We integrate systematic variant identification by deep high-throughput DNA sequencing with ACMG Guidelines for pathogenicity assignments.
Detailed clinical information, statistical and structural modelling all contribute to a framework to better prognosticate and treat HHT.
Hereditary hemorrhagic telangiectasia (HHT) is a vascular dysplasia inherited as an autosomal dominant trait. Care delivery is impeded by requirements for laborious, repeated phenotyping, and gaps in knowledge regarding the relationships between causal DNA variants in ENG, ACVRL1, SMAD4 and GDF2, and clinical manifestations. To address, we analysed DNA samples from 183 previously uncharacterised, unrelated HHT and suspected HHT cases using the ThromboGenomics high-throughput sequencing platform. We identified 168 heterozygous variants, 127 unique. Applying modified ACMG Guidelines, 106 were classified as pathogenic/likely pathogenic, 21 as non-pathogenic (variants of uncertain significance/benign). Unlike the protein products of ACVRL1 and SMAD4, the extracellular ENG amino acids are not strongly conserved. Our inferences of the functional consequences of causal variants in ENG were therefore informed by the crystal structure of endoglin. We then compared the accuracy of predictions of the causal gene blinded to the genetic data using two approaches: subjective clinical predictions and statistical predictions based on eight Human Phenotype Ontology (HPO) terms. Both approaches had some predictive power but they were insufficiently accurate to be used clinically in isolation from genetic testing. The distributions of red cell indices from larger HHT and control populations differed by causal gene but not sufficiently for clinical use in isolation of genetic data. We conclude that parallel sequencing of the four known HHT genes, MDT review of variant calls sequencing results in the context of detailed clinical information, and statistical and structural modelling are all required to provide a framework to better prognosticate and treat HHT.