair dyeing episodes than their younger peers, for whom we might not yet see the possible effect of hair dye use in breast cancer incidence. Odds ratios for cumulative hair dye use, however, were the highest among women born between 1950 and 1959. If there is a causal association between hair dye use and breast cancer and the length of the induction period is assumed to be some 20–25 years, with our design, we are more likely to catch cases in women of that age group. Cases born earlier or later than this, whose disease might have been influenced by hair dye use, have already got their diagnosis before our ascertainment period 2000–2007, whereas the youngest cohort is still at risk. P-value from the likelihood test on the heterogeneity between odds ratios for different age groups  0.86 for duration of hair dye use from two telephone interviews one year apart and the coefficients for cases and controls being almost similar .It is still evident that we miss out cases with most aggressive types of cancer due to retrospective design. However, given the relatively similar diagnostic age distribution and the high overall user prevalence of hair dyes, it is unlikely that missing of these cases would largely bias the results. Also, results from the analysis including only cases from the last diagnostic years suggest that recall bias is does not play a major role in the estimations. Concerning the potential role of national population based mammography screening, while 89% of the cases diagnosed before the age of 60 years had had their first mammogram before the diagnose, some 87% of the controls aged < 60 years at questionnaire had done so, suggesting no differences between cases and controls in terms of screening attendance.For further data-validation, we compared the distributions of age and education in the study population to the figures obtained from the official statistics representing the general population ,28. QuesTo address for the role of recall bias, we estimated the level of differential misclassification of the exposure. Even though we assumed there not to be major differences between cases and controls in reporting whether or not they have ever used hair dyes, it is possible that more unexposed cases have falsely classified themselves as exposed if they believed there to be a relationship between hair dye use and breast cancer. Thus in the sensitivity analysis, the sensitivity was set to 90% for both cases and controls, whereas specificity among the cases was set to 80% and to 90% regarding controls. The observed bias-adjusted odds ratio of 2.50 and 54% downward bias imply that the results obtained in this study are highly sensitive to differential misclassification of the exposure. As stated, however, recall bias is not expected to have major impact in reporting ever vs. never use of hair dyes, whereas the situation regarding the number of dye episodes and different dye types is likely to be different and the level of uncertainty could be higher.The response rates in the questionnaire were 69% in cases and 55% among controls. Based on this, we set the response probabilities with respect to hair dye exposure status in the sensitivity analysis to be 0.8 as for the exposed cases and 0.6 regarding non-exposed cases and correspondingly 0.6 as of the exposed controls and 0.5 as of the non-exposed controls. The probability was assumed to vary more among the cases whereas controls were likely to be more homogenous in responding hair dye-related questions, regardless of their exposure status. The estimated adjusted OR (1.04) implies that even if the response activity between the cases and controls and between the exposed and unexposed was assumed to be rather heterogeneous, the direction or the magnitude of the observed association does not majorly change.As for uncontrolled confounding, socio-economic status was considered to be the most probable source of such bias in our questionnaire. According to official population statistics , on averThere has been evidence on current commercial hair dyes containing 4-ABP and contaminated PPD has been speculated as the source of it. In 2003, Turesky et al.  found adRisk assessment in cosmetic industry is still largely self-regulated and lacks independent evaluation. Safety reports are often provided by the stakeholders of the cosmetic industry . ConsideOur results suggest that increasingly popular use of hair coloring products may be substantial in the etiology of new breast cancer cases. The study subjects, being permanent residents of Finland, were likely to be mostly of Caucasian race. Considering the fairly blonde and homogenous Finnish population, the results presented here may only be generalised to other western societies with Caucasian majorities. Hair coloring habits and products in terms of dye types, colors, and dye frequency are likely to differ between the cultures and ethnicities.Even if the excess relative risk of breast cancer due to hair dye use is likely to be small at the individual-level, taken the prevalence of the exposure into account, its impact on public health can be considerable. We, however, acknowledge the limitations in retrospective study design and further research with prospective design is warranted before making conclusive arguments on the risks of hair dye use.S1 Funding Statement(DOCX)Click here for additional data file.S1 STROBE Checklist(DOCX)Click here for additional data file.S1 Supporting Information(PDF)Click here for additional data file.S2 Supporting Information(PDF)Click here for additional data file.S1 Appendix(DOCX)Click here for additional data file.


ESR1; 6q25 region). The minor allele for this variant is strongly protective (rs140068132: odds ratio (OR) 0.60, 95% confidence interval (CI) 0.53–0.67, P=9 × 10−18), originates from Indigenous Americans and is uncorrelated with previously reported risk variants at 6q25. The association is stronger for oestrogen receptor-negative disease  than oestrogen receptor-positive disease  and is also associated with mammographic breast density, a strong risk factor for breast cancer (P=0.001). rs140068132 is located within several transcription factor-binding sites and electrophoretic mobility shift assays with MCF-7 nuclear protein demonstrate differential binding of the G/A alleles at this locus. These results highlight the importance of conducting research in diverse populations.The genetic contributions to breast cancer development among Latinas are not well understood. Here we carry out a genome-wide association study of breast cancer in Latinas and identify a genome-wide significant risk variant, located 5′ of the Estrogen Receptor 1 gene ( Genome-wide association studies (GWAS) have revealed gene variants associated with breast cancer, but their association with breast cancer development in Latinas is not clear. Here, the authors carry out a GWAS of breast cancer in Latinas and identify a significant protective variant of Indigenous American origin in the 6q25 region. Breast cancer incidence varies substantially across racial and ethnic groups in the United States. The age-adjusted incidence of breast cancer in US European Americans and African Americans is 133.4 and 121.4 , respectively, whereas US women of Latin American origin have an incidence of 90.8 .Since 2007, breast cancer genome-wide association studies (GWAS) have identified ~80 loci with small to moderate effects on risk (odds ratios (ORs) ranging from 1.05 go 1.53)678910111213141516171819202122232425262720252627102We initially performed a GWAS of Latina women from the San Francisco Bay Area including 977 cases and 722 controls, from the San Francisco Bay Area Breast Cancer Study (SFBCS), the Northern California site of the Breast Cancer Family Registry (NC-BCFR) and the Genetics of Asthma in Latino Americans . We also conducted a GWAS of 520 cases and 2,491 controls from the Multiethnic Cohort (MEC). After imputation, the analysis of the San Francisco study, which used an Affymetrix 6.0 array, included 7,402,011 markers and the MEC, which used a combination of Illumina 1 and 2.5 M arrays, included 9,031,188 markers.TOX3 gene, a previously reported breast cancer risk locus at 16q12.1 , P=3 × 10−9; P heterogeneity=0.24). The strongest associated variant outside the TOX3 region was variant rs147157845, located ~50 kb upstream of the ESR1 gene within a second known breast cancer risk locus at 6q25 (OR: 0.59 (95% CI: 0.50–0.71), P=1.5 × 10−7; P heterogeneity=0.47; imputation information co-efficient=0.92; Fig. 1). The quantile–quantile (Q–Q) plot and the corresponding genomic inflation factor showed that adjustment by the first 10 principal components dealt appropriately with issues of population structure  in the replication sample (r2=0.97). For further validation, we tested the association of the rs140068132/rs147157845 SNPs with breast cancer risk in a sample of 546 Colombian women with breast cancer and 440 Colombian women without breast cancer, which also showed a strong association, and in Latinas from the Women’s Health Initiative (WHI) SHARe Study , which replicated both the magnitude and direction of the associations (We selected 14 single-nucleotide polymorphisms (SNPs) with n sample . Variantciations .P value of 0.03 in the Latinas and the direction of the OR was concordant with that previously reported The rs140068132/rs147157845 SNPs are relatively common in Latin American populations  but are absent in Europeans and Africans, and they have a very low frequency in East Asians . Neither1218P values in the sequencing data . Furthermore, in conditional analyses with the full data set, they were all nonsignificant in models that included rs140068132. In a previous admixture-mapping analysis that included a subset of these samples, higher Indigenous American ancestry within the 6q25 locus was associated with lower risk of breast cancerWe sequenced a 245-K region  at 6q25 in 451 cases and 456 controls from the MEC and did not identify any new variants  that were associated with breast cancer. We did find three variants  that had more significant ing data . HoweverP heterogeneity=0.01; In analyses by oestrogen receptor (ER) status, the associations with variants rs147157845 and rs140068132 were stronger for ER− disease versus ER+ disease . The mean density among control women homozygous for the rs140068132 common allele (AA) was 16% , while among women homozygous for the protective allele (GG) the mean density was 8%  from the Mexican study for whom mammographic density measures were available. In multivariate models, we found a significant association between mammographic density and the variants at 6q25 among the 809 controls  had ORs that were directionally concordant with those previously reported  in ENCODE data including ESR1 gene and breast cancer risk. The minor allele is protective: the odds of having breast cancer decrease by a factor of 0.60 per allele. We also found that the minor allele is more protective against ER-negative disease and that it is associated with decreased mammographic density. The rs140068132/rs147157845 SNPs are relatively common in Latin American populations, ranging between 5 and 15% depending on the proportion of Indigenous American ancestry of the region but are rare (<2%) or absent in other groups. These variants were not in LD with the index variants reported in Asians and Europeans, which suggests that the newly discovered SNPs represent a novel signal that is specific to populations with Indigenous American ancestry.We performed a GWAS for breast cancer in Latinas and identified an association between two linked variants within the 6q25 region, 5′ of the Previous studies have reported some risk variants at 6q25 to be more strongly associated with ER-negative disease720We have previously conducted a breast cancer admixture-mapping analysis, which showed that higher Indigenous American ancestry within the 6q25 locus was associated with lower risk of breast cancerHigh mammographic density is one of the strongest risk factors for breast cancer. Some of the SNPs associated with breast cancer risk have also been associated with breast density394041in vitro assays (EMSA) to help fine map and assess functionality. The sequence data did not identify any novel SNP in the region that could explain the association. Given that the rs140068132 SNP is located within the binding site of multiple transcription factors, we conducted EMSA assays to evaluate whether the two alleles at this position had differential binding affinity to nuclear protein. Results clearly showed that the protective G allele had a reduced binding affinity to nuclear protein compared with the A allele. While our work suggests that the A/G SNP at rs140068132 has functional relevance, further work will be necessary to understand the exact mechanism by which rs140068132 confers decreased breast cancer risk.We used both sequencing and In summary, in this GWAS of breast cancer in Latinas we report a risk variant at the 6q25 locus that, to our knowledge, represents the strongest association effect size on breast cancer for a common variant reported to date. The rs140068132 variant is limited to populations of Indigenous American ancestry, explained at least part of the previously reported association between breast cancer risk and genetic ancestry at the 6q25 locus in Latinas and may partially account for the lower incidence of breast cancer in this population. Overall, our findings highlight the importance of conducting genetic studies in non-European ancestry populations. Additional larger efforts in minority populations may reveal novel variants and loci contributing to complex traits.All participants provided written informed consent and the studies were approved by local Human Subjects Committees: The Fred Hutchinson Cancer Research Center IRB , Comité de Ética en Investigación (CEI), Ethics Committee of the University of Tolima, Cancer Prevention Institute of California IRB, University of Southern California IRB and the University of California San Francisco IRB.The following studies provided samples for the discovery GWAS:SFBCS: The SFBCS is a population-based multiethnic case–control study of breast cancer43BCFR: The BCFR is an international, National Cancer Institute (NCI)-funded family study that has recruited and followed over 13,000 breast cancer familiesMEC: MEC is a large prospective cohort study in California (mainly Los Angeles County) and HawaiiGALA1: GALA1 is a family-based study (including children with asthma and their parents) of pediatric asthma in Latino AmericansIn order to replicate the top associations from the discovery GWAS, we analysed multiple independent samples from the following studies:The Mexico Breast Cancer Study: This study is a population-based case–control study of breast cancer conducted in Mexico City, Monterrey and VeracruzColombian Study of Environmental and Heritable Causes of Breast Cancer (COLUMBUS): COLUMBUS is a population-based case–control study of breast cancer conducted in four cities: Bogota, Ibague and Neiva, from the Central Colombian Andes region, and Pasto, from the Colombian South. Incident cases with invasive breast cancer aged 18–75 years have been recruited in two population registries and two large cancer hospitals. Recruitment started in 2011. Cancer-free controls were recruited through the same institutions and were matched on education, socioeconomic status and local origin using a genealogical interview. In the current study, we genotyped DNA samples from 546 cases and 440 controls.WHI SNP Health Association Resource (WHI SHARe): WHI is a long-term national health study that focuses on understanding risk factors for common diseases such as heart disease, cancer and fractures in postmenopausal women. A total of 161,838 women aged 50–79 years were recruited from 40 clinical centres in the United States between 1993 and 1998 refs , 50. Med51The SFBCS, NC-BCFR and GALA1 samples were genotyped with the Affymetrix 6.0 array according to the manufacturer’s instructions in the Laboratory of Esteban Gonzalez Burchard at UCSF. The MEC samples were genotyped with the Illumina Infinitum 660 W-Quad or the Omni 2.5 array in the Genomics Center at USC and at the Broad Institute .Before imputation, we excluded 15 cases and 30 controls from the SFBCS/NC-BCFR/GALA1 set that had a genotyping call rate <95% or showed either known or cryptic relatedness. We excluded 26 cases and 8 controls from the MEC because of unexpected relatedness. The final analysis included 1,497 cases and 3,213 controls  and 3,011 from the MEC ).A scatter plot of the first and second principal components estimated for the US Latina samples included in the discovery phase of the study showed the expected distribution for this population, with most samples spreading between the European and Asian axes (and beyond the Asian cluster towards what would be the Indigenous American cluster) and a smaller proportion of samples deviating towards the African cluster .www.1000genomes.org) were used as the reference data set. These samples are from African, African American, Asian, Caucasian and Native American populations. We excluded SNPs with an information coefficient value <0.5 and minor allele frequency <1%. For markers in the MEC data, we conducted additional stringent quality-control analyses to exclude SNPs with different minor allele frequencies in controls typed on or imputed from different genotyping platforms. SNPs that exhibited differences in minor allele frequencies between the controls genotyped with the Illumina Infinitum 660 W-Quad or Omni 2.5 M platforms at P<0.01, and/or had ORs >10 or <0.1 were excluded. The final GWAS analysis included 7,229,558 SNPs.The discovery GWAS included genotyped as well as imputed SNPs for better coverage. Sample genotypes were phased and missing markers were imputed using the software IMPUTE2 ref. . Phased P value <5 × 10−7; (3) SNPs that have not been previously associated with breast cancer risk; and (4) when multiple SNPs were in high LD (r2>0.8), one or two with the lowest P value were selected for genotyping.SNPs were selected for replication in an independent sample of Mexican women according to the following criteria: (1) the polymorphic site was an SNP or captured by an SNP, as opposed to insertion/deletion; (2) A total of 14 SNPs were selected for replication. Four SNPs failed during assay design. Genotyping for the replication of 10 SNPs was completed using Sequenom iPLEX assays run on the MassArray Analyzer 4 platform at the University of Minnesota Genomics Center. One SNP failed the experimental assay and was excluded from the analysis. Each sample plate included one to three duplicates with a replication genotyping concordance of 100%. Two SNPs had a call rate of 99.7% and the remaining seven SNPs had a call rate of 100%. We excluded all individuals with any missing genotypes from further analysis (six cases and six controls). The final analysis included 977 cases and 1,158 controls. Genetic ancestry was estimated for all Mexican samples using a previously described panel of 106 ancestry informative markersSamples from COLUMBUS were genotyped for rs140068132 and rs14757845 using the KASP genotyping technology following the manufacturer’s instructions. Samples were genotyped in 384-well plates that contained positive genotyping controls for the three genotypes and two duplicates. The call rates for rs140068132 and rs14757845 were 98.0% and 98.2%, respectively. The final analyses included 546 cases and 440 controls. Association testing and meta-analyses were carried out with PLINKWe sequenced the ESR1 region at 6q25 in 451 breast cancer cases and 456 controls from MEC as part of a multiethnic targeted sequencing project of known breast cancer GWAS loci. Region boundaries were defined by nearest recombination hotspot downstream and upstream from the original GWAS signal (rs2046210) as identified using the HapMap CEU population. Briefly, 12 GWAS-identified regions covering 5,500 kb were hybrid-captured and sequenced. Sequencing was performed at the Broad Institute and details of the sequencing method have been described elsewhere60The sequence data at 6q25 encompassed 245 K (positions: 151765132 to 152010131). Of a total of 4,936 variants observed, 443 had a minor allele frequency of >0.01.P values for heterogeneity.We used logistic regression models to estimate the association between SNPs and breast cancer risk. ORs were estimated for the variant allele based on a log-additive model and adjusted for the first 10 principal components. PLINK version 1.06 ref.  was usedP value lower than 5 × 10−8.In order to use a systematic approach to analyse the replication of previously reported associated variants, we decided to only include previously published SNPs that were registered in the Catalog of Published Genome-Wide Association Studies compiled by the National Human Genome Research Institute. In addition, we used a restriction criteria of Replication analyses of newly discovered variants in Mexican women, Colombian women and in Latinas from WHI were conducted using logistic regression models. The analysis in Mexicans was adjusted for age at diagnosis and global genetic ancestry. For the WHI samples, genotypes for the rs140068132/rs147157845 SNPs were available from genome-wide genotypes that were generated as part of the WHI SHARe GWAS. The WHI analysis included adjustment for principal components 1 to 4, region and age at diagnosis. The Colombian samples included women from two different regions  who were analysed separately and were combined in a meta-analysis using the inverse-variance method. The final meta-analysis with all studies was conducted using the same method.Genome-wide association analyses were performed for cases versus controls as well as for ER-negative (ER−) and ER-positive (ER+) cases versus controls. Among the MEC cases with available ER status, 303 were ER+ and 108 ER−. Of the SFBCS/NC-BCFR cases, 505 were ER+ and 185 ER−. The analyses by hormone receptor status were based on 808 ER+ and 293 ER− cases (303 ER+ and 108 ER− from MEC and 505 ER+ and 185 ER− from SFBCS/NC-BCFR).We used logistic regression to evaluate the effect of global and locus-specific ancestry on breast cancer risk when the SNPs rs140068132/rs147157845 were included in the model. We also included the first 10 principal components, age and study as covariates.We used linear regression to evaluate the association between the rs140068132/rs147157845 polymorphisms and percent breast density among controls from the Mexican study. Percent mammographic density was log-transformed in order to obtain a distribution that would more closely approximate normality. We included age, body mass index, height, parity, breastfeeding, Indigenous American ancestry and African ancestry as covariates. These analyses were conducted with the STATA 12.1 softwareENCODE: The UCSC genome browser (genome.ucsc.edu) was used to get an overview of the genetic architecture surrounding our SNPs of interest, and specifically whether the SNPs fell within TFBSs determined by ENCODE ChIP-seq data.Homo sapiens sequence and bioinformatically predict putative transcription factor sites to which our SNP was critical. We took significant putative sites to be E value <15.MAPPERPercent mammographic density measures and potential confounder variables  were available for 1,113 (304 cases and 809 controls) women from the Mexican study. Information on covariates was obtained by questionnaire. Mammograms from cases were collected from participating hospitals; those from controls were performed at the same hospitals. Craniocaudal views were digitized using an Astra 2400S scanner . A single observer measured mammographic density using Mamgr, a computer-assisted programme developed at the Department of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine−1, unbiotinylated primer 10 pmol, 2 μl nuclear protein extract and biotinylated primer 20 fmol. Preincubation of all components was performed on ice for 2 min before addition of the biotinylated primer, and all components were then incubated for 55 min at room temperature before running the gel. Polyacrylamide gel (6%) was pre-run for 50 min, run for 1 h 15 min after loading and transferred to membrane for 45 min. Thereafter, crosslinking and washes were performed as per protocol. The experiment was replicated four times, twice each with protein derived from two different passages of MCF-7 cells, with similar results.MCF-7 cells (ATCC) were grown in DMEM high-glucose media with 10% fetal bovine serum in T25 flasks using standard cell culture practices. Nuclear protein extracts were harvested from passage 2 cells at 75% confluence and passage 3 cells at 85% confluence using the Pierce Scientific’s NE-PER nuclear and cytoplasmic extract kit with addition of Pierce Halt protease inhibitor cocktail. Biotinylated probes were synthesized and high-performance liquid chromatography purified from IDT DNA. EMSA were performed using LightShift Chemiluminescent EMSA kit (Pierce Scientific). The control reactions were performed as suggested by the protocol, except complete quenching of specific binding was not obtained at 200-fold concentration of unbiotinylated competitor but was obtained at 500-fold excess competitor. The kit protocol was followed with optimization to include the following components in each 20 μl reaction in the following order when relevant: water (variable), binding buffer 1X, poly dI.dC 50 ng μlE.Z., C.A.H. and L.F. contributed to the study concept and design. L.F. wrote the manuscript. N.A. and K.T. designed and conducted the EMSA experiments. D.H., S.H., J.L.C. and C.R.G. contributed to the statistical analyses. E.M.J., E.Z., C.A.H., B.H. and L.L.M. contributed data during the discovery phase. G.T.-M., L.C., M.M.E., A.M.D.T., C.R., C.K., L.H. and I.A. contributed data, conducted genotyping and performed study-specific analyses during the replication phase. C.E. and E.G.-B. conducted part of the discovery phase genome-wide genotyping. K.B.B. designed and supervised the genotyping of Mexican samples in the replication phase. E.J.P.-S. helped in the interpretation and discussion of the findings. P.K. and S.L. designed the assays and produced the sequenced data for the 6q25 region in the subset of MEC samples. All authors helped in the interpretation and discussion of the findings and approved the manuscript.How to cite this article: Fejerman, L. et al. Genome-wide association study of breast cancer in latinas identifies novel protective variants on 6q25. Nat. Commun. 5:5260 doi: 10.1038/ncomms6260 (2014).Supplementary Figures 1-5 and Supplementary Tables 1-6


FGFR2) rs2981582, trinucleotide-repeat-containing 9 (TNRC9) rs3803662, rs12443621, and leukocyte-specific protein 1 (LSP1) rs3817198 polymorphisms with breast cancer and mammographic density in Han Chinese population.This study is to investigate the association of fibroblast growth factor receptor 2 (TaqMan Single Nucleotide Polymorphism (SNP) Genotyping Assays and unconditional logistic regression analysis were used to examine these SNPs in 105 breast cancer cases and 382 controls.P = 0.017 and 0.006, respectively). Subjects carrying G allele of rs12443621 had increased breast cancer risk . Subjects carrying an allele of rs2981582 had reduced breast cancer risk . rs3803662 and rs3817198 SNPs did not significantly differ between cases and controls . Interestingly, the AA genotype of rs2981582 was also associated with reduced mammographic densities .The genotype frequencies of rs12443621 and rs2981582 were significantly different between controls and cases (Our findings indicate that the GG genotype of rs12443621 is associated with increased breast cancer risk whereas the GA and AA genotypes of rs2981582 are reduced risk in Han Chinese population. Breast cancer is one of the most common malignancies and a leading cause of cancer death in women worldwide, with over one million new cases each year . In ChinTNRC9), fibroblast growth factor receptor 2 (FGFR2), mitogen-activated protein kinase 1 (MAP3K1), and leukocyte-specific protein 1 (LSP1) as four novel loci with consistent evidence of association with breast cancer.The development and progression of breast cancer is a multi-step complicated process that involves both genetic and epigenetic factors. Although significant advancement has been made in understanding the genetic susceptibility to breast cancer, known susceptibility genes account for less than a quarter of familial breast cancer risk. To further identify novel susceptibility alleles associated with breast cancer, genome-wide association studies (GWAS) have been performed. One of these studies was published on Nature , which iTNRC9 rs12443621 and the CT/TT genotype of FGFR2 rs2981582 had a decreased risk for death in breast cancer patients [TNRC9 rs12443621 and the AA genotypes of FGFR2 rs2981582 both had increased breast cancer risk [FGFR2 rs2981582 had increased risk of breast cancer [TNRC9 rs12443621 was not significantly associated with breast cancer risk. Strong ethnic differences have been observed in breast cancer risk. Racial/ethnic differences and environmental factors that vary among populations may affect the associations between SNPs and risk of breast cancer by modulating complex interactions between various genes. Therefore, more studies are needed to clarify the relationship between these SNPs and breast cancer risk.Since then, a number of case-control or cohort studies have been carried out to further examine the association of the single nucleotide polymorphisms (SNPs) with breast cancer, but the results are not completely consistent. For example, a cohort study in American population found that the AG/GG genotypes of t cancer , but TNRTRC9 had higher mammographic density than women with two alleles [FGFR2 had non-significantly decreased mammographic density than women with two C alleles.Mammographic density has been shown to be strongly linked to breast cancer risk . Women wFGFR2 rs2981582, TNRC9 rs3803662, rs12443621, and LSP1 rs3817198 polymorphisms with breast cancer, we investigated these SNPs in Han Chinese women in Heilongjiang Province and analyzed their association with breast cancer risk and mammographic density.To have a better understanding of the association of All samples were collected at the First Affiliated Hospital of Harbin Medical University in 2010 between June and November. A total of 487 participants were recruited in this study. The case group was comprised of 105 female patients with histopathologically diagnosed breast cancer. Patients with a history of cancer, tumor chemotherapy, or radiotherapy were excluded from this study. The control group was comprised of 382 age-matched healthy women. Ninety of the breast cancer cases and 229 of controls had mammographic X-ray. All subjects gave written consent for participation in this research. This study was approved by the Ethical Committee of the First Hospital Affiliated to Haerbing Medical University.FGFR2 rs2981582, TNRC9 rs3803662, rs12443621, and LSP1 rs3817198 was carried out using TaqMan SNP Genotyping Assays  with Mini Option2 Real Time PCR System . Assays were performed with TaqMan Universal Master Mix, TaqMan probe, and 50 ng of DNA per reaction. PCR conditions were provided by the manufacturer: 5 min initial denaturation at 94 °C followed by 45 cycles of 94 °C denaturation for 15 s and 60 °C annealing/extension for 1 min.EDTA-anti-coagulated venous blood samples were preserved at −70 °C. Genomic DNA was isolated from whole blood using the Wizard® kit  according to the manufacturer’s protocol. Blinded genotyping of Information on age, age at menarche, age at menopause, breast-feeding, parity, and miscarriages/abortions was assessed from the questionnaire. The number of miscarriages/abortions was categorized into three groups: 0, 1–2, and 3 or more.Mediolateral oblique (MLO) and craniocaudal (CC) view digital mammograms were evaluated by three radiologists specialized in mammographic diagnosis. Mammographic density was described by using the Breast Imaging Reporting and Data System  four-category terminology : D1, lesP value less than 0.05 was considered to be statistically significant.Quantitative data were expressed as mean ± SD and analyzed using ANOVA or rank sum test. Categorical data were analyzed using chi-square test. The association between the genotypes and breast cancer risk or mammographic density was evaluated by unconditional logistic regression analysis and expressed as odds ratio (OR) and their 95 % confidence intervals (CI) using SPSS 18.0 software . Throughout the analysis, a two-sided FGFR2 rs2981582, TNRC9 rs3803662, TNRC9 rs12443621, and LP1 rs3817198 polymorphisms in 487 subjects, including 105 breast cancer cases and 382 controls. The genotype frequencies for these SNPs in cases and controls and the allele frequencies in all subjects are listed in Table Using TaqMan SNP Genotyping Assays, we evaluated P = 0.022). Controls had longer average breast-feeding duration (0.000) and higher rate of breast-feeding history (0.009). Controls also had a larger number of parity (0.03) and higher rate of childbearing history compared to cases (0.006). These factors were hence included in the multivariate analyses. All the other factors were similarly distributed between cases and controls.Reproductive characteristics of cases and controls are summarized in Table FGFR2 rs2981582, TNRC9 rs3803662, TNRC9 rs12443621, and LP1 rs3817198 and breast cancer risk, and the results are shown in Table FGFR2 rs2981582 and TNRC9 rs12443621 genotype frequencies were significantly different between case and control groups . The AG and GG genotypes of rs12443621 in TNRC9 were more prevalent among cases than among controls . The GA and AA genotypes of rs2981582 in FGFR2 were more prevalent among controls than among cases . After adjusting for age and reproductive risk factors, subjects carrying G allele of rs12443621 in TNRC9 were found to have a higher breast cancer risk compared with those carrying AA genotype .We examined the association between TNRC9 rs3803662 and LSP1 rs3817198 genotype distribution in cases and controls was not significantly different .χ2 = 4.4530, P = 0.0348). As shown in Table FGFR2 rs2981582 polymorphism, but not the other three SNPs, was significantly different among the four mammographic density categories (P = 0.0342). Subjects carrying AA genotype of rs2981582 in FGFR2 were associated with reduced mammographic density . After adjusting for age and reproductive risk factors, this remained significant .Analysis of mammographic density using rank sum test showed a significant difference between cases and controls Table , with hiIn the present study, we found that early age at menarche is associated with increased breast cancer risk, whereas breast-feeding and parity are associated with reduced breast cancer risk. Multiple studies have examined the relationship between reproductive factors and breast cancer risk, but the results are somewhat inconsistent. A case-control study in Japanese population reported that early age at menarche, late age at first birth, and premenopausal status are significantly associated with breast cancer risk, while high parity is a protective factor . A meta-TNRC9 rs12443621 and breast cancer risk. Specifically, the GG genotype of TNRC9 rs12443621 had increased risk of breast cancer. The rs12443621 SNP of TNRC9  is located at chromosome 16q12 [TNRC9 is unclear, but a recent paper has reported that TNRC9 down-regulates BRCA1 expression and promotes breast cancer aggressiveness [TNRC9 polymorphisms and breast cancer risk remains controversial. A meta-analysis in 2011 found that TNRC9 rs3803662, but not TNRC9 rs12443621, polymorphism was significantly correlated with breast cancer risk [Our study revealed a significant association between siveness . The asscer risk , which dFGFR2 is a member of the FGFR family of receptor tyrosine kinases that has been found to be overexpressed in some breast cancer cell lines [FGFR2 gene occurs in a small subset of breast cancer [FGFR2 rs2981582 are associated with reduced risk of breast cancer. This is surprising, since most studies reported that the T allele of FGFR2 rs2981582 is associated with increased breast cancer risk [FGFR2 rs2981582 and decreased mammographic density. Meanwhile, our data showed that lower mammographic density is linked to lower risk of breast cancer. These findings are consistent with each other. One limitation of the current study was that the sample size for breast cancer cases was relatively small (105 cases were included in this study), and all patients were from Heilongjiang Province in Northeast China. We cannot rule out the potential instability rising from a relatively small number of patients. Further studies are necessary to elude the reasons for the disparity between our results and some of the earlier reports.ll lines . Amplifit cancer . Our stucer risk , 19. Howcer risk . It is wTNRC9 rs12443621 and elevated breast cancer risk. Moreover, the GA and AA genotypes of FGFR2 rs2981582 appear to be associated with lower mammographic density and reduced breast cancer risk. These data provide support for the potential importance of these polymorphisms in breast cancer biology. Further studies are needed to define the role of these SNPs in breast cancer and test the possibility of using them as biomarkers for diagnostic, prognostic, or therapeutic purposes in Chinese Han population.In conclusion, we detected a significant association between the GG genotype of


Molecular breast imaging (MBI) is a functional test used for supplemental screening of women with mammographically dense breasts. Additionally, MBI depicts variable levels of background parenchymal uptake (BPU) within nonmalignant, dense fibroglandular tissue. We investigated whether BPU is a risk factor for breast cancer.We conducted a retrospective case-control study of 3027 eligible women who had undergone MBI between February 2004 and February 2014. Sixty-two incident breast cancer cases were identified. A total of 179 controls were matched on age, menopausal status, and MBI year. Two radiologists blinded to case status independently assessed BPU as one of four categories: photopenic, minimal to mild, moderate, or marked. Conditional logistic regression analysis was performed to estimate the associations (OR) of BPU categories  and breast cancer risk, adjusted for other risk factors.p = 0.88). Women with moderate or marked BPU had a 3.4-fold (95 % CI 1.6–7.3) and 4.8-fold (95 % CI 2.1–10.8) increased risk of breast cancer, respectively, compared with women with photopenic or minimal to mild BPU, for two radiologists. The results were similar after adjustment for BI-RADS density (OR 3.3 [95 % CI 1.6–7.2] and OR 4.6 [95 % CI 2.1–10.5]) or postmenopausal hormone use (OR 3.6 [95 % CI 1.7–7.7] and OR 5.0 [95 % CI 2.2–11.4]). The association of BPU with breast cancer remained in analyses limited to postmenopausal women only (OR 3.8 [95 % CI 1.5–9.3] and OR 4.1 [95 % CI 1.6–10.2]) and invasive breast cancer cases only (OR 3.6 [95 % CI 1.5–8.8] and OR 4.4 [95 % CI 1.7–11.1]). Variable BPU was observed among women with similar mammographic density; the distribution of BPU categories differed across density categories (p < 0.0001).The median age was 60.2 years (range 38–86 years) for cases vs. 60.2 years (range 38–88 years) for controls  contains supplementary material, which is available to authorized users. Mammographic density is known to be an important factor in reducing the sensitivity of mammography , 2. Therbackground parenchymal uptake (BPU)  of 3202). For women who had had multiple MBI examinations performed, data from the earliest (index) MBI were used for analysis. Follow-up for breast cancer through December 2014 was conducted through review of medical records and linkage to the Mayo Clinic Tumor Registry.We performed a retrospective case-control study that was compliant with the U.S. Health Insurance Portability and Accountability Act and approved by the Mayo Clinic Institutional Review Board, which issued a waiver of informed consent. Our institutional MBI database was reviewed to identify all patients  or invasive carcinoma in either breast at least 180 days after the index MBI. Sixty-two incident breast cancer cases were identified. The median time between index MBI examination and cancer diagnosis was 3.1 years (IQR 1.5–4.2 years). Fifty-eight (94 %) of sixty-two cases were diagnosed more than 1 year after the index MBI.n = 179) were selected from among the 2965 women who were not diagnosed with breast cancer over the study period, with matching to cases on age (within 5 years), menopausal status (exact), and year of MBI (within 1 year). Matched controls were required to be followed for at least as long as matched cases and to have had negative findings on all subsequent breast imaging performed at our institution over the corresponding follow-up time. Median follow-up time for controls was 6.1 years (IQR 3.7–7.8 years).Up to three control subjects per case . In the remaining 13 women (5 %), MBI was performed for further evaluation of the following: breast mass initially detected on mammography or ultrasound , recent histopathologic diagnosis of atypia or lobular carcinoma in situ , bloody nipple discharge (one case), and breast pain (one control).Covariate information, including body mass index (BMI), menopausal status, postmenopausal hormone use, breast biopsy history, and family history of breast cancer was obtained primarily in a prospective manner through questionnaires and medical record review performed at the time of the MBI examination. We examined only those factors previously shown to be associated with BPU . MissingMBI examinations were performed using one of two dedicated dual-head gamma camera systems equipped with cadmium zinc telluride detectors . Patients received an intravenous injection of Tc-99m sestamibi in an arm vein. Before June 2009, MBI examinations were performed with administered doses of 740 MBq of Tc-99 m sestamibi. Changes to the MBI detectors’ collimation, system energy window settings, and radiopharmaceutical injection techniques over the course of the study period resulted in an approximately threefold gain in the number of counts that could be collected during an MBI examination, such that we were able to lower the administered dose to patients proportionally while preserving count density and image quality , 18. In Imaging commenced approximately 5 minutes after injection. Bilateral views in craniocaudal and mediolateral oblique-analogous projections were acquired for 10 minutes per view, with the breast under light compression to limit patient motion. All study participants had bilateral MBI examinations.MBI examinations were retrospectively reviewed by two breast imaging radiologists with 6 and 10 years of experience, respectively, in MBI interpretation. Readers interpreted BPU independently while blinded to the participants’ case status. BPU was qualitatively assessed per breast according to a validated lexicon for gamma imaging of the breast as one of four categories: photopenic, minimal to mild, moderate, or marked  of 241 subjects. Most mammograms were obtained within 21 days of MBI (223 [96 %] of 232). Six were obtained within 6 months, and the remaining three were obtained within 14 months of MBI. During the course of routine clinical practice, mammographic density was subjectively assessed according to ACR BI-RADS density categories (fourth edition) by breast imaging radiologists . DensityCase and control characteristics are presented as mean, SD, and range for continuous variables and frequency and percentage for categorical variables. Conditional logistic regression analysis was performed to test for differences between cases and controls and to estimate the associations of BPU categories and risk of breast cancer with adjustments for covariates. Exploratory analyses were also repeated within premenopausal and postmenopausal subgroups and in a subgroup limited to invasive breast cancer cases. Further, we performed analyses on data from before and after June 2009 to examine whether changes in MBI protocol influenced the results. To measure the discriminatory ability of the models, the AUC for BPU discrimination was calculated within case-control sets to match the design.Analysis was performed by first considering BPU as a four-category variable, using the category “minimal to mild” as a reference group because this was the largest group and provided a more stable relative risk estimate. Tests for trend were examined by including BPU as an ordinal variable in the conditional logistic regression model. Analysis was also performed considering BPU as a dichotomous variable by combining categories of “photopenic” with “minimal to mild” and “moderate” with “marked.”The maximum BPU was used in participants whose BPU assessment differed between breasts, similarly to how clinical assessment of BI-RADS density is done . To asseInterreader agreement in BPU assessment was summarized by the weighted κ statistic. κ values were interpreted as ≤0.20 or less, poor; 0.21–0.40, fair; 0.41–0.60, moderate; 0.61–0.80, good; and 0.81–1.00, very good agreement .2 test was used as appropriate to test for differences in distribution of BPU categories across BI-RADS density categories. For all comparisons, p < 0.05 was considered statistically significant. Analyses were performed using SAS software version 9.4 .The χCharacteristics of breast cancer cases and matched controls are shown in Table Of the 62 incident breast cancer cases, 45 (73 %) were invasive and 17 (27 %) were DCIS. Images from an example breast cancer case are given in Fig. When BPU was considered as a four-category ordinal variable, interreader agreement was good  with 85 % (205 of 241) agreement. When BPU was considered as a dichotomous variable, interreader agreement was good to very good  with 94 % (227 of 241) agreement. BPU differed between breasts in 10 (4 %) of 241 participants  for reader 1 and in 24 (10 %) of 241 participants  for reader 2.p-trend = 0.007). For reader 2, the OR increased from 0.5 for photopenic BPU to 6.2 for marked BPU (p-trend < 0.001).BPU level using either categorization was associated with breast cancer risk. When BPU was considered as a four-category variable, the BMI-adjusted OR increased with increasing BPU Table . For reaWhen we considered BPU as a dichotomous variable, we found that women with moderate or marked BPU had a greater risk of incident breast cancer than women with photopenic or minimal to mild BPU. For the two readers, the BMI-adjusted ORs for moderate or marked BPU vs. photopenic or minimal to mild BPU was 3.4 (95 % CI 1.6–7.3) and 4.8 (95 % CI 2.1–10.8) (Table p < 0.0001), and among cases for one reader , and among controls for both readers (p < 0.001), as shown Fig. Neither BI-RADS density nor percentage density was statistically significantly associated with breast cancer in this study  Table  and percAdditional adjustment for family history or Gail model 5-year risk within the model that included BMI and BI-RADS density adjustments had minimal impact on OR estimates. When additional adjustment for family history was made, the ORs for moderate or marked BPU vs. photopenic or minimal to mild BPU were 3.3 (95 % CI 1.5–7.2) and 4.7 (95 % CI 2.1–10.6), whereas additional adjustment for Gail model risk resulted in ORs of 3.5 (95 % CI 1.6–7.8) and 4.9 (95 % CI 2.1–11.5) for readers 1 and 2, respectively.p < 0.001). As shown in Table p = 0.28–0.45). The results were similar when we considered BPU assessment from the contralateral vs. ipsilateral breast for cancer cases and their respective matched controls  than among postmenopausal women  for a model including BMI and BI-RADS mammographic density . The addition of BPU to this model including BMI and density resulted in AUCs of 0.64–0.67  , noting While mammographic density is established as an important breast cancer risk factor, a growing body of work supports the existence of additional anatomical and functional features of breast fibroglandular tissue that differ in discriminatory capacity for predicting breast cancer risk. For instance, extraction of breast density’s textural features has shown potential to improve risk discrimination over BI-RADS density categories and quantitative density assessment –26. In cbenign parenchymal enhancement (BPE). Similar to our findings with BPU on MBI, BPE on MR imaging is influenced by hormonal and reproductive risk factors [Breast magnetic resonance (MR) imaging also depicts functional behavior of breast lesions and benign fibroglandular tissue through gadolinium-based contrast enhancement, known as  factors , 30 and  factors , 32. Sim factors . One stu factors . Several factors –37.Within the Mayo Clinic practice, MBI is currently offered to the population of women with mammographically dense breasts (BI-RADS density c or d) who seek supplemental screening but do not meet criteria for breast MR  . Also, MSupplemental MBI screening in dense breasts has been shown to offer a relatively high incremental cancer detection rate (8.8 cancers per 1000 women screened), a low false-positive rate , and lower cost per cancer detected compared with mammography alone , 39. TheA strength of our study was the inclusion of only incident breast cancer cases, diagnosed at least 180 days after index MBI. This study design allowed us to establish BPU as a risk factor for future development of breast cancer, thus supporting the potential utility of BPU in risk prediction. While a case-control study including prevalent cases , 32 coulOur study had several limitations. First, BPU was assessed as a subjective measure, which led to some differences between the two readers. However, this subjective measure represents how MBI is currently read in practice, and the two readers agreed on BPU assessment in 94 % of subjects.A second potential limitation of our study was that we did not have follow-up on approximately 6 % (183 of 3085) of patients in our MBI database from which the breast cancer cases were selected. Therefore, it is possible that we could have missed some breast cancers diagnosed outside our institution. However, we matched on known follow-up time, so our controls represented our cases and we do not anticipate a systematic bias.p = 0.65) [Finally, the study data lacked specific information on day of menstrual cycle at which MBI was performed among premenopausal women. In a prior cross-sectional analysis including 417 premenopausal or perimenopausal women, no association between BPU category and follicular vs. luteal phase was found ( = 0.65) . However = 0.65) . It is cOur study included primarily women with mammographically dense breasts (80 % were either heterogeneously or extremely dense). The low number of women with nondense breasts likely accounts for the lack of a statistically significant association between mammographic density measures and breast cancer observed in this population. However, since this population is the target subgroup that would receive MBI, it is appropriate for our investigation.BPU, which describes the functional uptake observed within fibroglandular tissue on MBI, is strongly associated with breast cancer risk, and this association remained after adjustments for mammographic density or postmenopausal hormone use. For women with dense breasts, who comprise over 40 % of the screening-eligible population, BPU may serve as an additional risk factor to help identify the subgroup most likely to benefit from tailored screening or primary prevention options.