# Identification of DNA methylation biomarkers in amniotic fluid for prenatal detection of congenital heart disease (CHD)

**Authors:** Weilun Zuo, Jianwei Rao, Yaqin Ma, Shiyu Sun, Xiaoqin He, Han Yang, Jiali Cao, Qichang Wu, Huiming Ye

PMC · DOI: 10.1186/s13148-026-02090-4 · Clinical Epigenetics · 2026-02-26

## TL;DR

This study identifies DNA methylation biomarkers in amniotic fluid that can help detect congenital heart disease before birth.

## Contribution

The study introduces a new methylation-based panel for prenatal detection of CHD using amniotic fluid samples.

## Key findings

- Differential methylation patterns were found in amniotic fluid DNA between CHD and normal fetuses.
- A four-marker methylation panel from the PCNT gene showed strong diagnostic performance in multiple cohorts.
- The panel demonstrated high specificity and moderate sensitivity for detecting both simple and complex CHD.

## Abstract

Congenital heart disease (CHD) is the most common birth defect worldwide, affecting approximately 1% of live births. Improving the prenatal diagnosis of CHD remains an urgent clinical priority. In this study, we aimed to screen and validate amniotic fluid methylation biomarkers from clinical cases for the prenatal diagnosis of CHD.

A total of 135 amniotic fluid samples (80 cases and 55 controls) collected during the second trimester were included and divided into three independent cohorts. Cohort I was used to screen for differentially methylated regions (DMRs) by whole-genome bisulfite sequencing (WGBS) during the discovery phase. The above candidate DMRs were detected using target bisulfite sequencing (TBS) in an independent cohort II. The final biomarker set was selected according to adjusted P-values, sequencing depth, group differences, and relevance to cardiac development and key metabolic pathways. The model was built using individual biomarker cut-off values. Its predictive performance and generalizability were evaluated in an independent cohort III.

WGBS and unsupervised clustering analysis revealed differential methylation patterns in amniotic fluid DNA between the CHD and normal groups. The 52 DMRs (adj P < 0.01) were identified by screening with the above factors. Then, the analysis of cohort II via TBS identified 25 differentially methylated sites. From these, a predictive model was constructed using the four hypermethylated sites with the greatest group differences, all located within a single intron of the PCNT gene. Validation in an independent cohort III identified 11 differentially methylated sites, with an 8-site overlap with cohort II. Notably, 7 of the overlapping sites were associated with PCNT, highlighting strong reproducibility. This model showed consistent and decent performance in the cohort III (specificity: 95.65%, sensitivity: 70.45%), the cohort II (specificity: 73.08%, sensitivity: 83.33%), as well as in simple congenital heart disease (SCHD) (specificity: 83.67%, sensitivity: 76.09%) and complex congenital heart disease (CCHD) sample sets (specificity: 83.67%, sensitivity: 75.00%).

DNA methylation profiles in amniotic fluid differ significantly between fetuses with CHD and normal fetuses. The methylation of PCNT was suggested to be associated with the pathogenesis of CHD. Furthermore, the four-marker methylation panel identified in this study demonstrated decent efficacy in distinguishing fetuses with CHD, highlighting its promise as a new adjunctive diagnostic approach for prenatal CHD in high-risk pregnant women.

The online version contains supplementary material available at 10.1186/s13148-026-02090-4.

## Linked entities

- **Genes:** PCNT (pericentrin) [NCBI Gene 5116]
- **Diseases:** congenital heart disease (MONDO:0005453)

## Full-text entities

- **Genes:** PCNT (pericentrin) [NCBI Gene 5116] {aka KEN, MOPD2, PCN, PCNT2, PCNTB, PCTN2}
- **Diseases:** CCHD (MESH:D006330), birth defect (MESH:D000014)
- **Species:** Homo sapiens (human, species) [taxon 9606]

## Full text

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## Figures

5 figures with captions in the complete paper: https://tomesphere.com/paper/PMC13041326/full.md

## References

7 references — full list in the complete paper: https://tomesphere.com/paper/PMC13041326/full.md

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Source: https://tomesphere.com/paper/PMC13041326