# Shared DNA methylation signatures in childhood allergy: The MeDALL study

Cheng-Jian Xu, Olena Gruzieva, Cancan Qi, Ana Esplugues, Ulrike Gehring, Anna Bergström, Dan Mason, Leda Chatzi, Daniela Porta, Karin C Lodrup Carlsen, et al.

<figure><img src="image_1.png" /></figure>

To cite this version:

Cheng-Jian Xu, Olena Gruzieva, Cancan Qi, Ana Esplugues, Ulrike Gehring, et al. Shared DNA methylation signatures in childhood allergy: The MeDALL study. Journal of Allergy and Clinical Immunology, 2021, 147 (3), pp.1031 - 1040. 10.1016/j.jaci.2020.11.044. hal-03477217

HAL Id: hal-03477217

https://hal.sorbonne-universite.fr/hal-03477217

Submitted on 13 Dec 2021

HAL is a multi-disciplinary open access
archive for the deposit and dissemination of sci-
entific research documents, whether they are pub-
lished or not. The documents may come from
teaching and research institutions in France or
abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est
destinée au dépôt et à la diffusion de documents
scientifiques de niveau recherche, publiés ou non,
émanant des établissements d'enseignement et de
recherche français ou étrangers, des laboratoires
publics ou privés.

<figure><img src="image_2.png" /></figure>

Distributed under a Creative Commons Attribution 4.0 International License
# Shared DNA methylation signatures in childhood allergy: The MeDALL study

<figure><img src="image_3.png" /></figure>

Check for updates

Cheng-Jian Xu, PhD,<sup>a,b,c,d,e*</sup> Olena Gruzieva, MD, PhD,<sup>f,g,*</sup> Cancan Qi, MSc,<sup>a,b</sup> Ana Esplugues, PhD,<sup>h,i,j</sup>
Ulrike Gehring, PhD,<sup>k</sup> Anna Bergström, PhD,<sup>f</sup> Dan Mason, PhD,<sup>l</sup> Leda Chatzi, MD, PhD,<sup>m</sup> Daniela Porta, MSc,<sup>n</sup>
Karin C. Lodrup Carlsen, MD, PhD,<sup>o,p</sup> Nour Baïz, PhD,<sup>q</sup> Anne-Marie Madore, PhD,<sup>r</sup> Harri Alenius, PhD,<sup>f</sup>
Bianca van Rijkom, BSc,<sup>s</sup> Soesma A. Jankipersadsing, MSc,<sup>s</sup> Pieter van der Vlies, BSc,<sup>s,t</sup> Inger Kull, PhD,<sup>u</sup>
Marianne van Hage, MD, PhD,<sup>v,w</sup> Mariona Bustamante, PhD,<sup>j,x,y</sup> Aitana Lertxundi, PhD,<sup>j,z,aa</sup> Matias Torrent, MD, PhD,<sup>bb,cc</sup>
Gillian Santorelli, MSc,<sup>l</sup> Maria Pia Fantini, MD,<sup>dd</sup> Vegard Hovland, MD, PhD,<sup>p</sup> Giancarlo Pesce, PhD,<sup>q</sup> the BIOS
Consortium, Nanna Fyhrquist, PhD,<sup>f,ee</sup> Tiina Laatikainen, MD, PhD,<sup>ff,gg</sup> Martijn C. Nawijn, PhD,<sup>b,hh</sup> Yang Li, PhD,<sup>c,d,e</sup>
Cisca Wijmenga, PhD,<sup>s</sup> Mihai G. Netea, MD, PhD,<sup>e,ii</sup> Jean Bousquet, MD, PhD,<sup>jj,kk</sup> Josep M. Anto, MD, PhD,<sup>j,x,y,ll</sup>
Catherine Laprise, PhD,<sup>r,mm,nn</sup> Tari Haahtela, MD, PhD,<sup>oo</sup> Isabella Annesi-Maesano, MD, PhD,<sup>q</sup>
Kai-Håkon Carlsen, MD, PhD,<sup>o,p</sup> Davide Gori, MD, PhD,<sup>dd</sup> Manolis Kogevinas, MD, PhD,<sup>x</sup> John Wright, FRCP,<sup>l</sup>
Cilla Söderhäll, PhD,<sup>pp,qq</sup> Judith M. Vonk, PhD,<sup>b,rr</sup> Jordi Sunyer, MD, PhD,<sup>j,x,y,ll</sup> Erik Melén, MD, PhD,<sup>u,ss</sup> and
Gerard H. Koppelman, MD, PhD<sup>a,b</sup>
Groningen, Nijmegen, Utrecht, and Metslawier, The Netherlands; Hannover,
Bonn, and Berlin, Germany; Stockholm, Sweden; València, Madrid, Barcelona, Bizkaia, Leioa, Donostia-San Sebastian, Balearic Islands,
and Menorca, Spain; Bradford, United Kingdom; Los Angeles, Calif; Rome and Bologna, Italy; Oslo, Norway; Paris and Montpellier, France;
Québec City and Saguenay, Québec, Canada; and Helsinki and Kuopio, Finland

From <sup>a</sup>the Department of Pediatric Pulmonology and Pediatric Allergy, Beatrix Children's Hospital, University Medical Center Groningen; <sup>b</sup>the GRIAC Research Institute, <sup>c</sup>the Department of Genetics, <sup>hh</sup>the Department of Pathology and Medical Biology, Experimental Pulmonology and Inflammation Research, and <sup>rr</sup>the Department of Epidemiology, University Medical Center Groningen, University of Groningen; <sup>te</sup>the Centre for Individualized Infection Medicine, CiiM, a joint venture between Hannover Medical School and the Helmholtz Centre for Infection Research; <sup>th</sup>TWINCORE, Centre for Experimental and Clinical Infection Research, a joint venture between the Hannover Medical School and the Helmholtz Centre for Infection Research; <sup>ct</sup>the Department of Internal Medicine and Radboud Center for Infectious Diseases, Radboud University Medical Center, Nijmegen; <sup>th</sup>the Institute of Environmental Medicine, Karolinska Institutet, Stockholm; <sup>iv</sup>Division of Immunology and Allergy, <sup>pp</sup>the Department of Women's and Children's Health, and <sup>qq</sup>the Department of Biosciences and Nutrition, Karolinska Institutet, Stockholm; <sup>st</sup>the Centre for Occupational and Environmental Medicine, Region Stockholm; <sup>th</sup>the Nursing Department, Faculty of Nursing and Chiropody, Universitat de València; <sup>lF</sup>FISABIO-Universitat Jaume I-Universitat de València Joint Research Unit of Epidemiology and Environmental Health; <sup>lC</sup>IBER Epidemiología y Salud Pública (CIBERESP), Madrid; <sup>h</sup>the Institute for Risk Assessment Sciences, Utrecht University; <sup>l</sup>the Bradford Institute for Health Research; <sup>th</sup>the Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles; <sup>th</sup>the Department of Epidemiology, Lazio Regional Health Service, Rome; <sup>o</sup>the Division of Paediatric and Adolescent Medicine, The Faculty of Medicine, University of Oslo; <sup>th</sup>the Division of Paediatric and Adolescent Medicine, Oslo University Hospital; <sup>th</sup>the Sorbonne University and INSERM, Epidemiology of Allergic and Respiratory Diseases (EPAR) Department, IPLESP, Medical School Saint Antoine, Paris; <sup>lD</sup>épartement des sciences fondamentales and <sup>mm</sup>Centre intersectoriel en santé durable, Université du Québec à Chicoutimi, Saguenay; <sup>lHZ</sup>PC Research BV, Metslawier; <sup>th</sup>the Department of Clinical Sciences and Education, Karolinska Institutet, Södersjukhuset, Stockholm; <sup>th</sup>Karolinska University Hospital, Stockholm; <sup>lIS</sup>Global, Institute of Global Health, Barcelona; <sup>h</sup>Universitat Pompeu Fabra, Barcelona; <sup>th</sup>the Preventive Medicine and Public Health Department, University of Basque Country (UPV/EHU), Leioa; <sup>th</sup>the Health Research institute Biodonostia, Donostia-San Sebastian, Gipuzkoa; <sup>th</sup>the Health Research Institute of the Balearic Islands; <sup>cc</sup>ib-salut, Area de Salut de Menorca; <sup>dd</sup>the Department of Biomedical and Neuromotor Sciences, University of Bologna; <sup>th</sup>the Human Microbiome Program, Medicum, University of Helsinki; <sup>ff</sup>the Finnish Institute for Health and Welfare, Helsinki; <sup>gg</sup>the Institute of Public Health and Clinical Nutrition,

University of Eastern Finland, Kuopio; <sup>i</sup>the Department for Genomics and Immun regulation, Life and Medical Sciences Institute (LIMES), University of Bonn; <sup>j</sup>the University Hospital, Montpellier; <sup>k</sup>the Department of Dermatology, Charité, Berlin; <sup>l</sup>IMIM (Hospital del Mar Medical Research Institute), Barcelona; <sup>mm</sup>Centre de santé et de services sociaux du Saguenay-Lac-Saint-Jean; <sup>oo</sup>the Skin and Allergy Hospital, Helsinki University Hospital, University of Helsinki; and <sup>th</sup>the Sachs' Children's Hos pital, Stockholm.

*These authors contributed equally to this work as first authors.

The Mechanisms of the Development of Allergy (MeDALL) European Union project was supported by the Seventh Framework Programme (grant agreement 261357). The Biobank-Based Integrative Omics Studies (BIOS) Consortium was funded by BBMRI-NL, a research infrastructure financed by the Dutch government (NWO 184.021.007). Cohort-specific funding is described in the Online Supplement (at www.jacionline.org). The funders of the study had no role in design of the study, data gathering, analysis, interpretation, writing of the article, or in the decision to submit it for publication. M.G.N. was supported by a European Research Council Advanced Grant (833247) and a Spinoza Grant from The Netherlands Organization for Scientific Research.

Disclosure of potential conflict of interest: M. Hage reports personal fees from Thermo Fisher Scientific; ALK; Biomay AG, Vienna, Austria; and Hycor Biomedical LLC outside the submitted work. G. H. Koppelman participated in advisory board meetings for GSK and Pure-IMS outside the submitted work. The rest of the authors declare that they have no relevant conflicts of interest.

Received for publication May 7, 2020; revised October 14, 2020; accepted for publication November 19, 2020.

Available online December 15, 2020.

Corresponding author: Cheng-Jian Xu, PhD, Centre for Individualized Infection Medicine, c/o TWINCORE Feodor-Lynen-Street 7, 30625, Hannover, Germany. E-mail: Xu.Chengjian@mh-hannover.de.

<figure><img src="image_4.png" /></figure>

The CrossMark symbol notifies online readers when updates have been made to the article such as errata or minor corrections

0091-6749

© 2020 The Authors. Published by Elsevier Inc. on behalf of the American Academy of Allergy, Asthma & Immunology. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

https://doi.org/10.1016/j.jaci.2020.11.044
**Background:** Differential DNA methylation associated with allergy might provide novel insights into the shared or unique etiology of asthma, rhinitis, and eczema.

**Objective:** We sought to identify DNA methylation profiles associated with childhood allergy.

**Methods:** Within the European Mechanisms of the Development of Allergy (MeDALL) consortium, we performed an epigenome-wide association study of whole blood DNA methylation by using a cross-sectional design. Allergy was defined as having symptoms from at least 1 allergic disease (asthma, rhinitis, or eczema) and positive serum-specific IgE to common aeroallergens. The discovery study included 219 case patients and 417 controls at age 4 years and 228 case patients and 593 controls at age 8 years from 3 birth cohorts, with replication analyses in 325 case patients and 1111 controls. We performed additional analyses on 21 replicated sites in 785 case patients and 2124 controls by allergic symptoms only from 8 cohorts, 3 of which were not previously included in analyses.

**Results:** We identified 80 differentially methylated CpG sites that showed a 1% to 3% methylation difference in the discovery phase, of which 21 (including 5 novel CpG sites) passed genome-wide significance after meta-analysis. All 21 CpG sites were also significantly differentially methylated with allergic symptoms and shared between asthma, rhinitis, and eczema. The 21 CpG sites mapped to relevant genes, including *ACOT7*, *LMAN3*, and *CLDN23*. All 21 CpG sites were differently methylated in asthma in isolated eosinophils, and 10 were replicated in respiratory epithelium.

**Conclusion:** Reduced whole blood DNA methylation at 21 CpG sites was significantly associated with childhood allergy. The findings provide novel insights into the shared molecular mechanisms underlying asthma, rhinitis, and eczema. (J Allergy Clin Immunol 2021;147:1031-40.)

**Key words:** Epigenetics, DNA methylation, allergy, IgE, children

Allergic diseases, such as asthma, rhinitis, and eczema are of great public health concern and constitute the most prevalent childhood illnesses worldwide.¹ Many allergic diseases have a strong hereditary component, yet large-scale genome-wide association studies (GWASs)²⁻⁴ indicate that genetic polymorphisms explain only a limited proportion of the susceptibility to allergy. Moreover, the dramatic rise in prevalence of IgE-mediated allergic diseases in Western European countries over the last decades can be explained not by genetic factors but likely by environmental factors and lifestyle changes.⁵ The analysis of DNA methylation in relation to allergic diseases has therefore attracted much interest because epigenetic modification may mediate environmental effects on the development of allergic diseases.⁶,⁷ So far, many studies have linked the DNA methylene to a single trait, such as asthma,⁸,⁹ rhinitis,¹⁰ eczema,¹¹ total¹²,¹³ and allergen-specific IgE levels,¹⁴⁻¹⁶ and food allergy.¹⁴,¹⁷ However, allergic diseases often coexist in the same individual,¹⁸ an overlap that is partly explained by IgE sensitization. A recent large-scale GWAS² indicated that the majority of genetic risk factors for allergy are shared between asthma, eczema, and rhinitis, suggesting many shared causal mechanisms.¹⁸,¹⁹ So far, no study has assessed shared epigenetic factors related to these 3 allergic diseases.

**Abbreviations used**

BIOS: Biobank-Based Integrative Omics Studies

EDEN: Déterminants pré et post-natals du développement de la santé de l'enfant

eQTM: Expression quantitative trait methylation

EWAS: Epigenome-wide association study

GWAS: Genome-wide association study

INMA: Infancia y Medio Ambiente

MeDALL: Mechanisms of the Development of Allergy

NK: Natural killer

PIAMA: Prevention and Incidence of Asthma and Mite Allergy

SNP: Single-nucleotide polymorphism

To address this question, we implemented a large-scale epigenome-wide association study (EWAS) of allergy and whole blood DNA methylation in 3 birth cohorts participating in the Mechanisms of the Development of Allergy (MeDALL) consortium. This is a follow-up of our previous article on childhood asthma.⁸ In the current study, we investigated DNA methylation associated with IgE-mediated allergic diseases, asthma, rhinitis, or eczema in children at the ages of 4 and 8 years, followed by replication and meta-analysis of children up to 16 years of age. We further tested whether our differently methylated CpG sites were associated with allergic symptoms only, without inclusion of specific IgE in our case definition, were shared or different between children with asthma, rhinitis, or eczema only, and we also investigated the DNA methylation of replicated CpG sites in isolated eosinophils and nasal epithelial cells. Finally, we functionally annotated these CpG sites.

## METHODS

The Methods section in this article's Online Repository (available at www.jacionline.org) provides details on the methods used and cohorts included in this study. The study design and structure of this article are presented in Fig 1.

## Allergy definition

The primary outcome of the study was allergy, defined as agreed on by experts from the MeDALL consortium.¹⁸ A child was considered to have an allergy if he or she had at least 1 of 3 diseases—asthma, rhinitis, or eczema— as well as specific IgE against any of the tested allergens (≥0.35 IU/mL).

The term *allergy symptoms only* was defined as the situation in which a child had at least 1 of the 3 diseases asthma, rhinitis, and eczema, without consideration of information on the specific IgE results. This definition was also used for comparisons between single diseases.

Detailed definitions of allergy, asthma, rhinitis, and eczema, as well as specific IgE positivity in each cohort, are provided in the Online Repository.

## Study population and design

The present study was conducted within the framework of the MeDALL consortium and included cohorts with DNA methylation data measured at birth and/or during childhood. The study consisted of 2 phases, discovery and replication. In discovery and replication, allergic disease end point/IgE data were collected at the same time as DNA methylation analyses.

In the discovery phase, whole blood DNA methylation was measured in participants of 3 cohorts, namely, Barn/Children, Allergy, Milieu, Stockholm, Epidemiology (Sweden), Infancia y Medio Ambiente (INMA) (Sabadel, Spain), and Prevention and Incidence of Asthma and Mite Allergy (PIAMA) (The Netherlands) (Table I and see Table E1 in the Online Repository at
<figure><img src="image_5.png" /><figcaption>**FIG 1.** Overview of the study design. The present EWAS study consisted of a discovery and replication phase, followed by a meta-analysis. The top significant CpG sites from the discovery phase (n = 1457) were selected for replication from 5 European cohorts (n = 1436). Subsequently, results from the discovery and replication phases were combined in meta-analysis. The 21 replicated CpG sites were further investigated in an allergy symptoms-only analysis based on 8 cohorts (n = 2909), the lookup analysis in the cord blood and nasal epithelia cell, and case patient-only analysis, as well as functional analyses, including methylation quantitative trait loci (MeQTLs), eQTM, functional enrichment, and cell type annotation. **BIB**, Born in Bradford; **ECA**, Environment and Childhood Asthma Study in Oslo.</figcaption></figure>

www.jacionline.org). As DNA methylation is age specific,²⁰ we specified beforehand that the discovery analysis would be performed separately in 2 age groups, 4 years and 8 years. The discovery study was enriched with case patients with allergic disease and consisted of 219 case patients with allergy and 417 controls at age 4 years, as well as 228 case patients with allergy, and 593 controls at age 8 years. After identification of differentially methylated CpG sites, we performed replication analysis in 325 case patients with allergy and 1111 controls from 5 cohorts, namely, the cohorts EDEN (France), Environment and Childhood Asthma Study in Oslo (Norway), PIAMA (The Netherlands), INMA (Menorca, Spain), and Karelia (Finland), after which we meta-analyzed the results (Table I and see Table E1). Any individuals whose samples had been used in the discovery studies have been excluded in the replication.

We conducted an additional allergy symptoms-only analysis to test the association of allergy-replicated CpG sites in 785 case patients and 2124 controls from 8 cohorts, including the cohorts Born in Bradford (United Kingdom), EDEN (France), Environment and Childhood Asthma Study in Oslo (Norway), Karelia (Finland), PIAMA, Mother-Child Cohort in Crete (Greece), Robbic (Italy [the subsets Bologna and Rome]), and INMA (Spain [the subsets Gipuzkoa, Menorca, and València]) (Table I and see Table E1).

Furthermore, we investigated potential shared or disease-specific DNA methylation markers by comparing 3 nonoverlapping groups of case patients

who had a single allergic disease, namely, asthma only, rhinitis only, or eczema only. Thus, the following groups were compared: with asthma versus with rhinitis (118 vs 118), with asthma versus with eczema (252 vs 179), and with rhinitis versus with eczema (156 vs 170). Information on IgE sensitization status was not considered in the case-only analyses.

We investigated whether cord blood DNA methylation levels at replicated CpG sites could predict allergy at age 4 to 5 years in 298 children from the EDEN, and INMA-Sabadel cohorts (see Table E2 in the Online Repository at www.jacionline.org). We subsequently studied whether the allergy-replicated CpG sites in whole blood were also differentially methylated in nasal brush samples from 16-year-old children in the PIAMA cohort and isolated eosinophils (16 case patients with asthma and 8 controls aged 2-56 years) from families from the Saguenay–Lac-Saint-Jean region in Canada²¹ (see Table E2). Detailed information on these cohorts is provided in the Online Repository materials (at www.jacionly.org).

The medical ethics committees of all the institutions approved this study. Written informed consent was obtained from parents or legal guardians of all participating children.

## DNA methylation measurements

In the discovery analysis, DNA methylation was measured by Illumina Infinium HumanMethylation450 BeadChips (Illumina, San Diego, Calif), whereas in the cohorts contributing to the replication, it was measured by either Illumina Infinium HumanMethylation450 BeadChips or iPlex (Agena Biosciences, Hamburg, Germany). We applied the same quality control of DNA methylation data and covariates as published previously.⁸

## Functional follow-up of significant DNA methylation findings

We searched for the effects of genetic variants on DNA methylation variation (*cis* and *trans* methylation quantitative trait loci) by using the public Biobank-Based Integrative Omics Studies (BIOS) consortium database (the BIOS QTL browser, http://genenetwork.nl/biosqtlbrowser/). We associated blood CpG methylation with whole genome gene expression by RNA sequencing in the BIOS consortium data set.²² CpG sites were annotated by using Genomic Regions Enrichment of Annotations Tool.²³ Functional enrichment analysis was done by overlapping our replicated CpG sites with histone marks and chromatin states of 27 blood cell types in the Roadmap Epigenome Project.²⁴ Gene expression sets associated with replicated CpG sites were interrogated for cell type specificity using the 500 Functional Genomics Project data set.²⁵,²⁶

## Statistical analyses

Allergy-associated differentially methylated CpG sites were identified by robust linear regression to account for potential outliers and heteroscedasticity in the data,²⁷ adjusted for sex, cohort, and technical covariables. We used models without adjustment for blood cell type as the main model for discovery, as well as replication and report cell type-corrected models by inclusion of estimated cell type proportions²⁸ as covariates in sensitivity analyses. For regional analysis, comb-p²⁹ was used to identify differentially methylated regions by using the summary statistics from models of single CpG site analysis.

We defined genome-wide significance by using Bonferroni correction (*P* < 1.14 × 10⁻⁷ [439,306 tests]). In each age group, CpG sites with genome-wide significance were taken further for replication. If fewer than 10 CpG sites met the genome-wide significance level, the top 10 CpG sites were selected for replication. We performed inverse variance-weighted fixed-effects meta-analyses with METAL,³⁰ or random effects meta-analysis,³¹ the latter in the case of a heterogeneity χ² test *P* value less than .05. Our replicated CpG sites comprised those that were significantly associated with allergy in the meta-analysis of the replication samples (Bonferroni correction; *P* < .0006 [80 tests]) and passed the epigenome-wide significance threshold by using Bonferroni correction (*P*
<table><caption>TABLE I. Study characteristics of the discovery and replication cohorts in the whole blood DNA methylation analyses</caption><thead><tr><th>Cohort</th><th>Country</th><th>Age group</th><th>n</th><th>Age, (y), mean (SD)</th><th>Male sex, no. (%)</th><th>Individuals with allergy (according to questionnaire + aeroallergen sIgE level)</th><th>Design</th></tr></thead><tbody><tr><td>BAMSE</td><td>Sweden</td><td>Preschool age</td><td>247</td><td>4.26 (0.20)</td><td>134 (54.3%)</td><td>117 (47.4%)</td><td>Discovery</td></tr><tr><td>INMA-SAB</td><td>Spain</td><td></td><td>166</td><td>4.35 (0.23)</td><td>84 (50.6%)</td><td>38 (22.9%)</td><td></td></tr><tr><td>PIAMA</td><td>The Netherlands</td><td></td><td>223</td><td>4.08 (0.21)</td><td>119 (53.4%)</td><td>64 (28.7%)</td><td></td></tr><tr><td>BAMSE</td><td>Sweden</td><td>School age</td><td>235</td><td>8.32 (0.41)</td><td>125 (53.2%)</td><td>96 (40.9%)</td><td></td></tr><tr><td>BAMSE-epi</td><td>Sweden</td><td></td><td>383</td><td>8.30 (0.52)</td><td>207 (54.0%)</td><td>75 (19.6%)</td><td></td></tr><tr><td>PIAMA</td><td>The Netherlands</td><td></td><td>203</td><td>8.06 (0.28)</td><td>101 (49.8%)</td><td>57 (28.1%)</td><td></td></tr><tr><td>EDEN</td><td>France</td><td>Preschool age</td><td>143</td><td>5.65 (0.10)</td><td>87 (60.8%)</td><td>22 (15.4%)</td><td>Replication</td></tr><tr><td>BIB</td><td>United Kingdom</td><td></td><td>514</td><td>4.53 (0.36)</td><td>278 (54.1%)</td><td>NA</td><td></td></tr><tr><td>INMA-GIP</td><td>Spain</td><td></td><td>74</td><td>4</td><td>36 (48.6%)</td><td>NA</td><td></td></tr><tr><td>Rhea</td><td>Greece</td><td></td><td>490</td><td>4.26 (0.27)</td><td>254 (51.8%)</td><td>NA</td><td></td></tr><tr><td>ECA</td><td>Norway</td><td>School age</td><td>213</td><td>10.89 (0.78)</td><td>112 (52.6%)</td><td>35 (16.4%)</td><td></td></tr><tr><td>INMA-VAL</td><td>Spain</td><td></td><td>58</td><td>7.50 (0.20)</td><td>31 (53.4%)</td><td>NA</td><td></td></tr><tr><td>PIAMA</td><td>The Netherlands</td><td></td><td>361</td><td>8.30 (0.46)</td><td>193 (53.5%)</td><td>46 (12.7%)</td><td></td></tr><tr><td>Robbic-Bologna</td><td>Italy</td><td></td><td>123</td><td>7.82 (0.51)</td><td>63 (51.2%)</td><td>NA</td><td></td></tr><tr><td>Robbic-Rome</td><td>Italy</td><td></td><td>214</td><td>8.73 (0.27)</td><td>108 (50.5%)</td><td>NA</td><td></td></tr><tr><td>Karelia</td><td>Finland</td><td>Adolescent age</td><td>98</td><td>15.74 (1.59)</td><td>38 (38.8%)</td><td>35 (35.7%)</td><td></td></tr><tr><td>INMA-MEN</td><td>Spain</td><td></td><td>75</td><td>14</td><td>35 (46.7%)</td><td>14 (18.7%)</td><td></td></tr><tr><td>PIAMA</td><td>The Netherlands</td><td></td><td>546</td><td>16.35 (0.22)</td><td>271 (49.6%)</td><td>115 (21.1%)</td><td></td></tr></tbody></table>

BAMSE, Barn/Children, Allergy, Milieu, Stockholm, Epidemiology; BAMSE-epi, BAMSE-epigene; BIB, Born in Bradford; ECA, Environment and Childhood Asthma Study in Oslo; GIP, Gipuzkoa; INMA, Infancia y Medio Ambiente; MEN, Menorca; NA, not available; SAB, Sabadell; sIgE, specific IgE; VAL, València.

<1.14 × 10⁻⁷) in the meta-analysis of all studies (discovery and replication). To avoid unstable effect estimates owing to small numbers, we set a minimum of 10 case patients per participating cohort to be included in the analyses. Detailed description of the functional follow-up is provided in the Methods section of the Online Repository.

# RESULTS

## Discovery analyses

The baseline characteristics of the study populations are presented in Tables I and E1. In the discovery population, allergy prevalence ranged from 22.9% to 47.4% at age 4 years and from 19.6% to 40.9% at age 8 years. In the replication population with IgE data available, 12.7% to 16.4% of children fulfilled the definition of allergy at preschool age and school age, respectively, and 18.7% to 35.7% fulfilled the definition during adolescence.

At age 4 years, the discovery EWAS analysis identified 1 genome-wide significant CpG site, namely, cg15344640, annotated to Max dimerization protein 3 (MXD3) and lectin, mannose binding 2 (LMAN2) gene (P = 2.97 × 10⁻⁸ [Fig 2, A and see Fig E1, A and Table E3 in the Online Repository at www.jacionline.org]; genomic inflation factor λ = 1.15). According to our prespecified plan, we selected the top 10 CpG sites for replication in participants at age 4 years (see Table E3). In participants at age 8 years, 74 CpG sites passed genome-wide significance threshold, with the strongest association (P = 1.76 × 10⁻¹⁰) found for cg03695871 annotated to the adaptor related protein complex 5 subunit beta 1 (AP5B1) and ribonuclease H2 subunit C (RNASEH2C) genes (Fig 2, B and see and Fig E1, B and Table E4 in the Online Repository at www.jacionline.org [λ = 1.09]). White blood cell composition was estimated in all discovery cohorts; we did not observe significant, consistent cell composition differences between the allergy and control groups with regard to 7 cell types in our discovery cohorts at age 4 and 8 years (see Fig E2 and Table E5 in the Online Repository at www.jacionline.org in the Online Repository at www.jacionline.org). However, the association of CpG methylation with allergy became less significant after eosinophil and neutrophil correction:

the P values after correction ranged from 1.71 × 10⁻² to 1.12 × 10⁻⁵ versus from 3.58 × 10⁻⁷ to 8.27 × 10⁻¹⁰ before correction (see Tables E3 and E4), which did suggest that at least part of the results were driven by cell type. Between the top 10 CpG sites at age 4 years and the 74 genome-wide significant CpG sites at age 8 years, 4 CpG sites (cg13628444, cg20885063, cg11456013 and cg03131767) were overlapping; thus, 80 unique CpG sites were selected for replication. Differentially methylated regions analyses identified regions near genes (such as RUNX3, IL1B, IL13 and AP5B1) that were previously implicated in the development of allergy (see Tables E6 and E7 in the Online Repository at www.jacionline.org).

## Replication and meta-analysis

Iplex assays for 70 of these 80 CpG sites were available with use of the Iplex design and passed quality control. Two of 10 the CpG sites selected at age 4, as well as 19 of 74 significant CpG sites at age 8 years, were significantly associated with allergy across childhood in the replication setting (Table II). With regard to all 21 replicated CpG sites, subjects with allergy had lower methylation levels than the controls did. Genes annotated to these 21 CpG sites were investigated via literature review (see Table E8 in the Online Repository at www.jacionline.org). In the meta-analysis of the discovery and replication results (Table II), the most significant association (P = 9.84 × 10⁻²¹) was observed for cg06483820 annotated to A-kinase anchoring protein 1 (AKAP1) and Musashi RNA binding protein 2 (MSI2). Forest plots showing cohort-specific and combined estimates and 95% CIs of all replicated and nonreplicated CpG sites are shown in Fig E3 to E6 (in this article's Online Repository at www.jacionline.org).

## Additional replication and functional analyses

In an additional analysis, all 21 aforementioned CpG sites were significantly associated with allergy defined by symptoms only
A

<figure><img src="image_6.png" /></figure>

B

<figure><img src="image_7.png" /></figure>

**FIG 2.** Manhattan plots from the EWASs performed in 3 European birth cohorts of childhood allergic disease (discovery). A total of 439,306 CpG sites were tested for association. The red dotted horizontal line represents the Bonferroni-corrected threshold (P < 1.14 × 10⁻⁷) of genome-wide significance. All 21 replicated CpG sites are marked as green circles and annotated with CpG sites name. A, Results for the EWAS analysis in children aged 4 years (n = 636) from the 3 European cohorts Barn/Children, Allergy, Milieu, Stockholm, Epidemiology (BAMSE), Infancia y Medio Ambiente (INMA), and PIAMA. B, Results for the EWAS meta-analysis in children aged 8 years (n = 821) from the BAMSE and PIAMA cohorts.

(Table III and see Fig E7 in the Online Repository at www.jacionline.org). In a comparison of case patients with patients with asthma only, rhinitis only, or eczema only while not taking specific IgE into account, none of the 21 CpG sites were differentially methylated (ie, disease specific) in relation

to any of these 3 individual diseases (see Table E9 in the Online Repository at www.jacionline.org).

Methylation of the 21 allergy-associated CpG sites in 298 cord blood DNA samples at birth was not associated with allergy development during early childhood (see Table E10 in the Online
<table><caption>TABLE II. Description of 21 unique replicated allergic disease-related CpG sites across childhood</caption><thead><tr><th>CpG sites</th><th>Age group</th><th>Chr</th><th>bp Position*</th><th>Gene name†</th><th>Discovery coef‡</th><th>Discovery P value§</th><th>Houseman-corrected P value||</th><th>Eosinophil-corrected P value¶</th><th>Replication Coef#</th><th>Replication P value**</th><th>Meta-analysis Coef††</th><th>Meta-analysis P value‡‡</th></tr></thead><tbody><tr><td>cg11699125</td><td>4 y</td><td>1</td><td>6341327</td><td>GPR153, ACOT7</td><td>-0.0190</td><td>3.58 × 10<sup>-7</sup></td><td>1.02 × 10<sup>-5</sup></td><td>1.66 × 10<sup>-4</sup></td><td>-0.0306</td><td>2.87 × 10<sup>-14</sup></td><td>-0.0271</td><td>5.84 × 10<sup>-19</sup></td></tr><tr><td>cg15344640</td><td></td><td>5</td><td>176774729</td><td>MXD3, LMAN2</td><td>-0.0100</td><td>2.97 × 10<sup>-8</sup></td><td>9.46 × 10<sup>-7</sup></td><td>1.12 × 10<sup>-5</sup></td><td>-0.0104</td><td>1.62 × 10<sup>-7</sup></td><td>-0.0100</td><td>2.53 × 10<sup>-14</sup></td></tr><tr><td>cg23642826</td><td>8 y</td><td>1</td><td>6645463</td><td>ZBTB48, KLHL21</td><td>-0.0178</td><td>7.77 × 10<sup>-8</sup></td><td>7.87 × 10<sup>-5</sup></td><td>1.71 × 10<sup>-2</sup></td><td>-0.0127</td><td>2.88 × 10<sup>-8</sup></td><td>-0.0140</td><td>2.60 × 10<sup>-14</sup></td></tr><tr><td>cg21932513</td><td></td><td>1</td><td>17751974</td><td>RCC2, PADI4</td><td>-0.0161</td><td>1.79 × 10<sup>-8</sup></td><td>2.74 × 10<sup>-5</sup></td><td>2.81 × 10<sup>-3</sup></td><td>-0.0140</td><td>3.31 × 10<sup>-7</sup></td><td>-0.0150</td><td>5.34 × 10<sup>-14</sup></td></tr><tr><td>cg11725101</td><td></td><td>1</td><td>148739457</td><td>NBPF16</td><td>-0.0125</td><td>3.77 × 10<sup>-8</sup></td><td>9.03 × 10<sup>-7</sup></td><td>1.50 × 10<sup>-3</sup></td><td>-0.0077</td><td>5.22 × 10<sup>-4</sup></td><td>-0.0100</td><td>3.58 × 10<sup>-10</sup></td></tr><tr><td>cg06528816</td><td></td><td>2</td><td>47242277</td><td>TTC7A, CALM2</td><td>-0.0209</td><td>4.61 × 10<sup>-9</sup></td><td>1.81 × 10<sup>-6</sup></td><td>3.50 × 10<sup>-4</sup></td><td>-0.0169</td><td>1.57 × 10<sup>-10</sup></td><td>-0.0183</td><td>8.47 × 10<sup>-18</sup></td></tr><tr><td>cg05736642</td><td></td><td>4</td><td>3123132</td><td>RGS12, HTT</td><td>-0.0128</td><td>9.90 × 10<sup>-8</sup></td><td>4.67 × 10<sup>-6</sup></td><td>2.46 × 10<sup>-4</sup></td><td>-0.0129</td><td>2.90 × 10<sup>-6</sup></td><td>-0.0124</td><td>1.37 × 10<sup>-12</sup></td></tr><tr><td>cg16673806</td><td></td><td>5</td><td>137771872</td><td>REEP2</td><td>-0.0160</td><td>3.76 × 10<sup>-8</sup></td><td>4.94 × 10<sup>-6</sup></td><td>1.51 × 10<sup>-3</sup></td><td>-0.0098</td><td>6.56 × 10<sup>-5</sup></td><td>-0.0116</td><td>5.74 × 10<sup>-11</sup></td></tr><tr><td>cg08969102</td><td></td><td>5</td><td>133563532</td><td>PPP2CA</td><td>-0.0168</td><td>5.73 × 10<sup>-8</sup></td><td>1.09 × 10<sup>-5</sup></td><td>1.25 × 10<sup>-3</sup></td><td>-0.0103</td><td>3.74 × 10<sup>-5</sup></td><td>-0.0129</td><td>3.81 × 10<sup>-11</sup></td></tr><tr><td>cg12077460</td><td></td><td>8</td><td>8702053</td><td>ERI1, CLDN23</td><td>-0.0156</td><td>2.27 × 10<sup>-8</sup></td><td>1.03 × 10<sup>-6</sup></td><td>6.39 × 10<sup>-5</sup></td><td>-0.0144</td><td>2.98 × 10<sup>-6</sup></td><td>-0.0150</td><td>3.73 × 10<sup>-13</sup></td></tr><tr><td>cg13576859</td><td></td><td>9</td><td>97403129</td><td>FBP1</td><td>-0.0196</td><td>2.88 × 10<sup>-8</sup></td><td>5.63 × 10<sup>-7</sup></td><td>1.64 × 10<sup>-4</sup></td><td>-0.0128</td><td>1.05 × 10<sup>-7</sup></td><td>-0.0147</td><td>4.91 × 10<sup>-14</sup></td></tr><tr><td>cg13458609</td><td></td><td>9</td><td>130608923</td><td>ENG, FPGS</td><td>-0.0188</td><td>6.84 × 10<sup>-8</sup></td><td>1.52 × 10<sup>-6</sup></td><td>8.92 × 10<sup>-4</sup></td><td>-0.0164</td><td>1.53 × 10<sup>-8</sup></td><td>-0.0174</td><td>7.08 × 10<sup>-15</sup></td></tr><tr><td>cg06597413</td><td></td><td>11</td><td>69251883</td><td>CCND1, TPCN2</td><td>-0.0172</td><td>1.33 × 10<sup>-9</sup></td><td>3.91 × 10<sup>-6</sup></td><td>3.98 × 10<sup>-4</sup></td><td>-0.0123</td><td>2.25 × 10<sup>-7</sup></td><td>-0.0137</td><td>4.20 × 10<sup>-15</sup></td></tr><tr><td>cg21498475</td><td></td><td>12</td><td>113737469</td><td>SLC24A6, TPCN1</td><td>-0.0155</td><td>5.64 × 10<sup>-9</sup></td><td>2.20 × 10<sup>-6</sup></td><td>1.69 × 10<sup>-3</sup></td><td>-0.0121</td><td>2.20 × 10<sup>-9</sup></td><td>-0.0134</td><td>1.78 × 10<sup>-16</sup></td></tr><tr><td>cg13645296</td><td></td><td>15</td><td>64275810</td><td>HERC1, DAPK2</td><td>-0.0208</td><td>8.06 × 10<sup>-8</sup></td><td>1.41 × 10<sup>-7</sup></td><td>4.61 × 10<sup>-5</sup></td><td>-0.0220</td><td>3.17 × 10<sup>-11</sup></td><td>-0.0215</td><td>1.70 × 10<sup>-17</sup></td></tr><tr><td>cg26235490</td><td></td><td>17</td><td>1047567</td><td>ABR, TIMM22</td><td>-0.0132</td><td>4.64 × 10<sup>-9</sup></td><td>9.61 × 10<sup>-7</sup></td><td>2.20 × 10<sup>-3</sup></td><td>-0.0153</td><td>1.92 × 10<sup>-10</sup></td><td>-0.0142</td><td>1.07 × 10<sup>-17</sup></td></tr><tr><td>cg01330991</td><td></td><td>17</td><td>7648108</td><td>KDM6B, DNAH2</td><td>-0.0166</td><td>1.29 × 10<sup>-9</sup></td><td>1.58 × 10<sup>-6</sup></td><td>4.23 × 10<sup>-4</sup></td><td>-0.0098</td><td>9.32 × 10<sup>-6</sup></td><td>-0.0122</td><td>2.42 × 10<sup>-13</sup></td></tr><tr><td>cg09981841</td><td></td><td>17</td><td>19177387</td><td>EPN2, B9D1</td><td>-0.0171</td><td>5.21 × 10<sup>-8</sup></td><td>1.89 × 10<sup>-4</sup></td><td>2.50 × 10<sup>-2</sup></td><td>-0.0090</td><td>4.25 × 10<sup>-4</sup></td><td>-0.0122</td><td>4.63 × 10<sup>-10</sup></td></tr><tr><td>cg00170714</td><td></td><td>17</td><td>40724562</td><td>PSMC3IP, MLX</td><td>-0.0147</td><td>7.87 × 10<sup>-9</sup></td><td>1.23 × 10<sup>-5</sup></td><td>1.57 × 10<sup>-3</sup></td><td>-0.0113</td><td>6.92 × 10<sup>-7</sup></td><td>-0.0129</td><td>2.13 × 10<sup>-14</sup></td></tr><tr><td>cg06483820</td><td></td><td>17</td><td>55167149</td><td>MSI2, AKAP1</td><td>-0.0159</td><td>8.27 × 10<sup>-10</sup></td><td>7.96 × 10<sup>-7</sup></td><td>4.21 × 10<sup>-4</sup></td><td>-0.0140</td><td>1.41 × 10<sup>-12</sup></td><td>-0.0146</td><td>9.84 × 10<sup>-21</sup></td></tr><tr><td>cg22503106</td><td></td><td>17</td><td>81040906</td><td>METRNL</td><td>-0.0198</td><td>3.95 × 10<sup>-8</sup></td><td>3.07 × 10<sup>-6</sup></td><td>3.32 × 10<sup>-3</sup></td><td>-0.0143</td><td>2.28 × 10<sup>-5</sup></td><td>-0.0174</td><td>5.68 × 10<sup>-12</sup></td></tr></tbody></table>

Chr, Chromosome; Coef, coefficient.

*Base pair position according to Genome Build 37.

†The CpG sites were annotated by the Genomic Regions of Annotations Tool (GREAT), version 3.0.0 (available at http://bejerano.stanford.edu/great/).

‡Regression coefficient from the discovery study.

§P value from discovery study.

||P value from the discovery study after correction for estimated cell counts with the default Houseman setting (T cells [CD8T], T cells [CD4T], NK cells, B cells, monocytes, and granulocytes.

¶P value from the discovery study after correction for estimated cell counts (T cells [CD8T], T cells [CD4T], NK cells, B cells, monocytes, eosinophils, and neutrophils).

#Regression coefficient from replication study.

**P value from meta-analysis of replication study.

††Regression coefficient from meta-analysis of discovery and replication.

‡‡P value from meta-analysis of discovery and replication.

Repository at www.jacionline.org), whereas 10 of 21 tested CpG sites were associated with allergic disease with nominal significance (P < .05) in nasal respiratory epithelial cells of 16-year-old children of the PIAMA cohort, with matching direction of effect (see Table E11 in the Online Repository at www.jacionline.org).

In the Saguenay–Lac-Saint-Jean cohort, we found all 21 CpG sites to be significantly associated with asthma within eosinophils: on average, participants with asthma had 19% lower DNA methylation of these 21 CpG sites than did participants

without asthma. (see Table E12 in the Online Repository at www.jacionline.org).

Functional analyses using Roadmap epigenomics data showed that 17 of 21 allergy-associated CpG sites were significantly enriched for enhancer markers in the whole blood Roadmap and Encode data (see Tables E13 and E14 in the Online Repository at www.jacionline.org).

We next investigated whether DNA methylation of the 21 allergy-associated CpG sites is driven by allergy-associated genetic variants. Looking up methylation quantitative trait
<table><caption>**TABLE III.** Independent meta-analysis of the association of DNA methylation at 21 replicated CpG sites with allergic disease defined on the basis of symptoms without consideration for IgE levels in 8 replication cohorts</caption><thead><tr><th>CpG site</th><th>Gene name*</th><th>Meta-analysis coefficient</th><th>Meta-analysis P value</th><th>Direction</th></tr></thead><tbody><tr><td>cg11699125</td><td>GPR153, ACOT7</td><td>-0.0189</td><td>1.78E-09</td><td>—+—+—</td></tr><tr><td>cg15344640</td><td>MXD3, LMAN2</td><td>-0.0064</td><td>2.95E-04</td><td>—+—+—+—</td></tr><tr><td>cg23642826</td><td>ZBTB48, KLHL21</td><td>-0.0079</td><td>8.06E-07</td><td>—+—</td></tr><tr><td>cg21932513</td><td>RCC2, PADI4</td><td>-0.0093</td><td>8.26E-07</td><td>—+—+—+—</td></tr><tr><td>cg11725101</td><td>NBPF16</td><td>-0.0074</td><td>5.28E-05</td><td>—?+—+—+—</td></tr><tr><td>cg06528816</td><td>TTC7A, CALM2</td><td>-0.0111</td><td>3.51E-08</td><td>—+—?—</td></tr><tr><td>cg05736642</td><td>RGS12, HTT</td><td>-0.0069</td><td>4.73E-05</td><td>—+—</td></tr><tr><td>cg16673806</td><td>REEP2</td><td>-0.0064</td><td>3.43E-05</td><td>—+—+—</td></tr><tr><td>cg08969102</td><td>PPP2CA</td><td>-0.0089</td><td>2.73E-06</td><td>—?+—</td></tr><tr><td>cg12077460</td><td>ERI1, CLDN23</td><td>-0.0117</td><td>1.90E-06</td><td>—+—+—</td></tr><tr><td>cg13576859</td><td>FBP1</td><td>-0.0083</td><td>1.88E-08</td><td>—+—+—</td></tr><tr><td>cg13458609</td><td>ENG, FPGS</td><td>-0.0122</td><td>5.63E-08</td><td>—+—?+—</td></tr><tr><td>cg06597413</td><td>CCND1, TPCN2</td><td>-0.0084</td><td>1.71E-09</td><td>—+—+—</td></tr><tr><td>cg21498475</td><td>SLC24A6, TPCN1</td><td>-0.0088</td><td>1.48E-07</td><td>—+—?+—</td></tr><tr><td>cg13645296</td><td>HERC1, DAPK2</td><td>-0.0172</td><td>2.78E-12</td><td>—?—</td></tr><tr><td>cg26235490</td><td>ABR, TIMM22</td><td>-0.0097</td><td>3.17E-09</td><td>—+—+—</td></tr><tr><td>cg01330991</td><td>KDM6B, DNAH2</td><td>-0.008</td><td>3.28E-08</td><td>—+—+—</td></tr><tr><td>cg09981841</td><td>EPN2, B9D1</td><td>-0.0075</td><td>7.01E-05</td><td>—+—+—</td></tr><tr><td>cg00170714</td><td>PSMC3IP, MLX</td><td>-0.007</td><td>1.74E-04</td><td>—?+—+—</td></tr><tr><td>cg06483820</td><td>MSI2, AKAP1</td><td>-0.0086</td><td>1.01E-09</td><td>—+—</td></tr><tr><td>cg22503106</td><td>METRNL</td><td>-0.0108</td><td>8.34E-07</td><td>—+—+—</td></tr></tbody></table>

Coefficient is the regression coefficient from the meta-analysis. P value is the P value from meta-analysis of the replication cohorts only, without consideration for the discovery population. For each cohort participating in the analysis, the symbol + indicates a positive direction of effect, whereas the symbol – indicates a negative direction of effect and the symbol ? indicates missing information for that CpG site in a given cohort. The cohort order is as follows: Born in Bradford (BIB), Rhea, INMA (Gipuzkoa), EDEN, INMA (València), PIAMA (age 8 years), Robbic (Rome), Robbic (Bologna), Environment and Childhood Asthma Study in Oslo (ECA), INMA (Menorca), PIAMA (age 16 years), and Karelia.

loci from the BIOS QTL browser (https://genenetwork.nl/biosqtlbrowsel/), we found 1 of 21 CpG sites annotated with tetratricopeptide repeat domain 7A (TTC7A) and calmodulin 2 (CALM2) (ie, cg06528816) to be significantly associated *in trans* with the asthma-associated polymorphism rs2381416 in the IL33 gene (false discovery rate P value = .03) (see Table E15 in the Online Repository at www.jacionline.org).³² Interestingly, rs2381416-A has been associated with higher methylation and lower eosinophil levels and higher neutrophil percentage levels (see Tables E15 and E16 in the Online Repository at www.jacionline.org).³³ Expression quantitative trait methylation (eQTM) of the 21 CpG sites with gene expression *in cis* in 2353 adults identified 15 CpG sites to be associated with 38 blood gene transcripts (see Table E17 in the Online Repository at www.jacionline.org). All CpG sites that showed significant *trans*-eQTM with whole blood gene expression are shown in Table E18 (in the Online Repository at www.jacionline.org). In the *trans*-eQTM analysis, we identified 4 gene expression patterns in whole blood by hierarchic clustering (see Fig E8 in the Online Repository at www.jacionline.org), with clusters 1 and 3 showing distinct patterns. In cluster 1, CpG methylation was correlated with gene expression of C-C chemokine receptor type 7 (CCR7), charged multivesicular body protein 7 (CHMP7), and lymphoid enhancer binding factor 1 (LEF1). In cluster 3, CpG methylation was correlated with expression of the genes sialic acid binding Ig like lectin 8 (SIGLEC8), oligodendrocyte transcription factor 2 (OLIG2), adenosine A3 receptor (ADORA3), and IL-5 receptor subunit alpha (IL5RA), all of which are genes related to blood eosinophils. An RNA sequencing data set containing data on 89 individuals with 75 measured immune cell (sub)populations²⁵ from the 500 Functional Genomics

Project showed clustered RNA-transcripts associated with allergy CpG sites to be strongly associated with effector and memory CD8 and natural killer (NK) cells and naive CD8⁺ and CD4⁺ cells (see Fig E9 in the Online Repository at www.jacionline.org).

## DISCUSSION

This large consortium-based meta-analysis identified 21 CpG sites in whole blood to be associated with childhood allergic disease. Consistently lower methylation levels at 2 CpG sites were observed in children with allergy at the age of 4 years and 19 CpG sites in children with allergy at the age of 8 years, all of which were replicated in independent cohorts up to adolescence. These CpG sites were associated not only with allergy defined by asthma, rhinitis, or eczema in combination with specific IgE but also when allergy was defined by disease symptoms only. We found no evidence for single disease-specific CpG methylation signatures, suggesting shared DNA methylation signatures of allergy in blood. DNA methylation at these 21 CpG sites in cord blood was not predictive of allergy during early childhood, indicating that postnatal changes in DNA methylation may play an important role in the development of allergy.

Five of 21 differentially methylated CpG sites represent novel findings in the context of EWAS on allergy. One of them is cg21932513, which is annotated to regulator of chromosome condensation 2 (RCC2) and peptidyl arginine deiminase 4 (PADI4). Being a well-established genetic risk factor for rheumatoid arthritis,³⁴ PADI4 has recently been implicated in acute allergic reactions to peanut.³⁵ Other novel findings include cg11725101, mapping to neuroblastoma breakpoint family member 16 (NBPF16); cg16673806 - receptor accessory protein

<footnote>*The CpG sites were annotated by using the Genomic Regions of Annotations Tool, version 3.0.0 (available at http://bejerano.stanford.edu/great/).</footnote>
2 (REEP2); cg26235490 - ABR activator of RhoGEF and GTPase (ABR) and translocase of inner mitochondrial membrane 22 (TIMM22), as well as cg01330991 - lysine demethylase 6B (KDM6B) and dynein axonemal heavy chain 2 (DNAH2). These genes have not been previously implicated in allergic disease.

Some of the differentially methylated CpG sites found in this study were previously reported. We identified 2 overlapping CpG sites, namely, cg15344640 (MXD3, LMAN2) and cg06483820 (MSI2, AKAP1), which were found in our previous MeDALL EWAS on asthma,¹⁸ as well as 6 overlapping CpG sites (cg11699125, cg21498475, cg00170714, cg13576859, cg08969102, and cg13458609) in the Pregnancy and Childhood Epigenetics consortium study on asthma.⁸ Further, 2 of 21 CpG sites were previously reported in relation to total or specific IgE levels, namely, cg11699125 (belonging to G protein-coupled receptor 153 [GPR153]) and acyl-CoA thioesterase 7 (ACOT7), was found in the Project Viva birth cohort in the United States,³⁶ as well as in 2 studies of Hispanic children.¹¹ The CpG sites cg11699125 (GPR153, ACOT7) and cg12077460, mapping to exoribonuclease 1 (ERI1), and claudin 23 (CLDN23), were previously reported in the Isle of Wight cohort.¹⁶ Taken together, these 9 CpG sites represent replicated DNA methylation markers of allergic disease across multiple populations.

Our top significant CpG, cg06483820, mapped to AKAP1 and MSI2. A-kinase anchoring proteins have been identified in T cells; they contribute to the maintenance of T-cell homeostasis.³⁷ The second most significant finding was cg11699125 in ACOT7, which is known to play a role in inflammation responses through the production of arachidonic acid and to be involved in increased prostaglandin production.³⁸ ACOT7 is particularly interesting because differential methylation in ACOT7 was previously identified in an EWAS of blood in relation to both total and allergen-specific IgE level¹³,³⁹ and asthma,⁸,⁴⁰,⁴¹ as well as in an EWAS of nasal epithelium to asthma.⁴² In this study, we also observed differential methylation of cg11699125 in nasal respiratory epithelial cells associated with allergy. Thus, ACOT7 methylation may be related to asthma and IgE sensitization in both blood and epithelial cells, and it may provide a cross-tissue allergy-associated methylation site. In fact, we observed replication of 10 of the 21 CpG sites in respiratory nasal epithelial cells that further support our findings in whole blood. This suggests that many allergy-associated DNA methylation markers may be replicable across different tissues. To further investigate this possibility, we did a lookup of published nasal methylation sites that were significantly associated with allergic asthma⁴³ or IgE sensitization¹⁵ in our whole blood DNA methylation data on children at ages 4 and 8 years; we found many CpG sites to be significantly associated in blood (see Tables E19 and E20 in the Online Repository at www.jacionline.org).

A recent large GWAS on allergic disease defined by having either asthma, rhinitis, or eczema identified 136 single-nucleotide polymorphisms (SNPs) as being significantly associated with allergic disease,² with case patient-only analyses strongly suggesting that 130 of these 136 SNPs are associated with multimorbidity rather than with single disease phenotypes. Our epigenetic study is the first to confirm this finding for DNA methylation in blood: all 21 CpG sites were similarly associated with either allergic disease, and no disease specificity could be shown. This could be due to shared epigenetic signatures of IgE sensitization in blood cells, as disease specificity may be more

visible in the end organ. We acknowledge that a limitation of this analysis is the lack of data on IgE sensitization, so we suggest that further studies comparing epigenetic patterns in lung, nose, and skin in combination with IgE sensitization are needed to address this important question.

Integration of genetic and DNA methylation data revealed 2 genes that were implicated by both genetic and epigenetic studies. First, LMAN2 encodes a type I transmembrane lectin that shuttles between the endoplasmic reticulum, the Golgi apparatus, and the plasma membrane. This gene has previously been reported in an allergy GWAS² and an EWAS of childhood asthma.⁸ Thus, both genetic and epigenetic markers in LMAN2 are associated with allergy, which prompted us to investigate whether allergy-associated SNPs could be related to our top CpG sites. However, no significant association between SNPs and CpG sites in LMAN2 was found, suggesting that genetic and epigenetic factors may independently relate to or cointeract in allergy. In contrast, we did identify a strong association between the allergy-associated SNP rs2381416 in IL33 at chromosome 9 and CpG methylation in cg06528816 at chromosome 2. The latter finding may be driven by a direct effect of rs238141 on cg06528816 methylation in this gene or by an indirect effect of this SNP regulating blood eosinophils, which is then reflected by the eosinophil-associated CpG site cg06528816.

Correlation of our 21 CpG sites with genome-wide gene expression revealed clusters of associated genes. One cluster included genes such as CCR7, which plays a role in allergic airway inflammation,⁴⁴ and TCF7, which is involved in the pathogenesis of lung diseases.⁴⁵ Another cluster was inversely associated with cg11699125 and contained genes such as IDO1 (which was implicated earlier in the development of immune responses⁴⁶), HRASLS5, SPNS3, CCL23, ASB2, OLIG2, and SEMA7A (which is known to be correlated with blood eosinophil counts), CEBPE, (which is involved in activation of granulocyte production),⁴⁷ and PTGDR2, which is linked to asthma.⁴⁸

Through clustering of the 21 allergy-associated CpG sites with immune cell-specific gene expression signatures, we were also able to annotate the allergy-associated CpG sites to activated immune cell subsets. We observed 1 cluster consisting of genes related to eosinophil function, such as SIGLEC8, OLIG2, ADORA3, and IL5RA. The direction of effect suggests that the lower DNA methylation in allergy that was found in this study is related to a higher eosinophil level. The second cluster is in line with previous findings from the MeDALL EWAS asthma study that whole blood DNA from children with allergic diseases carries CpG methylation markers associated with lower activity of naive T cells and higher activity of effector and memory CD8 T-cells and NK cells.¹⁸ This allergy-associated shift in cell state might be due to past exposure, such as childhood infections or microbial stimulation. Thus, we interpret the DNA methylation signatures as markers of activated cell subsets in peripheral blood, reflecting current or past cell activation or suppression events in allergy development.

Our study has some strengths and limitations. This is the largest DNA methylation study in childhood allergy to use independent laboratory methods and cohorts for replication. The study uses detailed definition of allergy phenotype, as well as availability of samples from patients at multiple ages and with multiple nationalities. We further replicated our findings in 5 cohorts that defined allergy by symptoms and IgE sensitization, but we also found that all 21 sites were replicated in 8 cohorts in which allergy
was defined by symptoms only. This suggests that our allergy-associated CpG sites represent robust findings in the context of childhood allergy from the age of 4 years onward.

Previous studies have shown that differences in methylation patterns can be attributed to variability in cell type composition when whole blood is used in DNA methylation studies.²⁶ Thus, DNA methylation may reflect allergy-associated changes in cell type composition in whole blood, cell-specific changes within the DNA methylome, or a combination of thereof, as was shown for asthma in the MeDALL study.¹⁸ Because no blood cell-specific DNA methylation data in allergic disease are available, we could replicate our findings only in purified eosinophils for asthma. Here, we found that all CpG sites were significantly associated with asthma, indicating that our results are at least partly driven by DNA methylation changes within eosinophils. We also replicated 10 of the 21 CpG sites in nasal epithelial brush cells, further underlining the robustness of our findings. Another limitation is that the Illumina Infinium HumanMethylation450 BeadChip platform covered only about 1.6% of all methylation sites of the genome. One would expect to find more allergy-associated CpG sites by using whole methylome sequencing in the future. Because of the small numbers of case patients with single diseases in the case patient-only analysis, we had limited power to detect unique signatures of single diseases. In our analysis of allergy prediction at birth, we investigated cord blood samples and not peripheral blood, as was done in subjects later in life. Recent analyses showed that 70% of DNA methylation sites are in good agreement between cord and peripheral blood,⁴⁹ which suggests that analyzing cord blood may have introduced an additional source of variation into our analysis.

Our analyses were based on white populations, and whether the findings can be extrapolated to other ethnic groups remains to be investigated.

In conclusion, our study identified consistently lower DNA methylation levels in 21 CpG sites to be associated with allergy in childhood from ages 4 to 16 years, showing that these methylation sites are shared between asthma, rhinitis, and eczema and are implicated eosinophils. Our allergy-associated DNA methylation profiles are indicative of lower presence or activity of naive T cells and higher activity or presence of eosinophils and effector and memory CD8 T cells and NK cells in childhood allergy.

We are grateful to all children and families who participated in this study. We especially thank Professor Dirkje Postma for helpful comments and support during the course of this study. Catherine Laprise is part of the Quebec Respiratory Health Network (https://rsr-qc.ca/en/), the investigator of CHILD Study, the director of the Centre intersectoriel en santé durable de l'UQAC, and holder of the Canada Research Chair in the Environment and Genetics of Respiratory Disorders and Allergy (http://www.chairs.gc.ca).

## Key messages

* A consistently lower level of DNA methylation in whole blood DNA of 21 CpG sites was significantly associated with childhood allergy.

* The allergy-associated DNA methylation profiles are shared between asthma, rhinitis, and eczema and implicate the presence of and changes in DNA methylation within eosinophils.

## REFERENCES

1. Asher MI, Montefort S, Björkstén B, Lai CK, Strachan DP, Weiland SK, et al. Worldwide time trends in the prevalence of symptoms of asthma, allergic rhino-conjunctivitis, and eczema in childhood: ISAAC phases one and three repeat multi-country cross-sectional surveys. Lancet 2006;368:733-43.

2. Ferreira MA, Vonk JM, Baurecht H, Marenholz I, Tian C, Hoffman JD, et al. Shared genetic origin of asthma, hay fever and eczema elucidates allergic disease biology. Nat Genet 2017;49:1752-7.

3. Demenais F, Margaritte-Jeannin P, Barnes KC, Cookson WOC, Altmüller J, Ang W, et al. Multiancestry association study identifies new asthma risk loci that colocalize with immune-cell enhancer marks. Nat Genet 2018;50:42-53.

4. Paternoster L, Standl M, Waage J, Baurecht H, Hotze M, Strachan DP, et al. Multiancestry genome-wide association study of 21,000 cases and 95,000 controls identifies new risk loci for atopic dermatitis. Nat Genet 2015;47:1449-56.

5. Linneberg A. The increase in allergy and extended challenges. Allergy 2011;66: 1-3.

6. Tost J. A translational perspective on epigenetics in allergic diseases. J Allergy Clin Immunol 2018;142:715-26.

7. Qi C, Xu C-J, Koppelman GH. The role of epigenetics in the development of childhood asthma. Expert Rev Clin Immunol 2019;15:1287-302.

8. Xu C-J, Söderhäll C, Bustamante M, Baïz N, Gruzieva O, Gehring U, et al. DNA methylation in childhood asthma: an epigenome-wide meta-analysis. Lancet Respir Med 2018;6:379-88.

9. Reese SE, Xu C-J, den Dekker HT, Lee MK, Sikdar S, Ruiz-Arenas C, et al. Epigenome-wide meta-analysis of DNA methylation and childhood asthma. J Allergy Clin Immunol 2019;143:2062-74.

10. Qi C, Jiang Y, Yang IV, Forno E, Wang T, Vonk JM, et al. Nasal DNA methylation profiling of asthma and rhinitis. J Allergy Clin Immunol 2020;145: 1655-63.

11. Quraishi BM, Zhang H, Everson TM, Ray M, Lockett GA, Holloway JW, et al. Identifying CpG sites associated with eczema via random forest screening of epigenome-scale DNA methylation. Clin Epigenetics 2015;7:68.

12. Liang L, Willis-Owen SAG, Laprise C, Wong KCC, Davies GA, Hudson TJ, et al. An epigenome-wide association study of total serum immunoglobulin E concentration. Nature 2015;520:670-4.

13. Chen W, Wang T, Pino-Yanes M, Forno E, Liang L, Yan Q, et al. An epigenome-wide association study of total serum IgE in Hispanic children. J Allergy Clin Immunol 2017;140:571-7.

14. Peng C, Van Meel ER, Cardenas A, Rifas-Shiman SL, Sonawane AR, Glass KR, et al. Epigenome-wide association study reveals methylation pathways associated with childhood allergic sensitization. Epigenetics 2019;1-22.

15. Forno E, Wang T, Qi C, Yan Q, Xu C-J, Boutaoui N, et al. DNA methylation in nasal epithelium, atopy, and atopic asthma in children: a genome-wide study. Lancet Respir Med 2019;7:336-46.

16. Zhang H, Kaushal A, Merid SK, Melén E, Pershagen G, Rezwan FI, et al. DNA methylation and allergic sensitizations: a genome-scale longitudinal study during adolescence. Allergy 2019;74:1166-75.

17. Paparo L, Nocerino R, Bruno C, Di Scala C, Cosenza L, Bedogni G, et al. Randomized controlled trial on the influence of dietary intervention on epigenetic mechanisms in children with cow's milk allergy: the EPICMA study. Sci Rep 2019;9: 2828.

18. Pinart M, Benet M, Annesi-Maesano I, Berg A von, Berdel D, Carlsen KCL, et al. Comorbidity of eczema, rhinitis, and asthma in IgE-sensitised and non-IgE-sensitised children in MeDALL: a population-based cohort study. Lancet Respir Med 2014;2:131-40.

19. Lemonnier N, Melén E, Jiang Y, Joly S, Ménard C, Aguilar D, et al. A novel whole blood gene expression signature for asthma, dermatitis and rhinitis multimorbidity in children and adolescents. Allergy 2020;75:3248.

20. Xu C-J, Bonder MJ, Söderhäll C, Bustamante M, Baïz N, Gehring U, et al. The emerging landscape of dynamic DNA methylation in early childhood. BMC Genomics 2017;18:25.

21. Laprise C. The Saguenay-Lac-Saint-Jean asthma familial collection: the genetics of asthma in a young founder population. Genes Immun 2014;15: 247-55.

22. Bonder MJ, Luijk R, Zhernakova DV, Moed M, Deelen P, Vermaat M, et al. Disease variants alter transcription factor levels and methylation of their binding sites. Nat Genet 2017;49:131-8.

23. McLean CY, Bristor D, Hiller M, Clarke SL, Schaar BT, Lowe CB. GREAT improves functional interpretation of cis-regulatory regions. Nat Biotechnol 2010; 28:495-501.

24. Kundaje A, Meuleman W, Ernst J, Bilenky M, Yen A. Integrative analysis of 111 reference human epigenomes. Nature 2015;518:317-30.
25. Aguirre-Gamboa R, Joosten I, Urbano PCM, van der Molen RG, van Rijssen E, van Cranenbroek B, et al. Differential effects of environmental and genetic factors on T and B cell immune traits. Cell Rep 2016;17:2474-87.

26. Li Y, Oosting M, Smeekens SP, Jaeger M, Aguirre-Gamboa R, Le KTT, et al. A functional genomics approach to understand variation in cytokine production in humans. Cell 2016;167:1099-110.e14.

27. Fox J, Weisberg S. An R companion to applied regression. Thousand Oaks, CA: SAGE; 2011. 473 p.

28. Houseman EA, Accomando WP, Koestler DC, Christensen BC, Marsit CJ, Nelson HH. DNA methylation arrays as surrogate measures of cell mixture distribution. BMC Bioinformatics 2012;13:86.

29. Pedersen BS, Schwartz DA, Yang IV, Kechris KJ. Comb-p: software for combining, analyzing, grouping and correcting spatially correlated P-values. Bioinformatics 2012;28:2986-8.

30. Willer CJ, Li Y, Abecasis GR. METAL: fast and efficient meta-analysis of genome-wide association scans. Bioinformatics 2010;26:2190-1.

31. Viechtbauer W. Conducting Meta-Analyses in *R* with the metafor package. J Stat Softw 2010;36.

32. Grotenboer NS, Ketelaar ME, Koppelman GH, Nawijn MC. Decoding asthma: translating genetic variation in IL33 and IL1RL1 into disease pathophysiology. J Allergy Clin Immunol 2013;131:856-65.e9.

33. Astle WJ, Elding H, Jiang T, Allen D, Ruklisa D, Mann AL, et al. The allelic landscape of human blood cell trait variation and links to common complex disease. Cell 2016;167:1415-29.e19.

34. Suzuki A, Yamada R, Chang X, Tokuhiro S, Sawada T, Suzuki M, et al. Functional haplotypes of PADI4, encoding citrullinating enzyme peptidylarginine deiminase 4, are associated with rheumatoid arthritis. Nat Genet 2003;34:395-402.

35. Watson CT, Cohain AT, Griffin RS, Chun Y, Grishin A, Hacyznska H, et al. Integrative transcriptomic analysis reveals key drivers of acute peanut allergic reactions. Nat Commun 2017;8:1943.

36. Peng C, Cardenas A, Rifas-Shiman SL, Hivert M-F, Gold DR, Platts-Mills TA, et al. Epigenome-wide association study of total serum immunoglobulin E in children: a life course approach. Clin Epigenetics 2018;10:55.

37. Webbi VL, Taskén K. Molecular Mechanisms for cAMP-mediated immunoregulation in T cells - role of anchored protein kinase A signaling units. Front Immunol 2016;7:222.

38. Sakuma S, Usa K, Fujimoto Y. The regulation of formation of prostaglandins and arachidonoyl-CoA from arachidonic acid in rabbit kidney medulla microsomes by linoleic acid hydroperoxide. Prostaglandins Other Lipid Mediat 2006;79:271-7.

39. Everson TM, Lyons G, Zhang H, Soto-Ramírez N, Lockett GA, Patil VK, et al. DNA methylation loci associated with atopy and high serum IgE: a genome-wide application of recursive random forest feature selection. Genome Med 2015;7:89.

40. Yang IV, Pedersen BS, Liu A, O'Connor GT, Teach SJ, Kattan M, et al. DNA methylation and childhood asthma in the inner city. J Allergy Clin Immunol 2015;136:69-80.

41. Arathimos R, Suderman M, Sharp GC, Burrows K, Granell R, Tilling K, et al. Epigenome-wide association study of asthma and wheeze in childhood and adolescence. Clin Epigenetics 2017;9:112.

42. Yang IV, Pedersen BS, Liu AH, O'Connor GT, Pillai D, Kattan M, et al. The nasal methylome and childhood atopic asthma. J Allergy Clin Immunol 2017;139:1478-88.

43. Cardenas A, Sordillo JE, Rifas-Shiman SL, Chung W, Liang L, Coull BA, et al. The nasal methylome as a biomarker of asthma and airway inflammation in children. Nat Commun 2019;10:3095.

44. Afshar R, Strassner JP, Seung E, Causton B, Cho JL, Harris RS, et al. Compartmentsalized chemokine-dependent regulatory T-cell inhibition of allergic pulmonary inflammation. J Allergy Clin Immunol 2013;131:1645-52.e4.

45. Zhu Y, Wang W, Wang X. Roles of transcriptional factor 7 in production of inflammatory factors for lung diseases. J Transl Med 2015;13:273.

46. Salazar F, Hall L, Negm OH, Awuah D, Tighe PJ, Shakib F, et al. The mannose receptor negatively modulates the Toll-like receptor 4-aryl hydrocarbon receptor-indoleamine 2,3-dioxygenase axis in dendritic cells affecting T helper cell polarization. J Allergy Clin Immunol 2016;137:1841-51.e2.

47. Bigler J, Boedigheimer M, Schofield JPR, Skipp PJ, Corfield J, Rowe A, et al. A severe asthma disease signature from gene expression profiling of peripheral blood from U-BIOPRED cohorts. Am J Respir Crit Care Med 2016;195:1311-20.

48. Huang T, Hazen M, Shang Y, Zhou M, Wu X, Yan D, et al. Depletion of major pathogenic cells in asthma by targeting CRTh2. JCI Insight 2016;1:386689.

49. Jiang Y, Wei J, Zhang H, Ewart S, Rezwan FI, Holloway JW, et al. Epigenome wide comparison of DNA methylation profile between paired umbilical cord blood and neonatal blood on Guthrie cards. Epigenetics 2020;15:454-61.