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 (r g =-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.

Findings and insights from the genetic investigation of age of first reported occurrence for complex disorders in the UK Biobank and FinnGen

“…The growth of biobank-scale datasets may reveal more genetic risk factors that can modify age of onset and may represent new therapeutic targets. On the genome-wide scale, our observation that earlier onset is associated with a greater polygenic loading for disease is consistent with what has long been hypothesized for polygenic disorders and has been increasingly observed in individual GWAS studies 13,14,21 . For Mendelian disorders, studies have also shown that its polygenic background can modify the age of disease occurrence among those with rare monogenic mutations 22,23 .…”

Genome-wide association studies

“…A notable example is the UK Biobank, which includes data from approximately 500,000 individuals 76 and has enabled well-powered GWAS of hundreds of quantitative traits, including anthropometric traits 77 , blood cell traits 78 , metabolites 79 , cognitive traits 80 , brain imaging traits 81 and depressive symptoms (as described in ref. 82 ), as well as boosting sample sizes for GWAS of common diseases [83][84][85] .…”

Accounting for age of onset and family history improves power in genome-wide association studies

“…As more genetic data with linked electronic health records become available to researchers, we expect methods that account for additional health information, such as LT-FHþþ, to become even more beneficial.Currently, most case-control GWASs are conducted with a regression model where the outcome is the case-control status or occasionally the age of onset of disease. 20 In this paper, we have opted for using the phrase age of onset over age at first diagnosis because they commonly refer to the same underlying thing, i.e., when a diagnosis is given. Recently, researchers have proposed several methods that leverage additional information to improve the power to detect genetic associations without having to increase the number of genotyped individuals.…”