Background Age is one of the strongest predictors of cancer, chronic disease, and mortality, but biological responses to aging differ among people. Epigenetic DNA modifications have been used to estimate “biological age,” which may be a useful predictor of disease risk. We tested this hypothesis for breast cancer. Methods Using a case-cohort approach, we measured baseline blood DNA methylation of 2764 women enrolled in the Sister Study, 1566 of whom subsequently developed breast cancer after an average of 6 years. Using three previously established methylation-based “clocks” (Hannum, Horvath, and Levine), we defined biological age acceleration for each woman by comparing her estimated biological age with her chronological age. Hazard ratios and 95% confidence intervals for breast cancer risk were estimated using Cox regression models. All statistical tests were two-sided. Results Each of the three clocks showed that biological age acceleration was statistically significantly associated with increased risk of developing breast cancer (5-year age acceleration, Hannum’s clock: hazard ratio [HR] = 1.10, 95% confidence interval [CI] = 1.00 to 1.21, P = .04; Horvath’s clock: HR = 1.08, 95% CI = 1.00 to 1.17, P = .04; Levine’s clock: HR = 1.15, 95% CI = 1.07 to 1.23, P < .001). For Levine’s clock, each 5-year acceleration in biological age corresponded with a 15% increase in breast cancer risk. Although biological age may accelerate with menopausal transition, age acceleration in premenopausal women independently predicted breast cancer. Case-only analysis suggested that, among women who develop breast cancer, increased age acceleration is associated with invasive cancer (odds ratio for invasive = 1.09, 95% CI = 0.98 to 1.22, P = .10). Conclusions DNA methylation-based measures of biological age may be important predictors of breast cancer risk.

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.

BackgroundBreast cancer formation is associated with frequent changes in DNA methylation but the extent of very early alterations in DNA methylation and the biological significance of cancer-associated epigenetic changes need further elucidation.MethodsPyrosequencing was done on bisulfite-treated DNA from formalin-fixed, paraffin-embedded sections containing invasive tumor and paired samples of histologically normal tissue adjacent to the cancers as well as control reduction mammoplasty samples from unaffected women. The DNA regions studied were promoters (BRCA1, CD44, ESR1, GSTM2, GSTP1, MAGEA1, MSI1, NFE2L3, RASSF1A, RUNX3, SIX3 and TFF1), far-upstream regions (EN1, PAX3, PITX2, and SGK1), introns (APC, EGFR, LHX2, RFX1 and SOX9) and the LINE-1 and satellite 2 DNA repeats. These choices were based upon previous literature or publicly available DNA methylome profiles. The percent methylation was averaged across neighboring CpG sites.ResultsMost of the assayed gene regions displayed hypermethylation in cancer vs. adjacent tissue but the TFF1 and MAGEA1 regions were significantly hypomethylated (p ≤0.001). Importantly, six of the 16 regions examined in a large collection of patients (105 – 129) and in 15-18 reduction mammoplasty samples were already aberrantly methylated in adjacent, histologically normal tissue vs. non-cancerous mammoplasty samples (p ≤0.01). In addition, examination of transcriptome and DNA methylation databases indicated that methylation at three non-promoter regions (far-upstream EN1 and PITX2 and intronic LHX2) was associated with higher gene expression, unlike the inverse associations between cancer DNA hypermethylation and cancer-altered gene expression usually reported. These three non-promoter regions also exhibited normal tissue-specific hypermethylation positively associated with differentiation-related gene expression (in muscle progenitor cells vs. many other types of normal cells). The importance of considering the exact DNA region analyzed and the gene structure was further illustrated by bioinformatic analysis of an alternative promoter/intron gene region for APC.ConclusionsWe confirmed the frequent DNA methylation changes in invasive breast cancer at a variety of genome locations and found evidence for an extensive field effect in breast cancer. In addition, we illustrate the power of combining publicly available whole-genome databases with a candidate gene approach to study cancer epigenetics.Electronic supplementary materialThe online version of this article (doi:10.1186/s12885-015-1777-9) contains supplementary material, which is available to authorized users.

Key Points Question Is living in a neighborhood with a high concentration of household and population features characteristic of lower socioeconomic status (ie, a neighborhood with high deprivation) associated with epigenetic age acceleration across first- and second-generation clock metrics? Findings This cross-sectional study comprised 2630 women who had a sister with breast cancer but had not had breast cancer themselves. Those living in areas with the greatest compared with least neighborhood deprivation had higher epigenetic age acceleration estimated by Hannum, PhenoAge, and GrimAge clocks but not the Horvath clock. Meaning The results of this study suggest that residing in a neighborhood with a higher deprivation index appears to be reflected by methylation-based markers of aging.

We posit that maternal prenatal nutrition can influence offspring schizophrenia risk via epigenetic effects. In this article, we consider evidence that prenatal nutrition is linked to epigenetic outcomes in offspring and schizophrenia in offspring, and that schizophrenia is associated with epigenetic changes. We focus upon one-carbon metabolism as a mediator of the pathway between perturbed prenatal nutrition and the subsequent risk of schizophrenia. Although post-mortem human studies demonstrate DNA methylation changes in brains of people with schizophrenia, such studies cannot establish causality. We suggest a testable hypothesis that utilizes a novel two-step Mendelian randomization approach, to test the component parts of the proposed causal pathway leading from prenatal nutritional exposure to schizophrenia. Applied here to a specific example, such an approach is applicable for wider use to strengthen causal inference of the mediating role of epigenetic factors linking exposures to health outcomes in population-based studies.

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 nationwide Sister Study, we calculated six epigenetic age acceleration metrics using four epigenetic clocks (Hannum, Horvath, PhenoAge, GrimAge). Recreational physical activity was self-reported and adiposity measures were assessed by 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 PhenoAgeAccel, a measure of biological age that correlates with chronic disease (BMI≥35.0 vs 18.5–25: β=3.15 years, 95% CI: 2.41, 3.90; P-trend&lt;0.001). In a mutually-adjusted model, BMI and WtH ratio were both associated with PhenoAgeAccel (BMI≥35.0 vs 18.5–24.9: β=2.69 years, 95% CI: 1.90, 3.48; P-trend&lt;0.001; Quartile 4 vs 1 WtH: β=1.00 years, 95% CI: 0.34, 1.65; P-trend&lt;0.001). After adjustment, physical activity was only associated with GrimAgeAccel (Quartile 4 vs 1: β=−0.42 years, 95% CI: −0.70, −0.14; P-trend=0.001). Physical activity attenuated the waist circumference associations with PhenoAgeAccel and GrimAgeAccel. Excess adiposity was associated with epigenetic age acceleration; physical activity may attenuate associations with waist circumference.

Background: Epigenetic age, as defined by DNA methylation, may be influenced by air pollution exposure. Objective: To evaluate the relationship between NO 2 , 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 PM 2.5 , PM 10 and NO 2 using a model incorporating land-use regression and kriging. Predictive k -means was used to assign participants to clusters representing different PM 2.5 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 PM 2.5 , we stratified by cluster membership. We examined epigenome-wide associations using robust linear regression models corrected with false discovery rate q-values. Results: NO 2 was inversely associated with age acceleration using the Hannum clock (β = −0.24, 95% Cl: − 0.47, −0.02). No associations were observed for PM 10 . For PM 2.5 , the association with age acceleration varied by PM 2.5 component cluster. For example, with the Levine clock, an IQR increase in PM 2.5 was associated with an over 6-year age acceleration in a cluster that has relatively high fractions of crustal elements relative to overall PM 2.5 (β = 6.57, 95% CI: 2.68, 10.47), and an almost 2-year acceleration in a cluster characterized by relatively low sulfur fractions (β = 1.88, 95% CI: 0.51, 3.25). In a cluster distinguished by lower relative nitrate concentrations, PM 2.5 was inversely associated with age acceleration (β = −1.33, 95% CI: −2.43, −0.23). Across the epigenome, NO 2 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 PM 2.5 component profiles.

PurposeTo test the hypothesis that retinal vascular diameter and hemoglobin oxygen saturation alterations, according to stages of diabetic retinopathy (DR), are discernible with a commercially available scanning laser ophthalmoscope (SLO).MethodsOne hundred eighty-one subjects with no diabetes (No DM), diabetes with no DR (No DR), nonproliferative DR (NPDR), or proliferative DR (PDR, all had photocoagulation) underwent imaging with an SLO with dual lasers (532 nm and 633 nm). Customized image analysis software determined the diameters of retinal arteries and veins (DA and DV) and central retinal artery and vein equivalents (CRAE and CRVE). Oxygen saturations of hemoglobin in arteries and veins (SO2A and SO2V) were estimated from optical densities of vessels on images at the two wavelengths. Statistical models were generated by adjusting for effects of sex, race, age, eye, and fundus pigmentation.ResultsDA, CRAE, and CRVE were reduced in PDR compared to No DM (P ≤ 0.03). DV and CRVE were similar between No DM and No DR, but they were higher in NPDR than No DR (P ≤ 0.01). Effect of stage of disease on SO2A differed by race, being increased relative to No DM in NPDR and PDR in Hispanic participants only (P ≤ 0.02). Relative to No DM, SO2V was increased in NPDR and PDR (P ≤ 0.05).ConclusionsAlterations in retinal vascular diameters and SO2 by diabetic retinopathy stage can be detected with a widely available SLO, and covariates such as race can influence the results.