Abstract
The primary prevention of cardiovascular (CV) disease depends on the capacity to identify subjects at higher risk long before the occurrence of CV clinical manifestations. Traditional risk factors do not cover fully prediction of individual risk. Moreover, there is an area of gray for patients at intermediate CV risk, which offers wide margins of improvement. These observations highlight the need for new additive tools for a more accurate risk stratification. An increasing number of candidate biomarkers have been identified to predict CV risk and events, although they generally give only a moderate increase when added to currently available predictive scores. The approach utilizing a relative small number of biomarkers in multiple combinations, but only weakly related to each other or unrelated, thus belonging to independent-pathways, and so able to catch the multidimensional characteristic of atherosclerosis, appears promising. We discuss vitamin D and bone turnover biomarkers, hepatitis C virus, and psycho-emotional factors that may reflect alternative pathways over those generally considered for atherosclerosis (e.g., aspects directly related to inflammation and thrombosis). These new biomarkers could facilitate a more accurate assessment of CV risk stratification if incorporated in the current risk assessment algorithms.