International Journal of ImmunogeneticsGenetic & Genomic MedicinePeer-reviewed journal article
Analysis of rare coding variants in 470,000 UK Biobank participants reveals genetic associations with childhood asthma predisposition
Abstract
BackgroundPrevious studies of genetic contributions to risk of childhood asthma have implicated common variants with small effect sizes. Some studies using exome sequence data have reported associations with rare coding variants having larger effects on risk, notably an analysis of 145,000 subjects which found association with loss of function (LOF) variants in FLG, the gene coding for filaggrin. Here we report the results of an analysis of rare nonsynonymous and LOF variants, carried out on the full UK Biobank cohort of 470,000 exome-sequenced participants. MethodsThe phenotype of childhood asthma was defined as reporting asthma with onset before 18. Regression analysis was applied to gene-wise tests for association LOF and nonsynonymous variants. 45 tests using different pathogenicity predictors were applied to the first cohort of 200,000 participants. Subsequently the 100 genes showing strongest evidence for association were analysed in the second cohort of 270,000 participants, using only the best-performing predictor for each gene. For FLG, separate analyses were carried out for participants with atopic dermatitis. ResultsThree genes achieved statistical significance, FLG, IL33 and PRKCQ. The effects on asthma risk and frequencies of variants in different functional categories were characterised for these genes. Damaging coding variants were associated with increased risk of asthma in FLG and IL33 but reduced risk in PRKCQ. FLG LOF variants were also associated with risk of atopic dermatitis and their effect on asthma risk was higher in people who reported a diagnosis of atopic dermatitis. ConclusionsRare coding variants in a small number of genes have important effects on asthma risk. Further study of individual variant effects might elucidate mechanisms of pathogenesis. This research has been conducted using the UK Biobank Resource.
- organism: human
- assay: whole-exome sequencing
- research focus: GWAS / association mapping
- approach: statistical model
- Citations
- 2
- FWCI
- 1.28
- Field percentile
- top 23%
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