Integrative analysis of clinical and epigenetic biomarkers of mortality.

DNA methylation (DNAm) has been reported to be associated with many diseases and with mortality. We hypothesized that the integration of DNAm with clinical risk factors would improve mortality prediction. We performed an epigenome-wide association study of whole blood DNAm in relation to mortality in 15 cohorts (n = 15,013). During a mean follow-up of 10 years, there were 4314 deaths from all causes including 1235 cardiovascular disease (CVD) deaths and 868 cancer deaths. Ancestry-stratified meta-analysis of all-cause mortality identified 163 CpGs in European ancestry (EA) and 17 in African ancestry (AA) participants at p < 1 × 10-7 , of which 41 (EA) and 16 (AA) were also associated with CVD death, and 15 (EA) and 9 (AA) with cancer death. We built DNAm-based prediction models for all-cause mortality that predicted mortality risk after adjusting for clinical risk factors. The mortality prediction model trained by integrating DNAm with clinical risk factors showed an improvement in prediction of cancer death with 5% increase in the C-index in a replication cohort, compared with the model including clinical risk factors alone. Mendelian randomization identified 15 putatively causal CpGs in relation to longevity, CVD, or cancer risk. For example, cg06885782 (in KCNQ4) was positively associated with risk for prostate cancer (Beta = 1.2, PMR  = 4.1 × 10-4 ) and negatively associated with longevity (Beta = -1.9, PMR  = 0.02). Pathway analysis revealed that genes associated with mortality-related CpGs are enriched for immune- and cancer-related pathways. We identified replicable DNAm signatures of mortality and demonstrated the potential utility of CpGs as informative biomarkers for prediction of mortality risk.

17q12-21 risk-variants influence cord blood immune regulation and multitrigger-wheeze.

BACKGROUND: Childhood wheeze represents a first symptom of asthma. Early identification of children at risk for wheeze related to 17q12-21 variants and their underlying immunological mechanisms remain unknown. We aimed to assess the influence of 17q12-21 variants and mRNA expression at birth on the development of wheeze. METHODS: Children were classified as multitrigger/viral/no wheeze until six years of age. The PAULINA/PAULCHEN birth cohorts were genotyped (n = 216; GSA-chip). mRNA expression of 17q21 and innate/adaptive genes was measured (qRT-PCR) in cord blood mononuclear cells. Expression quantitative trait loci (eQTL) and mediation analyses were performed. Genetic variation of 17q12-21 asthma-single nucleotide polymorphisms (SNPs) was summarized as the first principal component (PC1) and used to classify single SNP effects on gene expression as (locus)-dependent/independent eQTL SNPs. RESULTS: Core region risk variants (IKZF3, ZPBP2, GSDMB, ORMDL3) were associated with multitrigger wheeze (OR: 3.05-5.43) and were locus-dependent eQTL SNPs with higher GSDMA, TLR2, TLR5, and lower TGFB1 expression. Increased risk of multitrigger wheeze with rs9303277 was in part mediated by TLR2 expression. Risk variants distal to the core region were mainly locus-independent eQTL SNPs with decreased CD209, CD86, TRAF6, RORA, and IL-9 expression. Distinct immune signatures in cord blood were associated either with multitrigger wheeze (increased innate genes, e.g., TLR2, IPS1, LY75) or viral wheeze (decreased NF-κB genes, e.g., TNFAIP3 and TNIP2). CONCLUSION: Locus-dependent eQTL SNPs (core region) associated with increased inflammatory genes (primarily TLR2) at birth and subsequent multitrigger wheeze indicate that early priming and imbalance may be crucial for asthma pathophysiology. Locus-independent eQTL SNPs (mainly distal region, rs1007654) may be involved in the initiation of dendritic cell activation/maturation (TRAF6) and interaction with T cells (CD209, CD86). Identifying potential mechanistic pathways at birth may point to critical key points during early immune development predisposing to asthma.

Smoking-related changes in DNA methylation and gene expression are associated with cardio-metabolic traits.

BACKGROUND: Tobacco smoking is a well-known modifiable risk factor for many chronic diseases, including cardiovascular disease (CVD). One of the proposed underlying mechanism linking smoking to disease is via epigenetic modifications, which could affect the expression of disease-associated genes. Here, we conducted a three-way association study to identify the relationship between smoking-related changes in DNA methylation and gene expression and their associations with cardio-metabolic traits. RESULTS: We selected 2549 CpG sites and 443 gene expression probes associated with current versus never smokers, from the largest epigenome-wide association study and transcriptome-wide association study to date. We examined three-way associations, including CpG versus gene expression, cardio-metabolic trait versus CpG, and cardio-metabolic trait versus gene expression, in the Rotterdam study. Subsequently, we replicated our findings in The Cooperative Health Research in the Region of Augsburg (KORA) study. After correction for multiple testing, we identified both cis- and trans-expression quantitative trait methylation (eQTM) associations in blood. Specifically, we found 1224 smoking-related CpGs associated with at least one of the 443 gene expression probes, and 200 smoking-related gene expression probes to be associated with at least one of the 2549 CpGs. Out of these, 109 CpGs and 27 genes were associated with at least one cardio-metabolic trait in the Rotterdam Study. We were able to replicate the associations with cardio-metabolic traits of 26 CpGs and 19 genes in the KORA study. Furthermore, we identified a three-way association of triglycerides with two CpGs and two genes (GZMA; CLDND1), and BMI with six CpGs and two genes (PID1; LRRN3). Finally, our results revealed the mediation effect of cg03636183 (F2RL3), cg06096336 (PSMD1), cg13708645 (KDM2B), and cg17287155 (AHRR) within the association between smoking and LRRN3 expression. CONCLUSIONS: Our study indicates that smoking-related changes in DNA methylation and gene expression are associated with cardio-metabolic risk factors. These findings may provide additional insights into the molecular mechanisms linking smoking to the development of CVD.

Accelerated epigenetic aging as a risk factor for chronic obstructive pulmonary disease and decreased lung function in two prospective cohort studies.

Chronic obstructive pulmonary disease (COPD) is a frequent diagnosis in older individuals and contributor to global morbidity and mortality. Given the link between lung disease and aging, we need to understand how molecular indicators of aging relate to lung function and disease. Using data from the population-based KORA (Cooperative Health Research in the Region of Augsburg) surveys, we associated baseline epigenetic (DNA methylation) age acceleration with incident COPD and lung function. Models were adjusted for age, sex, smoking, height, weight, and baseline lung disease as appropriate. Associations were replicated in the Normative Aging Study. Of 770 KORA participants, 131 developed incident COPD over 7 years. Baseline accelerated epigenetic aging was significantly associated with incident COPD. The change in age acceleration (follow-up - baseline) was more strongly associated with COPD than baseline aging alone. The association between the change in age acceleration between baseline and follow-up and incident COPD replicated in the Normative Aging Study. Associations with spirometric lung function parameters were weaker than those with COPD, but a meta-analysis of both cohorts provide suggestive evidence of associations. Accelerated epigenetic aging, both baseline measures and changes over time, may be a risk factor for COPD and reduced lung function.

Validated inference of smoking habits from blood with a finite DNA methylation marker set.

Inferring a person's smoking habit and history from blood is relevant for complementing or replacing self-reports in epidemiological and public health research, and for forensic applications. However, a finite DNA methylation marker set and a validated statistical model based on a large dataset are not yet available. Employing 14 epigenome-wide association studies for marker discovery, and using data from six population-based cohorts (N = 3764) for model building, we identified 13 CpGs most suitable for inferring smoking versus non-smoking status from blood with a cumulative Area Under the Curve (AUC) of 0.901. Internal fivefold cross-validation yielded an average AUC of 0.897 ± 0.137, while external model validation in an independent population-based cohort (N = 1608) achieved an AUC of 0.911. These 13 CpGs also provided accurate inference of current (average AUCcrossvalidation 0.925 ± 0.021, AUCexternalvalidation0.914), former (0.766 ± 0.023, 0.699) and never smoking (0.830 ± 0.019, 0.781) status, allowed inferring pack-years in current smokers (10 pack-years 0.800 ± 0.068, 0.796; 15 pack-years 0.767 ± 0.102, 0.752) and inferring smoking cessation time in former smokers (5 years 0.774 ± 0.024, 0.760; 10 years 0.766 ± 0.033, 0.764; 15 years 0.767 ± 0.020, 0.754). Model application to children revealed highly accurate inference of the true non-smoking status (6 years of age: accuracy 0.994, N = 355; 10 years: 0.994, N = 309), suggesting prenatal and passive smoking exposure having no impact on model applications in adults. The finite set of DNA methylation markers allow accurate inference of smoking habit, with comparable accuracy as plasma cotinine use, and smoking history from blood, which we envision becoming useful in epidemiology and public health research, and in medical and forensic applications.

Socioeconomic position, lifestyle habits and biomarkers of epigenetic aging: a multi-cohort analysis.

Differences in health status by socioeconomic position (SEP) tend to be more evident at older ages, suggesting the involvement of a biological mechanism responsive to the accumulation of deleterious exposures across the lifespan. DNA methylation (DNAm) has been proposed as a biomarker of biological aging that conserves memory of endogenous and exogenous stress during life.We examined the association of education level, as an indicator of SEP, and lifestyle-related variables with four biomarkers of age-dependent DNAm dysregulation: the total number of stochastic epigenetic mutations (SEMs) and three epigenetic clocks (Horvath, Hannum and Levine), in 18 cohorts spanning 12 countries.The four biological aging biomarkers were associated with education and different sets of risk factors independently, and the magnitude of the effects differed depending on the biomarker and the predictor. On average, the effect of low education on epigenetic aging was comparable with those of other lifestyle-related risk factors (obesity, alcohol intake), with the exception of smoking, which had a significantly stronger effect.Our study shows that low education is an independent predictor of accelerated biological (epigenetic) aging and that epigenetic clocks appear to be good candidates for disentangling the biological pathways underlying social inequalities in healthy aging and longevity.

Association of maternal prenatal smoking GFI1-locus and cardio-metabolic phenotypes in 18,212 adults.

BACKGROUND: DNA methylation at the GFI1-locus has been repeatedly associated with exposure to smoking from the foetal period onwards. We explored whether DNA methylation may be a mechanism that links exposure to maternal prenatal smoking with offspring's adult cardio-metabolic health. METHODS: We meta-analysed the association between DNA methylation at GFI1-locus with maternal prenatal smoking, adult own smoking, and cardio-metabolic phenotypes in 22 population-based studies from Europe, Australia, and USA (n = 18,212). DNA methylation at the GFI1-locus was measured in whole-blood. Multivariable regression models were fitted to examine its association with exposure to prenatal and own adult smoking. DNA methylation levels were analysed in relation to body mass index (BMI), waist circumference (WC), fasting glucose (FG), high-density lipoprotein cholesterol (HDL-C), triglycerides (TG), diastolic, and systolic blood pressure (BP). FINDINGS: Lower DNA methylation at three out of eight GFI1-CpGs was associated with exposure to maternal prenatal smoking, whereas, all eight CpGs were associated with adult own smoking. Lower DNA methylation at cg14179389, the strongest maternal prenatal smoking locus, was associated with increased WC and BP when adjusted for sex, age, and adult smoking with Bonferroni-corrected P < 0·012. In contrast, lower DNA methylation at cg09935388, the strongest adult own smoking locus, was associated with decreased BMI, WC, and BP (adjusted 1 × 10-7 < P < 0.01). Similarly, lower DNA methylation at cg12876356, cg18316974, cg09662411, and cg18146737 was associated with decreased BMI and WC (5 × 10-8 < P < 0.001). Lower DNA methylation at all the CpGs was consistently associated with higher TG levels. INTERPRETATION: Epigenetic changes at the GFI1 were linked to smoking exposure in-utero/in-adulthood and robustly associated with cardio-metabolic risk factors. FUND: European Union's Horizon 2020 research and innovation programme under grant agreement no. 633595 DynaHEALTH.

Novel DNA Methylation Sites Influence GPR15 Expression in Relation to Smoking.

Smoking is a major risk factor for cardiovascular diseases and has been implicated in the regulation of the G protein-coupled receptor 15 (GPR15) by affecting CpG methylation. The G protein-coupled receptor 15 is involved in angiogenesis and inflammation. An effect on GPR15 gene regulation has been shown for the CpG site CpG3.98251294. We aimed to analyze the effect of smoking on GPR15 expression and methylation sites spanning the GPR15 locus. DNA methylation of nine GPR15 CpG sites was measured in leukocytes from 1291 population-based individuals using the EpiTYPER. Monocytic GPR15 expression was measured by qPCR at baseline and five-years follow up. GPR15 gene expression was upregulated in smokers (beta (ß) = -2.699, p-value (p) = 1.02 × 10-77) and strongly correlated with smoking exposure (ß = -0.063, p = 2.95 × 10-34). Smoking cessation within five years reduced GPR15 expression about 19% (p = 9.65 × 10-5) with decreasing GPR15 expression over time (ß = 0.031, p = 3.81 × 10-6). Additionally, three novel CpG sites within GPR15 affected by smoking were identified. For CpG3.98251047, DNA methylation increased steadily after smoking cessation (ß = 0.123, p = 1.67 × 10-3) and strongly correlated with changes in GPR15 expression (ß = 0.036, p = 4.86 × 10-5). Three novel GPR15 CpG sites were identified in relation to smoking and GPR15 expression. Our results provide novel insights in the regulation of GPR15, which possibly linked smoking to inflammation and disease progression.

Association of Methylation Signals With Incident Coronary Heart Disease in an Epigenome-Wide Assessment of Circulating Tumor Necrosis Factor α.

Importance: Tumor necrosis factor α (TNF-α) is a proinflammatory cytokine with manifold consequences for mammalian pathophysiology, including cardiovascular disease. A deeper understanding of TNF-α biology may enhance treatment precision. Objective: To conduct an epigenome-wide analysis of blood-derived DNA methylation and TNF-α levels and to assess the clinical relevance of findings. Design, Setting, and Participants: This meta-analysis assessed epigenome-wide associations in circulating TNF-α concentrations from 5 cohort studies and 1 interventional trial, with replication in 3 additional cohort studies. Follow-up analyses investigated associations of identified methylation loci with gene expression and incident coronary heart disease; this meta-analysis included 11 461 participants who experienced 1895 coronary events. Exposures: Circulating TNF-α concentration. Main Outcomes and Measures: DNA methylation at approximately 450 000 loci, neighboring DNA sequence variation, gene expression, and incident coronary heart disease. Results: The discovery cohort included 4794 participants, and the replication study included 816 participants (overall mean [SD] age, 60.7 [8.5] years). In the discovery stage, circulating TNF-α levels were associated with methylation of 7 cytosine-phosphate-guanine (CpG) sites, 3 of which were located in or near DTX3L-PARP9 at cg00959259 (ß [SE] = -0.01 [0.003]; P = 7.36 × 10-8), cg08122652 (ß [SE] = -0.008 [0.002]; P = 2.24 × 10-7), and cg22930808(ß [SE] = -0.01 [0.002]; P = 6.92 × 10-8); NLRC5 at cg16411857 (ß [SE] = -0.01 [0.002]; P = 2.14 × 10-13) and cg07839457 (ß [SE] = -0.02 [0.003]; P = 6.31 × 10-10); or ABO, at cg13683939 (ß [SE] = 0.04 [0.008]; P = 1.42 × 10-7) and cg24267699 (ß [SE] = -0.009 [0.002]; P = 1.67 × 10-7), after accounting for multiple testing. Of these, negative associations between TNF-α concentration and methylation of 2 loci in NLRC5 and 1 in DTX3L-14 PARP9 were replicated. Replicated TNF-α-linked CpG sites were associated with 9% to 19% decreased risk of incident coronary heart disease per 10% higher methylation per CpG site (cg16411857: hazard ratio [HR], 0.86; 95% CI, 0.78-1.95; P = .003; cg07839457: HR, 0.89; 95% CI, 0.80-0.94; P = 3.1 × 10-5; cg00959259: HR, 0.91; 95% CI, 0.84-0.97; P = .002; cg08122652: HR, 0.81; 95% CI, 0.74-0.89; P = 2.0 × 10-5). Conclusions and Relevance: We identified and replicated novel epigenetic correlates of circulating TNF-α concentration in blood samples and linked these loci to coronary heart disease risk, opening opportunities for validation and therapeutic applications.

IgG glycosylation and DNA methylation are interconnected with smoking.

BACKGROUND: Glycosylation is one of the most common post-translation modifications with large influences on protein structure and function. The effector function of immunoglobulin G (IgG) alters between pro- and anti-inflammatory, based on its glycosylation. IgG glycan synthesis is highly complex and dynamic. METHODS: With the use of two different analytical methods for assessing IgG glycosylation, we aim to elucidate the link between DNA methylation and glycosylation of IgG by means of epigenome-wide association studies. In total, 3000 individuals from 4 cohorts were analyzed. RESULTS: The overlap of the results from the two glycan measurement panels yielded DNA methylation of 7 CpG-sites on 5 genomic locations to be associated with IgG glycosylation: cg25189904 (chr.1, GNG12); cg05951221, cg21566642 and cg01940273 (chr.2, ALPPL2); cg05575921 (chr.5, AHRR); cg06126421 (6p21.33); and cg03636183 (chr.19, F2RL3). Mediation analyses with respect to smoking revealed that the effect of smoking on IgG glycosylation may be at least partially mediated via DNA methylation levels at these 7 CpG-sites. CONCLUSION: Our results suggest the presence of an indirect link between DNA methylation and IgG glycosylation that may in part capture environmental exposures. GENERAL SIGNIFICANCE: An epigenome-wide analysis conducted in four population-based cohorts revealed an association between DNA methylation and IgG glycosylation patterns. Presumably, DNA methylation mediates the effect of smoking on IgG glycosylation.

The dynamics of smoking-related disturbed methylation: a two time-point study of methylation change in smokers, non-smokers and former smokers.

BACKGROUND: The evidence for epigenome-wide associations between smoking and DNA methylation continues to grow through cross-sectional studies. However, few large-scale investigations have explored the associations using observations for individuals at multiple time-points. Here, through the use of the Illumina 450K BeadChip and data collected at two time-points separated by approximately 7 years, we investigate changes in methylation over time associated with quitting smoking or remaining a former smoker, and those associated with continued smoking. RESULTS: Our results indicate that after quitting smoking the most rapid reversion of altered methylation occurs within the first two decades, with reversion rates related to the initial differences in methylation. For 52 CpG sites, the change in methylation from baseline to follow-up is significantly different for former smokers relative to the change for never smokers (lowest p-value 3.61 x 10-39 for cg26703534, gene AHRR). Most of these sites' respective regions have been previously implicated in smoking-associated diseases. Despite the early rapid change, dynamism of methylation appears greater in former smokers vs never smokers even four decades after cessation. Furthermore, our study reveals the heterogeneous effect of continued smoking: the methylation levels of some loci further diverge between smokers and non-smokers, while others re-approach. Though intensity of smoking habit appears more significant than duration, results remain inconclusive. CONCLUSIONS: This study improves the understanding of the dynamic link between cigarette smoking and methylation, revealing the continued fluctuation of methylation levels decades after smoking cessation and demonstrating that continuing smoking can have an array of effects. The results can facilitate insights into the molecular mechanisms behind smoking-induced disturbed methylation, improving the possibility for development of biomarkers of past smoking behavior and increasing the understanding of the molecular path from exposure to disease.

Are Epigenetic Factors Implicated in Chronic Widespread Pain?

BACKGROUND: Chronic widespread musculoskeletal pain (CWP) is the cardinal symptom of fibromyalgia and affects about 12% of the general population. Familial aggregation of CWP has been repeatedly demonstrated with estimated heritabilities of around 50%, indicating a genetic susceptibility. The objective of the study was to explore genome-wide disease-differentially methylated positions (DMPs) for chronic widespread pain (CWP) in a sample of unrelated individuals and a subsample of discordant monozygotic (MZ) twins. METHODOLOGY/PRINCIPLE FINDINGS: A total of N = 281 twin individuals from the TwinsUK registry, including N = 33 MZ twins discordant for self-reported CWP, were part of the discovery sample. The replication sample included 729 men and 756 women from a subsample of the KORA S4 survey-an independent population-based cohort from Southern Germany. Epigenome-wide analysis of DNA methylation was conducted using the Illumina Infinium HumanMethylation 450 DNA BeadChip in both the discovery and replication sample. Of our 40 main loci that were carried forward for replication, three CPGs reached significant p-values in the replication sample, including malate dehydrogenase 2 (MDH2; p-value 0.017), tetranectin (CLEC3B; p-value 0.039), and heat shock protein beta-6 (HSPB6; p-value 0.016). The associations between the collagen type I, alpha 2 chain (COL1A2) and monoamine oxidase B (MAOB) observed in the discovery sample-both of which have been previously reported to be biological candidates for pain-could not be replicated. CONCLUSION/SIGNIFICANCE: Our results may serve as a starting point to encourage further investigation in large and independent population-based cohorts of DNA methylation and other epigenetic changes as possible disease mechanisms in CWP. Ultimately, understanding the key mechanisms underlying CWP may lead to new treatments and inform clinical practice.

Epigenetic Signatures of Cigarette Smoking.

BACKGROUND: DNA methylation leaves a long-term signature of smoking exposure and is one potential mechanism by which tobacco exposure predisposes to adverse health outcomes, such as cancers, osteoporosis, lung, and cardiovascular disorders. METHODS AND RESULTS: To comprehensively determine the association between cigarette smoking and DNA methylation, we conducted a meta-analysis of genome-wide DNA methylation assessed using the Illumina BeadChip 450K array on 15 907 blood-derived DNA samples from participants in 16 cohorts (including 2433 current, 6518 former, and 6956 never smokers). Comparing current versus never smokers, 2623 cytosine-phosphate-guanine sites (CpGs), annotated to 1405 genes, were statistically significantly differentially methylated at Bonferroni threshold of P<1×10-7 (18 760 CpGs at false discovery rate <0.05). Genes annotated to these CpGs were enriched for associations with several smoking-related traits in genome-wide studies including pulmonary function, cancers, inflammatory diseases, and heart disease. Comparing former versus never smokers, 185 of the CpGs that differed between current and never smokers were significant P<1×10-7 (2623 CpGs at false discovery rate <0.05), indicating a pattern of persistent altered methylation, with attenuation, after smoking cessation. Transcriptomic integration identified effects on gene expression at many differentially methylated CpGs. CONCLUSIONS: Cigarette smoking has a broad impact on genome-wide methylation that, at many loci, persists many years after smoking cessation. Many of the differentially methylated genes were novel genes with respect to biological effects of smoking and might represent therapeutic targets for prevention or treatment of tobacco-related diseases. Methylation at these sites could also serve as sensitive and stable biomarkers of lifetime exposure to tobacco smoke.

Association between DNA Methylation in Whole Blood and Measures of Glucose Metabolism: KORA F4 Study.

Epigenetic regulation has been postulated to affect glucose metabolism, insulin sensitivity and the risk of type 2 diabetes. Therefore, we performed an epigenome-wide association study for measures of glucose metabolism in whole blood samples of the population-based Cooperative Health Research in the Region of Augsburg F4 study using the Illumina HumanMethylation 450 BeadChip. We identified a total of 31 CpG sites where methylation level was associated with measures of glucose metabolism after adjustment for age, sex, smoking, and estimated white blood cell proportions and correction for multiple testing using the Benjamini-Hochberg (B-H) method (four for fasting glucose, seven for fasting insulin, 25 for homeostasis model assessment-insulin resistance [HOMA-IR]; B-H-adjusted p-values between 9.2x10(-5) and 0.047). In addition, DNA methylation at cg06500161 (annotated to ABCG1) was associated with all the aforementioned phenotypes and 2-hour glucose (B-H-adjusted p-values between 9.2x10(-5) and 3.0x10(-3)). Methylation status of additional three CpG sites showed an association with fasting insulin only after additional adjustment for body mass index (BMI) (B-H-adjusted p-values = 0.047). Overall, effect strengths were reduced by around 30% after additional adjustment for BMI, suggesting that this variable has an influence on the investigated phenotypes. Furthermore, we found significant associations between methylation status of 21 of the aforementioned CpG sites and 2-hour insulin in a subset of samples with seven significant associations persisting after additional adjustment for BMI. In a subset of 533 participants, methylation of the CpG site cg06500161 (ABCG1) was inversely associated with ABCG1 gene expression (B-H-adjusted p-value = 1.5x10(-9)). Additionally, we observed an enrichment of the top 1,000 CpG sites for diabetes-related canonical pathways using Ingenuity Pathway Analysis. In conclusion, our study indicates that DNA methylation and diabetes-related traits are associated and that these associations are partially BMI-dependent. Furthermore, the interaction of ABCG1 with glucose metabolism is modulated by epigenetic processes.

Genome-Wide Analysis of DNA Methylation and Fine Particulate Matter Air Pollution in Three Study Populations: KORA F3, KORA F4, and the Normative Aging Study.

BACKGROUND: Epidemiological studies have reported associations between particulate matter (PM) concentrations and cancer and respiratory and cardiovascular diseases. DNA methylation has been identified as a possible link but so far it has only been analyzed in candidate sites. OBJECTIVES: We studied the association between DNA methylation and short- and mid-term air pollution exposure using genome-wide data and identified potential biological pathways for additional investigation. METHODS: We collected whole blood samples from three independent studies-KORA F3 (2004-2005) and F4 (2006-2008) in Germany, and the Normative Aging Study (1999-2007) in the United States-and measured genome-wide DNA methylation proportions with the Illumina 450k BeadChip. PM concentration was measured daily at fixed monitoring stations and three different trailing averages were considered and regressed against DNA methylation: 2-day, 7-day and 28-day. Meta-analysis was performed to pool the study-specific results. RESULTS: Random-effect meta-analysis revealed 12 CpG (cytosine-guanine dinucleotide) sites as associated with PM concentration (1 for 2-day average, 1 for 7-day, and 10 for 28-day) at a genome-wide Bonferroni significance level (p ≤ 7.5E-8); 9 out of these 12 sites expressed increased methylation. Through estimation of I2 for homogeneity assessment across the studies, 4 of these sites (annotated in NSMAF, C1orf212, MSGN1, NXN) showed p > 0.05 and I2 < 0.5: the site from the 7-day average results and 3 for the 28-day average. Applying false discovery rate, p-value < 0.05 was observed in 8 and 1,819 additional CpGs at 7- and 28-day average PM2.5 exposure respectively. CONCLUSION: The PM-related CpG sites found in our study suggest novel plausible systemic pathways linking ambient PM exposure to adverse health effect through variations in DNA methylation. CITATION: Panni T, Mehta AJ, Schwartz JD, Baccarelli AA, Just AC, Wolf K, Wahl S, Cyrys J, Kunze S, Strauch K, Waldenberger M, Peters A. 2016. A genome-wide analysis of DNA methylation and fine particulate matter air pollution in three study populations: KORA F3, KORA F4, and the Normative Aging Study. Environ Health Perspect 124:983-990; http://dx.doi.org/10.1289/ehp.1509966.

Prenatal and early life influences on epigenetic age in children: a study of mother-offspring pairs from two cohort studies.

DNA methylation-based biomarkers of aging are highly correlated with actual age. Departures of methylation-estimated age from actual age can be used to define epigenetic measures of child development or age acceleration (AA) in adults. Very little is known about genetic or environmental determinants of these epigenetic measures of aging. We obtained DNA methylation profiles using Infinium HumanMethylation450 BeadChips across five time-points in 1018 mother-child pairs from the Avon Longitudinal Study of Parents and Children. Using the Horvath age estimation method, we calculated epigenetic age for these samples. AA was defined as the residuals from regressing epigenetic age on actual age. AA was tested for associations with cross-sectional clinical variables in children. We identified associations between AA and sex, birth weight, birth by caesarean section and several maternal characteristics in pregnancy, namely smoking, weight, BMI, selenium and cholesterol level. Offspring of non-drinkers had higher AA on average but this difference appeared to resolve during childhood. The associations between sex, birth weight and AA found in ARIES were replicated in an independent cohort (GOYA). In children, epigenetic AA measures are associated with several clinically relevant variables, and early life exposures appear to be associated with changes in AA during adolescence. Further research into epigenetic aging, including the use of causal inference methods, is required to better our understanding of aging.