Multi-omics integration analysis identifies pathogenic candidate genes of congenital heart defects with vascular malformation

Abstract Background Congenital heart defects (CHD) with vascular malformation harbors numerous genetic and epigenetic aberrations of DNA copy numbers and methylation. Proteomic deregulation by the aberrations plays key driver roles in heterogeneous progression of CHD. However, it still remains largely unknown about integrative analysis of genetic, epigenetic regulation and proteome in CHD. Purpose We employed a multi-omics approach to explore pathogenic candidate genes in CHD with vascular malformation. Methods Previously, we gathered WES data for 216 CHD patients with vascular malformation and 100 healthy controls. Meanwhile, we carried out DNA methylation analysis from 11 patients and 5 controls. Here, we profile proteomics of vascular tissues from 11 patients and 5 controls. Integration analysis of DNA copy-number-correlated (CNVcor) genes, methylation-correlated (METcor) genes and differentially proteins reveal the innovative and crucial pathogenetic genes. We then detected spatiotemporal expression patterns of candidate genes in zebrafish embryos using in situ hybridization and qPCR, and verified the roles in vascular development by morpholino-mediated gene knockdown. Results 90 differentially expressed proteins (DEPs) were obtained using proteomics and were mainly related to cell adhesion and migration, angiogenesis, amino acid metabolism, and HIF-1 signaling pathway through GO and KEGG pathway enrichment analysis. 15 hub proteins were identified by WGCNA analysis (Fig 1). Additionally, we found that the frequencies of the aberrancies of the CNVcor genes were significantly correlated with the METcor genes (Fig 2 C). We obtained 1924 differentially CNVcor genes and 952 differentially METcor genes. Then, we computed the Pearson’s correlation coefficients of all three-omics by pairwise comparison and found that the distribution of correlations was bimodal (Fig 2 D). Meanwhile, 28 overlapped genes were observed among three-omics. We screened out 11 candidate genes (TIMP1, BGN, LTBP1, AKR1C3, LOXL3, MAOA, MAOB, GNA12, IFI30, CNTNAP1, IGF2BP1) according to the node degree of PPI network analysis between 28 genes and known vascular development related genes. We further figured out LOXL3, MAOA, CNTNAP1 and IGF2BP1 are the novel important genes for vascular malformation, of which CNTNAP1 is the joint gene of three-omics. Through expression patterns and gene knockdown in zebrafish embryos, we revealed that LOXL3, MAOA, CNTNAP1 and IGF2BP1 affect vascular development (Fig 2 E-G). Conclusions We identify novel key candidate genes (LOXL3, MAOA, CNTNAP1 and IGF2BP1) potentially related to CHD with vascular malformation and elucidate the possible molecular pathogenesis of CHD. Our multi-omics integrative analysis provides new insights on the multi-layered etiology of CHD, which might be helpful in developing clinical diagnosis and precaution for CHD.Figure 1Figure 2