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Over 200,000 individuals are diagnosed with lung cancer in the United States 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 postmenopausal 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 effect of smoking status, age, and sex on the tumor mutational landscape and identifies areas of unmet medical need.

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., (© 2023 American College of Rheumatology. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.)

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., (Copyright © 2023 American Society for Nutrition. Published by Elsevier Inc. All rights reserved.)

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., (Copyright © 2023 American Society for Nutrition. Published by Elsevier Inc. All rights reserved.)

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., (© 2023 by the American Diabetes Association.)

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., (© The Author(s) 2022. Published by Oxford University Press on behalf of the American Society for Nutrition.)

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.

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., (© The Author(s) 2022. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

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., Competing Interests: The authors declare no conflict of interest., (Copyright © 2020 Wolters Kluwer Health, Inc. All rights reserved.)

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.

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., (© The Author(s) 2022. Published by Oxford University Press on behalf of the American Society for Nutrition.)

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., (© The Author(s) 2022. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

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 Author(s) 2022. Published by Oxford University Press on behalf of the American Society for Nutrition.)