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 tr...

Chronic Obstructive Pulmonary Disease (COPD) is characterised by reduced lung function and is the third leading cause of death globally. Through genome-wide association discovery in 48,943 individuals, selected from extremes of the lung function distribution in UK Biobank, and follow-up in 95,375 individuals, we increased the yield of independent signals for lung function from 54 to 97. A genetic risk score was associated with COPD susceptibility (odds ratios per standard deviation of the risk score (~6 alleles) (95% confidence interval) 1.24 (1.20-1.27), P=5.05x10-49) and we observed a 3.7 fold difference in COPD risk between highest and lowest genetic risk score deciles in UK Biobank. The 97 signals show enrichment in development, elastic fibres and epigenetic regulation pathways. We highlight targets for drugs and compounds in development for COPD and asthma (genes in the inositol phosphate metabolism pathway and CHRM3) and describe targets for potential drug repositioning from other clinical indications.

An increasing proportion of the worldwide population is affected by allergic diseases such as allergic rhinitis (AR), atopic dermatitis (AD) and allergic asthma and improved treatment options are needed particularly for severe, refractory disease. Allergic diseases are complex and development involves both environmental and genetic factors. Although the existence of a genetic component for allergy was first described almost 100 years ago, progress in gene identification has been hindered by lack of high throughput technologies to investigate genetic variation in large numbers of subjects. The development of Genome-Wide Association Studies (GWAS), a hypothesis-free method of interrogating large numbers of common variants spanning the entire genome in disease and non-disease subjects has revolutionised our understanding of the genetics of allergic disease. Susceptibility genes for asthma, AR and AD have now been identified with confidence, suggesting there are common and distinct genetic loci associated with these diseases, providing novel insights into potential disease pathways and mechanisms. Genes involved in both adaptive and innate immune mechanisms have been identified, notably including multiple genes involved in epithelial function/secretion, suggesting that the airway epithelium may be particularly important in asthma. Interestingly, concordance/discordance between the genetic factors driving allergic traits such as IgE levels and disease states such as asthma have further supported the accumulating evidence for heterogeneity in these diseases. While GWAS have been useful and continue to identify novel genes for allergic diseases through increased sample sizes and phenotype refinement, future approaches will integrate analyses of rare variants, epigenetic mechanisms and eQTL approaches, leading to greater insight into the genetic basis of these diseases. Gene identification will improve our understanding of disease mechanisms and generate potential therapeutic opportunities.