Although cardiovascular risk factors such as increased age, hypertension, diabetes mellitus, smoking and dyslipidemia are well known, they do not accurately predict the risk of coronary artery disease. A Korean research group led by Sunsoo Cho1 evaluated whether adding additional biomarkers to these conventional risk factors would increase their ability to predict coronary artery disease.

This group compared a cohort of 503 subjects with documented angiographic, multi-vessel coronary artery disease with a sex- and age-matched cohort of 503 healthy control subjects. The researchers assessed the conventional risk factors in all subjects including hypertension, diabetes mellitus, dyslipidemia, smoking, and body mass index. They also measured fasting glucose, fasting insulin, triglycerides, and high-density lipoprotein (HDL) cholesterol.

In addition, they measured levels of six vascular inflammatory biomarkers that have been shown to be significantly associated with premature coronary artery disease. These biomarkers included high sensitivity C-reactive protein (hs-CPR) and interleukin 6 (IL-6), which are associated with the development of coronary artery disease. They also included the receptor for advanced glycation end products (RAGE), lipoprotein-associated phospholipase A2 (Lp-LPA2), adiponectin, and “regulated upon activation, normal T cells expressed and secreted” (RANTES), all of which are significantly associated with premature coronary artery disease.

The researchers created two prediction models. The first included the conventional risk factors and laboratory data only. The second included the conventional risk factors and laboratory data as well as the six biomarkers. What they found was that adding the six biomarkers moderately improved prediction of premature coronary artery disease compared to the conventional model (C-statistic 0.952 versus 0.937, P=0.0003). When individual biomarkers were added to the conventional model, only hs-CRP and IL-6 alone had significant discriminative power in predicting premature coronary artery disease.  This is the first time a study looked at the combination of RAGE, Lp-PLA2, adiponectin and RANTES.

Related:  Biomarker Basics

This study shows that combining biomarkers in an integrative core or algorithm that includes risk factors or other clinical data is more accurate than just using biomarkers by themselves.

The researchers discussed some interesting limitations of this study:

  • The cause and effect relationship between risk factors, biomarkers and coronary artery disease was not studied.
  • Many study participants were on medications such as aspirin, ACE inhibitors and statins, and they did not measure the influence of these medications in their study.
  • Although the study participants were age- and sex-matched, the control group was significantly healthier than the group with coronary artery disease as seen in their measures of hypertension and diabetes.
  • Larger scale cardiovascular studies of the novel biomarkers examined – RAGE, adiponectin, Lp-PLA2 and RANTES – are necessary.
  1. Cho S, Lee SH, Park S, et al. The additive value of multiple biomarkers in prediction of premature coronary artery disease. Acta Cardiol. 2015 Apr;70(2):205-10.