Biomarkers of cardiovascular disease: contributions to risk prediction in individuals with diabetes

Abstract

Cardiovascular disease is a leading cause of death, especially in individuals with diabetes mellitus, whose risk of morbidity and mortality due to cardiovascular disease is markedly increased compared with the general population. There has been growing interest in the identification of biomarkers of cardiovascular disease in people with diabetes. The present review focuses on the current and potential contributions of these biomarkers to predicting cardiovascular risk in individuals with diabetes. At present, certain biomarkers and biomarker combinations can lead to modest improvements in the prediction of cardiovascular disease in diabetes beyond traditional cardiovascular risk factors. Emerging technologies may enable the discovery of novel biomarkers and generate new information about known biomarkers (such as new combinations of biomarkers), which could lead to significant improvements in cardiovascular disease risk prediction. A critical question, however, is whether improvements in risk prediction will affect processes of care and decision making in clinical practice, as this will be required to achieve the ultimate goal of improving clinical outcomes in diabetes.

Keywords: Cardiac complications; Clinical diabetes; Clinical science; Epidemiology; Human; Macrovascular disease; Review.

Fig. 1

Increases in discrimination achieved by adding simulated biomarkers, according to the degree of correlation between biomarkers. The simulated HR for the outcome is 1.35 per SD increment in the biomarker. The y-axis displays the C-statistic from a model containing traditional risk factors plus a varying number of simulated biomarkers (x-axis), each with a fixed association with the outcome. Each of the three curves represents a different degree of biomarker–biomarker correlation. The simulation was performed by M. Pencina, Boston University, © 2011 Wolters Kluwer Health Inc. Figure adapted with permission from Wang (2011) (http://circ.ahajournals.org/content/123/5/551.long) [14]

Fig. 2

Multivariable adjusted HRs for risk of major cardiovascular events for the highest vs the lowest quartile of each candidate biomarker in two type 2 diabetes cohorts: white circles, Second Manifestations of Arterial Disease (SMART) study; black squares, European Prospective Investigation into Cancer and Nutrition-Netherlands (EPIC-NL). Analyses were adjusted for sex, age at diabetes diagnosis, duration of diabetes, HbA_1c, systolic blood pressure, total cholesterol/HDL ratio, urinary albumin/creatinine ratio, smoking status and previous cardiovascular event. Figure reproduced with minor adaptations from van der Leeuw et al [23], © 2016 under the Creative Commons Attribution 4.0 International (CC BY) license (https://creativecommons.org/licenses/by/4.0/legalcode). bFGF, basic fibroblast growth factor; CRP, C-reactive protein; E-FABP, epidermal-type fatty acid binding protein; H-FABP, heart-type fatty acid binding protein; MMP, matrix metalloproteinase; PLGF, placental growth factor; SAA, serum amyloid A; sFLT, soluble FMS-like tyrosine kinase; sICAM, soluble intercellular adhesion molecule; sVCAM, soluble vascular cell adhesion molecule; TIMP, tissue inhibitor of matrix metalloproteinase; VEGF, vascular endothelial growth factor