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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,*

1 Department of Ultrasound Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China
2 Clinical Research Center for Medical Imaging in Hubei Province, Huazhong University of Science and Technology, Wuhan, 430022, China
3 Hubei Province Key Laboratory of Molecular Imaging, Huazhong University of Science and Technology, Wuhan, 430022, China

* Corresponding Authors: Haiyan Cao. Email: email; Jing Wang. Email: email
# These authors contributed equally to this work

Congenital Heart Disease 2025, 20(2), 213-229. https://doi.org/10.32604/chd.2025.064950

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: Eight Hub genes were identified using the WGCNA network and PPI network, and functional enrichment analysis revealed that GJA1, RUNX2, PTK7, PRICKLE1, and SFRP1 were involved in the morphogenesis of an epithelium, and dysregulation of the signaling were also found in the other two TOF datasets. Furthermore, the study found that the promoters of GJA1, RUNX2, PTK7, and PRICKLE1 genes were hypermethylated and that GJA1 and SFRP1 are highly expressed in mouse second heart field cells and neural crest cells, and the latter is expressed in human embryonic outflow tract cells. Since RUNX2 was not expressed in human and mouse embryonic hearts, GJA1, PTK7, PRICKLE1, and SFRP1 were ultimately identified as TOF candidate genes. Conclusion: Based on the WGCNA network and various bioinformatics analysis approaches, we screened 4 TOF candidate pathogenic genes, and found that the signaling pathways related to the morphogenesis of an epithelium may be involved in the pathogenesis of TOF.

Keywords

Tetralogy of Fallot; gene regulatory networks; weighted gene co-expression network analysis; protein-protein interaction network; disease candidate genes

Supplementary Material

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Cite This Article

APA Style
Shi, J., Wang, Z., Bai, Y., Li, S., Zhang, X. et al. (2025). Bioinformatics and In-Silico Findings Reveal Candidate Genes for Tetralogy of Fallot via Integrative Multi-Omics Data. Congenital Heart Disease, 20(2), 213–229. https://doi.org/10.32604/chd.2025.064950
Vancouver Style
Shi J, Wang Z, Bai Y, Li S, Zhang X, Liu T, et al. Bioinformatics and In-Silico Findings Reveal Candidate Genes for Tetralogy of Fallot via Integrative Multi-Omics Data. Congeni Heart Dis. 2025;20(2):213–229. https://doi.org/10.32604/chd.2025.064950
IEEE Style
J. Shi et al., “Bioinformatics and In-Silico Findings Reveal Candidate Genes for Tetralogy of Fallot via Integrative Multi-Omics Data,” Congeni. Heart Dis., vol. 20, no. 2, pp. 213–229, 2025. https://doi.org/10.32604/chd.2025.064950



cc Copyright © 2025 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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