Comprehensive Clinical Diagnostic Pipelines Reveal New Variants in Alpha-1 Antitrypsin Deficiency

Alpha-1 antitrypsin deficiency (AATD) is an underdiagnosed disorder associated with mutations in the SERPINA1 gene encoding alpha-1 antitrypsin (AAT). Severe AATD can manifest as pulmonary emphysema and progressive liver disease. Besides the most common pathogenic variants S (E264V) and Z (E342K), many rarer genetic variants of AAT have been found in patients and in the general population. Here we report a panel of new SERPINA1 variants, including 4 null and 16 missense alleles, identified among a cohort of individuals with suspected AATD whose phenotypic follow-up showed inconclusive or atypical results. Because the pathogenic significance of the missense variants was unclear purely on the basis of clinical data, the integration of computational, biochemical, and cellular studies was used to define the associated risk of disease. Established pathogenicity predictors and structural analysis identified a panel of candidate damaging mutations that were characterized by expression in mammalian cell models. Polymer formation, intracellular accumulation, and secretory efficiency were evaluated experimentally. Our results identified two AAT mutants with a Z-like polymerogenic severe deficiency profile (S-milano and M-campolongo) and threemilder variants (X-sarezzo, P-dublin, and C-tiberias). Overall, the experimentally determined behavior of the variants was in agreement with the pathogenicity scores of the REVEL (an ensemble method for predicting the pathogenicity of rare missense variants) predictor, supporting the utility of this bioinformatic tool in the initial assessment of newly identified amino acid substitutions of AAT. Our study, in addition to describing 20 new SERPINA1 variants, provides a model for a multidisciplinary approach to classification of rare AAT variants and their clinical impact on individuals with rare AATD genotypes.

Automated summary

This study reports a panel of new SERPINA1 variants and describes their classification and clinical impact in individuals with AATD. The integration of computational, biochemical, and cellular studies was used to determine the associated risk of disease. The experimental results support the utility of the REVEL predictor in the initial assessment of newly identified AAT variants.