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Predictive value of epigenetic circulating free DNA (cfDNA) typing for cardiac function stratification in patients
Shida Cai1, Qingyuan Cai1, Chunwen Jia1
1Department of Cardiovascular Medicine, Zhongshan Hospital Affiliated to Xiamen University Xiamen 361000, Fujian, China.
Insights
Epigenetic markers in cell-free DNA (cfDNA) effectively stratify cardiac function in cardiovascular disease (CVD) patients. These noninvasive cfDNA epigenetic features, combined with clinical data, significantly enhance cardiac risk prediction.
Area of Science:
- Cardiovascular epigenetics
- Molecular diagnostics
- Biomarker discovery
Background:
- Cardiovascular disease (CVD) management requires accurate cardiac function stratification and risk prediction.
- Current methods may benefit from novel, noninvasive molecular markers.
- Circulating free DNA (cfDNA) offers a potential source for such biomarkers.
Purpose of the Study:
- To evaluate the utility of cfDNA epigenetic characteristics for cardiac function stratification in CVD patients.
- To assess the role of cfDNA epigenetics in predicting cardiovascular risk.
- To determine if cfDNA epigenetic markers can improve existing risk prediction models.
Main Methods:
- Retrospective analysis of 624 CVD patients categorized by NYHA classification (mild vs. severe).
- Assessment of genome-wide methylation levels, hypermethylation proportion, and "risk-type cfDNA".
- Development of logistic regression, Random Forest, and XGBoost models to identify predictors of severe cardiac dysfunction.
Main Results:
- Higher cfDNA methylation levels, hypermethylation proportion, and "risk-type cfDNA" were significantly associated with severe cardiac dysfunction (P < 0.05).
- cfDNA concentration independently predicted reduced risk of endpoint events (OR = 0.946, P = 0.0443).
- A combined model including cfDNA, LVEF, NT-proBNP, and age achieved an AUC of 0.994; machine learning identified age, cfDNA, and LVEF as key predictors.
Conclusions:
- cfDNA epigenetic characteristics correlate strongly with cardiac dysfunction severity in CVD patients.
- These epigenetic features show promise as noninvasive biomarkers for cardiac function stratification.
- Integrating cfDNA epigenetics with clinical indicators substantially enhances cardiovascular risk prediction accuracy.
Objective:
To evaluate the use of circulating free DNA (cfDNA) epigenetic characteristics in cardiac function stratification and risk prediction in patients with cardiovascular disease (CVD).
Methods:
This retrospective study included 624 CVD patients diagnosed from January 2023 to January 2025. Patients were grouped according to the New York Heart Association (NYHA) classification into mild (I-II) and severe (III-IV) cardiac insufficiency groups. Genome-wide methylation level, hypermethylation proportion, and "risk-type cfDNA" (defined by hypermethylation of cardioprotective gene promoters and hypomethylation of injury-promoting gene promoters) were assessed. Logistic regression, Random Forest, and XGBoost models were constructed to identify predictors of severe cardiac dysfunction.
Results:
Severe cardiac dysfunction was significantly associated with higher genome-wide methylation levels, hypermethylation proportion, and risk-type cfDNA (all P < 0.05). cfDNA concentration was an independent protective factor for endpoint events (OR = 0.946, 95% CI: 0.893-0.997, P = 0.0443). The combined model (cfDNA + left ventricular ejection fraction [LVEF] + N-terminal pro-brain natriuretic peptide [NT-proBNP] + age) achieved an area under the ROC curve (AUC) of 0.994. Machine learning models identified age, cfDNA concentration, and LVEF as the top three predictors of severe cardiac dysfunction.
Conclusion:
Epigenetic characteristics of cfDNA are closely associated with the severity of cardiac dysfunction in CVD patients and may serve as effective noninvasive molecular markers for cardiac function stratification. Integrating cfDNA epigenetic features with traditional clinical indicators significantly improves risk prediction accuracy.
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