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Chronic inflammation, marked by C-reactive protein, has been associated with changes in methylation, but the causal relationship is unclear. Here, the authors perform a Epigenome-wide association meta-analysis for C-reactive protein levels and find that these methylation changes are likely the consequence of inflammation and could contribute to disease.We performed a multi-ethnic Epigenome Wide Association study on 22,774 individuals to describe the DNA methylation signature of chronic low-grade inflammation as measured by C-Reactive protein (CRP). We find 1,511 independent differentially methylated loci associated with CRP. These CpG sites show correlation structures across chromosomes, and are primarily situated in euchromatin, depleted in CpG islands. These genomic loci are predominantly situated in transcription factor binding sites and genomic enhancer regions. Mendelian randomization analysis suggests altered CpG methylation is a consequence of increased blood CRP levels. Mediation analysis reveals obesity and smoking as important underlying driving factors for changed CpG methylation. Finally, we find that an activated CpG signature significantly increases the risk for cardiometabolic diseases and COPD.

The placenta is a central organ during early development, influencing trajectories of health and disease. DNA methylation (DNAm) studies of human placenta improve our understanding of how its function relates to disease risk. However, DNAm studies can be biased by cell type heterogeneity, so it is essential to control for this in order to reduce confounding and increase precision. Computational cell type deconvolution approaches have proven to be very useful for this purpose. For human placenta, however, an assessment of the performance of these estimation methods is still lacking. Here, we examine the performance of a newly available reference-based cell type estimation approach and compare it to an often-used reference-free cell type estimation approach, namely RefFreeEWAS, in placental genome-wide DNAm samples taken at birth and from chorionic villus biopsies early in pregnancy using three independent studies comprising over 1000 samples. We found both reference-free and reference-based estimated cell type proportions to have predictive value for DNAm, however, reference-based cell type estimation outperformed reference-free estimation for the majority of data sets. Reference-based cell type estimations mirror previous histological knowledge on changes in cell type proportions through gestation. Further, CpGs whose variation in DNAm was largely explained by reference-based estimated cell type proportions were in the proximity of genes that are highly tissue-specific for placenta. This was not the case for reference-free estimated cell type proportions. We provide a list of these CpGs as a resource to help researchers to interpret results of existing studies and improve future DNAm studies of human placenta.

Aims & methods: The aim of this study was to characterize the methylation level of a polymorphically imprinted gene, VTRNA2-1/nc886, in human populations and somatic tissues.48 datasets, consisting of more than 30 tissues and >30,000 individuals, were used. Results: nc886 methylation status is associated with twin status and ethnic background, but the variation between populations is limited. Monozygotic twin pairs present concordant methylation, whereas similar to 30% of dizygotic twin pairs present discordant methylation in the nc886 locus. The methylation levels of nc886 are uniform across somatic tissues, except in cerebellum and skeletal muscle. Conclusion: The nc886 imprint may be established in the oocyte, and, after implantation, the methylation status is stable, excluding a few specific tissues. Tweetable abstract Methylation status of a polymorphically imprinted gene, VTRNA2-1/nc886, is stable in human populations (48 cohorts, n > 30,000) and in somatic tissues, except in cerebellum and skeletal muscle. Twin data suggest it may already be established in the oocyte.

Background Birthweight reflects in utero exposures and later health evolution. Despite existing studies employing high-dimensional molecular measurements, the understanding of underlying mechanisms of birthweight remains limited. Methods To investigate the systems biology of birthweight, we cross-sectionally integrated the methylome, the transcriptome, the metabolome and a set of inflammatory proteins measured in cord blood samples, collected from four birth-cohorts (n = 489). We focused on two sets of 68 metabolites and 903 CpGs previously related to birthweight and investigated the correlation structures existing between these two sets and all other omic features via bipartite Pearson correlations. Results This dataset revealed that the set of metabolome and methylome signatures of birthweight have seven signals in common, including three metabolites [PC(34:2), plasmalogen PC(36:4)/PC(O-36:5), and a compound with m/z of 781.0545], two CpGs (on the DHCR24 and SC4MOL gene), and two proteins (periostin and CCL22). CCL22, a macrophage-derived chemokine has not been previously identified in relation to birthweight. Since the results of the omics integration indicated the central role of cholesterol metabolism, we explored the association of cholesterol levels in cord blood with birthweight in the ENVIRONAGE cohort (n = 1097), finding that higher birthweight was associated with increased high-density lipoprotein cholesterol and that high-density lipoprotein cholesterol was lower in small versus large for gestational age newborns. Conclusions Our data suggests that an integration of different omic-layers in addition to single omics studies is a useful approach to generate new hypotheses regarding biological mechanisms. CCL22 and cholesterol metabolism in cord blood play a mechanistic role in birthweight., Highlights • Using multiple omics, we provide an unprecedented window into the biological processes underlying birthweight. • We identified molecular signals never previously linked to birthweight, e.g. gene expression of JAK3 and chemokine CCL22. • Our data suggested that cholesterol and related metabolic pathways are related to birthweight. • The identified signals may create a molecular basis for the onset of health outcomes associated with birthweight variation.

Background Children born extremely preterm are at heightened risk for intellectual and social impairment, including Autism Spectrum Disorder (ASD). There is increasing evidence for a key role of the placenta in prenatal developmental programming, suggesting that the placenta may, in part, contribute to origins of neurodevelopmental outcomes. Methods We examined associations between placental transcriptomic and epigenomic profiles and assessed their ability to predict intellectual and social impairment at age 10 years in 379 children from the Extremely Low Gestational Age Newborn (ELGAN) cohort. Assessment of intellectual ability (IQ) and social function was completed with the Differential Ability Scales-II and Social Responsiveness Scale (SRS), respectively. Examining IQ and SRS allows for studying ASD risk beyond the diagnostic criteria, as IQ and SRS are continuous measures strongly correlated with ASD. Genome-wide mRNA, CpG methylation and miRNA were assayeds with the Illumina Hiseq 2500, HTG EdgeSeq miRNA Whole Transcriptome Assay, and Illumina EPIC/850 K array, respectively. We conducted genome-wide differential analyses of placental mRNA, miRNA, and CpG methylation data. These molecular features were then integrated for a predictive analysis of IQ and SRS outcomes using kernel aggregation regression. We lastly examined associations between ASD and the multi-omic-predicted component of IQ and SRS. Results Genes with important roles in neurodevelopment and placental tissue organization were associated with intellectual and social impairment. Kernel aggregations of placental multi-omics strongly predicted intellectual and social function, explaining approximately 8% and 12% of variance in SRS and IQ scores via cross-validation, respectively. Predicted in-sample SRS and IQ showed significant positive and negative associations with ASD case–control status. Limitations The ELGAN cohort comprises children born pre-term, and generalization may be affected by unmeasured confounders associated with low gestational age. We conducted external validation of predictive models, though the sample size (N = 49) and the scope of the available out-sample placental dataset are limited. Further validation of the models is merited. Conclusions Aggregating information from biomarkers within and among molecular data types improves prediction of complex traits like social and intellectual ability in children born extremely preterm, suggesting that traits within the placenta-brain axis may be omnigenic.

Background: Low lung function has been associated with increased body mass index (BMI). The aim of this study was to investigate whether the effect of BMI on lung function is mediated by DNA methylation. Methods: We used individual data from 285,495 participants in four population-based cohorts: the European Community Respiratory Health Survey, the Northern Finland Birth Cohort 1966, the Swiss Study on Air Pollution and Lung Disease in Adults, and the UK Biobank. We carried out Mendelian randomisation (MR) analyses in two steps using a two-sample approach with SNPs as instrumental variables (IVs) in each step. In step 1 MR, we estimated the causal effect of BMI on peripheral blood DNA methylation (measured at genome-wide level) using 95 BMI-associated SNPs as IVs. In step 2 MR, we estimated the causal effect of DNA methylation on FEV1, FVC, and FEV1/FVC using two SNPs acting as methQTLs occurring close (in cis) to CpGs identified in the first step. These analyses were conducted after exclusion of weak IVs (F statistic < 10) and MR estimates were derived using the Wald ratio, with standard error from the delta method. Individuals whose data were used in step 1 were not included in step 2. Results: In step 1, we found that BMI might have a small causal effect on DNA methylation levels (less than 1% change in methylation per 1 kg/m2 increase in BMI) at two CpGs (cg09046979 and cg12580248). In step 2, we found no evidence of a causal effect of DNA methylation at cg09046979 on lung function. We could not estimate the causal effect of DNA methylation at cg12580248 on lung function as we could not find publicly available data on the association of this CpG with SNPs. Conclusions: To our knowledge, this is the first paper to report the use of a two-step MR approach to assess the role of DNA methylation in mediating the effect of a non-genetic factor on lung function. Our findings do not support a mediating effect of DNA methylation in the association of lung function with BMI. This work was conducted within the Ageing Lungs in European Cohorts (ALEC) project and received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 633212. The funders of this study had no role in study design, data analysis and interpretation of results, or writing of the manuscript. The ECRHS was supported by a contract from the European Commission (018996), Fondo de Investigación Sanitaria (91/0016–060-05/E, 92/0319, 93/0393, 97/0035–01, 99/0034–01 and 99/0034–02), Hospital General de Albacete, Hospital General Ramón Jiménez, Consejería de Sanidad del Principado de Asturias, CIRIT (1997SGR 00079, 1999SGR 00241), and Servicio Andaluz de Salud, SEPAR, Public Health Service (R01 HL62633–01), RCESP (C03/09), Red RESPIRA (C03/011), Basque Health Department, Swiss National Science Foundation, Swiss Federal Office for Education and Science, Swiss National Accident Insurance Fund (SUVA), GSF-National Research Centre for Environment and Health, Deutsche Forschungsgemeinschaft (DFG) (FR 1526/1–1, MA 711/4–1), Programme Hospitalier de Recherche Clinique-DRC de Grenoble 2000 no. 2610, Ministry of Health, Direction de la Recherche Clinique, Ministere de l’Emploi et de la Solidarite, Direction Generale de la Sante, CHU de Grenoble, Comite des Maladies Respiratoires de l’Isere. UCB-Pharma (France), Aventis (France), Glaxo France. Estonian Science Foundation, and Asthma UK (formerly known as National Asthma Campaign UK). The NFBC resource has been supported by grants from the Academy of Finland (project grants 104781, 120315, 129269, 1114194, 24300796, Center of Excellence in Complex Disease Genetics and SALVE), University Hospital Oulu, Biocenter, University of Oulu, Finland (75617), NHLBI grant 5R01HL087679–02 (1RL1MH083268–01), NIH/NIMH (5R01MH63706:02), ENGAGE project and grant agreement HEALTH-F4–2007-201413, EU FP7 EurHEALTHAgeing − 277849, the Medical Research Council, UK (G0500539, G0600705, G1002319, PrevMetSyn/SALVE) and the MRC, Centenary Early Career Award. H2020 DynaHEALTH (European Union’s Horizon 2020 research and innovation programme under grant agreement No 633595); Exposomic, Genomic and Epigenomic Approach to Prediction of Metabolic and Cardiorespiratory function and Ill-Health (EGEA), Academy of Finland, Grant No 285547; ALEC Study (funded by the European Union’s Horizon 2020 Research and Innovation programme under grant agreement No. 633212); H2020 / Marie Skłodowska-Curie Actions, CAPICE (Marie Curie Grant agreement Number 721567); National Public Health Institute, Biomedicum Helsinki, Finland. The SAPALDIA study was funded by the Swiss National Science Foundation (grants no 33CS30–148470/1&2, 33CSCO-134276/1, 33CSCO-108796, 324730_135673, 3247BO-104283, 3247BO-104288, 3247BO-104284, 3247–065896, 3100–059302, 3200–052720, 3200–042532, 4026–028099, PMPDP3_129021/1, PMPDP3_141671/1), the Federal Office for the Environment, the Federal Office of Public Health, the Federal Office of Roads and Transport, the canton’s government of Aargau, Basel-Stadt, Basel-Land, Geneva, Luzern, Ticino, Valais, and Zürich, the Swiss Lung League, the canton’s Lung League of Basel Stadt/ Basel Landschaft, Geneva, Ticino, Valais, Graubünden and Zurich, Stiftung ehemals Bündner Heilstätten, SUVA, Freiwillige Akademische Gesellschaft, UBS Wealth Foundation, Talecris Biotherapeutics GmbH, Abbott Diagnostics, European Commission 018996 (GABRIEL), Wellcome Trust WT 084703MA, Exposomics EC FP7 grant (Grant agreement No: 308610).

Osteoporosis is mainly characterized by low bone mineral density (BMD) and is an increasingly serious public health concern. DNA methylation is a major epigenetic mechanism that may contribute to the variation in BMD and may mediate the effects of genetic and environmental factors of osteoporosis. In this study, we performed an epigenome-wide DNA methylation analysis in peripheral blood monocytes of 118 Caucasian women with extreme BMD values. Further, we developed and implemented a novel analytical framework that integrates Mendelian randomization with genetic fine mapping and colocalization to evaluate the causal relationships between DNA methylation and BMD phenotype. We identified 2,188 differentially methylated CpGs (DMCs) between the low and high BMD groups and distinguished 30 DMCs that may mediate the genetic effects on BMD. The causal relationship was further confirmed by eliminating the possibility of horizontal pleiotropy, linkage effect and reverse causality. The fine-mapping analysis determined 25 causal variants that are most likely to affect the methylation levels at these mediator DMCs. The majority of the causal methylation quantitative loci and DMCs reside within cell type-specific histone mark peaks, enhancers, promoters, promoter flanking regions and CTCF binding sites, supporting the regulatory potentials of these loci. The established causal pathways from genetic variant to BMD phenotype mediated by DNA methylation provide a gene list to aid in designing future functional studies and lead to a better understanding of the genetic and epigenetic mechanisms underlying the variation of BMD.

AIMS/HYPOTHESIS: Epigenetic mechanisms may play an important role in the aetiology of type 2 diabetes. Recent epigenome-wide association studies (EWASs) identified several DNA methylation markers associated with type 2 diabetes, fasting glucose and HbA1c levels. Here we present a systematic review of these studies and attempt to replicate the CpG sites (CpGs) with the most significant associations from these EWASs in a case-control sample of the Lifelines study.METHODS: We performed a systematic literature search in PubMed and EMBASE for EWASs to test the association between DNA methylation and type 2 diabetes and/or glycaemic traits and reviewed the search results. For replication purposes we selected 100 unique CpGs identified in peripheral blood, pancreas, adipose tissue and liver from 15 EWASs, using study-specific Bonferroni-corrected significance thresholds. Methylation data (Illumina 450K array) in whole blood from 100 type 2 diabetic individuals and 100 control individuals from the Lifelines study were available. Multivariate linear models were used to examine the associations of the specific CpGs with type 2 diabetes and glycaemic traits.RESULTS: From the 52 CpGs identified in blood and selected for replication, 15 CpGs showed nominally significant associations with type 2 diabetes in the Lifelines sample (p < 0.05). The results for five CpGs (in ABCG1, LOXL2, TXNIP, SLC1A5 and SREBF1) remained significant after a stringent multiple-testing correction (changes in methylation from -3% up to 3.6%, p < 0.0009). All associations were directionally consistent with the original EWAS results. None of the selected CpGs from the tissue-specific EWASs were replicated in our methylation data from whole blood. We were also unable to replicate any of the CpGs associated with HbA1c levels in the healthy control individuals of our sample, while two CpGs (in ABCG1 and CCDC57) for fasting glucose were replicated at a nominal significance level (p < 0.05).CONCLUSIONS/INTERPRETATION: A number of differentially methylated CpGs reported to be associated with type 2 diabetes in the EWAS literature were replicated in blood and show promise for clinical use as disease biomarkers. However, more prospective studies are needed to support the robustness of these findings.

Aims/hypothesis Epigenetic mechanisms may play an important role in the aetiology of type 2 diabetes. Recent epigenome-wide association studies (EWASs) identified several DNA methylation markers associated with type 2 diabetes, fasting glucose and HbA1c levels. Here we present a systematic review of these studies and attempt to replicate the CpG sites (CpGs) with the most significant associations from these EWASs in a case–control sample of the Lifelines study. Methods We performed a systematic literature search in PubMed and EMBASE for EWASs to test the association between DNA methylation and type 2 diabetes and/or glycaemic traits and reviewed the search results. For replication purposes we selected 100 unique CpGs identified in peripheral blood, pancreas, adipose tissue and liver from 15 EWASs, using study-specific Bonferroni-corrected significance thresholds. Methylation data (Illumina 450K array) in whole blood from 100 type 2 diabetic individuals and 100 control individuals from the Lifelines study were available. Multivariate linear models were used to examine the associations of the specific CpGs with type 2 diabetes and glycaemic traits. Results From the 52 CpGs identified in blood and selected for replication, 15 CpGs showed nominally significant associations with type 2 diabetes in the Lifelines sample (p

A plethora of environmental and behavioral factors interact, resulting in changes in gene expression and providing a basis for the development and progression of cardiovascular diseases. Heterogeneity in gene expression responses among cells and individuals involves epigenetic mechanisms. Advancing technology allowing genome-scale interrogation of epigenetic marks provides a rapidly expanding view of the complexity and diversity of the epigenome. In this review, the authors discuss the expanding landscape of epigenetic modifications and highlight their importance for future understanding of disease. The epigenome provides a mechanistic link between environmental exposures and gene expression profiles ultimately leading to disease. The authors discuss the current evidence for transgenerational epigenetic inheritance and summarize the data linking epigenetics to cardiovascular disease. Furthermore, the potential targets provided by the epigenome for the development of future diagnostics, preventive strategies, and therapy for cardiovascular disease are reviewed. Finally, the authors provide some suggestions for future directions. (C) 2017 by the American College of Cardiology Foundation.

Background One problem that plagues epigenome-wide association studies is the potential confounding due to cell mixtures when purified target cells are not available. Reference-free adjustment of cell mixtures has become increasingly popular due to its flexibility and simplicity. However, existing methods are still not optimal: increased false positive rates and reduced statistical power have been observed in many scenarios. Methods We develop SmartSVA, an optimized surrogate variable analysis (SVA) method, for fast and robust reference-free adjustment of cell mixtures. SmartSVA corrects the limitation of traditional SVA under highly confounded scenarios by imposing an explicit convergence criterion and improves the computational efficiency for large datasets. Results Compared to traditional SVA, SmartSVA achieves an order-of-magnitude speedup and better false positive control. It protects the signals when capturing the cell mixtures, resulting in significant power increase while controlling for false positives. Through extensive simulations and real data applications, we demonstrate a better performance of SmartSVA than the existing methods. Conclusions SmartSVA is a fast and robust method for reference-free adjustment of cell mixtures for epigenome-wide association studies. As a general method, SmartSVA can be applied to other genomic studies to capture unknown sources of variability. Electronic supplementary material The online version of this article (doi:10.1186/s12864-017-3808-1) contains supplementary material, which is available to authorized users.

Aim: Whole-blood DNA methylation depends on the underlying leukocyte composition and confounding hereby is a major concern in epigenome-wide association studies. Cell counts are often missing or may not be feasible. Computational approaches estimate leukocyte composition from DNA methylation based on reference datasets of purified leukocytes. We explored the possibility to train such a model on whole-blood DNA methylation and cell counts without the need for purification. Materials & methods: Using whole-blood DNA methylation and corresponding five-part cell counts from 2445 participants from the London Life Sciences Prospective Population Study, a model was trained on a subset of 175 subjects and evaluated on the remaining. Results: Correlations between cell counts and estimated cell proportions were high (neutrophils 0.85, eosinophils 0.88, basophils 0.02, lymphocytes 0.84, monocytes 0.55) and estimated proportions explained more variance in whole-blood DNA methylation levels than counts. Conclusion: Our model provided precise estimates for the common cell types.

BACKGROUND: Epigenetic signatures in the nasal epithelium, which is a primary interface with the environment and an accessible proxy for the bronchial epithelium, might provide insights into mechanisms of allergic disease. OBJECTIVE: We aimed to identify and interpret methylation signatures in nasal epithelial brushes associated with rhinitis and asthma. METHODS: Nasal epithelial brushes were obtained from 455 children at the 16 year follow-up of the Dutch PIAMA birth cohort study. Epigenome-wide association studies (EWAS) were performed on asthma, rhinitis and asthma and/or rhinitis (AsRh) using logistic regression, and top results were replicated in two independent cohorts of African American and Puerto Rican children. Significant CpG sites (CpGs) were related to environmental exposures (pets, active and passive smoking and molds) during secondary school, and correlated to gene expression by RNA-sequencing (n=244). RESULTS: The EWAS identified CpGs significantly associated with rhinitis (n=81) and AsRh (n=75), but not with asthma. We significantly replicated 62 /81 CpGs with rhinitis, and 60/75 with AsRh, as well as one CpG with asthma. Methylation of cg03565274 was negatively associated with AsRh, and positively associated with pets exposure during secondary school. DNA methylation signals associated with AsRh were mainly driven by specific IgE positive subjects. DNA methylation related to gene transcripts that were enriched for immune pathways, and expressed in immune and epithelial cells. Nasal CpGs performed well in predicting AsRh. CONCLUSIONS: We identified replicable DNA methylation profiles of asthma and rhinitis in nasal brushes. Pets exposure may affect nasal epithelial methylation in relation to asthma and rhinitis. CLINICAL IMPLICATIONS: Nasal DNA methylation profiles may serve as biomarker of asthma and rhinitis, and can be used across different populations to predict the presence of asthma and/or rhinitis in children.

Despite existing reports on differential DNA methylation in type 2 diabetes (T2D) and obesity, our understanding of its functional relevance remains limited. Here we show the effect of differential methylation in the early phases of T2D pathology by a blood-based epigenome-wide association study of 4808 non-diabetic Europeans in the discovery phase and 11,750 individuals in the replication. We identify CpGs in LETM1, RBM20, IRS2, MAN2A2 and the 1q25.3 region associated with fasting insulin, and in FCRL6, SLAMF1, APOBEC3H and the 15q26.1 region with fasting glucose. In silico cross-omics analyses highlight the role of differential methylation in the crosstalk between the adaptive immune system and glucose homeostasis. The differential methylation explains at least 16.9% of the association between obesity and insulin. Our study sheds light on the biological interactions between genetic variants driving differential methylation and gene expression in the early pathogenesis of T2D., Our understanding of the functional link between differential DNA methylation and type 2 diabetes and obesity remains limited. Here the authors present a blood-based EWAS of fasting glucose and insulin among 4808 non-diabetic Europeans and identify nine CpGs not previously implicated in glucose, insulin homeostasis and diabetes.

Prenatal maternal stress exposure has been associated with neonatal differential DNA methylation. However, the available evidence in humans is largely based on candidate gene methylation studies, where only a few CpG sites were evaluated. The aim of this study was to examine the association between prenatal exposure to maternal stress and offspring genome-wide cord blood methylation using different methods. First, we conducted a meta-analysis and follow-up pathway analyses. Second, we used novel region discovery methods [i.e., differentially methylated regions (DMRs) analyses]. To this end, we used data from two independent population-based studies, the Generation R Study (n = 912) and the Avon Longitudinal Study of Parents and Children (ALSPAC, n = 828), to (i) measure genome-wide DNA methylation in cord blood and (ii) extract a prenatal maternal stress composite. The meta-analysis (ntotal = 1,740) revealed no epigenome-wide (meta P

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

ObjectivesOccupational pesticide exposure is associated with a wide range of diseases, including lung diseases, but it is largely unknown how pesticides influence airway disease pathogenesis. A potential mechanism might be through epigenetic mechanisms, like DNA methylation. Therefore, we assessed associations between occupational exposure to pesticides and genome-wide DNA methylation sites.Methods1561 subjects of LifeLines were included with either no (n=1392), low (n=108) or high (n=61) exposure to any type of pesticides (estimated based on current or last held job). Blood DNA methylation levels were measured using Illumina 450K arrays. Associations between pesticide exposure and 420 938 methylation sites (CpGs) were assessed using robust linear regression adjusted for appropriate confounders. In addition, we performed genome-wide stratified and interaction analyses by gender, smoking and airway obstruction status, and assessed associations between gene expression and methylation for genome-wide significant CpGs (n=2802).ResultsIn total for all analyses, high pesticide exposure was genome-wide significantly (false discovery rate PRYR1, ALLC, PTPRN2, LRRC3B, PAX2 and VTRNA2-1, are genes previously linked to either pesticide exposure or lung-related diseases. Seven out of 31 CpGs were associated with gene expression levels.ConclusionsWe show for the first time that occupational exposure to pesticides is genome-wide associated with differential DNA methylation. Further research should reveal whether this differential methylation plays a role in the airway disease pathogenesis induced by pesticides.

Background Circulating levels of the chitinase-like protein YKL-40 are influenced by genetic variation in its encoding gene (chitinase 3–like 1 [CHI3L1] ) and are increased in patients with several diseases, including asthma. Epigenetic regulation of circulating YKL-40 early in life is unknown. Objective We sought to determine (1) whether methylation levels at CHI3L1 CpG sites mediate the association of CHI3L1 single nucleotide polymorphisms (SNPs) with YKL-40 levels in the blood and (2) whether these biomarkers ( CHI3L1 SNPs, methylation profiles, and YKL-40 levels) are associated with asthma in early childhood. Methods We used data from up to 2405 participants from the Spanish Infancia y Medio Ambiente; the Swedish Barn/Children, Allergy, Milieu, Stockholm, Epidemiological survey; and the Dutch Prevention and Incidence of Asthma and Mite Allergy birth cohorts. Associations between 68 CHI3L1 SNPs, methylation levels at 14 CHI3L1 CpG sites in whole-blood DNA, and circulating YKL-40 levels at 4 years of age were tested by using correlation analysis, multivariable regression, and mediation analysis. Each of these biomarkers was also tested for association with asthma at 4 years of age by using multivariable logistic regression. Results YKL-40 levels were significantly associated with 7 SNPs and with methylation at 5 CpG sites. Consistent associations between these 7 SNPs (particularly rs10399931 and rs4950928) and 5 CpG sites were observed. Alleles linked to lower YKL-40 levels were associated with higher methylation levels. Participants with high YKL-40 levels (defined as the highest YKL-40 tertile) had increased odds for asthma compared with subjects with low YKL-40 levels (meta-analyzed adjusted odds ratio, 1.90 [95% CI, 1.08-3.36]). In contrast, neither SNPs nor methylation levels at CpG sites in CHI3L1 were associated with asthma. Conclusions The effects of CHI3L1 genetic variation on circulating YKL-40 levels are partly mediated by methylation profiles. In our study YKL-40 levels, but not CHI3L1 SNPs or methylation levels, were associated with childhood asthma.

Certain human traits such as neurodevelopmental disorders (NDs) and congenital anomalies (CAs) are believed to be primarily genetic in origin. However, even after whole-genome sequencing (WGS), a substantial fraction of such disorders remain unexplained. We hypothesize that some cases of ND-CA are caused by aberrant DNA methylation leading to dysregulated genome function. Comparing DNA methylation profiles from 489 individuals with ND-CAs against 1534 controls, we identify epivariations as a frequent occurrence in the human genome. De novo epivariations are significantly enriched in cases, while RNAseq analysis shows that epivariations often have an impact on gene expression comparable to loss-of-function mutations. Additionally, we detect and replicate an enrichment of rare sequence mutations overlapping CTCF binding sites close to epivariations, providing a rationale for interpreting non-coding variation. We propose that epivariations contribute to the pathogenesis of some patients with unexplained ND-CAs, and as such likely have diagnostic relevance., The authors are grateful to the patients and families who participated in this study and to the collaborators who supported patient recruitment. This work was supported by NIH grant HG006696 and research grant 6-FY13-92 from the March of Dimes to A.J.S., grant HL098123 to B.D.G. and A.J.S., Gulbenkian Programme for Advanced Medical Education and the Portuguese Foundation for Science and Technology (SFRH/BDINT/51549/ 2011, PIC/IC/83026/2007, PIC/IC/83013/2007, SFRH/BD/90167/2012, Portugal) to P.M., F.L., and M.B., by the Northern Portugal Regional Operational Programme (NORTE 2020), under the Portugal 2020 Partnership Agreement, through the European Regional Development Fund (FEDER) (NORTE-01-0145-FEDER-000013) to P.M., a Beatriu de Pinos Postdoctoral Fellowship to R.S.J. (2011BP-A00515), and a Seaver Foundation fellowship to S.D.R. The views expressed are those of the authors and do not necessarily reflect those of the National Heart, Lung, and Blood Institute or the National Institutes of Health. Research reported in this paper was supported by the Office of Research Infrastructure of the National Institutes of Health under award number S10OD018522. This work was supported in part through the computational resources and staff expertise provided by Scientific Computing at the Icahn School of Medicine at Mount Sinai., The authors are grateful to the patients and families who participated in this study and to the collaborators who supported patient recruitment. This work was supported by NIH grant HG006696 and research grant 6-FY13-92 from the March of Dimes to A.J.S., grant HL098123 to B.D.G. and A.J.S., Gulbenkian Programme for Advanced Medical Education and the Portuguese Foundation for Science and Technology (SFRH/BDINT/51549/ 2011, PIC/IC/83026/2007, PIC/IC/83013/2007, SFRH/BD/90167/2012, Portugal) to P.M., F.L., and M.B., by the Northern Portugal Regional Operational Programme (NORTE 2020), under the Portugal 2020 Partnership Agreement, through the European Regional Development Fund (FEDER) (NORTE-01-0145-FEDER-000013) to P.M., a Beatriu de Pinos Postdoctoral Fellowship to R.S.J. (2011BP-A00515), and a Seaver Foundation fellowship to S.D.R. The views expressed are those of the authors and do not necessarily reflect those of the National Heart, Lung, and Blood Institute or the National Institutes of Health. Research reported in this paper was supported by the Office of Research Infrastructure of the National Institutes of Health under award number S10OD018522. This work was supported in part through the computational resources and staff expertise provided by Scientific Computing at the Icahn School of Medicine at Mount Sinai.

UK Medical Research Council; Wellcome Trust [102215/2/13/2, WT088806, 084762MA]; UK Biotechnology and Biological Sciences Research Council [BB/I025751/1, BB/I025263/1]; UK Medical Research Council Integrative Epidemiology Unit; University of Bristol [MC_UU_12013_1, MC_UU_12013_2, MC_UU_12013_5, MC_UU_12013_8]; United States National Institute of Diabetes and Digestive and Kidney Diseases [R01 DK10324]; Swedish Research Council; Swedish Heart-Lung Foundation; Freemason Child House Foundation in Stockholm; MeDALL (Mechanisms of the Development of ALLergy), within the European Union [261357]; Stockholm County Council (ALF); Swedish Foundation for Strategic Research (SSF) [RBc08-0027]; Strategic Research Programme (SFO) in Epidemiology at Karolinska Institutet; Swedish Research Council Formas; Swedish Environment Protection Agency; Center for Integrative Research on Childhood Leukemia and the Environment [P01ES018172]; NIH [P50ES018172, R01ES09137, 5P30CA082103, P01 ES009605, R01 ES021369, R01ES023067, K01ES017801, R01ES022216, P30ES007048, R01ES014447, P01ES009581, R826708-01, RD831861-01, P50ES026086, R01DK068001, R01 DK100340, R01 DK076648, R01ES022934, R01HL111108, R01NR013945, R37 HD034568, UL1 TR001082, P30 DK56350]; EPA [RD83451101, RD83615901, RD 82670901, RD 83451301, 83615801-0]; UCSF Comprehensive Cancer Center Support grant [P30 CA82103]; Swiss Science National Foundation [P2LAP3_158674]; Sutter-Stottner Foundation; Commission of the European Community, specific RTD Programme 'Quality of Life and Management of Living Resources' within the 5th Framework Programme [QLRT-2001-00389, QLK1-CT-2002-30582]; 6th Framework Programme [007036]; European Union's Seventh Framework Programme (FP7), project EarlyNutrition [289346]; European Research Council Advanced grant ERC-AdG [322605 META-GROWTH]; Autism Speaks grant [260377]; Funds for Research in Respiratory Health; French Ministry of Research: IFR program; INSERM Nutrition Research Program; French Ministry of Health: Perinatality Program; French National Institute for Population Health Surveillance (INVS); Paris-Sud University; French National Institute for Health Education (INPES); Nestle; Mutuelle Generale de l'Education Nationale (MGEN); French-speaking association for the study of diabetes and metabolism (Alfediam) [2012/51290-6]; EU; European Research Council [ERC-2012-StG.310898, 268479-BREATHE]; Flemish Scientific Research Council (FWO) [N1516112 / G.0.873.11N.10]; European Community's Seventh Framework Programme FP7 project EXPOsOMICS [308610]; People Program (Marie Curie Actions) of the European Union's Seventh Framework Program FP7 under REA grant [628858]; Bijzonder Onderzoeksfonds (BOF) Hasselt University; Ministry of the Flemish Community (Department of Economics, Science and Innovation); Ministry of the Flemish Community (Department of Environment, Nature and Energy); CEFIC LRI award by the Research Foundation-Flanders (FWO); CEFIC LRI award by the Research Foundation-Flanders (FWO) [12L5216N]; Flemish Institute for Technological Research (VITO) [12L5216N]; Bill AMP; Melinda Gates Foundation Grand Challenges Exploration grant [OPP119403]; Sandler Family Foundation; American Asthma Foundation; National Institutes of Health; National Heart, Lung and Blood Institute [HL117004]; National Institute of Environmental Health Sciences [ES24844]; National Institute on Minority Health and Health Disparities [MD006902, MD009523]; National Institute of General Medical Sciences [GM007546]; Tobacco-Related Disease Research Program [24RT-0025]; Hutchison Whampoa Ltd, Hong Kong; University of Groningen; Well Baby Clinic Foundation Icare; Noordlease; Youth Health Care Drenthe; Biobanking and Biomolecular Research Infrastructure Netherlands [CP2011-19]; Erasmus Medical Center, Rotterdam; Erasmus University Rotterdam; Netherlands Organization for Health Research and Development; Netherlands Genomics Initiative (NGI)/Netherlands Organization for Scientific Research (NWO); Netherlands Consortium for Healthy Aging (NCHA) [050-060-810]; Genetic Laboratory of the Department of Internal Medicine, Erasmus MC; European Union's Horizon research and innovation programme [733206, 633595]; National Institute of Child and Human Development [R01HD068437]; Netherlands Organization for Health Research and Development [VIDI 016.136.361]; Consolidator grant from the European Research Council [ERC-2014-CoG-648916]; Netherlands' Organization for Scientific Research (NWO VICI); European Research Council ERC; Netherlands' Organization for Scientific Research (NWO Spinoza Award); Gravitation program of the Dutch Ministry of Education, Culture, and Science; Netherlands Organization for Scientific Research (NWO) [024.001.003]; Lung Foundation Netherlands [3.2.12.089]; Fonds de Recherche du Quebec en Sante (FRQ-S) [20697]; Canadian Institute of Health Reseach (CIHR) [MOP 115071]; Diabete Quebec grant; Canadian Diabetes Association operating grant [OG-3-08-2622]; American Diabetes Association Pathways Accelerator Early Investigator Award [1-15-ACE-26]; MRC Integrative Epidemiology Unit - Medical Research Council [MC_UU_12013/1-9]; National Institute of Environmental Health Sciences, National Institutes of Health [K99ES025817]; Instituto de Salud Carlos III [Red INMA G03/176, CB06/02/0041]; Spanish Ministry of Health [FIS-PI04/1436, FIS-PI08/1151]; Spanish Ministry of Health (FEDER funds) [FIS-PI11/00610, FIS-FEDER-PI06/0867, FIS-FEDER-PI03-1615]; Generalitat de Catalunya [CIRIT 1999SGR 00241]; Fundacio La Marato de TV3 [090430]; EU Commission [261357-MeDALL]; National Institute of Allergy and Infectious Diseases [N01-AI90052]; National Institutes of Health USA [R01 HL082925, R01 HL132321]; Asthma UK [364]; NIAID/NIH [R01AI091905, R01AI121226]; National Institute of Health [R01AI121226, R01 AI091905, R01HL132321]; NIH/NIEHS [N01-ES75558]; NIH/NINDS [1 UO1 NS 047537-01, 2 UO1 NS 047537-06A1]; Intramural Research Program of the NIH, National Institute of Environmental Health Sciences [Z01-ES-49019, Z01 ES044005, ES049033, ES049032]; Norwegian Research Council/BIOBANK [221097]; Oslo University Hospital; Unger-Vetlesens foundation; Norwegian American Womens Club; INCA/Plan Cancer-EVA-INSERM, France; International Childhood Cancer Cohort Consortium (I4C); INCA/Plan Cancer-EVA-INSERM (France); IARC Postdoctoral Fellowship; EC FP7 Marie Curie Actions-People-Co-funding of regional, national and international programmes (COFUND); NIEHS [R21ES014947, R01ES016772]; NIDDK [R01DK085173]; National Institute of Environmental Health Science [P30 ES025128]; University of Oulu grant [65354]; Oulu University Hospital [2/97, 8/97]; Ministry of Health and Social Affairs [23/251/97, 160/97, 190/97]; National Institute for Health and Welfare, Helsinki [54121]; Regional Institute of Occupational Health, Oulu, Finland [50621, 54231]; EU [QLG1-CT-2000-01643, E51560]; NorFA grant [731, 20056, 30167]; Academy of Finland; NIH-NIEHS [P01 ES022832]; US EPA [RD83544201]; NIH-NIGMS [P20GM104416]; NCI [R25CA134286]; Netherlands Organization for Scientific Research and Development; Netherlands Asthma Fund; Netherlands Ministry of Spatial Planning, Housing, and the Environment; Netherlands Ministry of Health, Welfare, and Sport; MeDALL; European Union under the Health Cooperation Work Program of the 7th Framework program [261357]; Italian National Centre for Disease Prevention and Control (CCM grant); Italian Ministry of Health (art 12); Italian Ministry of Health (12bis Dl.gs.vo) [502/92]; EraNet; EVO; University of Helsinki Research Funds; Signe and Ane Gyllenberg foundation; Emil Aaltonen Foundation; Finnish Medical Foundation; Jane and Aatos Erkko Foundation; Novo Nordisk Foundation; Paivikki and Sakari Sohlberg Foundation; Sigrid Juselius Foundation; University of Helsinki; University of Western Australia (UWA); Curtin University; Raine Medical Research Foundation; UWA Faculty of Medicine, Dentistry and Health Sciences; Telethon Kids Institute; Women's and Infant's Research Foundation (KEMH); Edith Cowan University; National Health and Medical Research Council [1059711]; National Health and Medical Research Council (NHMRC) fellowship [1053384]; Australian National Health and Medical Research Council; United States National Institute of Health; Greek Ministry of Health (programme of prevention of obesity and neurodevelopmental disorders in preschool children, in Heraklion district, Crete, Greece); Greek Ministry of Health ('Rhea Plus': Primary Prevention Program of Environmental Risk Factors for Reproductive Health, and Child Health); European Union (EU) [EU FP6-2003-Food-3-NewGeneris, EU FP7 ENV.2007.1.2.2.2, 211250 ESCAPE, EU FP7-2008-ENV-1.2.1.4 Envirogenomarkers, EU FP7 ENV.2008.1.2.1.6, 226285 ENRIECO]; National Institutes of Health [NIH-NIMH R01MH094609, NIH-NIEHS R01ES022223, NIH-NIEHS R01ES025145]; Centers for Disease Control and Prevention [U10DD000180, U10DD000181, U10DD000182, U10DD000183, U10DD000184, U10DD000498]; Autism Speaks [7659]; Swedish Research Council through the Swedish Initiative for research on Microdata in the Social And Medical Sciences (SIMSAM) [340-2013-5867]; Stockholm County Council (ALF projects); Strategic Research Program in Epidemiology at Karolinska Institutet; Swedish Asthma and Allergy Association's Research Foundation; Stiftelsen Frimurare Barnahuset Stockholm; Norwegian Ministry of Health and Care Services; Ministry of the Flemish Community (Flemish Agency for Care and Health); University of Bristol; Ministry of Education and Research; European Union (EU) (EU FP7-HEALTH-single stage CHICOS); European Union (EU) (EU-FP7-HEALTH) [308333 HELIX]; European Union (EU) (EU FP6. STREP HiWATE); UK Medical Research Council; Wellcome Trust [102215/2/13/2, WT088806, 084762MA]; UK Biotechnology and Biological Sciences Research Council [BB/I025751/1, BB/I025263/1]; UK Medical Research Council Integrative Epidemiology Unit; University of Bristol [MC_UU_12013_1, MC_UU_12013_2, MC_UU_12013_5, MC_UU_12013_8]; United States National Institute of Diabetes and Digestive and Kidney Diseases [R01 DK10324]; Swedish Research Council; Swedish Heart-Lung Foundation; Freemason Child House Foundation in Stockholm; MeDALL (Mechanisms of the Development of ALLergy), within the European Union [261357]; Stockholm County Council (ALF); Swedish Foundation for Strategic Research (SSF) [RBc08-0027]; Strategic Research Programme (SFO) in Epidemiology at Karolinska Institutet; Swedish Research Council Formas; Swedish Environment Protection Agency; Center for Integrative Research on Childhood Leukemia and the Environment [P01ES018172]; NIH [P50ES018172, R01ES09137, 5P30CA082103, P01 ES009605, R01 ES021369, R01ES023067, K01ES017801, R01ES022216, P30ES007048, R01ES014447, P01ES009581, R826708-01, RD831861-01, P50ES026086, R01DK068001, R01 DK100340, R01 DK076648, R01ES022934, R01HL111108, R01NR013945, R37 HD034568, UL1 TR001082, P30 DK56350]; EPA [RD83451101, RD83615901, RD 82670901, RD 83451301, 83615801-0]; UCSF Comprehensive Cancer Center Support grant [P30 CA82103]; Swiss Science National Foundation [P2LAP3_158674]; Sutter-Stottner Foundation; Commission of the European Community, specific RTD Programme 'Quality of Life and Management of Living Resources' within the 5th Framework Programme [QLRT-2001-00389, QLK1-CT-2002-30582]; 6th Framework Programme [007036]; European Union's Seventh Framework Programme (FP7), project EarlyNutrition [289346]; European Research Council Advanced grant ERC-AdG [322605 META-GROWTH]; Autism Speaks grant [260377]; Funds for Research in Respiratory Health; French Ministry of Research: IFR program; INSERM Nutrition Research Program; French Ministry of Health: Perinatality Program; French National Institute for Population Health Surveillance (INVS); Paris-Sud University; French National Institute for Health Education (INPES); Nestle; Mutuelle Generale de l'Education Nationale (MGEN); French-speaking association for the study of diabetes and metabolism (Alfediam) [2012/51290-6]; EU; European Research Council [ERC-2012-StG.310898, 268479-BREATHE]; Flemish Scientific Research Council (FWO) [N1516112 / G.0.873.11N.10]; European Community's Seventh Framework Programme FP7 project EXPOsOMICS [308610]; People Program (Marie Curie Actions) of the European Union's Seventh Framework Program FP7 under REA grant [628858]; Bijzonder Onderzoeksfonds (BOF) Hasselt University; Ministry of the Flemish Community (Department of Economics, Science and Innovation); Ministry of the Flemish Community (Department of Environment, Nature and Energy); CEFIC LRI award by the Research Foundation-Flanders (FWO); CEFIC LRI award by the Research Foundation-Flanders (FWO) [12L5216N]; Flemish Institute for Technological Research (VITO) [12L5216N]; Bill AMP; Melinda Gates Foundation Grand Challenges Exploration grant [OPP119403]; Sandler Family Foundation; American Asthma Foundation; National Institutes of Health; National Heart, Lung and Blood Institute [HL117004]; National Institute of Environmental Health Sciences [ES24844]; National Institute on Minority Health and Health Disparities [MD006902, MD009523]; National Institute of General Medical Sciences [GM007546]; Tobacco-Related Disease Research Program [24RT-0025]; Hutchison Whampoa Ltd, Hong Kong; University of Groningen; Well Baby Clinic Foundation Icare; Noordlease; Youth Health Care Drenthe; Biobanking and Biomolecular Research Infrastructure Netherlands [CP2011-19]; Erasmus Medical Center, Rotterdam; Erasmus University Rotterdam; Netherlands Organization for Health Research and Development; Netherlands Genomics Initiative (NGI)/Netherlands Organization for Scientific Research (NWO); Netherlands Consortium for Healthy Aging (NCHA) [050-060-810]; Genetic Laboratory of the Department of Internal Medicine, Erasmus MC; European Union's Horizon research and innovation programme [733206, 633595]; National Institute of Child and Human Development [R01HD068437]; Netherlands Organization for Health Research and Development [VIDI 016.136.361]; Consolidator grant from the European Research Council [ERC-2014-CoG-648916]; Netherlands' Organization for Scientific Research (NWO VICI); European Research Council ERC; Netherlands' Organization for Scientific Research (NWO Spinoza Award); Gravitation program of the Dutch Ministry of Education, Culture, and Science; Netherlands Organization for Scientific Research (NWO) [024.001.003]; Lung Foundation Netherlands [3.2.12.089]; Fonds de Recherche du Quebec en Sante (FRQ-S) [20697]; Canadian Institute of Health Reseach (CIHR) [MOP 115071]; Diabete Quebec grant; Canadian Diabetes Association operating grant [OG-3-08-2622]; American Diabetes Association Pathways Accelerator Early Investigator Award [1-15-ACE-26]; MRC Integrative Epidemiology Unit - Medical Research Council [MC_UU_12013/1-9]; National Institute of Environmental Health Sciences, National Institutes of Health [K99ES025817]; Instituto de Salud Carlos III [Red INMA G03/176, CB06/02/0041]; Spanish Ministry of Health [FIS-PI04/1436, FIS-PI08/1151]; Spanish Ministry of Health (FEDER funds) [FIS-PI11/00610, FIS-FEDER-PI06/0867, FIS-FEDER-PI03-1615]; Generalitat de Catalunya [CIRIT 1999SGR 00241]; Fundacio La Marato de TV3 [090430]; EU Commission [261357-MeDALL]; National Institute of Allergy and Infectious Diseases [N01-AI90052]; National Institutes of Health USA [R01 HL082925, R01 HL132321]; Asthma UK [364]; NIAID/NIH [R01AI091905, R01AI121226]; National Institute of Health [R01AI121226, R01 AI091905, R01HL132321]; NIH/NIEHS [N01-ES75558]; NIH/NINDS [1 UO1 NS 047537-01, 2 UO1 NS 047537-06A1]; Intramural Research Program of the NIH, National Institute of Environmental Health Sciences [Z01-ES-49019, Z01 ES044005, ES049033, ES049032]; Norwegian Research Council/BIOBANK [221097]; Oslo University Hospital; Unger-Vetlesens foundation; Norwegian American Womens Club; INCA/Plan Cancer-EVA-INSERM, France; International Childhood Cancer Cohort Consortium (I4C); INCA/Plan Cancer-EVA-INSERM (France); IARC Postdoctoral Fellowship; EC FP7 Marie Curie Actions-People-Co-funding of regional, national and international programmes (COFUND); NIEHS [R21ES014947, R01ES016772]; NIDDK [R01DK085173]; National Institute of Environmental Health Science [P30 ES025128]; University of Oulu grant [65354]; Oulu University Hospital [2/97, 8/97]; Ministry of Health and Social Affairs [23/251/97, 160/97, 190/97]; National Institute for Health and Welfare, Helsinki [54121]; Regional Institute of Occupational Health, Oulu, Finland [50621, 54231]; EU [QLG1-CT-2000-01643, E51560]; NorFA grant [731, 20056, 30167]; Academy of Finland; NIH-NIEHS [P01 ES022832]; US EPA [RD83544201]; NIH-NIGMS [P20GM104416]; NCI [R25CA134286]; Netherlands Organization for Scientific Research and Development; Netherlands Asthma Fund; Netherlands Ministry of Spatial Planning, Housing, and the Environment; Netherlands Ministry of Health, Welfare, and Sport; MeDALL; European Union under the Health Cooperation Work Program of the 7th Framework program [261357]; Italian National Centre for Disease Prevention and Control (CCM grant); Italian Ministry of Health (art 12); Italian Ministry of Health (12bis Dl.gs.vo) [502/92]; EraNet; EVO; University of Helsinki Research Funds; Signe and Ane Gyllenberg foundation; Emil Aaltonen Foundation; Finnish Medical Foundation; Jane and Aatos Erkko Foundation; Novo Nordisk Foundation; Paivikki and Sakari Sohlberg Foundation; Sigrid Juselius Foundation; University of Helsinki; University of Western Australia (UWA); Curtin University; Raine Medical Research Foundation; UWA Faculty of Medicine, Dentistry and Health Sciences; Telethon Kids Institute; Women's and Infant's Research Foundation (KEMH); Edith Cowan University; National Health and Medical Research Council [1059711]; National Health and Medical Research Council (NHMRC) fellowship [1053384]; Australian National Health and Medical Research Council; United States National Institute of Health; Greek Ministry of Health (programme of prevention of obesity and neurodevelopmental disorders in preschool children, in Heraklion district, Crete, Greece); Greek Ministry of Health ('Rhea Plus': Primary Prevention Program of Environmental Risk Factors for Reproductive Health, and Child Health); European Union (EU) [EU FP6-2003-Food-3-NewGeneris, EU FP7 ENV.2007.1.2.2.2, 211250 ESCAPE, EU FP7-2008-ENV-1.2.1.4 Envirogenomarkers, EU FP7 ENV.2008.1.2.1.6, 226285 ENRIECO]; National Institutes of Health [NIH-NIMH R01MH094609, NIH-NIEHS R01ES022223, NIH-NIEHS R01ES025145]; Centers for Disease Control and Prevention [U10DD000180, U10DD000181, U10DD000182, U10DD000183, U10DD000184, U10DD000498]; Autism Speaks [7659]; Swedish Research Council through the Swedish Initiative for research on Microdata in the Social And Medical Sciences (SIMSAM) [340-2013-5867]; Stockholm County Council (ALF projects); Strategic Research Program in Epidemiology at Karolinska Institutet; Swedish Asthma and Allergy Association's Research Foundation; Stiftelsen Frimurare Barnahuset Stockholm; Norwegian Ministry of Health and Care Services; Ministry of the Flemish Community (Flemish Agency for Care and Health); University of Bristol; Ministry of Education and Research; European Union (EU) (EU FP7-HEALTH-single stage CHICOS); European Union (EU) (EU-FP7-HEALTH) [308333 HELIX]; European Union (EU) (EU FP6. STREP HiWATE); [R01ES017646]; [R01ES01900]; [R01ES16443]; [USA / NIHH 2000 G DF682]; [50945]; [R01 HL095606]; [R01 HL1143396]

DNA methylation mediates the association of prenatal famine exposure with higher adult BMI and serum triglyceride levels., Although it is assumed that epigenetic mechanisms, such as changes in DNA methylation (DNAm), underlie the relationship between adverse intrauterine conditions and adult metabolic health, evidence from human studies remains scarce. Therefore, we evaluated whether DNAm in whole blood mediated the association between prenatal famine exposure and metabolic health in 422 individuals exposed to famine in utero and 463 (sibling) controls. We implemented a two-step analysis, namely, a genome-wide exploration across 342,596 cytosine-phosphate-guanine dinucleotides (CpGs) for potential mediators of the association between prenatal famine exposure and adult body mass index (BMI), serum triglycerides (TG), or glucose concentrations, which was followed by formal mediation analysis. DNAm mediated the association of prenatal famine exposure with adult BMI and TG but not with glucose. DNAm at PIM3 (cg09349128), a gene involved in energy metabolism, mediated 13.4% [95% confidence interval (CI), 5 to 28%] of the association between famine exposure and BMI. DNAm at six CpGs, including TXNIP (cg19693031), influencing β cell function, and ABCG1 (cg07397296), affecting lipid metabolism, together mediated 80% (95% CI, 38.5 to 100%) of the association between famine exposure and TG. Analyses restricted to those exposed to famine during early gestation identified additional CpGs mediating the relationship with TG near PFKFB3 (glycolysis) and METTL8 (adipogenesis). DNAm at the CpGs involved was associated with gene expression in an external data set and correlated with DNAm levels in fat depots in additional postmortem data. Our data are consistent with the hypothesis that epigenetic mechanisms mediate the influence of transient adverse environmental factors in early life on long-term metabolic health. The specific mechanism awaits elucidation.

Chronic obstructive pulmonary disease (COPD) is an age and smoking related progressive, pulmonary disorder presenting with poorly reversible airflow limitation as a result of chronic bronchitis and emphysema. The prevalence, disease burden for the individual, and mortality of COPD continues to increase, whereas no effective treatment strategies are available. For many years now, a combination of bronchodilators and anti-inflammatory corticosteroids has been most widely used for therapeutic management of patients with persistent COPD. However, this approach has had disappointing results as a large number of COPD patients are corticosteroid resistant. In patients with COPD, there is emerging evidence showing aberrant expression of epigenetic marks such as DNA methylation, histone modifications and microRNAs in blood, sputum and lung tissue. Therefore, novel therapeutic approaches may exist using epigenetic therapy. This review aims to describe and summarize current knowledge of aberrant expression of epigenetic marks in COPD. In addition, tools available for restoration of epigenetic marks are described, as well as delivery mechanisms of epigenetic editors to cells. Targeting epigenetic marks might be a very promising tool for treatment and lung regeneration in COPD in the future.

A plethora of environmental and behavioral factors interact, resulting in changes in gene expression and providing a basis for the development and progression of cardiovascular diseases. Heterogeneity in gene expression responses among cells and individuals involves epigenetic mechanisms. Advancing technology allowing genome-scale interrogation of epigenetic marks provides a rapidly expanding view of the complexity and diversity of the epigenome. In this review, the authors discuss the expanding landscape of epigenetic modifications and highlight their importance for future understanding of disease. The epigenome provides a mechanistic link between environmental exposures and gene expression profiles ultimately leading to disease. The authors discuss the current evidence for transgenerational epigenetic inheritance and summarize the data linking epigenetics to cardiovascular disease. Furthermore, the potential targets provided by the epigenome for the development of future diagnostics, preventive strategies, and therapy for cardiovascular disease are reviewed. Finally, the authors provide some suggestions for future directions. (C) 2017 by the American College of Cardiology Foundation.

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. Electronic supplementary material The online version of this article (10.1007/s10654-019-00555-w) contains supplementary material, which is available to authorized users.

Epigenetic control of human immunodeficiency virus-1 (HIV-1) genes is critical for viral integration and latency. However, epigenetic changes in the HIV-1-infected host genome have not been well characterized. Here, we report the first large-scale epigenome-wide association study of DNA methylation for HIV-1 infection. We recruited HIV-infected (n = 261) and uninfected (n = 117) patients from the Veteran Aging Cohort Study (VACS) and all samples were profiled for 485,521 CpG sites in DNA extracted from the blood. After adjusting for cell type and clinical confounders, we identified 20 epigenome-wide significant CpGs for HIV-1 infection. Importantly, 2 CpGs in the promoter of the NLR family, CARD domain containing gene 5 (NLRC5), a key regulator of major histocompatibility complex class I gene expression, showed significantly lower methylation in HIV-infected subjects than in uninfected subjects (cg07839457: t = −6.03, Pnominal = 4.96 × 10−9; cg16411857: t = −7.63, Pnominal = 3.07 × 10−13). Hypomethylation of these 2 CpGs was replicated in an independent sample (GSE67705: cg07839457: t = −4.44, Pnominal = 1.61 × 10−5; cg16411857: t = −5.90; P = 1.99 × 10−8). Methylation of these 2 CpGs in NLRC5 was negatively correlated with viral load in the 2 HIV-infected samples (cg07839457: P = 1.8 × 10−4; cg16411857: P = 0.03 in the VACS; and cg07839457: P = 0.04; cg164111857: P = 0.01 in GSE53840). Our findings demonstrate that differential DNA methylation is associated with HIV infection and suggest the involvement of a novel host gene, NLRC5, in HIV pathogenesis.

Background Cells can be primed by external stimuli to obtain a long-term epigenetic memory. We hypothesize that long-term exposure to elevated blood lipids can prime circulating immune cells through changes in DNA methylation, a process that may contribute to the development of atherosclerosis. To interrogate the causal relationship between triglyceride, low-density lipoprotein (LDL) cholesterol, and high-density lipoprotein (HDL) cholesterol levels and genome-wide DNA methylation while excluding confounding and pleiotropy, we perform a stepwise Mendelian randomization analysis in whole blood of 3296 individuals. Results This analysis shows that differential methylation is the consequence of inter-individual variation in blood lipid levels and not vice versa. Specifically, we observe an effect of triglycerides on DNA methylation at three CpGs, of LDL cholesterol at one CpG, and of HDL cholesterol at two CpGs using multivariable Mendelian randomization. Using RNA-seq data available for a large subset of individuals (N = 2044), DNA methylation of these six CpGs is associated with the expression of CPT1A and SREBF1 (for triglycerides), DHCR24 (for LDL cholesterol) and ABCG1 (for HDL cholesterol), which are all key regulators of lipid metabolism. Conclusions Our analysis suggests a role for epigenetic priming in end-product feedback control of lipid metabolism and highlights Mendelian randomization as an effective tool to infer causal relationships in integrative genomics data. Electronic supplementary material The online version of this article (doi:10.1186/s13059-016-1000-6) contains supplementary material, which is available to authorized users.

Identification of subjects with a high risk of developing type 2 diabetes (T2D) is fundamental for prevention of the disease. Consequently, it is essential to search for new biomarkers that can improve the prediction of T2D. The aim of this study was to examine whether 5 DNA methylation loci in blood DNA (ABCG1, PHOSPHO1, SOCS3, SREBF1, and TXNIP), recently reported to be associated with T2D, might predict future T2D in subjects from the Botnia prospective study. We also tested if these CpG sites exhibit altered DNA methylation in human pancreatic islets, liver, adipose tissue, and skeletal muscle from diabetic vs. non-diabetic subjects. DNA methylation at the ABCG1 locus cg06500161 in blood DNA was associated with an increased risk for future T2D (OR = 1.09, 95% CI = 1.02-1.16, P-value = 0.007, Q-value = 0.018), while DNA methylation at the PHOSPHO1 locus cg02650017 in blood DNA was associated with a decreased risk for future T2D (OR = 0.85, 95% CI = 0.75-0.95, P-value = 0.006, Q-value = 0.018) after adjustment for age, gender, fasting glucose, and family relation. Furthermore, the level of DNA methylation at the ABCG1 locus cg06500161 in blood DNA correlated positively with BMI, HbA1c, fasting insulin, and triglyceride levels, and was increased in adipose tissue and blood from the diabetic twin among monozygotic twin pairs discordant for T2D. DNA methylation at the PHOSPHO1 locus cg02650017 in blood correlated positively with HDL levels, and was decreased in skeletal muscle from diabetic vs. non-diabetic monozygotic twins. DNA methylation of cg18181703 (SOCS3), cg11024682 (SREBF1), and cg19693031 (TXNIP) was not associated with future T2D risk in subjects from the Botnia prospective study.

Background: The prevalence of type 2 diabetes (T2D) and obesity has dramatically increased within a few generations, reaching epidemic levels. In addition to genetic risk factors, epigenetic mechanisms triggered by changing environment are investigated for their role in the pathogenesis of these complex diseases. Epigenome-wide association studies (EWASs) have revealed significant associations of T2D, obesity, and BMI with DNA methylation. However, populations from the Middle East, where T2D and obesity rates are highest worldwide, have not been investigated so far.Methods: We performed the first EWAS in an Arab population with T2D and BMI and attempted to replicate 47 EWAS associations previously reported in Caucasians. We used the Illumina Infinium HumanMethylation450 BeadChip to quantify DNA methylation in whole blood DNA from 123 subjects of 15 multigenerational families from Qatar. To investigate the effect of differing genetic background and environment on the epigenetic associations, we further assessed the effect of replicated loci in 810 twins from UK.Results: Our EWAS suggested a novel association between T2D and cg06721411 (DQX1; p value = 1.18 × 10−9). We replicated in the Qatari population seven CpG associations with BMI (SOCS3, p value = 3.99 × 10−6; SREBF1, p value = 4.33 × 10−5; SBNO2, p value = 5.87 × 10−5; CPT1A, p value = 7.99 × 10−5; PRR5L, p value = 1.85 × 10−4; cg03078551, intergenic region on chromosome 17; p value = 1.00 × 10−3; LY6G6E, p value = 1.10 × 10−3) and one with T2D (TXNIP, p value = 2.46 × 10−5). All the associations were further confirmed in the UK cohort for both BMI and T2D. Meta-analysis increased the significance of the observed associations and revealed strong heterogeneity of the effect sizes (apart from CPT1A), although associations at these loci showed concordant direction in the two populations.Conclusions: Our study replicated eight known CpG associations with T2D or BMI in an Arab population. Heterogeneity of the effects at all loci except CPT1A between the Qatari and UK studies suggests that the underlying mechanisms might depend on genetic background and environmental pressure. Our EWAS results provide a basis for comparison with other ethnicities.

Background Allogeneic hematopoietic stem cell transplantation (HSCT) is a curative treatment for many hematological conditions. Acute graft-versus-host disease (aGVHD) is a prevalent immune-mediated complication following HSCT. Current diagnostic biomarkers that correlate with aGVHD severity, progression, and therapy response in graft recipients are insufficient. Here, we investigated whether epigenetic marks measured in peripheral blood of healthy graft donors stratify aGVHD severity in human leukocyte antigen (HLA)-matched sibling recipients prior to T cell-depleted HSCT. Methods We measured DNA methylation levels genome-wide at single-nucleotide resolution in peripheral blood of 85 HSCT donors, matched to recipients with various transplant outcomes, with Illumina Infinium HumanMethylation450 BeadChips. Results Using genome-wide DNA methylation profiling, we showed that epigenetic signatures underlying aGVHD severity in recipients correspond to immune pathways relevant to aGVHD etiology. We discovered 31 DNA methylation marks in donors that associated with aGVHD severity status in recipients, and demonstrated strong predictive performance of these markers in internal cross-validation experiments (AUC = 0.98, 95 % CI = 0.96–0.99). We replicated the top-ranked CpG classifier using an alternative, clinical DNA methylation assay (P = 0.039). In an independent cohort of 32 HSCT donors, we demonstrated the utility of the epigenetic classifier in the context of a T cell-replete conditioning regimen (P = 0.050). Conclusions Our findings suggest that epigenetic typing of HSCT donors in a clinical setting may be used in conjunction with HLA genotyping to inform both donor selection and transplantation strategy, with the ultimate aim of improving patient outcome.

Most of the genetic variation associated with diabetes, through genome-wide association studies, does not reside in protein-coding regions, making the identification of functional variants and their eventual translation to the clinic challenging. In recent years, high-throughput sequencing-based methods have enabled genome-scale high-resolution epigenomic profiling in a variety of human tissues, allowing the exploration of the human genome outside of the well-studied coding regions. These experiments unmasked tens of thousands of regulatory elements across several cell types, including diabetes-relevant tissues, providing new insights into their mechanisms of gene regulation. Regulatory landscapes are highly dynamic and cell-type specific and, being sensitive to DNA sequence variation, can vary with individual genomes. The scientific community is now in place to exploit the regulatory maps of tissues central to diabetes etiology, such as pancreatic progenitors and adult islets. This giant leap forward in the understanding of pancreatic gene regulation is revolutionizing our capacity to discriminate between functional and non-functional non-coding variants, opening opportunities to uncover regulatory links between sequence variation and diabetes susceptibility. In this review, we focus on the non-coding regulatory landscape of the pancreatic endocrine cells and provide an overview of the recent developments in this field.

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 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. (c) 2018 The Authors. Published by Elsevier B.V.

Background The pathophysiological role of SERPINA1 in respiratory health may be more strongly determined by the regulation of its expression than by common genetic variants. A family based study of predominantly smoking adults found methylation at two Cytosine-phosphate-Guanine sites (CpGs) in SERPINA1 gene to be associated with chronic obstructive pulmonary disease risk. The objective of this study was to confirm the association of lung function with SERPINA1 methylation in general population samples by testing a comprehensive set of CpGs in the SERPINA gene cluster. We considered lung function level and decline in adult smokers from three European population-based cohorts and lung function level and growth in tobacco-smoke exposed children from a birth cohort. Methods DNA methylation using Illumina Infinium Human Methylation 450 k and EPIC beadchips and lung function were measured at two time points in 1076 SAPALDIA, ECRHS and NFBC adult cohort participants and 259 ALSPAC children. Associations of methylation at 119 CpG sites in the SERPINA gene cluster (PP4R4-SERPINA13P) with lung functions and circulating alpha-1-antitripsin (AAT) were assessed using multivariable cross-sectional and longitudinal regression models. Results Methylation at cg08257009 in the SERPINA gene cluster, located 32 kb downstream of SERPINA1, not annotated to a gene, was associated with FEV1/FVC at the Bonferroni corrected level in adults, but not in children. None of the methylation signals in the SERPINA1 gene showed associations with lung function after correcting for multiple testing. Conclusions The results do not support a role of SERPINA1 gene methylation as determinant of lung function across the life course in the tobacco smoke exposed general population exposed. Electronic supplementary material The online version of this article (10.1186/s12931-018-0850-8) contains supplementary material, which is available to authorized users.