An Association of Insulin Resistance with Numerous of Circulating Microparticles Originated from Endothelial Cells in Cardiac Failure Individuals without History of Diabetes Mellitus

Research Article

J Dis Markers. 2015; 2(4): 1032.

An Association of Insulin Resistance with Numerous of Circulating Microparticles Originated from Endothelial Cells in Cardiac Failure Individuals without History of Diabetes Mellitus

Berezin A¹*, Kremzer A², Berezina T³ and Martovitskaya Y4

¹Internal Medicine Department, State Medical University, Zaporozhye, Ukraine

²Clinical Pharmacology Department, State Medical University, Zaporozhye, Ukraine

³Private Medical Center “Vita-Center”, Zaporozhye, Ukraine

4Clinical Laboratory “Dia-Service”, Immunology and Pathology Unit, Zaporozhye, Ukraine

*Corresponding author: Alexander Berezin, Internal Medicine Department, State Medical University, Ukraine

Received: October 19, 2015; Accepted: November 12, 2015; Published: November 16, 2015

Abstract

Background: The causality role of insulin resistance (IR) in chronic heart failure (CHF) subjects has not determined. The study was conducted to examine a relationship between IR and numerous of circulating endothelial cell-derived microparticles (EMPs) in patients with CHF

Methods: Three hundreds ischemic-induced CHF patients aged 48 to 62 years who underwent multispiral computed tomography angiography or coronary angiography was involved in the study. Ischemic-induced CHF has documented when atherosclerotic stenos is > 50% of at least one coronary artery was presented or previously defined myocardial infarction was reported. Biomarkers were measured at baseline of the study. Circulating EMPs were isolated from peripheral blood and measured using flow cytometry technique.

Results: These were not significant differences between patients with and without IR in EMPs labeled as CD144+/CD31+, CD144+/annexin V+, and CD62E+ microparticles. Higher concentrations of CD144+/CD31+/annexin V+ EMPs and CD31+/annexin V+ EMPs were found in IR subjects when compared with none IR patients. Multivariate linear regression analyses has shown HOMAIR (OR = 1.14, 95% CI=1.08-1.21, P = 0.001), NT-proBNP (OR = 1.07, 95% CI=1.04-1.10, P = 0.001), hs-CRP (OR = 1.04, 95% CI=1.02-1.07, P = 0.001), and NYHA class (OR = 1.03, 95% CI=1.01-1.05, P = 0.001) were predictors for increased CD31+/annexin V+ EMPs. Additionally, HOMA-IR (OR = 1.10, 95% CI=1.05-1.17, P = 0.001), NT-proBNP (OR = 1.08, 95% CI=1.04-1.12, P = 0.001), and NYHA class (OR = 1.05, 95% CI=1.02-1.09, P = 0.001) significantly predicted elevation of CD144+/CD31+/annexin V+ EMPs. C-statistics for Models with HOMA-IR, NYHA class, and CHF biomarkers (hs-CRP, NT-proBNP) as continuous variables reported that adding of combination of these biomarkers to the based model constructed with HOMA-IR did not improve the relative IDI for increased CD144+/CD31+/annexin V+ and CD31+/annexin V+ microparticles.

Conclusion: we found that IR was statistically significant predictor for increased apoptotic EMPs labelled as CD144+/CD31+/annexin V+ and CD31+/ annexin V+ microparticles in CHF patients without history of T2DM. We suggest that these findings might reflect an impaired phenotype of circulating EMPs in this patient population.

Keywords: Chronic heart failure; Insulin resistance; Endothelial cell-derived Microparticles; Immune phenotype

Abbreviations

ACEI: Angiotensin-Converting Enzyme Inhibitors; ARBs: Angiotensin Receptor Blockers; AUC: Area Under Curve; BMI: Body Mass Index; BNP: Brain Natriuretic Peptide; CHF: Chronic Heart Failure; CV: Cardiovascular; EMPs: Endothelial-Derived Microparticles; GFR: Glomerular Filtration Rate; hs-CRP: High Sensitive C-Reactive Protein; HbA1c: Glycated Hemoglobin; HDL-C: High-Density Lipoprotein Cholesterol; HFpEF: CHF with Precerved LVEF; HFrEF: CHF with Reduced LVEF; IR: Insulin Resistance; LDL-C: Low-Density Lipoprotein Cholesterol; LVEF: Left Ventricular Ejection Fraction; MetS: Metabolic Syndrome; T2DM: Type 2 Diabetes Mellitus.

Introduction

Chronic heart failure (CHF) remains a major public health problem worldwide leading to growth of cardiovascular (CV) morbidity and mortality [1]. During the past decades prevalence and incidence of CHF has increased [2]. Despite contemporary understanding of the underlying disease mechanisms of CHF there is knowledge gap with respect to nature evolution CHF under influence of co-existing CV risk factors [3]. Indeed, the results of few population-based and epidemiological investigations have shown that multiple actual CV risk factors and various metabolic comorbidities presented in CHF patients may affect cardiac failure development [4,5]. There is still debate in the scientific community about whether identification of numerous of CV risk factors / the metabolic co-morbidities improves ability to predict CHF development beyond use of single risk factor [6].

Recent clinical investigations have revealed insulin resistance (IR) is as a distinct cause of cardiac dysfunction and CHF in diabetic and non-diabetic patients [7-9]. IR mediates excessive or inadequate proliferation of the extracellular matrix accelerates apoptosis via increased oxidative stress, neurohumoral and inflammatory activation that effect cardiac remodeling and endothelial function [10-13]. Despite IR is considered a main component of metabolic syndrome (MetS) and type two diabetes mellitus (T2DM), a lot of individuals with CHF may present IR prior to other dysmetabolic conditions including MetS / T2DM [14,15]. However, IR is persisted component of CV risk factors and it role in CHF development in the patients without history of T2DM is still unclear.

Recent studies have shown the association of circulating endothelial cell-derived microparticles (EMPs) with CV risk factors and nature evolution of CHF [16-20]. Extracellular EMPs are defined as microvesicles with sizes ranging between 50 and 1000 nm that released from plasma membrane of endothelial cells due to apoptosis or cell activation by specific (cytokine stimulation, mononuclear cooperation, coagulation, etc) and non-specific (shear stress) stimuli [21]. Apoptotic endothelial cell-derived or activated endothelial cellderived EMPs are capable of transferring biological information (miRNA, DNA), as well as hormones, proteins, lipid components, regulating peptides without direct cell-to-cell contact to maintain cell homeostasis and regulate cell response [22,23]. Interestingly, circulating EMPs derived from activated endothelial cells did not contain nuclear components and they have also been shown to have pro-angiogenic and cardio-protective properties [24,25]. In contrast, apoptotic EMPs realize wide spectrum immune mediators, which generate powerful signaling by the simultaneous receptor interaction. In this context apoptotic EMPs are considered a marker of endothelial cell injury and vascular aging [26,27]. However, the role of different immune phenotypes of EMPs in IR and CHF has not determined. The aim of the study was to assess relationship between IR and immune phenotypes of circulating EMPs in patients with CHF.

Methods

The study prospectively involved 300 ischemic-induced CHF patients aged 48 to 62 years who underwent multispiral computed tomography angiography or coronary angiography between February 2011 and November 2013.

As inclusion criteria in the study we used defined CHF with reduced left ventricular (LV) dysfunction (LV ejection fraction) presented due to stable CAD or myocardial infarction. CHF was defined accordingly clinical practice guideline recommendations as asymptomatic (NYHA I class) and symptomatic (NYHA II-IV classes) associated with declined LVEF (<50%) [28]. All enrolled subjects have demonstrated elevated level of NT-proBNP (>600 pg/ mL). Singes and symptoms of CHF were determined through classes of CHF as sodium and fluid retention, increased jugular venous pressure, peripheral edema, orthopnoea, paroxysmal nocturnal dyspnoea, fatigue. The relevant medical history, certain features / comorbidities were checked and interpreted also. Ischemic-induced CHF has documented when atherosclerotic stenosis > 50% of at least one coronary artery was presented or previously defined myocardial infarction was reported.

We excluded patients with acute infections; active inflammation; pulmonary edema; tachyarrhythmia; valvular heart disease; thyrotoxicosis; ischemic stroke; intracranial hemorrhage; surgery; trauma, autoimmune disease, malignancy, and acute coronary syndrome within 3 months prior to the study entry, and diabetes mellitus (DM). We checked past medical history and the results of laboratory report received prior to the study entry.

DM was diagnosed with revised criteria provided by American Diabetes Association when source documents were reviewed [29]. When one or more of the following components were found (glycated hemoglobin [HbA1c] ≥6.5%; fasting plasma glucose ≥7 mmol/L; 2-h plasma glucose ≥11.1 mmol/L during an oral glucose tolerance test; a random plasma glucose ≥11.1 mmol/L; exposure of insulin or oral antidiabetic drugs; a previous diagnosis of T2DM) Type 2 DM was determined.

All participants gave full written informed consent.

Sample size is calculated by using single population proportion formula by considering the following assumptions; 50% prevalence assumption, 95% confidence level of significance alpha 0.05 = 1.96, and 5% margin of error, which results in the sample size of 299.

Methods for visualization of coronary arteries

Contrast-enhanced multispiral computed tomography angiography has been performed for all patients with dysmetabolic disorder prior to their inclusion in the study on Optima СТ660 scanner (GE Healthcare, USA) using non-ionic contrast “Omnipaque” (Amersham Health, Ireland) [30].

Echocardiography and doppler examination

Transthoracic echocardiography was performed according to a conventional procedure on ACUSON ultrasound system (SIEMENS, Germany) using 2.5-5 МHz phased probe. The LV ejection fraction (EF) was measured by modified Simpson’s method [31].

Insulin resistance assessment

Insulin resistance was assessed by the homeostasis model assessment for insulin resistance (HOMA-IR) [32] using the following formula:

HOMA-IR (mmol/L × μU/mL) = fasting glucose (mmol/L) × fasting insulin (μU/mL) / 22.5

Insulin resistance was defined when estimated HOMA-IR value was over 2.77 mmol/L × μU/mL.

Calculation of glomerular filtration rate

Glomerular filtration rate (GFR) was calculated with CKD-EPI formula [33].

Blood sampling

After an overnight fast blood samples were drawn in the morning (at 7-8 a.m.) into cooled silicone test tubes wherein 2 mL of 5% Trilon B solution were added; then they were centrifuged upon permanent cooling at 6,000 rpm for 3 minutes. Then, plasma was refrigerated immediately to be stored at a temperature -70оС. All laboratory tests were performed using standard methods to measure the serum HbA1c, fasting plasma glucose, fating serum insulin and lipid profiles.

Fasting insulin level was measured by a double-antibody sandwich immunoassay (Elecsys 1010 analyzer, F. Hoffmann-La Roche Diagnostics, Mannheim, Germany). The intra-assay and interassay coefficients of variation were <5%. The lower detection limit of insulin level was 1.39 pmol/L.

Direct Enzymatic HbA1c Assay was used for glycated hemoglobin A1c (HbA1c) measurements on Beckman Synchron LX20 chemistry analyzer.

N-terminal pro-brain natriuretic peptide (NT-pro-BNP) level was measured by immunoelectrochemoluminescent assay using sets by R&D Systems (USA) on Elecsys 1010 analyzer (Roche, Mannheim, Germany).

Concentrations of total cholesterol (TC), cholesterol of highdensity lipoproteins (LDL-C), and cholesterol of high-density lipoproteins (HDL-C) were measured by enzymatic colorimetric method according standardized methodology on Beckman Synchron LX20 chemistry analyzer.

Identifying immune phenotype of EMPs

Circulating MPs were isolated from 5 ml of venous citrated blood drawn from the fistula-free arm. To prevent contamination of samples platelet-free plasma (PFP) was separated from whole blood. PFP was centrifugated at 20,500 × rpm for 30 min. MP pellets were washed with DMEM (supplemented with 10 μg/mL polymyxin B, 100 UI of streptomycin, and 100 U/ml penicillin) and centrifuged again (20,500 rpm for 30 min). The obtained supernatant was extracted, and MP pellets were re-suspended into the remaining 200 μL of supernatant. PFP, MPs, and supernatant were diluted five-, 10-, and five-fold in PBS, respectively. Only 100 μL of supernatant was prepared for further analysis through incubation with different fluorochromelabeled antibodies or their respective isotypic immunoglobulins (Beckman Coulter).

MPs were labeled and characterized by flow cytometry technique per HD-FACS (High-Definition Fluorescence Activated Cell Sorter) methodology independently after supernatant diluted without freeze [34].

CD41a+ was used as a more specific marker of platelets, and CD64+ was considered a more specific marker of monocytes. CD31 antigen was determined as essential marker for endothelial cells, platelets, and leukocytes. CD144+ was used to identify a pure population of endothelial cells. CD31+/annexin V+ and CD144+/ CD31+/annexin V+ MPs were defined as apoptotic endothelial cellderived MPs, MPs labeled for CD105+ or CD62E+ were determined as MPs produced due to activation of endothelial cells [35].

We used anti–CD31 [(platelet endothelial cell adhesion molecule [PECAM]-1)]-phycoerythrin (PE; 20 μl/test), anti–CD41a-PC5 (10 μl/test), anti–CD144 [(vascular endothelial [VE]-cadherin)]- allophycocyanin [APC] (10 μl/test), anti–CD64-FITC (20 μl/test), anti–CD105-FITC (20 μl/test), and anti–CD62E [E-selectin]-FITC (20 μl/test) antibodies obtained from Beckman Coulter. MPs that expressed phosphatidylserine were labeled using fluoresceinconjugated Annexin V solution (20 μl/test; BD Biosciences, USA) in the presence of CaCl2 (5 mM) according to the recommendation of the supplier.

The samples were incubated in the dark for 15 min at room temperature according to the manufacturer’s instructions. It was performed the analysis of area, height, and width forward scatter (FSC) and side scatter (SSC) parameters as well as side scatter width (SSC-W). The gate for MPs was defined by size, using 0.5 and 1.0 μm beads (Sigma, St Louis, MO, USA). For each sample, 500 thousand events have been analyzed. Compensation tubes were used with similar reagents as were used in the sample tubes. Data were constructed as numerous of MPs depending on marker presentation (positive or negative) and determination of MP populations.

Calculation of the number of MPs per liter plasma was based upon the particle count per unit time, the flow rate of the flow cytometer, and the net dilution during sample preparation of the analyzed MP suspension. MP-exposed antigen concentrations were calculated in each sample by multiplying the total concentration of positive MPs by the mean fluorescence intensity of the antigen exposure of the total positive MP population. CD31+/annexin V+ and CD144+/CD31+/ annexin V+ MPs were defined as apoptotic EMPs, EMPs positively labeled for CD62E+ were determined as EMPs produced due to activation of endothelial cells [36].

Statistical analysis

Statistical analysis of the results obtained was carried out in SPSS system for Windows, Version 20 (IBM Corp., Armonk, NY, USA). Baseline and biochemical characteristics were summarized as the mean (M) ± standard deviation (SD) and the median (Ме) and the 25%-75% interquartile range (IQR) for continuous variables, and as absolute numbers and percentages for discrete variables.

The hypothesis of normal distribution of the parameters analyzed was checked by Shapiro–Wilk test and Kolmogorov-Smirnov test. To compare the main parameters of patients’ groups (subject to the type of distribution of the parameters analyzed), one-tailed Student t-test or Mann–Whitney U-test were used. To compare categorical variables between groups, Chi2 test (χ2) and Fisher’s exact test were used. The factors, which could be associated potentially with circulating EMPs, were determined by univariate analysis of variance. Finally, we used univariate and multivariate linear regression to calculate the odds ratio (OR) and a 95% CI for all predictors of elevated circulating EMPs. Statistical significance was accepted for bilateral p< 0.05.

Results

The study population consisted of three hundred none diabetes patients with ischemic-induced CHF (62.0% males) with mean age for 59.50±7.30 years. CHF with reduced and preserved LVEF was found in 37.7% and 62.3% respectively. At least 40.7% patients were obese, 47.7% individuals were dyslipidemic, and 61.3% subjects were hypertensive. General characteristic of the patients included in the study is reported in Table 1.