Cardiovascular diseases (CVDs) remain the leading cause of death globally. Despite progress in treatment modalities for many CVDs large disparities remain across the disease continuum. Several risk factors have been identified; however, the underlying biological mechanisms remain to be fully understood. The emergence of high-throughput ‘omic and machine learning technologies has opened the door to drastically expand our mechanistic understanding of disease etiology and outcomes in order to identify patients at risk, improve patient care and reduce disparities.
We will examine the mechanisms through which multi-omics measures, lifestyle behaviors, and socioeconomic factors impact cardiovascular health, risk of CVDs, and mortality. The clinical implications of these novel markers will be evaluated by assessing their predicative value beyond established CVD risk prediction models.
The specific objectives for the initial phase of this research program are:
1. To examine the association of multi-omics measures (e.g., proteomics and metabolomics) with subclinical cardiac function, incident CVDs and mortality;
2. To examine associations between lifestyle behaviors and social determinants with cardiovascular health and related outcomes;
3. To evaluate the value and utility of these novel markers beyond current CVD risk prediction tools.