# Gene-Environment Interaction Affects Risk of Atopic Eczema: Population and In Vitro Studies

Marie Standl, Ashley Budu-Aggrey, Luke Johnston, Martina Elias, S Hasan Arshad, Peter Bager, Veronique Bataille, Helena Blakeway, Klaus Bønnelykke, Dorret Boomsma, et al.

► To cite this version:

Marie Standl, Ashley Budu-Aggrey, Luke Johnston, Martina Elias, S Hasan Arshad, et al. Gene-Environment Interaction Affects Risk of Atopic Eczema: Population and In Vitro Studies. Allergy, 2025, 10.1111/all.16605. hal-05107848

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Allergy

WILEY

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ORIGINAL ARTICLE

OPEN ACCESS

Atopic Dermatitis, Urticaria and Skin Disease

# Gene-Environment Interaction Affects Risk of Atopic Eczema: Population and In Vitro Studies

Marie Standl¹,² ID | Ashley Budu-Aggrey³ ID | Luke J. Johnston⁴ ID | Martina S. Elias⁴ ID | S. Hasan Arshad⁵,⁶,⁷ ID |

Peter Bager⁸ ID | Veronique Bataille⁹ ID | Helena Blakeway³ ID | Klaus Bønnelykke¹⁰ ID | Dorret Boomsma¹¹ ID |

Ben M. Brumpton¹² ID | Mariona Bustamante Pineda¹³,¹⁴,¹⁵ ID | Archie Campbell⁴ ID | John A. Curtin¹⁶ ID |

Anders Eliasen¹⁰ ID | João P. S. Fadista⁸ ID | Bjarke Feenstra⁸ ID | Trine Gerner¹⁷ ID | Carolina Medina-Gomez¹⁸ ID |

Sarah Grosche¹⁹ ID | Kristine B. Gutzkow²⁰ ID | Anne-Sofie Halling²¹ ID | Caroline Hayward⁴ ID | John Henderson³ ID |

Esther Herrera-Luis²² ID | John W. Holloway⁶,²³ ID | Joukejan Hottenga¹¹ ID | Jonathan O'B Hourihane²⁴,²⁵,²⁶ ID |

Chen Hu²⁷,²⁸ ID | Kristian Hveem¹²,²⁹ ID | Amaia Irizar¹⁵,³⁰,³¹ ID | Benedicte Jacquemi³² ID | Leon Jessen¹⁰ ID |

Sara Kress³³ ID | Ramesh J. Kurukulaaratchy⁵,⁶,⁷ ID | Susanne Lau³⁴ ID | Sabrina Llop¹⁵,³⁵ ID | Mari Løset¹²,³⁶ ID |

Ingo Marenholz¹⁹,³⁷ ID | Dan Mason³⁸ ID | Daniel L. McCartney⁴ ID | Mads Melbye³⁹,⁴⁰,⁴¹ ID | Erik Melén⁴² ID |

Camelia Minica¹¹ ID | Clare S. Murray¹⁶ ID | Tamar Nijsten²⁸ ID | Luba M. Pardo²⁸ ID | Suzanne Pasmans²⁸ ID |

Craig E. Pennell⁴³,⁴⁴ ID | Maria R. Rinnov¹⁷,⁴⁵ ID | Gillian Santorelli³⁸ ID | Tamara Schikowski³³ ID | Darina Sheehan²⁶,⁴⁶,⁴⁷ ID |

Angela Simpson¹⁶ ID | Cilla Söderhäll⁴⁸,⁴⁹ ID | Laurent F. Thomas¹²,⁵⁰,⁵¹ ID | Jacob P. Thyssen²¹ ID | Maties Torrent⁵² ID |

Toos van Beijsterveldt¹¹ ID | Alessia Visconti⁹,⁵³ ID | Judith M. Vonk⁵⁴,⁵⁵ ID | Carol A. Wang⁴³,⁴⁴ ID | Cheng-Jian Xu⁵⁶,⁵⁷ ID |

Ali H. Ziyab⁵⁸ ID | UK Translational Research Network in Dermatology | BIOMAP Consortium | Adnan Custovic⁵⁹ ID |

Paola Di Meglio⁶⁰ ID | Liesbeth Duijts⁶¹,⁶² ID | Carsten Flohr⁶³ ID | Alan D. Irvine⁶⁴ ID | Gerard H. Koppelman⁵⁵,⁶⁵ ID |

Young-Ae Lee¹⁹,³⁴,³⁷ ID | Nick J. Reynolds⁶⁶,⁶⁷ ID | Catherine Smith⁶⁰ ID | Sinéad M. Langan⁶⁸,⁶⁹ ID | Lavinia Paternoster³,⁷⁰ ID |

Sara J. Brown⁴,⁷¹ ID

**Correspondence:** Sara J. Brown (sara.brown@ed.ac.uk)

**Received:** 12 February 2025

**Revised:** 9 April 2025

**Accepted:** 11 May 2025

**Funding:** This project has received funding from the Innovative Medicines Initiative 2 Joint Undertaking (JU) under Grant agreement no. 821511 (BIOMAP). The JU receives support from the European Union's Horizon 2020 research and innovation programme and EFPIA. This publication/dissemination reflects only the author's view and the JU is not responsible for any use that may be made of the information it contains. M.S. has received funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (Grant agreement no. 949906). N.J.R.'s research/laboratory is funded in part by the Newcastle NIHR Biomedical Research Centre (BRC), the Newcastle NIHR Medtech and In vitro diagnostics co-operative, and the NIHR Newcastle Patient Safety Research Collaboration, and N.J.R. is a NIHR Senior Investigator. L.P. has received funding from a MRC Population Health Scientist Fellowship (MR/J012165/1) and receives support from the UK Medical Research Council Integrative Epidemiology Unit at the University of Bristol (MC_UU_00011/1, MC_UU_00032/1). S.J.B. holds a Wellcome Trust Senior Research Fellowship (220875/Z/20/Z). The MAS study up to adolescence was funded by several grants from the German Federal Ministry of Education and Research (07015633, 07 ALE 27, 01EE9405/5 and 01EE9406). E.H.-L. was supported by a fellowship awarded by MCIN/AEI/10.13039/501100011033 and by 'ESF Investing in your future' [PRE2018-083837]. MAAS was supported by the Asthma UK Grants no. 301 (1995-1998), no. 362 (1998-2001), no. 01/012 (2001-2004), No 04/014 (2004-2007), BMA James Trust (2005) and The JP Moulton Charitable Foundation (2004-current), The North west Lung Centre Charity (1997-current) and the Medical Research Council (MRC) G0601361 (2007-2012), MR/K002449/1 (2013-2014) and MR/L012693/1 (2014-2018) and MR/S025340/1 UNICORN (Unified Cohorts Research Network): Disaggregating asthma (2020-2024). This study was delivered through the National Institute for Health and Care Research (NIHR) Manchester Biomedical Research Centre (BRC) (NIHR203308). The views expressed are those of the author(s) and not necessarily those of the NIHR or the Department of Health and Social Care. The PIAMA study has been supported by project grants from the Netherlands Organisation for Health Research and Development; the Netherlands Organisation for Scientific Research; the Lung Foundation Netherlands (formerly Netherlands Asthma Fund); the Netherlands Ministry of Spatial Planning, Housing, and the Environment; and the Netherlands Ministry of Health, Welfare and Sport. CS is a NIHR Senior Investigator.

**Keywords:** atopic eczema | dog | environment | gene | interaction

Marie Standl, Ashley Budu-Aggrey, Sinéad M. Langan, Lavinia Paternoster and Sara J. Brown contributed equally.

For affiliations refer to page 10.

This is an open access article under the terms of the [Creative Commons Attribution License](https://creativecommons.org/licenses/by/4.0/), which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

© 2025 The Author(s). *Allergy* published by European Academy of Allergy and Clinical Immunology and John Wiley & Sons Ltd.
## ABSTRACT

**Background:** Multiple environmental and genetic factors play a role in the pathogenesis of atopic eczema (AE). We aimed to investigate gene–environment interactions (G×E) to improve understanding of the pathophysiology.

**Methods:** We analysed data from 16 European studies to test for interaction between the 24 most significant AE-associated loci identified from genome-wide association studies and 18 early-life environmental factors. We tested for replication using a further 10 studies and in vitro modeling to independently assess findings.

**Results:** The discovery analysis (including 25,339 individuals) showed suggestive evidence for interaction (p < 0.05) between seven environmental factors (antibiotic use, cat ownership, dog ownership, breastfeeding, elder sibling, smoking and washing practices) and at least one established variant for AE, 14 interactions in total. In the replication analysis (254,532 individuals) dog exposure × rs10214237 (on chromosome 5p13.2 near IL7R) was nominally significant (OR<sub>interaction</sub> = 0.91 [0.83–0.99] p = 0.025), with a risk effect of the T allele observed only in those not exposed to dogs. A similar interaction with rs10214237 was observed for siblings in the discovery analysis (OR<sub>interaction</sub> = 0.84 [0.75–0.94] p = 0.003), but replication analysis was under-powered (OR<sub>interaction</sub> = 1.09 [0.82–1.46]). rs10214237 homozygous risk genotype is associated with lower IL-7R expression in human keratinocytes, and dog exposure modelled in vitro showed a differential response according to rs10214237 genotype.

**Conclusion:** Interaction analysis and functional assessment provide preliminary evidence that early-life dog exposure may modify the genetic effect of rs10214237 on AE via IL7R, supporting observational epidemiology showing a protective effect for dog ownership. The lack of evidence for other G×E studied here implies only weak effects are likely to occur.

## 1 | Background

Atopic eczema (AE, synonymous with atopic dermatitis or eczema [1]) is a chronic inflammatory skin and systemic condition affecting approximately 20% of children and 10% of adults in high-income countries. Eczema is the dermatosis that contributes the greatest number of disability-adjusted life years worldwide [2] and co-morbid conditions, including asthma and allergies, obesity, cardiovascular disease, anxiety and depression, add substantially to the social, academic, occupational and financial impact [3]. Atopic eczema is a heritable trait [4] but the rapid rise in prevalence in industrialised areas over the past 30 years [3, 5] illustrates the importance of environmental factors in aetiology. A greater understanding of environmental effects in driving pathology could facilitate disease prevention.

The European Academy of Allergy and Clinical Immunology published an umbrella review of systematic reviews and identified a lack of research in eczema genetic epidemiology and environmental effects [6]. The investigation of environmental factors using observational epidemiology is inherently challenging in the context of AE because of multiple confounding factors and possible reverse causation [7]. Genetic studies, however, have made substantial progress in defining mechanisms in eczema predisposition and pathogenesis, including skin barrier dysfunction and aberrant immune response [8]. The evidence of individual variation in susceptibility to environmental allergens and irritants supports the concept of gene–environment interaction (G×E) [9] playing a role in AE. Loss-of-function variants in *FLG*, encoding the skin barrier protein filaggrin, have been implicated [10] but studies lack statistical power. Knowledge of genetic risk may provide an opportunity to identify key environmental effects and clarify important disease biology.

We aimed to investigate evidence of interaction between the most highly significant AE risk loci defined by genome-wide association

studies [11] and environmental risk factors defined by previous literature [7, 10] and of importance to patients and carers [12]. We used early-life environmental exposures (in utero and up to the first 24 months of life) to minimize reverse causation. G×E was tested in large cohorts from European populations, in discovery and replication phases, and mechanistic assessment was carried out in vitro using a skin keratinocyte model to validate interactions.

## 2 | Methods

### 2.1 | Genetic and Environmental Factors

Genetic risk loci were defined by the 24 top hits at each locus identified in European-ancestry AE genome-wide association studies [11, 13] and coded for the risk-increasing allele as effect allele (File S1). *FLG* null genotype was coded as presence/absence (0/1) of any of the loss-of-function variants prevalent in the white European population (R501X, 2282del4, R2447X, S3247X as previously reported [11, 14]).

Environmental exposures in utero or up to 24 months of age were selected on the basis of our literature review [10] and in discussion with representatives from a national eczema support group [12]. Data was available to allow analysis of 18 environmental effects: pet ownership for cat and dog separately; house dust mite exposure (at birth or 1 year); washing practices (at 6 months or 2 years); cigarette smoking within the household (in utero or up to 2 years); antibiotic use (6 or 12 months); environmental pollution (PM10 or at 5 months); breast feeding (ever and duration); mode of delivery; and presence of older siblings. These are listed in Files S2 and S3, with details of their definition and coding.

G×E effects showing a nominally significant interaction in the discovery and replication analyses were taken forward for in vitro modeling.
## 2.2 | Population Cohorts

Sixteen population-based cohorts from people of European ancestry (N=25,339) were included in the discovery analysis and a further 10 European population-based cohorts in the replication stage (N=254,532), giving a maximum total of 279,871 (maxN) in the final meta-analysis (File S4). AE was defined by parental report or doctor diagnosis for those who had 'ever had eczema'. Further details on the phenotype definitions can be found in File S2.

Each cohort has ethical approval for the sharing of anonymised data from study participants, with their written informed consent.

## 2.3 | Statistical Genetic Analysis

To test for G×E, a statistical model was fitted to include the main effect of each genetic variant upon eczema (G) (extracted from Paternoster et al. [11]), the main effect of the environmental factor upon eczema (E), and the product of the genetic effect and the environmental effect (G×E). Logistic regression models were applied to identify the main effect of each environmental factor (models M1–M4, File S5), and to test for interaction between the exposure and each SNP while adjusting for sex (models I1–I3, File S5). Sensitivity analyses were performed adjusting for family history of atopic disease (asthma, eczema or hay fever) and parental education as a proxy for socioeconomic status (models S1–S3, File S5).

Analyses were conducted separately within each cohort and then combined by fixed-effects meta-analysis. Genetic data was imputed separately for each cohort, detailed in File S2.

## 2.4 | Power Calculation

Posthoc estimates of statistical power were calculated in Quanto (version 1.2.4). These were informed by effect size estimates from the discovery analyses or previously published studies, assuming a case-to-control ratio of 1:3 and $\alpha=0.004$ in replication analyses (0.05/14 for multiple testing of 14 gene-environment pairs) (File S6).

## 2.5 | Review of In Silico Data for Genetic Variants

Variants showing statistical evidence of G×E were investigated using available data from previous publications [11, 13], the NHGRI-EBI GWAS Catalogue (https://www.ebi.ac.uk/gwas/), LDLLink (version 5.6.6), the Genome Aggregation Database (gnomAD v4.1.0, https://gnomad.broadinstitute.org/), UCSC Genome Browser (https://genome.ucsc.edu/), Open Targets (https://www.opentargets.org/), GTEx Portal (https://www.gtexportal.org/home/) and the Human Protein Atlas [15, 16].

## 2.6 | Keratinocyte Culture and Gene Expression

Full details are provided in File S7. In brief, primary human keratinocytes were isolated from normal human skin samples

and genotyped for rs10214237 using KASP (LGC Genomics, Teddington, England). IL7R mRNA expression was quantified in 34 keratinocyte samples (3 of C:C genotype, 15 T:C and 16 T:T) using RT-qPCR. Fold changes in gene expression were derived via the 2(-Delta Delta C[T]) method, using *EF1A* as the reference gene.

## 2.7 | In Vitro Analysis for rs10214237×Dog Interaction

Human keratinocytes comprise the outermost layer of skin and can therefore represent the first line of interaction in an allergen encounter in utero or early life. To further investigate the effect of dog exposure in early life, primary normal human keratinocytes were exposed to clinical-grade dog epithelial extract, a standardized reagent used for allergy testing in the clinic [17]. Methods are described in full in File S7. Briefly, gene expression was quantified using RT-qPCR, and cytokine, chemokine, and receptor expression was quantified using an ELISA array. Experiments were replicated using keratinocytes from a minimum of five independent donors. Gene ontology, network and pathway analyses were conducted using STRING v12.0.

## 3 | Results

Our analysis investigated the interaction between 24 variants identified in European GWAS studies [11, 13] and 18 environmental exposures selected through literature review (described in Section 2). We first assessed the observational association (of environmental effects) followed by testing for interaction effect (of environmental and genetic risk factors) in the discovery cohorts; next, the nominally significant findings and those with a priori evidence were tested for replication in available larger cohorts.

### 3.1 | Discovery Analysis

Meta-analyses of between 1084 and 22,263 participants (numbers dependent on exposure, File S4) showed strong evidence for anti-biotic use increasing the risk of AE (in utero $p=0.004$, at 6 months $p=0.001$ and at 12 months $p=6 \times 10^{-4}$); weaker evidence was found for a protective effect of dog ownership ($p=0.03$), a protective effect of childhood smoke exposure ($p=0.038$) and a risk effect of NO₂ levels ($p=0.035$) (M1 models, File S8). Little or no evidence ($p>0.05$) was found for effects of caesarean delivery, cat ownership, breastfeeding, elder siblings, in utero smoke exposure, washing practices at 6 months and 2 years, PM10 exposure, and house dust mite exposure at birth or 1 year (M1 models, File S8).

Of the 432 interactions tested (between 24 genetic variants and 18 environmental exposures), we found 14 nominally significant ($p_{int} < 0.05$) interactions, but no interactions passed multiple testing correction (Figure 1; Table 1). Of the nominally significant interactions, eight indicated a higher genetic risk in the presence of the exposure (OR > 1) and 6 indicated a higher genetic risk in the unexposed stratum (OR < 1). Of the 18 environmental exposures tested, the two with the strongest evidence for interaction with *FLG* null variants were exposure to tobacco smoke between 0 and
SNP

<figure><img src="image_3.png" /><figcaption>**FIGURE 1** | Heatmap to summarise results of interaction analyses. Strength of colour indicates beta in which blue is positive and red is a negative direction of effect; diameter of circle indicates sample size; 14 nominally significant interactions ($p_{int} < 0.05$) are highlighted with black outline; one association was reported in only one cohort, so it was not pursued further.</figcaption></figure>

2 years ($p_{int} = 0.018$) and washing practices during the same period ($p_{int} = 0.045$). There was little evidence ($p > 0.05$) for interactions between *FLG* null variants and other tested exposures, though confidence intervals for some interaction estimates were wide (File S8). Notably, there was little evidence for interaction between *FLG* null variants and cat exposure ($p = 0.36$), with strong effects of *FLG* in both the unexposed and exposed strata.

Sensitivity analyses, additionally adjusting for family history of AE and socioeconomic status, supported the main analyses (File S8), but many of the sensitivity analyses were based on much smaller sample sizes because of the requirement for data on additional covariates. There was little evidence of heterogeneity between cohorts (smallest $p_{het} = 0.01$) amongst the 14 reported interactions.

## 3.2 | Replication Analysis

Fourteen G×E interactions with nominal evidence were tested for replication. Additionally, exposures previously reported to interact

with *FLG* null variants (cat, siblings and breast-feeding [10]) were included in the replication analysis, making a total of 19 G×E interactions (8 exposures and 10 genetic variants) (File S9).

Dog exposure and rs1041237 showed evidence for interaction ($p_{int} = 0.025$, Table 1). In an analysis stratified by dog exposure, the T allele increases the risk of atopic eczema (OR = 1.14, 95% CI 1.08–1.22), but only amongst those who are not exposed to a dog in the family home. In individuals who are exposed to a dog in early life, this variant appears to have little or no effect (OR = 0.99, 95% CI 0.93–1.05, Figure 2).

Availability of environmental data for replication varied, with many of our attempted replications of interactions being insufficiently powered to be conclusive. Washing practices (0–2 years) and antibiotic use in utero interactions had only 3% and 4% power, respectively (File S6). The tobacco exposure in utero interaction had only 11% power, and the sibling interactions had 8%–37% power (dependent on variant). The breast-feeding duration interaction had 4% power in the replication phase, and so we extended the replication analysis to ‘ever breastfed’ to
<table><caption>TABLE 1 | Nominally significant interaction results from discovery and replication analyses.</caption><thead><tr><th rowspan="2">Exposure</th><th rowspan="2">SNV or gene</th><th colspan="6">Discovery</th><th colspan="6">Replication</th></tr><tr><th>N</th><th>N studies</th><th>OR</th><th>[95% CI]</th><th>p</th><th>p random</th><th>p heterogeneity</th><th>N</th><th>N studies</th><th>OR</th><th>[95% CI]</th><th>p</th><th>p combined</th></tr></thead><tbody><tr><td>Antibiotic use in utero</td><td>rs10995251</td><td>11,575</td><td>7</td><td>1.19</td><td>[1.00–1.42]</td><td>0.045</td><td>0.059</td><td>0.34</td><td>2666</td><td>1</td><td>0.88</td><td>[0.55–1.41]</td><td>0.59</td><td>0.09</td></tr><tr><td>Cat ownership</td><td>rs16948048</td><td>14,063</td><td>10</td><td>0.86</td><td>[0.76–0.97]</td><td>0.012</td><td>0.29</td><td>0.054</td><td>49,212</td><td>3</td><td>1</td><td>[0.92–1.08]</td><td>0.98</td><td>0.17</td></tr><tr><td>Cat ownership</td><td>rs2227483</td><td>14,644</td><td>11</td><td>1.13</td><td>[1.01–1.27]</td><td>0.037</td><td>0.18</td><td>0.014</td><td>49,212</td><td>3</td><td>1.05</td><td>[0.97–1.13]</td><td>0.25</td><td>0.036</td></tr><tr><td>Cat ownership</td><td>rs2228145</td><td>12,994</td><td>9</td><td>1.14</td><td>[1.01–1.29]</td><td>0.037</td><td>0.037</td><td>0.61</td><td>49,212</td><td>3</td><td>1</td><td>[0.92–1.08]</td><td>0.93</td><td>0.3</td></tr><tr><td>Cat ownership</td><td>rs2897442</td><td>12,702</td><td>9</td><td>0.87</td><td>[0.75–1.00]</td><td>0.044</td><td>0.11</td><td>0.35</td><td>49,212</td><td>3</td><td>1.02</td><td>[0.94–1.11]</td><td>0.59</td><td>0.58</td></tr><tr><td>Dog ownership</td><td>rs10214237</td><td>14,656</td><td>11</td><td>0.83</td><td>[0.72–0.96]</td><td>0.011</td><td>0.014</td><td>0.37</td><td>47,185</td><td>2</td><td>0.91</td><td>[0.83–0.99]</td><td>0.025</td><td>0.0013</td></tr><tr><td>Duration of any breastfeeding</td><td>rs13015714</td><td>14,474</td><td>9</td><td>1.02</td><td>[1.00–1.03]</td><td>0.049</td><td>0.068</td><td>0.32</td><td>4252</td><td>5</td><td>0.99</td><td>[0.95–1.02]</td><td>0.47</td><td>0.14</td></tr><tr><td>Elder siblings</td><td>rs10214237</td><td>19,155</td><td>11</td><td>0.84</td><td>[0.75–0.94]</td><td>0.003</td><td>0.003</td><td>0.99</td><td>5049</td><td>4</td><td>1.09</td><td>[0.82–1.46]</td><td>0.55</td><td>0.011</td></tr><tr><td>Elder siblings</td><td>rs10995251</td><td>18,608</td><td>10</td><td>0.89</td><td>[0.80–1.00]</td><td>0.042</td><td>0.042</td><td>0.44</td><td>7529</td><td>6</td><td>1.03</td><td>[0.85–1.25]</td><td>0.74</td><td>0.11</td></tr><tr><td>Elder siblings</td><td>rs7146581</td><td>19,176</td><td>11</td><td>1.25</td><td>[1.10–1.42]</td><td>0.00042</td><td>0.0031</td><td>0.32</td><td>7529</td><td>6</td><td>1.04</td><td>[0.84–1.29]</td><td>0.73</td><td>0.0012</td></tr><tr><td>Elder siblings</td><td>rs7927894</td><td>18,263</td><td>10</td><td>1.13</td><td>[1.01–1.26]</td><td>0.031</td><td>0.031</td><td>0.53</td><td>7529</td><td>6</td><td>1</td><td>[0.83–1.21]</td><td>0.97</td><td>0.058</td></tr><tr><td>Smoking in household up to 2 years</td><td>FLG<sup>a</sup></td><td>15,618</td><td>12</td><td>1.33</td><td>[1.05–1.68]</td><td>0.018</td><td>0.022</td><td>0.36</td><td>147,880</td><td>7</td><td>1.01</td><td>[0.81–1.25]</td><td>0.93</td><td>0.096</td></tr><tr><td>Smoking in household in utero</td><td>rs16948048</td><td>16,062</td><td>11</td><td>1.15</td><td>[1.02–1.31]</td><td>0.028</td><td>0.028</td><td>0.53</td><td>8078</td><td>5</td><td>1.04</td><td>[0.85–1.27]</td><td>0.72</td><td>0.039</td></tr><tr><td>Washing practices up to 2 years</td><td>FLG<sup>a</sup></td><td>6962</td><td>3</td><td>0.71</td><td>[0.51–0.99]</td><td>0.045</td><td>0.12</td><td>0.31</td><td>1061</td><td>1</td><td>1.93</td><td>[0.29–12.99]</td><td>0.5</td><td>0.063</td></tr></tbody></table>

Note: Results of testing for interaction between 24 genetic variants and 18 environmental exposures (File S3). Nominal significance defined as unadjusted $p_{int} < 0.05$.

Abbreviations: N, number; OR, odds ratio; p, significance from fixed effects meta-analysis; p combined, significance from combined fixed effects meta-analysis of discovery and replication; datap, random, significance from random effects meta-analysis.

<sup>a</sup>Combined null genotype for two or more loss-of-function mutations in FLG as detailed in cohort descriptions (File S2).
## A. Unexposed stratum

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

## B. Exposed stratum

<figure><img src="image_5.png" /><figcaption>FIGURE 2 | Legend on next page.</figcaption></figure>
**FIGURE 2** | Forest plot showing interaction of dog exposure with rs1041237 in (A) unexposed and (B) exposed strata. Interaction analysis for discovery (N=18,045), replication (N=47,185) and combined meta-analysis (total N=65,230) show the T allele of rs1041237 increases the risk of atopic eczema only amongst those who are not exposed to a dog in the family home. Full names and study cohort descriptions are given in File S2.

increase the power to 56%. The interactions with dog, cat and tobacco smoke exposure 0–2 years were all sufficiently powered (88%, 72%–88% and 99%, respectively). The previously reported interactions between *FLG* null mutations and cat, siblings, and ever breastfed had 99% power, based on their previously reported interaction effects (File S6).

## 3.3 | In Silico Follow-Up of rs10214237

rs10214237 is an intergenic variant (T>C) on chromosome 5p13.2; an association with AE was identified by genome-wide association study (GWAS) [11] in which *IL7R* was prioritized as the likely causal gene based on evidence including eQTL co-localization in macrophages and monocytes [13, 18]. The top single nucleotide variant (SNV) at this locus in a more recent GWAS meta-analysis [13] is rs10214273, but this variant is in complete linkage disequilibrium with rs10214237 in European populations ($R^2=1$, LDLink version 5.6.6, LDPair tool). Global population data from gnomAD shows ancestral differences in allele frequency, with rs10214237 being more frequent in European and South Asian populations (MAF 0.28 and 0.20, respectively) compared to African people (MAF 0.07) (1KG data accessed 10 Jan 2025).

rs10214237 is within a region of open chromatin in keratinocytes and fibroblasts, but not the lymphoblastoid cell line GM12878 (UCSC Genome Browser 6 Feb and 27 Nov 2024). Open Targets V2G analyses confirm *IL7R* as the most likely gene affected by this SNV based on pQTL, sQTL and eQTL (6 Feb and 27 Nov 2024). GTEx data show that the expression of *IL7R* is higher with T:T genotype in whole blood and cultured fibroblasts, and in our newly generated data, we show that individuals with the T:T genotype have slightly higher *IL7R* mRNA expression in primary human keratinocytes than those with the C:C genotype (File S10). Single cell data from the Human Protein Atlas [15, 16] confirm that IL-7R is expressed at the protein level in human keratinocytes, in addition to circulating immune cells.

## 3.4 | In Vitro Testing of the Effects of Dog Allergen on Human Keratinocytes

Dog allergen exposure stimulated an up-regulation in *CXCL8* (IL-8), *CSF2*, *CCL2* and *TNF* mRNA, but the atopy-related cytokines *IL33* and *TSLP* mRNA were down-regulated (Figure 3A). Network analysis of the proteins encoded by the upregulated transcripts showed significant enrichment for IL-10 signalling (Figure 3B, Reactome pathway FDR 7.71e-08) which plays a suppressive role in contact dermatitis and atopic eczema [19]. To test the keratinocyte response more broadly, we used an ELISA panel of 64 cytokines, chemokines and receptors (File S11). This confirmed the signature of increased IL-10 signalling (File S11).

Next, using primary human keratinocytes of known rs10214237 genotype and focusing on *CXCL8* (IL-8), *CCL2* and IL-6 as

molecules of relevance to IL-7R signalling in epithelial cells, we investigated the effect of dog allergen exposure, with and without IL-7 stimulation (Figure 3C–E). There was no difference in expression levels after IL-7 stimulation, but on stimulation with dog extract (or IL-7 plus dog extract), keratinocytes of the T:T genotype (homozygous for the eczema-risk allele) showed a greater response than the C:C genotype.

This work is preliminary and requires further mechanistic investigation in a larger number of samples, but these observations provide a possible mechanistic explanation for the finding that the T allele at rs10214237 increases risk for atopic eczema. The T:T genotype shows greater IL-7R mRNA expression, but in the context of dog exposure, the risk effect is overshadowed by an increase in cytokines and chemokines in the IL-10 pathway that suppress eczema to a greater extent in T:T than C:C individuals.

# 4 | Discussion

## 4.1 | Large, Systematic Study of G×E in Atopic Eczema

Our collaborative work represents the largest and most comprehensive analysis to date investigating G×E in AE, using a systematic approach focused on the most significant genetic loci and selected environmental factors. We first meta-analyzed data from available observational studies to test for association and then applied interaction analysis to investigate G×E. Statistical power remains a limiting factor and the nominal significance level (*p* < 0.05 without correction for multiple testing) means cautious interpretation is needed. We have identified important negative results as well as one interaction with functional validation in vitro and others that warrant further follow-up.

A variety of sources provide evidence that G×E plays a role in the aetiology of AE. These include rapidly rising prevalence [5], clinical observation [4], epidemiological studies [10], and in vitro analyses demonstrating molecular effects that include aryl hydrocarbon receptor signalling [20]. Some authors have even stated that ‘atopic eczema is an environmental disease’ [21]. Our meta-analysis of observational associations provides evidence that early-life exposure to antibiotics and $NO_2$ levels associates with an increased risk of AE, whilst early-life exposure to dog or tobacco smoke is associated with a lower risk of AE in the populations studied. However, these associations may be affected by bias through confounding and reverse causation.

## 4.2 | Genotype-Specific Effects of Early-Life Dog Exposure

Statistical interaction analysis indicates that early-life dog exposure may modify the genetic effect of rs10214237. Functional
<figure><img src="image_6.png" /><figcaption>**FIGURE 3** | In vitro testing of the effects of dog allergen on primary human keratinocytes. (A) Dog allergen exposure stimulated a reduction in IL33 and TSLP mRNA but upregulation of CXCL8 (IL-8), CSF2, CCL2, and TNF; negative indicates keratinocyte media with dog allergen carrier solution; 5–12 donor isolates shown, bars represent SEM one-way ANOVA, Dunnett post hoc test compared to negative control, \*\*p < 0.01, \*\*\*p < 0.001, \*\*\*\*p < 0.0001. (B) IL-10 signaling was the most significantly enriched Reactome pathway (4 out of 45 genes/proteins, FDR 7.71e-08). (C–E) Effects of IL-7 and dog allergen stimulation on primary human keratinocytes with different rs10214237 genotypes in which T is the eczema risk allele; graphs represent the mean fold change in cytokine mRNA expression relative to the housekeeping gene EF1A, from four keratinocyte isolates with T:T genotype and two keratinocyte isolates from donors of C:C genotype; untreated indicates keratinocyte media only and negative is keratinocyte media with dog allergen carrier solution; BSA as 0.0002% included for as carrier protein for recombinant Il-7; two-way ANOVA with Dunnett's post hoc test, compared to the negative control, bars represent SEM, \*p < 0.05, \*\*p < 0.01.</figcaption></figure>

genetic analyses show an effect mediated via the gene IL7R, which encodes the alpha-subunit of the IL-7 receptor. Rs10214237 T:T genotype was associated with an increased risk of atopic eczema in the population as a whole and in the sub-population without dog exposure (Figure 2) consistent with the T:T genotype showing slightly greater IL7R mRNA expression (File S10). The IL-7 receptor is a heterodimer composed of IL7R-alpha and IL2R-gamma. It is expressed in multiple cell types and tissues, including T-cells, NK-cells, glandular, and stratified epithelial cells (data from Human Protein Atlas [15, 16]). IL7R-alpha also contributes to a heteromeric complex with the thymic stromal lymphopoietin (TSLP) receptor, but our experimental work to test TSLP as an alternative ligand in keratinocytes was not informative (data not shown) likely in part because the TSLPR is only very lowly expressed in keratinocytes [16, 22].

Our detailed work in vitro focused on human epidermal keratinocytes as the earliest tissue to encounter dog allergen in the

initiation of atopic disease, in utero or early infancy. We have shown evidence that keratinocytes display a direct response to dog allergen exposure, with down-regulation of IL-33 and TSLP mRNA (both inducers of type 2 immune responses in atopy [23, 24]) and upregulation of a network of genes encoding chemokines and cytokines of IL-10 signaling (Reactome pathway HAS-6783783), contributing to the suppression of atopic inflammation [19]. This is consistent with observational epidemiology showing an apparent protective effect of dog exposure early in life [25, 26]. Gene ontology analysis of the same network indicates a role in cellular response to lipopolysaccharide (GO:0071222), likely to reflect a response to gram-negative components of the canine microbiome.

The proposed interaction with genotype was investigated using keratinocytes of known rs10214237 genotype. This is preliminary mechanistic work and further, more detailed investigations are required. However, our analyses indicate a trend in which
the T:T cells show a greater increase in IL-10 signaling in re-
sponse to dog allergen exposure than C:C. This is consistent
with the suppression of atopic eczema risk on a population level
in the dog-exposed T:T individuals, while non-dog-exposed T:T
individuals remain at risk of disease. The precise mechanistic
pathways remain to be defined, but the interaction between
rs10214237 and dog exposure in AE risk is analogous to the
17q21×dog interaction previously demonstrated in asthma, in
which the risk of persistent wheeze is attenuated by dog own-
ership [27]. There is also an interesting parallel in the interac-
tion of rs10214237 with exposure to older siblings, in which the
older sibling abrogates the risk effect for rs10214237. We spec-
ulate that this may be related to the increased microbial expo-
sure experienced by an infant with older siblings (or a dog) in
the household. There is evidence of shared skin and gut micro-
biomes between humans and their pets [28], but it could also
reflect lifestyle choices of dog-owning families and these hy-
potheses require further testing.

4.3 | Lack of Evidence for Previously Reported FLG×Environment Effects

In our previous systematic review focusing on gene–envi-
ronment interactions with FLG null mutations [10] we found
some published evidence for FLG×environment interactions
with exposures including early-life cat ownership, older sib-
lings, water hardness, phthalate exposure and prolonged
breastfeeding from the small number of previous studies. The
lack of replication of the FLG×cat ownership interaction in
the large, well-powered study reported here and another re-
cent meta-analysis [29] represents an important null finding.
Two small birth cohort studies [30, 31] (n = 379 and n = 503)
reported *p* values for interaction < 0.01 with evidence for in-
creased risks of AE in those with FLG null mutations exposed
to cat in early life, but the evidence for these G×E interactions
came from small numbers of individuals (n = 5 in one study
[30]) with FLG mutation, cat exposure, and development of
AE. We had very good power (99%) for the interaction magni-
tude previously reported (OR<sub>int</sub> = 11) [30] and 80% for an inter-
action as small as OR<sub>int</sub> = 1.26, suggesting very little evidence
in our data for FLG×cat interaction. We found little evidence
for FLG×breastfeeding, consistent with our systematic re-
view [10], where studies reported no evidence for interactions
with breastfeeding, although an FLG×breastfeeding duration
interaction was reported from the Isle of Wight cohort [32].
Here, our post hoc power calculation (File S6) showed ade-
quate power (99%) for the FLG×breastfed-ever interaction,
but low power (< 1%) for FLG×breastfeeding duration analy-
ses, which may explain the discrepancy.

4.4 | Limitations

The discovery analysis used selected SNVs to represent known
eczema risk loci, rather than conducting a genome-wide inter-
action analysis. This restricted approach is needed because of
power constraints even in large population datasets, and it has
been shown to be effective in other traits [33]. A post hoc esti-
mation of statistical power (File S6) showed that our replication
sample sizes were insufficient for some interactions. Therefore,

where replication results do not meet our pre-specified signifi-
cance threshold, it is not possible to definitively exclude an in-
teraction, but we report the interaction effect sizes for which
we had good statistical power, to demonstrate the magnitude
of interactions that are unlikely to exist, given our null results
(File S6). Furthermore, by focusing on selected SNVs within
the known AE risk loci, we acknowledge that there may be loci
in which an effect is only apparent in the context of interaction
with an environmental exposure. These would not be detected
by our analysis strategy, and genome-wide interaction analysis
should be considered in future work if far larger sample sizes
than those used here become available. The prospective col-
lection of detailed environmental data is challenging, and the
availability of relevant information has limited our analyses. A
specific example is the recording of washing practices, quanti-
fied by frequency of bathing but lacking important details such
as the type of wash product used.

An important limitation to this work is the use of European
cohort data including people of predominantly white ancestry;
this reflects the current sparsity of diverse ancestries in popu-
lation genetic studies of sufficient size to carry out these analy-
ses. The observed differences in allele frequency of rs10214237
in African compared to European and South Asian populations
illustrate the limited transferability of this variant effect across
populations, although other population-specific variants in
the same locus may contribute to similar mechanistic effects.
International efforts are on-going to address this limitation [34],
and future G×E studies are needed to investigate population-
specific environmental effects. More detailed sub-phenotyping
of AE may, in the future, reveal that more specific genetic
and environmental drivers exist in distinct ancestral or sub-
phenotype groups.

4.5 | Conclusions

We report observational evidence for an association of AE with
exposure to antibiotics, NO₂, and tobacco smoke in early life,
but the precise nature and mechanisms of action of these en-
vironmental factors on atopic skin inflammation remain un-
clear. We detected an observational association between early
life dog exposure and reduction in prevalence of AE, in keeping
with previous reports. Further interaction analysis and func-
tional assessments provide evidence that dog exposure reduces
the genetic risk effect of rs10214237 in a pathway via IL7R and
possibly IL-10, to suppress skin inflammation. There may be an
equivalent interaction effect with siblings, but this is not possi-
ble to model in vitro. The lack of statistical evidence for other
G×E explored in this analysis suggests that only weak inter-
actions are likely to exist, indicating that on a population level
the interactions tested and found to be null are unlikely to have
important contributions to AE pathogenesis. Future, larger lon-
gitudinal studies should therefore focus on alternative mecha-
nistic investigations.

Author Contributions

A.B.-A., P.B., K.B., D.B., S.J.B., M.B.P., A.Cu., C.F., J.He., J.W.H.,
J.O'B.H., A.D.I., G.H.K., P.D.M., S.M.L., Y.-A.L., D.M., E.M., C.S.M.,
DMM, S.P., L.P., CP, N.J.R., A.S., C.S., M.S., J.P.T., and C.A.W. made substantial contributions to the conception or design of the work; all authors contributed to the acquisition, analysis, or interpretation of data; A.B.-A., S.J.B., A.Cu., L.D., C.F., A.D.I., G.H.K., S.M.L., Y.-A.L., L.P., N.J.R., C.S., and M.S. drafted the work or substantively revised it. All authors have approved the submitted version.

## Affiliations

¹Institute of Epidemiology, Helmholtz Zentrum München – German Research Center for Environmental Health, Neuherberg, Germany | ²German Center for Child and Adolescent Health (DZKJ), partner site Munich, Munich, Germany | ³MRC Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, Bristol, UK | ⁴Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK | ⁵Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton, UK | ⁶NIHR Southampton Biomedical Research Centre, University Hospitals Southampton NHS Foundation Trust, Southampton, UK | ⁷Asthma and Allergy Research Centre, Isle of Wight, UK | ⁸Department of Epidemiology Research, Statens Serum Institute, Copenhagen, Denmark | ⁹Department of Twin Research and Genetic Epidemiology, King's College London, London, UK | ¹⁰COPSAC, Copenhagen Prospective Studies on Asthma in Childhood, Herlev and Gentofte Hospital, University of Copenhagen, Copenhagen, Denmark | ¹¹Department of Biological Psychology, Faculty of Behavioral and Movement Sciences, Vrije Universiteit, Amsterdam, the Netherlands | ¹²Department of Public Health and Nursing, HUNT Center for Molecular and Clinical Epidemiology, Norwegian University of Science and Technology, Trondheim, Norway | ¹³ISGlobal, Institute for Global Health, Barcelona, Spain | ¹⁴Universitat Pompeu Fabra (UPF), Barcelona, Spain | ¹⁵Spanish Consortium for Research on Epidemiology and Public Health (CIBERESP), Madrid, Spain | ¹⁶Division of Immunology, Immunity to Infection and Respiratory Medicine, School of Biological Sciences, The University of Manchester, Manchester Academic Health Science Centre, and Manchester University NHS Foundation Trust, Manchester, UK | ¹⁷Department of Dermatology and Allergy, Herlev and Gentofte Hospital, University of Copenhagen, Hellerup, Denmark | ¹⁸Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands | ¹⁹Max-Delbrück-Center (MDC) for Molecular Medicine, Berlin, Germany | ²⁰Division of Climate and Environmental Health, Department of Air Quality and Noise, Norwegian Institute of Public Health (NIPH), Oslo, Norway | ²¹Department of Dermatology and Venereology, Bispebjerg Hospital, University of Copenhagen, Copenhagen N, Denmark | ²²Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland, USA | ²³Human Development and Health, Faculty of Medicine, University of Southampton, Southampton, UK | ²⁴Royal College of Surgeons in Ireland, Dublin, Ireland | ²⁵Children's Health Ireland, Dublin, Ireland | ²⁶INFANT Centre, University College Cork, Cork, Ireland | ²⁷The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands | ²⁸Department of Dermatology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands | ²⁹Department for Research, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway | ³⁰Department of Preventive Medicine and Public Health, UPV/EHU, Leioa, Spain | ³¹Biogipuzkoa HRI, Donostia, Spain | ³²Univ Rennes, Inserm, EHESP, Irset (Institut de recherche en santé, environnement et travail) – UMR_S 1085, Rennes, France | ³³IUF-Leibniz Research Institute for Environmental Medicine, Düsseldorf, Germany | ³⁴Department of Pediatric Respiratory Medicine, Immunology, and Intensive Care Medicine, Charité-Universitätsmedizin Berlin, Berlin, Germany | ³⁵Epidemiology and Environmental Health Joint Research Unit, FISABIO-Universitat Jaume I-Universitat de València, Valencia, Spain | ³⁶Department of Dermatology, Clinic of Orthopedy, Rheumatology and Dermatology, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway | ³⁷Clinic for Pediatric Allergy, Experimental and Clinical

Research Center, Charité University Medical Center, Berlin, Germany | ³⁸Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust, Bradford, UK | ³⁹Danish Cancer Institute, Copenhagen, Denmark | ⁴⁰Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark | ⁴¹Department of Pediatrics, Stanford University School of Medicine, Stanford, California, USA | ⁴²Department of Clinical Science and Education, Södersjukhuset, Karolinska Institutet, Stockholm, Sweden | ⁴³School of Medicine and Public Health, The University of Newcastle, Newcastle, New South Wales, Australia | ⁴⁴Mothers and Babies Research Program, Hunter Medical Research Institute, Newcastle, New South Wales, Australia | ⁴⁵Department of Neonatology, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark | ⁴⁶University College Cork, Cork, Ireland | ⁴⁷Cork University Hospital, Cork, Ireland | ⁴⁸Department of Women's and Children's Health, Karolinska Institutet, Stockholm, Sweden | ⁴⁹Astrid Lindgren's Children's Hospital, Karolinska University Hospital, Stockholm, Sweden | ⁵⁰Department of Clinical and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, Norway | ⁵¹BioCore – Bioinformatics Core Facility, Norwegian University of Science and Technology, Trondheim, Norway | ⁵²Area de Salut de Menorca, ib-salut, Balearic Islands, Spain | ⁵³Department of Clinical and Biological Sciences, Center for Biostatistics, Epidemiology and Public Health, University of Turin, Turin, Italy | ⁵⁴Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands | ⁵⁵University of Groningen, University Medical Center Groningen, Groningen Research Institute for Asthma and COPD (GRIAC), Groningen, the Netherlands | ⁵⁶Centre for Individualised Infection Medicine (CiiM), a joint venture between the Helmholtz Centre for Infection Research (HZI) and Hannover Medical School (MHH), Hannover, Germany | ⁵⁷TWINCORE, a joint venture between the Helmholtz-Centre for Infection Research (HZI) and the Hannover Medical School (MHH), Hannover, Germany | ⁵⁸Department of Community Medicine and Behavioral Sciences, College of Medicine, Kuwait University, Kuwait City, Kuwait | ⁵⁹National Heart and Lung Institute, Imperial College London, London, UK | ⁶⁰St John's Institute of Dermatology and the School of Basic and Medical Sciences, King's College London, London, UK | ⁶¹Division of Respiratory Medicine and Allergology, and Neonatology, Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands | ⁶²Division of Neonatology, Department of Neonatal and Intensive Care, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands | ⁶³Department of Paediatric Dermatology, St John's Institute of Dermatology, Guy's and St Thomas' NHS Foundation Trust and King's College London, London, UK | ⁶⁴Department of Clinical Medicine, Trinity College Dublin, Dublin, Ireland | ⁶⁵Department of Pediatric Pulmonology and Pediatric Allergology, Beatrix Children's Hospital, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands | ⁶⁶Faculty of Medical Sciences, Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, UK | ⁶⁷Department of Dermatology and NIHR Newcastle Biomedical Research Centre, Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne, UK | ⁶⁸Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, UK | ⁶⁹St John's Institute of Dermatology, Guy's and St Thomas' NHS Foundation Trust, London, UK | ⁷⁰NIHR Bristol Biomedical Research Centre, University Hospital Bristol and Weston NHS Foundation Trust and University of Bristol, Bristol, UK | ⁷¹Department of Dermatology, NHS Lothian, Edinburgh, Scotland, UK

## Acknowledgements

We are grateful to all patients and participants in the contributing cohort studies and to the skin donors and surgical team at the Western General Hospital, Edinburgh, for providing samples of normal skin tissue for this research; to our UK-TREND collaborators including Mike Cork for informative discussion; to Heather J. Cordell for advice on
statistical genetics approaches; to Lisa Maier for preparing Figure 1; and to Dr. Lauren Kelly and Ms. Lucy Glass for administrative support.

## Conflicts of Interest

S.J.B. has received research funding (but no personal financial benefits) from the Wellcome Trust (220875/Z/20/Z), UKRI, Medical Research Council, Rosetrees Trust, Stoneygates Trust, British Skin Foundation, Charles Wolfson Charitable Trust, anonymous donations from people with eczema, Unilever, Pfizer, Abbvie, Sosei-Heptares, Janssen, and European Lead Factory (which includes multiple industry partners). S.J.B., A.B.-A., K.B., A.D.I., G.H.K., C.S., S.M.L., and L.P. have received funding from the BIOMAP-IMI consortium (EU H2020 project ref. no. 821511) which receives support from several pharmaceutical industry partners. L.P. has received an honorarium payment for a scientific talk on eczema genetics from LEO Pharma. G.H.K. reports grants from the Netherlands Lung Foundation, ZON-MW, Ubbo Emmius Foundation, TEVA the Netherlands, GSK, Vertex, outside the submitted work (money to institution). His institution received compensation for consultancy or lectures from Astra Zeneca, Boehringer Ingelheim, and Sanofi.

## Data Availability Statement

The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.

## References

1. S. Johansson, T. Bieber, R. Dahl, et al., "Revised Nomenclature for Allergy for Global Use: Report of the Nomenclature Review Committee of the World Allergy Organization, October 2003," *Journal of Allergy and Clinical Immunology* 113, no. 5 (2004): 832-836.

2. S. Mehrmal, P. Uppal, R. L. Giesey, and G. R. Delost, "Identifying the Prevalence and Disability-Adjusted Life Years of the Most Common Dermatoses Worldwide," *Journal of the American Academy of Dermatology* 82, no. 1 (2020): 258-259.

3. K. Urban, S. Chu, R. L. Giesey, et al., "The Global, Regional, and National Burden of Atopic Dermatitis in 195 Countries and Territories: An Ecological Study From the Global Burden of Disease Study 2017," *JAAD International* 2 (2021): 12-18.

4. S. M. Langan, A. D. Irvine, and S. Weidinger, "Atopic Dermatitis," *Lancet* 396, no. 10247 (2020): 345-360.

5. J. A. Odhiambo, H. C. Williams, T. O. Clayton, C. F. Robertson, M. I. Asher, and Group IPTS, "Global Variations in Prevalence of Eczema Symptoms in Children From ISAAC Phase Three," *Journal of Allergy and Clinical Immunology* 124, no. 6 (2009): 1251-1258.e3.

6. J. Genuneit, A. M. Seibold, C. J. Apfelbacher, et al., "Overview of Systematic Reviews in Allergy Epidemiology," *Allergy* 72, no. 6 (2017): 849-856.

7. C. E. Rutter, R. J. Silverwood, H. C. Williams, et al., "Are Environmental Factors for Atopic Eczema in ISAAC Phase Three due to Reverse Causation?," *Journal of Investigative Dermatology* 139, no. 5 (2019): 1023-1036.

8. S. J. Brown, "What Have We Learned From GWAS for Atopic Dermatitis?," *Journal of Investigative Dermatology* 141, no. 1 (2021): 19-22.

9. R. Ottman, "Gene-Environment Interaction: Definitions and Study Designs," *Preventive Medicine* 25, no. 6 (1996): 764-770.

10. H. Blakeway, V. Van-de-Velde, V. B. Allen, et al., "What Is the Evidence for Interactions Between Filaggrin Null Mutations and Environmental Exposures in the Aetiology of Atopic Dermatitis? A Systematic Review," *British Journal of Dermatology* 183, no. 3 (2020): 443-451.

11. L. Paternoster, M. Standl, J. Waage, et al., "Multi-Ancestry Genome-Wide Association Study of 21,000 Cases and 95,000 Controls Identifies

New Risk Loci for Atopic Dermatitis," *Nature Genetics* 47, no. 12 (2015): 1449-1456.

12. S. J. Brown, "Discussion With Eczema Outreach Scotland," 2018, https://eos.org.uk/.

13. A. Budu-Aggrey, A. Kilanowski, M. K. Sobczyk, et al., "European and Multi-Ancestry Genome-Wide Association Meta-Analysis of Atopic Dermatitis Highlights Importance of Systemic Immune Regulation," *Nature Communications* 14, no. 1 (2023): 6172.

14. A. Sandilands, A. Terron-Kwiatkowski, P. Hull, et al., "Comprehensive Analysis of the Gene Encoding Filaggrin Uncovers Prevalent and Rare Mutations in Ichthyosis Vulgaris and Atopic Eczema," *Nature Genetics* 39, no. 5 (2007): 650-654.

15. P. J. Thul, L. Akesson, M. Wiking, et al., "A Subcellular Map of the Human Proteome," *Science* 356, no. 6340 (2017): 3321.

16. "Human Protein Atlas," 2024, http://www.proteinatlas.org.

17. G. Patel and C. Saltoun, "Skin Testing in Allergy," *Allergy and Asthma Proceedings* 40, no. 6 (2019): 366-368.

18. M. K. Sobczyk, T. G. Richardson, V. Zuber, et al., "Triangulating Molecular Evidence to Prioritize Candidate Causal Genes at Established Atopic Dermatitis Loci," *Journal of Investigative Dermatology* 141, no. 11 (2021): 2620-2629.

19. O. Boyman, T. Werfel, and C. A. Akdis, "The Suppressive Role of IL-10 in Contact and Atopic Dermatitis," *Journal of Allergy and Clinical Immunology* 129, no. 1 (2012): 160-161.

20. T. Hidaka, E. Ogawa, E. H. Kobayashi, et al., "The Aryl Hydrocarbon Receptor AhR Links Atopic Dermatitis and Air Pollution via Induction of the Neurotrophic Factor Artemin," *Nature Immunology* 18, no. 1 (2017): 64-73.

21. D. Luschkova, K. Zeiser, A. Ludwig, and C. Traidl-Hoffmann, "Atopic Eczema Is an Environmental Disease," *Allergologie Select* 5 (2021): 244-250.

22. W. Zhong, X. Wu, W. Zhang, et al., "Aberrant Expression of Histamine-Independent Pruritogenic Mediators in Keratinocytes May Be Involved in the Pathogenesis of Prurigo Nodularis," *Acta Dermatovenereologica* 99, no. 6 (2019): 579-586.

23. R. Ebina-Shibuya and W. J. Leonard, "Role of Thymic Stromal Lymphopoietin in Allergy and Beyond," *Nature Reviews. Immunology* 23, no. 1 (2023): 24-37.

24. F. Y. Liew, J. P. Girard, and H. R. Turnquist, "Interleukin-33 in Health and Disease," *Nature Reviews. Immunology* 16, no. 11 (2016): 676-689.

25. S. Thorsteinsdottir, J. P. Thyssen, J. Stokholm, N. H. Vissing, J. Waage, and H. Bisgaard, "Domestic Dog Exposure at Birth Reduces the Incidence of Atopic Dermatitis," *Allergy* 71, no. 12 (2016): 1736-1744.

26. A. A. Eapen, A. R. Sitarik, G. Cheema, et al., "Effect of Prenatal Dog Exposure on Eczema Development in Early and Late Childhood," *Journal of Allergy and Clinical Immunology in Practice* 10, no. 12 (2022): 3312-3314.e11.

27. M. Tutino, R. Granell, J. A. Curtin, et al., "Dog Ownership in Infancy Is Protective for Persistent Wheeze in 17q21 Asthma-Risk Carriers," *Journal of Allergy and Clinical Immunology* 151, no. 2 (2023): 423-430.

28. J. Lehtimaki, H. Sinkko, A. Hielm-Bjorkman, T. Laatikainen, L. Ruokolainen, and H. Lohi, "Simultaneous Allergic Traits in Dogs and Their Owners Are Associated With Living Environment, Lifestyle and Microbial Exposures," *Scientific Reports* 10, no. 1 (2020): 21954.

29. J. P. Thyssen, T. S. Ahluwalia, L. Paternoster, et al., "Interaction Between Filaggrin Mutations and Neonatal Cat Exposure in Atopic Dermatitis," *Allergy* 75, no. 6 (2020): 1481-1485.

30. H. Bisgaard, A. Simpson, C. N. Palmer, et al., "Gene-Environment Interaction in the Onset of Eczema in Infancy: Filaggrin Loss-of-Function
Mutations Enhanced by Neonatal Cat Exposure,” *PLoS Medicine* 5, no. 6 (2008): e131, https://doi.org/10.1371/journal.pmed.0050131.

31. M. L. Schuttelaar, M. Kerkhof, M. F. Jonkman, et al., “Filaggrin Mutations in the Onset of Eczema, Sensitization, Asthma, Hay Fever and the Interaction With Cat Exposure,” *Allergy* 64, no. 12 (2009): 1758–1765, https://doi.org/10.1111/j.1398-9995.2009.02080.x.

32. A. H. Ziyab, N. Mukherjee, S. Ewart, et al., “Filaggrin Gene Loss-Of-Function Variants Modify the Effect of Breast-Feeding on Eczema Risk in Early Childhood,” *Allergy* 71, no. 9 (2016): 1371–1373.

33. D. Shungin, W. Q. Deng, T. V. Varga, et al., “Ranking and Characterization of Established BMI and Lipid Associated Loci as Candidates for Gene-Environment Interactions,” *PLoS Genetics* 13, no. 6 (2017): e1006812.

34. L. N. Borrell, J. R. Elhawary, E. Fuentes-Afflick, et al., “Race and Genetic Ancestry in Medicine – A Time for Reckoning With Racism,” *New England Journal of Medicine* 384, no. 5 (2021): 474–480.

**Supporting Information**

Additional supporting information can be found online in the Supporting Information section.