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Background: DNA methylation profiles associated with childhood asthma might provide novel insights into disease pathogenesis. We did an epigenome-wide association study to assess methylation profiles associated with childhood asthma. Methods: We did a large-scale epigenome-wide association study (EWAS) within the Mechanisms of the Development of ALLergy (MeDALL) project. We examined epigenome-wide methylation using Illumina Infinium Human Methylation450 BeadChips (450K) in whole blood in 207 children with asthma and 610 controls at age 4–5 years, and 185 children with asthma and 546 controls at age 8 years using a cross-sectional case-control design. After identification of differentially methylated CpG sites in the discovery analysis, we did a validation study in children (4–16 years; 247 cases and 2949 controls) from six additional European cohorts and meta-analysed the results. We next investigated whether replicated CpG sites in cord blood predict later asthma in 1316 children. We subsequently investigated cell-type-specific methylation of the identified CpG sites in eosinophils and respiratory epithelial cells and their related gene-expression signatures. We studied cell-type specificity of the asthma association of the replicated CpG sites in 455 respiratory epithelial cell samples, collected by nasal brushing of 16-year-old children as well as in DNA isolated from blood eosinophils (16 with asthma, eight controls [age 2–56 years]) and compared this with whole-blood DNA samples of 74 individuals with asthma and 93 controls (age 1–79 years). Whole-blood transcriptional profiles associated with replicated CpG sites were annotated using RNA-seq data of subsets of peripheral blood mononuclear cells sorted by fluorescence-activated cell sorting. Findings: 27 methylated CpG sites were identified in the discovery analysis. 14 of these CpG sites were replicated and passed genome-wide significance (p<1·14 × 10−7) after meta-analysis. Consistently lower methylation levels were observed at all associated loci across childhood from age 4 to 16 years in participants with asthma, but not in cord blood at birth. All 14 CpG sites were significantly associated with asthma in the second replication study using whole-blood DNA, and were strongly associated with asthma in purified eosinophils. Whole-blood transcriptional signatures associated with these CpG sites indicated increased activation of eosinophils, effector and memory CD8 T cells and natural killer cells, and reduced number of naive T cells. Five of the 14 CpG sites were associated with asthma in respiratory epithelial cells, indicating cross-tissue epigenetic effects. Interpretation: Reduced whole-blood DNA methylation at 14 CpG sites acquired after birth was strongly associated with childhood asthma. These CpG sites and their associated transcriptional profiles indicate activation of eosinophils and cytotoxic T cells in childhood asthma. Our findings merit further investigations of the role of epigenetics in a clinical context. Funding: EU and the Seventh Framework Programme (the MeDALL project). ; We are grateful to all children and families that participated in this study. We especially thank Professsor Dirkje Postma for helpful comments and support during the course of this study. The Mechanisms of the Development of ALLergy (MeDALL) EU project was supported by the seventh Framework programme (grant agreement number 261357). The Biobank-Based Integrative Omics Studies (BIOS) Consortium is funded by BBMRI-NL, a research infrastructure financed by the Dutch government (NWO 184.021.007).

Air pollution has been associated with adverse health effects across the life-course. Although underlying mechanisms are unclear, several studies suggested pollutant-induced changes in transcriptomic profiles. In this meta-analysis of transcriptome-wide association studies of 656 children and adolescents from three European cohorts participating in the MeDALL Consortium, we found two differentially expressed transcript clusters (FDR p < 0.05) associated with exposure to particulate matter < 2.5 µm in diameter (PM2.5) at birth, one of them mapping to the MIR1296 gene. Further, by integrating gene expression with DNA methylation using Functional Epigenetic Modules algorithms, we identified 9 and 6 modules in relation to PM2.5 exposure at birth and at current address, respectively (including NR1I2, MAPK6, TAF8 and SCARA3). In conclusion, PM2.5 exposure at birth was linked to differential gene expression in children and adolescents. Importantly, we identified several significant interactome hotspots of gene modules of relevance for complex diseases in relation to PM2.5 exposure. ; European Community's 75 Seventh Framework Program under grant agreement numbers: 211250 (ESCAPE), and 76 261357 (MeDALL) ; European Research Council (grant agreement number 757919, TRIBAL) ; Swedish Research Council ; The Swedish Heart-Lung Foundation, Region Stockholm ; Strategic Research Programme (SFO) in Epidemiology, Karolinska Institutet ; Formas ; Swedish Environment Protection Agency ; Swedish Asthma and Allergy Research Foundation ; Cancer and Allergy Foundation ; Swedish Research Council for Health, Working life and Welfare (FORTE 2017-01146) ; Federal Ministry for Education, Science, Research and Technology ; Helmholtz Zentrum Munich ; Research Institute at Marien-Hospital Wesel, LMU Munich, TU Munich ; Leibniz Research-Institute for Environmental Medicine at the University of Düsseldorf ; Federal Ministry for Environment (IUF Düsseldorf, FKZ 20462296) ; Mead Johnson ; Nestlé ; Instituto de Salud Carlos III (Red INMA G03/176; CB06/02/0041; PI04/1436; PI06/0867; PI08/1151; and PI18/01142 ; Generalitat de Catalunya-CIRIT 1999SGR 00241 ; Department of Health of the Basque Government (2005111093) ; Provincial Government of Gipuzkoa (DFG06/002) ; Municipalities of the study area (Zumarraga, Urretxu , Legazpi, 101 Azkoitia y Azpeitia y Beasain) ; Accepted

Blood eosinophil count is associated with a variety of common complex outcomes in epidemiological observation. The aim of this study was to explore the causal association between determined blood eosinophil count and 20 common complex outcomes (10 metabolic, 6 cardiac, and 4 pulmonary). Through Mendelian randomization, we investigated genetic evidence for the genetically determined eosinophil in association with each outcomes using individual-level LifeLines cohort data (n = 13,301), where a weighted eosinophil genetic risk score comprising five eosinophil associated variants was created. We further examined the associations of the genetically determined eosinophil with those outcomes using summary statistics obtained from genome-wide association study consortia (6 consortia and 14 outcomes). Blood eosinophil count, by a 1-SD genetically increased, was not statistically associated with common complex outcomes in the LifeLines. Using the summary statistics, we showed that a higher genetically determined eosinophil count had a significant association with lower odds of obesity (odds ratio (OR) 0.81, 95% confidence interval (CI) [0.74, 0.89]) but not with the other traits and diseases. To conclude, an elevated eosinophil count is unlikely to be causally associated to higher risk of metabolic, cardiac, and pulmonary outcomes. Further studies with a stronger genetic risk score for eosinophil count may support these results.

BACKGROUND: Asthma, rhinitis and eczema often co-occur in children, but their interrelationships at the population level have been poorly addressed. We assessed co-occurrence of childhood asthma, rhinitis and eczema using unsupervised statistical techniques. METHODS: We included 17 209 children at 4 years and 14 585 at 8 years from seven European population-based birth cohorts (MeDALL project). At each age period, children were grouped, using partitioning cluster analysis, according to the distribution of 23 variables covering symptoms 'ever' and 'in the last 12 months', doctor diagnosis, age of onset and treatments of asthma, rhinitis and eczema; immunoglobulin E sensitization; weight; and height. We tested the sensitivity of our estimates to subject and variable selections, and to different statistical approaches, including latent class analysis and self-organizing maps. RESULTS: Two groups were identified as the optimal way to cluster the data at both age periods and in all sensitivity analyses. The first (reference) group at 4 and 8 years (including 70% and 79% of children, respectively) was characterized by a low prevalence of symptoms and sensitization, whereas the second (symptomatic) group exhibited more frequent symptoms and sensitization. Ninety-nine percentage of children with comorbidities (co-occurrence of asthma, rhinitis and/or eczema) were included in the symptomatic group at both ages. The children's characteristics in both groups were consistent in all sensitivity analyses.CONCLUSION:At 4 and 8 years, at the population level, asthma, rhinitis and eczema can be classified together as an allergic comorbidity cluster. Future research including time-repeated assessments and biological data will help understanding the interrelationships between these diseases. ; This work was supported by Mechanisms of the Develop-ment of ALLergy (MeDALL), a collaborative project con-ducted within the European Union under the HealthCooperation Work Programme of the 7th Framework pro-gramme (grant agreement No. 261357)

Background: Prenatal exposure to air pollution has been associated with childhood respiratory disease and other adverse outcomes. Epigenetics is a suggested link between exposures and health outcomes. Objectives: We aimed to investigate associations between prenatal exposure to particulate matter (PM) with diameter <10 (PM10) or <2.5 mu m (PM2.5) and DNA methylation in newborns and children. Methods: We meta-analyzed associations between exposure to PM10 (n=1,949) and PM2.5 (n=1,551) at maternal home addresses during pregnancy and newborn DNA methylation assessed by Illumina Infinium HumanMethylation450K BeadChip in nine European and American studies, with replication in 688 independent newborns and look-up analyses in 2,118 older children. We used two approaches, one focusing on single cytosine-phosphate-guanine (CpG) sites and another on differentially methylated regions (DMRs). We also related PM exposures to blood mRNA expression. Results: Six CpGs were significantly associated [false discovery rate (FDR) <0.05] with prenatal PM10 and 14 with PM2.5 exposure. Two of the PM10-related CpGs mapped to FAM13A (cg00905156) and NOTCH4 (cg06849931) previously associated with lung function and asthma. Although these associations did not replicate in the smaller newborn sample, both CpGs were significant (p<0.05) in 7- to 9-y-olds. For cg06849931, however, the direction of the association was inconsistent. Concurrent PM10 exposure was associated with a significantly higher NOTCH4 expression at age 16 y. We also identified several DMRs associated with either prenatal PM10 and or PM2.5 exposure, of which two PM10-related DMRs, including H19 and MARCH11, replicated in newborns. Conclusions: Several differentially methylated CpGs and DMRs associated with prenatal PM exposure were identified in newborns, with annotation to genes previously implicated in lung-related outcomes. ; ALSPAC: The UK Medical Research Council and the Wellcome Trust (Grant ref. 102215/2/13/2) and the University of Bristol provide core support for ALSPAC. This publication is the work of the authors and P.Y. will serve as guarantors for the contents of this paper. A comprehensive list of grants funding is available on the ALSPAC website (http://www.bristoLac.uk/alspac/external/documents/grant-acknowledgements.pdf). This research was specifically funded by a joint grant from the UK Economic & Social and Biotechnology & Biological Sciences Research Councils (Grant ref. ES/N000498/1). ALSPAC was funded by the BBSRC (BBI025751/1 and BB/I025263/1). Air pollution exposure assessment was funded by Public Health England as part of the MRC-PHE Centre for Environment and Health, funded also by the UK Medical Research Council (Grant ref. MR/L01341X/1). This paper does not necessarily reflect the views of Public Health England or the Department of Health. BAMSE was supported by The Swedish Research Council, The Swedish Heart-Lung Foundation, Freemason Child House Foundation in Stockholm, MeDALL (Mechanisms of the Development of ALLergy) a collaborative project conducted within the European Union (grant agreement No. 261357), Centre for Allergy Research, Stockholm County Council (ALE), Swedish Foundation for Strategic Research (SSF) (RBc08-0027), the Strategic Research Programme (SFO) in Epidemiology at Karolinska Institutet, The Swedish Research Council Foams, and the Swedish Environment Protection Agency. E.M. is supported by a grant from the European Research Council under the European Union (EU) Horizon 2020 (H2020) research and innovation programme (grant agreement number 757919, TRIBAL). O.G. is supported by Forte (Swedish Research Council for Health, Working Life and Welfare) and The Swedish Society for Medical Research. CHS: This work was supported by NIEHS grants K01ES017801, R01ES022216, and P30ES007048. EARLI: This work was supported by NIH grants R01ES016443, R01ES023780, and R01ES017646 as well as by Autism Speaks (AS 5938). ENVIRONAGE: The ENVIRONAGE birth cohort is funded by the European Research Counsil (ERC-2012-StG.310898) and by funds of the Flemisch Scientific Research Council (FWO, N1516112/G.0.873.11N.10). The methylation assays were funded by the European Community's Seventh Framework Programme FP7/2007-2013 project EXPOsOMICS (grant no. 308610). Z.H. is supported by the Exposomics EC FP7 grant (Grant agreement no. 308610). ZH and A.G. and the Epigenetics Group at IARC are supported by grants from the Institut National du Cancer (INCa, Plan Cancer-EVA-Inserm, France) and Association pour la Recherche sur le Cancer (ARC, France). Generation R Study: The general design of the Generation R Study is made possible by financial support from the Erasmus Medical Center (MC), Rotterdam, the Erasmus University Rotterdam, Netherlands Organization for Health Research and Development and the Ministry of Health, Welfare and Sport. The EWAS data was funded by a grant to VWJ from Netherlands Genomics Initiative (NGI)/Netherlands Organisation for Scientific Research (NWO) Netherlands Consortium for Healthy Aging (NCHA; project no. 050-060-810), by funds from the Genetic Laboratory of the Department of Internal Medicine, Erasmus MC. V.W.J. also received a grant from Netherlands Organization for Health Research and Development (VIDI 016.136.361) and a Consolidator Grant from the European Research Council (ERC-2014-CoG-648916). J.F.F. has received funding from the European Union's Horizon 2020 Research and Innovation Programme under grant agreement no. 633595 (DynaHEALTH). This project received funding from the European Union's Horizon 2020 Research and Innovation Programme (733206, LIFECYCLE). HELIX: The research leading to these results has received funding from the European Community's Seventh Framework Programme (FP7/2007-206) under grant agreement no 308333 - the HELIX project. R.G. received the grant of the Lithuanian Agency for Science Innovation and Technology (No. 45 31V-66). The Norwegian Mother and Child Cohort Study (MoBa) is supported by the Ministry of Health and Care Services and the Ministry of Education and Research, NIH/NIEHS (contract no. N01-ES-75558), NIH/NINDS (grant no. 1 UO1 NS 047537-01 and grant no. 2 UO1 NS 047537-06A1). INMA: This study was funded by grants from Institut() de Salud Carlos III (Red INMA G03/176), Generalitat de Catalunya-CIRIT 1999SGR 00241, and EU Commission (261357; 211250; 268479). Piccolipiu: The study was approved and initially funded by the Italian National Centre for Disease Prevention and Control (CCM grant 2010) and by the Italian Ministry of Health (art 12 and 12bis Dl.gs.vo 502/92). The methylation assays were funded by the European Community's Seventh Framework Programme FP7/2007-2013 project EXPOsOMICS (grant no. 308610). Z.H. is supported by the Exposomics EC FP7 grant (Grant agreement no: 308610). Z.H. and A.G. and the Epigenetics Group at IARC are supported by grants from the Institut National du Cancer (INCa, Plan Cancer-EVA-INSERM, France) and Association pour la Recherche sur le Cancer (ARC, France). Rhea: The methylation assays were funded by the European Community's Seventh Framework Programme FP7/2007-2013 project EXPOsOMICS (grant no. 308610). Z.H. is supported by the Exposomics EC FP7 grant (grant agreement no. 308610). ZH and A.G. and the Epigenetics Group at IARC are supported by grants from the Institut National du Cancer (INCa, Plan Cancer-EVA INSERM, France) and Association pour la Recherche sur le Cancer (ARC, France). PRISM: R.J.W. received funding for the PRISM cohort under HL095606 and R01 HL1143396. A.C.J. is supported by R00 ES023450. Project Viva: This Project Viva study was supported by grants from the NIH (NIH R01 HL 111108, R01 NR013945, R01 HD 034568, K24 HD069408, K23 ES022242, P01ES009825, R01AI102960, P30 ES000002) and the U.S. Environmental Protection Agency (EPA) (R832416, RD834798). This publication's contents are solely the responsibility of the grantee and do not necessarily represent the official views of the U.S. Government, the U.S. Department of Health and Human Services or the NIH, or the EPA. Further, the EPA does not endorse the purchase of any commercial products or services mentioned in the publication. MeDALL: The methylation study of MeDALL cohorts was funded by MEDALL, a collaborative project supported by the European Union under the Health Cooperation Work Programme of the 7th Framework Programme (grant agreement no. 261357). The Biobank-Based Integrative Omics Studies (BIOS) Consortium is funded by BBMRI-NL, a research 'infrastructure financed by the Dutch government (NWO 184.021.007). BAMSE: We would like to thank all the families for their participation in the BAMSE study. In addition, we would like to thank E. Haliner, S. Nilsson, and A. Lauber at the BAMSE secretary for invaluable support, as well as Mutation Analysis Facility (MAF) at Karolinska Institutet for genome-wide methylation analysis, and I. Delin for excellent technical assistance. The computations were performed on resources provided by SNIC through Uppsala Multidisciplinary Center for Advanced Computational Science (UPPMAX) under Project b201.4110.