Association of clonal hematopoiesis and mosaic chromosomal alterations with solid malignancy incidence and mortality.

BACKGROUND: Understanding the impact of clonal hematopoiesis of indeterminate potential (CHIP) and mosaic chromosomal alterations (mCAs) on solid tumor risk and mortality can shed light on novel cancer pathways. METHODS: The authors analyzed whole genome sequencing data from the Trans-Omics for Precision Medicine Women's Health Initiative study (n = 10,866). They investigated the presence of CHIP and mCA and their association with the development and mortality of breast, lung, and colorectal cancers. RESULTS: CHIP was associated with higher risk of breast (hazard ratio [HR], 1.30; 95% confidence interval [CI], 1.03-1.64; p = .02) but not colorectal (p = .77) or lung cancer (p = .32). CHIP carriers who developed colorectal cancer also had a greater risk for advanced-stage (p = .01), but this was not seen in breast or lung cancer. CHIP was associated with increased colorectal cancer mortality both with (HR, 3.99; 95% CI, 2.41-6.62; p < .001) and without adjustment (HR, 2.50; 95% CI, 1.32-4.72; p = .004) for advanced-stage and a borderline higher breast cancer mortality (HR, 1.53; 95% CI, 0.98-2.41; p = .06). Conversely, mCA (cell fraction [CF] >3%) did not correlate with cancer risk. With higher CFs (mCA >5%), autosomal mCA was associated with increased breast cancer risk (HR, 1.39; 95% CI, 1.06-1.83; p = .01). There was no association of mCA (>3%) with breast, colorectal, or lung mortality except higher colon cancer mortality (HR, 2.19; 95% CI, 1.11-4.3; p = .02) with mCA >5%. CONCLUSIONS: CHIP and mCA (CF >5%) were associated with higher breast cancer risk and colorectal cancer mortality individually. These data could inform on novel pathways that impact cancer risk and lead to better risk stratification.

The Women's Health Initiative Randomized Trials and Clinical Practice: A Review.

Importance: Approximately 55 million people in the US and approximately 1.1 billion people worldwide are postmenopausal women. To inform clinical practice about the health effects of menopausal hormone therapy, calcium plus vitamin D supplementation, and a low-fat dietary pattern, the Women's Health Initiative (WHI) enrolled 161 808 postmenopausal US women (N = 68 132 in the clinical trials) aged 50 to 79 years at baseline from 1993 to 1998, and followed them up for up to 20 years. Observations: The WHI clinical trial results do not support hormone therapy with oral conjugated equine estrogens plus medroxyprogesterone acetate for postmenopausal women or conjugated equine estrogens alone for those with prior hysterectomy to prevent cardiovascular disease, dementia, or other chronic diseases. However, hormone therapy is effective for treating moderate to severe vasomotor and other menopausal symptoms. These benefits of hormone therapy in early menopause, combined with lower rates of adverse effects of hormone therapy in early compared with later menopause, support initiation of hormone therapy before age 60 years for women without contraindications to hormone therapy who have bothersome menopausal symptoms. The WHI results do not support routinely recommending calcium plus vitamin D supplementation for fracture prevention in all postmenopausal women. However, calcium and vitamin D are appropriate for women who do not meet national guidelines for recommended intakes of these nutrients through diet. A low-fat dietary pattern with increased fruit, vegetable, and grain consumption did not prevent the primary outcomes of breast or colorectal cancer but was associated with lower rates of the secondary outcome of breast cancer mortality during long-term follow-up. Conclusions and Relevance: For postmenopausal women, the WHI randomized clinical trials do not support menopausal hormone therapy to prevent cardiovascular disease or other chronic diseases. Menopausal hormone therapy is appropriate to treat bothersome vasomotor symptoms among women in early menopause, without contraindications, who are interested in taking hormone therapy. The WHI evidence does not support routine supplementation with calcium plus vitamin D for menopausal women to prevent fractures or a low-fat diet with increased fruits, vegetables, and grains to prevent breast or colorectal cancer. A potential role of a low-fat dietary pattern in reducing breast cancer mortality, a secondary outcome, warrants further study.

Two genome-wide interaction loci modify the association of nonsteroidal anti-inflammatory drugs with colorectal cancer.

Regular, long-term aspirin use may act synergistically with genetic variants, particularly those in mechanistically relevant pathways, to confer a protective effect on colorectal cancer (CRC) risk. We leveraged pooled data from 52 clinical trial, cohort, and case-control studies that included 30,806 CRC cases and 41,861 controls of European ancestry to conduct a genome-wide interaction scan between regular aspirin/nonsteroidal anti-inflammatory drug (NSAID) use and imputed genetic variants. After adjusting for multiple comparisons, we identified statistically significant interactions between regular aspirin/NSAID use and variants in 6q24.1 (top hit rs72833769), which has evidence of influencing expression of TBC1D7 (a subunit of the TSC1-TSC2 complex, a key regulator of MTOR activity), and variants in 5p13.1 (top hit rs350047), which is associated with expression of PTGER4 (codes a cell surface receptor directly involved in the mode of action of aspirin). Genetic variants with functional impact may modulate the chemopreventive effect of regular aspirin use, and our study identifies putative previously unidentified targets for additional mechanistic interrogation.

Long-Term Effect of Randomization to Calcium and Vitamin D Supplementation on Health in Older Women : Postintervention Follow-up of a Randomized Clinical Trial.

BACKGROUND: Although calcium and vitamin D (CaD) supplementation may affect chronic disease in older women, evidence of long-term effects on health outcomes is limited. OBJECTIVE: To evaluate long-term health outcomes among postmenopausal women in the Women's Health Initiative CaD trial. DESIGN: Post hoc analysis of long-term postintervention follow-up of the 7-year randomized intervention trial of CaD. (ClinicalTrials.gov: NCT00000611). SETTING: A multicenter (n = 40) trial across the United States. PARTICIPANTS: 36 282 postmenopausal women with no history of breast or colorectal cancer. INTERVENTION: Random 1:1 assignment to 1000 mg of calcium carbonate (400 mg of elemental calcium) with 400 IU of vitamin D3 daily or placebo. MEASUREMENTS: Incidence of colorectal, invasive breast, and total cancer; disease-specific and all-cause mortality; total cardiovascular disease (CVD); and hip fracture by randomization assignment (through December 2020). Analyses were stratified on personal supplement use. RESULTS: For women randomly assigned to CaD versus placebo, a 7% reduction in cancer mortality was observed after a median cumulative follow-up of 22.3 years (1817 vs. 1943 deaths; hazard ratio [HR], 0.93 [95% CI, 0.87 to 0.99]), along with a 6% increase in CVD mortality (2621 vs. 2420 deaths; HR, 1.06 [CI, 1.01 to 1.12]). There was no overall effect on other measures, including all-cause mortality (7834 vs. 7748 deaths; HR, 1.00 [CI, 0.97 to 1.03]). Estimates for cancer incidence varied widely when stratified by whether participants reported supplement use before randomization, whereas estimates on mortality did not vary, except for CVD mortality. LIMITATION: Hip fracture and CVD outcomes were available on only a subset of participants, and effects of calcium versus vitamin D versus joint supplementation could not be disentangled. CONCLUSION: Calcium and vitamin D supplements seemed to reduce cancer mortality and increase CVD mortality after more than 20 years of follow-up among postmenopausal women, with no effect on all-cause mortality. PRIMARY FUNDING SOURCE: National Heart, Lung, and Blood Institute of the National Institutes of Health.

Development and validation of age-specific predictive equations for total energy expenditure and physical activity levels for older adults.

BACKGROUND: Predicting energy requirements for older adults is compromised by the underpinning data being extrapolated from younger adults. OBJECTIVES: To generate and validate new total energy expenditure (TEE) predictive equations specifically for older adults using readily available measures (age, weight, height) and to generate and test new physical activity level (PAL) values derived from 1) reference method of indirect calorimetry and 2) predictive equations in adults aged ≥65 y. METHODS: TEE derived from "gold standard" methods from n = 1657 (n = 1019 females, age range 65-90 y), was used to generate PAL values. PAL ranged 1.28-2.05 for males and 1.26-2.06 for females. Physical activity (PA) coefficients were also estimated and categorized (inactive to very active) from population means. Nonlinear regression was used to develop prediction equations for estimating TEE. Double cross-validation in a randomized, sex-stratified, age-matched 50:50 split, and leave one out cross-validation were performed. Comparisons were made with existing equations. RESULTS: Equations predicting TEE using the Institute of Medicine method are as follows: For males, TEE = -5680.17 - 17.50 × age (years) + PA coefficient × (6.96 × weight [kilograms] + 44.21 × height [centimeters]) + 1.13 × resting metabolic rate (RMR) (kilojoule/day). For females, TEE = -5290.72 - 8.38 × age (years) + PA coefficient × (9.77 × weight [kilograms] + 41.51 × height [centimeters]) + 1.05 × RMR (kilojoule/day), where PA coefficient values range from 1 (inactive) to 1.51 (highly active) in males and 1 to 1.44 in females respectively. Predictive performance for TEE from anthropometric variables and population mean PA was moderate with limits of agreement approximately ±30%. This improved to ±20% if PA was adjusted for activity category (inactive, low active, active, and very active). Where RMR was included as a predictor variable, the performance improved further to ±10% with a median absolute prediction error of approximately 4%. CONCLUSIONS: These new TEE prediction equations require only simple anthropometric data and are accurate and reproducible at a group level while performing better than existing equations. Substantial individual variability in PAL in older adults is the major source of variation when applied at an individual level.

Diet and Chronic Disease Research in the Women's Health Initiative.

The Women's Health Initiative (WHI) has been a major contributor to diet and chronic disease research among postmenopausal US women over its 30+ year history (1993 to present). The WHI program included full-scale randomized trials of a low-fat dietary pattern high in fruits, vegetables, and grains, and of calcium and vitamin D supplementation, each with designated primary and secondary chronic disease outcomes. The history of these trials will be briefly reviewed here, along with principal findings that included evidence for breast cancer-related benefits for each of the 2 interventions. In recent years, WHI investigators have developed an active research program in nutritional biomarker development and in the application of these biomarkers in WHI cohorts, among various other nutritional epidemiology uses of WHI observational study resources. The intake biomarker work, which primarily relies on blood and urine metabolomics profiles, lends support to the low-fat dietary pattern trial results, and supports chronic disease benefits of higher carbohydrate diets more generally, especially through the fiber component of carbohydrate.

Metabolomics Biomarkers for Fatty Acid Intake and Biomarker-Calibrated Fatty Acid Associations with Chronic Disease Risk in Postmenopausal Women.

BACKGROUND: A substantial observational literature relating specific fatty acid classes to chronic disease risk may be limited by its reliance on self-reported dietary data. OBJECTIVES: We aimed to develop biomarkers for saturated (SFA), monounsaturated (MUFA), and polyunsaturated (PUFA) fatty acid densities, and to study their associations with cardiovascular disease (CVD), cancer, and type 2 diabetes (T2D) in Women's Health Initiative (WHI) cohorts. METHODS: Biomarker equations were based primarily on serum and urine metabolomics profiles from an embedded WHI human feeding study (n = 153). Calibration equations were based on biomarker values in a WHI nutritional biomarker study (n = 436). Calibrated intakes were assessed in relation to disease incidence in larger WHI cohorts (n = 81,894). Participants were postmenopausal women, aged 50-79 when enrolled at 40 United States Clinical Centers (1993-1998), with a follow-up period of ∼20 y. RESULTS: Biomarker equations meeting criteria were developed for SFA, MUFA, and PUFA densities. That for SFA density depended somewhat weakly on metabolite profiles. On the basis of our metabolomics platforms, biomarkers were insensitive to trans fatty acid intake. Calibration equations meeting criteria were developed for SFA and PUFA density, but not for MUFA density. With or without biomarker calibration, SFA density was associated positively with risk of CVD, cancer, and T2D, but with small hazard ratios, and CVD associations were not statistically significant after controlling for other dietary variables, including trans fatty acid and fiber intake. Following this same control, PUFA density was not significantly associated with CVD risk, but there were positive associations for some cancers and T2D, with or without biomarker calibration. CONCLUSIONS: Higher SFA and PUFA diets were associated with null or somewhat higher risk for clinical outcomes considered in this population of postmenopausal United States women. Further research is needed to develop even stronger biomarkers for these fatty acid densities and their major components. This study is registered with clinicaltrials.gov identifier: NCT00000611.

Metabolomics-Based Biomarker for Dietary Fat and Associations with Chronic Disease Risk in Postmenopausal Women.

BACKGROUND: The Women's Health Initiative (WHI) randomized, controlled Dietary Modification (DM) trial of a low-fat dietary pattern suggested intervention benefits related to breast cancer, coronary heart disease (CHD), and diabetes. Here, we use WHI observational data for further insight into the chronic disease implications of adopting this type of low-fat dietary pattern. OBJECTIVES: We aimed to use our earlier work on metabolomics-based biomarkers of carbohydrate and protein to develop a fat intake biomarker by subtraction, to use the resulting biomarker to develop calibration equations that adjusts self-reported fat intake for measurement error, and to study associations of biomarker-calibrated fat intake with chronic disease risk in WHI cohorts. Corresponding studies for specific fatty acids will follow separately. METHODS: Prospective disease association results are presented using WHI cohorts of postmenopausal women, aged 50-79 y when enrolled at 40 United States clinical centers. Biomarker equations were developed using an embedded human feeding study (n = 153). Calibration equations were developed using a WHI nutritional biomarker study (n = 436). Calibrated intakes were associated with cancer, cardiovascular diseases, and diabetes incidence in WHI cohorts (n = 81,954) over an approximate 20-y follow-up period. RESULTS: A biomarker for fat density was developed by subtracting protein, carbohydrate, and alcohol densities from one. A calibration equation was developed for fat density. Hazard ratios (95% confidence intervals) for 20% higher fat density were 1.16 (1.06, 1.27) for breast cancer, 1.13 (1.02, 1.26) for CHD, and 1.19 (1.13, 1.26) for diabetes, in substantial agreement with findings from the DM trial. With control for additional dietary variables, especially fiber, fat density was no longer associated with CHD, with hazard ratio (95% confidence interval) of 1.00 (0.88, 1.13), whereas that for breast cancer was 1.11 (1.00, 1.24). CONCLUSIONS: WHI observational data support prior DM trial findings of low-fat dietary pattern benefits in this population of postmenopausal United States women. TRIAL REGISTRATION NUMBER: This study is registered with clinicaltrials.gov identifier: NCT00000611.

A cross-sectional study of inflammatory markers as determinants of circulating kynurenines in the Lung Cancer Cohort Consortium.

Circulating concentrations of metabolites (collectively called kynurenines) in the kynurenine pathway of tryptophan metabolism increase during inflammation, particularly in response to interferon-gamma (IFN-γ). Neopterin and the kynurenine/tryptophan ratio (KTR) are IFN-γ induced inflammatory markers, and together with C-reactive protein (CRP) and kynurenines they are associated with various diseases, but comprehensive data on the strength of associations of inflammatory markers with circulating concentrations of kynurenines are lacking. We measured circulating concentrations of neopterin, CRP, tryptophan and seven kynurenines in 5314 controls from 20 cohorts in the Lung Cancer Cohort Consortium (LC3). The associations of neopterin, KTR and CRP with kynurenines were investigated using regression models. In mixed models, one standard deviation (SD) higher KTR was associated with a 0.46 SD higher quinolinic acid (QA), and 0.31 SD higher 3-hydroxykynurenine (HK). One SD higher neopterin was associated with 0.48, 0.44, 0.36 and 0.28 SD higher KTR, QA, kynurenine and HK, respectively. KTR and neopterin respectively explained 24.1% and 16.7% of the variation in QA, and 11.4% and 7.5% of HK. CRP was only weakly associated with kynurenines in regression models. In summary, QA was the metabolite that was most strongly associated with the inflammatory markers. In general, the inflammatory markers were most strongly related to metabolites located along the tryptophan-NAD axis, which may support suggestions of increased production of NAD from tryptophan during inflammation.

Enhancing Capacity for Food and Nutrient Intake Assessment in Population Sciences Research.

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 both for 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.

Associations of Biomarker-Calibrated Healthy Eating Index-2010 Scores with Chronic Disease Risk and Their Dependency on Energy Intake and Body Mass Index in Postmenopausal Women.

BACKGROUND: Prior studies examined associations between the Healthy Eating Index (HEI) and chronic disease risk based on self-reported diet without measurement error correction. OBJECTIVE: Our objective was to test associations between biomarker calibration of the food-frequency questionnaire (FFQ)-derived HEI-2010 with incident cardiovascular disease (CVD), cancer, and type 2 diabetes (T2D) among Women's Health Initiative (WHI) participants. METHODS: Data were derived from WHI postmenopausal women (n = 100,374) aged 50-79 y at enrollment (1993-1998) at 40 US clinical centers, linked to nutritional biomarker substudies and outcomes over subsequent decades of follow-up. Baseline or year 1 FFQ-derived HEI-2010 scores were calibrated with nutritional biomarkers and participant characteristics (e.g., BMI) for systematic measurement error correction. Calibrated data were then used in HR models examining associations with incidence of CVD (total, subtypes, mortality), cancer (total, subtypes, mortality), and T2D in WHI participants with approximately 2 decades of follow-up. Models were multivariable-adjusted with further adjustment for BMI and doubly labeled water (DLW)-calibrated energy. RESULTS: Multivariable-adjusted HRs modeled a 20% increment in HEI-2010 score in relation to outcomes. HRs were modest using uncalibrated HEI-2010 scores (HRs = 0.91-1.09). Using biomarker-calibrated HEI-2010, 20% increments in scores yielded multivariable-adjusted HRs (95% CIs) of 0.75 (0.60, 0.93) for coronary heart disease; 0.75 (0.61, 0.91) for myocardial infarction; 0.96 (0.92, 1.01) for stroke; 0.88 (0.75, 1.02) for CVD mortality; 0.81 (0.70, 0.94) for colorectal cancer; 0.81 (0.74, 0.88) for breast cancer; 0.79 (0.73, 0.87) for cancer mortality; and 0.45 (0.36-0.55) for T2D. Except for cancer mortality and T2D incidence, results became null when adjusted for DLW-calibrated energy intake and BMI. CONCLUSIONS: Biomarker calibration of FFQ-derived HEI-2010 was associated with lower CVD and cancer incidence and mortality and lower T2D incidence in postmenopausal women. Attenuation after adjustment with BMI and DLW-calibrated energy suggests that energy intake and/or obesity are strong drivers of diet-related chronic disease risk in postmenopausal women. The Women's Health Initiative is registered at clinicaltrials.gov at NCT00000611.

Constitutional BRCA1 Methylation and Risk of Incident Triple-Negative Breast Cancer and High-grade Serous Ovarian Cancer.

Importance: About 25% of all triple-negative breast cancers (TNBCs) and 10% to 20% of high-grade serous ovarian cancers (HGSOCs) harbor BRCA1 promoter methylation. While constitutional BRCA1 promoter methylation has been observed in normal tissues of some individuals, the potential role of normal tissue methylation as a risk factor for incident TNBC or HGSOC is unknown. Objective: To assess the potential association between white blood cell BRCA1 promoter methylation and subsequent risk of incident TNBC and HGSOC. Design, Setting, and Participants: This case-control study included women who were participating in the Women's Health Initiative study who had not received a diagnosis of either breast or ovarian cancer before study entrance. A total of 637 women developing incident TNBC and 511 women developing incident HGSOC were matched with cancer-free controls (1841 and 2982, respectively) in a nested case-control design. Cancers were confirmed after central medical record review. Blood samples, which were collected at entry, were analyzed for BRCA1 promoter methylation by massive parallel sequencing. The study was performed in the Mohn Cancer Research Laboratory (Bergen, Norway) between 2019 and 2022. Main Outcomes and Measures: Associations between BRCA1 methylation and incident TNBC and incident HGSOC were analyzed by Cox proportional hazards regression. Results: Of 2478 cases and controls in the TNBC group and 3493 cases and controls in the HGSOC group, respectively, 7 (0.3%) and 3 (0.1%) were American Indian or Alaska Native, 46 (1.9%) and 30 (0.9%) were Asian, 1 (0.04%) and 1 (0.03%) was Native Hawaiian or Pacific Islander, 326 (13.2%) and 125 (3.6%) were Black or African, 56 (2.3%) and 116 (3.3%) were Hispanic, 2046 (82.6%) and 3257 (93.2%) were White, and 35 (1.4%) and 35 (1.0%) were multiracial. Median (range) age at entry was 62 (50-79) years, with a median interval to diagnosis of 9 (TNBC) and 10 (HGSOC) years. Methylated BRCA1 alleles were present in 194 controls (5.5%). Methylation was associated with risk of incident TNBC (12.4% methylated; HR, 2.35; 95% CI, 1.70-3.23; P < .001) and incident HGSOC (9.4% methylated; HR, 1.93; 95% CI, 1.36-2.73; P < .001). Restricting analyses to individuals with more than 5 years between sampling and cancer diagnosis yielded similar results (TNBC: HR, 2.52; 95% CI, 1.75-3.63; P < .001; HGSOC: HR, 1.82; 95% CI, 1.22-2.72; P = .003). Across individuals, methylation was not haplotype-specific, arguing against an underlying cis-acting factor. Within individuals, BRCA1 methylation was observed on the same allele, indicating clonal expansion from a single methylation event. There was no association found between BRCA1 methylation and germline pathogenic variant status. Conclusions and Relevance: The results of this case-control suggest that constitutional normal tissue BRCA1 promoter methylation is significantly associated with risk of incident TNBC and HGSOC, with potential implications for prediction of these cancers. These findings warrant further research to determine if constitutional methylation of tumor suppressor genes are pancancer risk factors.

Criteria for Acceptable Dietary Intake Biomarkers.

Dietary intake biomarkers that can be written as actual intake, plus 'error' that is independent of actual intake and confounding factors can substitute for actual intake in disease association analyses. Also, such biomarkers can be used to develop calibration equations using self-reported diet and participant measures, and biomarker-calibrated intakes can be calculated in larger cohorts for use in disease association analyses. Criteria for biomarkers, and for biomarker-calibrated intakes, arise by working back from properties needed for valid disease association analyses. Accordingly, arguments for a potential biomarker are strengthened if error components are small relative to actual intakes, and important sources of reduced sensitivity or specificity are not apparent. Feeding study biomarker development can then involve regression of actual intake on putative biomarkers, with regression R2 values playing a role in biomarker evaluation. In comparison, 'predictive' biomarker status, as argued in this issue by Freedman and colleagues for 24-hour urinary sucrose plus fructose as biomarker for total sugars, involves regression of potential biomarker on actual intake and other variables, with parameter stability across populations and limited within-person variability as criteria. The choice of criteria for biomarkers and for biomarker-calibrated intakes, is discussed here, in the context of total sugars intake. See related article by Freedman et al., p. 1227.

Biomarker-Calibrated Red and Combined Red and Processed Meat Intakes with Chronic Disease Risk in a Cohort of Postmenopausal Women.

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.

Biomarkers for Components of Dietary Protein and Carbohydrate with Application to Chronic Disease Risk in Postmenopausal Women.

BACKGROUND: We recently developed protein and carbohydrate intake biomarkers using metabolomics profiles in serum and urine, and used them to correct self-reported dietary data for measurement error. Biomarker-calibrated carbohydrate density was inversely associated with chronic disease risk, whereas protein density associations were mixed. OBJECTIVES: To elucidate and extend this earlier work through biomarker development for protein and carbohydrate components, including animal protein and fiber. METHODS: Prospective disease association analyses were undertaken in Women's Health Initiative (WHI) cohorts of postmenopausal US women, aged 50-79 y when enrolled at 40 US clinical centers. Biomarkers were developed using an embedded human feeding study (n = 153). Calibration equations for protein and carbohydrate components were developed using a WHI nutritional biomarker study (n = 436). Calibrated intakes were associated with chronic disease incidence in WHI cohorts (n = 81,954) over a 20-y (median) follow-up period, using HR regression methods. RESULTS: Previously reported elevations in cardiovascular disease (CVD) with higher-protein diets tended to be explained by animal protein density. For example, for coronary heart disease a 20% increment in animal protein density had an HR of 1.20 (95% CI: 1.02, 1.42) relative to the HR for total protein density. In comparison, cancer and diabetes risk showed little association with animal protein density beyond that attributable to total protein density. Inverse carbohydrate density associations with total CVD were mostly attributable to fiber density, with a 20% increment HR factor of 0.89 (95% CI: 0.83, 0.94). Cancer risk showed little association with fiber density, whereas diabetes risk had a 20% increment HR of 0.93 (95% CI: 0.88, 0.98) relative to the HRs for total carbohydrate density. CONCLUSIONS: In a population of postmenopausal US women, CVD risk was associated with high-animal-protein and low-fiber diets, cancer risk was associated with low-carbohydrate diets, and diabetes risk was associated with low-fiber/low-carbohydrate diets.

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

Obesity and obesity-related metabolic disorders, such as diabetes and chronic inflammation, have been positively associated both with postmenopausal breast cancer and with resting energy expenditure (REE). However, there is limited epidemiologic evidence on the associations between REE and risk of postmenopausal breast cancer. We used multivariable Cox proportional hazards models to examine the association between predicted REE (calculated using the Ikeda, Livingston, and Mifflin equations) and risk of postmenopausal breast cancer overall and by subtypes, and by level of body fat) among 137,283 postmenopausal women in the Women's Health Initiative (WHI). All predicted REEs were positively associated with risk of invasive breast cancer [HRq5 vs. q1 = 1.69; 95% confidence interval (CI), 1.57-1.81; HR = 1.69; 95% CI, 1.57-1.82; and HR = 1.68; 95% CI, 1.56-1.80 for Ikeda, Livingston, and Mifflin, respectively]. These positive associations were observed irrespective of the hormone receptor subtype, grade, and stage of the tumors, but were most pronounced for estrogen receptor-positive/progesterone receptor-positive tumors. After additional adjustment for body mass index (BMI), the associations were mostly attenuated and remained statistically significant for most of the outcomes. We also observed an interaction between the predicted REEs and BMI, with the associations being somewhat stronger among normal weight and overweight women than among obese women (Pinteractions < 0.05). Our findings indicate that relatively high REE is associated with increased risk of invasive breast cancer among postmenopausal women (particularly for the obesity-related tumor subtypes), irrespective of the equation used. Further studies using more objective measures of REE are, however, needed to confirm our findings. PREVENTION RELEVANCE: This study showed that higher resting energy expenditure (REE) was associated with higher postmenopausal breast cancer risk. REE provides energy to support cancer-associated disorders such as obesity and inflammation. Thus, studies on its association with breast cancer can help to improve our understanding of the pathophysiology of breast cancer.

Four-Day Food Record Macronutrient Intake, With and Without Biomarker Calibration, and Chronic Disease Risk in Postmenopausal Women.

We recently evaluated associations of biomarker-calibrated protein intake, protein density, carbohydrate intake, and carbohydrate density with the incidence of cardiovascular disease, cancer, and diabetes among postmenopausal women in the Women's Health Initiative (1993-present, 40 US clinical centers). The biomarkers relied on serum and urine metabolomics profiles, and biomarker calibration used regression of biomarkers on food frequency questionnaires. Here we develop corresponding calibration equations using food records and dietary recalls. In addition, we use calibrated intakes based on food records in disease association estimation in a cohort subset (n = 29,294) having food records. In this analysis, more biomarker variation was explained by food records than by FFQs for absolute macronutrient intake, with 24-hour recalls being intermediate. However, the percentage of biomarker variation explained was similar for each assessment approach for macronutrient densities. Invasive breast cancer risk was related inversely to carbohydrate and protein densities using food records, in analyses that included (calibrated) total energy intake and body mass index. Corresponding analyses for absolute intakes did not differ from the null, nor did absolute or relative intakes associate significantly with colorectal cancer or coronary heart disease. These analyses do not suggest major advantages for food records or dietary recalls in comparison with less costly and logistically simpler food frequency questionnaires for these nutritional variables.

Mortality Associated with Healthy Eating Index Components and an Empirical-Scores Healthy Eating Index in a Cohort of Postmenopausal Women.

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 < 0.05) to total mortality, with favorable fruit, vegetable, whole grain, refined grain, and unsaturated fat associations and unfavorable sodium, saturated fat, and total energy associations. The E-HEI had cross-validated total mortality HRs (95% CIs) of 0.87 (0.82, 0.93), 0.80 (0.76, 0.86), 0.77 (0.72, 0.82), and 0.74 (0.69, 0.79) respectively, for quintiles 2 through 5 compared with quintile 1. These depart more strongly from the null than do HRs for HEI-2010 quintiles, primarily because of total energy. CONCLUSIONS: Mortality among US postmenopausal women depends strongly on diet, as evidenced by a new E-HEI that differs substantially from earlier dietary pattern score specifications.

Estimating 24-Hour Urinary Excretion of Sodium and Potassium Is More Reliable from 24-Hour Urine Than Spot Urine Sample in a Feeding Study of US Older Postmenopausal Women.

BACKGROUND: Assessing estimated sodium (Na) and potassium (K) intakes derived from 24-h urinary excretions compared with a spot urine sample, if comparable, could reduce participant burden in epidemiologic and clinical studies. OBJECTIVES: In a 2-week controlled-feeding study, Na and K excretions from a 24-h urine collection were compared with a first-void spot urine sample, applying established algorithms and enhanced models to estimate 24-h excretion. Actual and estimated 24-h excretions were evaluated relative to mean daily Na and K intakes in the feeding study. METHODS: A total of 153 older postmenopausal women ages 75.4 ± 3.5 y participated in a 2-wk controlled-feeding study with a 4-d repeating menu cycle based on their usual intake (ClinicalTrials.gov Identifier: NCT00000611). Of the 150 participants who provided both a first-void spot urine sample and a 24-h urine collection on the penultimate study day, statistical methods included Pearson correlations for Na and K between intake, 24-h collections, and the 24-h estimated excretions using 4 established algorithms: enhanced biomarker models by regressing ln-transformed intakes on ln-transformed 24-h excretions or ln-transformed 24-h estimated excretions plus participant characteristics and sensitivity analyses for factors potentially influencing Na or K excretion (e.g., possible kidney disease estimated glomerular filtration rate <60 mL/min/1.73 m2 ). RESULTS: Pearson correlation coefficients between Na and K intakes and actual 24-h excretions were 0.57 and 0.38-0.44 for estimated 24-h excretions, depending on electrolyte and algorithm used. Enhanced biomarker model cross-validated R 2 (CVR2) for 24-h excretions were 38.5% (Na), 40.2% (K), and 42.0% (Na/K). After excluding participants with possible kidney disease, the CVR2 values were 43.2% (Na), 40.2% (K), and 38.1% (Na/K). CONCLUSIONS: Twenty-four-hour urine excretion measurement performs better than estimated 24-h excretion from a spot urine as a biomarker for Na and K intake among a sample of primarily White postmenopausal women.

Epidemiology of 40 blood biomarkers of one-carbon metabolism, vitamin status, inflammation, and renal and endothelial function among cancer-free older adults.

Imbalances of blood biomarkers are associated with disease, and biomarkers may also vary non-pathologically across population groups. We described variation in concentrations of biomarkers of one-carbon metabolism, vitamin status, inflammation including tryptophan metabolism, and endothelial and renal function among cancer-free older adults. We analyzed 5167 cancer-free controls aged 40-80 years from 20 cohorts in the Lung Cancer Cohort Consortium (LC3). Centralized biochemical analyses of 40 biomarkers in plasma or serum were performed. We fit multivariable linear mixed effects models to quantify variation in standardized biomarker log-concentrations across four factors: age, sex, smoking status, and body mass index (BMI). Differences in most biomarkers across most factors were small, with 93% (186/200) of analyses showing an estimated difference lower than 0.25 standard-deviations, although most were statistically significant due to large sample size. The largest difference was for creatinine by sex, which was - 0.91 standard-deviations lower in women than men (95%CI - 0.98; - 0.84). The largest difference by age was for total cysteine (0.40 standard-deviation increase per 10-year increase, 95%CI 0.36; 0.43), and by BMI was for C-reactive protein (0.38 standard-deviation increase per 5-kg/m2 increase, 95%CI 0.34; 0.41). For 31 of 40 markers, the mean difference between current and never smokers was larger than between former and never smokers. A statistically significant (p < 0.05) association with time since smoking cessation was observed for 8 markers, including C-reactive protein, kynurenine, choline, and total homocysteine. We conclude that most blood biomarkers show small variations across demographic characteristics. Patterns by smoking status point to normalization of multiple physiological processes after smoking cessation.