Network Medicine: A Clinical Approach for Precision Medicine and Personalized Therapy in Coronary Heart Disease

Area of Science:

• Integrative biology and network medicine
• Precision medicine and personalized therapy
• Epigenetics and cardiovascular disease research

Background:

• Early identification of coronary atherosclerotic mechanisms is crucial for predicting coronary heart disease (CHD) risk and cardiac events.
• Epigenetic modifications offer potential biomarkers for CHD prevention, addressing 'missing heritability'.
• Systems biology and network science are advancing precision medicine for cardiovascular conditions.

Purpose of the Study:

• To integrate clinical data, cardiac imaging, and epigenetics using deep learning for molecular phenotyping in CHD.
• To explore novel drug development from natural compounds and repurposing existing drugs for CHD.
• To investigate circulating microRNAs (miRNAs) as biomarkers in association with imaging and functional parameters for CHD.

Main Methods:

• Network medicine approach combining clinical records, advanced cardiac imaging (e.g., CCTA, FFR/CT, PET/CT), and epigenetics.
• Deep learning for in-depth molecular phenotyping of CHD.
• Evaluation of circulating miRNAs (e.g., miR-8059, miR-320a) in blood samples.

Main Results:

• Clinical trials are evaluating epigenetic modifications and drugs for primary and secondary CHD prevention.
• Circulating miRNAs show potential as biomarkers when correlated with imaging parameters like coronary calcifications and stenosis.
• Network-based approaches are prioritizing epigenetic modifications, though the complete CHD interactome requires further investigation.

Conclusions:

• Network medicine offers a powerful framework for deep molecular phenotyping in CHD.
• Epigenetic biomarkers, particularly circulating miRNAs, hold promise for early CHD detection and risk stratification.
• Further research into the CHD interactome is essential for developing effective primary prevention strategies.