Genome-wide measures of DNA methylation in peripheral blood and the risk of urothelial cell carcinoma: a prospective nested case-control study

A prospective study of smoking-related white blood cell DNA methylation markers and risk of bladder cancer

Bladder cancer, a common neoplasm, is primarily caused by tobacco smoking. Epigenetic alterations including DNA methylation have the potential to be used as prospective markers of increased risk, particularly in at-risk populations such as smokers. We aimed to investigate the potential of smoking-related white blood cell (WBC) methylation markers to contribute to an increase in bladder cancer risk prediction over classical questionnaire-based smoking metrics (i.e., duration, intensity, packyears) in a nested case-control study within the prospective prostate, lung, colorectal, and ovarian (PLCO) Cancer Screening Trial and the alpha-tocopherol, beta-carotene cancer (ATBC) Prevention Study (789 cases; 849 controls). We identified 200 differentially methylated sites associated with smoking status and 28 significantly associated (after correction for multiple testing) with bladder cancer risk among 2670 previously reported smoking-related cytosine-phosphate-guanines sites (CpGs). Similar patterns were observed across cohorts. Receiver operating characteristic (ROC) analyses indicated that cg05575921 (AHHR), the strongest smoking-related association we identified for bladder cancer risk, alone yielded similar predictive performance (AUC: 0.60) than classical smoking metrics (AUC: 0.59-0.62). Best prediction was achieved by including the first principal component (PC1) from the 200 smoking-related CpGs alongside smoking metrics (AUC: 0.63-0.65). Further, PC1 remained significantly associated with elevated bladder cancer risk after adjusting for smoking metrics. These findings suggest DNA methylation profiles reflect aspects of tobacco smoke exposure in addition to those captured by smoking duration, intensity and packyears, and/or individual susceptibility relevant to bladder cancer etiology, warranting further investigation.

Relationship between Bladder Cancer, Nutritional Supply, and Treatment Strategies: A Comprehensive Review

Bladder cancer (BC) is the predominant neoplasm affecting the urinary system and ranks among the most widespread malignancies globally. The causes of bladder cancer include genetic factors; age; sex; and lifestyle factors, such as imbalanced nutrition, obesity, and metabolic disorders. The lack of proper nutrient intake leads to the development of bladder cancer because insufficient nutrients are consumed to prevent this disease. The purpose of this review was to analyze the nutrients closely linked to the onset and advancement of bladder cancer and to explore the relationship between dietary nutrients and bladder cancer. Particular emphasis was placed on nutrients that are frequently ingested in daily life, including sugar, fat, protein, and others. The focus of this research was to analyze how nutritional intake before and after surgery affects the recovery process of patients who have been diagnosed with bladder cancer. This article seeks to increase awareness among both society and the medical community about the significance of implementing appropriate dietary nutrition to reduce the chances of developing bladder cancer, enhance perioperative care for patients with bladder cancer, and aid in their recuperation.

Methylation scores for smoking, alcohol consumption and body mass index and risk of seven types of 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.

Does genetic predisposition modify the effect of lifestyle-related factors on DNA methylation?

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.

Repeatability of methylation measures using a QIAseq targeted methyl panel and comparison with the Illumina HumanMethylation450 assay

OBJECTIVE

In previous studies using Illumina Infinium methylation arrays, we have identified DNA methylation marks associated with cancer predisposition and progression. In the present study, we have sought to find appropriate technology to both technically validate our data and expand our understanding of DNA methylation in these genomic regions. Here, we aimed to assess the repeatability of methylation measures made using QIAseq targeted methyl panel and to compare them with those obtained from the Illumina HumanMethylation450 (HM450K) assay. We included in the analysis high molecular weight DNA extracted from whole blood (WB) and DNA extracted from formalin-fixed paraffin-embedded tissues (FFPE).

RESULTS

The repeatability of QIAseq-methylation measures was assessed at 40 CpGs, using the Intraclass Correlation Coefficient (ICC). The mean ICCs and 95% confidence intervals (CI) were 0.72 (0.62-0.81), 0.59 (0.47-0.71) and 0.80 (0.73-0.88) for WB, FFPE and both sample types combined, respectively. For technical replicates measured using QIAseq and HM450K, the mean ICCs (95% CI) were 0.53 (0.39-0.68), 0.43 (0.31-0.56) and 0.70 (0.59-0.80), respectively. Bland-Altman plots indicated good agreement between QIAseq and HM450K measurements. These results demonstrate that the QIAseq targeted methyl panel produces reliable and reproducible methylation measurements across the 40 CpGs that were examined.

Smoking Methylation Marks for Prediction of Urothelial Cancer Risk

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.

Methylation marks of prenatal exposure to maternal smoking and risk of cancer in adulthood

BACKGROUND

Prenatal 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.

METHODS

Eight 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.

RESULTS

All 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.

CONCLUSIONS

We 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.

Biological Aging Measures Based on Blood DNA Methylation and Risk of Cancer: A Prospective Study

Background

We 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.

Methods

We 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.

Results

We 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).

Conclusions

The 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.

Alcohol consumption is associated with widespread changes in blood DNA methylation: Analysis of cross-sectional and longitudinal data

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. Using the Illumina HumanMethylation450 BeadChip, DNA methylation was measured in blood samples from 5606 Melbourne Collaborative Cohort Study (MCCS) participants. For 1088 of them, these measures were repeated using blood samples collected a median of 11 years later. Associations between alcohol intake and blood DNA methylation were assessed using linear mixed-effects regression models. Independent data from the London Life Sciences Prospective Population (LOLIPOP) (N = 4042) and Cooperative Health Research in the Augsburg Region (KORA) (N = 1662) cohorts were used to replicate associations discovered in the MCCS. Cross-sectional analyses identified 1414 CpGs associated with alcohol intake at P < 10-7 , 1243 of which had not been reported previously. Of these novel associations, 1078 were replicated (P < .05) using LOLIPOP and KORA data. Using the MCCS data, we also replicated 403 of 518 previously reported associations. Interaction analyses suggested that associations were stronger for women, non-smokers, and participants genetically predisposed to consume less alcohol. Of the 1414 CpGs, 530 were differentially methylated (P < .05) in former compared with current drinkers. Longitudinal associations between the change in alcohol intake and the change in methylation were observed for 513 of the 1414 cross-sectional associations. Our study indicates that 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 alcohol consumption changes in adulthood.

DNA Methylation in Peripheral Blood and Risk of Gastric Cancer: A Prospective Nested Case-control Study

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.

A panel of DNA methylation signature from peripheral blood may predict colorectal cancer susceptibility

Background

Differential DNA methylation panel derived from peripheral blood could serve as biomarkers of CRC susceptibility. However, most of the previous studies utilized post-diagnostic blood DNA which may be markers of disease rather than susceptibility. In addition, only a few studies have evaluated the predictive potential of differential DNA methylation in CRC in a prospective cohort and on a genome-wide basis. The aim of this study was to identify a potential panel of DNA methylation biomarkers in peripheral blood that is associated with CRC risk and therefore serve as epigenetic biomarkers of disease susceptibility.

Methods

DNA methylation profile of a nested case-control study with 166 CRC and 424 healthy normal subjects were obtained from the Gene Expression Omnibus (GEO) database. The differentially methylated markers were identified by moderated t-statistics. The DNA methylation panel was constructed by stepwise logistic regression and the least absolute shrinkage and selection operator in the training dataset. A methylation risk score (MRS) model was constructed and the association between MRS and CRC risk assessed.

Results

We identified 48 differentially methylated CpGs sites, of which 33 were hypomethylated. Of these, sixteen-CpG based MRS that was associated with CRC risk (OR = 2.68, 95% CI: 2.13, 3.38, P <  0.0001) was constructed. This association is confirmed in the testing dataset (OR = 2.02, 95% CI: 1.48, 2.74, P <  0.0001) and persisted in both males and females, younger and older subjects, short and long time-to-diagnosis. The MRS also predicted CRC with AUC 0.82 (95% CI: 0.76, 0.88), indicating high accuracy.

Conclusions

Our study has identified a novel DNA methylation panel that is associated with CRC and could, if validated be useful for the prediction of CRC risk in the future.

Smoking and blood DNA methylation: an epigenome-wide association study and assessment of reversibility

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. DNA methylation was measured in baseline peripheral blood samples for 5,044 participants in the Melbourne Collaborative Cohort Study. 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 replicate previously reported associations for current (N = 3,327) and former (N = 172) smoking. A comprehensive smoking index accounting for the biological half-life of smoking compounds and several aspects of smoking history was constructed to assess the reversibility of smoking-induced methylation changes. This measure of lifetime exposure to smoking allowed us to detect more associations than comparing current with never smokers. We identified 4,496 cross-sectional associations at P < 10-7, including 3,296 annotated to 1,326 genes that were not previously implicated in smoking-associated DNA methylation changes at this significance threshold. We replicated the majority of previously reported associations (P < 10-7) 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 = 63-86%), corresponding to small values (median: 2.75, IQR = 1.5-5.25) for the half-life parameter of the comprehensive smoking index. Longitudinal analyses identified 368 sites at which methylation changed upon smoking cessation. Our study demonstrates the usefulness of the comprehensive smoking index to detect associations between smoking and DNA methylation at CpGs across the genome, replicates the vast majority of previously reported associations, and quantifies the reversibility of smoking-induced methylation changes.

One-carbon metabolism biomarkers and risk of urothelial cell carcinoma in the European prospective investigation into cancer and nutrition

Published associations between dietary folate and bladder cancer risk are inconsistent. Biomarkers may provide more accurate measures of nutrient status. This nested case-control analysis within the European Prospective Investigation into Cancer and Nutrition (EPIC) investigated associations between pre-diagnostic serum folate, homocysteine, vitamins B6 and B12 and the risk of urothelial cell carcinomas of the bladder (UCC). A total of 824 patients with newly diagnosed UCC were matched with 824 cohort members. Serum folate, homocysteine, and vitamins B6 and B12 were measured. Odds ratios (OR) and 95% confidence intervals (CI) for total, aggressive, and non-aggressive UCC were estimated using conditional logistic regression with adjustment for smoking status, smoking duration and intensity, and other potential confounders. Additionally, statistical interaction with smoking status was assessed. A halving in serum folate concentrations was moderately associated with risk of UCC (OR: 1.18; 95% CI: 0.98-1.43), in particular aggressive UCC (OR: 1.34; 95% CI: 1.02-1.75; p-heterogeneity = 0.19). Compared to never smokers in the highest quartile of folate concentrations, this association seemed only apparent among current smokers in the lowest quartile of folate concentrations (OR: 6.26; 95% CI: 3.62-10.81, p-interaction = 0.07). Dietary folate was not associated with aggressive UCC (OR: 1.26; 95% CI: 0.81-1.95; p-heterogeneity = 0.14). No association was observed between serum homocysteine, vitamins B6 and B12 and risk of UCC. This study suggests that lower serum folate concentrations are associated with increased UCC risk, in particular aggressive UCC. Residual confounding by smoking cannot be ruled out and these findings require confirmation in future studies with multiple measurements.

DNA methylation-based biological age, genome-wide average DNA methylation, and conventional breast cancer risk factors

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 < 0.05). Genome-wide average DNA methylation was negatively associated with smoking and number of live births, and positively associated with age at first live birth (all nominal P < 0.05). The association of DNAm age with BMI was also evident in within-twin-pair analyses that control for familial factors. This study suggests that some lifestyle and hormonal risk factors are associated with these DNA methylation-based breast cancer risk factors, and the observed associations are unlikely to be due to familial confounding but are likely causal. DNA methylation-based risk factors could interplay with conventional risk factors in modifying breast cancer risk.

Longitudinal study of leukocyte DNA methylation and biomarkers for cancer risk in older adults

Background

Changes in DNA methylation over the course of life may provide an indicator of risk for cancer. We explored longitudinal changes in CpG methylation from blood leukocytes, and likelihood of future cancer diagnosis.

Methods

Peripheral blood samples were obtained at baseline and at follow-up visit from 20 participants in the Health, Aging and Body Composition prospective cohort study. Genome-wide CpG methylation was assayed using the Illumina Infinium Human MethylationEPIC (HM850K) microarray.

Results

Global patterns in DNA methylation from CpG-based analyses showed extensive changes in cell composition over time in participants who developed cancer. By visit year 6, the proportion of CD8+ T-cells decreased (p-value = 0.02), while granulocytes cell levels increased (p-value = 0.04) among participants diagnosed with cancer compared to those who remained cancer-free (cancer-free vs. cancer-present: 0.03 ± 0.02 vs. 0.003 ± 0.005 for CD8+ T-cells; 0.52 ± 0.14 vs. 0.66 ± 0.09 for granulocytes). Epigenome-wide analysis identified three CpGs with suggestive p-values ≤10^− 5 for differential methylation between cancer-free and cancer-present groups, including a CpG located in MTA3, a gene linked with metastasis. At a lenient statistical threshold (p-value ≤3 × 10^− 5), the top 10 cancer-associated CpGs included a site near RPTOR that is involved in the mTOR pathway, and the candidate tumor suppressor genes REC8, KCNQ1, and ZSWIM5. However, only the CpG in RPTOR (cg08129331) was replicated in an independent data set. Analysis of within-individual change from baseline to Year 6 found significant correlations between the rates of change in methylation in RPTOR, REC8 and ZSWIM5, and time to cancer diagnosis.

Conclusion

The results show that changes in cellular composition explains much of the cross-sectional and longitudinal variation in CpG methylation. Additionally, differential methylation and longitudinal dynamics at specific CpGs could provide powerful indicators of cancer development and/or progression. In particular, we highlight CpG methylation in the RPTOR gene as a potential biomarker of cancer that awaits further validation.

Electronic supplementary material

The online version of this article (10.1186/s40364-019-0161-3) contains supplementary material, which is available to authorized users.

Blood DNA methylation and breast cancer risk: a meta-analysis of four prospective cohort studies

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 (< 50, ≥ 50), estrogen receptor (ER) status (+/-), and time since blood collection (< 5, 5-10, > 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.

Global DNA methylation of peripheral blood leukocytes from dogs bearing multicentric non-Hodgkin lymphomas and healthy dogs: A comparative study

Non-Hodgkin lymphomas are among the most common types of tumors in dogs, and they are currently accepted as comparative models of the disease in humans. Aberrant patterns of DNA methylation seem to play a key role in the development of hematopoietic neoplasms in humans, constitute a special mechanism of transcriptional control, and may be influenced by genetic and environmental factors. Blood leukocyte DNA global methylation has been poorly investigated in dogs. The aim of this study is to examine whether peripheral blood global DNA methylation is associated with canine multicentric lymphomas. Peripheral venous blood samples from ten healthy dogs and nine dogs bearing multicentric lymphomas were collected, and the buffy coat was separated. Global DNA methylation was analyzed by High Performance Liquid Chromatography (HPLC) and immunocytochemistry (ICC). In both analyses, leukocytes from dogs with lymphoma presented lower global DNA methylation than in healthy dogs (HPLC: p = 0.027/ 5MeCyt immunoreactivity scores: p = 0.015). Moderate correlation was observed between the results obtained by HPLC and ICC (correlation coefficient = 0.50). For the identification of differently methylated genes between both groups, the Infinium Human Methylation (HM) EPIC BeadChip (850K) was used. Of the 853,307 CpGs investigated in the microarray, there were 34,574 probes hybridized in the canine samples. From this total, significant difference was observed in the methylation level of 8433 regions, and through the homologous and orthologous similarities 525 differently methylated genes were identified between the two groups. This study is pioneer in suggesting that dogs bearing non-Hodgkin lymphoma presented DNA global hypomethylation of circulating leukocytes compared with healthy dogs. Although canine samples were used in an assay developed specifically for human DNA, it was possible to identify differently methylated genes and our results reiterate the importance of the use of peripheral blood leukocytes in cancer research and possible new biomarkers targets.

Dietary intake of one-carbon metabolism nutrients and DNA methylation in peripheral blood

Background

Folate and other one-carbon metabolism nutrients are essential to enable DNA methylation to occur, but the extent to which their dietary intake influences methylation in adulthood is unclear.

Objective

We assessed associations between dietary intake of these nutrients and DNA methylation in peripheral blood, overall and at specific genomic locations.

Design

We conducted a cross-sectional study using baseline data and samples from 5186 adult participants in the Melbourne Collaborative Cohort Study (MCCS). Nutrient intake was estimated from a food-frequency questionnaire. DNA methylation was measured by using the Illumina Infinium HumanMethylation450 BeadChip array (HM450K). We assessed associations of intakes of folate, riboflavin, vitamins B-6 and B-12, methionine, choline, and betaine with methylation at individual cytosine-guanine dinucleotides (CpGs), and with median (genome-wide) methylation across all CpGs, CpGs in gene bodies, and CpGs in gene promoters. We also assessed associations with methylation at long interspersed nuclear element 1 (LINE-1), satellite 2 (Sat2), and Arthrobacter luteus restriction endonuclease (Alu) repetitive elements for a subset of participants. We used linear mixed regression, adjusting for age, sex, country of birth, smoking, energy intake from food, alcohol intake, Mediterranean diet score, and batch effects to assess log-linear associations with dietary intake of each nutrient. In secondary analyses, we assessed associations with low or high intakes defined by extreme quintiles.

Results

No evidence of log-linear association was observed at P < 10-7 between the intake of one-carbon metabolism nutrients and methylation at individual CpGs. Low intake of riboflavin was associated with higher methylation at CpG cg21230392 in the first exon of PROM1 (P = 5.0 × 10-8). No consistent evidence of association was observed with genome-wide or repetitive element measures of methylation.

Conclusion

Our findings suggest that dietary intake of one-carbon metabolism nutrients in adulthood, as measured by a food-frequency questionnaire, has little association with blood DNA methylation. An association with low intake of riboflavin requires replication in independent cohorts. This study was registered at http://www.clinicaltrials.gov as NCT03227003.

Genome-wide average DNA methylation is determined in utero

BACKGROUND

Investigating the genetic and environmental causes of variation in genome-wide average DNA methylation (GWAM), a global methylation measure from the HumanMethylation450 array, might give a better understanding of genetic and environmental influences on methylation.

METHODS

We measured GWAM for 2299 individuals aged 0 to 90 years from seven twin and/or family studies. We estimated familial correlations, modelled correlations with cohabitation history and fitted variance components models for GWAM.

RESULTS

The correlation in GWAM for twin pairs was ∼0.8 at birth, decreased with age during adolescence and was constant at ∼0.4 throughout adulthood, with no evidence that twin pair correlations differed by zygosity. Non-twin first-degree relatives were correlated, from 0.17 [95% confidence interval (CI): 0.05-0.30] to 0.28 (95% CI: 0.08-0.48), except for middle-aged siblings (0.01, 95% CI: -0.10-0.12), and the correlation increased with time living together and decreased with time living apart. Spouse pairs were correlated in all studies, from 0.23 (95% CI: 0.3-0.43) to 0.31 (95% CI: 0.05-0.52), and the correlation increased with time living together. The variance explained by environmental factors shared by twins alone was 90% (95% CI: 74-95%) at birth, decreased in early life and plateaued at 28% (95% CI: 17-39%) in middle age and beyond. There was a cohabitation-related environmental component of variance.

CONCLUSIONS

GWAM is determined in utero by prenatal environmental factors, the effects of which persist throughout life. The variation of GWAM is also influenced by environmental factors shared by family members, as well as by individual-specific environmental factors.

Association of DNA Methylation-Based Biological Age With Health Risk Factors and Overall and Cause-Specific Mortality

Measures of biological age based on blood DNA methylation, referred to as age acceleration (AA), have been developed. We examined whether AA was associated with health risk factors and overall and cause-specific mortality. At baseline (1990-1994), blood samples were drawn from 2,818 participants in the Melbourne Collaborative Cohort Study (Melbourne, Victoria, Australia). DNA methylation was determined using the Infinium HumanMethylation450 BeadChip array (Illumina Inc., San Diego, California). Mixed-effects models were used to examine the association of AA with health risk factors. Cox models were used to assess the association of AA with mortality. A total of 831 deaths were observed during a median 10.7 years of follow-up. Associations of AA were observed with male sex, Greek nationality (country of birth), smoking, obesity, diabetes, lower education, and meat intake. AA measures were associated with increased mortality, and this was only partly accounted for by known determinants of health (hazard ratios were attenuated by 20%-40%). Weak evidence of heterogeneity in the association was observed by sex (P = 0.06) and cause of death (P = 0.07) but not by other factors. DNA-methylation-based AA measures are associated with several major health risk factors, but these do not fully explain the association between AA and mortality. Future research should investigate what genetic and environmental factors determine AA.

Dietary intake of nutrients involved in one-carbon metabolism and risk of urothelial cell carcinoma: A prospective cohort study

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.

Epigenetic supersimilarity of monozygotic twin pairs

BACKGROUND

Monozygotic twins have long been studied to estimate heritability and explore epigenetic influences on phenotypic variation. The phenotypic and epigenetic similarities of monozygotic twins have been assumed to be largely due to their genetic identity.

RESULTS

Here, by analyzing data from a genome-scale study of DNA methylation in monozygotic and dizygotic twins, we identified genomic regions at which the epigenetic similarity of monozygotic twins is substantially greater than can be explained by their genetic identity. This "epigenetic supersimilarity" apparently results from locus-specific establishment of epigenotype prior to embryo cleavage during twinning. Epigenetically supersimilar loci exhibit systemic interindividual epigenetic variation and plasticity to periconceptional environment and are enriched in sub-telomeric regions. In case-control studies nested in a prospective cohort, blood DNA methylation at these loci years before diagnosis is associated with risk of developing several types of cancer.

CONCLUSIONS

These results establish a link between early embryonic epigenetic development and adult disease. More broadly, epigenetic supersimilarity is a previously unrecognized phenomenon that may contribute to the phenotypic similarity of monozygotic twins.

DNA methylation-based biological aging and cancer risk and survival: Pooled analysis of seven prospective studies

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.

Twin birth changes DNA methylation of subsequent siblings

We asked if twin birth influences the DNA methylation of subsequent siblings. We measured whole blood methylation using the HumanMethylation450 array for siblings from two twin and family studies in Australia and Korea. We compared the means and correlations in methylation between pairs of siblings born before a twin birth (BT siblings), born on either side of a twin birth (B/AT pairs) and born after a twin birth (AT siblings). For the genome-wide average DNA methylation, the correlation for AT pairs (r_AT) was larger than the correlation for BT pairs (r_BT) in both studies, and from the meta-analysis, r_AT = 0.46 (95% CI: 0.26, 0.63) and r_BT = -0.003 (95% CI: -0.30, 0.29) (P = 0.02). B/AT pairs were not correlated (from the meta-analysis r_BAT = 0.08; 95% CI: -0.31, 0.45). Similar results were found for the average methylation of several genomic regions, e.g., CpG shelf and gene body. BT and AT pairs were differentially correlated in methylation for 15 probes (all P < 10^-7), and the top 152 differentially correlated probes (at P < 10^-4) were enriched in cell signalling and breast cancer regulation pathways. Our observations are consistent with a twin birth changing the intrauterine environment such that siblings both born after a twin birth are correlated in DNA methylation.