Cardiovascular Phenotypes Profiling for L-Transposition of the Great Arteries and Prognosis Analysis

Qiyu He; Huayan Shen; Xinyang Shao; Wen Chen; Yafeng Wu; Rui Liu; Shoujun Li; Zhou Zhou

doi:10.3389/fcvm.2021.781041

Cardiovascular Phenotypes Profiling for L-Transposition of the Great Arteries and Prognosis Analysis

Front Cardiovasc Med. 2022 Jan 21:8:781041. doi: 10.3389/fcvm.2021.781041. eCollection 2021.

Authors

Qiyu He¹, Huayan Shen², Xinyang Shao², Wen Chen², Yafeng Wu³, Rui Liu¹, Shoujun Li¹, Zhou Zhou²

Affiliations

¹ Pediatric Cardiac Center, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
² Department of Laboratory Medicine, National Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
³ Center for Applied Statistics, School of Statistics, Renmin University of China, Beijing, China.

Abstract

Objectives: Congenitally corrected transposition of the great arteries (ccTGA) is a rare and complex congenital heart disease with the characteristics of double discordance. Enormous co-existed anomalies are the culprit of prognosis evaluation and clinical decision. We aim at delineating a novel ccTGA clustering modality under human phenotype ontology (HPO) instruction and elucidating the relationship between phenotypes and prognosis in patients with ccTGA.

Methods: A retrospective review of 270 patients diagnosed with ccTGA in Fuwai hospital from 2009 to 2020 and cross-sectional follow-up were performed. HPO-instructed clustering method was administered in ccTGA risk stratification. Kaplan-Meier survival, Landmark analysis, and cox regression analysis were used to investigate the difference of outcomes among clusters.

Results: The median follow-up time was 4.29 (2.07-7.37) years. A total of three distinct phenotypic clusters were obtained after HPO-instructed clustering with 21 in cluster 1, 136 in cluster 2, and 113 in cluster 3. Landmark analysis revealed significantly worse mid-term outcomes in all-cause mortality (p = 0.021) and composite endpoints (p = 0.004) of cluster 3 in comparison with cluster 1 and cluster 2. Multivariate analysis indicated that pulmonary arterial hypertension (PAH), atrioventricular septal defect (AVSD), and arrhythmia were risk factors for composite endpoints. Moreover, the surgical treatment was significantly different among the three groups (p < 0.001) and surgical strategies had different effects on the prognosis of the different phenotypic clusters.

Conclusions: Human phenotype ontology-instructed clustering can be a potentially powerful tool for phenotypic risk stratification in patients with complex congenital heart diseases, which may improve prognosis prediction and clinical decision.

Keywords: congenitally corrected transposition of the great arteries; human phenotype ontology; prognosis; risk stratification; surgery.