Abstract

Abbreviations and Acronyms

CAD

coronary artery disease

CAR

CRP to serum albumin ratio

CCC

coronary collateral circulation

CRP

C-reactive protein

DM

diabetes mellitus

HDL-C

high-density lipoprotein cholesterol

Lp(a)

lipoprotein a

LDL-C

low-density lipoprotein cholesterol

NO

nitric oxide

PS

propensity score

TC

total cholesterol

SII index

systemic immune-inflammatory index

Introduction

Coronary collateral circulation (CCC) is an adaptive mechanism that occurs in the presence of chronic myocardial ischemia and stress after severe stenosis or obstruction.¹ Previous studies have shown that a well-developed collateral circulation reduces the infarct area, protects cardiac functions, reduces the development of cardiogenic shock, decreases the development of aneurysm of the left ventricle, and plays a very important role in short- and long-term prognoses for coronary artery disease (CAD).²

Despite many studies, the factors affecting coronary collateral development cannot be fully explained; however, the normal vascular endothelial layer and its functions are accepted as the basis for collateral development.^3,4 Previous studies on dyslipidemia, metabolic syndrome, diabetes mellitus (DM), and aging have shown the adverse effects of vascular endothelial dysfunction that result from decreasing collateral development.^5–7

Non–high-density lipoprotein cholesterol (non–HDL-C) contains multiple atherogenic cholesterols, including low-density lipoprotein cholesterol (LDL-C), very low-density lipoprotein, intermediate-density lipoprotein cholesterol, and lipoprotein a [Lp(a)] cholesterol.⁸ It shows the total atherogenic burden better than does LDL-C, which is the primary cholesterol target.^9,10 In addition to providing short- and long-term information for many diseases, such as CAD, various studies have shown that it is an early indicator of vascular endothelial dysfunction and is correlated with various inflammatory markers.^11,12

This study aimed to investigate the relationship between CCC and non–HDL-C levels in patients with stable CAD.

Patients and Methods

This retrospective cross-sectional study was conducted in patients who underwent coronary angiography between December 2016 and December 2020 at a single center after ethics committee approval (Adnan Menderes University Non-Interventional Clinical Research Ethics Committee permission dated December 10, 2021, and numbered 2021/65). Patients who were diagnosed with stable CAD according to the criteria recommended by the European Society of Cardiology and who underwent coronary angiography and were determined to have coronary stenosis of 95% or more in at least 1 major coronary vessel were included in the study. All patients included in the study had angina or angina-equivalent symptoms, and coronary angiography indications were established with positive noninvasive tests (exercise stress test, stress echocardiography, and myocardial perfusion scintigraphy). The study was conducted in accordance with the Declaration of Helsinki.

Exclusion criteria for the study were as follows: anemia, kidney failure or kidney disease affecting kidney clearance, history of coronary bypass surgery, malignant disease, collagenous connective tissue disease, congestive heart failure, acute cerebrovascular disease, percutaneous coronary intervention after previous acute coronary syndrome, fever, active infection, and the use of statins or other antihyperlipidemic drugs. After applying the exclusion criteria, 226 patients were enrolled in the study.

The demographic, clinical, and angiographic characteristics of all patients included in the study were recorded. All patients were interviewed in detail about hypertension, DM, smoking, history of myocardial infarction, family health history, and medication use. Chronic kidney failure was defined as a glomerular filtration rate of less than 60 mL/min for over 3 months. A diagnosis of hypertension was accepted if antihypertensive treatment was given or if there were at least 3 measurements of higher than 140 mm Hg systolic and 90 mm Hg diastolic. A diagnosis of DM was made if patients were taking antidiabetic medication or had at least 2 fasting blood glucose measurements above 126 mg/dL.

Results

A total of 226 patients were included in this study. According to Rentrop classification, groups were divided into those that had good (Rentrop grades 2–3) or poor (Rentrop grades 0–1) collateral. In the original study population, the median age of the 85 patients (68 males, 17 females) in the poor-collateral-circulation group was 67 (65.1–74.50) years. The mean age of the 141 patients (101 males, 40 females) in the good-collateral-circulation group was 69 (63.50–78) years.

Baseline clinical, demographic, and angiographic features are compared in Table I. Diabetes status, Gensini score, and use of angiotensin-converting enzyme inhibitors differed substantially between the 2 groups. Because of the differences in key baseline characteristics, the PS-matching method was used. In the 1-to-1 PS-matched data set, 84 patients remained in the good-collateral group and 84 patients remained in the poor-collateral group. All the variables were well balanced between the groups after the PS match (Table I).

TABLE I. Baseline Characteristics, Preoperative Medications, and Angiographic Findings

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In the PS-matched population, there was no difference between groups in terms of hematological and kidney function values. The CRP levels, SII index, and CAR were increased in the poor-collateral group (Table II). In a comparison of the two groups in terms of lipid parameters, there were no differences in the triglyceride and HDL-C levels. Low-density lipoprotein cholesterol, TC, and non–HDL-C levels were increased in the poor-collateral group in the PS-matched population (Table III).

TABLE II. Basic Laboratory Parameters of the Patients

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TABLE III. Lipid Parameters of the Patients

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Multivariate logistic regression analysis showed that LDL-C, non–HDL-C, CRP, SII index, and CAR remained independent predictors of poor-collateral development (Table IV).

TABLE IV. Multivariate Logistic Regression Analysis of the Risk Factors for Poor Collateral Circulation

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Discussion

This study is the first to examine the relationship between CCC and non–HDL-C in patients with stable CAD. In this study, high non–HDL-C was an independent risk factor for developing poor collaterals in patients with stable CAD.

Similar to previous studies, this study also supports the findings that LDL-C, CRP, SII index, and CAR are independent risk factors for poor-collateral development. A high LDL-C level, which is one of the most critical risk factors for developing endothelial dysfunction and atherosclerosis, is a risk factor for the development of poor collateral in many clinical and demographic studies. You et al¹⁵ showed that high LDL-C levels are an independent risk factor for developing poor collateral. In in vitro studies, CRP, one of the most noteworthy markers of inflammation, has been shown to reduce nitric oxide (NO) levels, which is a very important element of collateral development and angiogenesis inhibition. Gulec et al¹⁶ showed that high CRP levels are an independent risk factor for poor-collateral development. According to Fan et al¹⁷ in their study of 1,158 patients, high CRP levels were associated with poor-collateral development in patients with stable CAD. The SII index and CAR are inflammatory markers that have emerged in recent years, and various studies^18,19 have shown them to be more predictive markers for inflammation than the platelet to lymphocyte ratio, the neutrophil to lymphocyte ratio, and CRP. According to Keleşoğlu et al,^20,21 high SII index and CAR levels in patients with stable CAD are risk factors for developing poor collateral.

Although most studies do not fully explain the mechanism of collateral development, most agree that it is a complex process of cell organization.^1,2 In previous studies, angiogenesis and arteriogenesis have been shown to be the 2 primary mechanisms for collateral development. Angiogenesis involves the coordinated migration, proliferation, and differentiation of endothelial cells and pericytes from existing vascular beds. On the other hand, arteriogenesis is the growth of muscular arteries requiring similar events regulated by endothelial cells and smooth muscle cells from preexisting arteries.²² A solid and functional vascular endothelial layer is essential for the healthy continuation of angiogenesis and arteriogenesis processes.²³ The presence of vascular endothelial dysfunction is accepted as one of the main reasons for poor-collateral development. Numerous studies have shown that hyperlipidemia causes vascular endothelial dysfunction and adversely affects collateral development.^24,25 Aras et al²⁶ showed that at high Lp(a) levels, vascular endothelial growth factor secretion is negatively affected by Lp(a) and collateral development is poor as a result of endothelial dysfunction. Morishita et al²⁷ showed that transforming growth factor-β release is decreased because of endothelial dysfunction resulting from high Lp(a), and collateral development is adversely affected. Duan et al²⁸ demonstrated that collateral vessel formation and angiogenesis in response to hindlimb ischemia were significantly attenuated in rats with dietary hypercholesterolemia, which is related to endothelial cell dysfunction and decreased endothelium-derived NO.²⁸ Shen et al²⁹ found that in patients with DM, it was observed that Lp(a) levels were correlated with LDL-C and non–HDL-C; in addition, poor-collateral development was 4 times higher with high Lp(a) levels.

Many recent studies have shown that non–HDL-C is a good indicator for cardiovascular diseases compared with LDL-C, which is the primary target.^8–10 It is also the primary indicator for endothelial dysfunction and is associated with various inflammatory markers. The mechanism of poor-collateral development with high non–HDL-C is thought to occur from more than 1 factor. Hyperlipidemia, especially with high non–HDL-C, may adversely affect collateral development by causing vascular endothelial dysfunction. Wang and Chang¹² stated that non–HDL-C was an early marker of vascular endothelial dysfunction in patients with type 2 diabetes and was correlated with CRP. In a study that investigated serum lipid levels and the risk of microangiopathy in patients with type 2 diabetes, Toth et al³⁰ showed that each 1-mg/dl increase in non–HDL-C increased the risk of microangiopathy by 0.3%. In addition, the risk level was observed to be 17.3% in patients who were above the non–HDL-C target. Karasek et al³¹ found a positive correlation between non–HDL-C and high-sensitivity CRP, which is an inflammatory marker; C-peptide and homeostatic model assessment for insulin resistance, which is a marker of insulin resistance; and plasminogen activation inhibitor. In addition, many studies have shown that the presence of high non–HDL-C is an independent risk factor for increased arterial stiffness.³² de Oliveira Alvim et al³³ showed that high non–HDL-C is associated with increased arterial stiffness; as a result of this increased stiffness, high systolic blood pressure, low diastolic blood pressure, and increased pulse pressure develop. Baykan et al³⁴ showed that coronary perfusion and shear stress decrease as a result of increased arterial stiffness and adversely affect coronary collateral arteriogenesis.

Conclusion

This study demonstrates that high non–HDL-C levels negatively affect the development of stable CAD collateral. With this result, one can understand the pathophysiology of collateral development and new treatment strategies can be developed. Large and long-term prospective studies may help us better understand the diagnostic and therapeutic value of non–HDL-C in collateral development.