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Nutrition influences health throughout the life course. Good nutrition increases the probability of good pregnancy outcomes, proper childhood development, and healthy aging, and it lowers the probability of developing common diet-related chronic diseases, including obesity, cardiovascular disease, cancer, and type 2 diabetes. Despite the importance of diet and health, studying these exposures is among the most challenging in population sciences research. US and global food supplies are complex; eating patterns have shifted such that half of meals are eaten away from home, and there are thousands of food ingredients with myriad combinations. These complexities make dietary assessment and links to health challenging for both population sciences research and for public health policy and practice. Furthermore, most studies evaluating nutrition and health usually rely on self-report instruments prone to random and systematic measurement error. Scientific advances involve developing nutritional biomarkers and then applying these biomarkers as stand-alone nutritional exposures or for calibrating self-reports using specialized statistics. Expected final online publication date for the

Obesity is caused by a prolonged positive energy balance1,2. Whether reduced energy expenditure stemming from reduced activity levels contributes is debated3,4. Here we show that in both sexes, total energy expenditure (TEE) adjusted for body composition and age declined since the late 1980s, while adjusted activity energy expenditure increased over time. We use the International Atomic Energy Agency Doubly Labelled Water database on energy expenditure of adults in the United States and Europe (n = 4,799) to explore patterns in total (TEE: n = 4,799), basal (BEE: n = 1,432) and physical activity energy expenditure (n = 1,432) over time. In males, adjusted BEE decreased significantly, but in females this did not reach significance. A larger dataset of basal metabolic rate (equivalent to BEE) measurements of 9,912 adults across 163 studies spanning 100 years replicates the decline in BEE in both sexes. We conclude that increasing obesity in the United States/Europe has probably not been fuelled by reduced physical activity leading to lowered TEE. We identify here a decline in adjusted BEE as a previously unrecognized factor.

BACKGROUND: Studies of diet and chronic disease include a recent important focus on dietary patterns. Patterns are typically defined by listing dietary variables and by totaling scores that reflect whether consumption is encouraged or discouraged for listed variables. However, precision may be improved by including total energy consumption among the dietary variables and by scoring dietary variables empirically. OBJECTIVES: To relate Healthy Eating Index (HEI)–2010 components and total energy intake to all-cause and cause-specific mortality in Women's Health Initiative (WHI) cohorts and to define and evaluate an associated Empirical-Scores Healthy Eating Index (E-HEI). METHODS: Analyses are conducted in WHI cohorts (n = 67,247) of healthy postmenopausal women, aged 50–79 y, when enrolled during 1993–1998 at 40 US clinical centers, with embedded nutrition biomarker studies. Replicate food-frequency assessments for HEI-2010 ratio variables and doubly labeled water total energy assessments, separated by ∼6 mo, are used as response variables to jointly calibrate baseline dietary data to reduce measurement error influences, using 2 nutrition biomarker studies (n = 199). Calibrated dietary variables are associated with mortality risk, and an E-HEI is defined, using cross-validated HR regression estimation. RESULTS: Of 15 dietary variables considered, all but empty calories calibrated well. Ten variables related significantly (P

BACKGROUND: The associations of red and processed meat with chronic disease risk remain to be clarified, in part because of measurement error in self-reported diet. OBJECTIVES: We sought to develop metabolomics-based biomarkers for red and processed meat, and to evaluate associations of biomarker-calibrated meat intake with chronic disease risk among postmenopausal women. METHODS: Study participants were women who were members of the Women's Health Initiative (WHI) study cohorts. These participants were postmenopausal women aged 50–79 y when enrolled during 1993–1998 at 40 US clinical centers with embedded human feeding and nutrition biomarker studies. Literature reports of metabolomics correlates of meat consumption were used to develop meat intake biomarkers from serum and 24-h urine metabolites in a 153-participant feeding study (2010–2014). Resulting biomarkers were used in a 450-participant biomarker study (2007–2009) to develop linear regression calibration equations that adjust FFQ intakes for random and systematic measurement error. Biomarker-calibrated meat intakes were associated with cardiovascular disease, cancer, and diabetes incidence among 81,954 WHI participants (1993–2020). RESULTS: Biomarkers and calibration equations meeting prespecified criteria were developed for consumption of red meat and red plus processed meat combined, but not for processed meat consumption. Following control for nondietary confounding factors, hazard ratios were calculated for a 40% increment above the red meat median intake for coronary artery disease (HR: 1.10; 95% CI: 1.07, 1.14), heart failure (HR: 1.26; 95% CI: 1.20, 1.33), breast cancer (HR: 1.10; 95% CI: 1.07, 1.13) for, total invasive cancer (HR: 1.07; 95% CI: 1.05, 1.09), and diabetes (HR: 1.37; 95% CI: 1.34, 1.39). HRs for red plus processed meat intake were similar. HRs were close to the null, and mostly nonsignificant following additional control for dietary potential confounding factors, including calibrated total energy consumption. CONCLUSIONS: A relatively high-meat dietary pattern is associated with somewhat higher chronic disease risks. These elevations appear to be largely attributable to the dietary pattern, rather than to consumption of red or processed meat per se.

PDF file - 96K, ELISA data for individual markers in newly diagnosed samples separated based on stage at the time of diagnosis compared to matched controls. Only significant differences are demarcated. * indicates p

PDF file - 117K, ELISA data for individual markers in newly diagnosed samples separated by gender. Only significant differences are demarcated. * indicates p

PDF file - 225K, Histograms for case-to-control ratios for each of the 9 MS experiments used for normalization.

PDF file - 70K, Correlations between different markers based on ELISA data of newly diagnosed samples.

PDF file - 112K, Workflow of experiments and sample cohorts described in the manuscript.

Supplementary Data from The Association of Predicted Resting Energy Expenditure with Risk of Breast Cancer among Postmenopausal Women in the Women's Health Initiative Cohort

PDF fiel - 144K, Peptide coverage for each of the 6 individual proteins in two colorectal cancer cell lines with different driver mutations.

Background: The respiratory quotient (RQ), defined as the ratio of carbon dioxide exhaled to oxygen uptake, reflects substrate utilization when energy is expended. Fat and alcohol have RQ values of approximately 0.7, compared with 1.0 for carbohydrate, and approximately 0.8 for protein. Here, the association between RQ and postmenopausal breast cancer risk is studied.Methods: Paired RQ measurements were obtained, separated by approximately 6 months, for women in the reliability subset of a Women's Health Initiative (WHI) Nutrition and Physical Activity Assessment Study. Linear regression of the average of the paired log RQ assessments on a corresponding log food quotient (FQ) average and other study subject characteristics, including age, body mass index, race, and education, yielded calibration equations for predicting RQ.Results: Calibration equations, using any of food frequency, food record, or dietary recall data, explained an appreciable fraction of measured log RQ variation, and these were used to compute calibrated RQ estimates throughout WHI cohorts. Calibrated RQ estimates using 4-day food record (4DFR) data related inversely (P = 0.004) to (invasive) breast cancer risk in the WHI Dietary Modification trial comparison group, and corresponding RQ estimates using food-frequency data related inversely (P = 0.002) to breast cancer incidence in this cohort combined with the larger WHI observational study.Conclusion: Although preliminary, these analyses suggest a substantially higher postmenopausal breast cancer risk among women having relatively low RQ.Impact: RQ elevation could provide a novel target for breast cancer risk reduction. Cancer Epidemiol Biomarkers Prev; 22(12); 2374–83. ©2013 AACR.

Background: Selenium may prevent colorectal cancer. However, several previous studies are small and few investigated the association between selenium and colorectal cancer among women whose selenium metabolism may differ from men. Furthermore, genetic variants in selenoenzymes may be associated with colorectal cancer risk.Methods: This nested case–control study investigated whether serum selenium concentration and genetic variants in five selenoenzymes (glutathione peroxidase 1–4 and selenoprotein P) were associated with colorectal cancer risk in 804 colorectal cancer cases and 805 matched controls from the Women's Health Initiative (WHI) Observational Study. A meta-analysis was conducted to compare the WHI result with previous studies including 12 observational studies and two clinical trials on selenium.Results: Within the WHI, selenium concentrations were relatively high (mean = 135.6 μg/L) and were not associated with colorectal cancer risk (Ptrend = 0.10); the adjusted OR comparing the fifth with first quintile was 1.26 (95% CI, 0.91–1.73). Moreover, genetic variants in selenoenzymes were not significantly associated with colorectal cancer risk. Consistent with the finding in WHI, our meta-analysis showed no association between selenium and colorectal tumor risk in women (OR = 0.97; 95% CI, 0.79–1.18) comparing the highest quantile with the lowest); however, in men, there was a significant inverse association (OR = 0.68; 95% CI, 0.57–0.82) (P = 0.01).Conclusion: Consistent with previous studies, we observed no protective effect of selenium on colorectal cancer among women.Impact: Our analyses suggest that a population with relatively high selenium concentrations, especially women, would not benefit from increasing selenium intake. Cancer Epidemiol Biomarkers Prev; 20(9); 1822–30. ©2011 AACR.

Percentage of Participants Enrolled in the Women's Health Initiative Dietary Modification Trial Who Were Alive and Not Withdrawn on March 31, 2005 Who Consented to Extended Follow-up (n=45560 )

Purpose: Pancreatic ductal adenocarcinoma (PDA) is the fourth leading cause of cancer-related death in the United States, and its incidence is on the rise. Advanced disease is nearly uniformly lethal, emphasizing the need to identify PDA at its earliest stages. To discover early biomarkers of PDA, we evaluated the circulating proteome in murine preinvasive and invasive plasma samples and human prediagnostic and diagnostic samples.Experimental Design: Using a customized antibody microarray platform containing >4,000 features, we interrogated plasma samples spanning preinvasive and invasive disease from a highly faithful mouse model of PDA. In parallel, we mined prediagnostic plasma from women in the Women's Health Initiative (WHI) who would later succumb to PDA together with matched, cancer-free control samples. Samples collected after an establishing diagnosis of PDA were also interrogated to further validate markers.Results: We identified ERBB2 and TNC in our cross-species analyses, and multiple antibodies identified ESR1 in prediagnostic plasma from people that succumb to PDA. This 3-marker panel had an AUC of 0.86 (95% confidence interval [CI], 0.76–0.96) for the diagnostic cohort that increased to 0.97 (95% CI, 0.92–1.0) with CA19-9 included. The 3-marker panel also had an AUC of 0.68 (95% CI, 0.58–0.77) for the prediagnostic cohort.Conclusions: We identified potential disease detection markers in plasma up to 4 years before death from PDA with superior performance to CA19-9. These markers might be especially useful in high-risk cohorts to diagnose early, resectable disease, particularly in patients that do not produce CA19-9. Clin Cancer Res; 21(7); 1764–71. ©2015 AACR.

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Supplementary Fig. 1. Longitudinal plots of mean (95% CI) percentage of energy as fat during follow-up and the extension period, stratified by quartiles of percentage energy as fat at baseline. Estimates of mean (95% CI) for percentage of energy from fat were based on 24-hour dietary recall.

Background: The Women's Health Initiative (WHI) low-fat (20% kcal) dietary modification (DM) trial (1993–2005) demonstrated a nonsignificant reduction in breast cancer, a nominally significant reduction in ovarian cancer, and no effect on other cancers (mean 8.3 years intervention). Consent to nonintervention follow-up was 83% (n = 37,858). This analysis was designed to assess postintervention cancer risk in women randomized to the low-fat diet (40%) versus usual diet comparison (60%).Methods: Randomized, controlled low-fat diet intervention for prevention of breast and colorectal cancers conducted in 48,835 postmenopausal U.S. women, ages 50 to 79 years at 40 U.S. sites. Outcomes included total invasive cancer, breast cancer, and colorectal cancer, and cancer-specific and overall mortality.Results: There were no intervention effects on invasive breast or colorectal cancer, other cancers, or cancer-specific or overall mortality during the postintervention period or the combined intervention and follow-up periods. For invasive breast cancer, the hazard ratios (HR) and 95% confidence interval (CI) were 0.92 (0.84–1.01) during intervention, 1.08 (0.94–1.24) during the postintervention period, and 0.97 (0.89–1.05) during cumulative follow-up. A reduced risk for estrogen receptor positive/progesterone receptor–negative tumors was demonstrated during follow-up. In women with higher baseline fat intake (quartile), point estimates of breast cancer risk were HR, 0.76 (95% CI, 0.62–0.92) during intervention versus HR, 1.11 (95% CI, 0.84–1.4) during postintervention follow-up (Pdiff = 0.03).Conclusions: Dietary fat intake increased postintervention in intervention women; no long-term reduction in cancer risk or mortality was shown in the WHI DM trial.Impact: Dietary advisement to reduce fat for cancer prevention after menopause generally was not supported by the WHI DM trial. Cancer Epidemiol Biomarkers Prev; 23(12); 2924–35. ©2014 AACR.

Table S2: Odds ratio and 95% confidence limits for cancers associated with variants with pleiotropic associations. Figure S1: Flowchart showing analysis steps. Figure S2. Manhattan plots by chromosome for individual cancer sites. Figure S3. Results for rs11571833. Figure S4: Conditional QQ-plots.

Supplementary Material. Section A: Excluding incomplete 24-hour urine samples based on PABA Section B: Calibrating the urinary sugars biomarker using a measurement error model that does not include age

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Supplementary Table 2. Effects of Randomization Assignment to Dietary Modification Intervention vs. Comparison on Clinical Outcomes Before and After Termination of the Intervention in the Women's Health Initiative Dietary Modification Trial

Background: Measurement error in self-reported sugars intake may be obscuring the association between sugars and cancer risk in nutritional epidemiologic studies.Methods: We used 24-hour urinary sucrose and fructose as a predictive biomarker for total sugars, to assess measurement error in self-reported sugars intake. The Nutrition and Physical Activity Assessment Study (NPAAS) is a biomarker study within the Women's Health Initiative (WHI) Observational Study that includes 450 postmenopausal women ages 60 to 91 years. Food Frequency Questionnaires (FFQ), four-day food records (4DFR), and three 24-hour dietary recalls (24HRs) were collected along with sugars and energy dietary biomarkers.Results: Using the biomarker, we found self-reported sugars to be substantially and roughly equally misreported across the FFQ, 4DFR, and 24HR. All instruments were associated with considerable intake- and person-specific bias. Three 24HRs would provide the least attenuated risk estimate for sugars (attenuation factor, AF = 0.57), followed by FFQ (AF = 0.48) and 4DFR (AF = 0.32), in studies of energy-adjusted sugars and disease risk. In calibration models, self-reports explained little variation in true intake (5%–6% for absolute sugars and 7%–18% for sugars density). Adding participants' characteristics somewhat improved the percentage variation explained (16%–18% for absolute sugars and 29%–40% for sugars density).Conclusions: None of the self-report instruments provided a good estimate of sugars intake, although overall 24HRs seemed to perform the best.Impact: Assuming the calibrated sugars biomarker is unbiased, this analysis suggests that measuring the biomarker in a subsample of the study population for calibration purposes may be necessary for obtaining unbiased risk estimates in cancer association studies. Cancer Epidemiol Biomarkers Prev; 23(12); 2874–83. ©2014 AACR.

PDF file - 66K, Total Energy Calibration Equation Coefficients from Linear Regression of Log DLW Energy on Log Self-Reported Energy and Personal Characteristics, Using Data from 450 NPAAS Women.

Identifying genetic variants with pleiotropic associations can uncover common pathways influencing multiple cancers. We took a two-stage approach to conduct genome-wide association studies for lung, ovary, breast, prostate, and colorectal cancer from the GAME-ON/GECCO Network (61,851 cases, 61,820 controls) to identify pleiotropic loci. Findings were replicated in independent association studies (55,789 cases, 330,490 controls). We identified a novel pleiotropic association at 1q22 involving breast and lung squamous cell carcinoma, with eQTL analysis showing an association with ADAM15/THBS3 gene expression in lung. We also identified a known breast cancer locus CASP8/ALS2CR12 associated with prostate cancer, a known cancer locus at CDKN2B-AS1 with different variants associated with lung adenocarcinoma and prostate cancer, and confirmed the associations of a breast BRCA2 locus with lung and serous ovarian cancer. This is the largest study to date examining pleiotropy across multiple cancer-associated loci, identifying common mechanisms of cancer development and progression. Cancer Res; 76(17); 5103–14. ©2016 AACR.

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Supplementary Tables S1-S3, Figures S1-S2. Supplementary Table S1: Candidate biomarkers for KPC preinvasive and invasive plasma drawn between 8-10 weeks and midway through disease progression, respectively. Supplementary Table S2: Candidate down-regulated plasma biomarkers from analysis of WHI pre-diagnostic plasma antibody microarray interrogation. Supplementary Table S3: A comparison of receiver operator characteristic (ROC) area under the curve values for the 3-marker panel of ESR1, ERBB2 and TNC in pre-diagnostic plasma to those for previously reported serum and plasma biomarkers discovered in diagnostic plasma samples. Supplementary Figure S1: Plasma M-values for TNC, ERBB2 and ESR1 do not show significant change as the time between blood draw and death decreases. Supplementary Figure S2: Dot plot of individual case and control diagnostic plasma composite values for (A) 3 marker panel (TNC, ERBB2 and ESR1) and (B) 3 marker panel plus CA19-9. Mean and standard deviations are indicated.

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PDF file - 68K, Characteristics of Breast Cancer Cases and Controls in Four-day Food Record (4DFR)-Based Case-Control Analyses, and Food Frequency Questionnaire (FFQ)-Based Cohort Analyses from the Women's Health Initiative.

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Variants selected for replication

Funding sources, acknowledgements, consortia involved in study and bioinformatics tools used