The genomic landscape of lung cancer in never-smokers from the Women's Health Initiative.

Over 200,000 individuals are diagnosed with lung cancer in the U.S. every year, with a growing proportion of cases, especially lung adenocarcinoma, occurring in individuals who have never smoked. Women over the age of 50 comprise the largest affected demographic. To understand the genomic drivers of lung adenocarcinoma and therapeutic response in this population, we performed whole genome and/or whole exome sequencing on 73 matched lung tumor/normal pairs from post-menopausal women who participated in the Women's Health Initiative. Somatic copy number alterations showed little variation by smoking status, suggesting that aneuploidy may be a general characteristic of lung cancer regardless of smoke exposure. Similarly, clock-like and APOBEC mutation signatures were prevalent but did not differ in tumors from smokers and never-smokers. However, mutations in both EGFR and KRAS showed unique allelic differences determined by smoking status that are known to alter tumor response to targeted therapy. Mutations in the MYC-network member MGA were more prevalent in tumors from smokers. Fusion events in ALK, RET, and ROS1 were absent, likely due to age-related differences in fusion prevalence. Our work underscores the profound impact of smoking status, age, and sex on the tumor mutational landscape and identifies areas of unmet medical need.

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.

Life Events, Caregiving, and Risk of Autoimmune Rheumatic Diseases in the Women's Health Initiative Observational Study.

OBJECTIVE: Growing evidence suggests psychosocial stressors may increase risk of developing autoimmune disease. We examined stressful life events and caregiving in relation to incident rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE) in the Women's Health Initiative Observational Study cohort. METHODS: The sample of postmenopausal women included 211 incident RA or SLE cases reported within 3 years after enrollment, confirmed by use of disease-modifying antirheumatic drugs (i.e., probable RA/SLE), and 76,648 noncases. Baseline questionnaires asked about life events in the past year, caregiving, and social support. We used Cox regression models to calculate hazard ratios (HR) and 95% confidence intervals (95% CIs), adjusting for age, race/ethnicity, occupational class, education, pack-years of smoking and BMI. RESULTS: Incident RA/SLE was associated with reporting 3 or more life events (e.g., age-adjusted HR 1.70 [95% CI 1.14, 2.53]; P for trend = 0.0026). Elevated HRs were noted for physical (HR 2.48 [95% CI 1.02, 6.04]) and verbal (HR 1.34 [0.89, 2.02]) abuse (P for trend = 0.0614), 2 or more interpersonal events (HR 1.23 [95% CI 0.87, 1.73]; P for trend = 0.2403), financial stress (HR 1.22 [95% CI 0.90, 1.64]), and caregiving 3 or more days per week (HR 1.25 [95% CI 0.87, 1.81]; P for trend = 0.2571). Results were similar, excluding women with baseline symptoms of depression or moderate-to-severe joint pain in the absence of diagnosed arthritis. CONCLUSION: Our findings support the idea that diverse stressors may increase risk of developing probable RA or SLE in postmenopausal women, supporting the need for further studies in autoimmune rheumatic diseases, including childhood adverse events, life event trajectories, and modifying psychosocial and socioeconomic factors.

Investigating Gene-Diet Interactions Impacting the Association Between Macronutrient Intake and Glycemic Traits.

Few studies have demonstrated reproducible gene-diet interactions (GDIs) impacting metabolic disease risk factors, likely due in part to measurement error in dietary intake estimation and insufficient capture of rare genetic variation. We aimed to identify GDIs across the genetic frequency spectrum impacting the macronutrient-glycemia relationship in genetically and culturally diverse cohorts. We analyzed 33,187 participants free of diabetes from 10 National Heart, Lung, and Blood Institute Trans-Omics for Precision Medicine program cohorts with whole-genome sequencing, self-reported diet, and glycemic trait data. We fit cohort-specific, multivariable-adjusted linear mixed models for the effect of diet, modeled as an isocaloric substitution of carbohydrate for fat, and its interactions with common and rare variants genome-wide. In main effect meta-analyses, participants consuming more carbohydrate had modestly lower glycemic trait values (e.g., for glycated hemoglobin [HbA1c], -0.013% HbA1c/250 kcal substitution). In GDI meta-analyses, a common African ancestry-enriched variant (rs79762542) reached study-wide significance and replicated in the UK Biobank cohort, indicating a negative carbohydrate-HbA1c association among major allele homozygotes only. Simulations revealed that >150,000 samples may be necessary to identify similar macronutrient GDIs under realistic assumptions about effect size and measurement error. These results generate hypotheses for further exploration of modifiable metabolic disease risk in additional cohorts with African ancestry. ARTICLE HIGHLIGHTS: We aimed to identify genetic modifiers of the dietary macronutrient-glycemia relationship using whole-genome sequence data from 10 Trans-Omics for Precision Medicine program cohorts. Substitution models indicated a modest reduction in glycemia associated with an increase in dietary carbohydrate at the expense of fat. Genome-wide interaction analysis identified one African ancestry-enriched variant near the FRAS1 gene that may interact with macronutrient intake to influence hemoglobin A1c. Simulation-based power calculations accounting for measurement error suggested that substantially larger sample sizes may be necessary to discover further gene-macronutrient interactions.

Somatic mutation but not aneuploidy differentiates lung cancer in never-smokers and smokers.

Lung cancer in never-smokers disproportionately affects older women. To understand the mutational landscape of this cohort, we performed detailed genome characterization of 73 lung adenocarcinomas from participants of the Women’s Health Initiative (WHI). We find enrichment of EGFR mutations in never-/light-smokers and KRAS mutations in heavy smokers as expected, but we also show that the specific variants of these genes differ by smoking status, with important therapeutic implications. Mutational signature analysis revealed signatures of clock, APOBEC, and DNA repair deficiency in never-/light-smokers; however, the mutational load of these signatures did not differ significantly from those found in smokers. Last, tumors from both smokers and never-/light-smokers shared copy number subtypes, with no significant differences in aneuploidy. Thus, the genomic landscape of lung cancer in never-/light-smokers and smokers is predominantly differentiated by somatic mutations and not copy number alterations.

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.

Continuity of Care Among Postmenopausal Women With Cardiometabolic Diseases in the United States Early During the COVID-19 Pandemic: Findings From the Women's Health Initiative.

BACKGROUND: In response to the COVID-19 pandemic, public health measures, including stay-at-home orders, were widely instituted in the United States by March 2020. However, few studies have evaluated the impact of these measures on continuity of care among older adults living with chronic diseases. METHODS: Beginning in June 2020, participants of the national Women's Health Initiative (WHI) (N = 64 061) were surveyed on the impact of the pandemic on various aspects of their health and well-being since March 2020, including access to care appointments, medications, and caregivers. Responses received by November 2020 (response rate = 77.6%) were tabulated and stratified by prevalent chronic diseases, including hypertension, type 2 diabetes, and cardiovascular disease (CVD). RESULTS: Among 49 695 respondents (mean age = 83.6 years), 70.2% had a history of hypertension, 21.8% had diabetes, and 18.9% had CVD. Half of the respondents reported being very concerned about the pandemic, and 24.5% decided against seeking medical care to avoid COVID-19 exposure. A quarter reported difficulties with getting routine care, and 45.5% had in-person appointments converted to telemedicine formats; many reported canceled (27.8%) or rescheduled (37.7%) appointments. Among those taking prescribed medication (88.0%), 9.7% reported changing their method of obtaining medications. Those living with and without chronic diseases generally reported similar changes in care and medication access. CONCLUSIONS: Early in the pandemic, many older women avoided medical care or adapted to new ways of receiving care and medications. Therefore, optimizing alternative services, like telemedicine, should be prioritized to ensure that older women continue to receive quality care during public health emergencies.

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.

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.

Taking action to advance the study of race and ethnicity: the Women's Health Initiative (WHI).

"Race" and "ethnicity" are socially constructed terms, not based on biology - in contrast to biologic ancestry and genetic admixture - and are flexible, contested, and unstable concepts, often driven by power. Although individuals may self-identify with a given race and ethnic group, as multidimensional beings exposed to differential life influencing factors that contribute to disease risk, additional social determinants of health (SDOH) should be explored to understand the relationship of race or ethnicity to health. Potential health effects of structural racism, defined as "the structures, policies, practices, and norms resulting in differential access to goods, services, and opportunities of society by "race," have been largely ignored in medical research. The Women's Health Initiative (WHI) was expected to enroll a racially and ethnically diverse cohort of older women at 40 U.S. clinical centers between 1993 and 1998; yet, key information on the racial and ethnic make-up of the WHI cohort of 161,808 women was limited until a 2020-2021 Task Force was charged by the WHI Steering Committee to better characterize the WHI cohort and develop recommendations for WHI investigators who want to include "race" and/or "ethnicity" in papers and presentations. As the lessons learned are of relevance to most cohorts, the essence of the WHI Race and Ethnicity Language and Data Interpretation Guide is presented in this paper. Recommendations from the WHI Race and Ethnicity Language and Data Interpretation Guide include: Studies should be designed to include all populations and researchers should actively, purposefully and with cultural-relevance, commit to recruiting a diverse sample; Researchers should collect robust data on race, ethnicity and SDOH variables that may intersect with participant identities, such as immigration status, country of origin, acculturation, current residence and neighborhood, religion; Authors should use appropriate terminology, based on a participant's self-identified "race" and "ethnicity", and provide clear rationale, including a conceptual framework, for including race and ethnicity in the analytic plan; Researchers should employ appropriate analytical methods, including mixed-methods, to study the relationship of these sociocultural variables to health; Authors should address how representative study participants are of the population to which results might apply, such as by age, race and ethnicity.

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.

Association of Premature Menopause With Risk of Abdominal Aortic Aneurysm in the Women's Health Initiative.

OBJECTIVE: To determine if premature menopause and early menarche are associated with increased risk of AAA, and to explore potential effect modification by smoking history. SUMMARY OF BACKGROUND DATA: Despite worse outcomes for women with AAA, no studies have prospectively examined sex-specific risk factors, such as premature menopause and early menarche, with risk of AAA in a large, ethnically diverse cohort of women. METHODS: This was a post-hoc analysis of Women's Health Initiative participants who were beneficiaries of Medicare Parts A&B fee-for-service. AAA cases and interventions were identified from claims data. Follow-up period included Medicare coverage until death, end of follow-up or end of coverage inclusive of 2017. RESULTS: Of 101,119 participants included in the analysis, the mean age was 63 years and median follow-up was 11.3 years. Just under 10,000 (9.4%) women experienced premature menopause and 22,240 (22%) experienced early men-arche. Women with premature menopause were more likely to be overweight, Black, have >20 pack years of smoking, history of cardiovascular disease, hypertension, and early menarche. During 1,091,840 person-years of follow-up, 1125 women were diagnosed with AAA, 134 had premature menopause (11.9%), 93 underwent surgical intervention and 45 (48%) required intervention for ruptured AAA. Premature menopause was associated with increased risk of AAA [hazard ratio 1.37 (1.14, 1.66)], but the association was no longer significant after multivariable adjustment for demographics and cardiovascular disease risk factors. Amongst women with ≥20 pack year smoking history (n = 19,286), 2148 (11.1%) had premature menopause, which was associated with greater risk of AAA in all models [hazard ratio 1.63 (1.24, 2.23)]. Early menarche was not associated with increased risk of AAA. CONCLUSIONS: This study finds that premature menopause may be an important risk factor for AAA in women with significant smoking history. There was no significant association between premature menopause and risk of AAA amongst women who have never smoked. These results suggest an opportunity to develop strategies for better screening, risk reduction and stratification, and outcome improvement in the comprehensive vascular care of women.

Rare Coding Variants Associated With Electrocardiographic Intervals Identify Monogenic Arrhythmia Susceptibility Genes: A Multi-Ancestry Analysis.

BACKGROUND: Alterations in electrocardiographic (ECG) intervals are well-known markers for arrhythmia and sudden cardiac death (SCD) risk. While the genetics of arrhythmia syndromes have been studied, relations between electrocardiographic intervals and rare genetic variation at a population level are poorly understood. METHODS: Using a discovery sample of 29 000 individuals with whole-genome sequencing from Trans-Omics in Precision Medicine and replication in nearly 100 000 with whole-exome sequencing from the UK Biobank and MyCode, we examined associations between low-frequency and rare coding variants with 5 routinely measured electrocardiographic traits (RR, P-wave, PR, and QRS intervals and corrected QT interval). RESULTS: We found that rare variants associated with population-based electrocardiographic intervals identify established monogenic SCD genes (KCNQ1, KCNH2, and SCN5A), a controversial monogenic SCD gene (KCNE1), and novel genes (PAM and MFGE8) involved in cardiac conduction. Loss-of-function and pathogenic SCN5A variants, carried by 0.1% of individuals, were associated with a nearly 6-fold increased odds of the first-degree atrioventricular block (P=8.4×10-5). Similar variants in KCNQ1 and KCNH2 (0.2% of individuals) were associated with a 23-fold increased odds of marked corrected QT interval prolongation (P=4×10-25), a marker of SCD risk. Incomplete penetrance of such deleterious variation was common as over 70% of carriers had normal electrocardiographic intervals. CONCLUSIONS: Our findings indicate that large-scale high-depth sequence data and electrocardiographic analysis identifies monogenic arrhythmia susceptibility genes and rare variants with large effects. Known pathogenic variation in conventional arrhythmia and SCD genes exhibited incomplete penetrance and accounted for only a small fraction of marked electrocardiographic interval prolongation.

Novel Application of Nutritional Biomarkers From a Controlled Feeding Study and an Observational Study to Characterization of Dietary Patterns in Postmenopausal Women.

Dietary guidance emphasizes healthy dietary patterns, but supporting evidence comes from self-reported dietary data, which are prone to measurement error. We explored whether nutritional biomarkers from the Women's Health Initiative Nutrition and Physical Activity Assessment Study Feeding Study (NPAAS-FS) (n = 153; 2010-2014) and the Women's Health Initiative Nutrition and Physical Activity Assessment Study Observational Study (NPAAS-OS) (n = 450; 2006-2009) could identify biomarker signatures of dietary patterns for development of corresponding regression calibration equations to help mitigate measurement error. Fasting blood samples were assayed for a specific panel of vitamins, carotenoids, and phospholipid fatty acids; 24-hour urine samples were assayed for nitrogen, sodium, and potassium levels. Intake records from the NPAAS-FS were used to calculate Healthy Eating Index 2010 (HEI-2010), Alternative Healthy Eating Index 2010 (AHEI-2010), alternative Mediterranean diet (aMED), and Dietary Approaches to Stop Hypertension (DASH) scores. Scores were regressed on blood and urine nutritional measures for discovery of dietary pattern biomarkers using a cross-validated model R2 ≥ 36% criterion (stage 1). Next, stepwise models (P ≤ 0.10 for entry/removal) using NPAAS-OS data were used to regress stage 1 dietary pattern biomarkers on NPAAS-OS self-reported dietary pattern scores using a food frequency questionnaire, a 4-day food record, and a 24-hour recall (stage 2). HEI-2010 and aMED analyses met the cross-validated R2 ≥ 36% criterion in stage 1, while AHEI-2010 and DASH analyses did not. The R2 values for HEI-2010 stage 2 calibration equations were as follows: food frequency questionnaire, 63.5%; 4-day food record, 83.1%; and 24-hour recall, 77.8%. Stage 2 aMED R2 values were 34.9%-46.8%. Dietary pattern biomarkers have potential for calibrating self-reports to enhance studies of diet-disease associations.

Biomarker-Calibrated Macronutrient Intake and Chronic Disease Risk among Postmenopausal Women.

BACKGROUND: Knowledge about macronutrient intake and chronic disease risk has been limited by the absence of objective macronutrient measures. Recently, we proposed novel biomarkers for protein, protein density, carbohydrate, and carbohydrate density, using established biomarkers and serum and urine metabolomics profiles in a human feeding study. OBJECTIVES: We aimed to use these biomarkers to develop calibration equations for macronutrient variables using dietary self-reports and personal characteristics and to study the association between biomarker-calibrated intake estimates and cardiovascular disease, cancer, and diabetes risk in Women's Health Initiative (WHI) cohorts. METHODS: Prospective disease association analyses are based on WHI cohorts of postmenopausal US women aged 50-79 y when enrolled at 40 US clinical centers (n = 81,954). We used biomarker intake values in a WHI nutritional biomarker study (n = 436) to develop calibration equations for each macronutrient variable, leading to calibrated macronutrient intake estimates throughout WHI cohorts. We then examined the association of these intakes with chronic disease incidence over a 20-y (median) follow-up period using HR regression methods. RESULTS: In analyses that included doubly labeled water-calibrated total energy, HRs for cardiovascular diseases and cancers were mostly unrelated to calibrated protein density. However, many were inversely related to carbohydrate density, with HRs (95% CIs) for a 20% increment in carbohydrate density of 0.81 (0.69, 0.95) and 0.83 (0.74, 0.93), respectively, for primary outcomes of coronary heart disease and breast cancer, as well as 0.74 (0.60, 0.91) and 0.87 (0.81, 0.93) for secondary outcomes of heart failure and total invasive cancer. Corresponding HRs (95% CIs) for type 2 diabetes incidence in relation to protein density and carbohydrate density were 1.17 (1.09, 1.75) and 0.73 (0.66, 0.80), respectively. CONCLUSIONS: At specific energy intake, a diet high in carbohydrate density is associated with substantially reduced risk of major chronic diseases in a population of US postmenopausal women. This trial was registered at clinicaltrials.gov as NCT00000611.

Nutritional epidemiology and the Women's Health Initiative: a review.

The dietary modification (DM) clinical trial, within the Women's Health Initiative (WHI), studied a low-fat dietary pattern intervention that included guidance to increase vegetables, fruit, and grains. This study was motivated in part from uncertainty about the reliability of observational studies examining the association between dietary fat and chronic disease risk by using self-reported dietary data. In addition to this large trial, which had breast and colorectal cancer as its primary outcomes, a substantial biomarker research effort was initiated midway in the WHI program to contribute to nutritional epidemiology research more broadly. Here we review and update findings from the DM trial and from the WHI nutritional biomarker studies and examine implications for future nutritional epidemiology research. The WHI included the randomized controlled DM trial (n = 48,835) and a prospective cohort observational (OS) study (n = 93,676), both among postmenopausal US women, aged 50-79 y when enrolled during 1993-1998. Also reviewed is a nutrition and physical activity assessment study in a subset of 450 OS participants (2007-2009) and a related controlled feeding study among 153 WHI participants (2010-2014). Long-term follow-up in the DM trial provides evidence for intervention-related reductions in breast cancer mortality, diabetes requiring insulin, and coronary artery disease in the subset of normotensive healthy women, without observed adverse effects or changes in all-cause mortality. Studies of intake biomarkers, and of biomarker-calibrated intake, suggest important associations of total energy intake and macronutrient dietary composition with the risk for major chronic diseases among postmenopausal women. Collectively these studies argue for a nutrition epidemiology research agenda that includes major efforts in nutritional biomarker development, and in the application of biomarkers combined with self-reported dietary data in disease association analyses. We expect such efforts to yield novel disease association findings and to inform disease prevention approaches for potential testing in dietary intervention trials. This trial was registered at clinicaltrials.gov as NCT00000611.

Lipoprotein(a) levels and risk of abdominal aortic aneurysm in the Women's Health Initiative.

OBJECTIVE: Few studies have prospectively examined the associations of lipoprotein(a) [Lp(a)] levels with the risk of abdominal aortic aneurysm (AAA), especially in women. Accounting for commonly recognized risk factors, we investigated the baseline Lp(a) levels and the risk of AAA among postmenopausal women participating in the ongoing national Women's Health Initiative. METHODS: Women's Health Initiative participants with baseline Lp(a) levels available who were beneficiaries of Medicare parts A and B fee-for-service at study enrollment or who had aged into Medicare at any point were included. Participants with missing covariate data or known AAA at baseline were excluded. Thoracic aneurysms were excluded owing to the different pathophysiology. The AAA cases and interventions were identified using the International Classification of Diseases, 9th and 10th revision, codes and Current Procedural Terminology codes from claims data. Hazard ratios were computed using Cox proportional hazard models according to the quintiles of Lp(a). RESULTS: The mean age of the 6615 participants included in the analysis was 65.3 years. Of the 6615 participants, 66.6% were non-Hispanic white, 18.9% were black, 7% were Hispanic and 4.7% were Asian/Pacific Islander. Compared with the participants in the lowest Lp(a) quintile, those in higher quintiles were more likely to be overweight, black, and former or current smokers, to have hypertension, hyperlipidemia, and a history of cardiovascular disease, and to use menopausal hormone therapy and statins. During 65,476 person-years of follow-up, with a median of 10.4 years, 415 women had been diagnosed with an AAA and 36 had required intervention. More than one half had required intervention for a ruptured AAA. We failed to find a statistically significant association between Lp(a) levels and incident AAA. Additional sensitivity analyses stratified by race, with exclusion of statin users and alternative categorizations of Lp(a) using log-transformed levels, tertiles, and a cutoff of >50 mg/dL, were conducted, which did not reveal any significant associations. CONCLUSIONS: We found no statistically significant association between Lp(a) levels and the risk of AAA in a large and well-phenotyped sample of postmenopausal women. Women with high Lp(a) levels were more likely to be overweight, black, and former or current smokers, and to have hypertension, hyperlipidemia, and a history of cardiovascular disease, or to use hormone therapy and statins compared with those with lower Lp(a) levels. These findings differ from previous prospective, case-control, and meta-analysis studies that had supported a significant relationship between higher Lp(a) levels and an increased risk of AAA. Differences in the association could have resulted from study limitations or sex differences.