Imputation provides an opportunity to study filaggrin (FLG) null mutations in large population cohorts that lack bespoke genotyping [version 2; peer review: 2 approved]

Abstract

Background Null mutations within the filaggrin (FLG) gene are established genetic risk factors for atopic dermatitis. Studies of FLG have typically used sequencing or bespoke genotyping. Large-scale population cohorts with genome-wide imputed data offer powerful genetic analysis opportunities, but bespoke FLG genotyping is often not feasible in such studies. Therefore, we aimed to determine the quality of selected FLG null genotype data extracted from genome-wide imputed sources, focussing on UK population data. Methods We compared the allele frequencies of three FLG null mutations that could be detected by imputation (p.Arg501Ter, p.Arg2447Ter and p.Ser3247Ter; commonly referred to as R501X, R2447X and S3247X respectively) in directly genotyped and genome-wide imputed data in the ALSPAC cohort. Logistic regression analysis was used to test the association of atopic dermatitis with imputed and genotyped FLG null mutations in ALSPAC and UK Biobank to investigate the usefulness of imputed FLG data. Results The three FLG null mutations appear to be well imputed in datasets that use the Haplotype Reference Consortium (HRC) for imputation (0.3% discordance compared with directly genotyped data). However, a greater proportion of null alleles failed imputation compared to wild-type alleles. Despite the calling of FLG mutations in imputed data being imperfect, they are still strongly associated with atopic dermatitis (p-values between 7x10-10 and 5x10-75 in UK Biobank). Conclusions HRC imputed data appears to be adequate for UK population-based genetic analysis of selected FLG null mutations (p.Arg501Ter, p.Arg2447Ter and p.Ser3247Ter).

Keywords

• Filaggrin
• genotyping
• ALSPAC
• UK Biobank
• eng