Topological data analysis reveals genotype–phenotype relationships in primary ciliary dyskinesia

Abstract

BackgroundPrimary ciliary dyskinesia (PCD) is a heterogeneous inherited disorder caused by mutations in approximately 50 cilia-related genes. PCD genotype–phenotype relationships have mostly arisen from small case series because existing statistical approaches to investigating relationships have been unsuitable for rare diseases.MethodsWe applied a topological data analysis (TDA) approach to investigate genotype–phenotype relationships in PCD. Data from separate training and validation cohorts included 396 genetically defined individuals carrying pathogenic variants in PCD genes. To develop the TDA models, 12 clinical and diagnostic variables were included. TDA-driven hypotheses were subsequently tested using traditional statistics.ResultsDisease severity at diagnosis, measured by forced expiratory volume in 1 s (FEV1) z-score, was significantly worse in individuals with CCDC39 mutations (compared to other gene mutations) and better in those with DNAH11 mutations; the latter also reported less neonatal respiratory distress. Patients without neonatal respiratory distress had better preserved FEV1 at diagnosis. Individuals with DNAH5 mutations were phenotypically diverse. Cilia ultrastructure and beat pattern defects correlated closely to specific causative gene groups, confirming these tests can be used to support a genetic diagnosis.ConclusionsThis large scale, multi-national study presents PCD as a syndrome with overlapping symptoms and variations in phenotype according to genotype. TDA modelling confirmed genotype–phenotype relationships reported by smaller studies (e.g. FEV1 worse with CCDC39 mutation) and identified new relationships, including FEV1 preservation with DNAH11 mutations and diversity of severity with DNAH5 mutations.