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.
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Aging is associated with profound changes in DNA methylation levels. These can be used to build accurate age predictors (“epigenetic clocks”) that deviate from chronological age by only a few years, a phenomenon named “age acceleration”. In this study of seven types of cancer, the authors found that age acceleration was associated with both increased cancer risk and decreased cancer survival, independently of major health risk factors. These results support the usefulness of methylation markers of biological aging as a tool to predict health outcomes and may provide valuable insight into the relationship between aging and cancer.
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•Greenspace was associated with DNA methylation of multiple human genome loci.•Those loci are mapped to many genes related to many human diseases.•The greenspace-DNA methylation ...association could be modified by genetic variations.
DNA methylation is a potential biological mechanism through which residential greenness affects health, but little is known about its association with greenness and whether the association could be modified by genetic background. We aimed to evaluate the association between surrounding greenness and genome-wide DNA methylation and potential gene-greenness interaction effects on DNA methylation.
We measured blood-derived DNA methylation using the HumanMethylation450 BeadChip array (Illumina) for 479 Australian women, including 66 monozygotic, 66 dizygotic twin pairs, and 215 sisters of these twins. Surrounding greenness was represented by Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) within 300, 500, 1000 or 2000 m surrounding participants’ home addresses. For each cytosine-guanine dinucleotide (CpG), the associations between its methylation level and NDVI or EVI were evaluated by generalized estimating equations, after adjusting for age, education, marital status, area-level socioeconomic status, smoking behavior, cell-type proportions, and familial clustering. We used comb-p and DMRcate to identify significant differentially methylated regions (DMRs). For each significant CpG, we evaluated the interaction effects of greenness and single-nucleotide polymorphisms (SNPs) within ±1 Mb window on its methylation level.
We found associations between surrounding greenness and blood DNA methylation for one CpG (cg04720477, mapped to the promoter region of CNP gene) with false discovery rate FDR < 0.05, and for another 9 CpGs with 0.05 ≤ FDR < 0.10. For two of these CpGs, we found 33 SNPs significantly (FDR < 0.05) modified the greenness-methylation association. There were 35 significant DMRs related to surrounding greenness that were identified by both comb-p (Sidak p-value < 0.01) and DMRcate (FDR < 0.01). Those CpGs and DMRs were mapped to genes related to many human diseases, such as mental health disorders and neoplasms as well as nutritional and metabolic diseases.
Surrounding greenness was associated with blood DNA methylation of many loci across human genome, and this association could be modified by genetic variations.
Current risk prediction models estimate the probability of developing breast cancer over a defined period based on information such as family history, non-genetic breast cancer risk factors, genetic ...information from high and moderate risk breast cancer susceptibility genes and, over the past several years, polygenic risk scores (PRS) from more than 300 common variants. The inclusion of additional data such as PRS improves risk stratification, but it is anticipated that the inclusion of epigenetic marks could further improve model performance accuracy. Here, we present the case for including information on DNA methylation marks to improve the accuracy of these risk prediction models, and consider how this approach contrasts genetic information, as identifying DNA methylation marks associated with breast cancer risk differs inherently according to the source of DNA, approaches to the measurement of DNA methylation, and the timing of measurement. We highlight several DNA-methylation-specific challenges that should be considered when incorporating information on DNA methylation marks into risk prediction models, using BRCA1, a highly penetrant breast cancer susceptibility gene, as an example. Only after careful consideration of study design and DNA methylation measurement will prospective performance of the incorporation of information regarding DNA methylation marks into risk prediction models be valid.
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•Wildfire PM2.5 was associated with DNA methylation of many human genome loci.•Those loci were mapped to 47 genes related to many human diseases.•The genes were enriched in ...inflammatory regulation and platelet activation pathways.•DNA methylation signatures of wildfire and non-wildfire PM2.5 were quite different.
Wildfire-related fine particulate matter (PM2.5) has many adverse health impacts, but its impacts on human epigenome are unknown. We aimed to evaluate the associations between long-term exposure to wildfire-related PM2.5 and blood DNA methylation, and whether the associations differ from those with non-wildfire-related PM2.5.
We studied 479 Australian women comprising 132 twin pairs and 215 of their sisters. Blood-derived DNA methylation was measured using the HumanMethylation450 BeadChip array. Data on 3-year (year of blood collection and previous two years) average wildfire-related and non-wildfire-related PM2.5 at 0.01°×0.01° spatial resolution were created by combining information from satellite observations, chemical transport models, and ground-based observations. Exposure data were linked to each participant’s home address, assuming the address did not change during the exposure window. For DNA methylation of each cytosine-guanine dinucleotide (CpG), and for global DNA methylation represented by the average of all measured CpGs or CpGs in repetitive elements, we evaluated their associations with wildfire- or non-wildfire-related PM2.5 using a within-sibship analysis controlling for factors shared between siblings and other important covariates. Differentially methylated regions (DMRs) were defined by comb-p and DMRcate.
The 3-year average wildfire-related PM2.5 (range: 0.3 to 7.6 µg/m3, mean: 1.6 µg/m3) was negatively, but not significantly (p-values greater than 0.05) associated with all seven global DNA methylation measures. There were 26 CpGs and 33 DMRs associated with wildfire-related PM2.5 (Bonferroni adjusted p-value < 0.05) mapped to 47 genes enriched for pathways related to inflammatory regulation and platelet activation. These genes have been related to many human diseases or phenotypes e.g., cancer, mental disorders, diabetes, obesity, asthma, blood pressure. These CpGs, DMRs and enriched pathways did not overlap with the 1 CpG and 7 DMRs associated with non-wildfire-related PM2.5.
Long-term exposure to wildfire-related PM2.5 was associated with various blood DNA methylation signatures in Australian women, and these were distinct from those associated with non-wildfire-related PM2.5.
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.
Mutations in PIK3CA are present in 10 to 15% of colorectal carcinomas. We aimed to examine how PIK3CA mutations relate to other molecular alterations in colorectal carcinoma, to pathologic phenotype ...and survival. PIK3CA mutation testing was carried out using direct sequencing on 757 incident tumors from the Melbourne Collaborative Cohort Study. The status of O-6-methylguanine-DNA methyltransferase (MGMT) was assessed using both immunohistochemistry and methyLight techniques. Microsatellite instability, CpG island phenotype (CIMP), KRAS and BRAF V600E mutation status, and pathology review features were derived from previous reports. PIK3CA mutation was observed in 105 of 757 (14%) of carcinomas, characterized by location in the proximal colon (54% vs. 34%; P<0.001) and an increased frequency of KRAS mutation (48% vs. 25%; P<0.001). High-levels of CIMP were more frequently found in PIK3CA-mutated tumors compared with PIK3CA wild-type tumors (22% vs. 11%; P = 0.004). There was no difference in the prevalence of BRAF V600E mutation between these two tumor groups. PIK3CA-mutated tumors were associated with loss of MGMT expression (35% vs. 20%; P = 0.001) and the presence of tumor mucinous differentiation (54% vs. 32%; P<0.001). In patients with wild-type BRAF tumors, PIK3CA mutation was associated with poor survival (HR 1.51 95% CI 1.04-2.19, P = 0.03). In summary, PIK3CA-mutated colorectal carcinomas are more likely to develop in the proximal colon, to demonstrate high levels of CIMP, KRAS mutation and loss of MGMT expression. PIK3CA mutation also contributes to significantly decreased survival for patients with wild-type BRAF tumors.
DNA hypomethylation in certain genes is associated with tobacco exposure but it is unknown whether these methylation changes translate into increased lung cancer risk. In an epigenome-wide study of ...DNA from pre-diagnostic blood samples from 132 case-control pairs in the NOWAC cohort, we observe that the most significant associations with lung cancer risk are for cg05575921 in AHRR (OR for 1 s.d.=0.37, 95% CI: 0.31-0.54, P-value=3.3 × 10(-11)) and cg03636183 in F2RL3 (OR for 1 s.d.=0.40, 95% CI: 0.31-0.56, P-value=3.9 × 10(-10)), previously shown to be strongly hypomethylated in smokers. These associations remain significant after adjustment for smoking and are confirmed in additional 664 case-control pairs tightly matched for smoking from the MCCS, NSHDS and EPIC HD cohorts. The replication and mediation analyses suggest that residual confounding is unlikely to explain the observed associations and that hypomethylation of these CpG sites may mediate the effect of tobacco on lung cancer risk.
•This is the first study to assess the epigenetic impact of short-term temperature fluctuations.•Significant changes in methylation levels in 14 cytosine-guanine dinucleotides were associated with ...temperature fluctuations.•We identified 70 differentially methylated regions significantly associated with temperature fluctuation.•Differentially methylated signals were mapped to 68 genes that were linked to human diseases (e.g., cancer and mental disorders).
Temperature fluctuations can affect human health independent of the effect of mean temperature. However, no study has evaluated whether short-term temperature fluctuations could affect DNA methylation.
Peripheral blood DNA methylation for 479 female siblings of 130 families were analysed. Gridded daily temperatures data were obtained, linked to each participant’s home address, and used to calculate nine different metrics of short-term temperature fluctuations: temperature variabilities (TVs) within the day of blood draw and preceding one to seven days (TV 0–1 to TV 0–7), diurnal temperature range (DTR), and temperature change between neighbouring days (TCN). Within-sibship design was used to perform epigenome-wide association analyses, adjusting for daily mean temperatures, and other important covariates (e.g., smoking, alcohol use, cell-type proportions). Differentially methylated regions (DMRs) were further identified. Multiple-testing comparisons with a significant threshold of 0.01 for cytosine-guanine dinucleotides (CpGs) and 0.05 for DMRs were applied.
Among 479 participants (mean age ± SD, 56.4 ± 7.9 years), we identified significant changes in methylation levels in 14 CpGs and 70 DMRs associated with temperature fluctuations. Almost all identified CpGs were associated with exposure to temperature fluctuations within three days. Differentially methylated signals were mapped to 68 genes that were linked to human diseases such as cancer (e.g., colorectal carcinoma, breast carcinoma, and metastatic neoplasms) and mental disorder (e.g., schizophrenia, mental depression, and bipolar disorder). The top three most significantly enriched gene ontology terms were Response to bacterium (TV 0–3), followed by Hydrolase activity, acting on ester bonds (TCN), and Oxidoreductase activity (TV 0–3).
Short-term temperature fluctuations were associated with differentially methylated signals across the human genome, which provides evidence on the potential biological mechanisms underlying the health impact of temperature fluctuations. Future studies are needed to further clarify the roles of DNA methylation in diseases associated with temperature fluctuations.
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.
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