Bioinformatics and In-Silico Findings Reveal Candidate Genes for Tetralogy of Fallot via Integrative Multi-Omics Data
Jiawei Shi1,2,3,#, Zhen Wang1,2,3,#, Ying Bai1,2,3, Shiying Li1,2,3, Xin Zhang1,2,3, Tianshu Liu1,2,3, Liu Hong1,2,3, Li Cui1,2,3, Yi Zhang1,2,3, Jing Ma1,2,3, Juanjuan Liu1,2,3, Jing Zhang1,2,3, Haiyan Cao1,2,3,*, Jing Wang1,2,3,*
Congenital Heart Disease, Vol.20, No.2, pp. 213-229, 2025, DOI:10.32604/chd.2025.064950
- 30 April 2025
Abstract Background: Tetralogy of Fallot (TOF), the predominant cyanotic congenital heart defect, arises from multifactorial gene-environment interactions disrupting cardiac developmental networks. This study investigated TOF-specific transcriptional alterations and identified high-confidence candidate genes. Methods: Based on GSE36761 transcriptome data, a weighted gene co-expression network analysis (WGCNA) and protein-protein interaction (PPI) network were conducted to identify TOF-related sub-network and Hub genes. The potential biological functions among these genes were revealed by enrichment analysis. Genetic, epigenetic and transcriptional alteration in the Hub genes were analyzed with leveraged public resources: a methylation dataset (GSE62629) and two single-cell datasets (EGAS00001003996 and GSE126128). Results:… More >