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Identification of a new locus at 16q12 associated with time to asthma onset

2016; Elsevier BV; Volume: 138; Issue: 4 Linguagem: Inglês

10.1016/j.jaci.2016.03.018

1097-6825

Chloé Sarnowski, Pierre‐Emmanuel Sugier, Raquel Granell, Deborah Jarvis, Marie‐Hélène Dizier, Markus Ege, Medea Imboden, Catherine Laprise, Э. К. Хуснутдинова, Maxim B. Freidin, William Cookson, Miriam F. Moffatt, Mark Lathrop, Valérie Siroux, Л. М. Огородова, А. С. Карунас, Anthony James, Nicole Probst‐Hensch, Erika von Mutius, Isabelle Pin, Manolis Kogevinas, A. John Henderson, Florence Démenais, Emmanuelle Bouzigon,

IL-33, ST2, and ILC Pathways

BackgroundAsthma is a heterogeneous disease in which age of onset plays an important role.ObjectiveWe sought to identify the genetic variants associated with time to asthma onset (TAO).MethodsWe 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.ResultsWe 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).ConclusionThe 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. Asthma is a heterogeneous disease in which age of onset plays an important role. We sought to identify the genetic variants associated with time to asthma onset (TAO). 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. 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). 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.