Anna Gref1, Simon K Merid1, Olena Gruzieva1, Stéphane Ballereau2, Allan Becker3, Tom Bellander1,4, Anna Bergström1,4, Yohan Bossé5,6, Matteo Bottai1, Moira Chan-Yeung7, Elaine Fuertes8,9, Despo Ierodiakonou10,11, Ruiwei Jiang12, Stéphane Joly2, Meaghan Jones12, Michael S Kobor12, Michal Korek1, Anita L Kozyrskyj13, Ashish Kumar1,14, Nathanaël Lemonnier2, Elaina MacIntyre8,9,15, Camille Ménard2, David Nickle16, Ma'en Obeidat17, Johann Pellet2, Marie Standl9, Annika Sääf1, Cilla Söderhäll18,19,20, Carla M T Tiesler7,21, Maarten van den Berge22,23, Judith M Vonk11,23, Hita Vora24, Cheng-Jian Xu22,23,25, Josep M Antó26, Charles Auffray2, Michael Brauer8, Jean Bousquet27, Bert Brunekreef28, W James Gauderman24, Joachim Heinrich9, Juha Kere18,19, Gerard H Koppelman23,29, Dirkje Postma22,30, Christopher Carlsten7, Göran Pershagen1,4, Erik Melén1,4,31. 1. 1 Institute of Environmental Medicine. 2. 2 European Institute for Systems Biology and Medicine, CNRS-ENS-UCBL, Université de Lyon, Lyon, France. 3. 3 Department of Pediatrics and Child Health, University of Manitoba, Winnipeg, Manitoba, Canada. 4. 4 Centre for Occupational and Environmental Medicine, Stockholm County Council, Stockholm, Sweden. 5. 5 Quebec Heart and Lung Institute and. 6. 6 Department of Molecular Medicine, Laval University, Quebec City, Quebec, Canada. 7. 7 Department of Medicine. 8. 9 School of Population and Public Health. 9. 8 Institute of Epidemiology I, Helmholtz Zentrum München - German Research Centre for Environmental Health, Neuherberg, Germany. 10. 10 Section of Paediatrics, Department of Medicine, Imperial College London, London, United Kingdom. 11. 11 Department of Epidemiology. 12. 12 Centre for Molecular Medicine and Therapeutics, Child and Family Research Institute, Department of Medical Genetics, and. 13. 13 Department of Pediatrics, University of Alberta, Edmonton, Alberta, Canada. 14. 14 Department of Public Health Epidemiology, Unit of Chronic Disease Epidemiology, Swiss Tropical and Public Health Institute, University of Basel, Switzerland. 15. 15 Environmental and Occupational Health, Public Health Ontario, Toronto, Ontario, Canada. 16. 16 Merck & Co Inc, Rahway, New Jersey. 17. 17 Centre for Heart Lung Innovation, University of British Columbia, Vancouver, British Columbia, Canada. 18. 18 Department of Biosciences and Nutrition. 19. 19 Center for Innovative Medicine, and. 20. 20 Department of Women's and Children's Health, Karolinska Institutet, Stockholm, Sweden. 21. 21 Division of Metabolic Diseases and Nutritional Medicine, Ludwig-Maximilians-University of Munich, Dr. von Hauner Children's Hospital, Munich, Germany. 22. 22 Department of Pulmonology. 23. 23 Groningen Research Institute for Asthma and COPD. 24. 24 Preventive Medicine, University of Southern California, Los Angeles, California. 25. 25 Department of Genetics. 26. 26 Centre for Research in Environmental Epidemiology, Barcelona, Spain. 27. 27 CHU Montpellier, University of Montpellier, Montpellier, France. 28. 28 Institute for Risk Assessment Sciences, Utrecht University, Utrecht, the Netherlands; and. 29. 29 Pediatric Pulmonology and Pediatric Allerogology, Beatrix Children's Hospital, GRIAC Research Institute, and. 30. 30 Department of Pulmonary Medicine and Tuberculosis, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands. 31. 31 Sachs Children's Hospital, Stockholm, Sweden.
Abstract
RATIONALE: The evidence supporting an association between traffic-related air pollution exposure and incident childhood asthma is inconsistent and may depend on genetic factors. OBJECTIVES: To identify gene-environment interaction effects on childhood asthma using genome-wide single-nucleotide polymorphism (SNP) data and air pollution exposure. Identified loci were further analyzed at epigenetic and transcriptomic levels. METHODS: We used land use regression models to estimate individual air pollution exposure (represented by outdoor NO2 levels) at the birth address and performed a genome-wide interaction study for doctors' diagnoses of asthma up to 8 years in three European birth cohorts (n = 1,534) with look-up for interaction in two separate North American cohorts, CHS (Children's Health Study) and CAPPS/SAGE (Canadian Asthma Primary Prevention Study/Study of Asthma, Genetics and Environment) (n = 1,602 and 186 subjects, respectively). We assessed expression quantitative trait locus effects in human lung specimens and blood, as well as associations among air pollution exposure, methylation, and transcriptomic patterns. MEASUREMENTS AND MAIN RESULTS: In the European cohorts, 186 SNPs had an interaction P < 1 × 10-4 and a look-up evaluation of these disclosed 8 SNPs in 4 loci, with an interaction P < 0.05 in the large CHS study, but not in CAPPS/SAGE. Three SNPs within adenylate cyclase 2 (ADCY2) showed the same direction of the interaction effect and were found to influence ADCY2 gene expression in peripheral blood (P = 4.50 × 10-4). One other SNP with P < 0.05 for interaction in CHS, rs686237, strongly influenced UDP-Gal:betaGlcNAc β-1,4-galactosyltransferase, polypeptide 5 (B4GALT5) expression in lung tissue (P = 1.18 × 10-17). Air pollution exposure was associated with differential discs, large homolog 2 (DLG2) methylation and expression. CONCLUSIONS: Our results indicated that gene-environment interactions are important for asthma development and provided supportive evidence for interaction with air pollution for ADCY2, B4GALT5, and DLG2.
RATIONALE: The evidence supporting an association between traffic-related air pollution exposure and incident childhood asthma is inconsistent and may depend on genetic factors. OBJECTIVES: To identify gene-environment interaction effects on childhood asthma using genome-wide single-nucleotide polymorphism (SNP) data and air pollution exposure. Identified loci were further analyzed at epigenetic and transcriptomic levels. METHODS: We used land use regression models to estimate individual air pollution exposure (represented by outdoor NO2 levels) at the birth address and performed a genome-wide interaction study for doctors' diagnoses of asthma up to 8 years in three European birth cohorts (n = 1,534) with look-up for interaction in two separate North American cohorts, CHS (Children's Health Study) and CAPPS/SAGE (Canadian Asthma Primary Prevention Study/Study of Asthma, Genetics and Environment) (n = 1,602 and 186 subjects, respectively). We assessed expression quantitative trait locus effects in human lung specimens and blood, as well as associations among air pollution exposure, methylation, and transcriptomic patterns. MEASUREMENTS AND MAIN RESULTS: In the European cohorts, 186 SNPs had an interaction P < 1 × 10-4 and a look-up evaluation of these disclosed 8 SNPs in 4 loci, with an interaction P < 0.05 in the large CHS study, but not in CAPPS/SAGE. Three SNPs within adenylate cyclase 2 (ADCY2) showed the same direction of the interaction effect and were found to influence ADCY2 gene expression in peripheral blood (P = 4.50 × 10-4). One other SNP with P < 0.05 for interaction in CHS, rs686237, strongly influenced UDP-Gal:betaGlcNAc β-1,4-galactosyltransferase, polypeptide 5 (B4GALT5) expression in lung tissue (P = 1.18 × 10-17). Air pollution exposure was associated with differential discs, large homolog 2 (DLG2) methylation and expression. CONCLUSIONS: Our results indicated that gene-environment interactions are important for asthma development and provided supportive evidence for interaction with air pollution for ADCY2, B4GALT5, and DLG2.
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