MS is defined as the presence of any three or more of five quantitatively identified markers. Although the individual components of MS are related to one another, patients with MS could be comprised of heterogeneous subgroups . Therefore, it has been a matter of debate whether MS improves cardiovascular risk prediction beyond the risk associated with its individual components [9, 10]. Some studies have reported that MS score is more useful than the presence or absence of MS in predicting the severity of CAD [11, 12]. Moreover, it has been suggested that MS predicts CAD based primarily on high fasting blood glucose , and the relationship between the MS score and CAD severity is unclear in the presence of DM .
The present study demonstrated that incremental changes in angiographic CAD severity assessed by the Gensini score were observed in accordance with MS score, and MS score was an independent predictor for angiographic CAD. However, in a diabetic subgroup, this association was not observed, and MS score could not predict CAD. These results are consistent with previous findings [13, 19]. This study expands upon existing reports by demonstrating that MS scores are significantly related to IL-6 and adiponectin levels in the non-diabetic subgroup, but not in the diabetic subgroup. Regarding the prediction of angiographic CAD, adiponectin showed marginal significance only in the non-diabetic subgroup .
Although the pathophysiological mechanism by which MS increases cardiovascular risk is still unclear , insulin resistance and central obesity seem to be essential components of MS [22, 23]. Obesity as a predictor of cardiovascular events is related to many cardiovascular risk factors which are also components of MS [21, 24]. It has been shown that visceral adipose tissue is an active endocrine organ which produces several bioactive derivatives including proinflammatory and prothrombotic adipokines, and protective adiponectin . Visceral fat accumulation followed by increased production of proinflammatory adipokines and decreased production of adiponectin is associated with individual components of MS such as insulin resistance, hypertension, and dyslipidemia . Eventually, these abnormalities could lead to atherosclerosis and cardiovascular events [26, 27].
Some experts have suggested that increased cardiovascular risk associated with MS primarily arises from the presence of DM, and DM should be excluded from the definition of MS . The results of the present study also suggest that neither adipokines nor MS score have an incremental value for the prediction of CAD in the presence of DM. As DM is a very strong predictor of cardiovascular disease, the five components of MS and other non-traditional markers of cardiovascular disease did not improve cardiovascular disease prediction beyond the contribution of DM .
The definition of MS excludes other factors related to insulin resistance such as proinflammatory adipokines or adiponectin. It is unclear whether inclusion of these components would predict cardiovascular disease better than the current components [28, 30, 31]. However, in the non-diabetic subgroup, IL-6 and adiponectin changed gradually according to MS score, and MS score predicted angiographic CAD. Therefore, MS score could be used as a predictor of CAD in subjects without DM. The gradual change of inflammatory markers or adipokines according to MS score might be at least partly related with the usefulness of MS score in the prediction of CAD in non-diabetic patients.
The present study has several limitations. Firstly, the subjects in this study were patients who underwent coronary angiography for clinically suspected CAD. Therefore, the prevalence of DM (24%) or CAD (48%) was quite high, and selection bias may affect the results. Secondly, the severity of CAD was assessed by the Gensini scoring system based on the degree of angiographic luminal stenosis. Thus, lesion complexity or plaque vulnerability could not be analyzed in the present study. However, angiographic assessment of coronary stenosis is a widely accepted and clinically useful method for risk stratification in CAD patients. Lastly, this was a cross-sectional study and therefore it was not possible to determine causative relationships. In addition, the effects of medications that could influence the levels of inflammatory cytokines and adipokines, including anti-diabetic drugs, could not be fully analyzed in this study. Therefore, we cannot rule out completely the possibility that these medications might influence the results in some cases.