Women's Health Initiative Cohort Research Articles

Associations between dietary and supplemental vitamin A intake and melanoma and non‐melanoma skin cancer

AbstractBackgroundCutaneous melanoma (CM) and non‐melanoma skin cancer (NMSC) are rising in postmenopausal women. Although high doses of oral vitamin A reduce NMSC risk in high‐risk patients, the role of vitamin A in preventing skin cancer in this group remains unexplored.ObjectivesTo determine the association between total (dietary and supplemental) vitamin A and risk of CM and NMSC in postmenopausal women.MethodsThis retrospective cohort study included 52 877 White women from the Women's Health Initiative cohort, spanning from 1993 to 2019. Exposures were intake of total vitamin A, retinol and provitamin A carotenoids. Cox proportional hazard models estimated hazard ratios for overall CM incidence, whereas logistic regression determined odds ratios (ORs) for melanoma subtypes and NMSC.Results1154 cases of CM and 9085 cases of NMSC were identified over an average follow‐up period of 17.8 years (SD 6.7). No associations were identified between total vitamin A intake and melanoma risk. Higher dietary vitamin A intake was associated with higher risk of NMSC (OR of 3rd vs. 1st tertile of dietary intake = 1.12, 95% confidence interval [CI] [1.06, 1.18]), as was dietary beta‐cryptoxanthin, a provitamin A carotenoid (OR of 3rd vs. 1st tertile of dietary intake = 1.22, 95% CI [1.15, 1.29]); these results were consistent across both age‐ and fully adjusted regression models.ConclusionsTotal vitamin A intake was not associated with lower risk of CM or NMSC. Dietary vitamin A and beta‐cryptoxanthin intake were associated with a slightly higher risk of NMSC in postmenopausal women.

Intake Biomarkers for Nutrition and Health: Review and Discussion of Methodology Issues.

Metabolomics profiles from blood, urine, or other body fluids have the potential to assess intakes of foods and nutrients objectively, thereby strengthening nutritional epidemiology research. Metabolomics platforms may include targeted components that estimate the relative concentrations for individual metabolites in a predetermined set, or global components, typically involving mass spectrometry, that estimate relative concentrations more broadly. While a specific metabolite concentration usually correlates with the intake of a single food or food group, multiple metabolites may be correlated with the intake of certain foods or with specific nutrient intakes, each of which may be expressed in absolute terms or relative to total energy intake. Here, I briefly review the progress over the past 20 years on the development and application intake biomarkers for foods/food groups, nutrients, and dietary patterns, primarily by drawing from several recent reviews. In doing so, I emphasize the criteria and study designs for candidate biomarker identification, biomarker validation, and intake biomarker application. The use of intake biomarkers for diet and chronic disease association studies is still infrequent in nutritional epidemiology research. My comments here will derive primarily from our research group's recent contributions to the Women's Health Initiative cohorts. I will complete the contribution by describing some opportunities to build on the collective 20 years of effort, including opportunities related to the metabolomics profiling of blood and urine specimens from human feeding studies that approximate habitual diets.

Competing risks and multivariate outcomes in epidemiological and clinical trial research.

Data analysis methods for the study of treatments or exposures in relation to a clinical outcome in the presence of competing risks have a long history, often with inference targets that are hypothetical, thereby requiring strong assumptions for identifiability with available data. Here data analysis methods are considered that are based on single and higher dimensional marginal hazard rates, quantities that are identifiable under standard independent censoring assumptions. These lead naturally to joint survival function estimators for outcomes of interest, including competing risk outcomes, and provide the basis for addressing a variety of data analysis questions. These methods will be illustrated using simulations and Women's Health Initiative cohort and clinical trial data sets, and additional research needs will be described.

The American Society for Bone and Mineral Research Task Force on clinical algorithms for fracture risk report.

Using race and ethnicity in clinical algorithms potentially contributes to health inequities. The American Society for Bone and Mineral Research (ASBMR) Professional Practice Committee convened the ASBMR Task Force on Clinical Algorithms for Fracture Risk to determine the impact of race and ethnicity adjustment in the US Fracture Risk Assessment Tool (US-FRAX). The Task Force engaged the University of Minnesota Evidence-based Practice Core to conduct a systematic review investigating the performance of US-FRAX for predicting incident fractures over 10years in Asian, Black, Hispanic, and White individuals. Six studies from the Women's Health Initiative (WHI) and Study of Osteoporotic Fractures (SOF) were eligible; cohorts only included women and were predominantly White (WHI > 80% and SOF > 99%), data were not consistently stratified by race and ethnicity, and when stratified there were far fewer fractures in Black and Hispanic women vs White women rendering area under the curve (AUC) estimates less stable. In the younger WHI cohort (n = 64 739), US-FRAX without bone mineral density (BMD) had limited discrimination for major osteoporotic fracture (MOF) (AUC 0.53 (Black), 0.57 (Hispanic), and 0.57 (White)); somewhat better discrimination for hip fracture in White women only (AUC 0.54 (Black), 0.53 (Hispanic), and 0.66 (White)). In a subset of the older WHI cohort (n = 23 918), US-FRAX without BMD overestimated MOF. The Task Force concluded that there is little justification for estimating fracture risk while incorporating race and ethnicity adjustments and recommends that fracture prediction models not include race or ethnicity adjustment but instead be population-based and reflective of US demographics, and inclusive of key clinical, behavioral, and social determinants (where applicable). Research cohorts should be representative vis-à-vis race, ethnicity, gender, and age. There should be standardized collection of race and ethnicity; collection of social determinants of health to investigate impact on fracture risk; and measurement of fracture rates and BMD in cohorts inclusive of those historically underrepresented in osteoporosis research.

New-Onset Diabetes after an Obesity-Related Cancer Diagnosis and Survival Outcomes in the Women's Health Initiative.

Individuals diagnosed with an obesity-related cancer (ORC survivors) are at an elevated risk of incident diabetes compared with cancer-free individuals, but whether this confers survival disadvantage is unknown. We assessed the rate of incident diabetes in ORC survivors and evaluated the association of incident diabetes with all-cause and cancer-specific mortality among females with ORC in the Women's Health Initiative cohort (N = 14,651). Cox proportional hazards regression models stratified by exposure-risk periods (0-1, >1-3, >3-5, >5-7, and >7-10 years) from ORC diagnosis and time-varying exposure (diabetes) analyses were performed. Among the ORC survivors, a total of 1.3% developed diabetes within ≤1 year of follow-up and 2.5%, 2.3%, 2.3%, and 3.6% at 1-3, 3-5, 5-7, and 7-10 years of follow-up, respectively, after an ORC diagnosis. The median survival for those diagnosed with diabetes within 1-year of cancer diagnosis and those with no diabetes diagnosis in that time frame was 8.8 [95% confidence interval (CI), 7.0-14.5) years and 16.6 (95% CI, 16.1-17.0) years, respectively. New-onset compared with no diabetes as a time-varying exposure was associated with higher risk of all-cause (HR, 1.27; 95% CI, 1.16-1.40) and cancer-specific (HR, 1.17; 95% CI, 0.99-1.38) mortality. When stratified by exposure-risk periods, incident diabetes in ≤1 year of follow-up was associated with higher all-cause (HR, 1.76; 95% CI, 1.40-2.20) and cancer-specific (HR0-1, 1.82; 95% CI, 1.28-2.57) mortality, compared with no diabetes diagnosis. Incident diabetes was associated with worse cancer-specific and all-cause survival, particularly in the year after cancer diagnosis. These findings draw attention to the importance of diabetes prevention efforts among cancer survivors to improve survival outcomes.

Regression calibration utilizing biomarkers developed from high-dimensional metabolites.

Addressing systematic measurement errors in self-reported data is a critical challenge in association studies of dietary intake and chronic disease risk. The regression calibration method has been utilized for error correction when an objectively measured biomarker is available; however, biomarkers for only a few dietary components have been developed. This paper proposes to use high-dimensional objective measurements to construct biomarkers for many more dietary components and to estimate the diet disease associations. It also discusses the challenges in variance estimation in high-dimensional regression methods and presents a variety of techniques to address this issue, including cross-validation, degrees-of-freedom corrected estimators, and refitted cross-validation (RCV). Extensive simulation is performed to study the finite sample performance of the proposed estimators. The proposed method is applied to the Women's Health Initiative cohort data to examine the associations between the sodium/potassium intake ratio and the total cardiovascular disease.

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

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. 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). 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. 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. 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.

Long-term air pollution and risk of amyotrophic lateral sclerosis mortality in the Women's Health Initiative cohort

BackgroundAmyotrophic lateral sclerosis (ALS) is a neurodegenerative disorder with no cure. Although the etiology of sporadic ALS is largely unknown, environmental exposures may affect ALS risk. ObjectiveWe investigated relationships between exposure to long-term ambient particulate matter (PM) and gaseous air pollution (AP) and ALS mortality. MethodsWithin the Women's Health Initiative (WHI) cohort of 161,808 postmenopausal women aged 50–79 years at baseline (1993–1998), we performed a nested case-control study of 256 ALS deaths and 2486 matched controls with emphasis on PM constituents (PM2.5, PM10, and coarse PM [PM10-2.5]) and gaseous pollutants (NOx, NO2, SO2, and ozone). Time-varying AP exposures estimates were averaged 5, 7.5, and 10 years prior to ALS death using both a GIS-based spatiotemporal generalized additive mixed model and ordinary kriging (empirical and multiple imputation, MI). Conditional logistic regression was used to estimate the relative risk of ALS death. ResultsIn general, PM2.5 and PM10-related risks were not significantly elevated using either method. However, for PM10-2.5, odds ratios (ORs) were >1.0 for both methods at all time periods using MI and empirical data for PM10-2.5 (coarse) except for 5 and 7.5 years using the kriging method with covariate adjustment. ConclusionThis investigation adds to the body of information on long-term ambient AP exposure and ALS mortality. Specifically, the 2019 US Environmental Protection Agency (EPA) Integrated Science Assessment summarized the neurotoxic effects of PM2.5, PM10, and PM10-2.5. The conclusion was that evidence of an effect of coarse PM is suggestive but the data is presently not sufficient to infer a causal relationship. Further research on AP and ALS is warranted. As time from symptom onset to death in ALS is ∼2–4 years, earlier AP measures may also be of interest to ALS development. This is the first study of ALS and AP in postmenopausal women controlling for individual-level confounders.

Using Controlled Feeding Study for Biomarker Development in Regression Calibration for Disease Association Estimation.

Correction for systematic measurement error in self-reported data is an important challenge in association studies of dietary intake and chronic disease risk. The regression calibration method has been used for this purpose when an objectively measured biomarker is available. However, a big limitation of the regression calibration method is that biomarkers have only been developed for a few dietary components. We propose new methods to use controlled feeding studies to develop valid biomarkers for many more dietary components and to estimate the diet disease associations. Asymptotic distribution theory for the proposed estimators is derived. Extensive simulation is performed to study the finite sample performance of the proposed estimators. We applied our method to examine the associations between the sodium/potassium intake ratio and cardiovascular disease incidence using the Women's Health Initiative cohort data. We discovered positive associations between sodium/potassium ratio and the risks of coronary heart disease, nonfatal myocardial infarction, coronary death, ischemic stroke, and total cardiovascular disease.

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

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. To elucidate and extend this earlier work through biomarker development for protein and carbohydrate components, including animal protein and fiber. 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. 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. 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.

Association of infertility with atherosclerotic cardiovascular disease among postmenopausal participants in the Women’s Health Initiative

To investigate the association of infertility with atherosclerotic cardiovascular disease (ASCVD) among postmenopausal participants in the Women's Health Initiative (WHI). We hypothesized that nulliparity and pregnancy loss may reveal more extreme phenotypes of infertility, enabling further understanding of the association of infertility with ASCVD. Prospective cohort study. Forty clinical centers in the United States. A total of 158,787 postmenopausal participants in the Women's Health Initiative cohort. Infertility, parity, and pregnancy loss. The primary outcome was risk of ASCVD among women with and without a history of infertility, stratified by history of live birth and pregnancy loss. Cox proportional-hazards models were adjusted for demographics and risk factors for ASCVD. Among 158,787 women, 25,933 (16.3%) reported a history of infertility; 20,427 (80%) had at least 1 live birth; and 9,062 (35%) had at least 1 pregnancy loss. There was a moderate overall association between infertility and ASCVD (adjusted hazard ratio, 1.02; 95% confidence interval [CI], 0.99-1.06) over 19 years of follow-up. Among nulliparous women, infertility was associated with a 13% higher risk of ASCVD (95% CI, 1.04-1.23). Among nulliparous women who had a pregnancy loss, infertility was associated with a 36% higher risk of ASCVD (95% CI, 1.09-1.71). Women with a history of infertility overall had a moderately higher risk of ASCVD compared with women without a history of infertility. Atherosclerotic cardiovascular disease risk was much higher among nulliparous infertile women and among nulliparous infertile women who also had a pregnancy loss, suggesting that in these more extreme phenotypes, infertility may be associated with ASCVD risk.

Biomarker-Based Methods and Study Designs to Calibrate Dietary Intake for Assessing Diet–Disease Associations

BackgroundDietary biomarkers measured in biospecimens can play an important role in correcting for random and systematic measurement error in self-reported nutrient intake when assessing diet–disease associations. To date, high-quality biomarkers for calibrating self-reported dietary intake have only been developed for a few nutrients. ObjectivesTo investigate new study designs and regression calibration approaches for calibrating self-reported nutrient intake for use in disease association analyses. MethodsWe studied 3 regression calibration approaches: 1) an existing approach built on a calibration cohort assuming the existence of an objective biomarker (i.e., biomarker with random independent measurement error), 2) a proposed approach using a biomarker development cohort, and 3) a proposed 2-stage approach using both cohorts. We conducted simulation studies to compare the performance of different study designs/methods for estimating diet–disease associations and applied suitable methods to examine the association of sodium and potassium intake with cardiovascular disease (CVD) risk in Women's Health Initiative cohorts. ResultsSimulation studies showed that the first approach can lead to biased association estimation when the objective biomarker assumption is violated; the second and third proposed approaches obviate the need for such an objective biomarker. Precision for estimating the association depends critically on sample size of the biomarker development cohort and the strength of the self-reported nutrient intake. Analyses based on the second and third approaches support previously reported significant findings using the first approach about associations of the ratio of sodium to potassium intake with CVD risk while providing efficiency gain for some outcomes. ConclusionsSelf-reported dietary intake needs to be calibrated for measurement error correction in diet–disease association analyses. When there are no existing objective biomarkers that can be used for calibration purpose, controlled feeding studies can be used to develop new biomarkers for use in calibration or can be used to calibrate self-reported dietary intake directly.

The association of walking pace and incident heart failure and subtypes among postmenopausal women.

To investigate the association between walking pace and the risk of heart failure (HF) and HF sub-types. We examined associations of self-reported walking pace with risk of incident HF and HF subtypes of preserved (HFpEF) and reduced (HFrEF) ejection fractions, among 25,183 postmenopausal women, ages 50-79 years. At enrollment into the Women's Health Initiative cohort in 1993-1998, this subset of women was free of HF, cancer, or the inability to walk one block, with self-reported information on walking pace and walking duration. Multivariable Cox regression was used to examine associations of walking pace (casual <2 mph [referent], average 2-3 mph, and fast >3 mph) with incident HF. We also examined the joint association of walking pace and duration with incident HF. There were 1455 incident adjudicated acute decompensated HF hospitalization cases during a median of 16.9 years of follow-up. There was a strong inverse association between walking pace and overall risk of HF (HR=0.73, 95% CI [0.65, 0.83] for average vs. casual walking; HR=0.66, 95%CI [0.56, 0.78] for fast vs. casual walking). There were similar associations of walking pace with HFpEF (HR=0.73, 95%CI [0.62, 0.86] average vs. casual; HR=0.63, 95%CI [0.50, 0.80] for fast vs. casual) and with HFrEF (HR=0.72, 95%CI [0.57, 0.91] for average vs. casual; HR=0.74, 95%CI [0.54, 0.99] for fast vs. casual). The risk of HF associated with fast walking with less than 1h/week walking duration was comparable with the risk of HF among casual and average walkers with more than 2h/week walking duration. Walking pace was inversely associated with risks of overall HF, HFpEF, and HFrEF in postmenopausal women. Whether interventions to increase the walking pace in older adults will reduce HF risk and whether fast pace will compensate for the short duration of walking warrants further study.

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

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.

Long-Term Air Pollution and Risk of Amyotrophic Lateral Sclerosis Mortality in the Women's Health Initiative Cohort

Long-Term Air Pollution and Risk of Amyotrophic Lateral Sclerosis Mortality in the Women's Health Initiative Cohort

Metabolomic Analysis of Coronary Heart Disease in an African American Cohort From the Jackson Heart Study

African American individuals have disproportionate rates of coronary heart disease (CHD) but lower levels of coronary artery calcium (CAC), a marker of subclinical CHD, than non-Hispanic White individuals. African American individuals may have distinct metabolite profiles associated with incident CHD risk compared with non-Hispanic White individuals, and examination of these differences could highlight important processes that differ between them. To identify novel biomarkers of incident CHD and CAC among African American individuals and to replicate incident CHD findings in a multiethnic cohort. This analysis targeted plasma metabolomic profiling of 2346 participants in the Jackson Heart Study (JHS), a prospective population-based cohort study that included 5306 African American participants who were examined at baseline (2000-2004) and 2 follow-up visits. Replication of CHD-associated metabolites was sought among 1588 multiethnic participants from the Women's Health Initiative (WHI), a prospective population-based multiethnic cohort study of 161 808 postmenopausal women who were examined at baseline (1991-1995) and ongoing follow-up visits. Regression analyses were performed for each metabolite to examine the associations with incident CHD and CAC scores. Data were collected from the WHI between 1994 and 2009 and from the JHS between 2000 and 2015. All data were analyzed from November 2020 to August 2021. Plasma metabolites. Incident CHD was defined as definite or probable myocardial infarction or definite fatal CHD in both the JHS and WHI cohorts. In the JHS cohort, silent myocardial infarction between examinations (as determined by electrocardiography) and coronary revascularization were included in the incident CHD analysis. Coronary artery calcium was measured using a 16-channel computed tomographic system and reported as an Agatston score. Among 2346 African American individuals in the JHS cohort, the mean (SD) age was 56 (13) years, and 1468 individuals (62.6%) were female. Among 1588 postmenopausal women in the WHI cohort, the mean (SD) age was 67 (7) years; 217 individuals (13.7%) self-identified as African American, 1219 (76.8%) as non-Hispanic White, and 152 (9.6%) as other races or ethnicities. In the fully adjusted model including 1876 individuals, 46 of 303 targeted metabolites were associated with incident CHD (false discovery rate q <0.100). Data for 32 of the 46 metabolites were available in the WHI cohort, and 13 incident CHD-associated metabolites from the JHS cohort were replicated in the WHI cohort. A total of 1439 participants from the JHS cohort with available CAC scores received metabolomic profiling. Nine metabolites were associated with CAC scores. Minimal overlap was found between the results from the incident CHD and CAC analyses, with only 3 metabolites shared between the 2 analyses. This cohort study identified metabolites that were associated with incident CHD among African American individuals, including 13 incident CHD-associated metabolites that were replicated in a multiethnic population and 9 novel metabolites that included N-acylamides, leucine, and lipid species. These findings may help to elucidate common and distinct metabolic processes that may be associated with CHD among individuals with different self-identified race.

Long-Term Exposures to Air Pollution and the Risk of Atrial Fibrillation in the Women's Health Initiative Cohort.

Background:Atrial fibrillation (AF) is associated with substantial morbidity and mortality. Short-term exposures to air pollution have been associated with AF triggering; less is known regarding associations between long-term air pollution exposures and AF incidence.Objectives:Our objective was to assess the association between long-term exposures to air pollution and distance to road on incidence of AF in a cohort of U.S. women.Methods:We assessed the association of high resolution spatiotemporal model predictions of long-term exposures to particulate matter ( and ), sulfur dioxide (), nitrogen dioxide (), and distance to major roads with incidence of AF diagnosis, identified through Medicare linkage, among 83,117 women in the prospective Women’s Health Initiative cohort, followed from enrollment in Medicare through December 2012, incidence of AF, or death. Using time-varying Cox proportional hazards models adjusted for age, race/ethnicity, study component, body mass index, physical activity, menopausal hormone therapy, smoking, diet quality, alcohol consumption, educational attainment, and neighborhood socioeconomic status, we estimated the relative risk of incident AF in association with each pollutant.Results:A total of 16,348 incident AF cases were observed over 660,236 person-years of follow-up. Most exposure–response associations were nonlinear. was associated with risk of AF in multivariable adjusted models [; 95% confidence interval (CI): 1.13, 1.24, comparing the top to bottom quartile, ]. Women living closer to roadways were at higher risk of AF (e.g., ; 95% CI: 1.01, 1.13 for living within of A3 roads, compared with , ), but we did not observe adverse associations with exposures to , , or . There were adverse associations with (top quartile ; 95% CI: 1.05, 1.16, ) and (top quartile ; 95% CI: 1.03, 1.14, ) in sensitivity models adjusting for census region.Discussion:In this study of postmenopausal women, and distance to road were consistently associated with higher risk of AF. https://doi.org/10.1289/EHP7683

Acute Myeloid Leukemia (AML) Patients Demonstrate Increased Prevalence of AML-Defining Mutations in Peripheral Blood Years Prior to the Development of Overt Leukemia: A Case-Control Study

Background: It is known that AML is preceded by the serial acquisition of somatic mutations but the pattern is unknown due to the lack of availability of samples prior to disease development. Clonal hematopoiesis of indeterminate potential has been associated with increased risk of hematologic malignancies but the specific contribution of subclonal genetic lesions to AML risk is unknown.We analyzed 725 samples from the Women's Health Initiative (WHI) cohort, which followed participants aged 50-79 from 1993-2010 for an average of 10.8 years. Cases and controls were selected as follows:Cases (n=212) included subjects with centrally adjudicated AML diagnosis. Peripheral blood samples were available from baseline and follow up (year 1 and 3) all prior to diagnosis of overt AML (average time to AML was 9.06 years).Controls (n=212) (healthy non-AML), were matched by age, timing of serial sample collection and history of cancer at WHI baseline and follow-up. Matching was done in a time forward manner to ensure similar follow up times.Methods: Ultra-deep targeted exome sequencing was performed using a 200 gene capture panel of recurrently mutated genes in hematologic malignancies. Variants present at 2.5% VAF minimum were selected and categorized as pathogenic significance vs. variant of uncertain significance (VUS) following rigorous quality control and filtration of SNPs. Analysis was focused on 67 genes recurrently mutated in MDS/AML in addition to categorical analysis of mutations (epigenetic regulators, activated signaling, spliceosome). Chromosomal rearrangements were assessed using information from split and paired end reads mapped to intronic regions of known breakpoints captured by the gene panel.Baseline characteristics of cases and controls were compared by using t-test or Wilcoxon rank-sum test for continuous variables, and the chi-square test or Fisher's exact test for categorical variables. Fisher's exact test was used to calculate the mutation status among cases and controls and to calculate the association of baseline mutation with AML diagnosis. Time to development of AML in cases was assessed by using regression analyses with the mutation status as a covariate. All p-values are two-sided with statistical significance evaluated at the 0.05 alpha levels.Results: The median age of cases and controls were 65.5 and 65 years respectively with average time to AML being 9.06 years. Myeloid specific mutations were detected in 35.4 % of controls and 59.04% of cases. The most commonly found mutations and their frequencies among cases and controls respectively were DNMT3A (22.8% and 10%), TET2 (19.5% and 4.2%) and ASXL1/ASXL2 (8% and 6.8%). TP53 (6.6%) and RUNX1 (2%) mutations were only seen in participants who eventually developed AML and were absent in controls. Subclonal mutations in DNMT3A, TET2, TP53, and SF3B1 revealed a general pattern of mutual exclusivity. Among cases, a >30-fold enrichment in pathogenic mutations was observed relative to controls (14.76 % vs.0.47%). One case demonstrated detectable MLL-ELL rearrangement 6 years prior to diagnosis of AML. There was no association of WBC, platelets or hemoglobin count with the presence of any mutation at the same time.There was an increased prevalence of myeloid specific mutation among cases compared to controls (OR 2.87, C.I. 1.90-4.37, p value <0.001). The presence of a pathogenic myeloid mutation was also significantly different among cases and controls (p value <.0001). In this matched case control analysis, the presence of a myeloid specific mutation at baseline was associated with the development of AML (OR 2.9, p value <0.001). Among cases, time to development of AML in participants with and without a prior myeloid specific mutation was 8.2 years and 9.6 years respectively (p value >0.05). Strikingly, all participants with a RUNX1 and TP53 and majority with the targetable IDH2 R140Q mutation (10/11) eventually developed AML many years later.Conclusions: The likelihood of having a myeloid -specific mutation at baseline, prior to the development of AML, was significantly higher in cases compared to controls from this WHI cohort. IDH2, TP53 and RUNX1 mutations were almost always predictive of development of AML. These findings suggest that subclonal stepwise acquisition of mutations may occur years prior to disease onset and that deep molecular monitoring using NGS may enable early intervention in selected patients. DisclosuresMencia-Trinchant:Cellectis: Research Funding. Lee:Clinipace: Consultancy; Baxalta: Consultancy; Amgen: Consultancy; Alexion Pharmaceuticals: Consultancy. Ritchie:Bristol-Myers Squibb: Other: Research funding to my institution; NS Pharma: Other: Research funding to my institution; Novartis: Consultancy, Other: Research funding to my institution, and travel, Speakers Bureau; Pfizer: Consultancy, Other: Research funding to my institution; Celgene: Consultancy, Other: Travel, Speakers Bureau; Incyte: Consultancy, Speakers Bureau; Astellas Pharma: Other: Research funding to my institution. Guzman:Cellectis: Research Funding. Roboz:AbbVie, Agios, Amgen, Amphivena, Array Biopharma Inc., Astex, AstraZeneca, Celator, Celgene, Clovis Oncology, CTI BioPharma, Genoptix, Immune Pharmaceuticals, Janssen Pharmaceuticals, Juno, MedImmune, MEI Pharma, Novartis, Onconova, Pfizer, Roche Pharmace: Consultancy; Cellectis: Research Funding. Hassane:Cellectis: Research Funding.

Non-coding variants in MYH11, FZD3, and SORCS3 are associated with dementia in women.

Recent studies suggest that both sex-specific genetic risk factors and those shared between dementia and stroke are involved in dementia pathogenesis. We performed both single-variant and gene-based genome-wide association studies of>11,000 whole genome sequences from the Women's Health Initiative cohort to discover loci associated with dementia, with adjustment for age, ethnicity, stroke, and venous thromboembolism status. Evidence for prior evidence of association and differential gene expression in dementia-related tissues and samples was gathered for each locus. Our multiethnic studies identified significant associations between variants within APOE, MYH11, FZD3, SORCS3, and GOLGA8B and risk of dementia. Ten genes implicated by these loci, including MYH11, FZD3, SORCS3, and GOLGA8B, were differentially expressed in the context of Alzheimer's disease. Our association of MYH11, FZD3, SORCS3, and GOLGA8B with dementia is supported by independent functional studies in human subjects, model systems, and associations with shared risk factors for stroke and dementia.

Can dietary self-reports usefully complement blood concentrations for estimation of micronutrient intake and chronic disease associations?

We recently presented associations between serum-based biomarkers of carotenoid and tocopherol intake and chronic disease risk in a Women's Health Initiative (WHI) Measurement Precision subcohort (n=5488). Questions remain as to whether self-reported dietary data can usefully augment such biomarkers or can be calibrated using biomarkers for reliable disease association estimation in larger WHI cohorts. The aims were to examine the potential of FFQ data to explain intake variation in a WHI Feeding Study and to compare association parameter estimates and their precision from studies based on biomarker-calibrated FFQ intake in larger WHI cohorts, with those previously presented. Serum-based intake measures were augmented by using FFQ data in a WHI Feeding Study (n=153). Corresponding calibration equations were generated, both in a companion Nutritional Biomarker Study (n=436) and in the previously mentioned subcohort (n=5488), by regressing these intake measures on dietary data and participant characteristics, for α- and β-carotene, lutein plus zeaxanthin, and α-tocopherol. The supplemental value of FFQ data was considered by examining the fraction of feeding study intake variation explained by these regression models. Calibrated intake and disease association analyses were evaluated by comparisons with previously reported subcohort results. The inclusion of FFQ data led to some increases in feeding study intake variation explained (total R2 of ∼50%). Calibrated intake estimates explained 25-75% of serum-based intake variation, whether developed using either of the 2 cohort subsamples. Related disease associations for micronutrients were precisely estimated in larger WHI cohorts (n=76,691) but were often closer to the null compared with previously reported associations. FFQ data may usefully augment blood concentrations in estimating the intake of carotenoids and tocopherols. Calibrated intake estimates using FFQ, dietary supplement, and participant characteristics only may require further justification to ensure reliable estimation of related disease associations.