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Original research
Association between serum galectin-3 levels and coronary atherosclerosis and plaque burden/structure in patients with type 2 diabetes mellitus Derya Ozturka, Omer Celika, Seckin Satilmisc, Serkan Aslana, Mehmet Erturka, Huseyin Altug Cakmakd, Ali Kemal Kalkana, Sinem Ozyilmaza, Vesile Dikerb and Mehmet Gula Background Levels of galectin-3, a member of a family of soluble β-galactoside-binding lectins, are reported to be higher in patients with type 2 diabetes mellitus (DM) and metabolic syndrome. Conflicting results exist on the effects of galectin-3 in diabetic patients. The aim of this study was to investigate the relationship between galectin-3 levels and coronary artery disease (CAD), coronary plaque burden, and plaque structures in patients with type 2 DM. Patients and methods A total of 158 consecutive patients with type 2 DM undergoing planned coronary computed tomography angiography (CCTA) were included in this study. The study population was divided into CAD and nonCAD groups according to the presence of CCTA-determined coronary atherosclerosis. Results Galectin-3 concentrations were significantly higher in the CAD group than in the non-CAD group (1412.0 ± 441.7 vs. 830.2 ± 434.9 pg/ml, P < 0.001). Galectin-3 levels were correlated positively with BMI, high-sensitivity C-reactive protein, the total number of diseased vessels, the number of plaques (all, P < 0.001), and the calcified plaque type (P = 0.001). In addition, galectin-3 levels were found to
Introduction Type 2 diabetes mellitus (DM) is an important risk factor for cardiovascular disease (CVD), with ∼ 60% of DM patients having CVD and an overall rate of cardiovascular mortality that is twice that of nondiabetic individuals [1]. Cardiovascular risk assessment is important for these patients as it influences decisions on the frequency of follow-up and the diagnostic methods used. New biomarkers and diagnostic strategies are therefore required for the early detection of CVD in patients with DM. Noninvasive imaging modalities, such as carotid intimamedia thickness measurements and coronary artery calcium score calculations, have gained attention in the diagnosis of subclinical atherosclerosis and risk predictions for future adverse cardiovascular events [2,3]. Coronary computed tomography angiography (CCTA), which is a noninvasive imaging technique with high sensitivity and specificity for the diagnosis of coronary artery disease (CAD), may provide valuable information on an individual’s plaque burden and plaque structure [4,5]. 0954-6928 Copyright © 2015 Wolters Kluwer Health, Inc. All rights reserved.
be a significant independent predictor of coronary atherosclerosis in type 2 diabetic patients (P = 021; odds ratio, 1.002; 95% confidence interval, 1.000–1.003). Conclusion Galectin-3 is a novel, promising biomarker that may help identify type 2 diabetic patients who may require early CAD intervention because of the potential risk of coronary atherosclerosis. Coron Artery Dis 26:396–401 Copyright © 2015 Wolters Kluwer Health, Inc. All rights reserved. Coronary Artery Disease 2015, 26:396–401 Keywords: coronary atherosclerosis, diabetes mellitus, galectin-3 Departments of aCardiology, bBiochemistry, Mehmet Akif Ersoy Thoracic and Cardiovascular Surgery Training and Research Hospital, cDepartment of Cardiology, Atakent Hospital, Acibadem University, Istanbul and dDepartment of Cardiology, Rize Kackar Government Hospital, Rize, Turkey Correspondence to Derya Ozturk, MD, Department of Cardiology, Mehmet Akif Ersoy Thoracic and Cardiovascular Surgery Training and Research Hospital, Istasyon Mah, Turgut Özal Bulvarı, No: 11, Küçükçekmece, Istanbul 34303, Turkey Tel: + 90 212 692 20 00; fax: + 90 212 471 94 94; e-mail: [email protected] Received 11 January 2015Received 10 March 2015 Accepted 19 March 2015
Levels of galectin-3, a member of a family of soluble β-galactoside-binding lectins, are reported to be higher in patients with type 2 DM and metabolic syndrome [6]. Although conflicting results exist on the effects of galectin-3 in these patients, studies have shown that high galectin-3 levels are related to microvascular and macrovascular complications in diabetic patients [7]. Although galectin-3 prevents diabetic nephropathy through its advanced glycation end product and advanced lipoxidation end product receptor functions, it is also related to an increased risk of diabetic retinopathy by the stimulation of macrophage chemotaxis, phagocytosis, neutrophil extravasation, oxidative stress, apoptosis, and angiogenesis [8,9]. In terms of the effects of galectin-3 on the macrovascular complications of DM, a relationship between peripheral artery disease and increased galectin-3 levels has been shown in DM patients by Jin et al. [10]. However, the exact pathophysiological relationship between coronary atherosclerosis and galectin-3 remains unclear, especially in diabetic adults. DOI: 10.1097/MCA.0000000000000252
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Galectin-3 and coronary atherosclerosis Ozturk et al. 397
To our knowledge, there are no studies on the association between galectin-3 levels and coronary plaque burdens/ structures in diabetic patients with coronary atherosclerosis. Thus, this study investigated the relationship between galectin-3 levels and CAD, coronary plaque burden, and plaque structure in patients with type 2 DM. As elevated galectin-3 levels are reported to be associated with inflammation, type 2 DM, metabolic syndrome, and peripheral artery disease [6–10], we hypothesized that galectin-3 may be associated with coronary plaque burdens/structures in diabetic patients with coronary atherosclerosis.
exceeded 140 mmHg and/or diastolic arterial pressure exceeded 90 mmHg, or if the patient was using antihypertensive drugs [11]. DM was diagnosed if fasting glucose levels exceeded 126 mg/dl or the patient used prescribed glucose-lowering agents [12]. Hyperlipidemia was defined as total serum cholesterol levels greater than 240 mg/dl, low-density lipoprotein (LDL) cholesterol more than 130 mg/dl, or serum triglycerides exceeding 180 mg/dl, or if the patient used lipid-lowering agents [13].
Patients and methods
CCTA images were obtained using a dual-source computed tomography system (Definition Flash; Siemens Medical Solutions, Forchheim, Germany) with 280 ms of rotation time, 2 × 128 slices, a pitch of 3.4, and triggering at 60% of the R-R interval. The tube current was set at 180–300 mAs and a 0.6 mm slice collimation was achieved. Nonionic contrast material (Iomeron 400 mg/ ml; Bracco, Milan, Italy) at a dose of 80–100 ml was administered at a rate of 5 ml/s with a dual-head power injector attached to an 18-gauge needle positioned in an antecubital vein. The bolus tracking technique was used, and images were obtained during a single, 6 s breathhold.
Patient selection
This single-center observational study was carried out at a tertiary heart care center. A total of 158 consecutive patients with DM undergoing planned CCTA were recruited for the present study. The indications for CCTA in the study population were patients with atypical chest pain, but at an intermediate risk for CAD, inconclusive or uninterpretable stress test results, suspected coronary anomalies, and without significant CAD before noncoronary cardiac surgery. The exclusion criteria were a previous diagnosis of CAD, coronary revascularization procedures, heart failure, valvular heart disease, aortic aneurysms, peripheral arterial atherosclerosis, type 1 DM, renal dysfunction, hepatitis B or C infection, other known liver diseases, hemolytic disorders, acute/chronic inflammatory conditions, neoplastic diseases, metformin use within the previous month, and missing laboratory parameters.
Coronary computed tomography angiography examination
Image analysis
Missing variables were obtained by telephone interviews with the patients and/or their relatives. Verbal and written informed consent was obtained from each study participant and the study protocol was approved by the local ethics committee.
Two experienced radiologists, blinded to the clinical data of the patients, analyzed the scans on a three-dimensional workstation (Syngo; Siemens Healthcare, Erlangen, Germany); a consensus diagnosis was achieved using multidetector computed tomography. The radiologists analyzed the characteristics of the stenosis and the number of coronary plaques/segments on the basis of the modified American Heart Association classification [14]. Plaques were defined as 1 mm2 structures within or adjacent to a vessel lumen that could be clearly distinguished from the lumen and the surrounding pericardial tissue. Coronary plaques were classified as noncalcified, calcified, and mixed according to their structure. Plaques without any calcification were defined as noncalcified plaques, plaques with more than 50% of the plaque area occupied by calcified tissue (density, ≥ 130 HU in native scans) were defined as calcified, and plaques with less than 50% calcified tissue were defined as mixed type [15]. The plaque burden was calculated as the sum of the atherosclerotic segments (one point for each) in the coronary arteries, which were divided into 15 segments [14].
Definitions
Laboratory analyses
The patients provided data on their daily smoking habits. Past smokers, who were included in the smoker category, were defined as those who had abstained from smoking for more than 3 months at the time of the examination. Hypertension was diagnosed if systolic arterial pressure
After they had undergone a 12 h fast, venous blood samples were drawn from the patients to determine levels of hemoglobin A1c (HbA1c), high-sensitivity C-reactive protein (hs-CRP), total cholesterol, triglycerides, and serum creatinine (Cobas C501 Autoanalyzer;
After an evaluation of the CCTA images, the study population was divided into two groups (a CAD group and a non-CAD group) on the basis of the presence of coronary atherosclerosis. Demographic information and cardiovascular risk factors (age, family history, smoking habits, hyperlipidemia, BMI, hypertension, and DM) were recorded following a systematic review of the patients’ hospital records. The heights and weights of the study participants were measured, and BMI was calculated as body weight in kilograms divided by the square of the height in meters (kg/m2).
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Coronary Artery Disease 2015, Vol 26 No 5
Roche Diagnostics, Mannheim, Germany). Serum creatinine levels were measured using the alkaline picrate (Jaffe) method and hs-CRP levels were analyzed turbidimetrically. Serum galectin-3 levels were measured with a commercially available kit using an enzyme-linked immunosorbent assay method (Human galectin-3 ELISA kit, Catalogue No. SK00199-01; Aviscera Bioscience Inc., Santa Clara, California, USA). Statistical analysis
Descriptive statistics were expressed as numbers (%) for categorical variables and as means ± SD for numerical variables. The normal distribution of continuous variables was checked using the Kolmogorov–Smirnov test. The differences between the patients and controls were evaluated using two-sample t-tests and the Mann–Whitney U-test, as appropriate. A χ2-test was used to compare independent categorical variables. The relationships between the numerical variables were identified using Spearman correlation tests and a receiver operator characteristic curve analysis was carried out to determine the galectin-3 cutoff values for the diagnosis of coronary atherosclerosis. In addition, stepwise multivariate logistic regression analyses, which included variables with P-values less than 0.10 in the univariate analysis, were carried out to identify the independent predictors of coronary atherosclerosis; a P-value less than 0.05 was considered significant. Data were analyzed using the Statistical Package for the Social Sciences, version 16.0 (SPSS Inc., Chicago, Illinois, USA).
Results The present study included 77 patients (mean age, 56.06 ± 8.1 years; 64.9% men) with coronary atherosclerosis and 80 patients with normal coronary arteries (mean age, 52.1 ± 7.4 years; 41.2% men). The baseline demographics and clinical and laboratory characteristics of the study groups are summarized in Table 1. When compared with the non-CAD group, the CAD group included older (P = 0.002) male (P = 0.003) patients with higher BMIs (P = 0.003) and more smokers (P = 0.001) than the non-CAD group. Among the CAD patients, the mean number of diseased vessels per patient was 2.6 ± 1.01, and the total number of plaques was 4.58 ± 2.1. Of a total of 353 plaques, the most commonly observed plaque structure was the mixed type (n = 155, 43.9%), with 116 (32.8%) of the remaining plaques being noncalcified and 82 (23.2%) calcified. An evaluation of the biochemical parameters showed that, compared with the non-CAD group, the plasma creatinine and hs-CRP levels were significantly higher in the CAD group (P < 0.001, each). The LDL cholesterol and triglyceride levels were also higher in the CAD group than in the non-CAD group (P = 0.02 and 0.01, respectively), and the high-density lipoprotein cholesterol
Table 1 Baseline demographic, clinical, and laboratory characteristics of the study groups Non-CAD group (n = 80) Age (years) Sex (male) [n (%)] Hypertension [n (%)] Smokers [n (%)] BMI (kg/m2) Laboratory findings Total cholesterol (mg/dl) HDL cholesterol (mg/dl) LDL cholesterol (mg/dl) Triglycerides (mg/dl) hs-CRP (mg/l) FPG (mg/dl) HbA1c (%) Creatinine (mg/dl) WBC (×109/l) Galectin-3 (pg/ml) CCTA findings Number of diseased vessels Number of plaques Distribution of plaques Mixed type [n (%)] Noncalcified type [n (%)] Calcified type [n (%)]
CAD group (n = 77)
P-value
52.1 ± 7.4 47 (58.7) 42 (52.5) 32 (40.0) 26.1 ± 3.9
56.0 ± 8.19 27 (35.0) 52 (67.5) 52 (67.5) 28 ± 3.5
0.002 0.003 0.055 0.001 0.003
179.3 ± 44.6 50.7 ± 13.0 100.4 ± 39.7 148.9 ± 56.0 1.3 ± 0.4 150.6 ± 45.0 7.6 ± 1.2 0.6 ± 0.1 7.5 ± 2.1 830.2 ± 434.9
189.4 ± 33.4 42.6 ± 10.4 114.1 ± 33.2 177.1 ± 85.0 2.0 ± 0.6 179.0 ± 125.7 8.0 ± 1.3 0.7 ± 0.2 8.4 ± 2.3 1412.0 ± 441.7
0.114 0.0001 0.002 0.01 0.0001 0.061 0.125 0.0001 0.014 0.0001
–
2.6 ± 1.01
–
–
4.5 ± 2.1
–
– – –
155 (43.9) 116 (32.8) 82 (23.2)
– – –
CAD, coronary artery disease; CCTA, coronary computed tomography angiography; FPG, fasting plasma glucose; HbA1c, hemoglobin A1c; HDL, highdensity lipoprotein; hs-CRP, high-sensitivity C-reactive protein; LDL, low-density lipoprotein; WBC, white blood cells.
levels were significantly lower in the CAD group (P < 0.001). However, the HbA1c and glucose levels were not significantly different between the two groups. The patients in the CAD group showed higher white blood cell and neutrophil counts than those in the non-CAD group (P = 0.01 and P < 0.001, respectively). Compared with the non-CAD group, the galectin-3 levels were also significantly higher in the CAD group (830.2 ± 434.9 vs. 1412.0 ± 441.7 pg/ml; P < 0.001) (Fig. 1). To investigate the predictive value of galectin-3 for coronary atherosclerosis in patients with DM, a receiver operator characteristic curve was generated for sensitivity and specificity using the respective areas under the curve. The analysis indicated that galectin-3 levels of more than 1102.5 pg/ml had a 76.6% sensitivity and an 80.0% specificity for predicting coronary atherosclerosis in the DM patients (area under the curve, 0.830; 95% confidence interval, 0.766–0.893; P < 0.001); its negative and positive predictive values were 78.7 and 78.0%, respectively (Fig. 2). In a univariate regression analysis, age, male sex, BMI, smoking, hypertension, hs-CRP, LDL cholesterol, highdensity lipoprotein cholesterol, creatinine, and galectin-3 levels were associated significantly with coronary atherosclerosis (Table 2). In the multivariate analysis, age, smoking, galectin-3, hs-CRP, and LDL cholesterol were significant independent predictors of coronary
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Galectin-3 and coronary atherosclerosis Ozturk et al. 399
Univariate analysis for predictors of coronary atherosclerosis
Fig. 1
Table 2
1.0 Age Creatinine Sex BMI Hypertension Smoking Galectin-3 HbA1c hs-CRP LDL cholesterol
Sensitivity
0.8
0.6
P-value
OR
95% confidence interval
0.003 0.001 0.003 0.002 0.056 0.001 < 0.001 0.128 < 0.001 0.023
1.066 21.862 2.637 1.139 1.882 3.120 1.003 1.211 11 255 1010
1022–1110 3462–138 057 1382–5032 1050–1234 984–3598 1622–6000 1002–1004 946–1550 4840–26 168 1001–1019
HbA1c, hemoglobin A1c; hs-CRP, high-sensitivity C-reactive protein; LDL, lowdensity lipoprotein; OR, odds ratio.
0.4
Multivariate logistic regression analysis for independent predictors of coronary atherosclerosis
Table 3
0.2
0.0 0.0
0.2
0.4 0.6 1 − specificity
0.8
1.0
Galectin-3 concentrations in the coronary artery disease (CAD) and non-CAD groups (AUC = 0.803; 95% confidence interval, 0.766–0.893; P < 0.001).
Age Creatinine Sex BMI Hypertension Smoking Galectin-3 hs-CRP LDL cholesterol
P
OR
95% confidence interval
0.002 0.675 0.299 0.186 0.821 0.005 0.021 0.005 0.013
1.149 0.576 2.003 1.091 1.155 7.073 1.002 7.172 1.021
1.054–1.252 0.044–7.605 0.540–7.433 0.959–1.241 0.334–3.997 1.827–27.384 1.000–1.003 1.831–28.103 1.004–1.037
hs-CRP, high-sensitivity C-reactive protein; LDL, low-density lipoprotein; OR, odds ratio. Fig. 2
2000.00
Correlation analysis between galectin-3 and other variables
Table 4
104
Galectin-3
Galectin-3
1500.00
1000.00
500.00
0.00 Non-CAD group
CAD group
Receiver operator characteristic curves showing the predictive value of galectin-3 for coronary atherosclerosis. CAD, coronary artery disease.
atherosclerosis after adjusting for other risk factors in patients with type 2 DM (Table 3). In the Spearman–Pearson correlation analysis, galectin-3 levels were correlated positively with BMI, hs-CRP, the number of diseased vessels, and the total number of plaques (each, P < 0.001). Moreover, a positive correlation was detected between the calcified plaque type and galectin-3 levels (r = 0.457, P < 0.001). However, galectin-3 levels were not correlated with HbA1c levels (Table 4).
BMI r P HbA1c r P hs-CRP r P Number of plaques r P Number of diseased vessels r P Number of diseased segments r P Calcified plaques r P Noncalcified plaques r P Mixed plaques r P
0.358 0.0001 0.112 0.162 0.713 0.0001 0.693 0.0001 0.53 0.0001 0.666 0.0001 0.457 0.001 0.115 0.321 0.188 0.101
HbA1c, hemoglobin A1c; hs-CRP, high-sensitivity C-reactive protein.
In addition, hs-CRP also correlated positively with the total number of plaques (r = 0.275, P = 0.01) and the number of diseased segments (r = 0.257, P =0.02).
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400 Coronary Artery Disease 2015, Vol 26 No 5
Discussion The main findings of the present study were as follows: (1) In patients with type 2 DM, high galectin-3 levels are a predictor of coronary atherosclerosis. (2) Galectin-3 levels are correlated with BMI, hs-CRP levels, the number of diseased vessels and segments, the total number of plaques, and the calcified plaque type in patients with type 2 DM. (3) In addition to galectin-3, older age, smoking, high hsCRP levels, and high LDL cholesterol levels are also predictors of coronary atherosclerosis in patients with type 2 DM. Galectin-3 is a carbohydrate-binding protein that plays an important role in the regulation of the inflammatory process. This lectin has both proinflammatory and antiinflammatory actions, depending on multiple factors, including the type of inflammatory setting and the target cell/tissue [16]. Galectin-3 expression on the left ventricle myocardium at both the transcriptional and translational levels in the early ischemic period has been reported by Hashmi and Al-Salam [17]. Recently, galectin-3 was described as a significant predictor of heart failure and is establishing itself as a useful prognostic marker for that indication [18,19]. Moreover, Bozcali et al. [20] reported increased levels of galectin-3 in patients with cardiac syndrome X compared with healthy individuals. Similar to our study, both the galectin-3 and the hsCRP levels were found to be significant independent predictors of cardiac syndrome X after adjusting for other confounding factors. Galectin-3 was also correlated positively with inflammatory markers such as hs-CRP, which is consistent with our findings. However, results on the association between galectin-3 and atherosclerosis have been inconsistent. Two studies investigating apolipoprotein E-deficient mice and galectin-3 gene inactivation reported fewer and smaller atherosclerotic lesions and reduced inflammation in animals with low levels of active galectin-3 [21,22]. However, Iacobini et al. [23] showed that in mice fed a high-fat diet, deletion of galectin-3 increased the degree of atherosclerosis. In a clinical study, Madrigal-Matute et al. [24] found a relationship between high galectin-3 levels and increased carotid intima-media thickness; high galectin-3 levels were also found to be associated with an increased CVD mortality risk in patients with peripheral artery disease. Despite previous studies showing that galectin-3 levels are higher in patients with type 2 DM and metabolic syndrome, the effect of galectin-3 on DM patients is conflicting [7]. High galectin-3 levels have been found to increase the risk of diabetic retinopathy through proinflammatory and profibrotic effects; however, the protective role of galectin-3 against diabetic nephropathy was
also shown and is believed to be because of its advanced glycation end product/advanced lipoxidation end product receptor function and possibly a direct anti-inflammatory effect [7,9]. Recently, Jin et al. [10] investigated the relationship between galectin-3 levels and microvascular and macrovascular complications in diabetic patients, showing an association between galectin-3 and diabetic nephropathy, retinopathy, and peripheral vascular disease. Nevertheless, to the best of our knowledge, despite a relationship between galectin-3 and cardiovascular events being shown in patients with CAD [25,26], data on the association between galectin-3 and coronary atherosclerosis/plaque burden have not been published to date. We investigated this relationship using CCTA, which is a noninvasive imaging technique with a high sensitivity and specificity for the diagnosis of CVD; the technique provides valuable information on an individual’s plaque burden and plaque structure [5]. In the present study, galectin-3 levels were higher in patients with coronary atherosclerosis, and they were also independent predictors of coronary atherosclerosis in patients with DM. This study also established a relationship between galectin-3 levels and CCTA-determined plaque burden/ structure, which had not been investigated previously. It was shown that galectin-3 levels are associated with plaque burden and correlated positively with the total number of plaques and diseased vessels. We also evaluated the association between plaque composition and galectin-3 levels. In the current study population, the most common plaque composition was the mixed type. However, galectin-3 levels were correlated with the presence of calcified plaque. Similarly, Menini et al. [27] investigated the association between galectin-3 levels and vascular osteogenesis in carotid plaques, reporting the presence of increased galectin-3 levels in sheet-like and lamellated (macrocalcified) plaques, which are more stable than microcalcified plaques. This association was considered to be because of galectin-3’s regulation of the Wnt/B-catenin signaling pathway, which regulates osteogenesis. The correlation between calcified coronary plaques and galectin-3 in the present study might also reflect the increased osteogenic effect of galectin-3 on vascular smooth muscle cells [27]. Study limitations
The present study has some limitations. First, this study involved a single center and a small study population. Second, the absence of follow-up data describing future cardiovascular events meant that the prognostic value of galectin-3 levels was not evaluated. Third, the study could have provided more accurate information if the association between galectin-3 and plaque composition had been evaluated with intravascular ultrasound.
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Galectin-3 and coronary atherosclerosis Ozturk et al. 401
Conclusion
We found a significant relationship between serum galectin-3 levels and the total number of coronary plaques and the macrocalcified plaque structures, as detected by CCTA, of patients with type 2 DM. In addition, galectin-3 levels were found to be a significant independent predictor of coronary atherosclerosis in type 2 diabetic patients. Galectin-3 is a novel, promising biomarker that may help identify diabetic patients who may require early CAD intervention because of the potential risk of coronary atherosclerosis.
13
14
15
Acknowledgements Conflicts of interest
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There are no conflicts of interest. 17
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Original research
Association between serum galectin-3 levels and coronary atherosclerosis and plaque burden/structure in patients with type 2 diabetes mellitus Derya Ozturka, Omer Celika, Seckin Satilmisc, Serkan Aslana, Mehmet Erturka, Huseyin Altug Cakmakd, Ali Kemal Kalkana, Sinem Ozyilmaza, Vesile Dikerb and Mehmet Gula Background Levels of galectin-3, a member of a family of soluble β-galactoside-binding lectins, are reported to be higher in patients with type 2 diabetes mellitus (DM) and metabolic syndrome. Conflicting results exist on the effects of galectin-3 in diabetic patients. The aim of this study was to investigate the relationship between galectin-3 levels and coronary artery disease (CAD), coronary plaque burden, and plaque structures in patients with type 2 DM. Patients and methods A total of 158 consecutive patients with type 2 DM undergoing planned coronary computed tomography angiography (CCTA) were included in this study. The study population was divided into CAD and nonCAD groups according to the presence of CCTA-determined coronary atherosclerosis. Results Galectin-3 concentrations were significantly higher in the CAD group than in the non-CAD group (1412.0 ± 441.7 vs. 830.2 ± 434.9 pg/ml, P < 0.001). Galectin-3 levels were correlated positively with BMI, high-sensitivity C-reactive protein, the total number of diseased vessels, the number of plaques (all, P < 0.001), and the calcified plaque type (P = 0.001). In addition, galectin-3 levels were found to
Introduction Type 2 diabetes mellitus (DM) is an important risk factor for cardiovascular disease (CVD), with ∼ 60% of DM patients having CVD and an overall rate of cardiovascular mortality that is twice that of nondiabetic individuals [1]. Cardiovascular risk assessment is important for these patients as it influences decisions on the frequency of follow-up and the diagnostic methods used. New biomarkers and diagnostic strategies are therefore required for the early detection of CVD in patients with DM. Noninvasive imaging modalities, such as carotid intimamedia thickness measurements and coronary artery calcium score calculations, have gained attention in the diagnosis of subclinical atherosclerosis and risk predictions for future adverse cardiovascular events [2,3]. Coronary computed tomography angiography (CCTA), which is a noninvasive imaging technique with high sensitivity and specificity for the diagnosis of coronary artery disease (CAD), may provide valuable information on an individual’s plaque burden and plaque structure [4,5]. 0954-6928 Copyright © 2015 Wolters Kluwer Health, Inc. All rights reserved.
be a significant independent predictor of coronary atherosclerosis in type 2 diabetic patients (P = 021; odds ratio, 1.002; 95% confidence interval, 1.000–1.003). Conclusion Galectin-3 is a novel, promising biomarker that may help identify type 2 diabetic patients who may require early CAD intervention because of the potential risk of coronary atherosclerosis. Coron Artery Dis 26:396–401 Copyright © 2015 Wolters Kluwer Health, Inc. All rights reserved. Coronary Artery Disease 2015, 26:396–401 Keywords: coronary atherosclerosis, diabetes mellitus, galectin-3 Departments of aCardiology, bBiochemistry, Mehmet Akif Ersoy Thoracic and Cardiovascular Surgery Training and Research Hospital, cDepartment of Cardiology, Atakent Hospital, Acibadem University, Istanbul and dDepartment of Cardiology, Rize Kackar Government Hospital, Rize, Turkey Correspondence to Derya Ozturk, MD, Department of Cardiology, Mehmet Akif Ersoy Thoracic and Cardiovascular Surgery Training and Research Hospital, Istasyon Mah, Turgut Özal Bulvarı, No: 11, Küçükçekmece, Istanbul 34303, Turkey Tel: + 90 212 692 20 00; fax: + 90 212 471 94 94; e-mail: [email protected] Received 11 January 2015Received 10 March 2015 Accepted 19 March 2015
Levels of galectin-3, a member of a family of soluble β-galactoside-binding lectins, are reported to be higher in patients with type 2 DM and metabolic syndrome [6]. Although conflicting results exist on the effects of galectin-3 in these patients, studies have shown that high galectin-3 levels are related to microvascular and macrovascular complications in diabetic patients [7]. Although galectin-3 prevents diabetic nephropathy through its advanced glycation end product and advanced lipoxidation end product receptor functions, it is also related to an increased risk of diabetic retinopathy by the stimulation of macrophage chemotaxis, phagocytosis, neutrophil extravasation, oxidative stress, apoptosis, and angiogenesis [8,9]. In terms of the effects of galectin-3 on the macrovascular complications of DM, a relationship between peripheral artery disease and increased galectin-3 levels has been shown in DM patients by Jin et al. [10]. However, the exact pathophysiological relationship between coronary atherosclerosis and galectin-3 remains unclear, especially in diabetic adults. DOI: 10.1097/MCA.0000000000000252
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Galectin-3 and coronary atherosclerosis Ozturk et al. 397
To our knowledge, there are no studies on the association between galectin-3 levels and coronary plaque burdens/ structures in diabetic patients with coronary atherosclerosis. Thus, this study investigated the relationship between galectin-3 levels and CAD, coronary plaque burden, and plaque structure in patients with type 2 DM. As elevated galectin-3 levels are reported to be associated with inflammation, type 2 DM, metabolic syndrome, and peripheral artery disease [6–10], we hypothesized that galectin-3 may be associated with coronary plaque burdens/structures in diabetic patients with coronary atherosclerosis.
exceeded 140 mmHg and/or diastolic arterial pressure exceeded 90 mmHg, or if the patient was using antihypertensive drugs [11]. DM was diagnosed if fasting glucose levels exceeded 126 mg/dl or the patient used prescribed glucose-lowering agents [12]. Hyperlipidemia was defined as total serum cholesterol levels greater than 240 mg/dl, low-density lipoprotein (LDL) cholesterol more than 130 mg/dl, or serum triglycerides exceeding 180 mg/dl, or if the patient used lipid-lowering agents [13].
Patients and methods
CCTA images were obtained using a dual-source computed tomography system (Definition Flash; Siemens Medical Solutions, Forchheim, Germany) with 280 ms of rotation time, 2 × 128 slices, a pitch of 3.4, and triggering at 60% of the R-R interval. The tube current was set at 180–300 mAs and a 0.6 mm slice collimation was achieved. Nonionic contrast material (Iomeron 400 mg/ ml; Bracco, Milan, Italy) at a dose of 80–100 ml was administered at a rate of 5 ml/s with a dual-head power injector attached to an 18-gauge needle positioned in an antecubital vein. The bolus tracking technique was used, and images were obtained during a single, 6 s breathhold.
Patient selection
This single-center observational study was carried out at a tertiary heart care center. A total of 158 consecutive patients with DM undergoing planned CCTA were recruited for the present study. The indications for CCTA in the study population were patients with atypical chest pain, but at an intermediate risk for CAD, inconclusive or uninterpretable stress test results, suspected coronary anomalies, and without significant CAD before noncoronary cardiac surgery. The exclusion criteria were a previous diagnosis of CAD, coronary revascularization procedures, heart failure, valvular heart disease, aortic aneurysms, peripheral arterial atherosclerosis, type 1 DM, renal dysfunction, hepatitis B or C infection, other known liver diseases, hemolytic disorders, acute/chronic inflammatory conditions, neoplastic diseases, metformin use within the previous month, and missing laboratory parameters.
Coronary computed tomography angiography examination
Image analysis
Missing variables were obtained by telephone interviews with the patients and/or their relatives. Verbal and written informed consent was obtained from each study participant and the study protocol was approved by the local ethics committee.
Two experienced radiologists, blinded to the clinical data of the patients, analyzed the scans on a three-dimensional workstation (Syngo; Siemens Healthcare, Erlangen, Germany); a consensus diagnosis was achieved using multidetector computed tomography. The radiologists analyzed the characteristics of the stenosis and the number of coronary plaques/segments on the basis of the modified American Heart Association classification [14]. Plaques were defined as 1 mm2 structures within or adjacent to a vessel lumen that could be clearly distinguished from the lumen and the surrounding pericardial tissue. Coronary plaques were classified as noncalcified, calcified, and mixed according to their structure. Plaques without any calcification were defined as noncalcified plaques, plaques with more than 50% of the plaque area occupied by calcified tissue (density, ≥ 130 HU in native scans) were defined as calcified, and plaques with less than 50% calcified tissue were defined as mixed type [15]. The plaque burden was calculated as the sum of the atherosclerotic segments (one point for each) in the coronary arteries, which were divided into 15 segments [14].
Definitions
Laboratory analyses
The patients provided data on their daily smoking habits. Past smokers, who were included in the smoker category, were defined as those who had abstained from smoking for more than 3 months at the time of the examination. Hypertension was diagnosed if systolic arterial pressure
After they had undergone a 12 h fast, venous blood samples were drawn from the patients to determine levels of hemoglobin A1c (HbA1c), high-sensitivity C-reactive protein (hs-CRP), total cholesterol, triglycerides, and serum creatinine (Cobas C501 Autoanalyzer;
After an evaluation of the CCTA images, the study population was divided into two groups (a CAD group and a non-CAD group) on the basis of the presence of coronary atherosclerosis. Demographic information and cardiovascular risk factors (age, family history, smoking habits, hyperlipidemia, BMI, hypertension, and DM) were recorded following a systematic review of the patients’ hospital records. The heights and weights of the study participants were measured, and BMI was calculated as body weight in kilograms divided by the square of the height in meters (kg/m2).
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Coronary Artery Disease 2015, Vol 26 No 5
Roche Diagnostics, Mannheim, Germany). Serum creatinine levels were measured using the alkaline picrate (Jaffe) method and hs-CRP levels were analyzed turbidimetrically. Serum galectin-3 levels were measured with a commercially available kit using an enzyme-linked immunosorbent assay method (Human galectin-3 ELISA kit, Catalogue No. SK00199-01; Aviscera Bioscience Inc., Santa Clara, California, USA). Statistical analysis
Descriptive statistics were expressed as numbers (%) for categorical variables and as means ± SD for numerical variables. The normal distribution of continuous variables was checked using the Kolmogorov–Smirnov test. The differences between the patients and controls were evaluated using two-sample t-tests and the Mann–Whitney U-test, as appropriate. A χ2-test was used to compare independent categorical variables. The relationships between the numerical variables were identified using Spearman correlation tests and a receiver operator characteristic curve analysis was carried out to determine the galectin-3 cutoff values for the diagnosis of coronary atherosclerosis. In addition, stepwise multivariate logistic regression analyses, which included variables with P-values less than 0.10 in the univariate analysis, were carried out to identify the independent predictors of coronary atherosclerosis; a P-value less than 0.05 was considered significant. Data were analyzed using the Statistical Package for the Social Sciences, version 16.0 (SPSS Inc., Chicago, Illinois, USA).
Results The present study included 77 patients (mean age, 56.06 ± 8.1 years; 64.9% men) with coronary atherosclerosis and 80 patients with normal coronary arteries (mean age, 52.1 ± 7.4 years; 41.2% men). The baseline demographics and clinical and laboratory characteristics of the study groups are summarized in Table 1. When compared with the non-CAD group, the CAD group included older (P = 0.002) male (P = 0.003) patients with higher BMIs (P = 0.003) and more smokers (P = 0.001) than the non-CAD group. Among the CAD patients, the mean number of diseased vessels per patient was 2.6 ± 1.01, and the total number of plaques was 4.58 ± 2.1. Of a total of 353 plaques, the most commonly observed plaque structure was the mixed type (n = 155, 43.9%), with 116 (32.8%) of the remaining plaques being noncalcified and 82 (23.2%) calcified. An evaluation of the biochemical parameters showed that, compared with the non-CAD group, the plasma creatinine and hs-CRP levels were significantly higher in the CAD group (P < 0.001, each). The LDL cholesterol and triglyceride levels were also higher in the CAD group than in the non-CAD group (P = 0.02 and 0.01, respectively), and the high-density lipoprotein cholesterol
Table 1 Baseline demographic, clinical, and laboratory characteristics of the study groups Non-CAD group (n = 80) Age (years) Sex (male) [n (%)] Hypertension [n (%)] Smokers [n (%)] BMI (kg/m2) Laboratory findings Total cholesterol (mg/dl) HDL cholesterol (mg/dl) LDL cholesterol (mg/dl) Triglycerides (mg/dl) hs-CRP (mg/l) FPG (mg/dl) HbA1c (%) Creatinine (mg/dl) WBC (×109/l) Galectin-3 (pg/ml) CCTA findings Number of diseased vessels Number of plaques Distribution of plaques Mixed type [n (%)] Noncalcified type [n (%)] Calcified type [n (%)]
CAD group (n = 77)
P-value
52.1 ± 7.4 47 (58.7) 42 (52.5) 32 (40.0) 26.1 ± 3.9
56.0 ± 8.19 27 (35.0) 52 (67.5) 52 (67.5) 28 ± 3.5
0.002 0.003 0.055 0.001 0.003
179.3 ± 44.6 50.7 ± 13.0 100.4 ± 39.7 148.9 ± 56.0 1.3 ± 0.4 150.6 ± 45.0 7.6 ± 1.2 0.6 ± 0.1 7.5 ± 2.1 830.2 ± 434.9
189.4 ± 33.4 42.6 ± 10.4 114.1 ± 33.2 177.1 ± 85.0 2.0 ± 0.6 179.0 ± 125.7 8.0 ± 1.3 0.7 ± 0.2 8.4 ± 2.3 1412.0 ± 441.7
0.114 0.0001 0.002 0.01 0.0001 0.061 0.125 0.0001 0.014 0.0001
–
2.6 ± 1.01
–
–
4.5 ± 2.1
–
– – –
155 (43.9) 116 (32.8) 82 (23.2)
– – –
CAD, coronary artery disease; CCTA, coronary computed tomography angiography; FPG, fasting plasma glucose; HbA1c, hemoglobin A1c; HDL, highdensity lipoprotein; hs-CRP, high-sensitivity C-reactive protein; LDL, low-density lipoprotein; WBC, white blood cells.
levels were significantly lower in the CAD group (P < 0.001). However, the HbA1c and glucose levels were not significantly different between the two groups. The patients in the CAD group showed higher white blood cell and neutrophil counts than those in the non-CAD group (P = 0.01 and P < 0.001, respectively). Compared with the non-CAD group, the galectin-3 levels were also significantly higher in the CAD group (830.2 ± 434.9 vs. 1412.0 ± 441.7 pg/ml; P < 0.001) (Fig. 1). To investigate the predictive value of galectin-3 for coronary atherosclerosis in patients with DM, a receiver operator characteristic curve was generated for sensitivity and specificity using the respective areas under the curve. The analysis indicated that galectin-3 levels of more than 1102.5 pg/ml had a 76.6% sensitivity and an 80.0% specificity for predicting coronary atherosclerosis in the DM patients (area under the curve, 0.830; 95% confidence interval, 0.766–0.893; P < 0.001); its negative and positive predictive values were 78.7 and 78.0%, respectively (Fig. 2). In a univariate regression analysis, age, male sex, BMI, smoking, hypertension, hs-CRP, LDL cholesterol, highdensity lipoprotein cholesterol, creatinine, and galectin-3 levels were associated significantly with coronary atherosclerosis (Table 2). In the multivariate analysis, age, smoking, galectin-3, hs-CRP, and LDL cholesterol were significant independent predictors of coronary
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Galectin-3 and coronary atherosclerosis Ozturk et al. 399
Univariate analysis for predictors of coronary atherosclerosis
Fig. 1
Table 2
1.0 Age Creatinine Sex BMI Hypertension Smoking Galectin-3 HbA1c hs-CRP LDL cholesterol
Sensitivity
0.8
0.6
P-value
OR
95% confidence interval
0.003 0.001 0.003 0.002 0.056 0.001 < 0.001 0.128 < 0.001 0.023
1.066 21.862 2.637 1.139 1.882 3.120 1.003 1.211 11 255 1010
1022–1110 3462–138 057 1382–5032 1050–1234 984–3598 1622–6000 1002–1004 946–1550 4840–26 168 1001–1019
HbA1c, hemoglobin A1c; hs-CRP, high-sensitivity C-reactive protein; LDL, lowdensity lipoprotein; OR, odds ratio.
0.4
Multivariate logistic regression analysis for independent predictors of coronary atherosclerosis
Table 3
0.2
0.0 0.0
0.2
0.4 0.6 1 − specificity
0.8
1.0
Galectin-3 concentrations in the coronary artery disease (CAD) and non-CAD groups (AUC = 0.803; 95% confidence interval, 0.766–0.893; P < 0.001).
Age Creatinine Sex BMI Hypertension Smoking Galectin-3 hs-CRP LDL cholesterol
P
OR
95% confidence interval
0.002 0.675 0.299 0.186 0.821 0.005 0.021 0.005 0.013
1.149 0.576 2.003 1.091 1.155 7.073 1.002 7.172 1.021
1.054–1.252 0.044–7.605 0.540–7.433 0.959–1.241 0.334–3.997 1.827–27.384 1.000–1.003 1.831–28.103 1.004–1.037
hs-CRP, high-sensitivity C-reactive protein; LDL, low-density lipoprotein; OR, odds ratio. Fig. 2
2000.00
Correlation analysis between galectin-3 and other variables
Table 4
104
Galectin-3
Galectin-3
1500.00
1000.00
500.00
0.00 Non-CAD group
CAD group
Receiver operator characteristic curves showing the predictive value of galectin-3 for coronary atherosclerosis. CAD, coronary artery disease.
atherosclerosis after adjusting for other risk factors in patients with type 2 DM (Table 3). In the Spearman–Pearson correlation analysis, galectin-3 levels were correlated positively with BMI, hs-CRP, the number of diseased vessels, and the total number of plaques (each, P < 0.001). Moreover, a positive correlation was detected between the calcified plaque type and galectin-3 levels (r = 0.457, P < 0.001). However, galectin-3 levels were not correlated with HbA1c levels (Table 4).
BMI r P HbA1c r P hs-CRP r P Number of plaques r P Number of diseased vessels r P Number of diseased segments r P Calcified plaques r P Noncalcified plaques r P Mixed plaques r P
0.358 0.0001 0.112 0.162 0.713 0.0001 0.693 0.0001 0.53 0.0001 0.666 0.0001 0.457 0.001 0.115 0.321 0.188 0.101
HbA1c, hemoglobin A1c; hs-CRP, high-sensitivity C-reactive protein.
In addition, hs-CRP also correlated positively with the total number of plaques (r = 0.275, P = 0.01) and the number of diseased segments (r = 0.257, P =0.02).
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400 Coronary Artery Disease 2015, Vol 26 No 5
Discussion The main findings of the present study were as follows: (1) In patients with type 2 DM, high galectin-3 levels are a predictor of coronary atherosclerosis. (2) Galectin-3 levels are correlated with BMI, hs-CRP levels, the number of diseased vessels and segments, the total number of plaques, and the calcified plaque type in patients with type 2 DM. (3) In addition to galectin-3, older age, smoking, high hsCRP levels, and high LDL cholesterol levels are also predictors of coronary atherosclerosis in patients with type 2 DM. Galectin-3 is a carbohydrate-binding protein that plays an important role in the regulation of the inflammatory process. This lectin has both proinflammatory and antiinflammatory actions, depending on multiple factors, including the type of inflammatory setting and the target cell/tissue [16]. Galectin-3 expression on the left ventricle myocardium at both the transcriptional and translational levels in the early ischemic period has been reported by Hashmi and Al-Salam [17]. Recently, galectin-3 was described as a significant predictor of heart failure and is establishing itself as a useful prognostic marker for that indication [18,19]. Moreover, Bozcali et al. [20] reported increased levels of galectin-3 in patients with cardiac syndrome X compared with healthy individuals. Similar to our study, both the galectin-3 and the hsCRP levels were found to be significant independent predictors of cardiac syndrome X after adjusting for other confounding factors. Galectin-3 was also correlated positively with inflammatory markers such as hs-CRP, which is consistent with our findings. However, results on the association between galectin-3 and atherosclerosis have been inconsistent. Two studies investigating apolipoprotein E-deficient mice and galectin-3 gene inactivation reported fewer and smaller atherosclerotic lesions and reduced inflammation in animals with low levels of active galectin-3 [21,22]. However, Iacobini et al. [23] showed that in mice fed a high-fat diet, deletion of galectin-3 increased the degree of atherosclerosis. In a clinical study, Madrigal-Matute et al. [24] found a relationship between high galectin-3 levels and increased carotid intima-media thickness; high galectin-3 levels were also found to be associated with an increased CVD mortality risk in patients with peripheral artery disease. Despite previous studies showing that galectin-3 levels are higher in patients with type 2 DM and metabolic syndrome, the effect of galectin-3 on DM patients is conflicting [7]. High galectin-3 levels have been found to increase the risk of diabetic retinopathy through proinflammatory and profibrotic effects; however, the protective role of galectin-3 against diabetic nephropathy was
also shown and is believed to be because of its advanced glycation end product/advanced lipoxidation end product receptor function and possibly a direct anti-inflammatory effect [7,9]. Recently, Jin et al. [10] investigated the relationship between galectin-3 levels and microvascular and macrovascular complications in diabetic patients, showing an association between galectin-3 and diabetic nephropathy, retinopathy, and peripheral vascular disease. Nevertheless, to the best of our knowledge, despite a relationship between galectin-3 and cardiovascular events being shown in patients with CAD [25,26], data on the association between galectin-3 and coronary atherosclerosis/plaque burden have not been published to date. We investigated this relationship using CCTA, which is a noninvasive imaging technique with a high sensitivity and specificity for the diagnosis of CVD; the technique provides valuable information on an individual’s plaque burden and plaque structure [5]. In the present study, galectin-3 levels were higher in patients with coronary atherosclerosis, and they were also independent predictors of coronary atherosclerosis in patients with DM. This study also established a relationship between galectin-3 levels and CCTA-determined plaque burden/ structure, which had not been investigated previously. It was shown that galectin-3 levels are associated with plaque burden and correlated positively with the total number of plaques and diseased vessels. We also evaluated the association between plaque composition and galectin-3 levels. In the current study population, the most common plaque composition was the mixed type. However, galectin-3 levels were correlated with the presence of calcified plaque. Similarly, Menini et al. [27] investigated the association between galectin-3 levels and vascular osteogenesis in carotid plaques, reporting the presence of increased galectin-3 levels in sheet-like and lamellated (macrocalcified) plaques, which are more stable than microcalcified plaques. This association was considered to be because of galectin-3’s regulation of the Wnt/B-catenin signaling pathway, which regulates osteogenesis. The correlation between calcified coronary plaques and galectin-3 in the present study might also reflect the increased osteogenic effect of galectin-3 on vascular smooth muscle cells [27]. Study limitations
The present study has some limitations. First, this study involved a single center and a small study population. Second, the absence of follow-up data describing future cardiovascular events meant that the prognostic value of galectin-3 levels was not evaluated. Third, the study could have provided more accurate information if the association between galectin-3 and plaque composition had been evaluated with intravascular ultrasound.
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Galectin-3 and coronary atherosclerosis Ozturk et al. 401
Conclusion
We found a significant relationship between serum galectin-3 levels and the total number of coronary plaques and the macrocalcified plaque structures, as detected by CCTA, of patients with type 2 DM. In addition, galectin-3 levels were found to be a significant independent predictor of coronary atherosclerosis in type 2 diabetic patients. Galectin-3 is a novel, promising biomarker that may help identify diabetic patients who may require early CAD intervention because of the potential risk of coronary atherosclerosis.
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15
Acknowledgements Conflicts of interest
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There are no conflicts of interest. 17
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