LDL-cholesterol predicts negative coronary artery remodelling in diabetic patients: an intravascular ultrasound study

Pilar Jiménez-Quevedo, Manel Sabaté*, Dominick Angiolillo, Fernando Alfonso, Rosana Hernández-Antolín, Camino Bañuelos, Esther Bernardo, Celia Ramirez, Raúl Moreno, Cristina Fernández, Javier Escaned and Carlos Macaya

Interventional Cardiology Unit, Cardiovascular Institute, Hospital Clínico San Carlos, C/Prof. Martín Lagos s/n, 28040 Madrid, Spain

Received 28 March 2005; revised 17 June 2005; accepted 23 June 2005; online publish-ahead-of-print 21 July 2005.

* Corresponding author. Tel: +34 91 3303283; fax: +34 91 3303289. E-mail address: manelsabate{at}telefonica.net


    Abstract
 Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
 Acknowledgement
 References
 
Aims To investigate the relationship between coronary artery remodelling and glycaemic and lipid profiles in diabetic patients.

Methods and results Intravascular ultrasound analyses of 131 angiographically non-significant coronary stenoses in 80 diabetic patients were performed. The remodelling index (RI) was calculated as the ratio between total vessel area at target site and total vessel area at proximal reference, and was assessed in two ways: as a continuous variable, and as a binary categorical variable: RI<1 namely, negative remodelling (group I), or RI≥1 (group II). Percentage cross-sectional narrowing was 57±13%. On average, RI was 0.93±0.13. Coronary shrinkage was found in 94 (71.7%) lesions. Significant inverse correlations were demonstrated between RI and total cholesterol (r=–0.26, P=0.003), apolipoprotein-B (r=–0.23, P=0.01) and LDL-cholesterol (r=–0.3, P=0.001) levels. Multivariable lineal regression analysis identified LDL-cholesterol as the only independent predictor of RI (P=0.001).

Conclusion Negative remodelling is a frequent finding in diabetics and it is associated with LDL-cholesterol levels. This may contribute to the diffuse coronary artery disease observed in diabetic patients.

Key Words: Coronary remodelling • Intravascular ultrasound • Diabetes mellitus • LDL-cholesterol • High-sensitivity C-reactive protein


    Introduction
 Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
 Acknowledgement
 References
 
Diabetic patients exhibit a high prevalence of coronary artery disease (CAD), which is associated with elevated rates of morbidity and mortality.1 CAD in diabetics is characterized by being multivessel, more diffuse, and with smaller vessel when compared with non-diabetics.2

Remodelling is defined as a compensatory enlargement of a coronary vessel in response to atherosclerotic plaque accumulation.3 Intravascular ultrasound (IVUS) is a valid diagnostic tool in assessing this phenomenon in patients.4 Given a certain degree of plaque proliferation, a reduced compensatory enlargement (failure of compensatory enlargement) or even shrinkage of total vessel dimension (negative coronary remodelling) leads to a more rapid development of coronary stenoses, as observed in diabetic patients.5

Several factors may influence remodelling patterns. In general population, negative remodelling has been found to be associated with smoke,6 hypertension,7 and plasma homocystein levels.8 Moreover, negative remodelling is more frequent in lesions with a superficial arc of calcium4 and in hard plaques.9 However, the underlying pathophysiological determinants that induce negative remodelling in diabetics remain unclear.

As insulin resistance and inflammation play a key role in the development of macrovascular complications in diabetics,10,11 the aim of this study was to investigate the relationship between coronary artery remodelling, assessed by IVUS, and metabolic and inflammatory profiles in diabetic patients.


    Methods
 Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
 Acknowledgement
 References
 
Patient selection
Between 1 February 2003 and 30 November 2003, 313 IVUS studies were performed in our institution: 148 in diagnostic procedures and 165 during percutaneous coronary interventions. Complete flow chart is depicted in Figure 1. The patient population is a subset of 80 patients who had been included in the DIABETES trial with available IVUS analysis.12 The DIABETES trial is a prospective, multicentre, randomized, controlled trial aimed to demonstrate the efficacy of sirolimus-eluting stent when compared with bare metal stent on the inhibition of neointimal hyperplasia in diabetic patients. In this study, diabetic patients, as defined by the World Health Organization Report, on pharmacological treatment (insulin or hypoglycaemic agents) for at least 1 month with angiographically significant coronary stenoses in native coronary vessel were included. The study complied with the provisions of the Declaration of Helsinki regarding investigations in humans, was approved by the ethics committee, and all patients signed a written inform consent.



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Figure 1 Flow chart of patient selection.

 
IVUS analysis
IVUS analysis was performed after stent implantation. The IVUS system used was ClearView console (CVIS, Sunnyvale, CA, USA) and the IVUS catheter was Atlantis-Pro 40 MHz with a single piezoelectric crystal transducer mechanically rotated at 1800 r.p.m. within a 2.6 F monorail catheter sheath. Nitroglycerin (200 µg) was administered directly into the target coronary artery before IVUS catheter insertion. After placing the IVUS catheter distal to the stent, an automated motorized pullback at a speed of 0.5 mm/s was performed until the aorto-ostial junction. All images were recorded on a VHS videotape for off-line analyses. For the purpose of the study, we considered those angiographically non-significant coronary stenoses eligible for the analysis, which were subsequently recognized by IVUS, observed within the target artery. Target lesion location was defined using side branches as anatomical landmarks. Further, the target lesion had to be located at least 10 mm distal or proximal from the previously stented segment and thus not subject to balloon injury during the index procedure. We excluded from the analysis those lesions with ostial location, those with diffuse calcified lesions (arc of calcium >90°) due to the impossibility of measuring vessel dimensions, and those with artefacts related to IVUS, such as non-uniform rotational distortion (Figure 1). In addition, patients with multiple balloon inflations during complex procedures were also excluded when doubts remained concerning the exact location of the inflated balloon. Measurement of external elastic membrane (EEM) and lumen (L) areas at the site of the lesion and at proximal and distal references were performed with computerized planimetry, as previously described.9 Because media thickness cannot be accurately measured, plaque+media (P+M) area was used as a measure of atherosclerotic plaque. P+M area was calculated as EEM area minus L area. End-diastolic frames were selected for calculations. References were taken at the most normal-looking cross-section within 10 mm proximal or distal to the lesion but distal or proximal to any side branch, respectively.13 IVUS measurements were performed by the same investigator (P.J.-Q.), who was blinded to the clinical, procedural, and laboratory data. Plaque composition, however, was defined with the agreement of two independent observers. Intraobserver variability of vessel and lumen areas was assessed by analysing a consecutive series of 40 post-interventional studies at least 5 months apart. The intraobserver differences in measurement were as follows: TV area (0.05±0.33 mm2), L area (0.05±0.12 mm2), P+M area (0.007±0.41 mm2), and intraclass correlation coefficient for repeated measurement of EEM, L, and P+M areas were 0.995, 0.997, and 0.992, respectively.

Definitions
EEM area was defined as the area encompassed by the external elastic lamina boundary, whereas L area as the area encompassed by the lumen–intima boundary. Plaque composition was defined as soft, hard, or calcified, following previously described guidelines.14 Percentage cross-sectional narrowing (%CSN) was calculated using the formula: (EEM area–L area)/EEM areax100. The remodelling index (RI) was assessed in two ways: as a continuous variable defined as the ratio between area at target site and EEM area at proximal reference and as a binary categorical variable: RI<1, namely, negative remodelling (group I) or RI≥1 (group II).15

Biochemical analyses
At the time of the procedure, total serum cholesterol, triglyceride, HDL-cholesterol (HDL-C), LDL-cholesterol (LDL-C), apolipoprotein-A (Apo-A), apolipoprotein-B (Apo-B), glycated haemoglobin A1c (HbA1c), and high sensitivity C-reactive protein (hs-C-reactive protein) were measured after overnight fasting, following a pre-specified protocol. Serum total cholesterol, triglyceride, and HDL were measured by automated enzymatic procedures and serum Apo-A and Apo-B were measured by immunochemical methods. LDL-C was calculated by Friedewald formula:16 LDL-C=total cholesterol–HDL-C–(triglyceride/5). All the lipid profiles were assessed at the central laboratory of our hospital. hs-C-reactive protein levels were measured from frozen serum samples by immunonephelometry using a commercially available kit (Beckman Coulter Inc., Fulerton, CA, USA).

Statistical analyses
Statistical analysis was performed by the SPSS 12.0 version. Quantitative data are presented as mean±SD and compared by Student's exact test or Fisher's exact test when at least 25% of values show an expected frequency <5. A two-tailed value of P<0.05 was considered significant. To measure the strength of association between two continuous variables, Pearson correlation analysis was used. Using an epidemiological approach, multivariable linear regression analysis was performed to identify independent predictors of RI by means of a backward stepwise model. After stratifying the analysis in order to explore confusion and interaction, those clinically relevant variables that better explain the model were selected following a saturated and hierarchical model. Thus, those variables associated with RI with a P-value less than 0.05 in the univariate analysis or which were clinically relevant were entered into the multivariable model. The variables finally included were LDL-C, HDL-C, total cholesterol levels, and diabetes treatment (insulin or oral agent). Assumptions of the regression linear model are checked with the residuals and its graphs to evaluate whether they have a mean value of 0 and a constant variance.


    Results
 Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
 Acknowledgement
 References
 
Baseline characteristics
Eighty patients and 131 lesions were included in the study. Demographic characteristics and laboratory tests are presented in Table 1. Mean age was 65±8.9 years and 67.5% of the patients were male. Thirty-six per cent of the patients were insulin-dependent, whereas 64% were treated with oral agents. Multivessel disease was identified in 62.5% of the patients.


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Table 1 Patient demographics and laboratory test
 
Mean %CSN was 57±13%. On average, RI was 0.93±0.13. Most of lesions showed an RI<1 (94 lesions, 71.7%). The same pattern of remodelling was evidenced in most of those lesions (>70%) assessed in the same patient. An example of a lesion with negative remodelling is depicted in Figure 2. The type of plaque most frequently observed was mixed in 54 lesions (41.2%) followed by soft in 38 lesions (29%) and calcified (<90°) in 39 lesions (29.8%).



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Figure 2 IVUS imaging of a lesion showing negative remodelling. (A) EEM area at proximal reference. (B) EEM area at target lesion. (C) EEM area at distal reference. RI was 0.72.

 
Continuous analysis of remodelling
RI was not significantly associated with any of the coronary risk factors, plaque composition, or statin use (Table 2). RI did not correlate with hs-C-reactive protein (r=–0.1, P=0.25), HbA1c (r=–0.04, P=0.6), triglyceride (r=–0.1, P=0.1), or HDL-C (r=–0.1, P=0.13) levels. However, a moderate but significant inverse correlation was observed between RI and total cholesterol (r=–0.26, P=0.003), Apo-B (r=–0.23, P=0.01), and LDL-C (r=–0.30, P=0.001) levels (Figure 3). In the multivariable linear regression analysis, LDL-C was the only independent predictor of RI (Beta: –0.01; 95%CI –0.02–0.001; P=0.001). Therefore, an increase of 10 U of LDL-C is associated with a decrease of 0.01 in RI. Moreover, patients with LDL-C>100 mg/dL showed a significantly lower RI than patients with LDL-C≤100 mg/dL (0.86±0.11 vs. 0.96±0.13, respectively; P=0.005).


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Table 2 Univariate analysis
 


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Figure 3 Pearson correlations between LDL-C, total cholesterol, Apo-B, and RI.

 
Predictors of negative remodelling
At target site, lesions with negative remodelling presented smaller EEM, L, and P+M areas than those with RI≥1 (Table 3). Importantly, both groups presented comparable vessel dimensions at reference sites.


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Table 3 IVUS finding grouped according to the presence or absence of negative remodelling
 
Metabolic profiles were impaired in lesions with negative remodelling (Table 4) with higher levels of total cholesterol, Apo-B, and LDL-C when compared with lesions with RI≥1. Multivariable linear regression analyses identified LDL-C as the only independent predictor of negative remodelling (Beta –0.02; 95%CI: 0.96–0.99; P=0.01).


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Table 4 Negative remodelling and metabolic profile
 

    Discussion
 Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
 Acknowledgement
 References
 
Main findings of this study were that negative remodelling was often observed in diabetic patients with documented CAD and that LDL-C was independently associated with this finding.

The prevalence of lesions with negative remodelling in the general population ranges from 15 to 50%.9,1719 Diabetic patients are at high risk for such vascular behaviour when compared with non-diabetic population.20 In our study, the prevalence of negative remodelling was 72%. Moreover, lesions with constrictive remodelling appeared to have significantly smaller L area despite having similar plaque burden when compared with lesions with compensatory enlargement (Table 3). Hence, constriction of EEM area remained the main contributor for lumen narrowing.

This is the first study that specifically focused on the remodelling pattern in diabetic population. In the current study, serum LDL-C level was identified as independent and negative predictor of RI. These findings support previous observations reported in non-diabetic patients21 and in histological studies.22 Yoneyama et al.21 performed IVUS studies in 36 non-diabetic patients with significant coronary lesions (>50%). Oxidized LDL levels were significantly higher and HDL-C levels lower in lesions showing constrictive remodelling. Moreover, HDL/LDL ratio correlated with RI (r=0.48, P<0.004). Taylor et al.23 evidenced a significant relationship between higher HDL-C and positive remodelling on histology of 97 autopsy cases study. Finally, Hamasaki et al.24 demonstrated that patients with inadequately controlled hypercholesterolaemia (defined by serum cholesterol levels >240 mg) had lesions with a comparable plaque burden but with a significantly smaller vessel area than those with adequately treated hypercholesterolaemia.

Several definitions of remodelling have been proposed in previous studies. In this regard, this lack of consensus on how to define remodelling has led to conflicting factors that influence this process.25 However, in this study, the same results have been evidenced by the use of two previously validated dichotomous definitions of remodelling, which enhance the consistency of our results.9,15,21

The mechanism of inadequate compensatory enlargement is not completely understood. In normal arteries, remodelling is a haemostatic response to changes in flow and shear stress and largely depends on endothelial production of nitric oxide.26 Those situations related to endothelial dysfunction, and subsequently impairment of nitric oxide release may contribute to an inadequate remodelling in response to plaque accumulation. In this regard, oxidized LDL inhibits the expression of constitutive endothelial nitric oxide synthase,27 induces expression of adhesion molecules on the endothelium, and facilitates inflammatory cells to adhere to the intima.28 Another mechanism that has been proposed to explain inward remodelling is related to the increase in the release of mitogenic and fibrogenic growth factors that induce an increment in smooth muscle cell proliferation and collagen deposition.29 The mitogenic effect of oxidized LDL may include induction of platelet-derived growth factor production and platelet-derived growth factor receptor expression in vascular smooth muscle cells,30 and also the induction of various growth factors in endothelial cells.31

hs-C-reactive protein is an inflammatory biomarker, which has emerged as predictor of coronary events32 and it is intimately related to the development of diabetes and the components of metabolic syndrome.33 In our study, however, there was not any association between coronary remodelling and hs-C-reactive protein levels. This finding is in accordance with previous observations showing a lack of association between hs-C-reactive protein levels and the degree and extension of atherosclerotic disease.34

Study limitations
This is an observational study that evaluates atherosclerosis plaque and adjacent segments only at one time point during the entire process of atherosclerosis. Thus, no conclusions regarding the natural history of remodelling can be drawn. The study cohort was sampled from patients who had IVUS. This fact raises the possibility of selection bias and the results cannot be extrapolated to the general population of diabetics.

Heavily calcified lesions were excluded from the analyses because measurement of EEM area may have been unreliable. Thus, the association between large deposits of calcium and remodelling could not be determined. In our study, measurement of EEM area of plaques containing deposits of calcium was obtained by interpolating the adventitial border. Although the arc of calcium was never larger than 90°, some inaccuracy of this measurement cannot be completely ruled out.


    Acknowledgement
 Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
 Acknowledgement
 References
 
P.J.-Q. is a recipient of a grant from the Community of Madrid—European Social Funding.


    References
 Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
 Acknowledgement
 References
 

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