Abstract

SummaryBackgroundFew genetic studies that focus on moderate-to-severe asthma exist. We aimed to identity novel genetic variants associated with moderate-to-severe asthma, see whether previously identified genetic variants for all types of asthma contribute to moderate-to-severe asthma, and provide novel mechanistic insights using expression analyses in patients with asthma.MethodsIn this genome-wide association study, we used a two-stage case-control design. In stage 1, we genotyped patient-level data from two UK cohorts (the Genetics of Asthma Severity and Phenotypes [GASP] initiative and the Unbiased BIOmarkers in PREDiction of respiratory disease outcomes [U-BIOPRED] project) and used data from the UK Biobank to collect patient-level genomic data for cases and controls of European ancestry in a 1:5 ratio. Cases were defined as having moderate-to-severe asthma if they were taking appropriate medication or had been diagnosed by a doctor. Controls were defined as not having asthma, rhinitis, eczema, allergy, emphysema, or chronic bronchitis as diagnosed by a doctor. For stage 2, an independent cohort of cases and controls (1:5) was selected from the UK Biobank only, with no overlap with stage 1 samples. In stage 1 we undertook a genome-wide association study of moderate-to-severe asthma, and in stage 2 we followed up independent variants that reached the significance threshold of p less than 1 × 10−6 in stage 1. We set genome-wide significance at p less than 5 × 10−8. For novel signals, we investigated their effect on all types of asthma (mild, moderate, and severe). For all signals meeting genome-wide significance, we investigated their effect on gene expression in patients with asthma and controls.FindingsWe included 5135 cases and 25 675 controls for stage 1, and 5414 cases and 21 471 controls for stage 2. We identified 24 genome-wide significant signals of association with moderate-to-severe asthma, including several signals in innate or adaptive immune-response genes. Three novel signals were identified: rs10905284 in GATA3 (coded allele A, odds ratio [OR] 0·90, 95% CI 0·88–0·93; p=1·76 × 10−10), rs11603634 in the MUC5AC region (coded allele G, OR 1·09, 1·06–1·12; p=2·32 × 10−8), and rs560026225 near KIAA1109 (coded allele GATT, OR 1·12, 1·08–1·16; p=3·06 × 10−9). The MUC5AC signal was not associated with asthma when analyses included mild asthma. The rs11603634 G allele was associated with increased expression of MUC5AC mRNA in bronchial epithelial brush samples via proxy SNP rs11602802; (p=2·50 × 10−5) and MUC5AC mRNA was increased in bronchial epithelial samples from patients with severe asthma (in two independent analyses, p=0·039 and p=0·022).InterpretationWe found substantial shared genetic architecture between mild and moderate-to-severe asthma. We also report for the first time genetic variants associated with the risk of developing moderate-to-severe asthma that regulate mucin production. Finally, we identify candidate causal genes in these loci and provide increased insight into this difficult to treat population.FundingAsthma UK, AirPROM, U-BIOPRED, UK Medical Research Council, and Rosetrees Trust.

Highlights

  • Asthma is a common disease and was identified as the most prevalent chronic respiratory disease in the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2015.1,2 10–15% of individuals with asthma have severe asthma and substantial unmet clinical needs, with symptoms including debilitating breathlessness, associ­ ated frequent exacer­bations, and increased hospital admissions despite the high use of medicines.[3]

  • We aimed to complete a large genome-wide association study of moderate-to-severe asthma to address three specific objectives: first, we aimed to identify novel signals predicting disease risk for moderate-to-severe asthma; second, we wanted to see whether asthma signals that have been previously described were associated with moderate-tosevere asthma; and we aimed to translate genetic findings into disease mechanisms via initial functional studies using the Unbiased BIOmarkers in PREDiction of Respiratory Disease Outcomes (U-BIOPRED) integrated asthma patient genomics resource,[26] which might in turn identify new targets for therapeutic intervention

  • From Genetics of Asthma Severity and Phenotypes (GASP) and U-BIOPRED, we identified patients with moderate-to-severe asthma by assessing clinical records that indicated that a patient was taking medication required for patients defined as having moderate-to-severe asthma according to the British Thoracic Society (BTS) 2014 guidelines.[29]

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Summary

Introduction

Asthma is a common disease and was identified as the most prevalent chronic respiratory disease in the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2015.1,2 10–15% of individuals with asthma have severe asthma and substantial unmet clinical needs, with symptoms including debilitating breathlessness, associ­ ated frequent exacer­bations, and increased hospital admissions despite the high use of medicines.[3]. We examined the original publications and included studies with more than 500 cases and 500 controls and we considered signals of relevance to be those that met genome-wide significance (p

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