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DNA methylation in cardiovascular disease and heart failure: novel prediction models?
Antonella Desiderio1,2, Monica Pastorino2,3, Michele Campitelli2
1Department of Translational Medicine, Federico II University of Naples, Naples, Italy.
Insights
DNA methylation (DNAm) biomarkers enhance cardiovascular disease (CVD) and heart failure (HF) prediction models. These epigenetic markers offer improved accuracy for risk prediction and personalized treatment strategies.
Area of Science:
- Biomarkers
- Genomics
- Cardiovascular Medicine
Background:
- Cardiovascular diseases (CVD) are the leading cause of global mortality, with heart failure (HF) prevalence increasing due to aging and risk factors.
- Heart failure (HF) contributes significantly to CVD deaths and hospitalizations, diminishing patients' quality of life.
Purpose of the Study:
- To review current information on DNA methylation (DNAm) in relation to CVD and HF.
- To discuss the utility of DNAm in enhancing clinical risk prediction for CVD and HF.
- To explore DNAm age as a proxy for cardiac aging.
Main Methods:
- Review of existing literature on DNA methylation (DNAm) and cardiovascular diseases (CVD) and heart failure (HF).
- Analysis of DNAm changes as potential biomarkers for risk prediction, diagnosis, prognosis, and treatment monitoring.
- Exploration of DNAm age in the context of cardiac aging.
Main Results:
- DNA methylation (DNAm) biomarkers significantly improve the accuracy of cardiovascular risk models.
- Numerous CpG sites have been identified for developing specific prediction scores for CVD and HF.
- DNAm-based prediction scores demonstrate comparable or superior performance to existing risk measures.
Conclusions:
- DNA methylation (DNAm) biomarkers provide a valuable tool for enhancing cardiovascular risk prediction accuracy.
- Future integration of DNA methylome data with other sources and advanced machine learning algorithms will enable more precise, personalized risk prediction for CVD and HF.
Background:
Cardiovascular diseases (CVD) affect over half a billion people worldwide and are the leading cause of global deaths. In particular, due to population aging and worldwide spreading of risk factors, the prevalence of heart failure (HF) is also increasing. HF accounts for approximately 36% of all CVD-related deaths and stands as the foremost cause of hospitalization. Patients affected by CVD or HF experience a substantial decrease in health-related quality of life compared to healthy subjects or affected by other diffused chronic diseases.
Main Body:
For both CVD and HF, prediction models have been developed, which utilize patient data, routine laboratory and further diagnostic tests. While some of these scores are currently used in clinical practice, there still is a need for innovative approaches to optimize CVD and HF prediction and to reduce the impact of these conditions on the global population. Epigenetic biomarkers, particularly DNA methylation (DNAm) changes, offer valuable insight for predicting risk, disease diagnosis and prognosis, and for monitoring treatment. The present work reviews current information relating DNAm, CVD and HF and discusses the use of DNAm in improving clinical risk prediction of CVD and HF as well as that of DNAm age as a proxy for cardiac aging.
Conclusion:
DNAm biomarkers offer a valuable contribution to improving the accuracy of CV risk models. Many CpG sites have been adopted to develop specific prediction scores for CVD and HF with similar or enhanced performance on the top of existing risk measures. In the near future, integrating data from DNA methylome and other sources and advancements in new machine learning algorithms will help develop more precise and personalized risk prediction methods for CVD and HF.
