Speakers:  Michiel J. Bom, Research fellow in the Cardiology Department of VU University Medical Center Amsterdam & Robert Gerszten, Chief of Cardiology at Beth Israel Deaconess Medical Center

Original Broadcast date:  May 19 2019

Despite great advances in the understanding and treatment of cardiovascular disease (CVD), as well as widespread education around proactive preventive measures, it remains an enormous global healthcare issue, causing almost 18 million deaths annually. While clinical parameters (blood pressure, circulating lipid levels, body mass index) and lifestyle risk factors (smoking, lack of exercise) are well known, additional biomarkers are needed for improved risk assessment, more accurate diagnosis/prognosis, and a clearer understanding of the underlying pathophysiology of CVD. Protein biomarkers such as troponin I and NT-proBNP (N-terminal pro–B-type natriuretic peptide) have been long established, while advanced proteomic technologies are enabling new biomarker discoveries that promise to provide insights into disease pathways and mechanisms, and to offer a better understanding of the links between diseases (e.g., between cardiovascular and metabolic conditions). Identification of multiprotein signatures may provide more reliable clinical tools than can be devised using single markers, while combining protein biomarkers with other 'omics approaches and sophisticated data analysis techniques holds enormous potential for the development of precision medicine within the CVD/cardiometabolic fields.

The main points discussed in the webinar:

• How identification of new protein biomarkers enables better understanding, diagnosis, and outcome prediction in cardiovascular/cardiometabolic disease
• How combining machine learning with targeted proteomics can outperform existing clinical risk assessment criteria for coronary heart disease
• New proteomic biomarkers of incident cardiometabolic diseases and explain how the integration of genetic information with model system studies can uncover novel pathways that may contribute to disease pathogenesis.

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