Diet quality and cardiovascular disease risk among breast cancer survivors in the Pathways Study.

BACKGROUND: Women with breast cancer are at higher risk of cardiovascular disease (CVD) compared with women without breast cancer. Whether higher diet quality at breast cancer diagnosis lowers this risk remains unknown. We set out to determine if higher diet quality at breast cancer diagnosis was related to lower risk of CVD and CVD-related death. METHODS: This analysis included 3415 participants from the Pathway Study, a prospective cohort of women diagnosed with invasive breast cancer at Kaiser Permanente Northern California between 2005 and 2013 and followed through December 31, 2021. Scores from 5 diet quality indices consistent with healthy eating were obtained at the time of breast cancer diagnosis. Scores were categorized into ascending quartiles of concordance for each diet quality index, and multivariable adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated. P values were 2-sided. RESULTS: The Dietary Approaches to Stop Hypertension diet quality index was associated with lower risk of heart failure (HR = 0.53, 95% CI = 0.33 to 0.87; Ptrend = .03), arrhythmia (HR = 0.77, 95% CI = 0.62 to 0.94; Ptrend = .008), cardiac arrest (HR = 0.77, 95% CI = 0.61 to 0.96; Ptrend = .02), valvular heart disease (HR = 0.79, 95% CI = 0.64 to 0.98; Ptrend = .046), venous thromboembolic disease (HR = 0.75, 95% CI = 0.60 to 0.93; Ptrend = .01), and CVD-related death (HR = 0.70, 95% CI = 0.50 to 0.99; Ptrend = .04), when comparing the highest with lowest quartiles. Inverse associations were also found between the healthy plant-based dietary index and heart failure (HR = 0.60, 95% CI = 0.39 to 0.94; Ptrend = .02), as well as the alternate Mediterranean dietary index and arrhythmia (HR = 0.74, 95% CI = 0.60 to 0.93; Ptrend = .02). CONCLUSION: Among newly diagnosed breast cancer patients, higher diet quality at diagnosis was associated with lower risk of CVD events and death.

Circulating Leukocyte Subsets Before and After a Breast Cancer Diagnosis and Therapy.

Importance: Changes in leukocyte composition often precede chronic disease onset. Patients with a history of breast cancer (hereinafter referred to as breast cancer survivors) are at increased risk for subsequent chronic diseases, but the long-term changes in peripheral leukocyte composition following a breast cancer diagnosis and treatment remain unknown. Objective: To examine longitudinal changes in peripheral leukocyte composition in women who did and did not develop breast cancer and identify whether differences in breast cancer survivors were associated with specific treatments. Design, Setting, and Participants: In this prospective cohort study, paired blood samples were collected from 2315 women enrolled in The Sister Study, a US-nationwide prospective cohort study of 50 884 women, at baseline (July 2003 to March 2009) and follow-up (October 2013 to March 2015) home visits, with a mean (SD) follow-up interval of 7.6 (1.4) years. By design, approximately half of the included women had been diagnosed and treated for breast cancer after enrollment and before the second blood draw. A total of 410 women were included in the present study, including 185 breast cancer survivors and 225 who remained free of breast cancer over a comparable follow-up period. Data were analyzed from April 21 to September 9, 2022. Exposures: Breast cancer status and, among breast cancer survivors, cancer treatment type (chemotherapy, radiotherapy, endocrine therapy, or surgery). Main Outcomes and Measures: Blood DNA methylation data were generated in 2019 using a genome-wide methylation screening tool and deconvolved to estimate percentages of 12 circulating leukocyte subsets. Results: Of the 410 women included in the analysis, the mean (SD) age at enrollment was 56 (9) years. Compared with breast cancer-free women, breast cancer survivors had decreased percentages of circulating eosinophils (-0.45% [95% CI, -0.87% to -0.03%]; P = .03), total CD4+ helper T cells (-1.50% [95% CI, -2.56% to -0.44%]; P = .01), and memory B cells (-0.22% [95% CI, -0.34% to -0.09%]; P = .001) and increased percentages of circulating naive B cells (0.46% [95% CI, 0.17%-0.75%]; P = .002). In breast cancer survivor-only analyses, radiotherapy was associated with decreases in total CD4+ T cell levels, whereas chemotherapy was associated with increases in naive B cell levels. Surgery and endocrine therapy were not meaningfully associated with leukocyte changes. Conclusions and Relevance: In this cohort study of 410 women, breast cancer survivors experienced lasting changes in peripheral leukocyte composition compared with women who remained free of breast cancer. These changes may be related to treatment with chemotherapy or radiotherapy and could influence future chronic disease risk.

Air pollution and epigenetic aging among Black and White women in the US.

BACKGROUND: DNA methylation-based measures of biological aging have been associated with air pollution and may link pollutant exposures to aging-related health outcomes. However, evidence is inconsistent and there is little information for Black women. OBJECTIVE: We examined associations of ambient particulate matter <2.5 µm and <10 µm in diameter (PM2.5 and PM10) and nitrogen dioxide (NO2) with DNA methylation, including epigenetic aging and individual CpG sites, and evaluated whether associations differ between Black and non-Hispanic White (NHW) women. METHODS: Validated models were used to estimate annual average outdoor residential exposure to PM2.5, PM10, and NO2 in a sample of self-identified Black (n=633) and NHW (n=3493) women residing in the contiguous US. We used sampling-weighted generalized linear regression to examine the effects of pollutants on six epigenetic aging measures (primary: DunedinPACE, GrimAgeAccel, and PhenoAgeAccel; secondary: Horvath intrinsic epigenetic age acceleration [EAA], Hannum extrinsic EAA, and skin & blood EAA) and epigenome-wide associations for individual CpG sites. Wald tests of nested models with and without interaction terms were used to examine effect measure modification by race/ethnicity. RESULTS: Black participants had higher median air pollution exposure than NHW participants. GrimAgeAccel was associated with both PM10 and NO2 among Black participants, (Q4 versus Q1, PM10: ß=1.09, 95% CI: 0.16-2.03; NO2: ß=1.01, 95% CI 0.08-1.94) but not NHW participants (p-for-heterogeneity: PM10=0.10, NO2=0.20). In Black participants, we also observed a monotonic exposure-response relationship between NO2 and DunedinPACE (Q4 versus Q1, NO2: ß=0.029, 95% CI: 0.004-0.055; p-for-trend=0.03), which was not observed in NHW participants (p-for-heterogeneity=0.09). In the EWAS, pollutants were significantly associated with differential methylation at 19 CpG sites in Black women and one in NHW women. CONCLUSIONS: In a US-wide cohort study, our findings suggest that air pollution is associated with DNA methylation alterations consistent with higher epigenetic aging among Black, but not NHW, women.

Differences in epigenetic age by HIV status among patients with a non-AIDS defining cancer.

OBJECTIVE: People with HIV (PWH) are living longer and experiencing higher numbers of non-AIDS-defining cancers (NADC). Epigenetic aging biomarkers have been linked to cancer risk, and cancer is now a leading cause of death in PWH, but these biomarkers have not been investigated in PWH and cancer. DESIGN: In order to compare epigenetic age by HIV status, HIV-uninfected participants were matched to PWH by reported age, tumor site, tumor sequence number, and cancer treatment status. METHODS: DNA from blood was assayed using Illumina MethylationEPIC BeadChip, and we estimated immune cell composition and aging from three epigenetic clocks: Horvath, GrimAge, and epiTOC2. Age acceleration by clock was computed as the residual from the expected value, calculated using linear regression, for each study participant. Comparisons across HIV status used the Wilcoxon rank sum test. Hazard ratios and 95% confidence intervals for the association between age acceleration and survival in PWH were estimated with Cox regression. RESULTS: Among 65 NADC participants with HIV and 64 without, biological age from epiTOC2 ( P  < 0.0001) and GrimAge ( P  = 0.017) was significantly higher in PWH. Biological age acceleration was significantly higher in PWH using epiTOC2 ( P  < 0.01) and GrimAge ( P  < 0.0001), with the difference in GrimAge remaining statistically significant after adjustment for immune cell composition. Among PWH, GrimAge acceleration was significantly associated with increased risk of death (hazard ratio 1.11; 95% confidence interval (CI) 1.04-1.18). CONCLUSION: We observed a higher epigenetic age in PWH with a NADC diagnosis compared with their HIV-uninfected counterparts, as well as a significant association between this accelerated biological aging and survival for patients diagnosed with a NADC.

Changes in methylation-based aging in women who do and do not develop breast cancer.

BACKGROUND: Breast cancer survivors have increased incidence of age-related diseases, suggesting that some survivors may experience faster biological aging. METHODS: Among 417 women enrolled in the prospective Sister Study cohort, DNA methylation data were generated on paired blood samples collected an average of 7.7 years apart and used to calculate 3 epigenetic metrics of biological aging (PhenoAgeAccel, GrimAgeAccel, and Dunedin Pace of Aging Calculated from the Epigenome [DunedinPACE]). Approximately half (n = 190) the women sampled were diagnosed and treated for breast cancer between blood draws, whereas the other half (n = 227) remained breast cancer-free. Breast tumor characteristics and treatment information were abstracted from medical records. RESULTS: Among women who developed breast cancer, diagnoses occurred an average of 3.5 years after the initial blood draw and 4 years before the second draw. After accounting for covariates and biological aging metrics measured at baseline, women diagnosed and treated for breast cancer had higher biological aging at the second blood draw than women who remained cancer-free as measured by PhenoAgeAccel (standardized mean difference [ß] = 0.13, 95% confidence interval [CI) = 0.00 to 0.26), GrimAgeAccel (ß = 0.14, 95% CI = 0.03 to 0.25), and DunedinPACE (ß = 0.37, 95% CI = 0.24 to 0.50). In case-only analyses assessing associations with different breast cancer therapies, radiation had strong positive associations with biological aging (PhenoAgeAccel: ß = 0.39, 95% CI = 0.19 to 0.59; GrimAgeAccel: ß = 0.29, 95% CI = 0.10 to 0.47; DunedinPACE: ß = 0.25, 95% CI = 0.02 to 0.48). CONCLUSIONS: Biological aging is accelerated following a breast cancer diagnosis and treatment. Breast cancer treatment modalities appear to differentially contribute to biological aging.

Methylation-Based Biological Age and Hypertension Prevalence and Incidence.

BACKGROUND: Hypertension is common in older individuals and is a major risk factor for cardiovascular disease. Blood DNA methylation profiles have been used to derive metrics of biological age that capture age-related physiological change, disease risk, and mortality. The relationships between hypertension and DNA methylation-based biological age metrics have yet to be carefully described. METHODS: Among 4419 women enrolled in the prospective Sister Study cohort, DNA methylation data generated from whole blood samples collected at baseline were used to calculate 3 biological age metrics (PhenoAgeAccel, GrimAgeAccel, DunedinPACE). Women were classified as hypertensive at baseline if they had high blood pressure (systolic blood pressure ≥140 mm Hg or diastolic blood pressure ≥90 mm Hg) or reported current use of antihypertensive medication. New incident cases of hypertension during follow-up were identified via self-report on annual health questionnaires. RESULTS: All 3 DNA methylation metrics of biological age were positively associated with prevalent hypertension at baseline (per 1-SD increase; PhenoAgeAccel, adjusted odds ratio, 1.16 [95% CI, 1.05-1.28]; GrimAgeAccel, adjusted odds ratio, 1.28 [95% CI, 1.14-1.45]; DunedinPACE, adjusted odds ratio, 1.16 [95% CI, 1.03-1.30]). Among 2610 women who were normotensive at baseline, women with higher biological age were more likely to be diagnosed with incident hypertension (per 1-SD increase; PhenoAgeAccel, adjusted hazard ratio, 1.09 [95% CI, 0.97-1.23]; GrimAgeAccel, adjusted hazard ratio, 1.16 [95% CI, 0.99-1.36]; DunedinPACE, adjusted hazard ratio, 1.16 [95% CI, 1.01-1.33]). CONCLUSIONS: Methylation-based biological age metrics increase before a hypertension diagnosis and appear to remain elevated in the years after clinical diagnosis and treatment.

Peripheral Immune Cell Composition is Altered in Women Before and After a Hypertension Diagnosis.

BACKGROUND: The development and consequences of hypertension involve multiple biological systems that may include changes in immune profiles. Whether hypertension is related to peripheral immune cell composition has not been examined in large human cohorts. METHODS: We estimated circulating proportions of 12 leukocyte subsets from the lymphoid and myeloid lineages by deconvolving cell-type-specific DNA methylation data from 4124 women. Hypertension status at baseline was defined by current use of antihypertensive medication and blood pressure measurements while new incident cases were identified during follow-up via annual health questionnaires. RESULTS: Among hypertension-free women at baseline, higher B cell and lower naïve CD4+ helper T cell proportions were associated with subsequent increased hazard of hypertension incidence (B cells; adjusted HR: 1.17 [95% CI: 1.02-1.35]; P=0.03; naïve CD4+ T cell, adjusted HR: 0.88 [95% CI: 0.78-0.99]; P=0.04). Blood pressure measurements at baseline were similarly positively associated with B cells and inversely associated with naïve CD4+ helper T cells. Compared to normotensive women, women with hypertension had higher circulating proportions of neutrophils (adjusted odds ratio: 1.18 [95% CI: 1.07-1.31]; P=0.001) and lower proportions of CD4+ helper T cells (adjusted odds ratio: 0.90 [95% CI: 0.81-1.00] P=0.05), natural killers (adjusted odds ratio: 0.82 [95% CI: 0.74-0.91]; P<0.001), and B cells (adjusted odds ratio: 0.84 [95% CI: 0.74-0.96]; P=0.01). CONCLUSIONS: These observations suggest that shifts in lymphocyte subsets occur before hypertension development, followed by later changes to neutrophils and additional lymphocytes.

Low Serum Klotho Associated With All-cause Mortality Among a Nationally Representative Sample of American Adults.

α-Klotho (klotho) is a protein involved in suppressing oxidative stress and inflammation. In animal models, it is reported to underlie numerous aging phenotypes and longevity. Among a nationally representative sample of adults aged 40-79 years in the United States, we investigated whether circulating concentrations of klotho is a marker of mortality risk. Serum klotho was measured by ELISA on 10 069 individuals enrolled in the National Health and Nutrition Examination Survey between 2007 and 2014. Mortality follow-up data based on the National Death Index were available through December 31, 2015. After a mean follow-up of 58 months (range: 1-108), 616 incident deaths occurred. Using survey-weighted Cox regression models adjusted for age, sex, and survey cycle, low serum klotho concentration (<666 pg/mL) was associated with a 31% higher risk of death (compared to klotho concentration > 985 pg/mL, hazard ratio [HR]: 1.31, 95% confidence interval [CI]: 1.00, 1.71, p = .05). Associations were consistent for mortality caused by heart disease or cancer. Associations of klotho with all-cause mortality did not appear to differ by most participant characteristics. However, we observed effect modification by physical activity, such that low levels of serum klotho were more strongly associated with mortality among individuals who did not meet recommendation-based physical activity guidelines. Our findings suggest that, among the general population of American adults, circulating levels of klotho may serve as a marker of mortality risk.

Healthy eating patterns and epigenetic measures of biological age.

BACKGROUND: Healthy eating is associated with lower risks of disease and mortality, but the mechanisms underlying these associations are unclear. Age is strongly related to health outcomes, and biological age can be estimated using the blood methylome. OBJECTIVES: To determine whether healthy eating patterns are associated with methylation-based measures of biological age. METHODS: Among women in the Sister Study, we calculated scores on 4 recommendation-based healthy eating indexes [Dietary Approaches to Stop Hypertension diet, Healthy Eating Index-2015, Alternative Healthy Eating Index (aHEI-2010), and the Alternative Mediterranean diet] using a validated 110-item Block FFQ completed at enrollment. Genome-wide DNA methylation data were generated using the HumanMethylation450 BeadChip on whole blood samples collected at enrollment from a case-cohort sample of 2694 women and were used to calculate 4 measures of epigenetic age acceleration (Hannum AgeAccel, Horvath AgeAccel, PhenoAgeAccel, and GrimAgeAccel). Linear regression models, adjusted for covariates and cohort sampling weights, were used to examine cross-sectional associations between eating patterns and measures of biological age. RESULTS: All 4 healthy eating indexes had inverse associations with epigenetic age acceleration, most notably with PhenoAgeAccel and GrimAgeAccel. Of these, the strongest associations were for aHEI-2010 [per 1-SD increase in diet quality, PhenoAgeAccel ß = -0.5 y (95% CI: -0.8 to -0.2 y) and GrimAgeAccel ß = -0.4 y (95% CI: -0.6 to -0.3 y)]. Although effect modification was not observed for most lifestyle factors, in analyses stratified by physical activity, the benefits of a healthy diet on epigenetic age acceleration were more pronounced among women who did not meet physical activity guidelines (reporting <2.5 h/wk of exercise). CONCLUSIONS: Higher diet quality is inversely associated with methylation-based measures of biological age. Improving diet could have the most benefits in lowering biological age among women with lower levels of physical activity. This trial was registered at clinicaltrials.gov as NCT00047970.

Blood DNA methylation profiles improve breast cancer prediction.

Although blood DNA methylation (DNAm) profiles are reported to be associated with breast cancer incidence, they have not been widely used in breast cancer risk assessment. Among a breast cancer case-cohort of 2774 women (1551 cases) in the Sister Study, we used candidate CpGs and DNAm estimators of physiologic characteristics to derive a methylation-based breast cancer risk score, mBCRS. Overall, 19 CpGs and five DNAm estimators were selected using elastic net regularization to comprise mBCRS. In a test set, higher mBCRS was positively associated with breast cancer incidence, showing similar strength to the polygenic risk score (PRS) based on 313 single nucleotide polymorphisms (313 SNPs). Area under the curve for breast cancer prediction was 0.60 for self-reported risk factors (RFs), 0.63 for PRS, and 0.63 for mBCRS. Adding mBCRS to PRS and RFs improved breast cancer prediction from 0.66 to 0.71. mBCRS findings were replicated in a nested case-control study within the EPIC-Italy cohort. These results suggest that mBCRS, a risk score derived using blood DNAm, can be used to enhance breast cancer prediction.

Genome-wide association studies identify 137 genetic loci for DNA methylation biomarkers of aging.

BACKGROUND: Biological aging estimators derived from DNA methylation data are heritable and correlate with morbidity and mortality. Consequently, identification of genetic and environmental contributors to the variation in these measures in populations has become a major goal in the field. RESULTS: Leveraging DNA methylation and SNP data from more than 40,000 individuals, we identify 137 genome-wide significant loci, of which 113 are novel, from genome-wide association study (GWAS) meta-analyses of four epigenetic clocks and epigenetic surrogate markers for granulocyte proportions and plasminogen activator inhibitor 1 levels, respectively. We find evidence for shared genetic loci associated with the Horvath clock and expression of transcripts encoding genes linked to lipid metabolism and immune function. Notably, these loci are independent of those reported to regulate DNA methylation levels at constituent clock CpGs. A polygenic score for GrimAge acceleration showed strong associations with adiposity-related traits, educational attainment, parental longevity, and C-reactive protein levels. CONCLUSION: This study illuminates the genetic architecture underlying epigenetic aging and its shared genetic contributions with lifestyle factors and longevity.

Alcohol Consumption and Methylation-Based Measures of Biological Age.

Epigenetic age acceleration is considered a measure of biological aging based on genome-wide patterns of DNA methylation. Although age acceleration has been associated with the incidence of diseases and death, less is known about how it is related to lifestyle behaviors. Among 2316 women, we evaluate associations between self-reported alcohol consumption and various metrics of epigenetic age acceleration. Recent average alcohol consumption was defined as the mean number of drinks consumed per week within the past year; lifetime average consumption was estimated as the mean number of drinks per year drinking. Whole-blood genome-wide DNA methylation was measured with HumanMethylation450 BeadChips and used to assess 4 epigenetic clocks (Hannum, Horvath, PhenoAge, and GrimAge) and their corresponding metrics of epigenetic age acceleration (Hannum AgeAccel, Horvath AgeAccel, PhenoAgeAccel, and GrimAgeAccel). Although alcohol consumption showed little association with most age acceleration metrics, both lifetime and recent average consumption measures were positively associated with GrimAgeAccel (lifetime, per additional 135 drinks/year: ß = 0.30 years, 95% confidence interval [CI]: 0.11, 0.48, p = .002; recent, per additional 5 drinks/week: ß = 0.19 years, 95% CI: 0.01, 0.37, p = .04). In a mutually adjusted model, only average lifetime alcohol consumption remained associated with GrimAgeAccel (lifetime, per additional 135 drinks/year: ß = 0.27 years, 95% CI: 0.04, 0.50, p = .02; recent, per 5 additional drinks/week: ß = 0.05 years, 95% CI: -0.16, 0.26, p = .64). Although alcohol use does not appear to be strongly associated with biological age measured by most epigenetic clocks, lifetime average consumption is associated with higher biological age assessed by the GrimAge epigenetic clock.

Associations of Body Composition and Physical Activity Level With Multiple Measures of Epigenetic Age Acceleration.

Epigenetic clocks use DNA methylation to estimate biological age. Whether body composition and physical activity are associated with these clocks is not well understood. Using blood samples collected at enrollment (2003-2009) from 2,758 women in the US nationwide Sister Study, we calculated 6 epigenetic age acceleration metrics using 4 epigenetic clocks (Hannum, Horvath, PhenoAge, GrimAge). Recreational physical activity was self-reported, and adiposity measures were assessed by trained medical examiners (body mass index (BMI), waist-to-hip ratio (WtH), waist circumference). In cross-sectional analyses, all adiposity measures were associated with epigenetic age acceleration. The strongest association was for BMI and PhenoAge, a measure of biological age that correlates with chronic disease (BMI of ≥35.0 vs. 18.5-24.9, ß = 3.15 years, 95% confidence interval (CI): 2.41, 3.90; P for trend < 0.001). In a mutual-adjustment model, both were associated with PhenoAge age acceleration (BMI of ≥35.0 vs. 18.5-24.9, ß = 2.69 years, 95% CI: 1.90, 3.48; P for trend < 0.001; quartile 4 vs.1 WtH, ß = 1.00 years, 95% CI: 0.34, 1.65; P for trend < 0.008). After adjustment, physical activity was associated only with GrimAge (quartile 4 vs. 1, ß = -0.42 years, 95% CI: -0.70, -0.14; P for trend = 0.001). Physical activity attenuated the waist circumference associations with PhenoAge and GrimAge. Excess adiposity was associated with epigenetic age acceleration; physical activity might attenuate associations with waist circumference.

Association of Neighborhood Deprivation With Epigenetic Aging Using 4 Clock Metrics.

Importance: Neighborhood deprivation is associated with age-related disease, mortality, and reduced life expectancy. However, biological pathways underlying these associations are not well understood. Objective: To evaluate the association between neighborhood deprivation and epigenetic measures of age acceleration and genome-wide methylation. Design, Setting, and Participants: This cross-sectional study used data from the Sister Study, a prospective cohort study comprising 50 884 women living in the US and Puerto Rico aged 35 to 74 years at enrollment who had a sister with breast cancer but had not had breast cancer themselves. Cohort enrollment occurred between July 2003 and March 2009. Participants completed a computer-assisted telephone interview on demographic, socioeconomic, lifestyle, and residential factors and provided anthropometric measures and peripheral blood samples at a home examination. DNA methylation data obtained for 2630 non-Hispanic White women selected for a case-cohort study in 2014 were used in this cross-sectional analysis. DNA methylation was measured using the HumanMethylation450 BeadChips in whole blood samples collected at baseline. Data analysis for this study was performed from October 17, 2019, to August 27, 2020. Exposures: Each participants' primary address was linked to an established index of neighborhood deprivation. Main Outcomes and Measures: Epigenetic age was estimated using 4 epigenetic clocks (Horvath, Hannum, PhenoAge, and GrimAge). Age acceleration was determined using residuals from regressing chronologic age on each of the 4 epigenetic age metrics. Linear regression was used to estimate associations between neighborhood deprivation and epigenetic age acceleration as well as DNA methylation at individual cytosine-guanine sites across the genome. Results: Mean (SD) age of the 2630 participants was 56.9 (8.7) years. Those with the greatest (>75th percentile) vs least (≤25th percentile) neighborhood deprivation had higher epigenetic age acceleration estimated by Hannum (ß = 0.23; 95% CI, 0.01-0.45), PhenoAge (ß = 0.28; 95% CI, 0.06-.50), and GrimAge (ß = 0.37; 95% CI, 0.12-0.62). Increasing US quartiles of neighborhood deprivation exhibited a trend with Hannum, PhenoAge, and GrimAge. For example, GrimAge showed a significant dose-response (P test for trend <.001) as follows: level 2 vs level 1 (ß = 0.30; 95% CI, 0.17-0.42), level 3 vs level 1 (ß = 0.35; 95% CI, 0.19-0.50), and level 4 vs level 1 (ß = 0.37; 95% CI, 0.12-0.62). Neighborhood deprivation was found to be associated with 3 cytosine-phosphate-guanine sites, with 1 of these annotated to a known gene MAOB (P = 9.71 × 10-08). Conclusions and Relevance: The findings of this study suggest that residing in a neighborhood with a higher deprivation index appears to be reflected by methylation-based markers of aging.

Prediagnostic Immune Cell Profiles and Breast Cancer.

Importance: Higher overall leukocyte counts in women may be associated with increased risk of breast cancer, but the association of specific leukocyte subtypes with breast cancer risk remains unknown. Objective: To determine associations between circulating leukocyte subtypes and risk of breast cancer. Design, Setting, and Participants: Between 2003 and 2009, the Sister Study enrolled 50 884 women who had a sister previously diagnosed with breast cancer but were themselves breast cancer free. A case-cohort subsample was selected in July 2014 from the full Sister Study cohort. Blood samples were obtained at baseline, and women were followed up through October 2016. Data analysis was performed in April 2019. Main Outcomes and Measures: The main outcome was the development of breast cancer in women. Whole-blood DNA methylation was measured, and methylation values were deconvoluted using the Houseman method to estimate proportions of 6 leukocyte subtypes (B cells, natural killer cells, CD8+ and CD4+ T cells, monocytes, and granulocytes). Leukocyte subtype proportions were dichotomized at their population median value, and Cox proportional hazard models were used to estimate associations with breast cancer. Results: Among 2774 non-Hispanic white women included in the analysis (mean [SD] age at enrollment, 56.6 [8.8] years), 1295 women were randomly selected from the full cohort (of whom 91 developed breast cancer) along with an additional 1479 women who developed breast cancer during follow-up (mean [SD] time to diagnosis, 3.9 [2.2] years). Circulating proportions of B cells were positively associated with later breast cancer (hazard ratio [HR], 1.17; 95% CI, 1.01-1.36; P = .04). Among women who were premenopausal at blood collection, the association between B cells and breast cancer was significant (HR, 1.38; 95% CI, 1.05-1.82; P = .02), and an inverse association for circulating proportions of monocytes was found (HR, 0.75; 95% CI, 0.57-0.99; P = .05). Among all women, associations between leukocyte subtypes and breast cancer were time dependent: higher monocyte proportions were associated with decreased near-term risk (within 1 year of blood collection, HR, 0.62; 95% CI, 0.43-0.89; P = .01), whereas higher B cell proportions were associated with increased risk 4 or more years after blood collection (HR, 1.38; 95% CI, 1.15-1.67; P = .001). Conclusions and Relevance: Circulating leukocyte profiles may be altered before clinical diagnoses of breast cancer and may be time-dependent markers for breast cancer risk, particularly among premenopausal women.

Epigenetic mortality predictors and incidence of breast cancer.

Measures derived using blood DNA methylation are increasingly under investigation as indicators of disease and mortality risk. Three existing epigenetic age measures or "epigenetic clocks" appear associated with breast cancer. Two newly-developed epigenetic mortality predictors may be related to all-cancer incidence, but associations with specific cancers have not been examined in large studies. Using HumanMethylation450 BeadChips to measure blood DNA methylation in 2,773 cancer-free women enrolled in the Sister Study, we calculated two epigenetic mortality predictors: 'GrimAgeAccel' and the 'mortality score' (MS). Using Cox proportional hazard models, neither GrimAgeAccel nor the MS were associated with overall breast cancer incidence (GrimAgeAccel hazard ratio [HR]: 1.06, 95% confidence interval [CI]: 0.98-1.14, P=0.17; MS HR: 0.99, 95% CI: 0.92-1.07, P=0.85); however, a weak, positive association was observed for GrimAgeAccel and invasive breast cancer (HR: 1.08, 95% CI: 0.99-1.17, P=0.08). Stratification of invasive cancers by menopause status at diagnoses revealed the association was predominantly observed for postmenopausal breast cancer (HR: 1.10, 95% CI: 1.01, 1.20, P=0.04). Although the MS was unrelated to breast cancer risk, we find evidence that GrimAgeAccel may be weakly associated with invasive breast cancer, particularly for women diagnosed after menopause.

Reproduction, DNA methylation and biological age.

STUDY QUESTION: Are reproductive characteristics associated with genome-wide DNA methylation and epigenetic age? SUMMARY ANSWER: Our data suggest that increasing parity is associated with differences in blood DNA methylation and small increases in epigenetic age. WHAT IS KNOWN ALREADY: A study of 397 young Filipino women (ages 20-22) observed increasing epigenetic age with an increasing number of pregnancies. STUDY DESIGN, SIZE, DURATION: We used data from 2356 non-Hispanic white women (ages 35-74) enrolled in the Sister Study cohort. PARTICIPANTS/MATERIALS, SETTING, METHODS: Data on reproductive history were ascertained via questionnaire. Of the 2356 women, 1897 (81%) reported at least one live birth. Among parous women, 487 (26%) women reported ever experiencing a pregnancy complication. Three epigenetic clocks (i.e. Hannum, Horvath and Levine) and genome-wide methylation were measured in DNA from whole blood using Illumina's HumanMethylation450 BeadChip. We estimated association ß-values and 95% CIs using linear regression. MAIN RESULTS AND THE ROLE OF CHANCE: All three epigenetic clocks showed weak associations between number of births and epigenetic age (per live birth; Hannum: ß = 0.16, 95% CI = 0.02, 0.29, P = 0.03; Horvath: ß = 0.12, 95% CI = -0.04, 0.27, P = 0.14; Levine: ß = 0.27, 95% CI = 0.08, 0.45, P = 0.01); however, additional adjustment for current BMI attenuated the associations. Among parous women, a history of abnormal glucose tolerance during pregnancy was associated with increased epigenetic age by the Hannum clock (ß = 0.96; 95% CI = 0.10, 1.81; P = 0.03) and Levine clocks (ß = 1.69; 95% CI = 0.54, 2.84; P < 0.01). In epigenome-wide analysis, increasing parity was associated with methylation differences at 17 CpG sites (Bonferroni corrected P≤ 1.0 × 10-7). LIMITATIONS, REASONS FOR CAUTION: We relied on retrospective recall to ascertain reproductive history and pregnancy complications. WIDER IMPLICATIONS OF THE FINDINGS: Our findings suggest that parity is associated with small increases in epigenetic age and with DNA methylation at multiple sites in the genome. STUDY FUNDING/COMPETING INTEREST(S): This research was supported by the Intramural Research program of the NIH, National Institute of Environmental Health Sciences (Z01-ES049033, Z01-ES049032 and Z01-ES044055). None of the authors have a conflict of interest. TRIAL REGISTRATION NUMBER: Not applicable.

Air pollution, particulate matter composition and methylation-based biologic age.

BACKGROUND: Epigenetic age, as defined by DNA methylation, may be influenced by air pollution exposure. OBJECTIVE: To evaluate the relationship between NO2, particulate matter (PM), PM components and accelerated epigenetic age. METHODS: In a sample of non-Hispanic white women living in the contiguous U.S. (n = 2747), we estimated residential exposure to PM2.5, PM10 and NO2 using a model incorporating land-use regression and kriging. Predictive k-means was used to assign participants to clusters representing different PM2.5 component profiles. We measured DNA methylation (DNAm) in blood using the Illumina's Infinium HumanMethylation450 BeadChip and calculated DNAm age using the Hannum, Horvath and Levine epigenetic clocks. Age acceleration was defined based on residuals after regressing DNAm age on chronological age. We estimated associations between interquartile range (IQR) increases in pollutants and age acceleration using linear regression. For PM2.5, we stratified by cluster membership. We examined epigenome-wide associations using robust linear regression models corrected with false discovery rate q-values. RESULTS: NO2 was inversely associated with age acceleration using the Hannum clock (ß = -0.24, 95% CI: -0.47, -0.02). No associations were observed for PM10. For PM2.5, the association with age acceleration varied by PM2.5 component cluster. For example, with the Levine clock, an IQR increase in PM2.5 was associated with an over 6-year age acceleration in a cluster that has relatively high fractions of crustal elements relative to overall PM2.5 (ß = 6.57, 95% CI: 2.68, 10.47), and an almost 2-year acceleration in a cluster characterized by relatively low sulfur fractions (ß = 1.88, 95% CI: 0.51, 3.25). In a cluster distinguished by lower relative nitrate concentrations, PM2.5 was inversely associated with age acceleration (ß = -1.33, 95% CI: -2.43, -0.23). Across the epigenome, NO2 was associated with methylation at 2 CpG sites. CONCLUSION: Air pollution was associated with epigenetic age, a marker of mortality and disease risk, among certain PM2.5 component profiles.

Metallic air pollutants and breast cancer heterogeneity.

BACKGROUND: Emerging evidence suggests airborne metals may be associated with breast cancer risk. However, breast cancer is heterogenous and associations with heavy metals vary by subtype. Heavy metals possess both carcinogenic and xenoestrogenic properties which may be related to different tumor etiologies. Therefore, we tested for etiologic heterogeneity, using a case-series approach, to determine whether associations between residential airborne metal concentrations and breast cancer differed by tumor subtype. METHODS: Between 2005 and 2008, we enrolled incident breast cancer cases into the Breast Cancer Care in Chicago study. Tumor estrogen and progesterone receptors status was determined by medical record abstraction and confirmed immunohistochemically (N = 696; 147 ER/PR-negative). The 2002 USEPA's National Air Toxics Assessment census-tract estimates of metal concentrations (antimony, arsenic, beryllium, cadmium, chromium, cobalt, lead, manganese, mercury, nickel and selenium) were matched to participants' residences of the same year. Adjusted logistic regression models were used to examine whether the airborne heavy metal associations differed by tumor ER/PR status. Principal component analysis was performed to assess associations by metal co-exposures. RESULTS: Comparing the highest and lowest quintiles, higher concentrations of antimony (odds ratio[OR]: 1.8, 95% confidence interval[CI]: 0.9, 3.7, P-trend: 0.05), cadmium (OR: 2.3, 95% CI: 1.2, 4.4, P-trend: 0.04) and cobalt (OR: 2.0, 95% CI: 0.9, 4.4, P-trend: 0.04) were associated with ER/PR-negative breast cancer. Mixture analysis using principal components suggested co-exposures to multiple airborne heavy metals may drive associations with tumor receptor status. CONCLUSIONS: Among women diagnosed with breast cancer, metallic air pollutants were associated with increased odds of developing ER/PR-negative breast cancer.