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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.

Nutritional epidemiology research using self-reported dietary intake is prone to measurement error. Objective methods are being explored to overcome this limitation.We aimed to examine 1) the association between plasma markers related to inflammation and derive marker scores for dietary patterns [Mediterranean dietary score (MDS), energy-adjusted Dietary Inflammatory Index (E-DIITM), Alternative Healthy Eating Index 2010 (AHEI)] and 2) the associations of these marker scores with mortality.Weighted marker scores were derived from the cross-sectional association between 30 plasma markers and each dietary score (assessed using food-frequency questionnaires) using linear regression for 770 participants in the Melbourne Collaborative Cohort Study (aged 50-82 y). Prospective associations between marker scores and mortality (n = 249 deaths) were assessed using Cox regression (median follow-up: 14.4 y).The MDS, E-DII, and AHEI were associated (P 0.05) with 9, 14, and 11 plasma markers, respectively. Healthier diets (higher MDS and AHEI, and lower anti-inflammatory, E-DII) were associated with lower concentrations of kynurenines, neopterin, IFN-γ, cytokines, and C-reactive protein. Five of 6 markers common to the 3 dietary scores were components of the kynurenine pathway. The 3 dietary-based marker scores were highly correlated (Spearman ρ: -0.74, -0.82, and 0.93). Inverse associations (for 1-SD increment) were observed with all-cause mortality for the MDS marker score (HR: 0.84; 95% CI: 0.72-0.98) and the AHEI marker score (HR: 0.76; 95% CI: 0.66-0.89), whereas a positive association was observed with the E-DII marker score (HR: 1.18; 95% CI: 1.01-1.39). The same magnitude of effect was not observed for the respective dietary patterns.Markers involved in inflammation-related processes are associated with dietary quality, including a substantial overlap between markers associated with the MDS, the E-DII, and the AHEI, especially kynurenines. Unfavorable marker scores, reflecting poorer-quality diets, were associated with increased mortality.

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.

Introduction Long-term effects of physical activity and television (TV) viewing on mortality have been inferred from observational studies. The associations observed do not allow for inferences about the effects of population interventions and could be subject to bias due to time-varying confounding. Methods Using data from the Australian Diabetes, Obesity and Lifestyle Study, collected in 1999–2000 (T0), 2004–2005 (T1), and 2011–2012 (T2), we applied the parametric g-formula to estimate cumulative risks of death under hypothetical interventions on physical activity and/or TV viewing determined from self-report while adjusting for time-varying confounding. Results In the 6377 participants followed up for 13 yr from 2004 to 2005 to death or censoring in 2017, 781 participants died. The observed cumulative risk of death was 12.2%. The most effective hypothetical intervention was to increase weekly physical activity to >300 min (risk ratio (RR), 0.66 (0.46–0.86) compared with a “worst-case” scenario; RR, 0.83 (0.73–0.94) compared with no intervention). Reducing daily TV viewing to

Genetic variants in FOXO3 are associated with longevity. Here, we assessed whether blood DNA methylation at FOXO3 was associated with cancer risk, survival, and mortality. We used data from eight prospective case–control studies of breast (n = 409 cases), colorectal (n = 835), gastric (n = 170), kidney (n = 143), lung (n = 332), prostate (n = 869), and urothelial (n = 428) cancer and B-cell lymphoma (n = 438). Case–control pairs were matched on age, sex, country of birth, and smoking (lung cancer study). Conditional logistic regression was used to assess associations between cancer risk and methylation at 45 CpGs of FOXO3 included on the HumanMethylation450 assay. Mixed-effects Cox models were used to estimate hazard ratios (HR) and 95% confidence intervals (CI) for associations with cancer survival (total n = 2286 deaths). Additionally, using data from 1088 older participants, we assessed associations of FOXO3 methylation with overall and cause-specific mortality (n = 354 deaths). Methylation at a CpG in the first exon region of FOXO3 (6:108882981) was associated with gastric cancer survival (HR = 2.39, 95% CI: 1.60–3.56, p = 1.9 × 10−5). Methylation at three CpGs in TSS1500 and gene body was associated with lung cancer survival (p < 6.1 × 10−5). We found no evidence of associations of FOXO3 methylation with cancer risk and mortality. Our findings may contribute to understanding the implication of FOXO3 in longevity.

Background Inflammation is a key feature of aging and a cause of numerous diseases. We investigated the association of 35 blood markers involved in inflammatory processes with age and mortality and developed a signature of ‘inflammaging’. Methods Thirty-five blood markers relating to the kynurenine pathway, vitamin status, and inflammation were measured in 976 participants in the Melbourne Collaborative Cohort Study at baseline (1990-1994, median age 59 years) and follow-up (2003-2007, median age 70 years). Associations of each marker with age and all-cause mortality were assessed using linear and Cox regression, respectively. A signature of inflammaging was obtained via Lasso regression of age on the markers and tested for association with mortality; we compared mortality associations for this signature and two weighted scores across all markers associated with age and mortality, respectively. Results Most markers (29/35) were associated with age, with strongest associations observed for cystatin C, neopterin, quinolinic acid, and the kynurenine/tryptophan ratio, PAr index, and 3-hydroxykynurenine/xanthurenic acid ratio. Many markers (14/35) showed strong associations with mortality in particular neopterin, quinolinic acid, HK/XA, PAr index, CRP, IL-6 and KTr. The inflammaging signature included six markers and showed strong association with mortality (HR = 1.5, 95%CI: 1.3-1.7), almost as strong as the association of weighted scores combining all measured markers. Conclusions Our study highlights the key role played by markers of the kynurenine pathway and vitamin B6 catabolism in aging, along with other well-established inflammation-related markers. Key messages A signature of ‘inflammaging’ based on 6 markers may be useful to better predict mortality.

Educational inequalities in mortality have been observed for decades, however the underlying biological mechanisms are not well known. We assessed the mediating role of altered aging of immune cells functioning captured by DNA methylation changes in blood (known as epigenetic clocks) in educational associated all-cause mortality. Data were from eight prospective population-based cohort studies, representing 13,021 participants. We found educational inequalities in mortality were larger for men than for women, estimated by hazard differences and ratios. Epigenetic clocks explained approximately 50% of educational inequalities in mortality for men, while the proportion was small for women. Most of this mediation was explained by differential effects of unhealthy lifestyles and morbidities of the WHO risk factors for premature mortality. These results support DNA methylation-based epigenetic aging as a signature of educational inequalities in life expectancy emphasizing the need for policies to address the unequal social distribution of these WHO risk factors.

Background Socio-economic inequalities in mortality are well established, yet the contribution of intermediate risk factors that may underlie these relationships remains unclear. We evaluated the role of multiple modifiable intermediate risk factors underlying socio-economic-associated mortality and quantified the potential impact of reducing early all-cause mortality by hypothetically altering socio-economic risk factors. Methods Data were from seven cohort studies participating in the LIFEPATH Consortium (total n = 179 090). Using both socio-economic position (SEP) (based on occupation) and education, we estimated the natural direct effect on all-cause mortality and the natural indirect effect via the joint mediating role of smoking, alcohol intake, dietary patterns, physical activity, body mass index, hypertension, diabetes and coronary artery disease. Hazard ratios (HRs) were estimated, using counterfactual natural effect models under different hypothetical actions of either lower or higher SEP or education. Results Lower SEP and education were associated with an increase in all-cause mortality within an average follow-up time of 17.5 years. Mortality was reduced via modelled hypothetical actions of increasing SEP or education. Through higher education, the HR was 0.85 [95% confidence interval (CI) 0.84, 0.86] for women and 0.71 (95% CI 0.70, 0.74) for men, compared with lower education. In addition, 34% and 38% of the effect was jointly mediated for women and men, respectively. The benefits from altering SEP were slightly more modest. Conclusions These observational findings support policies to reduce mortality both through improving socio-economic circumstances and increasing education, and by altering intermediaries, such as lifestyle behaviours and morbidities.

Men with prostate cancer experience side effects for which a supportive social environment may be beneficial. We examined the association between four measures of social connectedness and mortality after a prostate cancer diagnosis. Male participants in the Melbourne Collaborative Cohort Study in 1990-1994, who developed incident prostate cancer and attended follow-up in 2003-2007, were eligible for the study. Information on social connectedness, collected at follow-up, included (i) living arrangement; (ii) frequency of visits to friends/relatives and (iii) from friends/relatives; (iv) weekly hours of social activities. A total of 1,421 prostate cancer cases was observed (338 all-cause deaths, 113 from prostate cancer), including 867 after follow-up (150 all-cause deaths, 55 from prostate cancer) and 554 before follow-up (188 all-cause deaths, 58 from prostate cancer). Cox models stratified by tumour Gleason score and stage, and sequentially adjusted for socioeconomic, health- and lifestyle-related confounders, were used to calculate hazard ratios (HR) and 95% confidence intervals (95% CI) for the association between social connectedness and all-cause mortality after prostate cancer. Men who reported living alone before diagnosis had higher overall mortality (HR = 1.6, 95% CI: 1.0-2.5), after adjustment for socioeconomic, health and lifestyle confounders. Lower mortality was observed for men with more social activities (p-trend = 0.07), but not in comprehensively adjusted models. Consistent with these findings, men living alone after prostate cancer diagnosis had higher mortality (HR = 1.3, 95% CI: 0.9-1.9). Lower mortality was observed with increasing socializing hours in the age-adjusted model (p-trend = 0.06) but not after more comprehensive adjustment. Our findings suggest that living with someone, but not other aspects of social connectedness, may be associated with decreased mortality for men with prostate cancer.

Interval breast cancers (those diagnosed between recommended mammography screens) generally have poorer outcomes and are more common among women with dense breasts. We aimed to develop a risk model for interval breast cancer. We conducted a nested case–control study within the Melbourne Collaborative Cohort Study involving 168 interval breast cancer patients and 498 matched control subjects. We measured breast density using the CUMULUS software. We recorded first‐degree family history by questionnaire, measured body mass index (BMI) and calculated age‐adjusted breast tissue aging, a novel measure of exposure to estrogen and progesterone based on the Pike model. We fitted conditional logistic regression to estimate odds ratio (OR) or odds ratio per adjusted standard deviation (OPERA) and calculated the area under the receiver operating characteristic curve (AUC). The stronger risk associations were for unadjusted percent breast density (OPERA = 1.99; AUC = 0.66), more so after adjusting for age and BMI (OPERA = 2.26; AUC = 0.70), and for family history (OR = 2.70; AUC = 0.56). When the latter two factors and their multiplicative interactions with age‐adjusted breast tissue aging (p = 0.01 and 0.02, respectively) were fitted, the AUC was 0.73 (95% CI 0.69–0.77), equivalent to a ninefold interquartile risk ratio. In summary, compared with using dense breasts alone, risk discrimination for interval breast cancers could be doubled by instead using breast density, BMI, family history and hormonal exposure. This would also give women with dense breasts, and their physicians, more information about the major consequence of having dense breasts—an increased risk of developing an interval breast cancer., What's new? Breast cancers that are detected between regular screening intervals are more aggressive and have poorer outcomes than screen‐detected tumors but no valid risk model exists to predict “interval” breast cancers. Here the authors combined breast density with other breast cancer risk factors such as body mass index, family history and a novel measure of age‐adjusted hormonal exposure. Applying this to more than 150 women with interval breast cancer, they find that risk discrimination can be doubled with the combination of factors as compared with just using breast density alone, thus improving risk predictions and clinical recommendations for breast screening procedures.

Background Environmental and genetic factors play an important role in the etiology of breast cancer. Several small blood-based DNA methylation studies have reported risk associations with methylation at individual CpGs and average methylation levels; however, these findings require validation in larger prospective cohort studies. To investigate the role of blood DNA methylation on breast cancer risk, we conducted a meta-analysis of four prospective cohort studies, including a total of 1663 incident cases and 1885 controls, the largest study of blood DNA methylation and breast cancer risk to date. Methods We assessed associations with methylation at 365,145 CpGs present in the HumanMethylation450 (HM450K) Beadchip, after excluding CpGs that did not pass quality controls in all studies. Each of the four cohorts estimated odds ratios (ORs) and 95% confidence intervals (CI) for the association between each individual CpG and breast cancer risk. In addition, each study assessed the association between average methylation measures and breast cancer risk, adjusted and unadjusted for cell-type composition. Study-specific ORs were combined using fixed-effect meta-analysis with inverse variance weights. Stratified analyses were conducted by age at diagnosis ( 10 years). The false discovery rate (q value) was used to account for multiple testing. Results The average age at blood draw ranged from 52.2 to 62.2 years across the four cohorts. Median follow-up time ranged from 6.6 to 8.4 years. The methylation measured at individual CpGs was not associated with breast cancer risk (q value > 0.59). In addition, higher average methylation level was not associated with risk of breast cancer (OR = 0.94, 95% CI = 0.85, 1.05; P = 0.26; P for study heterogeneity = 0.86). We found no evidence of modification of this association by age at diagnosis (P = 0.17), ER status (P = 0.88), time since blood collection (P = 0.98), or CpG location (P = 0.98). Conclusions Our data indicate that DNA methylation measured in the blood prior to breast cancer diagnosis in predominantly postmenopausal women is unlikely to be associated with substantial breast cancer risk on the HM450K array. Larger studies or with greater methylation coverage are needed to determine if associations exist between blood DNA methylation and breast cancer risk.

Age- and body mass index (BMI)-adjusted mammographic density is one of the strongest breast cancer risk factors. DNA methylation is a molecular mechanism that could underlie inter-individual variation in mammographic density. We aimed to investigate the association between breast cancer risk-predicting mammographic density measures and blood DNA methylation. For 436 women from the Australian Mammographic Density Twins and Sisters Study and 591 women from the Melbourne Collaborative Cohort Study, mammographic density (dense area, nondense area and percentage dense area) defined by the conventional brightness threshold was measured using the CUMULUS software, and peripheral blood DNA methylation was measured using the HumanMethylation450 (HM450) BeadChip assay. Associations between DNA methylation at >400,000 sites and mammographic density measures adjusted for age and BMI were assessed within each cohort and pooled using fixed-effect meta-analysis. Associations with methylation at genetic loci known to be associated with mammographic density were also examined. We found no genome-wide significant (p 0.05/299 = 1.7 × 10-4 ). In summary, our study did not find evidence for associations between blood DNA methylation, as measured by the HM450 assay, and conventional mammographic density measures that predict breast cancer risk.

We investigated aberrant DNA methylation (DNAm) changes and the contribution of ageing-associated methylomic drift and age acceleration to early-onset colorectal cancer (EOCRC) carcinogenesis. Genome-wide DNAm profiling using the Infinium HM450K on 97 EOCRC tumour and 54 normal colonic mucosa samples was compared with: (1) intermediate-onset CRC (IOCRC, diagnosed between 50–70 years, 343 tumour and 35 normal), and (2) late-onset CRC (LOCRC, &gt, 70 years, 318 tumour and 40 normal). CpGs associated with age-related methylation drift were identified using a public dataset of 231 normal mucosa samples from people without CRC. DNAm-age was estimated using epiTOC2. Common to all three age-of-onset groups, 88,385 (20% of all CpGs) CpGs were differentially methylated between tumour and normal mucosa. We identified 234 differentially methylated genes that were unique to the EOCRC group, 13 of these DMRs/genes were replicated in EOCRC compared with LOCRCs from TCGA. In normal mucosa from people without CRC, we identified 28,154 CpGs that undergo ageing-related DNAm drift, and of those, 65% were aberrantly methylated in EOCRC tumours. Based on the mitotic-based DNAm clock epiTOC2, we identified age acceleration in normal mucosa of people with EOCRC compared with normal mucosa from the IOCRC, LOCRC groups (p = 3.7 × 10−16) and young people without CRC (p = 5.8 × 10−6). EOCRC acquires unique DNAm alterations at 234 loci. CpGs associated with ageing-associated drift were widely affected in EOCRC without needing the decades-long accrual of DNAm drift as commonly seen in intermediate- and late-onset CRCs. Accelerated ageing in normal mucosa from people with EOCRC potentially underlies the earlier age of diagnosis in CRC carcinogenesis.

BackgroundThe role of DNA methylation (DNAm) in the carcinogenesis of colorectal cancer (CRC) diagnosed MethodsGenome-wide DNAm profiling using the Infinium HM450K on 97 EOCRC tumour and 54 normal colonic mucosa samples was compared with: 1) intermediate-onset CRC (IOCRC; diagnosed between 50-70 years; 343 tumour and 35 normal); and 2) late-onset CRC (LOCRC; >70 years; 318 tumour and 40 normal). CpGs associated with age-related methylation drift were identified using a public dataset of 231 normal mucosa samples from people without CRC. DNAm-age was estimated using epiTOC2.ResultsCommon to all three age-of-onset groups, 88,385 (20% of all CpGs) CpGs were differentially methylated between tumour and normal mucosa. We identified 234 differentially methylated genes that were unique to the EOCRC group. In normal mucosa from people without CRC, we identified 28,154 CpGs that undergo ageing-related DNAm drift and of those, 65% were aberrantly methylated in EOCRC tumours. Based on the mitotic-based DNAm clock epiTOC2, we identified age acceleration in normal mucosa of people with EOCRC compared with normal mucosa from the IOCRC, LOCRC groups (p=3.7×10−16) and young people without CRC (p=5.8×10−6).ConclusionEOCRC acquires unique DNAm alterations at 234 loci. CpGs associated with ageing-associated drift were widely affected in EOCRC without needing the decades-long accrual of DNAm drift as commonly seen in intermediate- and late-onset CRCs. We found accelerated ageing in normal mucosa from people with EOCRC, as evidenced by a faster stem-cell division rate, potentially contributing to EOCRC carcinogenesis.

BackgroundSelf-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.MethodsConditional logistic regression was used to assess associations between blood-based methylation and UCC risk using two matched case-control samples,N=404 pairs from the Melbourne Collaborative Cohort Study (MCCS) andN=440 pairs from the Women’s Health Initiative (WHI) cohort, respectively. Results were pooled using fixed-effects meta-analysis. We developed methylation-based predictors of UCC and evaluated their prediction accuracy on two replication datasets using the area under the curve (AUC).ResultsThe meta-analysis identified associations (P−5) for 29 of 1,061 smoking-associated methylation sites, but these were substantially attenuated after adjustment for self-reported smoking. Nominally significant associations (PN=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 dataset in WHI (N=440, OR=1.09, 95%CI=0.91-1.30).ConclusionsCombination of smoking-associated methylation marks may provide some improvement to UCC risk prediction. Our findings need further evaluation using larger datasets.ImpactDNA 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.

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=7.7×10−4) and colorectal (HR=1.52, P=1.8×10−4) cancer, respectively, with significant age-by-sex interaction. Our results may provide markers for cancer early detection and prognosis prediction.Simple SummaryAgeing 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.

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=3,123). 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 standard deviation 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.

While gene panel sequencing is becoming widely used for cancer risk prediction, its clinical utility with respect to predicting aggressive prostate cancer (PrCa) is limited by our current understanding of the genetic risk factors associated with predisposition to this potentially lethal disease phenotype. This study included 837 men diagnosed with aggressive PrCa and 7261 controls (unaffected men and men who did not meet criteria for aggressive PrCa). Rare germline pathogenic variants (including likely pathogenic variants) were identified by targeted sequencing of 26 known or putative cancer predisposition genes. We found that 85 (10%) men with aggressive PrCa and 265 (4%) controls carried a pathogenic variant (p &lt, 0.0001). Aggressive PrCa odds ratios (ORs) were estimated using unconditional logistic regression. Increased risk of aggressive PrCa (OR (95% confidence interval)) was identified for pathogenic variants in BRCA2 (5.8 (2.7–12.4)), BRCA1 (5.5 (1.8–16.6)), and ATM (3.8 (1.6–9.1)). Our study provides further evidence that rare germline pathogenic variants in these genes are associated with increased risk of this aggressive, clinically relevant subset of PrCa. These rare genetic variants could be incorporated into risk prediction models to improve their precision to identify men at highest risk of aggressive prostate cancer and be used to identify men with newly diagnosed prostate cancer who require urgent treatment.

Background:DNA methylation may be one of the mechanisms by which alcohol consumption is associated with the risk of disease. We conducted a large-scale, cross-sectional, genome-wide DNA methylation association study of alcohol consumption and a longitudinal analysis of repeated measurements taken several years apart.Methods:Using the Illumina Infinium HumanMethylation450 BeadChip, DNA methylation measures were determined using baseline peripheral blood samples from 5,606 adult Melbourne Collaborative Cohort Study (MCCS) participants. For a subset of 1,088 of them, these measures were repeated using blood samples collected at follow-up, a median of 11 years later. Associations between alcohol intake and blood DNA methylation were assessed using linear mixed-effects regression models adjusted for batch effects and potential confounders. Independent data from the LOLIPOP (N=4,042) and KORA (N=1,662) cohorts were used to replicate associations discovered in the MCCS.Results:Cross-sectional analyses identified 1,414 CpGs associated with alcohol intake at P-7, 1,243 of which had not been reported previously. Of these 1,243 novel associations, 1,078 were replicated (PConclusion:Our study indicates that, for middle-aged and older adults, alcohol intake is associated with widespread changes in DNA methylation across the genome. Longitudinal analyses showed that the methylation status of alcohol-associated CpGs may change with changes in alcohol consumption.

BackgroundWe previously investigated the association between 5 “first-generation” measures of epigenetic aging and cancer risk in the Melbourne Collaborative Cohort Study. This study assessed cancer risk associations for 3 recently developed methylation-based biomarkers of aging: PhenoAge, GrimAge, and predicted telomere length.MethodsWe estimated rate ratios (RRs) for the association between these 3 age-adjusted measures and risk of colorectal (N = 813), gastric (N = 165), kidney (N = 139), lung (N = 327), mature B-cell (N = 423), prostate (N = 846), and urothelial (N = 404) cancer using conditional logistic regression models. We also assessed associations by time since blood draw and by cancer subtype, and we investigated potential nonlinearity.ResultsWe observed relatively strong associations of age-adjusted PhenoAge with risk of colorectal, kidney, lung, mature B-cell, and urothelial cancers (RR per SD was approximately 1.2-1.3). Similar findings were obtained for age-adjusted GrimAge, but the association with lung cancer risk was much larger (RR per SD = 1.82, 95% confidence interval [CI] = 1.44 to 2.30), after adjustment for smoking status, pack-years, starting age, time since quitting, and other cancer risk factors. Most associations appeared linear, larger than for the first-generation measures, and were virtually unchanged after adjustment for a large set of sociodemographic, lifestyle, and anthropometric variables. For cancer overall, the comprehensively adjusted rate ratio per SD was 1.13 (95% CI = 1.07 to 1.19) for PhenoAge and 1.12 (95% CI = 1.05 to 1.20) for GrimAge and appeared larger within 5 years of blood draw (RR = 1.29, 95% CI = 1.15 to 1.44 and 1.19, 95% CI = 1.06 to 1.33, respectively).ConclusionsThe methylation-based measures PhenoAge and GrimAge may provide insights into the relationship between biological aging and cancer and be useful to predict cancer risk, particularly for lung cancer.

Background Questions remain about the effect on mortality of physical activity and sedentary behaviour over time. We summarized the evidence from studies that assessed exposure from multiple time points and critiqued the analytic approaches used. Methods A search was performed on MEDLINE, Embase, Emcare, Scopus and Web of Science up to January 2021 for studies of repeatedly assessed physical activity or sedentary behaviour in relation to all-cause or cause-specific mortality. Relative risks from individual studies were extracted. Each study was assessed for risk of bias from multiple domains. Results We identified 64 eligible studies (57 on physical activity, 6 on sedentary behaviour, 1 on both). Cox regression with a time-fixed exposure history (n = 45) or time-varying covariates (n = 13) were the most frequently used methods. Only four studies used g-methods, which are designed to adjust for time-varying confounding. Risk of bias arose primarily from inadequate adjustment for time-varying confounders, participant selection, exposure classification and changes from measured exposure. Despite heterogeneity in methods, most studies found that being consistently or increasingly active over adulthood was associated with lower all-cause and cardiovascular-disease mortality compared with being always inactive. Few studies examined physical-activity changes and cancer mortality or effects of sedentary-behaviour changes on mortality outcomes. Conclusions Accumulating more evidence using longitudinal data while addressing the methodological challenges would provide greater insight into the health effects of initiating or maintaining a more active and less sedentary lifestyle.

BackgroundPrenatal exposure to maternal smoking is detrimental to child health but its association with risk of cancer has seldom been investigated. Maternal smoking induces widespread and long-lasting DNA methylation changes, which we study here for association with risk of cancer in adulthood.MethodsEight prospective case–control studies nested within the Melbourne Collaborative Cohort Study were used to assess associations between maternal-smoking-associated methylation marks in blood and risk of several cancers: breast (n = 406 cases), colorectal (n = 814), gastric (n = 166), kidney (n = 139), lung (n = 327), prostate (n = 847) and urothelial (n = 404) cancer and B-cell lymphoma (n = 426). We used conditional logistic regression models to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for associations between cancer and five methylation scores calculated as weighted averages for 568, 19, 15, 28 and 17 CpG sites. Models were adjusted for confounders, including personal smoking history (smoking status, pack-years, age at starting and quitting) and methylation scores for personal smoking.ResultsAll methylation scores for maternal smoking were strongly positively associated with risk of urothelial cancer. Risk estimates were only slightly attenuated after adjustment for smoking history, other potential confounders and methylation scores for personal smoking. Potential negative associations were observed with risk of lung cancer and B-cell lymphoma. No associations were observed for other cancers.ConclusionsWe found that methylation marks of prenatal exposure to maternal smoking are associated with increased risk of urothelial cancer. Our study demonstrates the potential for using DNA methylation to investigate the impact of early-life, unmeasured exposures on later-life cancer risk.

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.

BackgroundMammograms 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).MethodsWe 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.ResultsFor 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.ConclusionsOur 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.

DNA methylation in peripheral blood is a potential biomarker of gastric cancer risk which could be used for early detection. We conducted a prospective case–control study nested within the Melbourne Collaborative Cohort Study. Genomic DNA was prepared from blood samples collected a median of 12 years before diagnosis for cases (N = 168). Controls (N = 163) were matched to cases on sex, year of birth, country of birth, and blood sample type using incidence density sampling. Genome-wide DNA methylation was measured using the Infinium HumanMethylation450K Beadchip. Global measures of DNA methylation were defined as the median methylation M value, calculated for each of 13 CpG subsets representing genomic function, mean methylation and location, and reliability of measurement. Conditional logistic regression was conducted to assess associations between these global measures of methylation and gastric cancer risk, adjusting for Helicobacter pylori and other potential confounders. We tested nonlinear associations using quintiles of the global measure distribution. A genome-wide association study of DNA methylation and gastric cancer risk was also conducted (N = 484,989 CpGs) using conditional logistic regression, adjusting for potential confounders. Differentially methylated regions (DMR) were investigated using the R package DMRcate. We found no evidence of associations with gastric cancer risk for individual CpGs or DMRs (P > 7.6 × 10−6). No evidence of association was observed with global measures of methylation (OR 1.07 per SD of overall median methylation; 95% confidence interval, 0.80–1.44; P = 0.65). We found no evidence that blood DNA methylation is prospectively associated with gastric cancer risk. Prevention Relevance: We studied DNA methylation in blood to try and predict who was at risk of gastric cancer before symptoms developed, by which stage survival is poor. We did not find any such markers, but the importance of early diagnosis in gastric cancer remains, and the search for markers continues.

B-group vitamins, as components of the one carbon metabolism pathway, are involved in DNA synthesis, repair and methylation. Our aim was to investigate associations between circulating plasma levels of B vitamins and urothelial cell carcinoma (UCC). We conducted a nested case-control study of UCC within the Melbourne Collaborative Cohort Study. B vitamins were measured in pre-diagnostic plasma samples. Conditional logistic regression was used to estimate odds ratios (OR) for UCC risk associated with circulating B vitamins in 363 matched cases and controls. In a case-only analysis (N = 390), hazard ratios (HR) for overall survival associated with plasma B vitamins were estimated using Cox regression. There were no strong associations between UCC risk and pre-diagnostic levels of plasma B vitamins. No heterogeneity in UCC risk was observed by subtype (invasive or superficial), sex, smoking status or alcohol intake. There was no heterogeneity by country of birth for most B vitamins, except for folate (p-homogeneity = 0.03). In UCC cases, there were no strong associations between plasma B vitamins and overall survival. We found no associations between pre-diagnostic plasma concentrations of B-group vitamins and UCC risk or survival.

Several studies have reported DNA methylation in blood to be associated with body mass index (BMI), but few have investigated causal aspects of the association. We used a twin family design to assess this association at two life points and applied a novel analytical approach to appraise the evidence for causality. The methylation profile of DNA from peripheral blood was measured for 479 Australian women from 130 twin families. Linear regression was used to estimate the associations of DNA methylation at ~410,000 cytosine-guanine dinucleotides (CpGs), and of the average DNA methylation at ~20,000 genes, with current BMI, BMI at age 18–21 years, and the change between the two (BMI change). A novel regression-based methodology for twins, Inference about Causation through Examination of Familial Confounding (ICE FALCON), was used to assess causation. At a 5% false discovery rate, nine, six and 12 CpGs at 24 loci were associated with current BMI, BMI at age 18–21 years and BMI change, respectively. The average DNA methylation of the BHLHE40 and SOCS3 loci was associated with current BMI, and of the PHGDH locus with BMI change. From the ICE FALCON analyses with BMI as the predictor and DNA methylation as the outcome, a woman’s DNA methylation level was associated with her co-twin’s BMI, and the association disappeared after conditioning on her own BMI, consistent with BMI causing DNA methylation. To the contrary, using DNA methylation as the predictor and BMI as the outcome, a woman’s BMI was not associated with her co-twin’s DNA methylation level, consistent with DNA methylation not causing BMI. For middle-aged women, peripheral blood DNA methylation at several genomic locations is associated with current BMI, BMI at age 18–21 years and BMI change. Our study suggests that BMI has a causal effect on peripheral blood DNA methylation.

Nutrients involved in one-carbon metabolism may play a role in carcinogenesis through DNA replication, repair and methylation mechanisms. Most studies on urothelial cell carcinoma (UCC) have focused on folate. We sought to examine the association between B-group vitamins and methionine intake and UCC risk, overall and by subtype, and to test whether these associations are different for population subgroups whose nutritional status may be compromised. We followed participants in the Melbourne Collaborative Cohort Study (N = 41,513) for over 20 years and observed 500 UCC cases (89% originating in the bladder; superficial: 279, invasive: 221). Energy-adjusted dietary intakes of B vitamins (B1, B2, B3, B5, B6, B8, B9 and B12) and methionine were estimated from a 121-item food frequency questionnaire administered at baseline (1990-1994), using the residuals method. We used Cox regression models to compute hazard ratios (HRs) of UCC risk per standard deviation (SD) of log-transformed nutrient intakes and 95% confidence intervals, adjusted for potential confounders. We investigated associations by tumor subtype, and tested interactions with sex, country of birth, smoking and alcohol drinking. The risk of UCC appeared not to be associated with intake of B-group vitamins or methionine, and findings were consistent across tumor subtypes and across demographic and lifestyle characteristics of the participants. A potential interaction between vitamin B1 and alcohol drinking was observed (all participants: HR per 1 SD = 0.99 (0.91-1.09), never drinkers: HR = 0.81 (0.69-0.97), p-interaction = 0.02), which needs to be confirmed by other studies. Our findings do not indicate that dietary intake of nutrients involved in one-carbon metabolism are associated with UCC risk.

The association between aging and cancer is complex. Recent studies have developed measures of biological aging based on DNA methylation and called them "age acceleration." We aimed to assess the associations of age acceleration with risk of and survival from seven common cancers. Seven case-control studies of DNA methylation and colorectal, gastric, kidney, lung, prostate and urothelial cancer and B-cell lymphoma nested in the Melbourne Collaborative Cohort Study were conducted. Cancer cases, vital status and cause of death were ascertained through linkage with cancer and death registries. Conditional logistic regression and Cox models were used to estimate odds ratios (OR) and hazard ratios (HR) and 95% confidence intervals (CI) for associations of five age acceleration measures derived from the Human Methylation 450 K Beadchip assay with cancer risk (N = 3,216 cases) and survival (N = 1,726 deaths), respectively. Epigenetic aging was associated with increased cancer risk, ranging from 4% to 9% per five-year age acceleration for the 5 measures considered. Heterogeneity by study was observed, with stronger associations for risk of kidney cancer and B-cell lymphoma. An associated increased risk of death following cancer diagnosis ranged from 2% to 6% per five-year age acceleration, with no evidence of heterogeneity by cancer site. Cancer risk and mortality were increased by 15-30% for the fourth versus first quartile of age acceleration. DNA methylation-based measures of biological aging are associated with increased cancer risk and shorter cancer survival, independently of major health risk factors.

Objective Blood pressure (BP) and breast cancer may share a common pathophysiologic pathway involving chronic inflammation, hormone synthesis and metabolism. Previous studies investigating the association between BP and breast cancer measured BP at a single time point and did not examine associations by breast cancer molecular subtypes. Methods We used data from 22 833 female participants in the Melbourne Collaborative Cohort Study. BP was objectively measured at baseline (1990-1994) and a follow-up visit (2003-2007). Cox regression was used to estimate hazard ratios for baseline BP and temporal changes in BP in relation to risk of breast cancer, overall and by molecular subtypes. Results We did not observe any associations between BP measured at baseline and breast cancer risk overall (per 5 mmHg SBP, hazard ratio = 1.00, 95% confidence interval: 0.99-1.02), nor by subtype (per 5 mmHg SBP: estrogen-receptor-negative: hazard ratio = 0.99, 0.96-1.03, progesterone-receptor-negative: hazard ratio = 1.01, 0.99-1.04, human epidermal growth factor receptor 2 negative: hazard ratio = 1.00, 0.98-1.01). Temporal changes in BP were not associated with risk of breast cancer (per 5 mmHg change in SBP, hazard ratio = 1.00, 0.97-1.03). Increased DBP over time was associated with higher risk of triple-negative breast cancer (P = 0.04), based on a small number of cases (N = 41). Conclusion Our study supports previous findings of no association between BP and breast cancer. Similar conclusions were reached when assessing BP over time and when examining specific tumor subtypes.

DNA methylation-based biological age (DNAm age), as well as genome-wide average DNA methylation, have been reported to predict breast cancer risk. We aimed to investigate the associations between these DNA methylation-based risk factors and 18 conventional breast cancer risk factors for disease-free women. A sample of 479 individuals from the Australian Mammographic Density Twins and Sisters was used for discovery, a sample of 3354 individuals from the Melbourne Collaborative Cohort Study was used for replication, and meta-analyses pooling results from the two studies were conducted. DNAm age based on three epigenetic clocks (Hannum, Horvath and Levine) and genome-wide average DNA methylation were calculated using the HumanMethylation 450 K BeadChip assay data. The DNAm age measures were positively associated with body mass index (BMI), smoking, alcohol drinking and age at menarche (all nominal P P

Aims We conducted a genome-wide association study of blood DNA methylation and smoking, attempted replication of previously discovered associations, and assessed the reversibility of smoking-associated methylation changes. Methods DNA methylation was measured in baseline peripheral blood samples for 5,044 participants in the Melbourne Collaborative Cohort Study using the HumanMethylation450 BeadChip assay. For 1,032 participants, these measures were repeated using blood samples collected at follow-up, a median of 11 years later. A cross-sectional analysis of the association between smoking and DNA methylation and a longitudinal analysis of changes in smoking status and changes in DNA methylation were conducted. We used our cross-sectional analysis to attempt replication of previously reported associations for current (N=3,327) and former (N=172) smoking. A comprehensive smoking index accounting for and biological half-life of smoking compounds bioactivity was constructed to assess the reversibility of smoking-associated methylation changes. Results We identified 4,496 cross-sectional associations between smoking and blood DNA methylation at P −7 , including 3,296 that had not been reported before. We replicated the majority (90%) of previously reported associations for current and former smokers. In our data, we observed for former smokers a substantial degree of return to the methylation levels of never smokers, compared with current smokers (median: 74%, IQR=63% to 86%). Consistent with this, analyses using the comprehensive smoking index indicated a wide-ranging rate of reversibility of smoking-associated methylation changes. Longitudinal analyses identified 368 sites at which methylation changed upon smoking cessation. Conclusion Our study provides evidence of many novel associations between smoking and DNA methylation at CpGs across the genome and replicates the vast majority of previously reported associations. The reversibility of smoking-associated methylation was quantified by using a comprehensive smoking index accounting for both the bioactivity of smoking and several aspects of smoking history that are relevant to DNA methylation, and using longitudinal methylation measures.

Background It is well established that estrogens and other hormonal factors influence breast cancer susceptibility. We hypothesized that a woman’s total lifetime estrogen exposure accumulates changes in DNA methylation, detectable in the blood, which could be used in risk assessment for breast cancer. Methods An estimated lifetime estrogen exposure (ELEE) model was defined using epidemiological data from EPIC-Italy (n = 31,864). An epigenome-wide association study (EWAS) of ELEE was performed using existing Illumina HumanMethylation450K Beadchip (HM450K) methylation data obtained from EPIC-Italy blood DNA samples (n = 216). A methylation index (MI) of ELEE based on 31 CpG sites was developed using HM450K data from EPIC-Italy and the Generations Study and evaluated for association with breast cancer risk in an independent dataset from the Generations Study (n = 440 incident breast cancer cases matched to 440 healthy controls) using targeted bisulfite sequencing. Lastly, a meta-analysis was conducted including three additional cohorts, consisting of 1187 case-control pairs. Results We observed an estimated 5% increase in breast cancer risk per 1-year longer ELEE (OR = 1.05, 95% CI 1.04–1.07, P = 3 × 10−12) in EPIC-Italy. The EWAS identified 694 CpG sites associated with ELEE (FDR Q

Simple Summary Ageing is the strongest cancer risk factor, and men and women exhibit different 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 contributes 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 2754 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 for these CpGs using GS summary data were 94%, 86% and 91%, respectively. Significant associations for cancer risk and survival were identified at some individual age-related CpGs. Opposite to previous findings using epigenetic clocks, there was a strong negative trend in the association between epigenetic drift and risk of colorectal cancer. Methylation at two CpGs overlapping TMEM49 and ARX genes was associated with survival of overall (HR = 0.91, p = 7.7 × 10−4) and colorectal (HR = 1.52, p = 1.8 × 10−4) cancer, respectively, with significant age-by-sex interaction. Our results may provide markers for cancer early detection and prognosis prediction.

Studies investigating the association of food and nutrient consumption with the risk of urothelial cell carcinoma (UCC) have produced mixed results. We used three common dietary scores, the Mediterranean Diet Score (MDS), the Alternate Healthy Eating Index 2010 (AHEI-2010) and the Dietary Inflammatory Index (DII) to assess the evidence of an association between diet and the risk of UCC. Over a median follow-up time of 21.3 years, 379 incident UCC cases were diagnosed. Dietary scores were calculated using data from a 121-item food frequency questionnaire administered at baseline. We used Cox models to compute hazard ratios (HR) for the association between dietary scores (per one standard deviation) and UCC risk. In order to reflect overall adherence to a healthy diet, a metascore was constructed by summing the quintiles of each of the three scores. None of the dietary scores was associated with the risk of UCC overall. A healthier diet was found to be inversely associated with the risk of invasive (MDS: HR = 0.86, 95% CI: 0.74-1.00, metascore: HR = 0.84, 95% CI: 0.71-0.98), but not superficial disease (heterogeneity between subtypes p = 0.04 and p = 0.03, respectively). Results were consistent but weaker for the DII and the AHEI-2010. We found some evidence of effect modification by smoking, in particular for the metascore (Current: HR = 0.77, 95% CI: 0.58-1.01, Former: HR = 0.77, 95% CI: 0.64-0.92, Never: HR = 1.01, 95% CI: 0.81-1.26, p for heterogeneity = 0.05). A healthy diet may be protective against the risk of invasive, but not superficial, UCC. Promoting healthy dietary habits may help lower the risk of invasive UCC, especially for current and former smokers.

Age- and body mass index (BMI)-adjusted mammographie density is one the strongest breast cancer risk factors. DNA methylation is a molecular mechanism that could underlie interindividual variation in mammographic density. We aimed to investigate the association between breast cancer risk-predicting mammographic density measures and blood DNA methylation. For 436 women from the Australian Mammographic Density Twins and Sisters Study and 591 women from the Melbourne Collaborative Cohort Study, mammographic density (dense area, non-dense area and percentage dense area) defined by the conventional brightness threshold was measured using the CUMULUS software, and peripheral blood DNA methylation was measured using the HumanMethylation450 (HM450) BeadChip assay. Associations between DNA methylation at >400,000 sites and mammographic density measures adjusted for age and BMI were assessed within each cohort and pooled using fixed-effect meta-analysis. Associations with methylation at genetic loci known to be associated with mammographic density were also examined. We found no genome-wide significant(P−7)association for any mammographic density measure from the meta-analysis, or from the cohort-specific analyses. None of the 299 methylation sites located at genetic loci associated with mammographic density was associated with any mammographic density measure after adjusting for multiple testing (all P>0.05/299 = 1.7 × 10−4). In summary, our study did not detect associations between blood DNA methylation, as measured by the HM450 assay, and conventional mammographic density measures that predict breast cancer risk.

Introduction Physical activity may affect health via DNA methylation. The epigenetic influences of sedentary behaviors such as television viewing are unknown. We performed a genomewide study of DNA methylation in peripheral blood in relation to physical activity and television viewing time.Methods DNA methylation was measured using the Illumina Infinium HumanMethylation450K BeadChip array in blood samples collected at baseline (N = 5513) and follow-up (N = 1249) from participants in the Melbourne Collaborative Cohort Study. At baseline, times per week of leisure-time physical activity were self-reported. At follow-up, the International Physical Activity Questionnaire was used to assess MET-hours per week of total and leisure-time physical activity and hours per day of television viewing time. Linear mixed models were used to assess associations between physical activity and television viewing measures and DNA methylation at individual CpG sites, adjusted for potential confounders and batch effects.Results At follow-up, total physical activity was associated with DNA methylation at cg10266336 (P = 6.0 x 10(-9)), annotated to the SAA2 gene. Weaker evidence of associations (P Conclusion Physical activity and television viewing may be associated with blood DNA methylation, a potential pathway to chronic disease development. Further research using accelerometer data and larger sample sizes is warranted.

Breast cancers arising in women carrying a germline mutation in BRCA1 are typically high-grade, early-onset and have distinct morphological features (BRCA1-like). However, the majority of early-onset breast cancers of this morphological type are not associated with germline BRCA1 mutations or constitutional BRCA1 promoter methylation. We aimed to assess DNA methylation across the genome for associations with the "BRCA1-like" morphology. Genome-wide methylation in blood-derived DNA was measured using the Infinium HumanMethylation450K BeadChip assay for women under the age of 40 years participating in the Australian Breast Cancer Family Study (ABCFS) diagnosed with: i) BRCA1-like breast cancer (n = 30); and ii) breast cancer without BRCA1-like morphological features (non BRCA1-like; n = 30), and age-matched unaffected women (controls; n = 30). Corresponding tumour-derived DNA from 43 of the affected women was also assessed. Methylation of blood-derived DNA was found to be elevated across 17 consecutive marks in the BRCA1 promoter region and decreased at several other genomic regions (including TWIST2 and CTBP1) for 7 women (23%) diagnosed with BRCA1-like breast cancer compared with women in the other groups. Corresponding tumour-derived DNA available from 5 of these 7 women had elevated methylation within the BRCA1 and SPHK2 promoter region and decreased methylation within the ADAP1, IGF2BP3 and SPATA13 promoter region when compared with the other breast tumours. These methylation marks could be biomarkers of risk for BRCA1-like breast cancer, and could be responsible in part for their distinctive morphological features and biology. As such, they may assist with prevention and targeted therapies for this cancer subtype.

Background DNA methylation can mimic the effects of germline mutations in cancer predisposition genes. Recently, we identified twenty-four heritable methylation marks associated with breast cancer risk. As breast and prostate cancer share genetic risk factors, including rare, high-risk mutations (eg, in BRCA2), we hypothesized that some of these heritable methylation marks might also be associated with the risk of prostate cancer. Methods We studied 869 incident prostate cancers (430 aggressive and 439 non-aggressive) and 869 matched controls nested within a prospective cohort study. DNA methylation was measured in pre-diagnostic blood samples using the Illumina Infinium HM450K BeadChip. Conditional logistic regression models, adjusted for prostate cancer risk factors and blood cell composition, were used to estimate odds ratios and 95% confidence intervals for the association between the 24 methylation marks and the risk of prostate cancer. Results Five methylation marks within the VTRNA2-1 promoter region (cg06536614, cg00124993, cg26328633, cg25340688, and cg26896946), and one in the body of CLGN (cg22901919) were associated with the risk of prostate cancer. In stratified analyses, the five VTRNA2-1 marks were associated with the risk of aggressive prostate cancer. Conclusions This work highlights a potentially important new area of investigation for prostate cancer susceptibility and adds to our knowledge about shared risk factors for breast and prostate cancer.

There is increasing evidence of a relationship between blood DNA methylation and body mass index (BMI). We aimed to assess associations of BMI with individual methylation measures (CpGs) through a cross-sectional genome-wide DNA methylation association study and a longitudinal analysis of repeated measurements over time. Using the Illumina Infinium HumanMethylation450 BeadChip, DNA methylation measures were determined in baseline peripheral blood samples from 5361 adults recruited to the Melbourne Collaborative Cohort Study (MCCS) and selected for nested case–control studies, 2586 because they were subsequently diagnosed with cancer (cases) and 2775 as controls. For a subset of 1088 controls, these measures were repeated using blood samples collected at wave 2 follow-up, a median of 11 years later; weight was measured at both time points. Associations between BMI and blood DNA methylation were assessed using linear mixed-effects regression models adjusted for batch effects and potential confounders. These were applied to cases and controls separately, with results combined through fixed-effects meta-analysis. Cross-sectional analysis identified 310 CpGs associated with BMI with P

OBJECTIVE: This study aimed to assess the long-term use of health care services in women with abnormal cytology results compared to women with normal cytology results.METHODS: We did a nationwide population-based study, using women aged 23 to 59years participating in the national organized cervical cancer screening program. We included a study population of 40,153 women with abnormal cytology (exposed) and 752,627 women with normal cytology (non-exposed). We retrieved data from the Danish Civil Registration System, the Danish Pathology Data Bank, the National Health Service, the National Patient and the National Prescription Register. We calculated the frequencies of contacts to general practitioner (GP), to private psychiatrist and/or psychologist, admissions to hospitals and use of prescription drugs. These frequencies were calculated separately in the 5-year period "before" the cytology result and for the 5-year period "after" the result.RESULTS: During the "before" period exposed women had more contacts to GPs, more contacts to psychologists/psychiatrist, and more hospital admissions than non-exposed women. In both exposed and non-exposed women, health care use increased from the "before" to the "after" period. This increase was significantly higher for exposed than non-exposed women regarding contacts to GP, admissions to hospitals, and drug use.CONCLUSION: Women with abnormal cytology results constitute a selected group with a higher health care use than other women even before they have the abnormal cytology. This difference is further enhanced after the abnormal cytology result.

DNA methylation changes in peripheral blood DNA have been shown to be associated with solid tumors. We sought to identify methylation alterations in whole blood DNA that are associated with breast cancer (BC). Epigenome-wide DNA methylation profiling on blood DNA from BC cases and healthy controls was performed by applying Infinium HumanMethylation450K BeadChips. Promising CpG sites were selected and validated in three independent larger sample cohorts via MassARRAY EpiTyper assays. CpG sites located in three genes (cg06418238 in RPTOR, cg00736299 in MGRN1 and cg27466532 in RAPSN), which showed significant hypomethylation in BC patients compared to healthy controls in the discovery cohort (p < 1.00 × 10−6) were selected and successfully validated in three independent cohorts (validation I, n =211; validation II, n=378; validation III, n=520). The observed methylation differences are likely not cell-type specific, as the differences were only seen in whole blood, but not in specific sub cell-types of leucocytes. Moreover, we observed in quartile analysis that women in the lower methylation quartiles of these three loci had higher ORs than women in the higher quartiles. The combined AUC of three loci was 0.79 (95%CI 0.73-0.85) in validation cohort I, and was 0.60 (95%CI 0.54-0.66) and 0.62 (95%CI 0.57-0.67) in validation cohort II and III, respectively. Our study suggests that hypomethylation of CpG sites in RPTOR, MGRN1 and RAPSN in blood is associated with BC and might serve as blood-based marker supplements for BC if these could be verified in prospective studies.

BackgroundSeveral studies have reported DNA methylation in blood to be associated with body mass index (BMI), but only a few have investigated causal aspects of the association. We used a twin family design to assess this association at two life points and applied a novel analytical approach to investigate the evidence for causality.MethodsThe methylation profile of DNA from peripheral blood was measured for 479 Australian women (mean age 56 years) from 130 twin families. Linear regression was used to estimate the associations of methylation at ~410 000 cytosine-guanine dinucleotides (CpG), and of the average methylation at ~20 000 genes, with current BMI, BMI at age 18-21 years, and the change between the two (BMI change). A novel regression-based methodology for twins, Inference about Causation through Examination of Familial Confounding (ICE FALCON), was used to assess causation.ResultsAt 5% false discovery rate, nine, six and 12 CpGs at 24 loci were associated with current BMI, BMI at age 18-21 years and BMI change, respectively. The average methylation of BHLHE40 and SOCS3 loci was associated with current BMI, and of PHGDH locus was associated with BMI change. From the ICE FALCON analyses with BMI as the predictor and methylation as the outcome, a woman’s methylation level was associated with her co-twin’s BMI, and the association disappeared conditioning on her own BMI, consistent with BMI causing methylation. To the contrary, using methylation as the predictor and BMI as the outcome, a woman’s BMI was not associated with her co-twin’s methylation level, consistent with methylation not causing BMI.ConclusionFor middle-aged women, peripheral blood DNA methylation at several genomic locations is associated with current BMI, BMI at age 18-21 years and BMI change. Our study suggests that BMI has a causal effect on peripheral blood DNA methylation.

Background and Aims Dietary patterns are associated with risk of cardiovascular disease (CVD). We aimed to examine associations of the Dietary Inflammatory Index (DII) and the Mediterranean Diet Score (MDS) with total, cardiovascular disease (CVD) and coronary heart disease (CHD) mortality in the Melbourne Collaborative Cohort Study; and compare the strengths of the associations. Methods and Results In our prospective cohort study of 41,513 men and women aged 40–69 years, a food frequency questionnaire was completed at baseline and mortality data were obtained via linkage with local and national registries over an average of 19 years follow up. At baseline, questionnaires were completed and physical measures and blood samples taken. Cox proportional hazards models, adjusting for age, alcohol consumption, sex, region of origin, personal history of CVD or diabetes and family history of CVD, were used to assess associations between dietary scores and mortality. More Mediterranean or less inflammatory diets were associated with lower total, CVD and CHD mortality. The hazard ratio for total mortality comparing the highest and lowest quintiles was 1.16 (95%CI: 1.08–1.24) for DII; and 0.86 (95%CI: 0.80–0.93) comparing the highest and lowest three categories of MDS. Using the Bayesian information criterion, there was no evidence that the DII score was more strongly associated with total and CVD mortality than was the MDS. Conclusions The MDI and the DII show similar associations with total and cardiovascular mortality, consistent with the consensus that plant-based diets are beneficial for health.

ObjectiveMost studies investigating the association between resting heart rate (RHR) and mortality have focused on cardiovascular disease (CVD) mortality, and measured RHR at only one time point. We aimed to assess associations of RHR and changes in RHR over approximately a decade with overall and cause-specific mortality.MethodsWe used data from participants in the Melbourne Collaborative Cohort Study with RHR measures at baseline (1990–1994; n=41 386; 9846 deaths) and at follow-up (2003–2007; n=21 692; 2818 deaths). RHR measures were taken by trained staff, using Dinamap monitors. Cox models were used to estimate HR and 95% CI for the associations between RHR and mortality. Vital status and cause of death were ascertained until August 2015 and December 2013, respectively.ResultsAfter adjustment for confounders, including blood pressure and known medical conditions but not arrhythmias or atrial fibrillation, RHR was associated with a higher risk of death of similar magnitude for CVD (HR per 10 beats per minute (bpm)=1.11, 95% CI 1.07 to 1.16), cancer (HR=1.10, 95% CI 1.06 to 1.13) and other causes (HR=1.20, 95% CI 1.16 to 1.25). Higher mortality was observed for most cancer sites, including breast (HR=1.16, 95% CI 1.03 to 1.31), colorectal (HR=1.18, 95% CI 1.08 to 1.29), kidney (HR=1.27, 95% CI 1.03 to 1.57) and lung cancer (HR=1.19, 95% CI 1.10 to 1.29). Temporal increases in RHR were associated with higher mortality, particularly for individuals whose RHR increased by more than 15 bpm.ConclusionsRHR and changes in RHR over a decade are associated with mortality risk, including from causes other than CVD such as breast, colorectal or lung cancer. Monitoring of RHR may have utility in identifying individuals at higher mortality risk.

Severely immunosuppressed individuals have a strongly increased risk of cervical cancer. In patients with autoimmune diseases (AID), who have defects in their immune system and receive immunosuppressants, the risk of cervical cancer is less clear. We conducted a cohort study, using Danish nationwide population-based registers including information on AID diagnoses, immunosuppressant intake, cervical screening participation, and cervical cancer incidence. Standardized incidence ratios (SIR) were computed to compare the risk of cervical cancer in AID patients to that of the general population. Hazard ratios (HR) from time-dependent Cox models stratified by AID were used to explore the effect of the most frequently used immunosuppressants, taking into account potential dose-response relationships and lag times between drug exposure and cervical cancer development. Cervical screening coverage of patients with AIDs was compared to the general population. Among 341,758 patients with AIDs, the risk of cervical cancer was not higher than in the general population (SIR = 1.0, 95% CI: 0.9-1.1, based on 720 cases). The intake of immunosuppressants was generally not associated with the risk, apart from azathioprine. The crude HR comparing the period of exposure versus non-exposure to azathioprine was 1.4 (95% CI: 0.9-2.1). Furthermore, the risk was substantially increased in patients who received a high cumulative dose of azathioprine (HR = 2.2, 95% CI = 1.2-3.9), and appeared to be highest when considering that the immunosuppressant exposure would take 5 years to trigger cervical cancer. Patients with AIDs had similarly high screening rates as the general population. Although most patients with AIDs do not have an increased risk of cervical cancer, those taking substantial amounts of azathioprine might need more stringent cervical screening measures.

Cervical screening has been one of the most successful public health prevention programmes. For 50 years, cytology formed the basis for screening, and detected cervical intraepithelial lesions (CIN) were treated surgically to prevent progression to cancer. In a high-risk country as Denmark, screening decreased the incidence of cervical cancer from 34 to 11 per 100,000, age-standardized rate (World Standard Population). Screening is, however, also expensive; Denmark (population: 5.6 million) undertakes close to half a million tests per year, and has 6-8 CIN-treated women for each prevented cancer case. The discovery of human papillomavirus (HPV) as the cause of cervical cancer dramatically changed perspectives for disease control. Screening with HPV testing was launched around 1990, and preventive HPV vaccination was licensed in 2006. Long-term randomized controlled trials (RCT) demonstrated that HPV testing provides better protection against cervical cancer than cytology, but it requires extra repeated testing. HPV vaccination RCTs, furthermore, have proved that HPV vaccination protects against vaccine-type high-grade CIN in women vaccinated prior to sexual activity, but less so in women vaccinated later. The challenge now is therefore to find an algorithm for screening of a heterogeneous population including non-vaccinated women; women vaccinated prior to start of sexual activity; and women vaccinated later.