Disentangling the relationships of body mass index and circulating sex hormone concentrations in mammographic density using Mendelian randomization.

PURPOSE: Mammographic density phenotypes, adjusted for age and body mass index (BMI), are strong predictors of breast cancer risk. BMI is associated with mammographic density measures, but the role of circulating sex hormone concentrations is less clear. We investigated the relationship between BMI, circulating sex hormone concentrations, and mammographic density phenotypes using Mendelian randomization (MR). METHODS: We applied two-sample MR approaches to assess the association between genetically predicted circulating concentrations of sex hormones [estradiol, testosterone, sex hormone-binding globulin (SHBG)], BMI, and mammographic density phenotypes (dense and non-dense area). We created instrumental variables from large European ancestry-based genome-wide association studies and applied estimates to mammographic density phenotypes in up to 14,000 women of European ancestry. We performed analyses overall and by menopausal status. RESULTS: Genetically predicted BMI was positively associated with non-dense area (IVW: ß = 1.79; 95% CI = 1.58, 2.00; p = 9.57 × 10-63) and inversely associated with dense area (IVW: ß = - 0.37; 95% CI = - 0.51,- 0.23; p = 4.7 × 10-7). We observed weak evidence for an association of circulating sex hormone concentrations with mammographic density phenotypes, specifically inverse associations between genetically predicted testosterone concentration and dense area (ß = - 0.22; 95% CI = - 0.38, - 0.053; p = 0.009) and between genetically predicted estradiol concentration and non-dense area (ß = - 3.32; 95% CI = - 5.83, - 0.82; p = 0.009), although results were not consistent across a range of MR approaches. CONCLUSION: Our findings support a positive causal association between BMI and mammographic non-dense area and an inverse association between BMI and dense area. Evidence was weaker and inconsistent for a causal effect of circulating sex hormone concentrations on mammographic density phenotypes. Based on our findings, associations between circulating sex hormone concentrations and mammographic density phenotypes are weak at best.

Predictors of visceral and subcutaneous adipose tissue and muscle density: The ShapeUp! Kids study.

BACKGROUND AND AIMS: Body fat distribution, i.e., visceral (VAT), subcutaneous adipose tissue (SAT) and intramuscular fat, is important for disease prevention, but sex and ethnic differences are not well understood. Our aim was to identify anthropometric, demographic, and lifestyle predictors for these outcomes. METHODS AND RESULTS: The cross-sectional ShapeUp!Kids study was conducted among five ethnic groups aged 5-18 years. All participants completed questionnaires, anthropometric measurements, and abdominal MRI scans. VAT and SAT areas at four lumbar levels and muscle density were assessed manually. General linear models were applied to estimate coefficients of determination (R2) and to compare the fit of VAT and SAT prediction models. After exclusions, the study population had 133 male and 170 female participants. Girls had higher BMI-z scores, waist circumference (WC), and SAT than boys but lower VAT/SAT and muscle density. SAT, VAT, and VAT/SAT but not muscle density differed significantly by ethnicity. R2 values were higher for SAT than VAT across groups and improved slightly after adding WC. For SAT, R2 increased from 0.85 to 0.88 (girls) and 0.62 to 0.71 (boys) when WC was added while VAT models improved from 0.62 to 0.65 (girls) and 0.57 to 0.62 (boys). VAT values were significantly lower among Blacks than Whites with little difference for the other groups. CONCLUSION: This analysis in a multiethnic population identified BMI-z scores and WC as the major predictors of MRI-derived SAT and VAT and highlights the important ethnic differences that need to be considered in diverse populations.

Diet Quality and Body Mass Index Over 20 Years in the Multiethnic Cohort.

BACKGROUND: With increasing rates of overweight and obesity and disparities by ethnicity, it is important to understand the role of diet in ameliorating this health problem. OBJECTIVE: This study examined the relation of diet quality as measured by the Healthy Eating Index 2015 with body mass index (BMI; calculated as kg/m2) and obesity among participants of the Multiethnic Cohort (MEC) in cross-sectional analyses at 3 time points (T-1, T-2, and T-3) over 20 years. DESIGN: In a subset of 1,860 MEC participants, 3 cross-sectional analyses at cohort entry (1993 to 1996, T-1) and follow-ups in 2003 to 2008 (T-2) and 2013 to 2016 (T-3) were performed. PARTICIPANTS/SETTING: The cohort consists of African American, Native Hawaiian, Japanese American, Latino, and White adults in Hawaii and California; mean age was 48 years at T-1. MAIN OUTCOME MEASURE: BMI and weight status in relation to diet quality were measured. STATISTICAL ANALYSIS: Linear and multinomial logistic regressions were applied to analyze the relation of diet quality with BMI and obesity, while adjusting for known confounders. RESULTS: Healthy Eating Index 2015 increased by 6.1 and 5.1 units for men and women, respectively, from T-1 to T-3; the respective values for BMI were 1.5 and 2.4. Diet quality was inversely associated with BMI across time: BMI was lower by -0.47, -0.72, and -0.92 units for every 10-point increase in Healthy Eating Index 2015 scores at T-1, T-2, and T-3, respectively (P < .0001 for all). During the 20 years, the association was consistently high among Japanese American participants (-0.79, -0.87, and -1.02) and weakest in African American cohort members (-0.34, -0.37, and -0.40). Higher diet quality was related to lower odds of having obesity at all 3 time points; prevalence odds ratios were 0.72, 0.57, and 0.60. CONCLUSIONS: These findings suggest that consuming a high-quality diet is related to lower BMI and rates of overweight and obesity but with the strongest association at an older age. To understand the ethnic differences, investigations of dietary habits and behaviors and/or fat distribution patterns will be needed in the future.

The association of a healthy lifestyle index and imaging-based body fat distribution with glycemic status and Type 2 diabetes in the Multi Ethnic Cohort: a cross-sectional analysis.

INTRODUCTION: As several behaviors captured by the Lifestyle Risk Factor Index (LSRI) are protective against Type 2 diabetes (T2D) and may affect body fat distribution, we examined its relation with both outcomes. METHODS: In a subset of the Multiethnic Cohort, participants from five ethnic groups (60-77 years) were assigned LSRI scores (one point each for consuming <1 (women)/<2 (men) alcoholic drinks/day, ≥1.5 physical activity hours/week, not smoking, and adhering to ≥3/7 dietary recommendations). All participants completed an extensive Quantitative Food Frequency Questionnaire to allow estimation of adherence to intake recommendations for fruits, vegetables, refined and whole grains, fish, processed and non-processed meat. Glycemic/T2D status was classified according to self-reports and fasting glucose. We estimated prevalence odds ratios (POR) of LSRI with glycemic/T2D status and DXA- and MRI-based body fat distribution using logistic regression. RESULTS: Of 1713 participants, 43% had normoglycemia, 30% Pre-T2D, 9% Undiagnosed T2D, and 18% T2D. Overall, 39% scored 0-2, 49% 3, and 12% 4 LSRI points. T2D prevalence was 55% (POR 0.45; 95% confidence intervals 0.27, 0.76) lower for 4 vs. 0-2 LSRI points with weaker associations for abnormal glycemic status. Despite the low adherence to dietary recommendations (22%), this was the only component related to lower T2D prevalence. The inverse LSRI-T2D association was only observed among Latinos and Japanese Americans in ethnic-specific models. Visceral fat measures were higher in T2D patients and attenuated the LSRI-T2D association. CONCLUSION: These findings support the role of a healthy lifestyle, especially diet, in T2D prevention with differences across ethnicity.

Cross-sectional assessment of body composition and detection of malnutrition risk in participants with low body mass index and eating disorders using 3D optical surface scans.

BACKGROUND: New recommendations for the assessment of malnutrition and sarcopenia include body composition, specifically reduced muscle mass. Three-dimensional optical imaging (3DO) is a validated, accessible, and affordable alternative to dual X-ray absorptiometry (DXA). OBJECTIVE: Identify strengths and weaknesses of 3DO for identification of malnutrition in participants with low body mass index (BMI) and eating disorders. DESIGN: Participants were enrolled in the cross-sectional Shape Up! Adults and Kids studies of body shape, metabolic risk, and functional assessment and had BMI of <20 kg/m2 in adults or <85% of median BMI (mBMI) in children and adolescents. A subset was referred for eating disorders evaluation. Anthropometrics, scans, strength testing, and questionnaires were completed in clinical research centers. Lin's Concordance Correlation Coefficient (CCC) assessed agreement between 3DO and DXA; multivariate linear regression analysis examined associations between weight history and body composition. RESULTS: Among 95 participants, mean ± SD BMI was 18.3 ± 1.4 kg/m2 in adult women (N = 56), 19.0 ± 0.6 in men (N = 14), and 84.2% ± 4.1% mBMI in children (N = 25). Concordance was excellent for fat-free mass (FFM, CCC = 0.97) and strong for appendicular lean mass (ALM, CCC = 0.86) and fat mass (FM, CCC = 0.87). By DXA, 80% of adults met the low FFM index criterion for malnutrition, and 44% met low ALM for sarcopenia; 52% of children and adolescents were <-2 z-score for FM. 3DO identified 95% of these cases. In the subset, greater weight loss predicted lower FFM, FM, and ALM by both methods; a greater percentage of weight regained predicted a higher percentage of body fat. CONCLUSIONS: 3DO can accurately estimate body composition in participants with low BMI and identify criteria for malnutrition and sarcopenia. In a subset, 3DO detected changes in body composition expected with weight loss and regain secondary to eating disorders. These findings support the utility of 3DO for body composition assessment in patients with low BMI, including those with eating disorders. This trial was registered at clinicaltrials.gov as NCT03637855.

Association of Obesity and Type 2 Diabetes with Non-Hodgkin Lymphoma: The Multiethnic Cohort.

BACKGROUND: Given the role of the immune system in non-Hodgkin lymphoma (NHL) etiology, obesity and type 2 diabetes (T2D) may impact NHL development. We examined the association of body mass index (BMI) and T2D with NHL in the multiethnic cohort (MEC). METHODS: The MEC recruited >215,000 participants in Hawaii and Los Angeles from five racial/ethnic groups; NHL cases were identified through cancer registry linkages. T2D status, and BMI at age 21 and cohort entry were derived from repeated self-reports; for T2D, Medicare claims were also applied. HRs and 95% confidence intervals (CI) for BMI and T2D as predictors of NHL were determined using Cox regression adjusted for relevant covariates. RESULTS: Among 192,424 participants, 3,472 (1.8%) with NHL and 68,850 (36%) with T2D after 19.2 ± 6.6 years follow-up, no significant association between T2D and NHL (HR, 1.04; 95% CI, 0.96-1.13) was observed. Stratification by BMI at cohort entry showed a significant association of T2D with NHL among individuals with normal weight only (HR, 1.18; 95% CI, 1.03-1.37). In a model with both BMI values plus T2D, only overweight (HR, 1.13; 95% CI, 1.01-1.26) and obesity (HR, 1.25; 95% CI, 0.99-1.59) at age 21 were associated with NHL incidence. Stratification by sex, race/ethnicity, and NHL subtype indicated no differences. CONCLUSIONS: Our findings suggest an association between T2D and NHL incidence in several subgroups but not in the total population and an elevated risk related to early-life BMI. IMPACT: Excess body weight in early life, rather than T2D, may be a predictor of NHL incidence.

Risk Factors for Type 2 Diabetes in the Multiethnic Cohort.

OBJECTIVES: In this report, we investigated the association between established risk factors and type 2 diabetes (T2D) across 5 distinct ethnic groups and explored differences according to T2D definition within the Multiethnic Cohort (MEC) Study. METHODS: Using the full MEC, with participants in Hawaii and Los Angeles (N=172,230), we applied Cox regression to estimate hazard ratios (HRs) and 95% confidence intervals (CIs). All participants completed questionnaires asking about demographics, anthropometrics, lifestyle factors, and regular diet. T2D status was determined from self-reported diagnosis/medication and Medicare claims. We assessed the associations between well-established risk factors and T2D in the full cohort, after stratification by ethnic group, according to the T2D definition, and in a biorepository subset. Effect modification by ethnicity was evaluated using Wald's tests. RESULTS: Overall, 46,500 (27%) participants had an incident T2D diagnosis after a mean follow-up of 17.1±6.9 years. All predictors were significantly associated with T2D: overweight (HR=1.74), obesity (HR=2.90), red meat intake (HR=1.15), short (HR=1.04) and long (HR=1.08) sleep duration, and smoking (HR=1.26) predicted a significantly higher T2D incidence, whereas coffee (HR=0.90) and alcohol (HR=0.78) consumption, physical activity (HR=0.89), and diet quality (HR=0.96) were associated with lower T2D incidence. The strength of these associations was similar across ethnic groups with noteworthy disparities for overweight/obesity, physical activity, alcohol intake, coffee consumption, and diet quality. CONCLUSIONS: These findings confirm the importance of known risk factors for T2D across ethnic groups, but small differences were detected that may contribute to disparate incidence rates in some ethnic groups, especially for obesity and physical activity.

Accuracy and Precision of 3-dimensional Optical Imaging for Body Composition by Age, BMI, and Ethnicity.

BACKGROUND: The obesity epidemic brought a need for accessible methods to monitor body composition, as excess adiposity has been associated with cardiovascular disease, metabolic disorders, and some cancers. Recent 3-dimensional optical (3DO) imaging advancements have provided opportunities for assessing body composition. However, the accuracy and precision of an overall 3DO body composition model in specific subgroups are unknown. OBJECTIVES: This study aimed to evaluate 3DO's accuracy and precision by subgroups of age, body mass index, and ethnicity. METHODS: A cross-sectional analysis was performed using data from the Shape Up! Adults study. Each participant received duplicate 3DO and dual-energy X-ray absorptiometry (DXA) scans. 3DO meshes were digitally registered and reposed using Meshcapade. Principal component analysis was performed on 3DO meshes. The resulting principal components estimated DXA whole-body and regional body composition using stepwise forward linear regression with 5-fold cross-validation. Duplicate 3DO and DXA scans were used for test-retest precision. Student's t tests were performed between 3DO and DXA by subgroup to determine significant differences. RESULTS: Six hundred thirty-four participants (females = 346) had completed the study at the time of the analysis. 3DO total fat mass in the entire sample achieved R2 of 0.94 with root mean squared error (RMSE) of 2.91 kg compared to DXA in females and similarly in males. 3DO total fat mass achieved a % coefficient of variation (RMSE) of 1.76% (0.44 kg), whereas DXA was 0.98% (0.24 kg) in females and similarly in males. There were no mean differences for total fat, fat-free, percent fat, or visceral adipose tissue by age group (P > 0.068). However, there were mean differences for underweight, Asian, and Black females as well as Native Hawaiian or other Pacific Islanders (P < 0.038). CONCLUSIONS: A single 3DO body composition model produced accurate and precise body composition estimates that can be used on diverse populations. However, adjustments to specific subgroups may be warranted to improve the accuracy in those that had significant differences. This trial was registered at clinicaltrials.gov as NCT03637855 (Shape Up! Adults).

Interethnic Differences in Bladder Cancer Incidence and the Association between Type 2 Diabetes and Bladder Cancer in the Multiethnic Cohort Study.

Background: Research on the association between type 2 diabetes (T2D) and bladder cancer (BCA) risk among non-European ancestry populations is sparse to nonexistent, and most prior studies rely on a single baseline assessment of T2D status. Methods: We estimated the T2D-BCA association using the Multiethnic Cohort Study of 185,059 men and women in California and Hawaii. Participants were African American, European American, Japanese American, Latin American, and Native Hawaiian, ages 45-75 years at enrollment (1993-1996). T2D was assessed by self-report at baseline, follow-up surveys, and Medicare claims. Cases were identified using Surveillance, Epidemiology and End Results Program cancer registries through 2016. Associations were estimated by race/ethnicity using Cox proportional hazards regression. Adjusted attributable fractions (AAF) and cumulative absolute risk of bladder cancer were estimated across groups. Results: Over an average 19.7 years of follow-up 1,890 incident bladder cancer cases were diagnosed. Time-varying T2D was associated with bladder cancer in the multiethnic sample (HR = 1.17; 95% confidence interval, 1.05-1.30); however, the HR did not differ by race/ethnicity (P = 0.85). The AAF was 4.2% in the multiethnic sample and largest among Native Hawaiians (9.8%). Absolute risk of bladder cancer among European Americans without T2D was higher than all other groups with T2D. Conclusion: T2D is significantly associated with bladder cancer risk in a multiethnic sample. Significance: Those with T2D have higher incidence of bladder cancer, regardless of racial/ethnic group. Reducing T2D prevalence could substantially lower bladder cancer incidence among Native Hawaiians due to T2D being more common in this group. High absolute risk of bladder cancer among European Americans, regardless of T2D status, indicates that elevated bladder cancer risk in this group may be due to factors other than T2D. Future studies must explore reasons for this difference in incidence.

Monitoring body composition change for intervention studies with advancing 3D optical imaging technology in comparison to dual-energy X-ray absorptiometry.

BACKGROUND: Recent 3-dimensional optical (3DO) imaging advancements have provided more accessible, affordable, and self-operating opportunities for assessing body composition. 3DO is accurate and precise in clinical measures made by DXA. However, the sensitivity for monitoring body composition change over time with 3DO body shape imaging is unknown. OBJECTIVES: This study aimed to evaluate the ability of 3DO in monitoring body composition changes across multiple intervention studies. METHODS: A retrospective analysis was performed using intervention studies on healthy adults that were complimentary to the cross-sectional study, Shape Up! Adults. Each participant received a DXA (Hologic Discovery/A system) and 3DO (Fit3D ProScanner) scan at the baseline and follow-up. 3DO meshes were digitally registered and reposed using Meshcapade to standardize the vertices and pose. Using an established statistical shape model, each 3DO mesh was transformed into principal components, which were used to predict whole-body and regional body composition values using published equations. Body composition changes (follow-up minus the baseline) were compared with those of DXA using a linear regression analysis. RESULTS: The analysis included 133 participants (45 females) in 6 studies. The mean (SD) length of follow-up was 13 (5) wk (range: 3-23 wk). Agreement between 3DO and DXA (R2) for changes in total FM, total FFM, and appendicular lean mass were 0.86, 0.73, and 0.70, with root mean squared errors (RMSEs) of 1.98 kg, 1.58 kg, and 0.37 kg, in females and 0.75, 0.75, and 0.52 with RMSEs of 2.31 kg, 1.77 kg, and 0.52 kg, in males, respectively. Further adjustment with demographic descriptors improved the 3DO change agreement to changes observed with DXA. CONCLUSIONS: Compared with DXA, 3DO was highly sensitive in detecting body shape changes over time. The 3DO method was sensitive enough to detect even small changes in body composition during intervention studies. The safety and accessibility of 3DO allows users to self-monitor on a frequent basis throughout interventions. This trial was registered at clinicaltrials.gov as NCT03637855 (Shape Up! Adults; https://clinicaltrials.gov/ct2/show/NCT03637855); NCT03394664 (Macronutrients and Body Fat Accumulation: A Mechanistic Feeding Study; https://clinicaltrials.gov/ct2/show/NCT03394664); NCT03771417 (Resistance Exercise and Low-Intensity Physical Activity Breaks in Sedentary Time to Improve Muscle and Cardiometabolic Health; https://clinicaltrials.gov/ct2/show/NCT03771417); NCT03393195 (Time Restricted Eating on Weight Loss; https://clinicaltrials.gov/ct2/show/NCT03393195), and NCT04120363 (Trial of Testosterone Undecanoate for Optimizing Performance During Military Operations; https://clinicaltrials.gov/ct2/show/NCT04120363).

Circulating vitamin D and breast cancer risk: an international pooling project of 17 cohorts.

Laboratory and animal research support a protective role for vitamin D in breast carcinogenesis, but epidemiologic studies have been inconclusive. To examine comprehensively the relationship of circulating 25-hydroxyvitamin D [25(OH)D] to subsequent breast cancer incidence, we harmonized and pooled participant-level data from 10 U.S. and 7 European prospective cohorts. Included were 10,484 invasive breast cancer cases and 12,953 matched controls. Median age (interdecile range) was 57 (42-68) years at blood collection and 63 (49-75) years at breast cancer diagnosis. Prediagnostic circulating 25(OH)D was either newly measured using a widely accepted immunoassay and laboratory or, if previously measured by the cohort, calibrated to this assay to permit using a common metric. Study-specific relative risks (RRs) for season-standardized 25(OH)D concentrations were estimated by conditional logistic regression and combined by random-effects models. Circulating 25(OH)D increased from a median of 22.6 nmol/L in consortium-wide decile 1 to 93.2 nmol/L in decile 10. Breast cancer risk in each decile was not statistically significantly different from risk in decile 5 in models adjusted for breast cancer risk factors, and no trend was apparent (P-trend = 0.64). Compared to women with sufficient 25(OH)D based on Institute of Medicine guidelines (50- < 62.5 nmol/L), RRs were not statistically significantly different at either low concentrations (< 20 nmol/L, 3% of controls) or high concentrations (100- < 125 nmol/L, 3% of controls; ≥ 125 nmol/L, 0.7% of controls). RR per 25 nmol/L increase in 25(OH)D was 0.99 [95% confidence intervaI (CI) 0.95-1.03]. Associations remained null across subgroups, including those defined by body mass index, physical activity, latitude, and season of blood collection. Although none of the associations by tumor characteristics reached statistical significance, suggestive inverse associations were seen for distant and triple negative tumors. Circulating 25(OH)D, comparably measured in 17 international cohorts and season-standardized, was not related to subsequent incidence of invasive breast cancer over a broad range in vitamin D status.

White Rice Consumption and Risk of Colorectal Cancer Among Japanese Americans: The Multiethnic Cohort Study.

BACKGROUND: White rice is a staple food for Japanese, a population at high risk for colorectal cancer (CRC). We investigated the association between white rice intake and CRC among Japanese Americans in the Multiethnic Cohort (MEC) study. METHODS: The MEC study is a prospective study established in Hawaii and California in 1993-1996. Usual dietary intake was assessed using a validated quantitative food frequency questionnaire at baseline. Cox proportional hazards models were used to compute hazard ratios (HRs) and 95% confidence intervals (CIs) for quartiles of intake and to perform trend tests across sex-specific quartiles with adjustment for relevant confounders. RESULTS: We identified 1,553 invasive CRC cases among 49,136 Japanese Americans (23,595 men and 25,541 women) during a mean follow-up of 19 years. White rice consumption was not associated with overall CRC incidence in men (Ptrend = 0.11) or women (Ptrend = 0.56). After excluding participants with a history of diabetes, the inverse associations were significant for CRC (Ptrend = 0.03, HR for quartile 4 [Q4] vs quartile 1 [Q1], 0.81; 95% CI, 0.64-1.03) and tumors of the distal colon (Ptrend = 0.006, HR for Q4 vs Q1, 0.66; 95% CI, 0.44-0.99) among men but not women. CONCLUSION: White rice consumption was not associated with an increased risk of overall CRC among Japanese Americans. An inverse association was observed with risk of CRC and distal colon cancer in men without a history of diabetes.

The accuracy of polygenic score models for anthropometric traits and Type II Diabetes in the Native Hawaiian Population.

Polygenic scores (PGS) are promising in stratifying individuals based on the genetic susceptibility to complex diseases or traits. However, the accuracy of PGS models, typically trained in European- or East Asian-ancestry populations, tend to perform poorly in other ethnic minority populations, and their accuracies have not been evaluated for Native Hawaiians. Using body mass index, height, and type-2 diabetes as examples of highly polygenic traits, we evaluated the prediction accuracies of PGS models in a large Native Hawaiian sample from the Multiethnic Cohort with up to 5,300 individuals. We evaluated both publicly available PGS models or genome-wide PGS models trained in this study using the largest available GWAS. We found evidence of lowered prediction accuracies for the PGS models in some cases, particularly for height. We also found that using the Native Hawaiian samples as an optimization cohort during training did not consistently improve PGS performance. Moreover, even the best performing PGS models among Native Hawaiians would have lowered prediction accuracy among the subset of individuals most enriched with Polynesian ancestry. Our findings indicate that factors such as admixture histories, sample size and diversity in GWAS can influence PGS performance for complex traits among Native Hawaiian samples. This study provides an initial survey of PGS performance among Native Hawaiians and exposes the current gaps and challenges associated with improving polygenic prediction models for underrepresented minority populations.

Association of Habitual Intake of Probiotic Supplements and Yogurt with Characteristics of the Gut Microbiome in the Multiethnic Cohort Adiposity Phenotype Study.

Consumption of probiotics and/or yogurt could be a solution for restoring the balance of the gut microbiota. This study examined associations of regular intake of probiotic supplements or yogurt with the gut microbiota among a diverse population of older adults (N=1,861; 60-72 years). Fecal microbial composition was obtained from 16S rRNA gene sequencing (V1-V3 region). General Linear Models were used to estimate the associations of probiotic supplement or yogurt intake with microbiome measures adjusting for covariates. Compared to non-yogurt consumers (N=1,023), regular yogurt consumers (≥once/week, N=818) had greater Streptococcus (ß=0.29, P=0.0003) and lower Odoribacter (ß=-0.33, P<0.0001) abundance. The directions of the above associations were consistent across the five ethnic groups but stronger among Japanese Americans (Streptococcus: ß=0.56, P=0.0009; Odoribacter: ß=-0.62, P=0.0005). Regular intake of probiotic supplements (N=175) was not associated with microbial characteristics (i.e., alpha diversity and the abundance of 152 bacteria genera). Streptococcus is one of the predominant bacteria genera in yogurt products, which may explain the positive association between yogurt consumption and Streptococcus abundance. Our analyses suggest that changes in Odoribacter were independent of changes in Streptococcus abundance. Future studies may investigate whether these microbial genera and their sub-level species mediate potential pathways between yogurt consumption and health.

A genome-wide gene-based gene-environment interaction study of breast cancer in more than 90,000 women.

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.

The association of age at menarche and adult height with mammographic density in the International Consortium of Mammographic Density.

BACKGROUND: Early age at menarche and tall stature are associated with increased breast cancer risk. We examined whether these associations were also positively associated with mammographic density, a strong marker of breast cancer risk. METHODS: Participants were 10,681 breast-cancer-free women from 22 countries in the International Consortium of Mammographic Density, each with centrally assessed mammographic density and a common set of epidemiologic data. Study periods for the 27 studies ranged from 1987 to 2014. Multi-level linear regression models estimated changes in square-root per cent density (√PD) and dense area (√DA) associated with age at menarche and adult height in pooled analyses and population-specific meta-analyses. Models were adjusted for age at mammogram, body mass index, menopausal status, hormone therapy use, mammography view and type, mammographic density assessor, parity and height/age at menarche. RESULTS: In pooled analyses, later age at menarche was associated with higher per cent density (ß√PD = 0.023 SE = 0.008, P = 0.003) and larger dense area (ß√DA = 0.032 SE = 0.010, P = 0.002). Taller women had larger dense area (ß√DA = 0.069 SE = 0.028, P = 0.012) and higher per cent density (ß√PD = 0.044, SE = 0.023, P = 0.054), although the observed effect on per cent density depended upon the adjustment used for body size. Similar overall effect estimates were observed in meta-analyses across population groups. CONCLUSIONS: In one of the largest international studies to date, later age at menarche was positively associated with mammographic density. This is in contrast to its association with breast cancer risk, providing little evidence of mediation. Increased height was also positively associated with mammographic density, particularly dense area. These results suggest a complex relationship between growth and development, mammographic density and breast cancer risk. Future studies should evaluate the potential mediation of the breast cancer effects of taller stature through absolute breast density.

Associations between exploratory dietary patterns and incident type 2 diabetes: a federated meta-analysis of individual participant data from 25 cohort studies.

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.

Genome-wide and transcriptome-wide association studies of mammographic density phenotypes reveal novel loci.

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.

Dietary Intake Mediates Ethnic Differences in Gut Microbial Composition.

Background: The human gut microbiome (GM) has been observed to vary by race/ethnicity. Objective: Assess whether racial/ethnic GM variation is mediated by differences in diet. Design: Stool samples collected from 2013 to 2016 from 5267 healthy Multiethnic Cohort participants (age 59−98) were analyzed using 16S rRNA gene sequencing to estimate the relative abundance of 152 bacterial genera. For 63 prevalent genera (>50% in each ethnic group), we analyzed the mediation of GM differences among African Americans, Japanese Americans, Latinos, Native Hawaiians, and Whites by overall diet quality (Healthy Eating Index score (HEI-2015)) and intake amounts of 14 component foods/nutrients assessed from 2003 to 2008. For each significant mediation (p < 1.3 × 10−5), we determined the percent of the total ethnicity effect on genus abundance mediated by the dietary factor. Results: Ethnic differences in the abundance of 12 genera were significantly mediated by one or more of eight dietary factors, most frequently by overall diet quality and intakes of vegetables and red meat. Lower vegetable intake mediated differences in Lachnospira (36% in African Americans, 39% in Latinos) and Ruminococcus-1 (−35% in African Americans, −43% in Latinos) compared to Native Hawaiians who consumed the highest amount. Higher red meat intake mediated differences in Lachnospira (−41%) and Ruminococcus-1 (36%) in Native Hawaiians over African Americans, who consumed the least. Dairy and alcohol intakes appeared to mediate and counterbalance the difference in Bifidobacterium between Whites and Japanese Americans. Conclusions: Overall diet quality and component food intakes may contribute to ethnic differences in GM composition and to GM-related racial/ethnic health disparities.

Subcutaneous and visceral fat assessment by DXA and MRI in older adults and children.

OBJECTIVE: Given the importance of body fat distribution in chronic disease development, feasible methods to assess body fat are essential. This study compared dual-energy x-ray absorptiometry (DXA) in measuring visceral and subcutaneous adipose tissue (VAT and SAT) with magnetic resonance imaging (MRI). METHODS: VAT and SAT were assessed using similar DXA and MRI protocols among 1,795 elderly participants of the Adiposity Phenotype Study (APS) and 309 children/adolescents in Shape Up! Kids (SKids). Spearman correlations, Bland-Altman plots, and coefficients of determination (R2 ) assessed agreement between DXA and MRI measures. RESULTS: DXA overestimated SAT values in APS (315 vs. 229 cm2 ) and SKids (212 vs. 161 cm2 ), whereas DXA underestimated VAT measures (141 vs. 167 cm2 ) in adults only. The correlations between DXA and MRI values were stronger for SAT than VAT (APS: r = 0.92 vs. 0.88; SKids: 0.90 vs. 0.74). Bland-Altman plots confirmed better agreement for SAT than VAT despite differences by sex, ethnicity, and weight status with respective R2 values for SAT and VAT of 0.88 and 0.84 (APS) and 0.81 and 0.69 (SKids). CONCLUSION: These findings indicate that SAT by DXA reflects MRI measures in children and older adults, whereas agreement for VAT is weaker for individuals with low VAT levels.