Epidemiology of cardiovascular disease: recent novel outlooks on risk factors and clinical approaches

Abstract

Introduction: Cardiovascular (CVD) risk assessment with traditional risk factors (age, sex, blood pressure, lipids, smoking and diabetes) has remained relatively invariant over the past decades despite some inaccuracies associated with this approach. However, the search for novel, robust and cost-effective risk markers of CVD risk is ongoing.

Areas covered: A large share of the major developments in CVD risk prediction during the past five years has been made in large-scale biomarker discovery and the so called 'omics' - the rapidly growing fields of genomics, transcriptomics, epigenetics and metabolomics. This review focuses on how these new technologies are helping drive primary CVD risk estimation forward in recent years, and speculates on how they could be utilized more effectively for discovering novel risk factors in the future. Expert commentary: The search for new CVD risk factors is currently undergoing a significant revolution as the simple relationship between single risk factors and disease will have to be replaced by models that strive to integrate the whole field of omics into medicine.

Keywords: Cardiovascular risk; biomarkers; cardiovascular disease; epigenetics; genomics; metabolomics; risk factors; transcriptomics.

Figure 1

Concepts of two metrics for evaluating improvement in discrimination when a new risk factor (RF) is added to an existing model: 1) improvement in c-statistic (the proportion of pairs in which the person who experienced the event had a higher predicted probability of experiencing the event than the subject who did not experience the event) and 2) net reclassification index, the percentage of persons with and without the event correctly reclassified.

Figure 2

Principles of a randomized controlled trial and Mendelian randomization.