Novel childhood asthma genes interact with in utero and early-life tobacco smoke exposure

Salome Scholtens; Dirkje S Postma; Miriam F Moffatt; Sviatlana Panasevich; Raquel Granell; A John Henderson; Erik Melén; Fredrik Nyberg; Göran Pershagen; Deborah Jarvis; Adaikalavan Ramasamy; Matthias Wjst; Cecilie Svanes; Emmanuelle Bouzigon; Florence Demenais; Francine Kauffmann; Valérie Siroux; Erika von Mutius; Markus Johannes Ege; Charlotte Braun-Fahrländer; Jon Genuneit; GABRIELA study group; Bert Brunekreef; Henriette A Smit; Alet H Wijga; Marjan Kerkhof; Ivan Curjuric; Medea Imboden; Gian A Thun; Nicole Probst-Hensch; Maxim B Freidin; Elena Iu Bragina; IA Deev; VP Puzyrev; Denise Daley; Julie Park; Allan Becker; Moira Chan-Yeung; Anita L Kozyrskyj; Peter Pare; Ingo Marenholz; Susanne Lau; Thomas Keil; Young-Ae Lee; Michael Kabesch; Cisca Wijmenga; Lude Franke; Ilja M Nolte; Judith Vonk; Ashish Kumar; Martin Farrall; William OCM Cookson; David P Strachan; Gerard H Koppelman; H Marike Boezen

doi:10.1016/j.jaci.2013.08.049

. 2014 Mar;133(3):885–888. doi: 10.1016/j.jaci.2013.08.049

Novel childhood asthma genes interact with in utero and early-life tobacco smoke exposure^☆

Salome Scholtens ^a,^b, Dirkje S Postma ^b,^c, Miriam F Moffatt ^d, Sviatlana Panasevich ^e, Raquel Granell ^f, A John Henderson ^f, Erik Melén ^e,^g, Fredrik Nyberg ^e,^h, Göran Pershagen ^e, Deborah Jarvis ⁱ, Adaikalavan Ramasamy ⁱ, Matthias Wjst ^j,^k, Cecilie Svanes ^l, Emmanuelle Bouzigon ^m,^n,^o, Florence Demenais ^m,^n,^o, Francine Kauffmann ^p,^q, Valérie Siroux ^r,^s, Erika von Mutius ^t, Markus Johannes Ege ^t, Charlotte Braun-Fahrländer ^u,^v, Jon Genuneit ^w; GABRIELA study group, Bert Brunekreef ^x,^y, Henriette A Smit ^y,^z, Alet H Wijga ^z, Marjan Kerkhof ^a,^b, Ivan Curjuric ^u,^v, Medea Imboden ^u,^v, Gian A Thun ^u,^v, Nicole Probst-Hensch ^u,^v, Maxim B Freidin ^aa, Elena Iu Bragina ^aa, IA Deev ^bb, VP Puzyrev ^aa,^bb, Denise Daley ^cc, Julie Park ^cc, Allan Becker ^dd, Moira Chan-Yeung ^ee, Anita L Kozyrskyj ^ff, Peter Pare ^cc, Ingo Marenholz ^gg,^hh, Susanne Lau ⁱⁱ, Thomas Keil ^jj, Young-Ae Lee ^gg,^hh, Michael Kabesch ^kk, Cisca Wijmenga ^ll, Lude Franke ^ll, Ilja M Nolte ^a, Judith Vonk ^a, Ashish Kumar ^u,^v,^mm, Martin Farrall ^mm, William OCM Cookson ^d, David P Strachan ⁿⁿ, Gerard H Koppelman ^b,^oo, H Marike Boezen ^a,^b

^aDepartment of Epidemiology, University of Groningen, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands

^bGroningen Research Institute for Asthma and COPD (GRIAC), University of Groningen, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands

^cDepartment of Pulmonology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands

^dDivision of Respiratory Sciences, Imperial College, London, United Kingdom

ⁱRespiratory Epidemiology and Public Health, Imperial College, London, United Kingdom

^eInstitute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden

^fALSPAC, School of Social and Community Medicine, University of Bristol, Bristol, United Kingdom

^gSachs' Children's Hospital, Stockholm, Sweden

^hGlobal Epidemiology, AstraZeneca R&D, Mölndal, Sweden

^jInstitute of Medical Statistics and Epidemiology (IMSE), Klinikum Rechts der Isar, Technical University, Munich, Germany

^kComprehensive Pneumology Center (CPC), Institute of Lung Biology and Disease (iLBD), Helmholtz Center Munich, Neuherberg, Germany

^lBergen Respiratory Research Group, Institute of Medicine, University of Bergen and Department of Occupational Medicine, Haukeland University Hospital Bergen, Bergen, Norway

^mInserm U946, Genetic Variation and Human Diseases Unit, Paris, France

ⁿUniversité Paris Diderot, Sorbonne Paris Cité, Institut Universitaire d'Hématologie, Paris, France

^oFondation Jean Dausset, Centre d'Etude du Polymorphisme Humain (CEPH), Paris, France

^pInserm U1018, CESP Centre for research in Epidemiology and Population Health, Respiratory and environmental epidemiology Team, Villejuif, France

^qUniversité Paris Sud, UMRS 1018, Villejuif, France

^rInserm U823, Centre de Recherche Albert Bonniot, La Tronche, France

^sUniversité Joseph Fourier, Grenoble, France

^tLMU Munich, University Children's Hospital, Munich, Germany

^uDepartment of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Basel, Switzerland

^vUniversity of Basel, Basel, Switzerland

^wInstitute of Epidemiology and Medical Biometry, Ulm University, Ulm, Germany

^xInstitute for Risk Assessment Sciences, Utrecht University, Utrecht, The Netherlands

^yJulius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands

^zCentre for Prevention and Health Services Research, National Institute of Public Health and the Environment, Bilthoven, The Netherlands

^aaResearch Institute of Medical Genetics of the Siberian Branch of Russian Academy of Medical Sciences, Tomsk, Russia

^bbSiberian State Medical University, Tomsk, Russia

^ccJames Hogg iCAPTURE Center, University of British Columbia, Vancouver, British Columbia, Canada

^eeOccupational and Environmental Lung Disease Unit, University of British Columbia, Vancouver, British Columbia, Canada

^ddPediatrics and Child Health, University of Manitoba, Winnipeg, Manitoba, Canada

^ffDepartment of Pediatrics, Faculty of Medicine and Dentistry, University of Alberta and School of Public Health, University of Alberta, Edmonton, Canada

^ggPediatric Pneumology, Experimental and Clinical Research Center, Charité–Medical University, Berlin, Germany

ⁱⁱPediatric Pneumology and Immunology, Charité–Medical University, Berlin, Germany

^jjInstitute of Social Medicine, Epidemiology and Health Economics, Charité–Medical University, Berlin, Germany

^hhMax-Delbrück-Center (MDC) for Molecular Medicine, Berlin, Germany

^kkDepartment of Paediatric Pneumology and Allergy, University Children's Hospital Regensburg (KUNO), Regensburg, Germany

^llDepartment of Genetics, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands

^mmWellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom

ⁿⁿDivision of Population Health Sciences and Education, St George's, University of London, London, United Kingdom

^ooDepartment of Pediatric Pulmonology and Pediatric Allergology, Beatrix Children's Hospital, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands

PMCID: PMC3969577 PMID: 24315450

To the Editor:

Complex diseases, including asthma, have genetic and environmental origins. Genome-wide association studies have identified multiple genes for the development of asthma, yet they only explain a limited proportion of asthma heritability. Interactions between genetic predisposition and exposure to passive smoking might explain in part the hidden heritability of childhood asthma. However, to date, this approach has not been reported for the discovery of interactions between genes and tobacco smoke exposure.

We performed a genome-wide interaction study (GWIS) on childhood asthma to identify genes that interact with 2 well-known environmental risk factors for childhood-onset asthma: in utero and childhood tobacco smoke exposure. We meta-analyzed interaction results from 9 studies participating in the GABRIEL consortium¹ including more than 6,000 subjects of European descent. We replicated our findings in 4 independent studies including more than 13,000 subjects. Childhood-onset asthma was defined as asthma diagnosed by a doctor before the age of 16 years, which is consistent with the definition in the GABRIEL consortium.¹ In utero tobacco smoke exposure was defined as “exposure to maternal tobacco smoking at any time during pregnancy.” Childhood tobacco smoke exposure was defined as “exposure to passive tobacco smoking at any time from birth until 16 years of age.” Details on the number of subjects, the design of the individual studies, and outcome and exposure definitions are provided in Tables E1 to E4 in this article's Online Repository at www.jacionline.org.

The effects of in utero tobacco smoke exposure and childhood tobacco smoke exposure were analyzed separately. All individual studies were analyzed by using a logistic regression model containing the genetic effect, the effect of tobacco smoke exposure, and an interaction term indicating the interaction between the genetic effect and tobacco smoke exposure. Further methodological considerations on GWISs and details on the statistical analyses are described in this article's Online Repository at www.jacionline.org.

For in utero tobacco smoke exposure, the discovery genome-wide meta-analysis consisted of 2,654 cases and 3,073 control subjects derived from 7 studies (see Table E1). Overall, in utero tobacco smoke exposure increased the risk of childhood-onset asthma (see Fig E1 in this article's Online Repository at www.jacionline.org). A total of 536,705 single nucleotide polymorphisms (SNPs) were included in the interaction meta-analysis. Fig E2 in this article's Online Repository at www.jacionline.org shows the Manhattan plot. We identified 27 SNPs in the discovery sample with a P value of less than 10⁻⁴ based on the fixed effect model (Table I and see Table E5 in this article's Online Repository at www.jacionline.org). Findings did not reach genome-wide significance but were consistent over all studies included, and no significant heterogeneity across studies was present (P value Q-statistic < .05). Four of these SNPs on chromosome 10 were in high linkage disequilibrium with each other in the discovery meta-analysis (r² = 0.82-0.96). The most prominent marker was located on chromosome 18 near EPB41L3 (Forest plot, see Fig E3 in this article's Online Repository at www.jacionline.org). Table E6 in this article's Online Repository at www.jacionline.org shows the associations in exposed and nonexposed subjects. EPB41L3 belongs to the protein 4.1 family of membrane-associated proteins, is involved in cell-cell junctions,² and might play a role in apoptosis.³ The literature shows that in utero tobacco smoke exposure affects the expression of genes involved in biological processes, such as cell proliferation and apoptosis, and influences lung development of the child in general.⁴ Our data suggest that this effect of in utero smoke exposure might potentially occur through mechanisms involving EPB41L3 (see the additional text in this article's Online Repository).

Table I.

Results of the GWIS of in utero tobacco smoke exposure and childhood-onset asthma

Ch	SNP	Closest gene^∗	Type	Discovery			Replication
Ch	SNP	Closest gene^∗	Type	N^†	OR_int^‡	Pf	N^†	OR_int^‡	Pf
1	rs1674877	—	Intergenic	2654	0.51	2.19 × 10⁻⁵	201	1.06	.89
2	rs4670230	FAM82A1	Intronic	2654	1.94	2.10 × 10⁻⁵	201	0.78	.51
2	rs12624082	GALNT13	Intronic	2654	1.78	3.22 × 10⁻⁵	697	1.00	.98
2	rs11684139	GALNT13	Intronic	2654	1.77	7.57 × 10⁻⁵	697	0.85	.35
2	rs729454	—	Intergenic	2654	1.67	9.52 × 10⁻⁵	697	1.13	.45
3	rs3856848	IL5RA	Intronic	2654	1.96	5.32 × 10⁻⁶	201	0.59	.19
4	rs7682603	—	Intergenic	2247	0.54	1.19 × 10⁻⁵	562	1.20	.29
5	rs1990977	RNU6ATAC2P	Intergenic	2654	2.12	7.79 × 10⁻⁵	697	0.88	.60
5	rs4700239	—	Intergenic	2654	2.15	6.39 × 10⁻⁵	562	0.78	.34
6	rs6456433	—	Intergenic	2654	1.99	7.99 × 10⁻⁵	562	0.71	.15
6	rs14398	WDR46	Nonsynonymous	2654	0.45	5.44 × 10⁻⁵	562	1.77	.01
8	rs360968	—	Intergenic	2654	0.54	5.05 × 10⁻⁵	697	0.93	.72
9	rs943856	—	Intergenic	2654	0.59	4.94 × 10⁻⁵	697	0.70	.04
10	rs11006296	—	Intergenic	2654	2.01	3.70 × 10⁻⁵	562	0.84	.47
10	rs1407696	PDCD4	Intronic	2654	0.57	2.36 × 10⁻⁵	66	0.58	.34
10	rs7079511	SHOC2	Intronic	2654	0.58	3.24 × 10⁻⁵	697	0.98	.91
10	rs521674	ADRA2A	Upstream	2654	0.57	5.35 × 10⁻⁵	562	1.16	.45
10	rs602618	ADRA2A	Downstream	2654	0.57	5.63 × 10⁻⁵	562	1.15	.45
11	rs1123991	OR51E2	Synonymous	2654	0.50	6.51 × 10⁻⁵	697	0.68	.11
11	rs3898589	CNTN5	Intronic	2654	1.83	6.11 × 10⁻⁵	562	1.17	.40
11	rs10892848	CNTN5	Intronic	2654	1.82	5.72 × 10⁻⁵	697	1.07	.71
12	rs706793	ACCN2	Intronic	2654	1.66	3.62 × 10⁻⁵	697	0.75	.07
13	rs7321384	C13orf35	Intronic	2654	0.58	9.82 × 10⁻⁵	697	0.92	.63
16	rs8051325	ANKS4B	Intronic	2654	0.47	8.37 × 10⁻⁵	562	0.80	.37
18	rs8094633	EPB41L3	Intergenic	2654	2.13	4.29 × 10⁻⁵	201	2.87	.03
21	rs858003	KCNJ6	Intronic	2654	1.81	8.50 × 10⁻⁵	697	1.00	1.00
22	rs9613256	CTA-211A9.5	Within noncoding gene	2654	0.59	5.44 × 10⁻⁵	562	1.11	.60

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Ch, Chromosome; OR_int, odds ratio interaction; Pf, P value, fixed effect.

^∗

Closest gene within range of 500 kb of the position of the SNP.

^†

Number of studies and cases included in meta-analysis.

^‡

Additive genetic model.

For childhood tobacco smoke exposure, the discovery genome-wide meta-analysis consisted of 3,048 cases and 3,509 control subjects derived from 9 studies (see Table E1). Overall, childhood tobacco smoke exposure increased the risk of childhood-onset asthma (see Fig E1). A total of 538,233 SNPs were included in the interaction meta-analysis. Fig E4 in this article's Online Repository at www.jacionline.org shows the Manhattan plot. We identified 35 SNPs in the discovery sample with a P value of less than 10⁻⁴ based on the fixed effect model. Four of these SNPs were excluded because they showed heterogeneity, and the P value of the random effect was greater than 10⁻⁴. Findings did not reach genome-wide significance. Table II and Table E7 (see this article's Online Repository at www.jacionline.org) the results for the top SNPs. Seven SNPs on chromosome 5 (except rs2312164) were in high linkage disequilibrium with each other in the discovery studies (r² = 0.83-1.00).

Table II.

Results of the GWIS on childhood tobacco smoke exposure and childhood-onset asthma

Ch	SNP	Closest gene^∗	Type	Discovery			Replication
Ch	SNP	Closest gene^∗	Type	N^†	OR_int^‡	Pf	N^†	OR_int^‡	Pf
1	rs2026604	S100A7L2	Downstream	3048	1.44	7.49 × 10⁻⁵	1003	0.83	.17
2	rs10184453	—	Intergenic	3048	1.53	8.85 × 10⁻⁵	1003	1.18	.30
2	rs895565	—	Intergenic	3048	1.53	7.26 × 10⁻⁵	1003	1.18	.30
2	rs11126185	—	Intergenic	3048	0.67	6.81 × 10⁻⁶	868	1.22	.16
3	rs4234677	CTD-2230D16.1	Within noncoding gene	3048	0.65	6.57 × 10⁻⁵	261	1.58	.22
3	rs264096	MAGI1	Intronic	3048	0.62	6.93 × 10⁻⁶	396	0.89	.63
3	rs17239426	KCNAB1	Intronic	3048	0.58	7.28 × 10⁻⁵	1003	1.18	.39
4	rs1425551	IRF2	Intronic	3048	1.40	6.92 × 10⁻⁵	1003	0.98	.86
5	rs162036	MTRR	Nonsynonymous	3048	0.60	8.26 × 10⁻⁵	1003	1.14	.45
5	rs7719963	—	Intergenic	3048	0.56	3.06 × 10⁻⁵	868	0.89	.59
5	rs7447231	—	Intergenic	3048	1.55	8.36 × 10⁻⁶	868	0.85	.31
5	rs10155635	—	Intergenic	3048	1.56	7.55 × 10⁻⁶	261	0.62	.11
5	rs10038850	—	Intergenic	3048	1.53	1.51 × 10⁻⁵	261	0.41	.04
5	rs10479335	—	Intergenic	3048	1.52	5.98 × 10⁻⁵	868	0.85	.29
5	rs2312164	—	Intergenic	3048	1.42	7.18 × 10⁻⁵	1003	0.82	.14
5	rs13357477	—	Intergenic	3048	1.58	3.59 × 10⁻⁶	868	0.83	.24
5	rs12719549	—	Intergenic	3048	1.57	4.61 × 10⁻⁶	868	0.82	.21
5	rs4607330	—	Intergenic	3048	1.59	2.70 × 10⁻⁶	868	0.85	.31
6	rs441463	LYRM4	Intronic	3048	1.41	4.91 × 10⁻⁵	1003	0.90	.42
6	rs1575472	PACRG	Intronic	3048	1.78	1.37 × 10⁻⁵	1003	1.51	.06
7	rs17544971	GRB10	Intronic	3048	1.70	8.12 × 10⁻⁵	868	1.26	.28
9	rs4977750	MTAP	Nonsense-mediated decay transcript	3048	0.61	1.91 × 10⁻⁵	1003	0.93	.66
13	rs4769148	—	Intergenic	2445	0.67	4.45 × 10⁻⁵	261	0.72	.21
13	rs12874184	—	Intergenic	3048	1.98	8.75 × 10⁻⁵	868	1.18	.50
13	rs16972472	—	Intergenic	3048	1.79	9.59 × 10⁻⁵	868	0.79	.32
14	rs10141836	OR11G2	Upstream	3048	0.70	8.89 × 10⁻⁵	1003	0.90	.41
15	rs2602923	C15orf41	Intronic	3048	1.61	4.52 × 10⁻⁵	1003	1.19	.33
16	rs13331814	ZP2	Intronic	3048	0.62	8.38 × 10⁻⁵	868	0.85	.34
19	rs11085080	PLIN5	Intronic	3048	0.51	6.30 × 10⁻⁵	1003	1.12	.63
20	rs6077755	PSMF1	Upstream	3048	1.52	6.65 × 10⁻⁶	1003	1.11	.47
X	rs6641609	PRKX	Intronic	1939	0.49	3.43 × 10⁻⁵	261	1.90	.15

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Ch, Chromosome; OR_int, odds ratio interaction; Pf, P value, fixed effect.

^∗

Closest gene within range of 500 kb of the position of the SNP.

^†

Number of cases and control subjects included in the meta-analysis.

^‡

Additive genetic model.

The most prominent marker was located on chromosome 6 in PACRG (parkin coregulated gene; Forest plot, see Fig E5 in this article's Online Repository at www.jacionline.org). Table E8 in this article's Online Repository at www.jacionline.org shows the associations in exposed and nonexposed subjects. PACRG is located next to and has an overlapping promoter region with parkin 2 (PARK2).⁵ The gene has been associated with leprosy and parkinsonian diseases and has an important role in motile cilia function and cilia morphogenesis.^2,6 PACRG is relatively highly expressed in the trachea and nasal mucosa. Ciliary dysfunction might impair mucus clearance from the airways and has been shown to affect asthma severity. Our data suggest that changes in ciliary function particularly affect the development of asthma in children exposed to passive tobacco smoke.

The genes that have been reported previously to interact with tobacco smoke exposure with respect to asthma development (ie, TNF,⁷ GSTP1,⁷ and ADAM33⁸) were not among our most significant hits. This can be explained by the fact that the genetic variants in these candidate gene studies have a strong main effect on asthma development. Bouzigon et al⁹ showed a more pronounced effect of the 17q21 region on the development of early-onset asthma in children with early-life tobacco smoke exposure than in those without. The genetic effect of these markers in our GWIS showed a similar direction, but the interaction was not significant.

This study on childhood asthma is the first hypothesis-free GWIS specifically aiming to identify SNPs that interact with tobacco smoke exposure in disease development. We found suggestive evidence for an interaction between rs8094633 on chromosome 18 near EPB41L3 and in utero tobacco smoke exposure and an interaction between rs1575472 on chromosome 6 in PACRG and childhood tobacco smoke exposure. The SNPs found have not been identified previously in general genome-wide association studies on childhood asthma. Interestingly, the SNPs interacting with in utero and childhood tobacco smoke exposure were different and were not involved in the same pathway (see Fig E6 in this article's Online Repository at www.jacionline.org). Interactions between these SNPs and tobacco smoke exposure in utero and in childhood might explain part of the missing heritability of asthma. Future research needs to confirm these findings and further unravel the biological pathways.

Acknowledgments

For acknowledgments, see this article's Online Repository at www.jacionline.org.

Footnotes

^☆

This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial-No Derivative Works License, which permits non-commercial use, distribution, and reproduction in any medium, provided the original author and source are credited.

The GABRIEL study (a multidisciplinary study to identify the genetic and environmental causes of asthma in the European Community) was supported by the European Commission, contract number 018996, under the Integrated Program LSH-2004-1.2.5-1 and the Wellcome Trust (WT084703MA). Funding of the individual studies is described in this article's Online Repository at www.jacionline.org.

Disclosure of potential conflict of interest: A. J. Henderson has been supported by grants from the Medical Research Council (UK) and from the Wellcome Trust. F. Nyberg is employed by AstraZeneca. G. Pershagen has been supported by one or more grants from the European Union and the Swedish Research Council. D. Jarvis has been supported by one or more grants from the European Union. M. Wjst has been supported by one or more grants from the European Union (FP6). F. Kauffmann has been supported by one or more grants from the ANR French National Agency of research, the French Agency for Environmental and Occupational Health Safety, Inserm, and Merck Sharp and Dohme. E. Von Mutius has been supported by one or more grants from the European Commission; is an Associate Editor of the Journal of Allergy and Clinical Immunology; and has consultancy arrangements with GlaxoSmithKline, Novartis, ALK-Abelló, and Astellas Pharma. M. J. Ege has been supported by grants from the European Commission and from Deutsche Forschungsgemeinschaft. P. Pare has been supported by one or more grants from Allergen NCE. S. Lau has been supported by one or more grants from the German Research Foundation, is a member of a Drug Monitoring Committee, has consultancy arrangements with Symbiopharm and Allergopharm, and has received one or more payments for lecturing from or is on the speakers' bureau for Symbiopharm, Dannone, GlaxoSmithKline, and Novartis. T. Keil has received one or more grants from or has one or more grants pending with EU-FP7. Y. Lee has received one or more grants from or has one or more grants pending with the European Union and the German Research Foundation. M. Kabesch has been supported by one or more grants from the European Union, the German Ministry of Education and Research, and the German Research Foundation and has received one or more payments for lecturing from or is on the speakers' bureau for the European Respiratory Society, the European Academy of Allergy and Clinical Immunology, the American Thoracic Society, Novartis, and GlaxoSmithKline. M. Farrall has been supported by one or more grants from and has received support for travel from EU FP7. G. H. Koppelman has been supported by one or more grants from the European Union and has received one or more grants from or has one or more grants pending with the Netherlands Asthma Foundation, Stichting Asthma Bestrijding. The rest of the authors declare that they have no relevant conflicts of interest.

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Tables E1-E8

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References

1.Moffatt M.F., Gut I.G., Demenais F., Strachan D.P., Bouzigon E., Heath S. A large-scale, consortium-based genomewide association study of asthma. N Engl J Med. 2010;363:1211–1221. doi: 10.1056/NEJMoa0906312. [DOI] [PMC free article] [PubMed] [Google Scholar]
2.UniProt Consortium Reorganizing the protein space at the Universal Protein Resource (UniProt) Nucleic Acids Res. 2012;40(Database issue):D71–D75. doi: 10.1093/nar/gkr981. [DOI] [PMC free article] [PubMed] [Google Scholar]
3.Dafou D., Grun B., Sinclair J., Lawrenson K., Elizabeth C., Benjamin E.C. Microcell-mediated chromosome transfer identifies EPB41L3 as a functional suppressor of epithelial ovarian cancers. Neoplasia. 2010;12:579–589. doi: 10.1593/neo.10340. [DOI] [PMC free article] [PubMed] [Google Scholar]
4.Maritz G.S., Harding R. Life-long Programming implications of exposure to tobacco smoking and nicotine before and soon after birth: evidence for altered lung development. Int J Environ Res Public Health. 2011;8:875–898. doi: 10.3390/ijerph8030875. [DOI] [PMC free article] [PubMed] [Google Scholar]
5.West A.B., Lockhart P.J., O'Farell C., Farrer M.J. Identification of a novel gene linked to parkin via a bi-directional promoter. J Mol Biol. 2003;326:11–19. doi: 10.1016/s0022-2836(02)01376-1. [DOI] [PubMed] [Google Scholar]
6.Wilson G.R., Wang H.X., Egan G.F., Robinson P.J., Delatycki M.B., O'Bryan M.K. Deletion of the Parkin co-regulated gene causes defects in ependymal ciliary motility and hydrocephalus in the quakingviable mutant mouse. Hum Mol Genet. 2010;19:1593–1602. doi: 10.1093/hmg/ddq031. [DOI] [PubMed] [Google Scholar]
7.Panasevich S., Lindgren C., Kere J., Wickman M., Pershagen G., Nyberg F. Interaction between early maternal smoking and variants in TNF and GSTP1 in childhood wheezing. Clin Exp Allergy. 2010;40:458–467. doi: 10.1111/j.1365-2222.2010.03452.x. [DOI] [PubMed] [Google Scholar]
8.Reijmerink N.E., Kerkhof M., Koppelman G.H., Gerritsen J., De Jongste J.C., Smit H.A. Smoke exposure interacts with ADAM33 polymorphisms in the development of lung function and hyperresponsiveness. Allergy. 2009;64:898–904. doi: 10.1111/j.1398-9995.2009.01939.x. [DOI] [PubMed] [Google Scholar]
9.Bouzigon E., Corda E., Aschard H., Dizier M.H., Boland A., Bousquet J. Effect of 17q21 variants and smoking exposure in early-onset asthma. N Engl J Med. 2008;359:1985–1994. doi: 10.1056/NEJMoa0806604. [DOI] [PubMed] [Google Scholar]

Associated Data

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Supplementary Materials

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mmc1.doc^{(139KB, doc)}

Tables E1-E8

mmc2.doc^{(358KB, doc)}

Figures E1-E6 Legends and Figures

mmc3.doc^{(1.9MB, doc)}

[bib1] 1.Moffatt M.F., Gut I.G., Demenais F., Strachan D.P., Bouzigon E., Heath S. A large-scale, consortium-based genomewide association study of asthma. N Engl J Med. 2010;363:1211–1221. doi: 10.1056/NEJMoa0906312. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib2] 2.UniProt Consortium Reorganizing the protein space at the Universal Protein Resource (UniProt) Nucleic Acids Res. 2012;40(Database issue):D71–D75. doi: 10.1093/nar/gkr981. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib3] 3.Dafou D., Grun B., Sinclair J., Lawrenson K., Elizabeth C., Benjamin E.C. Microcell-mediated chromosome transfer identifies EPB41L3 as a functional suppressor of epithelial ovarian cancers. Neoplasia. 2010;12:579–589. doi: 10.1593/neo.10340. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib4] 4.Maritz G.S., Harding R. Life-long Programming implications of exposure to tobacco smoking and nicotine before and soon after birth: evidence for altered lung development. Int J Environ Res Public Health. 2011;8:875–898. doi: 10.3390/ijerph8030875. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib5] 5.West A.B., Lockhart P.J., O'Farell C., Farrer M.J. Identification of a novel gene linked to parkin via a bi-directional promoter. J Mol Biol. 2003;326:11–19. doi: 10.1016/s0022-2836(02)01376-1. [DOI] [PubMed] [Google Scholar]

[bib6] 6.Wilson G.R., Wang H.X., Egan G.F., Robinson P.J., Delatycki M.B., O'Bryan M.K. Deletion of the Parkin co-regulated gene causes defects in ependymal ciliary motility and hydrocephalus in the quakingviable mutant mouse. Hum Mol Genet. 2010;19:1593–1602. doi: 10.1093/hmg/ddq031. [DOI] [PubMed] [Google Scholar]

[bib7] 7.Panasevich S., Lindgren C., Kere J., Wickman M., Pershagen G., Nyberg F. Interaction between early maternal smoking and variants in TNF and GSTP1 in childhood wheezing. Clin Exp Allergy. 2010;40:458–467. doi: 10.1111/j.1365-2222.2010.03452.x. [DOI] [PubMed] [Google Scholar]

[bib8] 8.Reijmerink N.E., Kerkhof M., Koppelman G.H., Gerritsen J., De Jongste J.C., Smit H.A. Smoke exposure interacts with ADAM33 polymorphisms in the development of lung function and hyperresponsiveness. Allergy. 2009;64:898–904. doi: 10.1111/j.1398-9995.2009.01939.x. [DOI] [PubMed] [Google Scholar]

[bib9] 9.Bouzigon E., Corda E., Aschard H., Dizier M.H., Boland A., Bousquet J. Effect of 17q21 variants and smoking exposure in early-onset asthma. N Engl J Med. 2008;359:1985–1994. doi: 10.1056/NEJMoa0806604. [DOI] [PubMed] [Google Scholar]

PERMALINK

Novel childhood asthma genes interact with in utero and early-life tobacco smoke exposure☆

Salome Scholtens, PhD

Dirkje S Postma, PhD

Miriam F Moffatt, PhD

Sviatlana Panasevich, PhD

Raquel Granell, PhD

A John Henderson, MD

Erik Melén, PhD

Fredrik Nyberg, PhD

Göran Pershagen, PhD

Deborah Jarvis, PhD

Adaikalavan Ramasamy, PhD

Matthias Wjst, PhD

Cecilie Svanes, PhD

Emmanuelle Bouzigon, PhD

Florence Demenais, PhD

Francine Kauffmann, PhD

Valérie Siroux, PhD

Erika von Mutius, PhD

Markus Johannes Ege, MD

Charlotte Braun-Fahrländer, PhD

Jon Genuneit, PhD

Bert Brunekreef, PhD

Henriette A Smit, PhD

Alet H Wijga, PhD

Marjan Kerkhof, PhD

Ivan Curjuric, PhD

Medea Imboden, PhD

Gian A Thun, PhD

Nicole Probst-Hensch, PhD

Maxim B Freidin, PhD

Elena Iu Bragina, PhD

IA Deev, PhD

VP Puzyrev, PhD

Denise Daley, PhD

Julie Park, MMath

Allan Becker, MD

Moira Chan-Yeung, PhD

Anita L Kozyrskyj, PhD

Peter Pare, MD

Ingo Marenholz, PhD

Susanne Lau, PhD

Thomas Keil, PhD

Young-Ae Lee, PhD

Michael Kabesch, PhD

Cisca Wijmenga, PhD

Lude Franke, PhD

Ilja M Nolte, PhD

Judith Vonk, PhD

Ashish Kumar, PhD

Martin Farrall, PhD

William OCM Cookson, PhD

David P Strachan, PhD

Gerard H Koppelman, PhD

H Marike Boezen, PhD

Table I.

Table II.

Acknowledgments

Footnotes

Supplementary data

References

Associated Data

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Novel childhood asthma genes interact with in utero and early-life tobacco smoke exposure^☆