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Meta-Analysis
. 2019 Jun;143(6):2062-2074.
doi: 10.1016/j.jaci.2018.11.043. Epub 2018 Dec 21.

Epigenome-wide meta-analysis of DNA methylation and childhood asthma

Sarah E Reese  1 Cheng-Jian Xu  2 Herman T den Dekker  3 Mi Kyeong Lee  1 Sinjini Sikdar  1 Carlos Ruiz-Arenas  4 Simon K Merid  5 Faisal I Rezwan  6 Christian M Page  7 Vilhelmina Ullemar  8 Phillip E Melton  9 Sam S Oh  10 Ivana V Yang  11 Kimberley Burrows  12 Cilla Söderhäll  13 Dereje D Jima  14 Lu Gao  15 Ryan Arathimos  16 Leanne K Küpers  17 Matthias Wielscher  18 Peter Rzehak  19 Jari Lahti  20 Catherine Laprise  21 Anne-Marie Madore  22 James Ward  1 Brian D Bennett  1 Tianyuan Wang  1 Douglas A Bell  1 BIOS consortiumJudith M Vonk  23 Siri E Håberg  24 Shanshan Zhao  1 Robert Karlsson  8 Elysia Hollams  25 Donglei Hu  10 Adam J Richards  11 Anna Bergström  26 Gemma C Sharp  27 Janine F Felix  28 Mariona Bustamante  29 Olena Gruzieva  26 Rachel L Maguire  30 Frank Gilliland  15 Nour Baïz  31 Ellen A Nohr  32 Eva Corpeleijn  33 Sylvain Sebert  34 Wilfried Karmaus  35 Veit Grote  19 Eero Kajantie  36 Maria C Magnus  37 Anne K Örtqvist  8 Celeste Eng  10 Andrew H Liu  38 Inger Kull  39 Vincent W V Jaddoe  28 Jordi Sunyer  40 Juha Kere  41 Cathrine Hoyo  42 Isabella Annesi-Maesano  31 Syed Hasan Arshad  43 Berthold Koletzko  19 Bert Brunekreef  44 Elisabeth B Binder  45 Katri Räikkönen  46 Eva Reischl  47 John W Holloway  48 Marjo-Riitta Jarvelin  49 Harold Snieder  33 Nabila Kazmi  16 Carrie V Breton  15 Susan K Murphy  50 Göran Pershagen  26 Josep Maria Anto  40 Caroline L Relton  12 David A Schwartz  11 Esteban G Burchard  51 Rae-Chi Huang  25 Wenche Nystad  24 Catarina Almqvist  52 A John Henderson  53 Erik Melén  54 Liesbeth Duijts  55 Gerard H Koppelman  56 Stephanie J London  57
Affiliations
Meta-Analysis

Epigenome-wide meta-analysis of DNA methylation and childhood asthma

Sarah E Reese et al. J Allergy Clin Immunol. 2019 Jun.

Abstract

Background: Epigenetic mechanisms, including methylation, can contribute to childhood asthma. Identifying DNA methylation profiles in asthmatic patients can inform disease pathogenesis.

Objective: We sought to identify differential DNA methylation in newborns and children related to childhood asthma.

Methods: Within the Pregnancy And Childhood Epigenetics consortium, we performed epigenome-wide meta-analyses of school-age asthma in relation to CpG methylation (Illumina450K) in blood measured either in newborns, in prospective analyses, or cross-sectionally in school-aged children. We also identified differentially methylated regions.

Results: In newborns (8 cohorts, 668 cases), 9 CpGs (and 35 regions) were differentially methylated (epigenome-wide significance, false discovery rate < 0.05) in relation to asthma development. In a cross-sectional meta-analysis of asthma and methylation in children (9 cohorts, 631 cases), we identified 179 CpGs (false discovery rate < 0.05) and 36 differentially methylated regions. In replication studies of methylation in other tissues, most of the 179 CpGs discovered in blood replicated, despite smaller sample sizes, in studies of nasal respiratory epithelium or eosinophils. Pathway analyses highlighted enrichment for asthma-relevant immune processes and overlap in pathways enriched both in newborns and children. Gene expression correlated with methylation at most loci. Functional annotation supports a regulatory effect on gene expression at many asthma-associated CpGs. Several implicated genes are targets for approved or experimental drugs, including IL5RA and KCNH2.

Conclusion: Novel loci differentially methylated in newborns represent potential biomarkers of risk of asthma by school age. Cross-sectional associations in children can reflect both risk for and effects of disease. Asthma-related differential methylation in blood in children was substantially replicated in eosinophils and respiratory epithelium.

Keywords: Epigenetics; asthma; childhood; drug development; methylation; newborn.

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Conflict of interest statement

Disclosure of potential conflict of interest: C. Ruiz-Arenas receives grant support from Agència de Gestió d’Ajuts Universitaris i de Recerca. S. S. Oh, C. Eng, and E. G. Burchard receive grant support from the NIH and the Tobacco-Related Disease Research Program. I. V. Yang and C. V. Breton receive grant support from the National Institutes of Health (NIH). C. Söderhäll receives grant support from several competitive grants from public and private sources and receives royalties from book chapters in study material. R. Arathimos and G. C. Sharp receive support from the Medical Research Council. E. Kajantie receives grant support from the European Commission, Academy of Finland, Foundation for Pediatric Research, Sigrid Jus×lius Foundation, Signe and Ane Gyllenberg Foundation, and Juho Vainio Foundation. G. Pershagen receives grant support from the Swedish Research Council. C. L. Relton receives grant support from Wellcome Trust. C. Almqvist receives grant support from the Swedish Research Council through the Swedish Initiative for Research on Microdata in the Social And Medical Sciences (SIMSAM) framework, Stockholm County Council (ALF-projects), Swedish Heart-Lung Foundation, and Swedish Asthma and Allergy Association’s Research Foundation. A. J. Henderson receives grant support from the Medical Research Council and Wellcome Trust. E. Melén received grant support from the European Research Council during conduct of the study and lecture fees from Thermo Fisher Scientific and Meda outside the submitted work. G. H. Koppelman receives grant support from the Lung Foundation of the Netherlands, MEDALL EU FP7, the UBBO EMMIUS Foundation, TEVA The Netherlands, Vertex, GlaxoSmithKline, and the TETRI Foundation. The rest of the authors declare that they have no relevant conflicts of interest.

Figures

FIG 1.
FIG 1.
Meta-analysis of asthma in relation to newborn methylation: A, Manhattan plot; B, volcano plot. The model is adjusted for covariates and cell types.
FIG 2.
FIG 2.
Meta-analysis of asthma in relation to childhood methylation: A, Manhattan plot; B, volcano plot. The model is adjusted for covariates and cell types. CpGs corresponding to more than 1 gene with significant CpGs (FDR < 0.05) are highlighted in red.
FIG 3.
FIG 3.
A network is shown for 4 categories of disease and biological functions overlapping between analyses of asthma in relation to either newborn or childhood methylation: immunological disease, cell-mediated immune response, inflammatory disease, and tissue morphology. A gene is connected to a disease or function if it has been previously shown to be involved in it. All genes marked in red are implicated from newborn methylation analyses, and those marked in in orange are implicated from childhood methylation analyses.

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