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BACKGROUND: Genome-wide association studies (GWAS) have identified more than 200 susceptibility loci for breast cancer, but these variants explain less than a fifth of the disease risk. Although gene-environment interactions have been proposed to account for some of the remaining heritability, few studies have empirically assessed this. METHODS: We obtained genotype and risk factor data from 46,060 cases and 47,929 controls of European ancestry from population-based studies within the Breast Cancer Association Consortium (BCAC). We built gene expression prediction models for 4,864 genes with a significant (P<0.01) heritable component using the transcriptome and genotype data from the Genotype-Tissue Expression (GTEx) project. We leveraged predicted gene expression information to investigate the interactions between gene-centric genetic variation and 14 established risk factors in association with breast cancer risk, using a mixed-effects score test. RESULTS: After adjusting for number of tests using Bonferroni correction, no interaction remained statistically significant. The strongest interaction observed was between the predicted expression of the C13orf45 gene and age at first full-term pregnancy (PGXE=4.44×10-6). CONCLUSION: In this transcriptome-informed genome-wide gene-environment interaction study of breast cancer, we found no strong support for the role of gene expression in modifying the associations between established risk factors and breast cancer risk. IMPACT: Our study suggests a limited role of gene-environment interactions in breast cancer risk.

BACKGROUND: Mammographic density (MD) phenotypes, including percent density (PMD), area of dense tissue (DA), and area of non-dense tissue (NDA), are associated with breast cancer risk. Twin studies suggest that MD phenotypes are highly heritable. However, only a small proportion of their variance is explained by identified genetic variants. METHODS: We conducted a genome-wide association study, as well as a transcriptome-wide association study (TWAS), of age- and BMI-adjusted DA, NDA, and PMD in up to 27,900 European-ancestry women from the MODE/BCAC consortia. RESULTS: We identified 28 genome-wide significant loci for MD phenotypes, including nine novel signals (5q11.2, 5q14.1, 5q31.1, 5q33.3, 5q35.1, 7p11.2, 8q24.13, 12p11.2, 16q12.2). Further, 45% of all known breast cancer SNPs were associated with at least one MD phenotype at p < 0.05. TWAS further identified two novel genes (SHOX2 and CRISPLD2) whose genetically predicted expression was significantly associated with MD phenotypes. CONCLUSIONS: Our findings provided novel insight into the genetic background of MD phenotypes, and further demonstrated their shared genetic basis with breast cancer.

PURPOSE: In several studies, exploratory dietary patterns (DP), derived by principal component analysis, were inversely or positively associated with incident type 2 diabetes (T2D). However, findings remained study-specific, inconsistent and rarely replicated. This study aimed to investigate the associations between DPs and T2D in multiple cohorts across the world. METHODS: This federated meta-analysis of individual participant data was based on 25 prospective cohort studies from 5 continents including a total of 390,664 participants with a follow-up for T2D (3.8-25.0 years). After data harmonization across cohorts we evaluated 15 previously identified T2D-related DPs for association with incident T2D estimating pooled incidence rate ratios (IRR) and confidence intervals (CI) by Piecewise Poisson regression and random-effects meta-analysis. RESULTS: 29,386 participants developed T2D during follow-up. Five DPs, characterized by higher intake of red meat, processed meat, French fries and refined grains, were associated with higher incidence of T2D. The strongest association was observed for a DP comprising these food groups besides others (IRRpooled per 1 SD = 1.104, 95% CI 1.059-1.151). Although heterogeneity was present (I2 = 85%), IRR exceeded 1 in 18 of the 20 meta-analyzed studies. Original DPs associated with lower T2D risk were not confirmed. Instead, a healthy DP (HDP1) was associated with higher T2D risk (IRRpooled per 1 SD = 1.057, 95% CI 1.027-1.088). CONCLUSION: Our findings from various cohorts revealed positive associations for several DPs, characterized by higher intake of red meat, processed meat, French fries and refined grains, adding to the evidence-base that links DPs to higher T2D risk. However, no inverse DP-T2D associations were confirmed.

Mammograms contain information that predicts breast cancer risk. We developed two novel mammogram-based breast cancer risk measures based on image brightness (Cirrocumulus) and texture (Cirrus). Their risk prediction when fitted together, and with an established measure of conventional mammographic density (Cumulus), is not known. We used three studies consisting of: 168 interval cases and 498 matched controls; 422 screen-detected cases and 1197 matched controls; and 354 younger-diagnosis cases and 944 controls frequency-matched for age at mammogram. We conducted conditional and unconditional logistic regression analyses of individually- and frequency-matched studies, respectively. We estimated measure-specific risk gradients as the change in odds per standard deviation of controls after adjusting for age and body mass index (OPERA) and calculated the area under the receiver operating characteristic curve (AUC). For interval, screen-detected and younger-diagnosis cancer risks, the best fitting models (OPERAs [95% confidence intervals]) involved: Cumulus (1.81 [1.41-2.31]) and Cirrus (1.72 [1.38-2.14]); Cirrus (1.49 [1.32-1.67]) and Cirrocumulus (1.16 [1.03 to 1.31]); and Cirrus (1.70 [1.48 to 1.94]) and Cirrocumulus (1.46 [1.27-1.68]), respectively. The AUCs were: 0.73 [0.68-0.77], 0.63 [0.60-0.66], and 0.72 [0.69-0.75], respectively. Combined, our new mammogram-based measures have twice the risk gradient for screen-detected and younger-diagnosis breast cancer (P <= 10-12), have at least the same discriminatory power as the current polygenic risk score, and are more correlated with causal factors than conventional mammographic density. Discovering more information about breast cancer risk from mammograms could help enable risk-based personalised breast screening.Copyright © 2020 UICC

BACKGROUND: Menopausal hormone therapy (MHT) is a risk factor for breast cancer (BC). Evidence suggests that its effect on BC risk could be partly mediated by mammographic density. The aim of this study was to investigate the relationship between MHT, mammographic density and BC risk using data from a prospective study. METHODS: We used data from a case-control study nested within the French cohort E3N including 453 cases and 453 matched controls. Measures of mammographic density, history of MHT use during follow-up and information on potential confounders were available for all women. The association between MHT and mammographic density was evaluated by linear regression models. We applied mediation modelling techniques to estimate, under the hypothesis of a causal model, the proportion of the effect of MHT on BC risk mediated by percent mammographic density (PMD) for BC overall and by hormone receptor status. RESULTS: Among MHT users, 4.2% used exclusively oestrogen alone compared with 68.3% who used exclusively oestrogens plus progestogens. Mammographic density was higher in current users (for a 60-year-old woman, mean PMD 33%; 95% CI 31 to 35%) than in past (29%; 27 to 31%) and never users (24%; 22 to 26%). No statistically significant association was observed between duration of MHT and mammographic density. In past MHT users, mammographic density was negatively associated with time since last use; values similar to those of never users were observed in women who had stopped MHT at least 8 years earlier. The odds ratio of BC for current versus never MHT users, adjusted for age, year of birth, menopausal status at baseline and BMI, was 1.67 (95% CI, 1.04 to 2.68). The proportion of effect mediated by PMD was 34% for any BC and became 48% when the correlation between BMI and PMD was accounted for. These effects were limited to hormone receptor-positive BC. CONCLUSIONS: Our results suggest that, under a causal model, nearly half of the effect of MHT on hormone rec

Mammograms contain information that predicts breast cancer risk. We developed two novel mammogram-based breast cancer risk measures based on image brightness (Cirrocumulus) and texture (Cirrus). Their risk prediction when fitted together, and with an established measure of conventional mammographic density (Cumulus), is not known. We used three studies consisting of: 168 interval cases and 498 matched controls; 422 screen-detected cases and 1197 matched controls; and 354 younger-diagnosis cases and 944 controls frequency-matched for age at mammogram. We conducted conditional and unconditional logistic regression analyses of individually- and frequency-matched studies, respectively. We estimated measure-specific risk gradients as the change in odds per standard deviation of controls after adjusting for age and body mass index (OPERA) and calculated the area under the receiver operating characteristic curve (AUC). For interval, screen-detected and younger-diagnosis cancer risks, the best fitting models (OPERAs [95% confidence intervals]) involved: Cumulus (1.81 [1.41-2.31]) and Cirrus (1.72 [1.38-2.14]); Cirrus (1.49 [1.32-1.67]) and Cirrocumulus (1.16 [1.03 to 1.31]); and Cirrus (1.70 [1.48 to 1.94]) and Cirrocumulus (1.46 [1.27-1.68]), respectively. The AUCs were: 0.73 [0.68-0.77], 0.63 [0.60-0.66], and 0.72 [0.69-0.75], respectively. Combined, our new mammogram-based measures have twice the risk gradient for screen-detected and younger-diagnosis breast cancer (P ≤ 10-12 ), have at least the same discriminatory power as the current polygenic risk score, and are more correlated with causal factors than conventional mammographic density. Discovering more information about breast cancer risk from mammograms could help enable risk-based personalised breast screening.

Background: Mammographic breast density, adjusted for age and body mass index, and a polygenic risk score (PRS), comprised of common genetic variation, are both strong risk factors for breast cancer and increase discrimination of risk models. Understanding their joint contribution will be important to more accurately predict risk. Method(s): Using 3628 breast cancer cases and 5126 controls of European ancestry from eight case-control studies, we evaluated joint associations of a 77-single nucleotide polymorphism (SNP) PRS and quantitative mammographic density measures with breast cancer. Mammographic percent density and absolute dense area were evaluated using thresholding software and examined as residuals after adjusting for age, 1/BMI, and study. PRS and adjusted density phenotypes were modeled both continuously (per 1 standard deviation, SD) and categorically. We fit logistic regression models and tested the null hypothesis of multiplicative joint associations for PRS and adjusted density measures using likelihood ratio and global and tail-based goodness of fit tests within the subset of six cohort or population-based studies. Result(s): Adjusted percent density (odds ratio (OR) = 1.45 per SD, 95% CI 1.38-1.52), adjusted absolute dense area (OR = 1.34 per SD, 95% CI 1.28-1.41), and the 77-SNP PRS (OR = 1.52 per SD, 95% CI 1.45-1.59) were associated with breast cancer risk. There was no evidence of interaction of the PRS with adjusted percent density or dense area on risk of breast cancer by either the likelihood ratio (P > 0.21) or goodness of fit tests (P > 0.09), whether assessed continuously or categorically. The joint association (OR) was 2.60 in the highest categories of adjusted PD and PRS and 0.34 in the lowest categories, relative to women in the second density quartile and middle PRS quintile. Conclusion(s): The combined associations of the 77-SNP PRS and adjusted density measures are generally well described by multiplicative models, and both risk fact

BACKGROUND: Mammographic breast density, adjusted for age and body mass index, and a polygenic risk score (PRS), comprised of common genetic variation, are both strong risk factors for breast cancer and increase discrimination of risk models. Understanding their joint contribution will be important to more accurately predict risk. METHODS: Using 3628 breast cancer cases and 5126 controls of European ancestry from eight case-control studies, we evaluated joint associations of a 77-single nucleotide polymorphism (SNP) PRS and quantitative mammographic density measures with breast cancer. Mammographic percent density and absolute dense area were evaluated using thresholding software and examined as residuals after adjusting for age, 1/BMI, and study. PRS and adjusted density phenotypes were modeled both continuously (per 1 standard deviation, SD) and categorically. We fit logistic regression models and tested the null hypothesis of multiplicative joint associations for PRS and adjusted density measures using likelihood ratio and global and tail-based goodness of fit tests within the subset of six cohort or population-based studies. RESULTS: Adjusted percent density (odds ratio (OR) = 1.45 per SD, 95% CI 1.38-1.52), adjusted absolute dense area (OR = 1.34 per SD, 95% CI 1.28-1.41), and the 77-SNP PRS (OR = 1.52 per SD, 95% CI 1.45-1.59) were associated with breast cancer risk. There was no evidence of interaction of the PRS with adjusted percent density or dense area on risk of breast cancer by either the likelihood ratio (P > 0.21) or goodness of fit tests (P > 0.09), whether assessed continuously or categorically. The joint association (OR) was 2.60 in the highest categories of adjusted PD and PRS and 0.34 in the lowest categories, relative to women in the second density quartile and middle PRS quintile. CONCLUSIONS: The combined associations of the 77-SNP PRS and adjusted density measures are generally well described by multiplicative models, and both risk factors pr

Background We applied machine learning to find a novel breast cancer predictor based on information in a mammogram. Methods Using image-processing techniques, we automatically processed 46 158 analog mammograms for 1345 cases and 4235 controls from a cohort and case–control study of Australian women, and a cohort study of Japanese American women, extracting 20 textural features not based on pixel brightness threshold. We used Bayesian lasso regression to create individual- and mammogram-specific measures of breast cancer risk, Cirrus. We trained and tested measures across studies. We fitted Cirrus with conventional mammographic density measures using logistic regression, and computed odds ratios (OR) per standard deviation adjusted for age and body mass index. Results Combining studies, almost all textural features were associated with case–control status. The ORs for Cirrus measures trained on one study and tested on another study ranged from 1.56 to 1.78 (all P < 10−6). For the Cirrus measure derived from combining studies, the OR was 1.90 (95% confidence interval [CI] = 1.73 to 2.09), equivalent to a fourfold interquartile risk ratio, and was little attenuated after adjusting for conventional measures. In contrast, the OR for the conventional measure was 1.34 (95% CI = 1.25 to 1.43), and after adjusting for Cirrus it became 1.16 (95% CI = 1.08 to 1.24; P = 4 × 10−5). Conclusions A fully automated personal risk measure created from combining textural image features performs better at predicting breast cancer risk than conventional mammographic density risk measures, capturing half the risk-predicting ability of the latter measures. In terms of differentiating affected and unaffected women on a population basis, Cirrus could be one of the strongest known risk factors for breast cancer.

© 2018, Springer Nature Limited. Background/Objectives: This study examined the long-term relation of lipid-soluble micronutrients with diet quality as assessed by four a priori-defined dietary patterns. Subjects/Methods: In a prospective design, nutritional biomarkers (carotenoids, tocopherols, retinol, and coenzyme Q10) were measured using a validated HPLC-based assay. General linear models were applied to obtain covariate-adjusted means of biomarkers for tertiles of four a priori diet quality indices: Healthy Eating Index (HEI) 2010, Alternative HEI (AHEI) 2010, Alternate Mediterranean Diet Score (aMED), and Dietary Approaches to Stop Hypertension (DASH). For a subcohort of 8367 participants within the Multiethnic Cohort (MEC), diet was assessed by a validated quantitative food frequency questionnaire in 1993–96 and serum was collected in 2001–06. Results: Participants with the highest diet-quality scores had significantly higher serum concentrations of all carotenoids, total tocopherols, and a-tocopherol, whereas ?-tocopherol was inversely associated with diet quality. Adjusted means for the lowest vs. highest tertile of HEI 2010 were 1.2 vs. 1.5 mg/L for total carotenoids, 11.4 vs. 12.3 mg/L for total tocopherols, and 1.9 vs. 1.6 mg/L for ?-tocopherol (ptrend < 0.0001). The associations for the other dietary indices were similar; no indication for sex and ethnic differences was detected. Vegetable and fruit components were major predictors of most circulating micronutrients, but most other components were also associated. Conclusions: Higher diet-quality scores measured by four a priori diet quality indices were significantly associated higher serum concentrations of carotenoids and a-tocopherol, whereas ?-tocopherol was inversely associated with diet quality.

© 2018 Macmillan Publishers Limited, part of Springer Nature Background/objectives: Several diets, e.g., those low in fruits/vegetables, high in sodium, and red/processed meat, have been related to a higher stroke risk. We investigated stroke mortality associated with a priori diet-quality indices in the Multiethnic Cohort study. Subjects/methods: Based on 172,043 observations including 3548 stroke deaths, we investigated the Healthy Eating Index-2010 (HEI-2010), the Alternative HEI-2010, the alternate Mediterranean diet score, and the Dietary Approaches to Stop Hypertension index in relation to stroke mortality. Using Cox regression, we estimated adjusted population attributable risks (PAR) and hazard ratios (HR) for tertiles of the indices while adjusting for relevant confounders. Results: The associations between all diet-quality indices and stroke mortality were consistent in direction; a low-quality diet was associated with a greater risk of stroke death, but the HEI-2010 was the strongest predictor. The PAR for stroke death based on HEI-2010 was 7.9% (95%-CI: 3.7–12.2%), indicating the preventable percentage of deaths if the total population had the same diet quality as those in the highest tertile for this diet-quality index. The lowest as compared to the highest tertile of the HEI-2010 was associated with a 1.23-fold (95%-CI: 1.13–1.34) risk. The PARs for low and medium adherence to the indices were similar by sex and follow-up time, but varied by ethnicity, with the highest PAR in Whites (15.4%) and no association in Latinos. Conclusions: Findings for four diet-quality indices, in particular the HEI-2010, indicated that diet quality acts as an independent risk factor for stroke mortality. Promotion of a high diet quality could have a substantial impact on the prevention of stroke deaths.

© 2018 Macmillan Publishers Limited, part of Springer Nature Background/objectives: As cocoa products may be protective against chronic disease due to their polyphenol content, the current study determined the association of chocolate consumption and flavanol intake with type-2 diabetes (T2D) incidence in the Multiethnic Cohort (MEC) Study. Subjects/methods: The analysis included 151,691 participants of Native Hawaiian, Japanese American, Latino, African American, and white ancestry with 8487 incident T2D cases after 7.8 ± 3.5 years of follow-up. T2D status was based on three self-reports and confirmed by at least one of three administrative data sources. Dietary intake was assessed using a validated quantitative food frequency questionnaire, and flavanols from cocoa products were estimated from self-reported consumption of chocolate candy and drinks. Cox hazard regression, adjusted for potential confounders was applied to estimate hazard ratios (HR) and 95% confidence intervals (CI). Results: For chocolate candy, both the highest vs. lowest (=10 vs. < 1 g/day) consumption (HR = 0.90; 95% CI, 0.83–0.97; p trend = 0.01) and the frequency (=4/week vs. < 1/month) of intake (HR = 0.81; 95% CI, 0.72–0.91; p trend = 0.0002) were inversely associated with T2D. The estimated flavanol intake from cocoa products (=3 vs. < 1 mg/day) also showed an inverse association with T2D risk (HR = 0.93; 95% CI, 0.88–0.99; p trend = 0.02). Significant interaction terms indicated that the inverse relation was limited to Japanese Americans, normal-weight individuals, and to those without comorbidities. Conclusions: The current study confirms previous reports that participants with high intake of chocolate products and cocoa-derived flavanols experience a reduced risk of developing T2D even after controlling for sugar intake, diet quality, and other aspects of the diet.

BACKGROUND: Mammographic density (MD) is one of the strongest breast cancer risk factors. Its age-related characteristics have been studied in women in western countries, but whether these associations apply to women worldwide is not known. METHODS AND FINDINGS: We examined cross-sectional differences in MD by age and menopausal status in over 11,000 breast-cancer-free women aged 35-85 years, from 40 ethnicity- and location-specific population groups across 22 countries in the International Consortium on Mammographic Density (ICMD). MD was read centrally using a quantitative method (Cumulus) and its square-root metrics were analysed using meta-analysis of group-level estimates and linear regression models of pooled data, adjusted for body mass index, reproductive factors, mammogram view, image type, and reader. In all, 4,534 women were premenopausal, and 6,481 postmenopausal, at the time of mammography. A large age-adjusted difference in percent MD (PD) between post- and premenopausal women was apparent (-0.46 cm [95% CI: -0.53, -0.39]) and appeared greater in women with lower breast cancer risk profiles; variation across population groups due to heterogeneity (I2) was 16.5%. Among premenopausal women, the √PD difference per 10-year increase in age was -0.24 cm (95% CI: -0.34, -0.14; I2 = 30%), reflecting a compositional change (lower dense area and higher non-dense area, with no difference in breast area). In postmenopausal women, the corresponding difference in √PD (-0.38 cm [95% CI: -0.44, -0.33]; I2 = 30%) was additionally driven by increasing breast area. The study is limited by different mammography systems and its cross-sectional rather than longitudinal nature. CONCLUSIONS: Declines in MD with increasing age are present premenopausally, continue postmenopausally, and are most pronounced over the menopausal transition. These effects were highly consistent across diverse groups of women worldwide, suggesting that they result from an intrinsic biological, likel

Dietary indices have been related to risk for type 2 diabetes (T2D) predominantly in white populations. The present study evaluated this association in the ethnically diverse Multiethnic Cohort and examined four diet quality indices in relation to T2D risk, homoeostatic model assessment-estimated insulin resistance (HOMA-IR) and biomarkers of dyslipidaemia, inflammation and adipokines. The T2D analysis included 166 550 white, African American, Native Hawaiian, Japanese American and Latino participants (9200 incident T2D cases). Dietary intake was assessed at baseline using a quantitative FFQ and T2D status was based on three self-reports and confirmed by administrative data. Biomarkers were assessed about 10 years later in a biomarker subcohort (n 10 060). Sex- and ethnicity-specific hazard ratios were calculated for the Healthy Eating Index-2010 (HEI-2010), the alternative HEI-2010 (AHEI-2010), the alternate Mediterranean diet score (aMED) and the Dietary Approaches to Stop Hypertension (DASH). Multivariable-adjusted means of biomarkers were compared across dietary index tertiles in the biomarker subcohort. The AHEI-2010, aMED (in men only) and DASH scores were related to a 10-20 % lower T2D risk, with the strongest associations in whites and the direction of the relationships mostly consistent across ethnic groups. Higher scores on the four indices were related to lower HOMA-IR, TAG and C-reactive protein concentrations, not related to leptin, and the DASH score was directly associated with adiponectin. The AHEI-2010 and DASH were directly related to HDL-cholesterol in women. Potential underlying biological mechanisms linking diet quality and T2D risk are an improved lipid profile and reduced systemic inflammation and, with regards to DASH alone, an improved adiponectin profile.

© 2017 The Obesity Society Objective: The relationship of diet quality assessed by established indices (HEI-2010, AHEI-2010, aMED, DASH) with adiposity measures was examined, especially visceral adipose tissue (VAT) and nonalcoholic fatty liver (NAFL). Methods: Close to 2,000 participants of the Multiethnic Cohort completed validated food frequency questionnaires at cohort entry (1993-1996) and clinic visit (2013-2016) when they underwent whole-body dual-energy x-ray absorptiometry and abdominal magnetic resonance imaging scans. Linear regression was used to estimate mean values of adiposity measures by dietary index tertiles at baseline and standardized regression coefficients (ß s ) after adjusting for total adiposity and other covariates. Logistic regression of VAT and NAFL on dietary indices was also performed. Results: Higher dietary quality scores at cohort entry were inversely related to all adiposity measures, with the strongest associations for percent liver fat (ß s = -0.14 to -0.08), followed by VAT (ß s = -0.11 to -0.05), BMI (ß s = -0.11 to -0.06), and total body fat (ß s = -0.09 to -0.05). Odds ratios adjusted for total adiposity ranged between 0.57 and 0.77 for NAFL and between 0.41 and 0.65 for high VAT when comparing the highest versus lowest tertiles of diet quality. Conclusions: These longitudinal findings indicate that maintaining a high-quality diet during mid-to-late adulthood may prevent adverse metabolic consequences related to VAT and NAFL.

BACKGROUND: Inter-women and intra-women comparisons of mammographic density (MD) are needed in research, clinical and screening applications; however, MD measurements are influenced by mammography modality (screen film/digital) and digital image format (raw/processed). We aimed to examine differences in MD assessed on these image types. METHODS: We obtained 1294 pairs of images saved in both raw and processed formats from Hologic and General Electric (GE) direct digital systems and a Fuji computed radiography (CR) system, and 128 screen-film and processed CR-digital pairs from consecutive screening rounds. Four readers performed Cumulus-based MD measurements (n = 3441), with each image pair read by the same reader. Multi-level models of square-root percent MD were fitted, with a random intercept for woman, to estimate processed-raw MD differences. RESULTS: Breast area did not differ in processed images compared with that in raw images, but the percent MD was higher, due to a larger dense area (median 28.5 and 25.4 cm2 respectively, mean √dense area difference 0.44 cm (95% CI: 0.36, 0.52)). This difference in √dense area was significant for direct digital systems (Hologic 0.50 cm (95% CI: 0.39, 0.61), GE 0.56 cm (95% CI: 0.42, 0.69)) but not for Fuji CR (0.06 cm (95% CI: -0.10, 0.23)). Additionally, within each system, reader-specific differences varied in magnitude and direction (p < 0.001). Conversion equations revealed differences converged to zero with increasing dense area. MD differences between screen-film and processed digital on the subsequent screening round were consistent with expected time-related MD declines. CONCLUSIONS: MD was slightly higher when measured on processed than on raw direct digital mammograms. Comparisons of MD on these image formats should ideally control for this non-constant and reader-specific difference.

Background: Colorectal cancer (CRC) is the second leading cause of cancer-related death in the United States, with a 5-y survival rate of ~65%. Therefore, the identification of modifiable health factors to improve CRC survival is crucial. Objective: We investigated the association of 4 prediagnostic a priori diet quality indexes with CRC-specific and all-cause mortality in the Multiethnic Cohort (MEC). Methods: The MEC included >215,000 African-American, Native Hawaiian, Japanese-American, Latino, and white adults living in Hawaii and California who completed a validated quantitative food-frequency questionnaire in 1993-1996. CRC cases and deaths were identified through linkages to cancer registries and to state and national vital registries. Sexspecific HRs and 95% CIs were estimated for the Healthy Eating Index (HEI) 2010, the Alternative HEI (AHEI) 2010, the alternate Mediterranean Diet (aMED) score, and the Dietary Approaches to Stop Hypertension (DASH) index with CRC-specific and overall mortality as the primary outcomes. Ethnicity-specific analyses were the secondary outcomes. Results: Among 4204 MEC participants diagnosed with invasive CRC through 2010, 1976 all-cause and 1095 CRC-specific deaths were identified. A higher aMED score was associated with lower CRC-specific mortality in women [HR continuous pattern score divided by its respective SD (HR1SD): 0.86; 95% CI: 0.77, 0.96] but not in men (HR1SD: 1.01; 95% CI: 0.92, 1.11). A higher aMED score was also associated with lower all-cause mortality in women (HR1SD: 0.88; 95% CI: 0.81, 0.96) but not in men (HR1SD: 1.00; 95% CI: 0.93, 1.07). The HEI-2010, AHEI-2010, and DASH index were not significantly associated with CRC-specific or with all-cause mortality. The inverse relation for the aMED score was limited to African Americans and to colon (compared with rectal) cancer. Conclusions: The aMED score was related to lower mortality only in African-American women (1 of 5 ethnic groups studied). The results

Genome-wide association studies have identified SNPs near ZNF365 at 10q21.2 that are associated with both breast cancer risk and mammographic density. To identify the most likely causal SNPs, we fine mapped the association signal by genotyping 428 SNPs across the region in 89,050 European and 12,893 Asian case and control subjects from the Breast Cancer Association Consortium. We identified four independent sets of correlated, highly trait-associated variants (iCHAVs), three of which were located within ZNF365. The most strongly risk-associated SNP, rs10995201 in iCHAV1, showed clear evidence of association with both estrogen receptor (ER)-positive (OR = 0.85 [0.82-0.88]) and ER-negative (OR = 0.87 [0.82-0.91]) disease, and was also the SNP most strongly associated with percent mammographic density. iCHAV2 (lead SNP, chr10: 64,258,684:D) and iCHAV3 (lead SNP, rs7922449) were also associated with ER-positive (OR = 0.93 [0.91-0.95] and OR = 1.06 [1.03-1.09]) and ER-negative (OR = 0.95 [0.91-0.98] and OR = 1.08 [1.04-1.13]) disease. There was weaker evidence for iCHAV4, located 5′ of ADO, associated only with ER-positive breast cancer (OR = 0.93 [0.90-0.96]). We found 12, 17, 18, and 2 candidate causal SNPs for breast cancer in iCHAVs 1-4, respectively. Chrom

INTRODUCTION: Mammographic density is an established breast cancer risk factor with a strong genetic component and can be increased in women using menopausal hormone therapy (MHT). Here, we aimed to identify genetic variants that may modify the association between MHT use and mammographic density. METHODS: The study comprised 6,298 postmenopausal women from the Mayo Mammography Health Study and nine studies included in the Breast Cancer Association Consortium. We selected for evaluation 1327 single nucleotide polymorphisms (SNPs) showing the lowest P-values for interaction (P int) in a meta-analysis of genome-wide gene-environment interaction studies with MHT use on risk of breast cancer, 2541 SNPs in candidate genes (AKR1C4, CYP1A1-CYP1A2, CYP1B1, ESR2, PPARG, PRL, SULT1A1-SULT1A2 and TNF) and ten SNPs (AREG-rs10034692, PRDM6-rs186749, ESR1-rs12665607, ZNF365-rs10995190, 8p11.23-rs7816345, LSP1-rs3817198, IGF1-rs703556, 12q24-rs1265507, TMEM184B-rs7289126, and SGSM3-rs17001868) associated with mammographic density in genome-wide studies. We used multiple linear regression models adjusted for potential confounders to evaluate interactions between SNPs and current use of MHT on mammographic density. RESULTS: No significant interactions were identified after adjustment for multiple testing. The strongest SNP-MHT interaction (unadjusted P int <0.0004) was observed with rs9358531 6.5kb 5' of PRL. Furthermore, three SNPs in PLCG2 that had previously been shown to modify the association of MHT use with breast cancer risk were found to modify also the association of MHT use with mammographic density (unadjusted P int <0.002), but solely among cases (unadjusted P int SNP×MHT×case-status <0.02). CONCLUSIONS: The study identified potential interactions on mammographic density between current use of MHT and SNPs near PRL and in PLCG2, which require confirmation. Given the moderate size of the interactions observed, larger studies are needed to identify genetic modifiers of the

Aims/hypothesis: Dietary patterns have been associated with the incidence of type 2 diabetes, but little is known about the impact of ethnicity on this relationship. This study evaluated the association between four a priori dietary quality indexes and risk of type 2 diabetes among white individuals, Japanese-Americans and Native Hawaiians in the Hawaii component of the Multiethnic Cohort.Methods: After excluding participants with prevalent diabetes and missing values, the analysis included 89,185 participants (11,217 cases of type 2 diabetes). Dietary intake was assessed at baseline with a quantitative food frequency questionnaire designed for use in the relevant ethnic populations. Sex- and ethnicity-specific HRs were calculated for the Healthy Eating Index-2010 (HEI-2010), the Alternative HEI-2010 (AHEI-2010), the Alternate Mediterranean Diet Score (aMED) and the Dietary Approaches to Stop Hypertension (DASH).Results: We observed significant inverse associations between higher DASH index scores and risk of type 2 diabetes in white men and women, as well as in Japanese-American women and Native Hawaiian men, with respective risk reductions of 37%, 31%, 19% and 21% (in the highest compared with the lowest index category). A higher adherence to the AHEI-2010 and aMED diet was related to a 13–28% lower risk of type 2 diabetes in white participants but not in other ethnic groups. No significant associations with risk of type 2 diabetes were observed for the HEI-2010 index.Conclusions/interpretation: The small ethnic differences in risk of type 2 diabetes associated with scores of a priori-defined dietary patterns may be due to a different consumption pattern of food components and the fact that the original indexes were not based on diets typical for Asians and Pacific Islanders.