Dušan Ušjak1, Martina Mia Mitić1, Maja Milošević2, Sofija Dunjić Manevski1, Marija Cumbo1, Branko Tomić1, Petar Otašević2, Milovan Bojić2, Ivana Petrović2 and Valentina Đorđević1*
1 Institute of Molecular Genetics and Genetic Engineering, University of Belgrade, Belgrade, Serbia
2 Institute for Cardiovascular Diseases Dedinje, Belgrade, Serbia
valentina [at] imgge.bg.ac.rs
Abstract
Unicuspid aortic valve (UAV) disease is a congenital heart defect that can lead to severe cardiovascular complications. This study aimed to identify genetic variants contributing to UAV disease by integrating whole exome sequencing (WES) data with single-cell transcriptomics of the developing human heart.
WES was conducted on 28 subjects, including 9 with UAV and 19 non-affected family members by using protocol of the Beijing Genomics Institute (BGI). To refine the candidate gene set, previously published single-cell RNA sequencing data from 6.5-7 weeks post-conception (PCW) embryonic hearts were utilized. The cell type and differential gene expression analyses were performed using Python, employing libraries such as Scanpy and scVI. WES data were filtered for high-impact and damaging missense variants, as predicted by three independent in silico tools, with an allele frequency of less than 10% in the GnomAD database, in genes that were notably expressed in cell types involved in aortic valve development. Subsequently, g:Profiler was utilized to perform functional profiling of the candidate genes and principal component analysis (PCA) was conducted to identify clustering patterns among the UAV patients.
The analysis identified 308 candidate variants in 283 genes, the majority of which are crucial in maintaining and organizing the extracellular matrix, supporting cellular adhesion and signaling, and contributing to the development of anatomical structures. Among these, 62 genes had damaging variants present in at least two UAV patients. Additionally, 15 novel variants were identified, not previously reported in the GnomAD database. Eleven variants were classified as pathogenic or likely pathogenic according to ClinVar or ACMG (American College of Medical Genetics and Genomics) criteria. Further, the PCA results revealed significant genetic variation across the UAV patients, with some patients showing closer proximity in affected gene profiles, suggesting potential clustering.
In conclusion, the approach of integrating WES data with existing single-cell transcriptomics data provided valuable insights into the genetic underpinnings of UAV disease. The study identified several novel candidate genes and variants, enhancing our understanding of the genetic basis of this congenital heart defect and potentially guiding future research, and diagnostic or therapeutic strategies.
Keywords: congenital heart disease, unicuspid aortic valves, genetic variants, whole exome sequencing, single-cell transcriptomics