HTAADVar: Aggregation and fully automated clinical interpretation of genetic variants in heritable thoracic aortic aneurysm and dissection

Abstract

Purpose: Early detection and pathogenicity interpretation of disease-associated variants are crucial but challenging in molecular diagnosis, especially for insidious and life-threatening diseases, such as heritable thoracic aortic aneurysm and dissection (HTAAD). In this study, we developed HTAADVar, an unbiased and fully automated system for the molecular diagnosis of HTAAD.

Methods: We developed HTAADVar (http://htaadvar.fwgenetics.org) under the American College of Medical Genetics and Genomics/Association for Molecular Pathology framework, with optimizations based on disease- and gene-specific knowledge, expert panel recommendations, and variant observations. HTAADVar provides variant interpretation with a self-built database through the web server and the stand-alone programs.

Results: We constructed an expert-reviewed database by integrating 4373 variants in HTAAD genes, with comprehensive metadata curated from 697 publications and an in-house study of 790 patients. We further developed an interpretation system to assess variants automatically. Notably, HTAADVar showed a multifold increase in performance compared with public tools, reaching a sensitivity of 92.64% and specificity of 70.83%. The molecular diagnostic yield of HTAADVar among 790 patients (42.03%) also matched the clinical data, independently demonstrating its good performance in clinical application.

Conclusion: HTAADVar represents the first fully automated system for accurate variant interpretation for HTAAD. The framework of HTAADVar could also be generalized for the molecular diagnosis of other genetic diseases.

Keywords: Bioinformatics; Clinical significance; Genetic variant interpretation; Next-generation sequencing; Thoracic aortic aneurysm and dissection.