Gene-environment interaction analysis in atopic eczema: evidence from large population datasets and modelling in vitro

Gene-environment interaction analysis in atopic eczema: evidence from large population datasets and modelling in vitro | medRxiv /* */ /* */ <!-- <!-- /*! * yepnope1.5.4 * (c) WTFPL, GPLv2 */ (function(a,b,c){function d(a){return"[object Function]"==o.call(a)}function e(a){return"string"==typeof a}function f(){}function g(a){return!a||"loaded"==a||"complete"==a||"uninitialized"==a}function h(){var a=p.shift();q=1,a?a.t?m(function(){("c"==a.t?B.injectCss:B.injectJs)(a.s,0,a.a,a.x,a.e,1)},0):(a(),h()):q=0}function i(a,c,d,e,f,i,j){function k(b){if(!o&&g(l.readyState)&&(u.r=o=1,!q&&h(),l.onload=l.onreadystatechange=null,b)){"img"!=a&&m(function(){t.removeChild(l)},50);for(var d in y[c])y[c].hasOwnProperty(d)&&y[c][d].onload()}}var j=j||B.errorTimeout,l=b.createElement(a),o=0,r=0,u={t:d,s:c,e:f,a:i,x:j};1===y[c]&&(r=1,y[c]=[]),"object"==a?l.data=c:(l.src=c,l.type=a),l.width=l.height="0",l.onerror=l.onload=l.onreadystatechange=function(){k.call(this,r)},p.splice(e,0,u),"img"!=a&&(r||2===y[c]?(t.insertBefore(l,s?null:n),m(k,j)):y[c].push(l))}function j(a,b,c,d,f){return q=0,b=b||"j",e(a)?i("c"==b?v:u,a,b,this.i++,c,d,f):(p.splice(this.i++,0,a),1==p.length&&h()),this}function k(){var a=B;return a.loader={load:j,i:0},a}var l=b.documentElement,m=a.setTimeout,n=b.getElementsByTagName("script")[0],o={}.toString,p=[],q=0,r="MozAppearance"in l.style,s=r&&!!b.createRange().compareNode,t=s?l:n.parentNode,l=a.opera&&"[object Opera]"==o.call(a.opera),l=!!b.attachEvent&&!l,u=r?"object":l?"script":"img",v=l?"script":u,w=Array.isArray||function(a){return"[object Array]"==o.call(a)},x=[],y={},z={timeout:function(a,b){return b.length&&(a.timeout=b[0]),a}},A,B;B=function(a){function b(a){var a=a.split("!"),b=x.length,c=a.pop(),d=a.length,c={url:c,origUrl:c,prefixes:a},e,f,g;for(f=0;f<d;f++)g=a[f].split("="),(e=z[g.shift()])&&(c=e(c,g));for(f=0;f<b;f++)c=x[f](c);return c}function g(a,e,f,g,h){var i=b(a),j=i.autoCallback;i.url.split(".").pop().split("?").shift(),i.bypass||(e&&(e=d(e)?e:e[a]||e[g]||e[a.split("/").pop().split("?")[0]]),i.instead?i.instead(a,e,f,g,h):(y[i.url]?i.noexec=!0:y[i.url]=1,f.load(i.url,i.forceCSS||!i.forceJS&&"css"==i.url.split(".").pop().split("?").shift()?"c":c,i.noexec,i.attrs,i.timeout),(d(e)||d(j))&&f.load(function(){k(),e&&e(i.origUrl,h,g),j&&j(i.origUrl,h,g),y[i.url]=2})))}function h(a,b){function c(a,c){if(a){if(e(a))c||(j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}),g(a,j,b,0,h);else if(Object(a)===a)for(n in m=function(){var b=0,c;for(c in a)a.hasOwnProperty(c)&&b++;return b}(),a)a.hasOwnProperty(n)&&(!c&&!--m&&(d(j)?j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}:j[n]=function(a){return function(){var b=[].slice.call(arguments);a&&a.apply(this,b),l()}}(k[n])),g(a[n],j,b,n,h))}else!c&&l()}var h=!!a.test,i=a.load||a.both,j=a.callback||f,k=j,l=a.complete||f,m,n;c(h?a.yep:a.nope,!!i),i&&c(i)}var i,j,l=this.yepnope.loader;if(e(a))g(a,0,l,0);else if(w(a))for(i=0;i (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0];var j=d.createElement(s);var dl=l!='dataLayer'?'&l='+l:'';j.src='//www.googletagmanager.com/gtm.js?id='+i+dl;j.type='text/javascript';j.async=true;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-P4HH5NV'); Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search Gene-environment interaction analysis in atopic eczema: evidence from large population datasets and modelling in vitro Marie Standl , Ashley Budu-Aggrey , Luke J Johnston , Martina S Elias , S Hasan Arshad , Peter Bager , Veronique Bataille , Helena Blakeway , Klaus Bonnelykke , Dorret Boomsma , Ben M Brumpton , Mariona Bustamante Pineda , Archie Campbell , John A Curtin , Anders Eliasen , João PS Fadista , Bjarke Feenstra , Trine Gerner , Carolina Medina Gomez , Sarah Grosche , Kristine B. Gutzkow , Anne-Sofie Halling , Caroline Hayward , John Henderson , Esther Herrera-Luis , John W Holloway , Joukejan Hottenga , Jonathan O’B Hourihane , Chen Hu , Kristian Hveem , Amaia Irizar , Benedicte Jacquemin , Leon Jessen , Sara Kress , Ramesh J Kurukulaaratchy , Susanne Lau , Sabrina Llop , Mari Løset , Ingo Marenholtz , Dan Mason , Daniel L McCartney , Mads Melbye , Erik Melén , Camelia Minica , Clare S Murray , Tamar Nijsten , Luba M Pardo , Suzanne Pasmans , Craig E Pennell , Maria R Rinnov , Gillian Santorelli , Tamara Schikowski , Darina Sheehan , Angela Simpson , Cilla Söderhäll , Laurent F Thomas , Jacob P Thyssen , Maties Torrent , Toos van Beijsterveldt , Alessia Visconti , Judith M. Vonk , Carol A Wang , Cheng-Jian Xu , Ali H Ziyab , UK Translational Research Network in Dermatology , BIOMAP consortium , Adnan Custovic , Paola Di Meglio , Liesbeth Duijts , Carsten Flohr , Alan D Irvine , Gerard H Koppelman , Young-Ae Lee , Nick J Reynolds , Catherine Smith , Sinéad M Langan , Lavinia Paternoster , Sara J Brown doi: https://doi.org/10.1101/2025.01.24.25321071 Marie Standl 1 Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health , Neuherberg, Germany 2 German Center for Child and Adolescent Health (DZKJ), partner site Munich , Munich, Germany Find this author on Google Scholar Find this author on PubMed Search for this author on this site Ashley Budu-Aggrey 3 MRC Integrative Epidemiology Unit , Bristol Medical School, University of Bristol, UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site Luke J Johnston 4 Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, Crewe Road South, University of Edinburgh , Edinburgh, UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site Martina S Elias 4 Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, Crewe Road South, University of Edinburgh , Edinburgh, UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site S Hasan Arshad 5 Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton , Southampton, UK 6 NIHR Southampton Biomedical Research Centre, University Hospitals Southampton NHS Foundation Trust , Southampton, UK 7 Asthma and Allergy Research Centre, Isle of Wight , UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site Peter Bager 8 Department of Epidemiology Research, Statens Serum Institute , Copenhagen, Denmark Find this author on Google Scholar Find this author on PubMed Search for this author on this site Veronique Bataille 9 Department of Twin Research and Genetic Epidemiology, King’s College London , London, UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site Helena Blakeway 3 MRC Integrative Epidemiology Unit , Bristol Medical School, University of Bristol, UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site Klaus Bonnelykke 10 COPSAC, Copenhagen Prospective Studies on Asthma in Childhood, Herlev and Gentofte Hospital, University of Copenhagen , Copenhagen, Denmark Find this author on Google Scholar Find this author on PubMed Search for this author on this site Dorret Boomsma 11 Vrije Universiteit, Department of Biological Psychology Van der Boechorststraat , Amsterdam, The Netherlands Find this author on Google Scholar Find this author on PubMed Search for this author on this site Ben M Brumpton 12 HUNT Center for Molecular and Clinical Epidemiology, Department of Public Health and Nursing, Norwegian University of Science and Technology , Trondheim, Norway Find this author on Google Scholar Find this author on PubMed Search for this author on this site Mariona Bustamante Pineda 13 ISGlobal, Institute for Global Health , Barcelona, Spain 14 Universitat Pompeu Fabra (UPF) , Barcelona, Spain 15 Spanish Consortium for Research on Epidemiology and Public Health (CIBERESP) , Madrid, Spain Find this author on Google Scholar Find this author on PubMed Search for this author on this site Archie Campbell 4 Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, Crewe Road South, University of Edinburgh , Edinburgh, UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site John A Curtin 16 Division 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, United Kingdom Find this author on Google Scholar Find this author on PubMed Search for this author on this site Anders Eliasen 10 COPSAC, Copenhagen Prospective Studies on Asthma in Childhood, Herlev and Gentofte Hospital, University of Copenhagen , Copenhagen, Denmark Find this author on Google Scholar Find this author on PubMed Search for this author on this site João PS Fadista 8 Department of Epidemiology Research, Statens Serum Institute , Copenhagen, Denmark Find this author on Google Scholar Find this author on PubMed Search for this author on this site Bjarke Feenstra 8 Department of Epidemiology Research, Statens Serum Institute , Copenhagen, Denmark Find this author on Google Scholar Find this author on PubMed Search for this author on this site Trine Gerner 17 Department of Dermatology and Allergy, Herlev and Gentofte Hospital, University of Copenhagen , Hellerup, Denmark Find this author on Google Scholar Find this author on PubMed Search for this author on this site Carolina Medina Gomez 18 Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, 3000 CA Rotterdam , The Netherlands Find this author on Google Scholar Find this author on PubMed Search for this author on this site Sarah Grosche 19 Max-Delbrück-Center (MDC) for Molecular Medicine , 13125, Berlin, Germany Find this author on Google Scholar Find this author on PubMed Search for this author on this site Kristine B. Gutzkow 20 Department of Air Quality and Noise, Division of Climate and Environmental Health, Norwegian Institute of Public Health (NIPH) , Oslo, Norway Find this author on Google Scholar Find this author on PubMed Search for this author on this site Anne-Sofie Halling 21 Department of Dermatology and Venereology, Bispebjerg Hospital, University of Copenhagen, Bispebjerg Bakke 23 , build. 4, 2400 Copenhagen N, Denmark Find this author on Google Scholar Find this author on PubMed Search for this author on this site Caroline Hayward 4 Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, Crewe Road South, University of Edinburgh , Edinburgh, UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site John Henderson 3 MRC Integrative Epidemiology Unit , Bristol Medical School, University of Bristol, UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site Esther Herrera-Luis 22 Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University , Baltimore, MD 21205, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site John W Holloway 6 NIHR Southampton Biomedical Research Centre, University Hospitals Southampton NHS Foundation Trust , Southampton, UK 23 Human Development and Health, Faculty of Medicine, University of Southampton , Southampton, UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site Joukejan Hottenga 11 Vrije Universiteit, Department of Biological Psychology Van der Boechorststraat , Amsterdam, The Netherlands Find this author on Google Scholar Find this author on PubMed Search for this author on this site Jonathan O’B Hourihane 24 Royal College of Surgeons in Ireland , Dublin, Ireland 25 Children’s Health Ireland , Dublin, Ireland 26 INFANT Centre, University College Cork , Cork, Ireland Find this author on Google Scholar Find this author on PubMed Search for this author on this site Chen Hu 27 The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam , Rotterdam, The Netherlands 28 Department of Dermatology, Erasmus MC, University Medical Center Rotterdam , Rotterdam, The Netherlands Find this author on Google Scholar Find this author on PubMed Search for this author on this site Kristian Hveem 12 HUNT Center for Molecular and Clinical Epidemiology, Department of Public Health and Nursing, Norwegian University of Science and Technology , Trondheim, Norway 29 Department for Research, St. Olavs hospital, Trondheim University Hospital , Trondheim, Norway Find this author on Google Scholar Find this author on PubMed Search for this author on this site Amaia Irizar 15 Spanish Consortium for Research on Epidemiology and Public Health (CIBERESP) , Madrid, Spain 30 Department of Preventive Medicine and Public health , UPV/EHU, Spain 31 Biogipuzkoa HRI , Donostia, Spain Find this author on Google Scholar Find this author on PubMed Search for this author on this site Benedicte Jacquemin 32 Univ Rennes, Inserm, EHESP, Irset (Institut de recherche en santé, environnement et travail) - UMR_S 1085, F-35000 Rennes , France Find this author on Google Scholar Find this author on PubMed Search for this author on this site Leon Jessen 10 COPSAC, Copenhagen Prospective Studies on Asthma in Childhood, Herlev and Gentofte Hospital, University of Copenhagen , Copenhagen, Denmark Find this author on Google Scholar Find this author on PubMed Search for this author on this site Sara Kress 33 IUF-Leibniz Research Institute for Environmental Medicine , Düsseldorf, Germany Find this author on Google Scholar Find this author on PubMed Search for this author on this site Ramesh J Kurukulaaratchy 5 Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton , Southampton, UK 6 NIHR Southampton Biomedical Research Centre, University Hospitals Southampton NHS Foundation Trust , Southampton, UK 7 Asthma and Allergy Research Centre, Isle of Wight , UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site Susanne Lau 34 Department of Pediatric Respiratory Medicine, Immunology, and Intensive Care Medicine, Charité-Universitätsmedizin Berlin , Berlin, Germany Find this author on Google Scholar Find this author on PubMed Search for this author on this site Sabrina Llop 15 Spanish Consortium for Research on Epidemiology and Public Health (CIBERESP) , Madrid, Spain 35 Epidemiology and Environmental Health Joint Research Unit, FISABIO-Universitat Jaume I–Universitat de València , Valencia, Spain Find this author on Google Scholar Find this author on PubMed Search for this author on this site Mari Løset 12 HUNT Center for Molecular and Clinical Epidemiology, Department of Public Health and Nursing, Norwegian University of Science and Technology , Trondheim, Norway 36 Department of Dermatology, Clinic of Orthopedy, Rheumatology and Dermatology, St. Olavs hospital, Trondheim University Hospital , Trondheim, Norway Find this author on Google Scholar Find this author on PubMed Search for this author on this site Ingo Marenholtz 19 Max-Delbrück-Center (MDC) for Molecular Medicine , 13125, Berlin, Germany 37 Clinic for Pediatric Allergy, Experimental and Clinical Research Center, Charité University Medical Center , Berlin, Germany Find this author on Google Scholar Find this author on PubMed Search for this author on this site Dan Mason 38 Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust, Bradford , England, BD9 6RJ, UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site Daniel L McCartney 4 Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, Crewe Road South, University of Edinburgh , Edinburgh, UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site Mads Melbye 39 Danish Cancer Institute, Copenhagen , Denmark 40 Department of Clinical Medicine, University of Copenhagen , Copenhagen, Denmark 41 Department of Pediatrics, Stanford University School of Medicine , Stanford, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Erik Melén 42 Department of Clinical Science and Education, Södersjukhuset, Karolinska Institutet , Stockholm, Sweden Find this author on Google Scholar Find this author on PubMed Search for this author on this site Camelia Minica 11 Vrije Universiteit, Department of Biological Psychology Van der Boechorststraat , Amsterdam, The Netherlands Find this author on Google Scholar Find this author on PubMed Search for this author on this site Clare S Murray 16 Division 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, United Kingdom Find this author on Google Scholar Find this author on PubMed Search for this author on this site Tamar Nijsten 28 Department of Dermatology, Erasmus MC, University Medical Center Rotterdam , Rotterdam, The Netherlands Find this author on Google Scholar Find this author on PubMed Search for this author on this site Luba M Pardo 28 Department of Dermatology, Erasmus MC, University Medical Center Rotterdam , Rotterdam, The Netherlands Find this author on Google Scholar Find this author on PubMed Search for this author on this site Suzanne Pasmans 28 Department of Dermatology, Erasmus MC, University Medical Center Rotterdam , Rotterdam, The Netherlands Find this author on Google Scholar Find this author on PubMed Search for this author on this site Craig E Pennell 43 School of Medicine and Public Health, The University of Newcastle, New South Wales , NSW 2308, Australia 44 Mothers and Babies Research Program, Hunter Medical Research Institute, New South Wales , NSW 2305, Australia Find this author on Google Scholar Find this author on PubMed Search for this author on this site Maria R Rinnov 17 Department of Dermatology and Allergy, Herlev and Gentofte Hospital, University of Copenhagen , Hellerup, Denmark 45 Department of Neonatology, Rigshospitalet, University of Copenhagen , Copenhagen, Denmark Find this author on Google Scholar Find this author on PubMed Search for this author on this site Gillian Santorelli 38 Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust, Bradford , England, BD9 6RJ, UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site Tamara Schikowski 33 IUF-Leibniz Research Institute for Environmental Medicine , Düsseldorf, Germany Find this author on Google Scholar Find this author on PubMed Search for this author on this site Darina Sheehan 26 INFANT Centre, University College Cork , Cork, Ireland 46 University College Cork , College Road, Cork, Ireland 47 Cork University Hospital , Wilton, Cork, Ireland Find this author on Google Scholar Find this author on PubMed Search for this author on this site Angela Simpson 16 Division 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, United Kingdom Find this author on Google Scholar Find this author on PubMed Search for this author on this site Cilla Söderhäll 48 Department of Women’s and Children’s Health, Karolinska Institutet , Stockholm, Sweden Find this author on Google Scholar Find this author on PubMed Search for this author on this site Laurent F Thomas 12 HUNT Center for Molecular and Clinical Epidemiology, Department of Public Health and Nursing, Norwegian University of Science and Technology , Trondheim, Norway 49 Department of Clinical and Molecular Medicine, Norwegian University of Science and Technology , Trondheim, Norway 50 BioCore - Bioinformatics Core Facility, Norwegian University of Science and Technology , Trondheim, Norway Find this author on Google Scholar Find this author on PubMed Search for this author on this site Jacob P Thyssen 21 Department of Dermatology and Venereology, Bispebjerg Hospital, University of Copenhagen, Bispebjerg Bakke 23 , build. 4, 2400 Copenhagen N, Denmark Find this author on Google Scholar Find this author on PubMed Search for this author on this site Maties Torrent 51 Area de Salut de Menorca, ib-salut , Balearic Islands, Spain Find this author on Google Scholar Find this author on PubMed Search for this author on this site Toos van Beijsterveldt 11 Vrije Universiteit, Department of Biological Psychology Van der Boechorststraat , Amsterdam, The Netherlands Find this author on Google Scholar Find this author on PubMed Search for this author on this site Alessia Visconti 9 Department of Twin Research and Genetic Epidemiology, King’s College London , London, UK 52 Center for Biostatistics, Epidemiology and Public Health, Department of Clinical and Biological Sciences, University of Turin , Turin, Italy Find this author on Google Scholar Find this author on PubMed Search for this author on this site Judith M. Vonk 53 University of Groningen, University Medical Center Groningen, Department of Epidemiology , Groningen, The Netherlands 54 University of Groningen, University Medical Center Groningen, Groningen Research Institute for Asthma and COPD (GRIAC) , Groningen, The Netherlands Find this author on Google Scholar Find this author on PubMed Search for this author on this site Carol A Wang 43 School of Medicine and Public Health, The University of Newcastle, New South Wales , NSW 2308, Australia 44 Mothers and Babies Research Program, Hunter Medical Research Institute, New South Wales , NSW 2305, Australia Find this author on Google Scholar Find this author on PubMed Search for this author on this site Cheng-Jian Xu 55 Centre for Individualised Infection Medicine (CiiM), a joint venture between the Helmholtz Centre for Infection Research (HZI) and Hannover Medical School (MHH) . Hannover, Germany 56 TWINCORE, a joint venture between the Helmholtz-Centre for Infection Research (HZI) and the Hannover Medical School (MHH) , Hannover, Germany Find this author on Google Scholar Find this author on PubMed Search for this author on this site Ali H Ziyab 57 Department of Community Medicine and Behavioral Sciences, College of Medicine, Kuwait University , Kuwait Find this author on Google Scholar Find this author on PubMed Search for this author on this site Adnan Custovic 58 National Heart and Lung Institute , Imperial College London, UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site Paola Di Meglio 59 The Francis Crick Institute , London, UK 60 St John’s Institute of Dermatology, School of Basic & Medical Biosciences , King’s College London Find this author on Google Scholar Find this author on PubMed Search for this author on this site Liesbeth Duijts 61 Department of Pediatrics, divisions of Respiratory Medicine and Allergology, and Neonatology, Erasmus MC, University Medical Center Rotterdam , Rotterdam, The Netherlands 62 Department of Neonatal and Intensive Care, division of Neonatology, Erasmus MC, University Medical Center Rotterdam , Rotterdam, The Netherlands Find this author on Google Scholar Find this author on PubMed Search for this author on this site Carsten Flohr 63 Department of Paediatric Dermatology, St John’s Institute of Dermatology, Guy’s and St Thomas’ NHS Foundation Trust and King’s College London , London, UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site Alan D Irvine 64 Department of Clinical Medicine, Trinity College Dublin , Dublin, Ireland Find this author on Google Scholar Find this author on PubMed Search for this author on this site Gerard H Koppelman 54 University of Groningen, University Medical Center Groningen, Groningen Research Institute for Asthma and COPD (GRIAC) , Groningen, The Netherlands 65 University of Groningen, University Medical Center Groningen, Beatrix Children’s Hospital, Department of Pediatric Pulmonology and Pediatric Allergology , Groningen, The Netherlands Find this author on Google Scholar Find this author on PubMed Search for this author on this site Young-Ae Lee 19 Max-Delbrück-Center (MDC) for Molecular Medicine , 13125, Berlin, Germany 34 Department of Pediatric Respiratory Medicine, Immunology, and Intensive Care Medicine, Charité-Universitätsmedizin Berlin , Berlin, Germany 37 Clinic for Pediatric Allergy, Experimental and Clinical Research Center, Charité University Medical Center , Berlin, Germany Find this author on Google Scholar Find this author on PubMed Search for this author on this site Nick J Reynolds 66 Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University , Newcastle upon Tyne, UK 67 Department of Dermatology and NIHR Newcastle Biomedical Research Centre, Newcastle upon Tyne Hospitals NHS Foundation Trust , Newcastle upon Tyne, UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site Catherine Smith 60 St John’s Institute of Dermatology, School of Basic & Medical Biosciences , King’s College London Find this author on Google Scholar Find this author on PubMed Search for this author on this site Sinéad M Langan 68 Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine , London, UK 69 St John’s Institute of Dermatology, Guy’s and St Thomas’ NHS Foundation Trust , London, UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site Lavinia Paternoster 3 MRC Integrative Epidemiology Unit , Bristol Medical School, University of Bristol, UK 70 NIHR Bristol Biomedical Research Centre, University Hospital Bristol and Weston NHS Foundation Trust and University of Bristol , Bristol, UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site Sara J Brown 4 Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, Crewe Road South, University of Edinburgh , Edinburgh, UK 71 Department of Dermatology, NHS Lothian, Lauriston Building, Edinburgh , Scotland, UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site For correspondence: sara.brown{at}ed.ac.uk Abstract Full Text Info/History Metrics Supplementary material Data/Code Preview PDF Abstract Background Environmental factors play a role in the pathogenesis of complex traits including atopic eczema (AE) and a greater understanding of gene-environment interactions (G*E) is needed to define pathomechanisms for disease prevention. 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 modelling to independently assess findings. Results The discovery analysis showed suggestive evidence for interaction (p<0.05) between 7 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 (maxN=25,339). In replication analysis (maxN=252,040) dog exposure*rs10214237 (on chromosome 5p13.2 near IL7R ) was nominally significant (OR interaction =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 interaction =0.84[0.75-0.94] P=0.003), but replication analysis was under-powered OR interaction =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. Conclusions Interaction analysis and functional assessment provide 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 that only weak effects are likely to occur. 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 which 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 in allergy epidemiology and identified a relative 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 there are 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 and loss-of-function variants in FLG encoding the skin barrier protein filaggrin have been implicated [ 10 ]. Knowledge of genetic risk may therefore 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 eczema risk loci defined by genome-wide association studies [ 11 ] and environmental risk factors selected based on previous literature [ 7 , 10 ] and importance to patients and carers [ 12 ]. We used early-life environmental exposures ( in utero and up to the first 12 months of life) to minimise reverse causation and focus on disease pathogenesis. G*E was tested in cohorts and data from European populations, in discovery and replication phases as a pragmatic approach to maximise sample size. Mechanistic assessment was carried out in vitro in a skin keratinocyte model to validate the observed interactions. Results Analysis was conducted to assess observational association (of environmental effects) followed by 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. Discovery analysis In meta-analyses of between 1,084 and 22,263 participants (dependent on exposure, Additional file 1 ) we found strong evidence for antibiotic use increasing risk of AE ( in utero p=0.004, at 6 months p=0.001 and at 12 months p=6×10 -4 ); weaker evidence was found for a protective effect of dog ownership (p=0.03), protective effect of childhood smoke exposure (p=0.038) and risk effect of NO 2 levels (p=0.035) (M1 models, Additional file 2 ). Little evidence (p>0.05) was found for main 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, Additional file 2 ). Of the 432 interactions tested (between 24 genetic variants and 18 environmental exposures), we found no significant interactions that passed multiple testing correction, yet 14 nominally significant (p int 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 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 ( Additional file 2 ). 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. Download figure Open in new tab 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 was not pursued further. View this table: View inline View popup Download powerpoint Table 1. Nominally significant interaction results from discovery and replication analyses Reults of testing for interaction between 24 genetic variants and 18 environmental exposures; *combined null genotype for 2 or more loss-of-function mutations in FLG as detailed in cohort descriptions (Additional file 6); nominal significance defined as unadjusted p int <0.05. N, number; OR, odds ratio; p-value indicates significance from fixed effects meta-analysis; p-value random indicates significance from random effects meta-analysis; p-value combined indicates significance from combined fixed effects meta-analysis of discovery and replication data. Sensitivity analyses, additionally adjusting for family history of AE and socioeconomic status, broadly supported the results of the main analyses ( Additional file 2 ), but many of the sensitivity analyses are 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. Replication analysis We took the 14 interactions with nominal evidence forward to replication, but also the exposures that had prior literature suggesting an interaction with FLG null variants (cat, siblings and breast-feeding [ 10 ]). In total, 19 interactions based on 8 different exposures and 10 genetic variants were included in the replication. In replication analysis dog exposure and rs10214237 showed evidence for interaction (p=0.025), Table 1 . In an analysis stratified by dog exposure the T allele increases risk of atopic eczema (OR=1.14, 95% CI 1.08 to 1.22), but only amongst those who are not exposed to a dog in the family home. In individuals who are exposed to dog in early life, this variant appears to have little effect (OR=0.98, 95% CI 0.68-1.11 Figure 2 ). Download figure Open in new tab Figure 2. Forest plot showing interaction of dog exposure with rs10214237 in exposed and unexposed 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 rs10214237 increases 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 Additional file 6. Availability of environmental data for replication varied, with many of our attempted replications of interactions being insufficiently powered to be conclusive. Washing practices (0-2y) and antibiotic use in utero interactions had only 3 and 4% power respectively (given the interaction effects observed in the discovery phase, Additional file 3 ). The tobacco exposure in utero interaction only reached 11% power and the four sibling interactions had between 8 and 37% power (dependent on variant). The breast-feeding duration interaction only had 4% power in the replication phase and so we extended the replication analysis to ‘ever breastfed’ to 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, Additional file 3 ). The previously reported interactions between FLG null mutations and cat, siblings and ever breastfed had 99% power given their reported interaction effects ( Additional file 3 ). In silico follow-up of rs10214237*dog interaction Rs10214237 is an intergenic variant (T>C) on chromosome 5p13.2; this was identified in association with eczema by a genome-wide association study (GWAS) [ 11 ] in which IL7R was prioritised as the likely causal gene based on evidence including eQTL colocalisation in macrophages and monocytes [ 13 , 14 ]. The top single nucleotide variant (SNV) at this locus in more recent 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 difference 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 06 Feb and 27 Nov 2024). Open Targets V2G analyses confirm IL7R as most likely gene affected by this SNV based on pQTL, sQTL and eQTL (06 Feb and 27 Nov 2024). GTEx data show that expression of IL7R is higher with T:T genotype in whole blood and cultured fibroblasts and in 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 ( Additional file 4 ). Single cell data from the Human Protein Atlas [ 15 , 16 ] confirms that IL-7R is expressed at protein level in human keratinocytes, in addition to circulating immune cells. In vitro testing of the effects of dog allergen on human keratinocytes 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 standardised reagent used for allergy testing in the clinic [ 17 ]. 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 [ 18 ]. To test the keratinocyte response more broadly, we used an ELISA panel of 64 cytokine, chemokines and receptors ( Additional file 5 ). This confirmed the signature of increased IL-10 signalling ( Additional file 5 ). Download figure Open in new tab Figure 3. In vitro testing of the effects of dog allergen on primary human keratinocytes (3A) 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, Dunnet post hoc test compared to negative control, **p<0.01, ***p<0.001 ****p<0.0001. (3B) IL-10 signalling was the most significantly enriched Reactome pathway (4 out of 45 genes/proteins, FDR 7.71e-08). (3C-3E) Effects of IL-7 and dog allergen stimulation on primary human keratinocytes with different rs10214237 genotypes in which T is eczema risk allele; graphs represent the mean fold change in cytokine mRNA expression relative to the housekeeping gene EF1A, from 4 keratinocyte isolates with T:T genotype and 2 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. 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 T:T genotype (homozygous for the eczema-risk allele) showed a greater response than the C:C genotype. Together 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 which suppresses eczema to a greater extent in T:T than C:C individuals. Discussion Our collaborative work represents the largest and most comprehensive analysis to date investigating G*E in atopic eczema, using a systematic approach focussed on the most significant genetic loci and selected environmental factors. We first meta-analysed 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 atopic eczema. 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 [ 19 ]. Some authors have even stated that ‘atopic eczema is an environmental disease’ [ 20 ]. Our meta-analysis of observational associations provides evidence that early-life exposure to antibiotics and NO 2 levels associate with 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. Statistical interaction analysis indicates that early-life dog exposure may modify the genetic effect of rs10214237. Functional 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 population as a whole and in the sub-population without dog exposure ( Figure 2 ) consistent with the T:T genotype showing greater IL7R mRNA expression ( Additional file 4 ). The IL-7 receptor is a heterodimer composed of IL7R-alpha and IL2R-gamma. It is expressed is 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 this cell type [ 21 ]. Our detailed in vitro work focussed 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 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 [ 22 , 23 ]) and upregulation of a network of genes encoding chemokines and cytokines of IL-10 signalling (Reactome pathway HAS-6783783), contributing to the suppression of atopic inflammation [ 18 ]. This is consistent with observational epidemiology showing an apparent protective effect of dog exposure early in life [ 24 ] [ 25 ]. 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 status. Here the T:T genotype showed a greater increase in IL-10 signalling in response to dog allergen exposure than the C:C genotype, which is consistent with the suppression of atopic eczema risk on a population level in the dog-exposed T:T individuals, whilst non-dog-exposed T:T individuals remain at risk of disease. The interaction is analogous to a 17q21*dog interaction demonstrated in asthma [ 26 ] in which the risk of persistent wheeze is attenuated by dog ownership [ 26 ]. There is an interesting parallel in the interaction of rs10214237 with exposure to older siblings, in which the older sibling abrogates risk effect for rs10214237. We speculate that this may be related to the increased microbial exposure experienced by an infant with older siblings (or a dog) in the household, and there is evidence of shared skin and gut microbiome between humans and their pets[ 27 ], but it could also reflect lifestyle choices of dog-owning families and these hypotheses require further testing. There are some limitations to this work. The discovery analysis used selected SNVs to represent known eczema risk loci, rather than conducting a genome-wide interaction analysis. This restricted approach has been shown to be effective in other traits [ 28 ]; it is needed because of power constraints, even in large population datasets. A post-hoc estimation of statistical power ( Additional file 3 ) showed that our replication sample sizes were insufficient for some interactions. Therefore, where replication results do not meet our pre-specified significance threshold it is not possible to definitively exclude an interaction, but we report the interaction effect sizes for which we had good statistical power, to demonstrate the magnitude of interactions which are unlikely to exist, given our null results ( Additional file 3 ). 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 used here become available. 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 population genetic studies of sufficient size to carry out these analyses. The observed differences in allele frequency of rs10214237 in African compared to European and South Asian populations illustrates the limited transferability of this variant effect across population, although other population-specific variants in the same locus may contribute to similar mechanistic effects. International efforts are on-going to address this limitation [ 29 ], 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. In our previous systematic review focusing on gene-environment interactions with FLG null mutations [ 10 ] we found some published evidence for FLG *environment interactions with exposures including early-life cat ownership, older siblings, water hardness, phthalate exposure, and prolonged breastfeeding from the small number of previous studies. The lack of replication of FLG *cat ownership interaction in the large well-powered study reported here, and another recent meta-analysis [ 30 ] represents an interesting null finding, contrasting with two small birth cohort studies ([ 31 , 32 ] n=379 and n=503) which reported p values for interaction <0.01 with evidence for increased risks of atopic eczema in those with FLG null mutations exposed to cat in early life. Evidence for these G*E interactions came from small numbers of individuals with FLG mutation, cat exposure and development of atopic eczema (five people in one study [ 31 ]). We had very good power (99%) for the interaction magnitude previously reported (OR int =11[ 31 ]) and 80% for an interaction as small as OR int =1.26, suggesting very little evidence in our data for this interaction. We found little evidence for FLG *breastfeeding, consistent with our systematic review [ 10 ], where studies reported no evidence for interactions with breastfeeding, although an FLG *breastfeeding duration interaction was reported from the Isle of Wight cohort [ 33 ]. Here, our post-hoc power calculation ( Additional file 3 ) showed adequate power (99%) for the FLG *breastfed-ever interaction, but low power (<1%) for FLG *breastfeeding duration analyses, which may explain the discrepancy. Conclusions We report observational evidence for an association of atopic eczema with exposure to antibiotics, NO 2 , and tobacco smoke in early life, but the precise nature and mechanisms of action of these environmental factors on atopic skin inflammation remain unclear. We also detected an observational association between early life dog exposure and reduction in prevalence of atopic eczema. Further interaction analysis and functional assessments have provided 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 possible to model in vitro . The lack of statistical evidence for other G*E explored in this analysis suggests that only weak interactions 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. Therefore further, larger longitudinal studies should focus on alternative mechanistic questions. Methods Aim This work aimed to investigate evidence of interaction between 24 genetic risk loci for atopic eczema and 18 early-life environmental effects. Study design and setting Genetic risk loci were defined by the 24 top hits at each locus from genome-wide association analysis [ 11 , 13 ] and coded for the risk-increasing allele as effect allele ( Additional file 8 ). 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 , 34 ]). Environmental exposures were selected on the basis of our recently published literature review [ 10 ], interest from representative of a national eczema support group [ 12 ] and refined for pragmatic reasons, based on data availability. Genetic epidemiology and interaction analysis was used for discovery and replication. In vitro modelling was performed to independently assess the one G*E effect that showed a nominally significant interaction in the discovery and replication analyses. Characteristics of participants Cohort descriptions The discovery analysis included 16 population-based cohorts from people of European ancestry (N = 25,339) and a further 10 European population-based cohorts were included in the replication stage (N = 254,532), giving a maximum total of 279,871 (maxN) in the final meta-analysis ( Additional file 1A and 1B ). Disease status was determined by either parental report or doctor diagnosis for those who had “ever had eczema”. Further details on the phenotype definitions for the included studies can be found in Additional file 6 . Keratinocyte culture and gene expression Primary human keratinocytes were isolated from normal human skin samples excised during routine surgical procedures, with patient consent, under governance of the Lothian Bioresource (reference SR1665). Samples were genotyped for rs10214237 using KASP TM (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. RNA was isolated with TRIzol (15596026, Invitrogen, Carlsbad, USA) and spin filtration columns using Direct-zol (R2072, Zymo, Irvine, USA). cDNA was prepared using 200ng/ml random primers (48190011, Invitrogen, Carlsbad, USA) with reverse transcriptase using SuperScript IV (18090050, Invitrogen, Carlsbad, USA). qPCR was carried out using exon-spanning probes ( IL7R : HS00902334_m1, Thermo, Waltham, USA) and ( EF1A : HS.PT.58.24345862, Integrated DNA Technologies, San Diego, USA) with TaqMan Universal Master Mix II (4440040, Thermo, Waltham, USA) and run on a CFX384 PCR Detection System (Bio-Rad, Hercules, USA) using cycling conditions: 95°C for 10 mins, 40 cycles of [95°C for 15 secs, 60°C for 1 min]. Fold changes in gene expression were derived via the 2(-Delta Delta C[T]) method, using EF1A as the reference gene. In vitro analysis for rs10214237*dog interaction To investigate the effect of dog allergen on human keratinocytes, monolayers were treated for 8h with 10ug/ml dog allergen (Can f 1, catalogue E802, Immunotek, Madrid, Spain). RNA isolation and RT-qPCR were carried out as above ( CXCL8 : Hs.PT.58.38869678.g, CSF2 : Hs.PT.58.20138984, CCL2 : Hs.PT.58.45467977, TNF : Hs.PT.58.45380900, IL33 : Hs.PT.58.21416460, EF1A : HS.PT.58.24345862, Integrated DNA Technologies, San Diego, USA) and ( TSLP : Hs00263639_m1, Thermo, Waltham, USA). Experiments were replicated using keratinocytes from 5-12 independent donors. To investigate a genotype-specific effect of IL-7 and/or dog allergen stimulation, keratinocytes were grown to confluency and treated with 100ng/ml recombinant human IL-7 (rhIL-7) (BioTechne, Minneapolis, USA, catalogue: 207-IL) and 500ng/ml Dog dander (Lofarma, Milan, Italy) for 8 hours. The carrier solution for dog dander (Lofarma) or 0.002% BSA, used as a carrier protein for rhIL-7 were negative controls and experiments were conducted in duplicate for each condition. One-way analysis of variance (ANOVA) with Dunnett’s post-hoc test for multiple comparisons was used to compare samples’ means and results displayed showing standard error of the mean (SEM). Gene ontology, network and pathway analyses were conducted using STRING v12.0. Statistical genetic analysis The early-life environmental exposures for investigation included pet ownership for cat and dog separately, house dust mite exposure, washing practices (to represent environmental irritants), cigarette tobacco smoking within the household, antibiotic use, environmental pollution, breast feeding mode of delivery and presence of older siblings. These are listed in Additional file 7 , with details of their definition and coding. The exposures were tested for interaction effects with 24 SNPs previously reported for eczema risk [ 11 , 35 ] ( Additional file 8 ). This involved fitting a statistical model to include the main effect of the SNP upon eczema (G) (extracted from Paternoster et al, 2015[ 11 ]), the main effect of the environmental factors upon eczema (E), and the product of the SNP effect and the environmental effect (G*E). Logistic regression models were applied to identify the main effect of each environmental factor (models M1 to M4, Additional file 9 ), and to test for interaction between the exposure and each SNP while adjusting for sex (models I1 to I3, Additional file 9 ). Sensitivity analyses were also performed while adjusting for family history of atopic disease (asthma, eczema or hay fever) and parental education as a proxy for socioeconomic status (models S1 to S3, Additional file 9 ). Analyses were performed separately within each cohort and then combined by performing fixed-effects meta-analyses. Genetic data was imputed separately for each cohort. Further imputation details can be found in the Additional file 6 . 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 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) ( Additional file 3 ). Data Availability All data produced in the present study are available upon reasonable request to the authors Declarations Ethics approval and consent to participate Each contributing cohort has ethical approval for the sharing of anonymised data from study participants, with their written informed consent. Consent for publication The named authors provide consent for publication of this work. Availability of data and materials All results supporting the conclusions of this article are included within manuscript and Additional files. Specifically, full results for all the models tested are given in Additional files 2 and 10 . Each cohort contributing to the analysis has their own controlled-access procedures and should be contacted directly to obtain access to individual level data. Competing interests SJB 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, European Lead Factory (which includes multiple industry partners). SJB, AB-A, KB, ADI, GHK, CS, SML and LP have received funding from the BIOMAP-IMI consortium (EU H2020 project ref No 821511) which receives support from several pharmaceutical industry partners. LP has received honorarium payment for a scientific talk on eczema genetics from LEO Pharma. GHK 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. 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). NJR’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 NJR is a NIHR Senior Investigator. LP 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_00032/01). SJB 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). EHL 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 Organization for Health Research and Development; the Netherlands Organization 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. Authors’ contributions AB-A, PB, KB, DB, SJB, MBP, ACu, CF, JHe, JWH, JO’BH, ADI, GK, PdM, SML, Y-AL, DM, EM, CSM, DMM, SP, LP, CP, NJR, AS, CS, MS, JPT and CW made substantial contributions to the conception or design of the work; all authors contributed to the acquisition, analysis, or interpretation of data; AB-A, SJB, ACu, LD, CF, ADI, GK, SML, Y-AL, LP, NJR, CS and MS drafted the work or substantively revised it. All authors have approved the submitted version and have agreed both to be personally accountable for the author’s own contributions and to ensure that questions related to the accuracy or integrity of any part of the work, even ones in which the author was not personally involved, are appropriately investigated, resolved, and the resolution documented in the literature. Authors’ information MS, AB-A, LP are experts in statistical genetic analysis of complex traits including AE; SML is a clinical academic dermatologist with epidemiology expertise; SJB is a clinical academic dermatologist with expertise in genetic epidemiology and functional genetics. NJR is a clinical academic dermatologist with expertise in immune mediated inflammatory skin disorders and precision medicine. List of additional Files Additional file 1. List of cohorts and available exposure data 1A. Included cohorts and exposure availability at discovery stage. 1B. Included cohorts and exposure availability at replication stage. Additional file 2. Full results of the discovery analysis Exposure, environmental exposure; N, number of individuals; N_studies, number of studies; OR_fixed, odds ratio from fixed effect meta-analysis; CI_fixed: 95%-confidence interval from fixed effect meta-analysis; p_fixed: p-value from fixed effect meta-analysis; OR_random: odds ratio from random effects meta-analysis; CI_random: 95%-confidence interval from random effects meta-analysis; p_random: p-value from random effects meta-analysis; p_heterogeneity: p-value from Q-statistic. Additional file 3. Estimation of statistical power Posthoc power calculations performed to facilitate interpretation of negative findings. Additional file 4. IL7R mRNA expression in cells of different rs10214237 genotype Rs10214237 T:T genotype is associated with higher expression level of IL7R mRNA than C:C genotype; 4A and 4B , Screenshots from GTEx Portal ( https://www.gtexportal.org/home/snp/rs10214237 accessed 14/04/2024) showing T:T genotype is associated with higher IL7R mRNA expression in cultured fibroblasts and whole blood; 4C , shows higher mRNA expression levels in primary human keratinocytes of T:T than C:C genotype. Additional file 5. Results of cytokine, chemokine and receptor expression on human primary keratinocytes following dog allergen exposure 5A. Protein detection by ELISA. 5B. STRING network analysis of upregulated genes. 5C. Cytokine expression from primary human keratinocytes. 5D. STRING network analysis of genes showing no significant change in expression. Additional file 6. Supplementary methods Additional file 7. Definition and coding of environmental exposures Additional file 8. Table of selected SNVs, risk alleles and risk allele frequencies Additional file 9. Logistic regression models on ever having atopic eczema Additional file 10. Full results of the replication analysis Exposure, environmental exposure; N, number of individuals; N_studies, number of studies; OR_fixed, odds ratio from fixed effect meta-analysis; CI_fixed, 95%-confidence interval from fixed effect meta-analysis; p_fixed, p-value from fixed effect meta-analysis; OR_random, odds ratio from random effects meta-analysis; CI_random, 95%-confidence interval from random effects meta-analysis; p_random, p-value from random effects meta-analysis; p_heterogeneity, p-value from Q-statistic. 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. Footnotes There was a typo in rs1041237, which was named three times in the results. The correct SNV is rs10214237. The co-author name Beneticte Jaquemin was mis-spelled (Jaquemi - corrected to Jaquemin). Abbreviations ANOVA Analysis of variance FLG Gene encoding filaggrin G*E Gene-environment interaction GWAS Genome-wide association study maxN Maximum number of individuals in the analysis OR Odds ratio SEM Standard error of mean SNV Single nucleotide variant TSLP Thymic stromal lymphopoietin References 1. ↵ Johansson S , Bieber T , Dahl R , Friedmann P , Lanier B , Lockey R , Motala C , Ortega Martell J , Platts-Mills T , Ring J , et al. Revised nomenclature for allergy for global use: Report of the Nomenclature Review Committee of the World Allergy Organization, October 2003 . J Allergy Clin Immunol 2004 , 113 : 832 – 836 . OpenUrl CrossRef PubMed Web of Science 2. ↵ Mehrmal S , Uppal P , Giesey RL , Delost GR : Identifying the prevalence and disability-adjusted life years of the most common dermatoses worldwide . J Am Acad Dermatol 2020 , 82 : 258 – 259 . OpenUrl PubMed 3. ↵ Urban K , Chu S , Giesey RL , Mehrmal S , Uppal P , Nedley N , Delost GR : 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 Int 2021 , 2 : 12 – 18 . OpenUrl PubMed 4. ↵ Langan SM , Irvine AD , Weidinger S : Atopic dermatitis . Lancet 2020 , 396 : 345 – 360 . OpenUrl PubMed 5. ↵ Odhiambo JA , Williams HC , Clayton TO , Robertson CF , Asher MI , Group IPTS : Global variations in prevalence of eczema symptoms in children from ISAAC Phase Three . J Allergy Clin Immunol 2009 , 124 : 1251 – 1258 e1223. OpenUrl CrossRef PubMed 6. ↵ Genuneit J , Seibold AM , Apfelbacher CJ , Konstantinou GN , Koplin JJ , La Grutta S , Logan K , Perkin MR , Flohr C , Task Force ‘Overview of Systematic Reviews in Allergy Epidemiology’ of the EIGoE: Overview of systematic reviews in allergy epidemiology . Allergy 2017 , 72 : 849 – 856 . OpenUrl PubMed 7. ↵ Rutter CE , Silverwood RJ , Williams HC , Ellwood P , Asher I , Garcia-Marcos L , Strachan DP , Pearce N , Langan SM , Group IPTS : Are Environmental Factors for Atopic Eczema in ISAAC Phase Three due to Reverse Causation? J Invest Dermatol 2018 . 8. ↵ Brown SJ : What Have We Learned from GWAS for Atopic Dermatitis? J Invest Dermatol 2021 , 141 : 19 – 22 . OpenUrl CrossRef PubMed 9. ↵ Ottman R : Gene-environment interaction: definitions and study designs . Prev Med 1996 , 25 : 764 – 770 . OpenUrl CrossRef PubMed Web of Science 10. ↵ Blakeway H , Van-de-Velde V , Allen VB , Kravvas G , Palla L , Page MJ , Flohr C , Weller RB , Irvine AD , McPherson T , et al : What is the evidence for interactions between filaggrin null mutations and environmental exposures in the aetiology of atopic dermatitis? - A systematic review . Br J Dermatol 2019 . 11. ↵ Paternoster L , Standl M , Waage J , Baurecht H , Hotze M , Strachan DP , Curtin JA , Bonnelykke K , Tian C , Takahashi A , et al : Multi-ancestry genome-wide association study of 21,000 cases and 95,000 controls identifies new risk loci for atopic dermatitis . Nat Genet 2015 , 47 : 1449 – 1456 . OpenUrl CrossRef PubMed 12. ↵ Brown SJ : Discussion with Eczema Outreach Scotand 2018 . 13. ↵ Budu-Aggrey A , Kilanowski A : European and multi-ancestry genome-wide association meta-analysis of atopic dermatitis highlights importance of systemic immune regulation . Nat Commun 2023 , in press. 14. ↵ Sobczyk MK , Richardson TG , Zuber V , Min JL , Gaunt TR , Paternoster L , eQtlgen Consortium BCG : Triangulating Molecular Evidence to Prioritize Candidate Causal Genes at Established Atopic Dermatitis Loci . J Invest Dermatol 2021 , 141 : 2620 – 2629 . OpenUrl CrossRef PubMed 15. ↵ Thul PJ , Akesson L , Wiking M , Mahdessian D , Geladaki A , Ait Blal H , Alm T , Asplund A , Bjork L , Breckels LM , et al : A subcellular map of the human proteome . Science 2017 , 356 . 16. ↵ Human Protein Atlas available from http://www.proteinatlas.org 17. ↵ Patel G , Saltoun C : Skin testing in allergy . Allergy Asthma Proc 2019 , 40 : 366 – 368 . OpenUrl PubMed 18. ↵ Boyman O , Werfel T , Akdis CA : The suppressive role of IL-10 in contact and atopic dermatitis . J Allergy Clin Immunol 2012 , 129 : 160 – 161 . OpenUrl PubMed 19. ↵ Hidaka T , Ogawa E , Kobayashi EH , Suzuki T , Funayama R , Nagashima T , Fujimura T , Aiba S , Nakayama K , Okuyama R , Yamamoto M : The aryl hydrocarbon receptor AhR links atopic dermatitis and air pollution via induction of the neurotrophic factor artemin . Nat Immunol 2017 , 18 : 64 – 73 . OpenUrl CrossRef PubMed 20. ↵ Luschkova D , Zeiser K , Ludwig A , Traidl-Hoffmann C : Atopic eczema is an environmental disease . Allergol Select 2021 , 5 : 244 – 250 . OpenUrl PubMed 21. ↵ Zhong W , Wu X , Zhang W , Zhang J , Chen X , Chen S , Huang H , Yang Y , Yu B , Dou X : Aberrant Expression of Histamine-independent Pruritogenic Mediators in Keratinocytes may be Involved in the Pathogenesis of Prurigo Nodularis . Acta Derm Venereol 2019 , 99 : 579 – 586 . OpenUrl PubMed 22. ↵ Ebina-Shibuya R , Leonard WJ : Role of thymic stromal lymphopoietin in allergy and beyond . Nat Rev Immunol 2023 , 23 : 24 – 37 . OpenUrl CrossRef PubMed 23. ↵ Liew FY , Girard JP , Turnquist HR : Interleukin-33 in health and disease . Nat Rev Immunol 2016 , 16 : 676 – 689 . OpenUrl CrossRef PubMed 24. ↵ Thorsteinsdottir S , Thyssen JP , Stokholm J , Vissing NH , Waage J , Bisgaard H : Domestic dog exposure at birth reduces the incidence of atopic dermatitis . Allergy 2016 , 71 : 1736 – 1744 . OpenUrl PubMed 25. ↵ Eapen AA , Sitarik AR , Cheema G , Kim H , Ownby D , Johnson CC , Zoratti E : Effect of prenatal dog exposure on eczema development in early and late childhood . J Allergy Clin Immunol Pract 2022 , 10 : 3312 – 3314 e3311. OpenUrl PubMed 26. ↵ Tutino M , Granell R , Curtin JA , Haider S , Fontanella S , Murray CS , Roberts G , Arshad SH , Turner S , Morris AP , et al : Dog ownership in infancy is protective for persistent wheeze in 17q21 asthma-risk carriers . J Allergy Clin Immunol 2023 , 151 : 423 – 430 . OpenUrl CrossRef 27. ↵ Lehtimaki J , Sinkko H , Hielm-Bjorkman A , Laatikainen T , Ruokolainen L , Lohi H : Simultaneous allergic traits in dogs and their owners are associated with living environment, lifestyle and microbial exposures . Sci Rep 2020 , 10 : 21954 . 28. ↵ Shungin D , Deng WQ , Varga TV , Luan J , Mihailov E , Metspalu A , Consortium G , Morris AP , Forouhi NG , Lindgren C , et al : Ranking and characterization of established BMI and lipid associated loci as candidates for gene-environment interactions . PLoS Genet 2017 , 13 : e1006812 . OpenUrl CrossRef PubMed 29. ↵ Borrell LN , Elhawary JR , Fuentes-Afflick E , Witonsky J , Bhakta N , Wu AHB , Bibbins-Domingo K , Rodriguez-Santana JR , Lenoir MA , Gavin JR , 3rd . , et al : Race and Genetic Ancestry in Medicine - A Time for Reckoning with Racism . N Engl J Med 2021 , 384 : 474 – 480 . OpenUrl CrossRef PubMed 30. ↵ Thyssen JP , Ahluwalia TS , Paternoster L , Ballardini N , Bergstrom A , Melen E , Chawes BL , Stokholm J , Hourihane JO , O’Sullivan DM , et al : Interaction between filaggrin mutations and neonatal cat exposure in atopic dermatitis . Allergy 2020 , 75 : 1481 – 1485 . OpenUrl PubMed 31. ↵ Bisgaard H , Simpson A , Palmer CN , Bonnelykke K , McLean I , Mukhopadhyay S , Pipper CB , Halkjaer LB , Lipworth B , Hankinson J , et al : Gene-environment interaction in the onset of eczema in infancy: filaggrin loss-of-function mutations enhanced by neonatal cat exposure . PLoS Med 2008 , 5 : e131 . OpenUrl CrossRef PubMed 32. ↵ Schuttelaar ML , Kerkhof M , Jonkman MF , Koppelman GH , Brunekreef B , de Jongste JC , Wijga A , McLean WH , Postma DS : Filaggrin mutations in the onset of eczema, sensitization, asthma, hay fever and the interaction with cat exposure . Allergy 2009 , 64 : 1758 – 1765 . OpenUrl CrossRef PubMed 33. ↵ Ziyab AH , Mukherjee N , Ewart S , Arshad SH , Karmaus W , Turati F , Bertuccio P , Galeone C , Pelucchi C , Naldi L , et al : Filaggrin gene loss-of-function variants modify the effect of breast-feeding on eczema risk in early childhood . Allergy 2016 , 71 : 1371 – 1373 . OpenUrl PubMed 34. ↵ Sandilands A , Terron-Kwiatkowski A , Hull P , O’Regan G , Clayton T , Watson R , Carrick T , Evans A , Liao H , Zhao Y , et al : Comprehensive analysis of the gene encoding filaggrin uncovers prevalent and rare mutations in ichthyosis vulgaris and atopic eczema . Nat Genet 2007 , 39 : 650 – 654 . OpenUrl CrossRef PubMed Web of Science 35. ↵ Budu-Aggrey A , Kilanowski A , Sobczyk MK , and Me Research T , Shringarpure SS , Mitchell R , Reis K , Reigo A , Estonian Biobank Research T , Magi R , et al : European and multi-ancestry genome-wide association meta-analysis of atopic dermatitis highlights importance of systemic immune regulation . Nat Commun 2023 , 14 : 6172 . OpenUrl CrossRef PubMed View the discussion thread. Back to top Previous Next Posted September 04, 2025. Download PDF Supplementary Material Data/Code Email Thank you for your interest in spreading the word about medRxiv. 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Share Gene-environment interaction analysis in atopic eczema: evidence from large population datasets and modelling in vitro Marie Standl , Ashley Budu-Aggrey , Luke J Johnston , Martina S Elias , S Hasan Arshad , Peter Bager , Veronique Bataille , Helena Blakeway , Klaus Bonnelykke , Dorret Boomsma , Ben M Brumpton , Mariona Bustamante Pineda , Archie Campbell , John A Curtin , Anders Eliasen , João PS Fadista , Bjarke Feenstra , Trine Gerner , Carolina Medina Gomez , Sarah Grosche , Kristine B. 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Vonk , Carol A Wang , Cheng-Jian Xu , Ali H Ziyab , UK Translational Research Network in Dermatology , BIOMAP consortium , Adnan Custovic , Paola Di Meglio , Liesbeth Duijts , Carsten Flohr , Alan D Irvine , Gerard H Koppelman , Young-Ae Lee , Nick J Reynolds , Catherine Smith , Sinéad M Langan , Lavinia Paternoster , Sara J Brown medRxiv 2025.01.24.25321071; doi: https://doi.org/10.1101/2025.01.24.25321071 Share This Article: Copy Citation Tools Gene-environment interaction analysis in atopic eczema: evidence from large population datasets and modelling in vitro Marie Standl , Ashley Budu-Aggrey , Luke J Johnston , Martina S Elias , S Hasan Arshad , Peter Bager , Veronique Bataille , Helena Blakeway , Klaus Bonnelykke , Dorret Boomsma , Ben M Brumpton , Mariona Bustamante Pineda , Archie Campbell , John A Curtin , Anders Eliasen , João PS Fadista , Bjarke Feenstra , Trine Gerner , Carolina Medina Gomez , Sarah Grosche , Kristine B. Gutzkow , Anne-Sofie Halling , Caroline Hayward , John Henderson , Esther Herrera-Luis , John W Holloway , Joukejan Hottenga , Jonathan O’B Hourihane , Chen Hu , Kristian Hveem , Amaia Irizar , Benedicte Jacquemin , Leon Jessen , Sara Kress , Ramesh J Kurukulaaratchy , Susanne Lau , Sabrina Llop , Mari Løset , Ingo Marenholtz , Dan Mason , Daniel L McCartney , Mads Melbye , Erik Melén , Camelia Minica , Clare S Murray , Tamar Nijsten , Luba M Pardo , Suzanne Pasmans , Craig E Pennell , Maria R Rinnov , Gillian Santorelli , Tamara Schikowski , Darina Sheehan , Angela Simpson , Cilla Söderhäll , Laurent F Thomas , Jacob P Thyssen , Maties Torrent , Toos van Beijsterveldt , Alessia Visconti , Judith M. 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