Ralf Jp van der Valk1,2,3, Liesbeth Duijts2,3,4, Nicolas J Timpson4,5, Muhammad T Salam6, Marie Standl7, John A Curtin8, Jon Genuneit9, Marjan Kerhof10, Eskil Kreiner-Møller11,12, Alejandro Cáceres13,14,15, Anna Gref16, Liming L Liang17,18, H Rob Taal1,2,3, Emmanuelle Bouzigon19,20, Florence Demenais19,20, Rachel Nadif21,22, Carole Ober23, Emma E Thompson23, Karol Estrada3,24, Albert Hofman3, André G Uitterlinden1,3,24, Cornélia van Duijn3, Fernando Rivadeneira3, Xia Li6, Sandrah P Eckel6, Kiros Berhane6, W James Gauderman6, Raquel Granell4, David M Evans4,5, Beate St Pourcain4, Wendy McArdle4, John P Kemp4,5, George Davey Smith4,5, Carla Mt Tiesler7, Claudia Flexeder7, Angela Simpson8, Clare S Murray8, Oliver Fuchs25,26, Dirkje S Postma27,28, Klaus Bønnelykke11,12, Maties Torrent15,29, Martin Andersson30,31, Patrick Sleiman32, Hakon Hakonarson32, William O Cookson33, Miriam F Moffatt33, Lavinia Paternoster4,5, Erik Melén16,34, Jordi Sunyer13,14,15,35, Hans Bisgaard11,12, Gerard H Koppelman10,27,28, Markus Ege26, Adnan Custovic8, Joachim Heinrich7, Frank D Gilliland6, Alexander J Henderson4, Vincent Wv Jaddoe1,2,3, Johan C de Jongste2. 1. The Generation R Study Group, Erasmus Medical Center, Rotterdam, The Netherlands. 2. Department of Pediatrics, Erasmus Medical Center, Rotterdam, The Netherlands. 3. Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands. 4. School of Social and Community Medicine, University of Bristol, Uk. 5. MRC Centre for Causal Analyses in Translational Epidemiology, University of Bristol, UK. 6. Department of Preventive Medicine, University of Southern California Keck School of Medicine, Los Angeles, USA. 7. Institute of Epidemiology I, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany. 8. University of Manchester, Manchester Academic Health Science Centre, University Hospital of South Manchester NHS Foundation Trust, Manchester, United Kingdom. 9. Institute of Epidemiology and Medical Biometry, Ulm University, Ulm, Germany. 10. University Medical Center Groningen, University of Groningen, Department of Pediatric Pulmonology and Pediatric Allergology, Beatrix Children's Hospital. 11. COPSAC, Copenhagen Prospective Studies on Asthma in Childhood, The Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark. 12. The Danish Pediatric Asthma Center, Copenhagen University Hospital, Gentofte, Copenhagen, Denmark. 13. Center for Research in Environmental Epidemiology (CREAL), Barcelona, Catalonia, Spain. 14. Institut Hospital del Mar d'Investigacions Mèdiques (IMIM), Barcelona, Catalonia, Spain. 15. Spanish consortium for Research on Epidemiology and Public Health (CIBERESP), Spain. 16. Institute of Environmental Medicine and Centre for Allergy Research, Karolinska Institutet, Stockholm, Sweden. 17. Department of Epidemiology, Harvard School of Public Health, Boston, USA. 18. Department of Biostatistics, Harvard School of Public Health, Boston, USA. 19. Inserm, UMR 946, Genetic Variation and Human Diseases Unit, F-75010, Paris, France. 20. Univ Paris Diderot, Sorbonne Paris Cité, Institut Universitaire d'Hématologie, F- 75007, Paris, France. 21. Inserm, Centre for research in Epidemiology and Population Health (CEPH), U1018, Respiratory and Environmental Epidemiology Team, F-94807, Villejuif, France. 22. Univ Paris-Sud, UMRS 1018, F-94807, Villejuif, France. 23. Department of Human Genetics, University of Chicago, Chicago, IL 60637. 24. Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands. 25. Inselspital, Universitätsspital, Bern, Universitätklinik für Kinderheilkunde, Bern, Switzerland. 26. Dr. von Hauner Children's Hospital, Ludwig Maximilian University, Munich, Germany. 27. University of Groningen, University Medical Center Groningen, Department of Pulmonology, Groningen, The Netherlands. 28. Groningen Research Institute for Asthma and COPD (GRIAC), University of Groningen, University Medical Center Groningen, Groningen, The Netherlands. 29. ib-salut, Area de Salut de Menorca, Balearic Islands, Spain. 30. Department of Public Health Sciences, Karolinska Institutet, Stockholm, Sweden. 31. Department of Physiology, South Central Hospital, Stockholm, Sweden. 32. Center for Applied Genomics, Abramson Research Center, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA. 33. National Heart and Lung Institute, Imperial College London, London SW3 6LY. 34. Sach's Children's Hospital, Stockholm, Sweden. 35. Pompeu Fabra University (UPF), Barcelona, Catalonia, Spain.
Abstract
BACKGROUND: The fraction of exhaled nitric oxide (Feno) value is a biomarker of eosinophilic airway inflammation and is associated with childhood asthma. Identification of common genetic variants associated with childhood Feno values might help to define biological mechanisms related to specific asthma phenotypes. OBJECTIVE: We sought to identify the genetic variants associated with childhood Feno values and their relation with asthma. METHODS: Feno values were measured in children age 5 to 15 years. In 14 genome-wide association studies (N = 8,858), we examined the associations of approximately 2.5 million single nucleotide polymorphisms (SNPs) with Feno values. Subsequently, we assessed whether significant SNPs were expression quantitative trait loci in genome-wide expression data sets of lymphoblastoid cell lines (n = 1,830) and were related to asthma in a previously published genome-wide association data set (cases, n = 10,365; control subjects: n = 16,110). RESULTS: We identified 3 SNPs associated with Feno values: rs3751972 in LYR motif containing 9 (LYRM9; P = 1.97 × 10(-10)) and rs944722 in inducible nitric oxide synthase 2 (NOS2; P = 1.28 × 10(-9)), both of which are located at 17q11.2-q12, and rs8069176 near gasdermin B (GSDMB; P = 1.88 × 10(-8)) at 17q12-q21. We found a cis expression quantitative trait locus for the transcript soluble galactoside-binding lectin 9 (LGALS9) that is in linkage disequilibrium with rs944722. rs8069176 was associated with GSDMB and ORM1-like 3 (ORMDL3) expression. rs8069176 at 17q12-q21, but not rs3751972 and rs944722 at 17q11.2-q12, were associated with physician-diagnosed asthma. CONCLUSION: This study identified 3 variants associated with Feno values, explaining 0.95% of the variance. Identification of functional SNPs and haplotypes in these regions might provide novel insight into the regulation of Feno values. This study highlights that both shared and distinct genetic factors affect Feno values and childhood asthma.
BACKGROUND: The fraction of exhaled nitric oxide (Feno) value is a biomarker of eosinophilic airway inflammation and is associated with childhood asthma. Identification of common genetic variants associated with childhood Feno values might help to define biological mechanisms related to specific asthma phenotypes. OBJECTIVE: We sought to identify the genetic variants associated with childhood Feno values and their relation with asthma. METHODS: Feno values were measured in children age 5 to 15 years. In 14 genome-wide association studies (N = 8,858), we examined the associations of approximately 2.5 million single nucleotide polymorphisms (SNPs) with Feno values. Subsequently, we assessed whether significant SNPs were expression quantitative trait loci in genome-wide expression data sets of lymphoblastoid cell lines (n = 1,830) and were related to asthma in a previously published genome-wide association data set (cases, n = 10,365; control subjects: n = 16,110). RESULTS: We identified 3 SNPs associated with Feno values: rs3751972 in LYR motif containing 9 (LYRM9; P = 1.97 × 10(-10)) and rs944722 in inducible nitric oxide synthase 2 (NOS2; P = 1.28 × 10(-9)), both of which are located at 17q11.2-q12, and rs8069176 near gasdermin B (GSDMB; P = 1.88 × 10(-8)) at 17q12-q21. We found a cis expression quantitative trait locus for the transcript soluble galactoside-binding lectin 9 (LGALS9) that is in linkage disequilibrium with rs944722. rs8069176 was associated with GSDMB and ORM1-like 3 (ORMDL3) expression. rs8069176 at 17q12-q21, but not rs3751972 and rs944722 at 17q11.2-q12, were associated with physician-diagnosed asthma. CONCLUSION: This study identified 3 variants associated with Feno values, explaining 0.95% of the variance. Identification of functional SNPs and haplotypes in these regions might provide novel insight into the regulation of Feno values. This study highlights that both shared and distinct genetic factors affect Feno values and childhood asthma.
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