Personalizing treatments for patients based on cardiovascular phenotyping

Area of Science:

• Cardiovascular medicine
• Genomics
• Proteomics
• Metabolomics

Background:

• Cardiovascular disease is a leading global cause of death, with current treatments often based on a reductionist view of patient phenotypes.
• Existing therapeutic approaches assume uniform patient responses, which is challenged by the complex and heterogeneous nature of cardiovascular diseases.

Purpose of the Study:

• To explore the role of advanced phenotyping in personalizing cardiovascular disease treatment.
• To highlight the potential of integrating molecular data for more precise patient stratification and outcome prediction.

Main Methods:

• Utilizing high-throughput omics platforms (genomics, proteomics, metabolomics) to gather large-scale molecular data.
• Combining molecular data with traditional clinical information (history, physical examination, lab results) for comprehensive phenotyping.
• Analyzing multiscale data to identify diverse patient phenotypes within cardiovascular disease cohorts.

Main Results:

• Omics profiling has enabled the definition of more precise cardiovascular phenotypes.
• Molecular data aids in predicting adverse outcomes and informing drug efficacy based on individual patient profiles.
• Multiscale phenotyping reveals patient diversity crucial for personalized pharmacotherapies.

Conclusions:

• Precision phenotyping in cardiovascular disease, though nascent, offers significant potential for improving patient care.
• Personalized pharmacotherapies and outcome prediction are key benefits of advanced phenotyping.
• Demonstrating improved treatment responses and reduced adverse events is essential for clinical adoption of precision cardiovascular medicine.