Genome-Wide Association Studies of Asthma in Population-Based Cohorts Confirm Known and Suggested Loci and Identify an Additional Association near HLA

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Ramasamy, Adaikalavan ; Kuokkanen, Mikko ; Vedantam, Sailaja ; Gajdos, Zofia K. ; Alves, Alexessander Couto ; Lyon, Helen N. ; Ferreira, Manuel A. R. ; Strachan, David P. ; Zhao, Jing Hua ; Abramson, Michael J. ; Brown, Matthew A. ; Coin, Lachlan ; Dharmage, Shyamali C. ; Duffy, David L. ; Haahtela, Tari ; Heath, Andrew C. ; Janson, Christer ; Kahonen, Mika ; Khaw, Kay-Tee ; Laitinen, Jaana ; Le Souef, Peter ; Lehtimaki, Terho ; Madden, Pamela A. F. ; Marks, Guy B. ; Martin, Nicholas G. ; Matheson, Melanie C. ; Palmer, Cameron D. ; Palotie, Aarno ; Pouta, Anneli ; Robertson, Colin F. ... view all 46 authors (2012)
  • Publisher: Uppsala universitet, Lungmedicin och allergologi
  • Journal: (issn: 1932-6203, vol: 7, pp: e44008)
  • Related identifiers: doi: 10.1371/journal.pone.0044008, pmc: PMC3461045
  • Subject: Computational Biology | Molecular Genetics | Genetics of the Immune System | Population Genetics | Human Genetics | Biology | Genetics of Disease | Research Article | Medicine | Pulmonology | Asthma | Medical and Health Sciences | fi=Biolääketieteet | en=Biomedicine| | Genetics | Allergy and Hypersensitivity | Medicin och hälsovetenskap | Clinical Immunology | Immunology

Rationale: Asthma has substantial morbidity and mortality and a strong genetic component, but identification of genetic risk factors is limited by availability of suitable studies. Objectives: To test if population-based cohorts with self-reported physician-diagnosed asthma and genome-wide association (GWA) data could be used to validate known associations with asthma and identify novel associations. Methods: The APCAT (Analysis in Population-based Cohorts of Asthma Traits) consortium consists of 1,716 individuals with asthma and 16,888 healthy controls from six European-descent population-based cohorts. We examined associations in APCAT of thirteen variants previously reported as genome-wide significant (P<5x\(10^{−8}\)) and three variants reported as suggestive (P<5×\(10^{−7}\)). We also searched for novel associations in APCAT (Stage 1) and followed-up the most promising variants in 4,035 asthmatics and 11,251 healthy controls (Stage 2). Finally, we conducted the first genome-wide screen for interactions with smoking or hay fever. Main Results: We observed association in the same direction for all thirteen previously reported variants and nominally replicated ten of them. One variant that was previously suggestive, rs11071559 in RORA, now reaches genome-wide significance when combined with our data (P = 2.4×\(10^{−9}\)). We also identified two genome-wide significant associations: rs13408661 near IL1RL1/IL18R1 (\(P_{Stage1+Stage2}\) = 1.1x\(10^{−9}\)), which is correlated with a variant recently shown to be associated with asthma (rs3771180), and rs9268516 in the HLA region (\(P_{Stage1+Stage2}\) = 1.1x\(10^{−8}\)), which appears to be independent of previously reported associations in this locus. Finally, we found no strong evidence for gene-environment interactions with smoking or hay fever status. Conclusions: Population-based cohorts with simple asthma phenotypes represent a valuable and largely untapped resource for genetic studies of asthma.