Hostname: page-component-89b8bd64d-shngb Total loading time: 0 Render date: 2026-05-09T14:47:50.138Z Has data issue: false hasContentIssue false

Comprehensive Multiomics Analysis of Monozygotic Twin Discordant for Double Outlet Right Ventricle

Published online by Cambridge University Press:  15 December 2023

Zhen Liu
Affiliation:
National Center for Birth Defect Monitoring of China, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, Chengdu, Sichuan, China
Nana Li
Affiliation:
National Center for Birth Defect Monitoring of China, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, Chengdu, Sichuan, China
Xiaoyu Pan
Affiliation:
Guangdong Province Key Laboratory of Genome, BGI-Shenzhen, Shenzhen, Guangdong, China Shenzhen Municipal Key Laboratory of Birth Defects Screening and Engineering, Shenzhen, Guangdong, China
Jun Li
Affiliation:
Department of Ultrasonic Diagnosis, Xijing Hospital, Xi’ an, Shanxi, China
Shengli Li
Affiliation:
Department of Ultrasound, Shenzhen Maternity & Child Healthcare Hospital, Shenzhen, Guangdong, China
Qintong Li
Affiliation:
Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, Chengdu, Sichuan, China Laboratory of Stem Cell & Tissue Engineering, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China
Ping Li
Affiliation:
Longquanyi District Maternal and Child Health Hospital, Chengdu, Sichuan, China
Ying Deng
Affiliation:
National Center for Birth Defect Monitoring of China, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China
Fang Chen
Affiliation:
Guangdong Province Key Laboratory of Genome, BGI-Shenzhen, Shenzhen, Guangdong, China Shenzhen Municipal Key Laboratory of Birth Defects Screening and Engineering, Shenzhen, Guangdong, China
Hui Jiang
Affiliation:
Guangdong Province Key Laboratory of Genome, BGI-Shenzhen, Shenzhen, Guangdong, China Shenzhen Municipal Key Laboratory of Birth Defects Screening and Engineering, Shenzhen, Guangdong, China
Wei Wang
Affiliation:
Guangdong Province Key Laboratory of Genome, BGI-Shenzhen, Shenzhen, Guangdong, China Shenzhen Municipal Key Laboratory of Birth Defects Screening and Engineering, Shenzhen, Guangdong, China
Dezhi Mu
Affiliation:
Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, Chengdu, Sichuan, China Department of Pediatrics, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China
Ping Yu*
Affiliation:
National Center for Birth Defect Monitoring of China, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, Chengdu, Sichuan, China
Jun Zhu*
Affiliation:
National Center for Birth Defect Monitoring of China, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, Chengdu, Sichuan, China
*
Corresponding authors: Ping Yu; Email: yup@scu.edu.cn; Jun Zhu; Email: zhujun028@163.com)
Corresponding authors: Ping Yu; Email: yup@scu.edu.cn; Jun Zhu; Email: zhujun028@163.com)

Abstract

The objective of this study was to understand and measure epigenetic changes associated with the occurrence of CHDs by utilizing the discordant monozygotic twin model. A unique set of monozygotic twins discordant for double-outlet right ventricles (DORVs) was used for this multiomics study. The cardiac and muscle tissue samples from the twins were subjected to whole genome sequencing, whole genome bisulfite sequencing, RNA-sequencing and liquid chromatography-tandem mass spectrometry analysis. Sporadic DORV cases and control fetuses were used for validation. Global hypomethylation status was observed in heart tissue samples from the affected twins. Among 36,228 differentially methylated regions (DMRs), 1097 DMRs involving 1039 genes were located in promoter regions. A total of 419 genes, and lncRNA–mRNA pairs involved 30 genes, and 62 proteins were significantly differentially expressed. Multiple omics integrative analysis revealed that five genes, including BGN, COL1A1, COL3A1, FBLN5, and FLAN, and three pathways, including ECM-receptor interaction, focal adhesion and TGF-β signaling pathway, exhibited differences at all three levels. This study demonstrates a multiomics profile of discordant twins and explores the possible mechanism of DORV development. Global hypomethylation might be associated with the risk of CHDs. Specific genes and specific pathways, particularly those involving ECM–receptor interaction, focal adhesion and TGF–β signaling, might be involved in the occurrence of CHDs.

Information

Type
Article
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2023. Published by Cambridge University Press on behalf of International Society for Twin Studies
Figure 0

Figure 1. Comparison of DNA methylation levels between the MZ twin and the distribution of DMR. (A) Overview the average genome-scale DNA methylation levels by WGBS. (B) The average genome-scale DNA methylation levels by LC-MS/MS. (C) The differences of methylation levels in genomic elements by WGBS. (D) The distribution of DMR in promoter elements. (E) The hypomethylation of COL1A1 and THBS3 by BSP.

Figure 1

Table 1. Pathway analysis of promoter DMR associated genes

Figure 2

Figure 2. The expression level of COL1A1and THBS3 by qPCR data were confirmed to be consistent with RNA-Seq results.

Figure 3

Table 2. Pathway analysis of differentially expressed genes

Figure 4

Table 3. Pathway analysis of differential protein-encoding genes

Figure 5

Figure 3. The three common pathway and genes at three levels.

Figure 6

Figure 4. The methylation and expression validation of COL1A1 and THBS3. A: The methylation level in sporadic cases and controls. B: The methylation and mRNA expression in cell model.

Supplementary material: File

Liu et al. supplementary material

Liu et al. supplementary material

Download Liu et al. supplementary material(File)
File 1.6 MB