Genotype and functional correlates of disease phenotype in deficiency of adenosine deaminase 2 (DADA2)

Abstract

Background: Deficiency of adenosine deaminase 2 (DADA2) is a syndrome with pleiotropic manifestations including vasculitis and hematologic compromise. A systematic definition of the relationship between adenosine deaminase 2 (ADA2) mutations and clinical phenotype remains unavailable.

Objective: We sought to test whether the impact of ADA2 mutations on enzyme function correlates with clinical presentation.

Methods: Patients with DADA2 with severe hematologic manifestations were compared with vasculitis-predominant patients. Enzymatic activity was assessed using expression constructs reflecting all 53 missense, nonsense, insertion, and deletion genotypes from 152 patients across the DADA2 spectrum.

Results: We identified patients with DADA2 presenting with pure red cell aplasia (n = 5) or bone marrow failure (BMF, n = 10) syndrome. Most patients did not exhibit features of vasculitis. Recurrent infection, hepatosplenomegaly, and gingivitis were common in patients with BMF, of whom half died from infection. Unlike patients with DADA2 with vasculitis, patients with pure red cell aplasia and BMF proved largely refractory to TNF inhibitors. ADA2 variants associated with vasculitis predominantly reflected missense mutations with at least 3% residual enzymatic activity. In contrast, pure red cell aplasia and BMF were associated with missense mutations with minimal residual enzyme activity, nonsense variants, and insertions/deletions resulting in complete loss of function.

Conclusions: Functional interrogation of ADA2 mutations reveals an association of subtotal function loss with vasculitis, typically responsive to TNF blockade, whereas more extensive loss is observed in hematologic disease, which may be refractory to treatment. These findings establish a genotype-phenotype spectrum in DADA2.

Keywords: Adenosine deaminase 2; DADA2; bone marrow failure; pure red cell aplasia; vasculitis.

Figure 1.. Analysis of ADA2 mutations by patient phenotype.

A) Schematic of literature review and case selection for mutation analysis. B) Venn diagram of unique ADA2 mutations illustrating overlaps between disease phenotypes. C) Display of ADA2 gene structure illustrating the distribution of mutations associated with different phenotypes. Shared mutations are displayed by color coding. D) Circle charts illustrating the types of mutations associated with each phenotype. Analysis of individual alleles is displayed in the upper panel while analysis of homozygous individuals is shown in the lower panel.

Figure 2.. Analysis of common mutations associated with each disease phenotype.

A) Histogram display of allelic count for the most common mutations associated with each disease phenotype. All cases in the current cohort and those selected from literature review were included. B) Phenotype distribution of the most common mutation association with vasculitis (G47R), PRCA (G358R) and BMF (R169Q).

Figure 3.. Functional analysis of ADA2 mutations in vitro.

A) ADA2 enzyme activity of individual mutant constructs sorted by mutation type. B) ADA2 enzyme activity of individual mutant constructs sorted by disease phenotype. C) Stratification of mutations within each disease phenotype according to various cut-off values of residual ADA2 enzyme activity. D) Bar graph display of residual enzyme activity for individual mutations associated with each disease phenotype. Dotted line in all panels represent the cut-off value of 3% residual activity. For all panels, results are normalized as percentage of residual activity relative to wildtype (WT) ADA2. Each dot or bar represents the average of results from three independent experiments and error bar represents standard deviation.

Figure 4.. Genotype to phenotype analysis using patient mutation configurations.

Distribution of patients with vasculitis, PRCA or BMF phenotype in genotype categories assigned based on ADA2 mutation type and residual enzymatic activity of missense mutations (p < 0.0001, Chi-square test). Bars represent the percentage of patients of the given phenotype.