Long-term exposure to ambient fine particulate components and leukocyte epigenome-wide DNA Methylation in older men: the Normative Aging Study.

BACKGROUND: Epigenome-wide association studies of ambient fine particulate matter (PM2.5) have been reported. However, few have examined PM2.5 components (PMCs) and sources or included repeated measures. The lack of high-resolution exposure measurements is the key limitation. We hypothesized that significant changes in DNA methylation might vary by PMCs and the sources. METHODS: We predicted the annual average of 14 PMCs using novel high-resolution exposure models across the contiguous U.S., between 2000-2018. The resolution was 50 m × 50 m in the Greater Boston Area. We also identified PM2.5 sources using positive matrix factorization. We repeatedly collected blood samples and measured leukocyte DNAm with the Illumina HumanMethylation450K BeadChip in the Normative Aging Study. We then used median regression with subject-specific intercepts to estimate the associations between long-term (one-year) exposure to PMCs / PM2.5 sources and DNA methylation at individual cytosine-phosphate-guanine CpG sites. Significant probes were identified by the number of independent degrees of freedom approach, using the number of principal components explaining > 95% of the variation of the DNA methylation data. We also performed regional and pathway analyses to identify significant regions and pathways. RESULTS: We included 669 men with 1,178 visits between 2000-2013. The subjects had a mean age of 75 years. The identified probes, regions, and pathways varied by PMCs and their sources. For example, iron was associated with 6 probes and 6 regions, whereas nitrate was associated with 15 probes and 3 regions. The identified pathways from biomass burning, coal burning, and heavy fuel oil combustion sources were associated with cancer, inflammation, and cardiovascular diseases, whereas there were no pathways associated with all traffic. CONCLUSIONS: Our findings showed that the effects of PM2.5 on DNAm varied by its PMCs and sources.

Epigenome-wide DNA methylation in leukocytes and toenail metals: The normative aging study.

BACKGROUND: Environmental metal exposures have been associated with multiple deleterious health endpoints. DNA methylation (DNAm) may provide insight into the mechanisms underlying these relationships. Toenail metals are non-invasive biomarkers, reflecting a medium-term time exposure window. OBJECTIVES: This study examined variation in leukocyte DNAm and toenail arsenic (As), cadmium (Cd), lead (Pb), manganese (Mn), and mercury (Hg) among elderly men in the Normative Aging Study, a longitudinal cohort. METHODS: We repeatedly collected samples of blood and toenail clippings. We measured DNAm in leukocytes with the Illumina HumanMethylation450 K BeadChip. We first performed median regression to evaluate the effects of each individual toenail metal on DNAm at three levels: individual cytosine-phosphate-guanine (CpG) sites, regions, and pathways. Then, we applied a Bayesian kernel machine regression (BKMR) to assess the joint and individual effects of metal mixtures on DNAm. Significant CpGs were identified using a multiple testing correction based on the independent degrees of freedom approach for correlated outcomes. The approach considers the effective degrees of freedom in the DNAm data using the principal components that explain >95% variation of the data. RESULTS: We included 564 subjects (754 visits) between 1999 and 2013. The numbers of significantly differentially methylated CpG sites, regions, and pathways varied by metals. For example, we found six significant pathways for As, three for Cd, and one for Mn. The As-associated pathways were associated with cancer (e.g., skin cancer) and cardiovascular disease, whereas the Cd-associated pathways were related to lung cancer. Metal mixtures were also associated with 47 significant CpG sites, as well as pathways, mainly related to cancer and cardiovascular disease. CONCLUSIONS: This study provides an approach to understanding the potential epigenetic mechanisms underlying observed relations between toenail metals and adverse health endpoints.

Short- and intermediate-term exposure to ambient fine particulate elements and leukocyte epigenome-wide DNA methylation in older men: the Normative Aging Study.

BACKGROUND: Several epigenome-wide association studies (EWAS) of ambient particulate matter with aerodynamic diameter ≤ 2.5 µm (PM2.5) have been reported. However, EWAS of PM2.5 elements (PEs), reflecting different emission sources, are very limited. OBJECTIVES: We performed EWAS of short- and intermediate-term exposure to PM2.5 and 13 PEs. We hypothesized that significant changes in DNAm may vary by PM2.5 mass and its elements. METHODS: We repeatedly collected blood samples in the Normative Aging Study and measured leukocyte DNA methylation (DNAm) with the Illumina HumanMethylation450K BeadChip. We collected daily PM2.5 and 13 PEs at a fixed central site. To estimate the associations between each PE and DNAm at individual cytosine-phosphate-guanine (CpG) sites, we incorporated a distributed-lag (0-27 d) term in the setting of median regression with subject-specific intercept and examined cumulative lag associations. We also accounted for selection bias due to loss to follow-up and mortality prior to enrollment. Significantly differentially methylated probes (DMPs) were identified using Bonferroni correction for multiple testing. We further conducted regional and pathway analyses to identify significantly differentially methylated regions (DMRs) and pathways. RESULTS: We included 695 men with 1,266 visits between 1999 and 2013. The subjects had a mean age of 75 years. The significant DMPs, DMRs, and pathways varied by to PM2.5 total mass and PEs. For example, PM2.5 total mass was associated with 2,717 DMPs and 10,470 DMRs whereas Pb was associated with 3,173 DMPs and 637 DMRs. The identified pathways by PM2.5 mass were mostly involved in mood disorders, neuroplasticity, immunity, and inflammation, whereas the pathways associated with motor vehicles (BC, Cu, Pb, and Zn) were related with cardiovascular disease and cancer (e.g., "PPARs signaling"). CONCLUSIONS: PM2.5 and PE were associated with methylation changes at multiple probes and along multiple pathways, in ways that varied by particle components.

DNA methylation-based biomarkers of age acceleration and all-cause death, myocardial infarction, stroke, and cancer in two cohorts: The NAS, and KORA F4.

BACKGROUND: DNA methylation (DNAm) may play a role in age-related outcomes. It is not yet known which DNAm-based biomarkers of age acceleration (BoAA) has the strongest association with age-related endpoints. METHODS: We collected the blood samples from two independent cohorts: the Normative Ageing Study, and the Cooperative Health Research in the Region of Augsburg cohort. We measured epigenome-wide DNAm level, and generated five DNAm BoAA at baseline. We used Cox proportional hazards model to analyze the relationships between BoAA and all-cause death. We applied the Fine and Gray competing risk model to estimate the risk of BoAA on myocardial infarction (MI), stroke, and cancer, accounting for death of other reasons as the competing risks. We used random-effects meta-analyses to pool the individual results, with adjustment for multiple testing. FINDINGS: The mean chronological ages in the two cohorts were 74, and 61, respectively. Baseline GrimAgeAccel, and DNAm-related mortality risk score (DNAmRS) both had strong associations with all-cause death, MI, and stroke, independent from chronological age. For example, a one standard deviation (SD) increment in GrimAgeAccel was significantly associated with increased risk of all-cause death [hazard ratio (HR): 2.01; 95% confidence interval (CI), 1.15, 3.50], higher risk of MI (HR: 1.44; 95% CI, 1.16, 1.79), and elevated risk of stroke (HR: 1.42; 95% CI, 1.06, 1.91). There were no associations between any BoAA and cancer. INTERPRETATION: From the public health perspective, GrimAgeAccel is the most useful tool for identifying at-risk elderly, and evaluating the efficacy of anti-aging interventions. FUNDING: National Institute of Environmental Health Sciences of U.S., Harvard Chan-NIEHS Center for Environmental Health, German Federal Ministry of Education and Research, and the State of Bavaria in Germany.

Impact of confounding by leukocyte composition on associations of leukocyte DNA methylation with common risk factors.

AIM: One concern in epigenome-wide studies investigating leukocyte DNA methylation is that observed associations may at least partly reflect differences in leukocyte composition (LC) rather than changes in methylation. We estimated the magnitude of confounding by LC for common risk factors and diseases. MATERIALS & METHODS: Variation of LC according to sex, race, age, smoking, alcohol consumption, BMI, cardiovascular fitness, hypertension, coronary heart disease and diabetes was analyzed using blood differentials from 4117 participants of NHANES. Furthermore, leukocyte DNA methylation levels of biomarkers of smoking, BMI, diabetes, age and sex were regressed on these outcomes in a sample of 989 participants of ESTHER, and regression coefficients with and without adjustment for estimated LC were compared. RESULTS: Aside from race and ages below 25 years, none of the investigated factors had substantial impact on LC. Adjusted and unadjusted coefficients were virtually identical. CONCLUSION: Confounding by LC might often be a minor issue.

Epigenome-wide discovery and evaluation of leukocyte DNA methylation markers for the detection of colorectal cancer in a screening setting.

BACKGROUND: Colorectal cancer (CRC) is the third most common cancer worldwide. If detected at an early stage, prognosis is good. Despite increasing evidence for the benefits of implemented screening programs, such as screening colonoscopy, compliance is rather low. Hence there is demand for non-invasive tests for the early detection of CRC with high acceptance in population-wide screening. The objective of this study was to identify and evaluate leukocyte DNA methylation patterns as a potential biomarker for early detection of CRC. METHODS: Blood samples of patients scheduled for a screening colonoscopy were collected before the procedure. Additionally, blood samples from CRC cases recruited in a clinical setting were collected. DNA was extracted from leukocytes, and DNA methylation was measured with the Infinium 450K BeadChip. In total, 46 CRC cases and 140 controls from the screening setting and 93 CRC cases from the clinical setting were measured. RESULTS: An epigenome-wide discovery revealed two CpG sites in the promoter region of KIAA1549L that were significantly differentially methylated between cases and controls. A third marker in the body region of BCL2 was discovered in a candidate approach testing biomarkers reported in the literature. Logistic regression models built on these three markers yielded an optimism-corrected c-statistic of 0.69 in the screening setting and 0.73 in the clinical setting. CONCLUSIONS: Although diagnostic performance of the DNA methylation signature identified in this first epigenome-wide association study of leukocyte DNA methylation with CRC in a screening setting is not competitive with established screening tests, the identified markers may contribute to multimarker panels for early detection of CRC.

DNA methylation signatures in peripheral blood strongly predict all-cause mortality.

DNA methylation (DNAm) has been revealed to play a role in various diseases. Here we performed epigenome-wide screening and validation to identify mortality-related DNAm signatures in a general population-based cohort with up to 14 years follow-up. In the discovery panel in a case-cohort approach, 11,063 CpGs reach genome-wide significance (FDR<0.05). 58 CpGs, mapping to 38 well-known disease-related genes and 14 intergenic regions, are confirmed in a validation panel. A mortality risk score based on ten selected CpGs exhibits strong association with all-cause mortality, showing hazard ratios (95% CI) of 2.16 (1.10-4.24), 3.42 (1.81-6.46) and 7.36 (3.69-14.68), respectively, for participants with scores of 1, 2-5 and 5+ compared with a score of 0. These associations are confirmed in an independent cohort and are independent from the 'epigenetic clock'. In conclusion, DNAm of multiple disease-related genes are strongly linked to mortality outcomes. The DNAm-based risk score might be informative for risk assessment and stratification.

Type 2 diabetes and leucocyte DNA methylation: an epigenome-wide association study in over 1,500 older adults.

AIMS/HYPOTHESIS: Development of type 2 diabetes depends on environmental and genetic factors. We investigated the epigenome-wide association of prevalent diabetes with DNA methylation (DNAm) in peripheral blood. METHODS: DNAm was measured in whole blood with the Illumina Infinium HumanMethylation450 BeadChip in two subsamples of participants from the ESTHER cohort study. Cohort 1 included 988 participants, who were consecutively recruited between July and October 2000 and cohort 2 included 527 randomly selected participants. The association of DNAm with prevalent type 2 diabetes at recruitment was estimated using median regression analysis adjusting for sex, age, BMI, smoking behaviour, cell composition and batch at 361,922 CpG sites. RESULTS: Type 2 diabetes was prevalent in 16% of the participants, and diabetes was poorly controlled in 45% of the diabetic patients. In cohort 1 (discovery) DNAm at 39 CpGs was significantly associated with prevalent diabetes after correction for multiple testing. In cohort 2 (replication) at one of these CpGs, DNAm was still significantly associated. Decreasing methylation levels at cg19693031 with increasing fasting glucose and HbA1c concentrations were observed using restricted cubic spline analysis. In diabetic patients with poorly controlled diabetes, the decrease in estimated DNAm levels was approximately 5% in comparison with participants free of diagnosed diabetes. CONCLUSIONS/INTERPRETATION: Cg19693031, which is located within the 3'-untranslated region of TXNIP, might play a role in the pathophysiology of type 2 diabetes. This result appears biologically plausible given that thioredoxin-interacting protein is overexpressed in diabetic animals and humans and 3'-untranslated regions are known to play a regulatory role in gene expression.

Detection of cancer through exhaled breath: a systematic review.

BACKGROUND: Timely diagnosis of cancer represents a challenging task; in particular, there is a need for reliable non-invasive screening tools that could achieve high levels of adherence at virtually no risk in population-based screening. In this review, we summarize the current evidence of exhaled breath analysis for cancer detection using standard analysis techniques and electronic nose. METHODS: Relevant studies were identified searching Pubmed and Web of Science databases until April 30, 2015. Information on breath test performance, such as sensitivity and specificity, was extracted together with volatile compounds that were used to discriminate cancer patients from controls. Performance of different breath analysis techniques is provided for various cancers together with information on methodological issues, such as breath sampling protocol and validation of the results. RESULTS: Overall, 73 studies were included, where two-thirds of the studies were conducted on lung cancer. Good discrimination usually required a combination of multiple biomarkers, and area under the receiver operating characteristic curve or accuracy reached levels of 0.9 or higher in multiple studies. In 25% of the reported studies, classification models were built and validated on the same datasets. Huge variability was seen in different aspects among the studies. CONCLUSIONS: Analyses of exhaled breath yielded promising results, although standardization of breath collection, sample storage and data handling remain critical issues. In order to foster breath analysis implementation into practice, larger studies should be implemented in true screening settings, paying particular attention to standardization in breath collection, consideration of covariates, and validation in independent population samples.

Discovery of a novel epigenetic cancer marker related to the oxidative status of human blood.

Long-lasting oxidative stress exposure may lead to relatively stable epigenetic modifications of the DNA in order to activate anti-oxidative defence mechanisms. Oxidative stress related DNA methylation may therefore be associated (causally or as a by-product) with cancer. We measured derivatives of reactive oxygen metabolites (D-ROM), total thiol levels (TTL) and DNA methylation with the Illumina Infinium 450K BeadChip in three samples of German individuals aged ≥50 years: n = 1,000 ESTHER study baseline participants (DNA methylation only), n = 99 ESTHER eight-year follow-up participants and n = 142 participants of the BLITZ study. The correlation coefficient of methylation at cg10342304 and D-ROM in the ESTHER 8-year follow-up sample (r = -0.427; P = 1 × 10(-5)) was replicated with a P-value indicating statistical significance after correction for multiple testing in the BLITZ sample (r = -0.192; P = 0.022). The association was robust to adjusting for potential confounders. In the ESTHER baseline sample, the hazard ratio for cancer development in 11 years of follow-up comparing bottom and top quartile of DNA methylation at cg10342304 was 1.86 (95%-confidence-interval 1.01-3.43). In summary, this first epigenome-wide screening and replication study with oxidative status markers observed a negative correlation of D-ROM levels and DNA methylation at cg10342304 in two independent cohorts. This CpG site is located in the body region of the nucleoredoxin gene. The nucleoredoxin protein is a redox-dependent inhibitor of the Wnt/ß-catenin signaling pathway, a well-characterized cancer pathway. If the observed CpG-cancer association can be successfully replicated by other studies, this epigenetic marker could be an interesting biomarker of cancer risk.

Between-array normalization for 450K data.

The Illumina Infinium HumanMethylation450 BeadChip is frequently used in epigenetic research. Besides quantile normalization there is currently no standard method to normalize the data between arrays. We describe some properties of the data generated by this platform and present a normalization method based on local regression. We compare the performance of this method with other commonly used approaches in three benchmarks (correlation between 21 pairs of technical replicates, detection of differential methylation and correlation of methylation levels for smoking-associated CpG sites with smoking behavior of 655 participants of an epidemiological study). Results indicate that the proposed method improves reproducibility, whereas some commonly used methods can have adverse effects.