Age-of-onset information helps identify 76 genetic variants associated with allergic disease

Abstract

Risk factors that contribute to inter-individual differences in the age-of-onset of allergic diseases are poorly understood. The aim of this study was to identify genetic risk variants associated with the age at which symptoms of allergic disease first develop, considering information from asthma, hay fever and eczema. Self-reported age-of-onset information was available for 117,130 genotyped individuals of European ancestry from the UK Biobank study. For each individual, we identified the earliest age at which asthma, hay fever and/or eczema was first diagnosed and performed a genome-wide association study (GWAS) of this combined age-of-onset phenotype. We identified 50 variants with a significant independent association (P<3x10-8) with age-of-onset. Forty-five variants had comparable effects on the onset of the three individual diseases and 38 were also associated with allergic disease case-control status in an independent study (n = 222,484). We observed a strong negative genetic correlation between age-of-onset and case-control status of allergic disease (rg = -0.63, P = 4.5x10-61), indicating that cases with early disease onset have a greater burden of allergy risk alleles than those with late disease onset. Subsequently, a multivariate GWAS of age-of-onset and case-control status identified a further 26 associations that were missed by the univariate analyses of age-of-onset or case-control status only. Collectively, of the 76 variants identified, 18 represent novel associations for allergic disease. We identified 81 likely target genes of the 76 associated variants based on information from expression quantitative trait loci (eQTL) and non-synonymous variants, of which we highlight ADAM15, FOSL2, TRIM8, BMPR2, CD200R1, PRKCQ, NOD2, SMAD4, ABCA7 and UBE2L3. Our results support the notion that early and late onset allergic disease have partly distinct genetic architectures, potentially explaining known differences in pathophysiology between individuals.

Fig 1. Summary of results from the GWAS of allergic disease age-of-onset in the UK Biobank study (n = 117,130).

UK Biobank participants reported age-of-onset for asthma and, in a single separate question, for hay fever/eczema. In this analysis, we took the earliest age-of-onset reported across these two questionnaire items and tested this phenotype for association with SNP allelic dosage. We identified 4,160 variants associated with age-of-onset at a P<3x10^-8 (red circles), including 50 with a statistically independent association.

Fig 2. Variants with evidence for disease-specific effects on age-of-onset.

Each of the 50 variants identified in the GWAS of age-of-onset were tested for association with age-of-onset in three non-overlapping groups of individuals: those suffering from asthma only (n = 22,029), hay fever only (n = 14,474) and eczema only (n = 3,969). We then compared the effects (i.e. betas) obtained in these three groups. For 5 of the 50 variants (shown with an orange inner triangle), the effect on age-of-onset was significantly different (P<0.05/(3 x 50) = 3.3x10^-4) between at least two groups. For a given variant, the vertices of the inner triangle point to the position along the edges of the outer triangle that corresponds to difference in effect observed between pairs of single-disease cases. For example, the rs61816761[A] allele, which is located in the FLG gene (filaggrin), had an effect on age-of-onset that was larger (absolute of difference = 0.42) in individuals suffering only from eczema when compared to individuals suffering only from hay fever (P = 4.3x10⁻⁸), consistent with this SNP having a stronger effect on the age-of-onset of eczema than of hay fever. For comparison, a variant with no significant differences when comparing the effect on age-of-onset in all three pairwise single-disease association analyses is also shown (rs705699, in the RAB5B gene). In this case, the difference in effect was approximately equal to 0 in the three pairwise comparisons. The color of the difference in effect reflects the significance of the corresponding z-score (see Methods): red for P< 3.2x10⁻⁴ (correction for multiple testing), blue for P<0.05 and black for P>0.05.

Fig 3. Distribution of allergic disease age-of-onset as a function of a polygenic risk score (PRS) for allergic disease in UK Biobank participants who reported suffering from a single disease (asthma only, hay fever only and eczema only).

The PRS of each individual was calculated based on 136 SNPs that were associated with allergic disease risk in our recent GWAS [22]. The mean and median of each distribution are shown in red and blue, respectively.

Fig 4. Summary of results from the multivariate analysis of allergic disease age-of-onset and allergic disease case-control status.

The GWAS of allergic disease age-of-onset was performed in the UK Biobank study (n = 117,130) as described in the main text. The GWAS of allergic disease case-control status included 360,838 individuals, has reported recently [22]. Single-SNP results from each GWAS were adjusted for the top independent associations (P<3x10^-8) identified and then multivariate analysis was performed using metaUSAT [33]. We identified 281 variants with a multivariate P<3x10^-8 (red circles), including 26 that were in low LD (r²<0.05) with each other and so that are likely to represent statistically independent associations.