Clinical implications of experimental analyses of AID function on predictive computational tools: Challenge of missense variants.

Abstract

Due to the increased usage of high throughput sequencing for the diagnosis of genetically inherited disorders, it is vital to evaluate the risk of new variants and novel genes before accepting them in clinical practice. However, discordant in silico and in vitro results, challenge estimations of the effect of an identified genetic variant. We aimed to comprehensively evaluate pathogenic and polymorphic variants using the activation-induced-cytidine-deaminase (AICDA) gene as a model. We systematically searched and identified patients with confirmed AICDA-mutations. Population-based-databases were screened for germline-polymorphic-AICDA-variants. Activity of AICDA-mutant and severity of the clinical and immunologic-phenotype were showed comparing 108 population-based-variants with 48 pathogenic mutations (12 overlapping-variants). Discordant predictions of different algorithms were observed on average in 38% of the population-database variants, mainly for missense mutations. Functional activity in mutations observed only in patients was significantly lower than variants in the population databases and overlapping-variants between patients and the general-population. Surprisingly, overlapping-variants had an even higher functional activity than the most common polymorphic-variants; however, their pathogenicity was still distinguishable when their function was compared with wild-type AICDA. Classifications of genetic variants cannot readily be translated into a clinical implication. Combined databases of functional and computational assays should therefore be developed for each specific gene.