ABSTRACT Lifestyle-related phenotypes have been shown to be heritable and associated with DNA methylation. We aimed to investigate whether genetic predisposition to tobacco smoking, alcohol consumption, and higher body mass index (BMI) moderates the effect of these phenotypes on blood DNA methylation. We calculated polygenic scores (PGS) to quantify genetic predisposition to these phenotypes using training (N = 7,431) and validation (N = 4,307) samples. Using paired genetic-methylation data (N = 4,307), gene–environment interactions (i.e., PGS × lifestyle) were assessed using linear mixed-effects models with outcomes: 1) methylation at sites found to be strongly associated with smoking (1,061 CpGs), alcohol consumption (459 CpGs), and BMI (85 CpGs) and 2) two epigenetic ageing measures, PhenoAge and GrimAge. In the validation sample, PGS explained ~1.4% (P = 1 × 10−14), ~0.6% (P = 2 × 10−7), and ~8.7% (P = 7 × 10−87) of variance in smoking initiation, alcohol consumption, and BMI, respectively. Nominally significant interaction effects (P < 0.05) were found at 61, 14, and 7 CpGs for smoking, alcohol consumption, and BMI, respectively. There was strong evidence that all lifestyle-related phenotypes were positively associated with PhenoAge and GrimAge, except for alcohol consumption with PhenoAge. There was weak evidence that the association of smoking with GrimAge was attenuated in participants genetically predisposed to smoking (interaction term: −0.022, standard error [SE] = 0.012, P = 0.058) and that the association of alcohol consumption with PhenoAge was attenuated in those genetically predisposed to drink alcohol (interaction term: −0.030, SE = 0.015, P = 0.041). In conclusion, genetic susceptibility to unhealthy lifestyles did not strongly modify the association between observed lifestyle behaviour and blood DNA methylation. Potential associations were observed for epigenetic ageing measures, which should be replicated in additional studies.

We examined demographic and lifestyle risk factors for incidence of gastroesophageal reflux disease (GERD) and Barrett's esophagus (BE) in an Australian cohort of 20,975 participants aged 40-63 at recruitment (1990-1994). Information on GERD and BE was collected between 2007 and 2010. GERD symptoms were defined as self-reported heartburn or acid regurgitation. BE was defined as endoscopically confirmed columnar-lined esophagus. Risk factors for developing GERD symptoms, BE diagnosis, age at symptom onset, and age at BE diagnosis were quantified using regression. During a mean follow-up of 15.8 years, risk of GERD symptoms was 7.5% (n = 1,318) for daily, 7.5% (n = 1,333) for 2-6 days/week, and 4.3% (n = 751) for 1 day/week. There were 210 (1.0%) endoscopically diagnosed BE cases, of whom 141 had histologically confirmed esophageal intestinal metaplasia. Female sex, younger age, lower socioeconomic position (SEP) and educational attainment, and former smoking were associated with higher GERD risk. Male sex and smoking were associated with earlier GERD symptom onset. Men, older participants, those with higher SEP, and former smokers were at higher BE risk. There was some evidence higher SEP was associated with earlier BE diagnosis. GERD and BE had different demographic risk factors but shared similar lifestyle factors. Earlier GERD symptom onset for men and smokers might have contributed to higher BE risk. The SEP patterns observed for GERD and BE suggest potential inequity in access to care. These findings would be important in the development of clinical risk prediction models for early detection of BE.

Background: Self-reported information may not accurately capture smoking exposure. We aimed to evaluate whether smoking-associated DNA methylation markers improve urothelial cell carcinoma (UCC) risk prediction. Methods: Conditional logistic regression was used to assess associations between blood-based methylation and UCC risk using two matched case–control samples: 404 pairs from the Melbourne Collaborative Cohort Study (MCCS) and 440 pairs from the Women's Health Initiative (WHI) cohort. Results were pooled using fixed-effects meta-analysis. We developed methylation-based predictors of UCC and evaluated their prediction accuracy on two replication data sets using the area under the curve (AUC). Results: The meta-analysis identified associations (P < 4.7 × 10−5) for 29 of 1,061 smoking-associated methylation sites, but these were substantially attenuated after adjustment for self-reported smoking. Nominally significant associations (P < 0.05) were found for 387 (36%) and 86 (8%) of smoking-associated markers without/with adjustment for self-reported smoking, respectively, with same direction of association as with smoking for 387 (100%) and 79 (92%) markers. A Lasso-based predictor was associated with UCC risk in one replication data set in MCCS [N = 134; odds ratio per SD (OR) = 1.37; 95% CI, 1.00–1.90] after confounder adjustment; AUC = 0.66, compared with AUC = 0.64 without methylation information. Limited evidence of replication was found in the second testing data set in WHI (N = 440; OR = 1.09; 95% CI, 0.91–1.30). Conclusions: Combination of smoking-associated methylation marks may provide some improvement to UCC risk prediction. Our findings need further evaluation using larger data sets. Impact: DNA methylation may be associated with UCC risk beyond traditional smoking assessment and could contribute to some improvements in stratification of UCC risk in the general population.

Simple Summary: Ageing is the strongest cancer risk factor, and men and women exhibit disparate risk profiles in terms of incidence and survival. DNA methylation is known to strongly vary by age and sex. Epigenetic drift refers to age-related DNA methylation changes and the tendency for increasing discordance between epigenomes over time, but it remains unknown to what extent the epigenetic drift might contribute to cancer risk and survival. The aims of this study were to identify age-associated, sex-associated and sexually dimorphic age-associated (age-by-sex-associated) DNA methylation markers and investigate whether age- and age-by-sex-associated markers are associated with cancer risk and survival. Our study, which used a total of 3,215 matched case-control pairs with DNA methylation in pre-diagnostic blood, is the first large study to examine the association between sex-specific epigenetic drift and cancer development and progression. The results may be useful for cancer early diagnosis and prediction of prognosis. Abstract: To investigate age- and sex-specific DNA methylation alterations related to cancer risk and survival, we used matched case-control studies of colorectal (N=835), gastric (N=170), kidney (N=143), lung (N=332), prostate (N=869) and urothelial (N=428) cancers, and mature B-cell lymphoma (N=438). Linear mixed-effects models were conducted to identify age-, sex- and age-by-sex-associated methylation markers using a discovery (controls) - replication (cases) strategy. Replication was further examined using summary statistics from Generation Scotland (GS). Associations between replicated markers and risk of and survival from cancer were assessed using conditional logistic regression and Cox models (hazard ratios [HR]), respectively. We found 32,659, 23,141 and 48 CpGs with replicated associations for age, sex and age-by-sex, respectively. The replication rates (GS summary data) for these CpGs were 94%, 86% and 91%, respectively. Significant signals for cancer risk and survival were identified at some individual age-related CpGs. There was a strong negative trend in the association between epigenetic drift and risk of colorectal cancer. Two CpGs overlapping TMEM49 and ARX genes were associated with survival of overall (HR=0.91, P=7.7x10-4) and colorectal (HR=1.52, P=1.8x10-4) cancer, respectively, with significant age-by-sex interaction. Our results may provide markers for cancer early detection and prognosis prediction.

Abstract It was not known whether the polygenic risk scores (PRSs) that predict colorectal cancer could predict colorectal cancer for people with inherited pathogenic variants in DNA mismatch repair genes—people with Lynch syndrome. We tested a PRS comprising 107 established single-nucleotide polymorphisms associated with colorectal cancer in European populations for 826 European-descent carriers of pathogenic variants in DNA mismatch repair genes (293 MLH1, 314 MSH2, 126 MSH6, 71 PMS2, and 22 EPCAM) from the Colon Cancer Family Registry, of whom 504 had colorectal cancer. There was no evidence of an association between the PRS and colorectal cancer risk, irrespective of which DNA mismatch repair gene was mutated, or sex (all 2-sided P > .05). The hazard ratio per standard deviation of the PRS for colorectal cancer was 0.97 (95% confidence interval = 0.88 to 1.06; 2-sided P = .51). Whereas PRSs are predictive of colorectal cancer in the general population, they do not predict Lynch syndrome colorectal cancer.

Methylation marks of exposure to health risk factors may be useful markers of cancer risk as they might better capture current and past exposures than questionnaires, and reflect different individual responses to exposure. We used data from seven case‐control studies nested within the Melbourne Collaborative Cohort Study of blood DNA methylation and risk of colorectal, gastric, kidney, lung, prostate and urothelial cancer, and B‐cell lymphoma (N cases = 3123). Methylation scores (MS) for smoking, body mass index (BMI), and alcohol consumption were calculated based on published data as weighted averages of methylation values. Rate ratios (RR) and 95% confidence intervals for association with cancer risk were estimated using conditional logistic regression and expressed per SD increase of the MS, with and without adjustment for health‐related confounders. The contribution of MS to discriminate cases from controls was evaluated using the area under the curve (AUC). After confounder adjustment, we observed: large associations (RR = 1.5‐1.7) with lung cancer risk for smoking MS; moderate associations (RR = 1.2‐1.3) with urothelial cancer risk for smoking MS and with mature B‐cell neoplasm risk for BMI and alcohol MS; moderate to small associations (RR = 1.1‐1.2) for BMI and alcohol MS with several cancer types and cancer overall. Generally small AUC increases were observed after inclusion of several MS in the same model (colorectal, gastric, kidney, urothelial cancers: +3%; lung cancer: +7%; B‐cell neoplasms: +8%). Methylation scores for smoking, BMI and alcohol consumption show independent associations with cancer risk, and may provide some improvements in risk prediction.

Abstract Objective: To examine associations between diet and risk of developing gastro-oesophageal reflux disease (GERD). Design: Prospective cohort with a median follow-up of 15·8 years. Baseline diet was measured using a FFQ. GERD was defined as self-reported current or history of daily heartburn or acid regurgitation beginning at least 2 years after baseline. Sex-specific logistic regressions were performed to estimate OR for GERD associated with diet quality scores and intakes of nutrients, food groups and individual foods and beverages. The effect of substituting saturated fat for monounsaturated or polyunsaturated fat on GERD risk was examined. Setting: Melbourne, Australia. Participants: A cohort of 20 926 participants (62 % women) aged 40–59 years at recruitment between 1990 and 1994. Results: For men, total fat intake was associated with increased risk of GERD (OR 1·05 per 5 g/d; 95 % CI 1·01, 1·09; P = 0·016), whereas total carbohydrate (OR 0·89 per 30 g/d; 95 % CI 0·82, 0·98; P = 0·010) and starch intakes (OR 0·84 per 30 g/d; 95 % CI 0·75, 0·94; P = 0·005) were associated with reduced risk. Nutrients were not associated with risk for women. For both sexes, substituting saturated fat for polyunsaturated or monounsaturated fat did not change risk. For both sexes, fish, chicken, cruciferous vegetables and carbonated beverages were associated with increased risk, whereas total fruit and citrus were associated with reduced risk. No association was observed with diet quality scores. Conclusions: Diet is a possible risk factor for GERD, but food considered as triggers of GERD symptoms might not necessarily contribute to disease development. Potential differential associations for men and women warrant further investigation.

Mammograms contain information that predicts breast cancer risk. We developed two novel mammogram‐based breast cancer risk measures based on image brightness (Cirrocumulus) and texture (Cirrus). Their risk prediction when fitted together, and with an established measure of conventional mammographic density (Cumulus), is not known. We used three studies consisting of: 168 interval cases and 498 matched controls; 422 screen‐detected cases and 1197 matched controls; and 354 younger‐diagnosis cases and 944 controls frequency‐matched for age at mammogram. We conducted conditional and unconditional logistic regression analyses of individually‐ and frequency‐matched studies, respectively. We estimated measure‐specific risk gradients as the change in odds per standard deviation of controls after adjusting for age and body mass index (OPERA) and calculated the area under the receiver operating characteristic curve (AUC). For interval, screen‐detected and younger‐diagnosis cancer risks, the best fitting models (OPERAs [95% confidence intervals]) involved: Cumulus (1.81 [1.41‐2.31]) and Cirrus (1.72 [1.38‐2.14]); Cirrus (1.49 [1.32‐1.67]) and Cirrocumulus (1.16 [1.03 to 1.31]); and Cirrus (1.70 [1.48 to 1.94]) and Cirrocumulus (1.46 [1.27‐1.68]), respectively. The AUCs were: 0.73 [0.68‐0.77], 0.63 [0.60‐0.66], and 0.72 [0.69‐0.75], respectively. Combined, our new mammogram‐based measures have twice the risk gradient for screen‐detected and younger‐diagnosis breast cancer (P ≤ 10−12), have at least the same discriminatory power as the current polygenic risk score, and are more correlated with causal factors than conventional mammographic density. Discovering more information about breast cancer risk from mammograms could help enable risk‐based personalised breast screening.

Lipid dyshomeostasis is associated with the most common form of dementia, Alzheimer’s disease (AD). Substantial progress has been made in identifying positron emission tomography (PET) and cerebrospinal fluid (CSF) biomarkers for AD, but they have limited use as front-line, non-invasive diagnostic tools. Small extracellular vesicles (EVs) are released by all cell types and contain an enriched subset of their parental cell molecular composition, including lipids. EVs are released from the brain into the periphery, providing a potential source of tissue and disease specific lipid biomarkers. However, the EV lipidome of the central nervous system (CNS) is currently unknown and the potential of brain-derived EVs (BDEVs) to inform on lipid dyshomeostasis in AD remains unclear. The aim of this study was to reveal the lipid composition of BDEVs in human frontal cortex tissue, and to determine whether BDEVs in AD have altered lipid profiles compared to age-matched neurological controls (NC). Here, using semi-quantitative mass spectrometry, we describe the BDEV lipidome, covering 4 lipid categories, 17 lipid classes and 692 lipid molecules. Frontal cortex-derived BDEVs were enriched in glycerophosphoserine (PS) lipids, a characteristic of small EVs. Here we report that BDEVs are enriched in ether-containing PS lipids. A novel finding that further establishes ether lipids as a feature of EVs. While no significant changes were detected in the frontal cortex in AD, the lipid profile of the BDEVs from this tissue exhibited disease related differences. AD BDEVs had altered glycerophospholipid (GP) and sphingolipid (SP) levels, specifically increased plasmalogen glycerophosphoethanolamine (PE-P) and decreased polyunsaturated fatty acyl containing lipids (PUFAs), and altered amide-linked acyl chain content in sphingomyelin (SM) and ceramide (Cer) lipids relative to vesicles from neurological control subjects. The most prominent alteration being a two-fold decrease in lipid species containing docosahexaenoic acid (DHA). The in-depth lipidome analysis provided in this study highlights the advantage of EVs over more complex tissues for improved detection of dysregulated lipids that may serve as potential biomarkers in the periphery.

Background: Age-related epigenetic dysregulations are associated with several diseases, including cancer. The number of stochastic epigenetic mutations (SEM) has been suggested as a biomarker of life-course accumulation of exposure-related DNA damage; however, the predictive role of SEMs in cancer has seldom been investigated. Methods: A SEM, at a given CpG site, was defined as an extreme outlier of DNA methylation value distribution across individuals. We investigated the association of the total number of SEMs with the risk of eight cancers in 4,497 case–control pairs nested in three prospective cohorts. Furthermore, we investigated whether SEMs were randomly distributed across the genome or enriched in functional genomic regions. Results: In the three-study meta-analysis, the estimated ORs per one-unit increase in log(SEM) from logistic regression models adjusted for age and cancer risk factors were 1.25; 95% confidence interval (CI), 1.11–1.41 for breast cancer, and 1.23; 95% CI, 1.07–1.42 for lung cancer. In the Melbourne Collaborative Cohort Study, the OR for mature B-cell neoplasm was 1.46; 95% CI, 1.25–1.71. Enrichment analyses indicated that SEMs frequently occur in silenced genomic regions and in transcription factor binding sites regulated by EZH2 and SUZ12 (P < 0.0001 and P = 0.0005, respectively): two components of the polycomb repressive complex 2 (PCR2). Finally, we showed that PCR2-specific SEMs are generally more stable over time compared with SEMs occurring in the whole genome. Conclusions: The number of SEMs is associated with a higher risk of different cancers in prediagnostic blood samples. Impact: We identified a candidate biomarker for cancer early detection, and we described a carcinogenesis mechanism involving PCR2 complex proteins worthy of further investigations.

Background Mammograms contain information that predicts breast cancer risk. We recently discovered two novel mammogram-based breast cancer risk measures based on image brightness (Cirrocumulus) and texture (Cirrus). It is not known whether these measures improve risk prediction when fitted together, and with an established measure of mammographic density (Cumulus). Methods We used three studies consisting of: 168 interval cases and 498 matched controls; 422 screen-detected cases and 1,197 matched controls; and 354 younger-diagnosis cases and 944 frequency-matched controls. We conducted conditional and unconditional logistic regression analyses of individually- and frequency-matched studies, respectively. We reported risk gradients as change in odds ratio per standard deviation of controls after adjusting for age and body mass index (OPERA). For models involving multiple measures, we calculated the OPERA equivalent to the area under the receiver operating characteristic curve. Results For interval, screen-detected and younger-diagnosis cancer, the best fitting models (OPERAs [95% confidence intervals]) were: Cumulus (1.81 [1.41 to 2.31]) and Cirrus (1.7 [1.38 to 2.14]); Cirrus (1.49 [1.32 to 1.67]) and Cirrocumulus (1.16 [1.03 to 1.31]); and Cirrus (1.70 [1.48 to 1.94]) and Cirrocumulus (1.46 [1.27 to 1.68]), respectively. Their OPERA equivalents were: 2.35, 1.58, and 2.28, respectively. Conclusions Our mammogram-based measures improved risk prediction beyond and, except for interval cancers, negated the influence of conventional mammographic density. Combined, these new mammogram-based risk measures are at least as accurate as the current polygenetic risk scores (OPERA ~ 1.6) in predicting, on a population basis, women who will be diagnosed with breast cancer.