Single‐Cell Reconstruction of Cellular Heterogeneity of Congenital Heart Disease

Abstract

Congenital heart disease (CHD) involves cardiovascular malformations and, are one of the most common type of birth defect. The estimated prevalence ranges from ~1‐3% of live births and it causes significant mortality worldwide. Although etiology and pathophysiology of CHD remains elusive, genetic factors are known to be a major contributor. In this study, we aim at deciphering the genomic, transcriptomic, and proteomic landscape of the mutations associated with CHD. We collected 14209 SNVs, and 63 CNVs representing a sample size of 3,408 individuals, from 58 different articles published between January 2000 and December 2020. We identified 6,641 genes impacted by these mutations of which the MYH6, GATA6, NOTCH1, OBSCN and PTPN11 harbour the most number of recurrent mutations. We observed a high prevalence of early onset and male subjects with CHD, carrying a mutation. Stringent downstream meta‐analysis will be performed on this preliminary dataset. We plan to first comprehensively annotate the collected mutations using ANNOVAR and GenomeArc Analytics. The mutations will be then classified on the basis of American College of Medical Genetics (ACMG) guidelines to retain clinically relevant (pathogenic, likely pathogenic and variant of unknown significance) rare mutations. Next, we will analyse the mutation hotspots using 3D protein structures to determine domains which are most affected by these mutations. Furthermore, we will investigate the spatiotemporal developmental (prenatal to adult) human heart single‐cell OMICs (transcriptome and proteome) datasets in order to identify CHD associated cell types. Our analysis will detect cell types where marker genes are enriched with clinically relevant mutations. Our study aims to uncover the genetic and cellular heterogeneity of CHD which will aid precision diagnosis and therapeutics.