Human phenotype ontology annotation and cluster analysis for pulmonary atresia to unravel clinical outcomes.

Abstract

BackgroundPulmonary atresia (PA) is a heterogeneous congenital heart defect and ventricular septal defect (VSD) is the most vital factor for the conventional classification of PA patients. The simple dichotomy could not fully describe the cardiac morphologies and pathophysiology in such a complex disease. We utilized the Human Phenotype Ontology (HPO) database to explore the phenotypic patterns of PA and the phenotypic influence on prognosis.MethodsWe recruited 786 patients with diagnoses of PA between 2008 and 2016 at Fuwai Hospital. According to cardiovascular phenotypes of patients, we retrieved 52 HPO terms for further analyses. The patients were classified into three clusters based on unsupervised hierarchical clustering. We used Kaplan–Meier curves to estimate survival, the log-rank test to compare survival between clusters, and univariate and multivariate Cox proportional hazards regression modeling to investigate potential risk factors.ResultsAccording to HPO term distribution, we observed significant differences of morphological abnormalities in 3 clusters. We defined cluster 1 as being associated with Tetralogy of Fallot (TOF), VSD, right ventricular hypertrophy (RVH), and aortopulmonary collateral arteries (ACA). ACA was not included in the cluster classification because it was not an HPO term. Cluster 2 was associated with hypoplastic right heart (HRH), atrial septal defect (ASD) and tricuspid disease as the main morphological abnormalities. Cluster 3 presented higher frequency of single ventricle (SV), dextrocardia, and common atrium (CA). The mortality rate in cluster 1 was significantly lower than the rates in cluster 2 and 3 (p = 0.04). Multivariable analysis revealed that abnormal atrioventricular connection (AAC, p = 0.011) and persistent left superior vena cava (LSVC, p = 0.003) were associated with an increased risk of mortality.ConclusionsOur study reported a large cohort with clinical phenotypic, surgical strategy and long time follow-up. In addition, we provided a precise classification and successfully risk stratification for patients with PA.