Chloé Sarnowski1, Pierre-Emmanuel Sugier1, Raquel Granell2, Debbie Jarvis3, Marie-Hélène Dizier1, Markus Ege4, Medea Imboden5, Catherine Laprise6, Elza K Khusnutdinova7, Maxim B Freidin8, William O C Cookson9, Miriam Moffatt9, Mark Lathrop10, Valérie Siroux11, Ludmila M Ogorodova12, Alexandra S Karunas7, Alan James13, Nicole M Probst-Hensch5, Erika von Mutius4, Isabelle Pin14, Manolis Kogevinas15, A John Henderson2, Florence Demenais1, Emmanuelle Bouzigon16. 1. Inserm, UMR-946, Paris, France; Université Paris Diderot, Sorbonne Paris Cité, Institut Universitaire d'Hématologie, Paris, France. 2. School of Social and Community Medicine, University of Bristol, Bristol, United Kingdom. 3. Respiratory Epidemiology, Occupational Medicine and Public Health, National Heart and Lung Institute, Imperial College, London, United Kingdom; MRC-PHE Centre for Environment & Health, London, United Kingdom. 4. Dr von Hauner Children's Hospital, Ludwig Maximilian University, Munich, Germany; Comprehensive Pneumology Center Munich (CPC-M), German Center for Lung Research, Munich, Germany. 5. Swiss Tropical and Public Health Institute, Basel, Switzerland; University of Basel, Basel, Switzerland. 6. Département des sciences fondamentales, Université du Québec à Chicoutimi, Saguenay, Quebec, Canada. 7. Institute of Biochemistry and Genetics, Ufa Scientific Centre, Russian Academy of Sciences, Ufa, Russia; Department of Genetics and Fundamental Medicine, Bashkir State University, Ufa, Russia. 8. Research Institute for Medical Genetics, Tomsk, Russia. 9. National Heart Lung Institute, Imperial College London, London, United Kingdom. 10. McGill University and Génome Québec Innovation Centre, Montreal, Quebec, Canada. 11. Université Grenoble Alpes, IAB, Team of Environmental Epidemiology applied to Reproduction and Respiratory Health, Grenoble, France; Inserm, IAB, Team of Environmental Epidemiology applied to Reproduction and Respiratory Health, Grenoble, France; CHU de Grenoble, IAB, Team of Environmental Epidemiology applied to Reproduction and Respiratory Health, Grenoble, France. 12. Siberian State Medical University, Tomsk, Russia. 13. Busselton Population Medical Research Institute, Department of Pulmonary Physiology and Sleep Medicine, Sir Charles Gairdner Hospital, Nedlands, and the School of Population Health, University of Western Australia, Crawley, Australia. 14. Université Grenoble Alpes, IAB, Team of Environmental Epidemiology applied to Reproduction and Respiratory Health, Grenoble, France; Inserm, IAB, Team of Environmental Epidemiology applied to Reproduction and Respiratory Health, Grenoble, France; CHU de Grenoble, Pediatrics, Grenoble, France. 15. Centre for Research in Environmental Epidemiology (CREAL), Barcelona, Spain; CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain; IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain; Universitat Pompeu Fabra, Barcelona, Spain. 16. Inserm, UMR-946, Paris, France; Université Paris Diderot, Sorbonne Paris Cité, Institut Universitaire d'Hématologie, Paris, France. Electronic address: emmanuelle.bouzigon@inserm.fr.
Abstract
BACKGROUND: Asthma is a heterogeneous disease in which age of onset plays an important role. OBJECTIVE: We sought to identify the genetic variants associated with time to asthma onset (TAO). METHODS: We conducted a large-scale meta-analysis of 9 genome-wide association studies of TAO (total of 5462 asthmatic patients with a broad range of age of asthma onset and 8424 control subjects of European ancestry) performed by using survival analysis techniques. RESULTS: We detected 5 regions associated with TAO at the genome-wide significant level (P < 5 × 10-8). We evidenced a new locus in the 16q12 region (near cylindromatosis turban tumor syndrome gene [CYLD]) and confirmed 4 asthma risk regions: 2q12 (IL-1 receptor-like 1 [IL1RL1]), 6p21 (HLA-DQA1), 9p24 (IL33), and 17q12-q21 (zona pellucida binding protein 2 [ZPBP2]-gasdermin A [GSDMA]). Conditional analyses identified 2 distinct signals at 9p24 (both upstream of IL33) and 17q12-q21 (near ZPBP2 and within GSDMA). Together, these 7 distinct loci explained 6.0% of the variance in TAO. In addition, we showed that genetic variants at 9p24 and 17q12-q21 were strongly associated with an earlier onset of childhood asthma (P ≤ .002), whereas the 16q12 single nucleotide polymorphism was associated with later asthma onset (P = .04). A high burden of disease risk alleles at these loci was associated with earlier age of asthma onset (4 vs 9-12 years, P = 10-4). CONCLUSION: The new susceptibility region for TAO at 16q12 harbors variants that correlate with the expression of CYLD and nucleotide-binding oligomerization domain 2 (NOD2), 2 strong candidates for asthma. This study demonstrates that incorporating the variability of age of asthma onset in asthma modeling is a helpful approach in the search for disease susceptibility genes.
BACKGROUND: Asthma is a heterogeneous disease in which age of onset plays an important role. OBJECTIVE: We sought to identify the genetic variants associated with time to asthma onset (TAO). METHODS: We conducted a large-scale meta-analysis of 9 genome-wide association studies of TAO (total of 5462 asthmatic patients with a broad range of age of asthma onset and 8424 control subjects of European ancestry) performed by using survival analysis techniques. RESULTS: We detected 5 regions associated with TAO at the genome-wide significant level (P < 5 × 10-8). We evidenced a new locus in the 16q12 region (near cylindromatosis turban tumor syndrome gene [CYLD]) and confirmed 4 asthma risk regions: 2q12 (IL-1 receptor-like 1 [IL1RL1]), 6p21 (HLA-DQA1), 9p24 (IL33), and 17q12-q21 (zona pellucida binding protein 2 [ZPBP2]-gasdermin A [GSDMA]). Conditional analyses identified 2 distinct signals at 9p24 (both upstream of IL33) and 17q12-q21 (near ZPBP2 and within GSDMA). Together, these 7 distinct loci explained 6.0% of the variance in TAO. In addition, we showed that genetic variants at 9p24 and 17q12-q21 were strongly associated with an earlier onset of childhood asthma (P ≤ .002), whereas the 16q12 single nucleotide polymorphism was associated with later asthma onset (P = .04). A high burden of disease risk alleles at these loci was associated with earlier age of asthma onset (4 vs 9-12 years, P = 10-4). CONCLUSION: The new susceptibility region for TAO at 16q12 harbors variants that correlate with the expression of CYLD and nucleotide-binding oligomerization domain 2 (NOD2), 2 strong candidates for asthma. This study demonstrates that incorporating the variability of age of asthma onset in asthma modeling is a helpful approach in the search for disease susceptibility genes.
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