- Academic Editor
†These authors contributed equally.
Background: Existing research has shown that retinol binding protein
(RBP4) has an impairing effect on arterial elasticity and induces insulin
resistance, but the clinical value of RBP4 in patients with coronary heart
disease (CHD) combined with type 2 diabetes mellitus (T2DM) has not been
investigated. This study sought to compare the complexity of coronary artery
lesions and coronary artery elasticity between patients with CHD combined with
T2DM and those with CHD without T2DM, analyze the risk factors affecting coronary
artery elasticity, and investigate the value of RBP4 in assessing coronary artery
elasticity in patients with CHD and T2DM. Methods: A total of 130
patients with confirmed CHD were consecutively enrolled, including 38 patients
with CHD combined with T2DM and 92 patients with CHD without T2DM. Basic clinical
data, laboratory findings, coronary angiography and intravascular ultrasound
(IVUS) imaging data, and Gensini scores and coronary artery elasticity parameters
were calculated in both groups. Elasticity parameters included: stiffness
parameter (
Coronary heart disease (CHD) is the most common type of cardiovascular diseases caused by atherosclerosis. Therefore it is of great importance to determine the risk factors and underlying mechanisms associated with CHD. Diabetes is considered to be one of the major risk factors for CHD, even after adjusting for the effects of hypertension, age, and smoking [1]. Moreover, diabetes mellitus is currently exhibiting an epidemic trend worldwide [2]. A retrospective cohort study by Booth et al. [3] showed that patients with type 2 diabetes mellitus (T2DM) had a 2- to 4-fold higher risk of developing CHD compared to the general population, and that the mortality rate of CHD was also increased [4]. Following percutaneous coronary intervention (PCI), the risk of stent restenosis in CHD patients with T2DM was 2.5-fold higher than those without T2DM [5].
Retinol-binding protein 4 (RBP4) is a novel adipokine secreted by adipocytes and
the liver, and is significantly elevated in patients with T2DM [6]. Previous
studies have confirmed that RBP4 can be involved in the development of T2DM by
inducing insulin resistance and impairing islet
These findings on the correlation between RBP4, T2DM and CHD suggest that elevated RBP4 levels act as an important risk factor for the progression of coronary lesions in patients with CHD combined with T2DM [10]. As an integral part of the cardiovascular system, changes in arterial elasticity often occur in the early stages of the disease and could reflect dysfunction of the entire cardiovascular system. Arterial elasticity has been shown to be an important predictor for the development of cardiovascular disease [11, 12]. There are currently several tools available for the measurement of coronary artery elasticity function. Intravascular ultrasound (IVUS), an invasive examination, is able to obtain images of lumen changes inside the coronary vessels for the complete cardiac cycle. Combined with the measurement of intracoronary pressure changes, the use of IVUS could allow more accurate calculation of elasticity parameters. In fact, this tool has already been used to measure pulmonary artery elasticity in patients with pulmonary hypertension [13].
This study sought to investigate the value of RBP4 in assessing coronary artery elasticity in patients with CHD combined with T2DM, to investigate new therapeutic strategies to improve the prognosis of these patients.
Patients with stable CHD who were admitted to the Department of Cardiology of the Second Affiliated Hospital of Soochow University from February 2017 to October 2021 and had coronary angiography and IVUS completed during their hospitalization were divided into two groups according to whether they had T2DM or not. A total of 130 patients were enrolled, including 38 patients in the CHD with T2DM group (31 males and 7 females) and 92 patients in the CHD without T2DM group (78 males and 14 females). All enrolled patients provided informed consent, and the study was approved by the Ethics Committee of the Second Affiliated Hospital of Soochow University.
CHD was defined as cardiac disease with
Clinical information collected included age, gender, height, weight, a past medical history (history of hypertension, diabetes, atrial fibrillation, stroke, myocardial infarction, PCI, and heart failure) and a personal history (history of smoking and drinking). Fasting blood was collected from in the early morning of the day after admission and sent for RBP4, hemoglobin, serum albumin, triglycerides, total cholesterol, low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), C-reactive protein (CRP), glucose, creatinine, urea nitrogen, cardiac troponin T, creatine kinase-MB (CK-MB), and N-terminal pro-B-type natriuretic peptide (NT-proBNP).
Coronary angiography was performed in all patients by interventional physicians specializing in cardiology. The determination of the degree of coronary stenosis, combined with computer-assisted quantification, was discussed and determined by at least two experienced physicians. The Gensini score was calculated according to the location of the lesion and the degree of stenosis in each coronary artery and its branches via the angiographic findings [15].
After successful completion of coronary angiography in all patients, IVUS was then performed. All IVUS images are burned to a CD after the procedure, and the results are analyzed offline (Boston Scientific Image Viewer 1.6, Boston Scientific, Marlborough, MA, USA). Changes in heart rate and pressure were monitored and recorded in real time during the IVUS examination including coronary systolic pressure (Ps), diastolic pressure (Pd) and heart rate (HR).
The offline analysis of the IVUS images was performed by two independent
individuals, blinded to each other’s measurements. We evaluated inter- and
intraobserver reliability for elasticity parameters, including stiffness
parameter (
Measurement image of a patient with left coronary artery lesion. The red arrow in the upper left panel indicates the anterior descending branch lesion, and the blue arrow indicates the measurement site of the left main stem; the upper right panel shows the measured area and diameter within the EEM of the left main stem; the lower panel shows the long-axis image of the left coronary artery, and the green arrow indicates the measurement site.
Measured images of a patient with a right coronary artery lesion. The red arrow in the upper left panel indicates the right coronary artery lesion, and the blue arrow indicates the measurement site proximal to the right coronary; the upper right panel shows the measured area and diameter within the EEM of the proximal right coronary; the lower panel shows the long-axis image of the right coronary artery, and the green arrow indicates the measurement site.
Non-invasive elastic parameters are commonly used clinically to quantify
arterial elastic function based on the linear correlation of blood
pressure-diameter curves. However, HaYaShi et al. [16] found a
non-linear correlation of blood pressure-diameter curves in arterial vessels
after a dissection, a characteristic unique to soft biological tissues. As shown
in Fig. 3a, the change in vessel diameter that can be caused by the same blood
pressure gradually decreases and the vascular elasticity gets worse when blood
pressure increases. This type of change makes it difficult to avoid the
calculation of elasticity parameters from being influenced by fluctuations in
blood pressure, even if they vary between systolic and diastolic blood pressure.
HaYaShi et al. [16] proposed a hardness parameter to solve this problem
by setting a standard pressure Pm, for example, 100 mmHg, and determining the
diameter Dm at that pressure and calculating Px/Pm and Dx/Dm. When ln (Px/Pm) was
further calculated and plotted against Dx/Dm, a linear relationship was seen at
blood pressures in the physiological range, as shown in Fig. 3b. Since the set
diameter Dm at standardized pressure was not clinically accessible, Hirai
et al. [17] then optimized the formula to obtain the above formula (1)
and confirmed that
Formulaic link between vascular diameter and blood pressure. (a) The blood pressure-vascular diameter curve of the human
artery. (b) The definition of stiffness parameter
The aim of our study was to study the stiffness of the coronary artery by IVUS and measure serum RBP4 levels in patients with CHD combined with or without T2DM, and to analyze the relationship between RBP4 and coronary artery stiffness.
SPSS 26.0 (IBM Corp., Armonk, NY, USA) was used for statistical analysis of the
collected data, and GraphPad Prism 9.0 software (Dotmatics, Boston, MA, USA) was used for graphing the
statistical results. Data with normal distribution were statistically described
by mean
Comparisons of continuous variables between two groups which conformed to a
normal distribution with equal variance were performed using the independent
sample t-test. The Mann-Whitney nonparametric test was used for
comparison between groups that did not conform to a normal distribution. The
effect of each coronary artery elasticity parameter on the Gensini score was
analyzed by simple linear regression. Multiple linear regression equations were
established with a
Patients in the CHD with T2DM group had higher RBP4 levels compared to the CHD
without T2DM group (49.26
CHD with T2DM | CHD without T2DM | p value | ||
---|---|---|---|---|
group (n = 38) | group (n = 92) | |||
Age, years | 58 (49,69) | 66 (48,76) | 0.140 | |
Gender (male), n (%) | 31 (81.58) | 78 (84.78) | 0.652 | |
BMI (kg/m |
25.15 |
24.47 |
0.256 | |
Past medical history | ||||
Smoking, n (%) | 19 (50.00) | 42 (45.65) | 0.651 | |
Drinking, n (%) | 4 (10.53) | 9 (9.78) | 0.898 | |
Hypertension, n (%) | 16 (42.11) | 36 (39.13) | 0.753 | |
Stroke, n (%) | 4 (10.53) | 5 (5.43) | 0.447 | |
Atrial fibrillation, n (%) | 3 (7.89) | 5 (5.43) | 0.691 | |
Heart failure, n (%) | 1 (2.63) | 4 (4.35) | 0.645 | |
Myocardial infarction, n (%) | 9 (23.68) | 14 (15.22) | 0.250 | |
PCI, n (%) | 11 (28.95) | 22 (23.91) | 0.549 | |
Laboratory assessment | ||||
RBP4,mg/L | 49.26 |
34.67 |
||
LDL-C, mmol/L | 2.52 (1.66, 3.90) | 1.96 (1.46, 2.97) | 0.049 | |
HDL-C, mmol/L | 1.05 (0.81, 1.34) | 1.10 (0.94, 1.68) | 0.152 | |
Triglycerides, mmol/L | 1.61 (1.05, 2.15) | 1.25 (0.85, 1.78) | 0.048 | |
Total cholesterol, mmol/L | 3.69 |
4.07 |
0.122 | |
Hb, g/L | 131.05 |
138.56 |
0.023 | |
Creatinine, umol/L | 77.00 (68.00, 90.75) | 77.50 (63.50, 89.00) | 0.632 | |
Urea nitrogen, mmol/L | 5.55 (4.55, 6.70) | 5.60 (4.53, 6.80) | 1.000 | |
Albumin, g/L | 41.87 |
40.45 |
0.098 | |
Glucose, mmol/L | 6.06 (5.32, 8.03) | 5.20 (4.85, 5.77) | ||
CRP, mg/L | 5.40 (5.20, 5.70) | 5.50 (5.10, 5.78) | 0.357 | |
CK-MB, ng/mL | 1.82 (1.29, 2.93) | 1.77 (1.14, 3.30) | 0.986 | |
Cardiac troponin T, pg/mL | 12.00 (6.75, 27.75) | 10.00 (4.00, 20.00) | 0.125 | |
NT-proBNP, pg/mL | 229.00 (104.75, 767.25) | 164.00 (56.80, 429.75) | 0.109 |
CHD, coronary heart disease; T2DM, type 2 diabetes mellitus; BMI, body mass index; PCI, percutaneous coronary intervention; RBP4, Retinol-binding protein 4; LDL-C, low-density lipoprotein cholesterol; HDL-C, high-density lipoprotein cholesterol; Hb, hemoglobin; CRP, C-reactive protein; CK-MB, creatine kinase-MB; NT-proBNP, N-terminal pro-B-type natriuretic peptide.
Higher RBP4 levels and Gensini scores in patients in the CHD with T2DM group compared to the CHD without T2DM group. (a) Comparison of RBP4 levels between the two groups of patients. (b) Comparison of the Gensini score between the two groups of patients.
Compared with the CHD without T2DM group, patients in the CHD with T2DM group
had a higher proportion of multivessel coronary lesions, higher Gensini scores
[49.50 (27.00, 81.63) vs. 30.50 (16.00, 44.63), p = 0.001] (Fig. 4b),
higher Ps values, higher Pd, and higher pulse pressure. In elasticity parameters,
patients in the CHD with T2DM group had higher values of
The difference of each elasticity parameter between patients in the CHD with T2DM group and the CHD without T2DM group. (a) Comparison of
CHD with T2DM | CHD without T2DM | p value | ||
---|---|---|---|---|
Group (n = 38) | Group (n = 92) | |||
Multiple vascular lesions, (%) | 23 (60.53) | 37 (40.22) | 0.035 | |
Gensini score | 49.50 (27.00, 81.63) | 30.50 (16.00, 44.63) | 0.001 | |
Ps, mmHg | 137.95 |
125.60 |
||
Pd, mmHg | 76.61 |
71.89 |
0.015 | |
Pulse pressure, mmHg | 61.34 |
53.71 |
||
HR, times/min | 75.21 |
73.22 |
0.369 | |
Smax, mm |
14.15 (10.79, 17.71) | 13.22 (10.87, 16.99) | 0.620 | |
Smin, mm |
13.82 (10.25, 16.92) | 12.52 (9.86, 14.50) | 0.122 | |
Dmax, mm | 4.25 (3.71, 4.75) | 4.10 (3.72, 4.66) | 0.612 | |
Dmin, mm | 4.20 (3.61, 4.64) | 3.99 (3.55, 4.30) | 0.123 | |
Elasticity parameters | ||||
58.69 (21.08, 140.98) | 12.51 (7.41, 25.77) | |||
E |
6349.09 (2215.68, 16224.85) | 1254.18 (729.20, 2473.61) | ||
DC, 10 |
0.32 (0.13, 0.92) | 1.57 (0.80, 2.65) | ||
CC, 10 |
0.40 (0.19, 1.27) | 2.12 (0.97, 3.37) |
CHD, coronary heart disease; T2DM, type 2 diabetes mellitus; Ps, systolic blood
pressure; Pd, diastolic blood pressure; HR, heart rate; Smax; maximum vessel
area; Smin, minimum vessel area; Dmax, maximum vessel diameter; Dmin, minimum
vessel diameter;
The scatter plot shows a linear correlation between Gensini score and each
elasticity parameter. To further analyze the effect of coronary artery elasticity
on the severity of coronary lesions in patients with CHD, simple linear
regression analysis was performed with Gensini score as the dependent variable
and elastic parameters
The linear correlation between Gensini score and each elasticity parameter. (a) Effect of
Variables | Coefficient | Standard deviation | Standardization coefficient | p value | 95% Confidence interval (CI) |
---|---|---|---|---|---|
0.263 | 0.042 | 0.484 | 0.180–0.346 | ||
E |
0.003 | 0.0004 | 0.521 | 0.002–0.003 | |
DC | –8.049 | 1.647 | –0.397 | (–11.310)–(–4.792) | |
CC | –5.386 | 1.184 | –0.373 | (–7.729)–(–3.045) |
The advantages of
Univariate linear regression analysis was established in all CHD
patients with
Variables | Univariate analysis | Multivariate analysis | ||||
---|---|---|---|---|---|---|
Coefficient (95% CI) | Standardization coefficient | p value | Coefficient (95% CI) | Standardization coefficient | p value | |
RBP4 | 2.96 (2.505–3.414) | 0.751 | 1.330 (0.909–1.751) | 0.338 | ||
Hypertension | 64.205 (47.977–80.433) | 0.569 | 31.451 (20.629–42.273) | 0.279 | ||
LDL-C | 28.223 (20.627–35.818) | 0.545 | 10.401 (5.761–15.041) | 0.201 | ||
Age | 2.414 (1.890–2.938) | 0.627 | 0.878 (0.487–1.268) | 0.228 | ||
T2DM | 61.450 (43.111–79.789) | 0.506 | 33.371 (22.354–44.387) | 0.275 | ||
BMI | 4.916 (1.341–8.490) | 0.234 | 0.007 | |||
Creatinine | 0.215 (0.046–0.384) | 0.217 | 0.013 | |||
HDL-C | –51.665 ((–69.401)–(–33.928)) | –0.454 | ||||
Smoking | 59.055 (42.666–75.444) | 0.533 |
RBP4, Retinol-binding protein 4; LDL-C, low-density lipoprotein cholesterol; T2DM, type 2 diabetes mellitus; BMI, body mass index; HDL-C, high-density lipoprotein cholesterol.
Univariate regression analysis was established with
Variables | Univariate analysis | Multivariate analysis | ||||
---|---|---|---|---|---|---|
Coefficient (95% CI) | Standardization coefficient | p value | Coefficient (95% CI) | Standardization coefficient | p value | |
RBP4 | 3.323 (2.751–3.894) | 0.891 | 1.185 (0.118–2.252) | 0.318 | 0.031 | |
Hypertension | 120.009 (91.417–148.600) | 0.817 | 34.304 (0.835–67.773) | 0.234 | 0.045 | |
LDL-C | 43.319 (29.306–57.332) | 0.722 | 16.602 (7.297–25.907) | 0.277 | 0.001 | |
Age | 3.65 (2.879–4.421) | 0.848 | 1.066 (0.092–2.039) | 0.248 | 0.033 | |
BMI | 7.785 (0.772–14.798) | 0.351 | 0.031 | |||
HDL-C | –101.302 ((–141.552)–(–61.051)) | –0.648 | ||||
Smoking | 111.854 (80.675–143.032) | 0.772 |
RBP4, Retinol-binding protein 4; LDL-C, low-density lipoprotein cholesterol; BMI, body mass index; HDL-C, high-density lipoprotein cholesterol.
Univariate regression analysis was established with
Variables | Univariate analysis | Multivariate analysis | ||||
---|---|---|---|---|---|---|
Coefficient (95% CI) | Standardization coefficient | p value | Coefficient (95% CI) | Standardization coefficient | p value | |
Hypertension | 38.442 (27.158–49.726) | 0.581 | 28.273 (16.948–39.599) | 0.427 | ||
LDL-C | 11.718 (5.206–18.231) | 0.353 | 0.001 | 9.047 (3.942–14.153) | 0.272 | 0.001 |
Age | 1.257 (0.812–1.703) | 0.509 | 0.683 (0.259–1.108) | 0.277 | 0.002 | |
RBP4 | 0.713 (–0.148–1.574) | 0.171 | 0.104 | |||
HDL-C | –24.139 ((–37.019)–(–11.260)) | –0.365 | ||||
Smoking | 34.065 (22.508–45.622) | 0.525 |
LDL-C, low-density lipoprotein cholesterol; RBP4, Retinol-binding protein 4; HDL-C, high-density lipoprotein cholesterol.
T2DM has been found to influence and participate in the development of CHD. Its
effect on vascular endothelial cells and vascular elasticity is particularly
significant and has important pathological significance. Endothelial dysfunction
is one of the pathological bases of CHD [18]. Quagliaro et al. [19]
found that the concentration of superoxide anion radical (O2
This study found that in addition to T2DM; RBP4, age, hypertension and LDL-C significantly affected coronary artery elasticity, which is generally consistent with the results of previous studies [22, 23, 24, 25]. A study by Chondrou et al. [22] regarding the effect of RBP4 on arterial elasticity, found that RBP4 was significantly associated with aortic stiffness after adjusting for the influence of age and pulse pressure, as RBP4 levels increased, arterial elasticity gradually decreased. Aging is also a known factor contributing to the decrease of the elastic function of large arteries. The effect of age on arterial elasticity is partly attributed to changes in the extracellular matrix within the arterial wall, such as degradation of elastin fibers and increased formation of cross-linked molecules such as AGEs [23]. In addition, ageing-induced imbalance in the vasoactive molecular environment, vascular oxidative stress and chronic inflammation are also thought to reduce arterial compliance. The negative effects of hypertension on vascular elastic function have also been demonstrated in clinical practice. Sustained high circulatory load in patients with hypertension will damage the elastin structure of the arterial wall, causing remodeling of the vessel wall and lumen enlargement, as well as inducing phenotypic changes in arterial endothelial and smooth muscle cells to decrease arterial elasticity [24]. Finally, Chen et al. [25] found in a cross-sectional study, that the risk of atherosclerosis increased with increasing duration of LDL-C exposure in a dose-dependent manner, demonstrating that elevated LDL-C levels will further decrease arterial compliance.
In this study, in order to determine whether the effect of RBP4 on coronary
artery elasticity was different in patients with CHD with and without T2DM, a
multiple linear regression analysis was established by using the
The effect of RBP4 on arterial elasticity may be partly attributed to its induction of insulin resistance in endothelial cells and the reduction of endothelium-derived NO production [26]. The mechanisms of insulin action on arterial endothelial cells have now been extensively elucidated [27, 28]. After binding to endothelial cell surface receptors, insulin can increase endothelial-derived NO production through the PI3K/Akt signaling pathway, and act on the mitogen-activated protein kinase (MAPK) signaling pathway to promote the secretion of endothelin-1 (ET-1), which has a strong vasoconstrictive effect and promotes the expression of adhesion factors. Insulin resistance (IR) could selectively inhibit the PI3K/Akt-eNOS-NO signaling pathway without reducing ET-1 secretion, and the imbalance between the two would impair arterial vasodilatory function [28].
RBP4 can also reduce arterial compliance and accelerate atherosclerosis progression by impairing mitochondrial function and inducing endothelial apoptosis in arterial endothelial cells. The PI3K/Akt signaling pathway not only is involved in regulating endothelial-derived NO production, but also functions to regulate the activity of the Bcl-2 family proteins [29]. An increase in the Bax/Bcl-2 ratio leads to a change in mitochondrial membrane permeability, increasing the release of mitochondrial cytochrome C (Cyt C) and promoting apoptotic events, whereas a decrease in the Bax/Bcl-2 ratio has the opposite effect. Wang et al. [10] found that RBP4 increased mitochondrial reactive oxygen species (ROS) production in human aortic endothelial cells (HAECs) in a dose-dependent manner, and decreased mitochondrial content, integrity and membrane potential. In either RBP4-treated HAECs or the transgenic mice expressing human RBP4 (RBP4-Tg), Cyt C expression and Bax/Bcl-2 ratio were found to be significantly elevated, which would eventually lead to apoptotic events in arterial endothelial cells. Combined with changes in phosphorylation levels at specific downstream sites (Ser473, Thr308), this suggests that high levels of RBP4 will inhibit the PI3K/Akt signaling pathway and induce apoptosis in aortic endothelial cells.
RBP4 may affect coronary artery elasticity by promoting the proliferation and migration of vascular smooth muscle cells (VSMCs), which exhibit a fully functional and differentiated phenotype under physiological conditions and express contractile proteins important for maintaining vascular tone. However, even though VSMCs are highly differentiated and mature, they are still highly plastic and can undergo a phenotypic transition from “contractile” to “synthetic” phenotype under conditions of injury or induction [30]. The phenotypic transition from a “contractile” to a “synthetic” phenotype is characterized by a decrease in myofilament density and contractile protein expression, which are replaced by an increase in the expression of proinflammatory factors and extracellular matrix [31]. For example, VSMCs can be involved in vascular calcification by transforming into osteoblasts. Zhou et al. [32, 33] found that RBP4 promoted the development of atherosclerosis in both diabetic rats by regulating the JAK2/STAT3 signaling pathway and rat aortic smooth muscle cells in a high-glucose environment, further validating that high levels of RBP4 promoted the proliferation of VSMCs by regulating this pathway. This further verified that high levels of RBP4 promoted the proliferation and migration of VSMCs and the occurrence of diabetic macrovascular events through the regulation of this pathway, consistent with the view in our study that RBP4 is a risk factor for the progression of coronary artery lesions in CHD patients with T2DM.
Finally, The relationship between pericardial fat thickness and coronary heart disease has been closely studied in recent years. Epicardial adipose tissue (EAT) volume (EAV) can be used to diagnose high-risk coronary plaque burden associated with coronary events [34]. Further research shows that pericoronary adipose tissue is closely related to atherosclerotic plaque formation. Right coronary artery Pericoronary adipose tissue computed tomography attenuation(PCATa) has prognostic value beyond clinical characteristics [35]. Several studies have found that EAV has a negative relationship with artery stiffness [36, 37]. The mechanism by which coronary peripheral fat or pericardial peripheral fat increases the risk of coronary atherosclerosis remains unclear. Salgado-Somoza et al. [38] showed that Retinol-binding protein 4 is expressed in EAT and subcutaneous adipose tissue (SAT), and that RBP4 protein levels were higher in EAT from CAD than non-CAD patients. Therefore, RBP4 produced by EAT is another risk factor for the progression of coronary artery lesions in CHD. Since RBP4 is produced by adipose tissue, one of the reasons for the increase of RBP4 in CHD patients may be due to the high proportion of adipose tissue or BMI in these patients. Controlling body fat to reduce the level of RBP4 may be an important measure to reduce the occurrence of coronary heart disease in diabetic patients.
Our patients all had diabetes and coronary heart disease and received medication to control blood sugar, hypertension and lipid levels. Weather these medical therapies can influence RBP4 levels is still unclear. These medications and dietary modifications will impact levels of oxidative stress and lifestyle changes such as cessation of smoking could modulate RBP4 concentrations [39]. Fortunately, both our study groups had similar clinical characteristics and these factors had limited impact on our results. In CHD patients, plaque component and plaque elasticity had a significant positive relationship with artery stiffness [40, 41]. Therefore, the left main coronary artery and the proximal part of the right coronary artery without plaque were selected as the locations for measuring arterial elasticity.
Our study is innovative in that the obtained coronary elasticity parameters were analyzed in correlation with RBP4 by using IVU. Furthermore, this study reveals that the adipokine RBP4 is an independent risk factor for coronary artery elasticity and shows differences in levels between CHD patients with and without T2DM, providing a new therapeutic strategy for patients with CHD combined with T2DM. However, this study still has some limitations. First, this study was a cross-sectional study and did not demonstrate the time-dependent effect of RBP4 on coronary artery elastic function. Second, the small sample size was small and derived from a single-center in Suzhou. Third, this study was based on the population with stable CHD, so the results cannot be extended to acute patients. Fourth, our study did not show RBP4 was an independent risk factor for vascular stiffness in patients with CHD without T2DM. It could be that the number of patients without diabetes and with significant vascular stiffness was too low. Finally, the correlation between RBP4, arterial stiffness and clinical outcomes had not been investigated, so further clinical studies are needed to understand whether reducing RBP4 levels in diabetic patients with CHD may actually have an impact on prognosis. This topic will need further investigation future studies.
Our study found that RBP4 was an independent risk factor for coronary artery elasticity in patients with CHD combined with T2DM and in all CHD patients, but it did not affect the coronary artery elasticity of CHD patients without T2DM. This suggests that RBP4 is important for the assessment of coronary artery elasticity in patients with CHD combined with T2DM and that treatment targeting RBP4 may decelerate the progression of coronary artery lesions in these patients.
The data and materials that support the findings of this study are openly available from the corresponding author upon reasonable resquest.
XG designed the research study. YJ, SD, CT and JS performed the research and analyzed the data. YJ wrote the manuscript. All authors contributed to editorial changes in the manuscript. All authors read and approved the final manuscript.
This study was approved by the Ethics Committee of the Second Affiliated Hospital of Soochow University (No. JD-LK-2021-029-01).
This study was funded by the Department of Cardiology of the Second Affiliated Hospital of Soochow University. We thank all the staff for their help with data collection.
This work was supported by the Project of State Key Laboratory of Radiation Medicine and Protection, Soochow University (NO. GZK1202135). Academic lifts project of the Second Affiliated Hospital of Soochow University (NO. XKTJ-HRC2021007).
The authors declare no conflict of interest.
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