Background
Type 2 diabetes is associated with a high prevalence of coronary artery disease (CAD) and with a 2- to 4-fold increase in silent myocardial ischemia (SMI) as compared with the non diabetic population [
1,
2]. SMI has been reported in 7 to 65% of the diabetic population [
3], this prevalence increasing with male gender, ageing, longer duration of diabetes and the presence of additional cardiovascular risk factors, nephropathy, retinopathy and peripheral or carotid occlusive arterial disease [
1‐
4]. SMI is a strong predictor of future coronary events and premature death [
5,
6], providing a significant additional value compared to routine cardiovascular risk assessment [
7].
Endothelial dysfunction is an early phenomenon during diabetic atherogenesis [
8,
9] and has been associated with a poor cardiovascular prognosis in the diabetic population [
10‐
12]. Therefore, peripheral endothelial dysfunction is considered as an integrator of cardiovascular risk. The association between endothelial and smooth muscle dysfunction evaluated by flow-mediated dilation (FMD) and SMI in patients with type 2 diabetes has been previously studied. Some authors did not find any association but reported a high negative predictive value for SMI when the endothelial function was normal [
13], whereas others reported a higher prevalence of SMI in the patients with abnormal FMD [
14]. However, these series included a limited number of subjects, whose
a priori cardiovascular risk was lower than what has been recommended for SMI screening [
2,
15]. Furthermore, the patients’ coronary status was unknown in these studies, with no opportunity to evaluate the potential association between endothelial function and SMI according to the presence or the absence of CAD. This could be crucial as the patients with SMI but no CAD on angiography are likely to have functional vascular disorders such as abnormal coronary reserve or coronary endothelial dysfunction [
16]. Finally, non-diabetic control subjects and non-diabetic overweight or obese patients were not included in these studies. If FMD has been shown to be lower in patients with type 2 diabetes than in age- and sex-matched subjects, BMI was higher in the former [
17] and it is known that obesity is associated with endothelial dysfunction [
18]. Thus, there is a need for further studies to validate the technique and evaluate the proper impact of diabetes instead of the combined effect of obesity with diabetes.
We raised the hypothesis that FMD would be impaired in the diabetic patients, with incremental impairment in those without SMI, those with SMI but no CAD and those with both SMI and CAD. The aim of the study was to investigate in a series of type 2 diabetic patients with a high cardiovascular risk according to the joint guidelines of the French Language Association for the Study of Diabetes and Metabolic Diseases (ALFEDIAM) and the French Society of Cardiology (SFC) if FMD was associated with SMI and/or asymptomatic CAD.
Discussion
We confirmed that peripheral FMD is impaired in type 2 diabetes, as compared to control subjects and non-diabetic obese patients. In particular, we report here for the first time that FMD is independently associated with SMI; and even more specifically when ischemia is associated with CAD on angiography. This was observed while the immediate post-ischemic flow increase, a surrogate for microcirculation, remained similar whatever the heart ischemic status in these diabetic patients.
In the present study, the mean FMD was around 4% in control subjects and overweight/obese patients, and 1% in diabetic patients. The fact that FMD was lower in diabetic patients than in non-diabetic obese subjects shows that obesity
per se did not affect FMD and that diabetes plays a major role in the impairment of FMD. FMD was lower than the levels reported elsewhere. Indeed, the normal values of FMD have not been well-established in a control population and are widely variable according to methods for measurements [
19]. Bots
et al. have reviewed more than 200 papers from 1992 to 2001 and reported in healthy subjects FMD from 0.2 to 19.2% and in diabetic patients from 0.75 to 12% [
23]. In their conclusion technical aspects of measurements, location and duration of occlusion may explain some of the differences while type of equipment, location of measurement and occlusion pressure do not. Our local control groups had low FMD but our results in our diabetic cohort may also be explained by long standing diabetes and a high
a priori cardiovascular risk, due to our inclusion criteria. For example, the prevalence of asymptomatic CAD was high in our cohort (17.8%), whereas we previously reported a lower prevalence (10-15%) in patients with type 2 diabetes who were screened for SMI only by stress scintigraphy [
7,
21,
22] instead of two tests in the present study. FMD may be considered as an integrator of cardiovascular risk,
i.e. a marker of cardiovascular stress related to the presence of risk factors and their levels, whatever the underlying mechanism. In the present study, paradoxical vasoconstriction was associated with a more impaired lipid profile, a poorer glycemic control, less current treatment by ACE-inhibitors, and a trend for smoking, despite a lower age.
FMD studies explore the peripheral vasculature response to transient ischemia. The flow response, as depicted by the flow velocity increase after cuff deflation, reflects the distal microcirculation response to ischemia, and an impaired response has been reported to predict cardio-vascular events [
24]. Diameter changes after the increase in flow depend on the endothelium, mainly through a nitric oxide-dependent mechanism, but also on vascular smooth muscle cell contraction/relaxation. Endothelial dysfunction may be considered as a cardiovascular risk factor or at least as a cardiovascular risk marker [
12,
25], but impairment of vascular smooth muscle cell function has been also reported in diabetic patients [
9] and may be involved in altered FMD. The mechanism of impaired FMD cannot be explained in our results since we did not test specifically vascular smooth muscle cell function, like Peix
et al.[
14]. The absence of significant difference between patients who constricted their brachial artery and those who did not for VCAM and albuminuria, which are usually considered as endothelium markers [
26], might be consistent with the role of impaired smooth muscle cell function in our population. The important fact is that an impaired FMD response
per se, whatever its mechanism, was shown to predict a poor cardio-vascular prognosis in several large population studies [
25,
27].
Abnormal coronary vasomotion [
10,
28] and coronary endothelial dysfunction [
29] are also associated with a poor cardiovascular prognosis in diabetes. A direct relationship between peripheral and coronary vascular function may be difficult to demonstrate. FMD was reported to statistically correlate with coronary response to acetylcholine, but this correlation was weak [
30]. Gori
et al. recently showed that using FMD provides significant additional information in predicting the presence of CAD in patients suffering from angina [
31]. Furthermore, FMD has recently been shown to be independently associated with slow coronary flow in patients with angina and non significant narrowed CAD [
32]. Although, we have clearly demonstrated here that an altered FMD was independently associated with SMI, other studies failed to show a strong association between FMD and SMI. This discrepancy seems to be related to the difference in the cardiovascular risks of the patients in these studies compared to our study population (Table
2: diabetes duration 13 years, hypertension and dyslipidemia in 87.3% and smoking in 19% of the patients). In the Detection of Ischemia in Asymptomatic Diabetics (DIAD) study, FMD was measured in 75 asymptomatic type 2 diabetic patients and was found to be similar in those with or without SMI [
13]. The cardiovascular risk profile was better than in our study population, with a mean diabetes duration of 8.4 years, and hypertension, dyslipidemia and smoking habits in 49%, 59% and 8% of the patients, respectively, and only 15 (20%) of the patients had SMI. When the cardiovascular risk profile of the patients was intermediate as in Peix
et al. study (diabetes duration 11 years, age 58 years, hypertension, dyslipidemia and smoking habits in 77%, 73% and 32% of the patients, respectively), there was a higher prevalence of abnormal FMD in those with SMI as compared with those without, whereas no difference was found for the mean values of FMD [
14]. As reported by Naka
et al., duration of diabetes appears to be an important factor for developing impaired FMD [
33]. In these two studies performed in diabetic patients, coronary status was not determined by angiography. This is a crucial issue as SMI actually includes two entities: only 30-70% of the patients with SMI have significant CAD [
3] while ischemia in patients without CAD may result from functional disorders [
16], such as abnormal coronary reserve or coronary endothelial dysfunction. In our study population, 35% of the patients with SMI had CAD. We report for the first time that the flow-mediated vascular response was worse, with more paradoxical vasoconstriction, when SMI or CAD were present. Abnormal FMD was gradually further impaired in the patients without SMI, with SMI but no CAD, and with both SMI and CAD (Figure
1). This result is consistent with the role of silent coronary disease in the poorer prognosis associated with lower FMD in the diabetic population.
The use of FMD as a screening test for SMI was tested in the DIAD study [
13]. The negative predictive value for SMI of a normal FMD was 93%. FMD was considered as abnormal when <8%
i.e. at the threshold that maximized the negative predictive value and had the least impact on sensitivity while the study did not include control subjects. The threshold that we considered in the present study was lower (<0%,
i.e. paradoxical vasoconstriction) and was in line with the high cardiovascular risk of our patients. We found that paradoxical vasoconstriction was independently associated not only with SMI but also with CAD. However, while the presence of a paradoxical vasoconstriction had an 88.7% negative predictive value for CAD, the positive predictive value for CAD was too low to suggest the inclusion of this criterion in the algorithm of CAD screening.
The present study has some limitations. The control groups were not matched for gender, and by definition age and BMI were different in the three groups of patients (healthy controls, non-diabetic obese patients and diabetic patients). However, FMD was lower in the diabetic patients even after adjustment on age and gender. Due to obvious ethical issues, no coronary angiography was performed in the patients without SMI, and some patients with CAD but no SMI may have been missed. Furthermore, the cut-off for significant epicardial CAD we used was 70% stenoses, whereas stenoses are nowadays considered as significant with milder stenoses (i.e. 50% or more) when abnormal fractional flow reserve is observed. However, in our study, these measurements were not available for all the patients. Our FMD cutoff of 0% may not be applicable to diabetic patients with a low a priori cardiovascular risk. Lastly, we could not distinguish whether abnormal FMD resulted from endothelium-dependent or -independent disorders as nitroglycerin-induced vasodilation was not tested.
Competing interests
The authors declare no competing interests.
Authors’ contributions
MTN researched data, made statistic, contributed to discussion; IP performed the FMD and stress echography studies, contributed to discussion, reviewed/edited manuscript; PV directed research, contributed to discussion, reviewed/edited manuscript; HR made statistic; EV made statistic, contributed to discussion, reviewed/edited manuscript; CLM made biochemical measurement and contributed to discussion, AN contributed to discussion; EC directed research, wrote manuscript. Prof Eric Vicaut is the guarantor of this work and, as such, had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. All authors read and approved the final manuscript.