PLATELET CHANGES IN ATHEROSCLEROSIS

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LITHUANIAN UNIVERSITY OF HEALTH SCIENCES MEDICAL ACADEMY, FACULTY OF MEDICINE

MEDICAL INTEGRATED MASTER’S STUDIES PROGRAMME

Ilan Ivgeny Vashurin

PLATELET CHANGES IN ATHEROSCLEROSIS

Master Thesis

Department of Laboratory Medicine

Supervised by Viltė Marija Gintauskienė, Lecturer, M.D, Ph.D

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SUMMARY

Ilan Ivgeni Vashurin

PLATELET CHANGES IN ATHEROSCLEROSIS

Atherosclerosis is the most important risk factor for cardiovascular events worlwide. The process behind it is very complex, it involves numerous cells, cytokines, factors and other molecules. According to the pathophysiological involvement of platelets in the process of atherosclerotic plaque formation and other articles that proved this phenomenon in patients with confirmed cardiovascular disease.

The aim of the thesis – to analyze the platelet count and mean platelet volume changes in patients that are considered high risk for vascular disease according to other, more applicable laboratory biomarkers such as dyslipidemia and inflammation.

Objectives of the thesis: 1. To observe the changes in platelet count (PLT) and mean platelet volume (MPV) values in patients with high risk of atherosclerosis and the relationship between their PLT, MPV, lipids and CRP values by gender. 2. To observe the changes in PLT and MPV values in patients with high risk of atherosclerosis and the relationship between their PLT, MPV, lipids and CRP values by age. 3. To analyze the changes and correlations in PLT, MPV, CRP, LDL, High Density Lipoproteins (HDL), Triglycerides (TG) and Total cholesterol values in patients with high risk of atherosclerosis by gender and age.

Methodology and methods. According to this the sample was consist of 99 patients with elevated Total cholesterol, LDL and CRP values. This laboratory data was be collected randomly from Cardiology, Endocrinology and Nephrology departments of the Hospital of Lithuanian University of Health Sciences (LSMU) without knowing of their medical statuses. The sample will be divided to subgroups and will be interpretated with the help of statatistical analysis in SPSS software. The purpose is to analyse the mean values of PLT and MPV values in different subgroups and to find correlations between PLT, MPV, CRP and Lipids.

Results. After the statistical interpretation of the results PLT and MPV values were within the reference ranges. Based on these results the conclusion is that theoretical hypothesis was not proved by statistical analysis and further investigations would be needed.

In this population it was found that higher the PLT values lower were the MPV values (r=-0.258, p<0.01) that was not literaturelly based. Negative correlation between CRP and HDL values (r=-0.322, p<0.01). Higher were the age of males higher were values of TG (r=0.726, p<0.05) and with increase in age of females values of PLT were increased as well (r=0.902, p<0.05). Male patients

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between 65 and 75 years old showed negative correlation between CRP and LDL (r=-0.942, p<0.01). PLT found to have a negative correlation with CRP, HDL and TG and with increase in total cholesterol values LDL, HDL and TG values were increased as well.

Conclusions.

1. In dyslipidemic patients it was found that in females and males negative association observed between PLT and MPV values and CRP and HDL values.

2. In the age groups 20–55 and 66–75 negative relation was observed between CRP and HDL values, and between PLT and MPV in age group 56–65.

3. Negative association was observed in the analysis in age and gender group between CRP and HDL values and PLT and MPV values in females, especially in age group 66–75. In group of males between 56 and 65 years old negative association was observed between PLT and HDL values.

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ACKNOWLEDGMENTS

The author thanks Viltė Marija Gintauskienė Lecturer, M.D, Ph.D for her assistance in making this research.

CONFLICTS OF INTEREST

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ABBREVIATIONS

ABP – Androgen-binding protein ADP – Adenosine diphosphate AT-II – Angiotensin II

ATP – Adenosine triphosphate CCL – Chemokine (C-C motif) CCR – CC chemokine receptor

CD36 – Cluster of differentiation 36 , aka fatty acid translocase CRP – C reactive protein CVD – Cerebrovascular disease CXCL – Chemokine (C-X-C motif) CXCR – CXC chemokine receptor DAG – Diacyl-glycerol DRP – Dynamin-1-like protein ECM – Extracellular matrix ET-1 – Endothelin 1

GM-CSF – Granulocyte macrophage colony-stimulating factor Gp1b – Glycoprotein 1b

GpIIb/GpIIIa – Glycoprotein IIb/IIIa H2S – Hydrogen Sulfide HDL – High-density lipoprotein

ICAM-1 – Intracellular adhesion molecule 1 IFN-# – Interferon gamma

IL-4 – Interleukin 4

IP3 – Inositol triphosphate LDL – Low-density lipoprotein

LFA-1 – Lymphocyte function-associated antigen 1 LOX-1 – Oxidized low-density lipoprotein receptor 1 LPS – Lipopolysaccharide

M-CSF – Macrophage colony-stimulating factor MMPs – Matrix metallo proteinases

MPV – Mean platelet volume

N – Number

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NO – Nitric Oxide

Ox-LDL – Oxidized low-density lipoprotein PAF – Platelet-activating factor

PAR – Protease-activated receptor PDGF – Platelet derived growth factor PGI2 – Prostaglandin I2, aka Prostacyclin PIP2 – Phosphatidylinositol 4,5-bisphosphate PKC – Protein kinase C

PLCß – 1-Phosphatidylinositol-4,5-biphosphate phosphodiesterase beta-1 PSGL-1 – P-selectin glycoprotein ligand-1, aka CD162

ROS – Reactive oxygen species. SMC – Smooth muscle cell

SMP – Amooth muscle progentitor cells SR-A1/2 – Steroid receptor RNA activator ½

SR-B1 – Scavenger receptor class B member 1, aka SCARB1 Src – Proto-oncogene tyrosine-protein kinase Src

Std – Standard TG – Triglycerides

TGF – Transforming growth factor TGF-ß – Transforming growth factor beta TLR – Toll-like receptors

TH1 – T-helper 1

VCAM-1 – Vascular cell adhesion molecule 1 VEGF – Vascular endothelial growth factor VLDL – Very low-density lipoprotein vWF – Von Willebrand factor

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INTRODUCTION

Atherosclerosis is a major pathogenetic factor in numerous vascular events that can result in coronary artery disease, myocardial infarction, stroke, hypertensive disease, aneurysms, thrombosis, etc. As a result it has high mortality rates worldwide.

Atherosclerosis has conventional and modifiable risk factors. Conventional risk factors are; age (over age 45 in men and over age 55 in women), family history and race (high rates in African Americans) [1]. Modifiable risk factors include; high blood cholesterol levels especially Low density lipoproteins (LDL), high blood pressure, cigarette smoking, diabetes mellitus, obesity, lack of physical activity, metabolic syndrome and mental stress or depression 1.

Over the past decades scientists were investigating diagnostic methods for detection of atherosclerosis that are widely used nowadays. The most specific biomarkers that exist today are C-reactive protein (CRP), LDL particles, homocysteine and fibrinogen [1].

Over a long period of time it is accepted worldwide that dyslipidemia and endothelial damage are two of highly important factors in pathogenesis of atherosclerosis among others. Endothelial damage is an important step in this process. This damage results in inflammation that is initiated by inflammatory cells and more importantly platelets that maintains the primary homeostasis. Numerous other cells, cytokines and growth factors all highly involved in the pathogenesis of the disease. Hyperlipidemia is another important risk factor. The process involves oxidation of the lipoprotein particles and their buildup in the intima. The most common locations for the atherosclerosis are abdominal aorta, coronary arteries, popliteal arteries, internal carotid arteries and circle of Willis (circulus arteriosus cerebri) [2]. According to literature platelets highly involved in the process of inflammation and are involved in the pathogenesis of the disease.

In this study the main idea is to investigate the role of platelets in the process of atherosclerosis. Because of other studies [3–6] that already performed showed that platelet count and mean platelet volume is elevated in patients with confirmed vascular disease, in this work the main target is to analyze if these changes are applicable to high-risk patients without confirmed vascular disease or events. In order to investigate it, samples of high-risk patient were collected and their platelet count and mean platelet volume were studied. The risk will be predicted according to confirmed factors like, dyslipidemia and increased CRP values that confirm the high blood levels of LDL particles and the state of inflammation, respectively.

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AIM AND OBJECTIVES

The aim of the thesis – to analyze the platelet count and mean platelet volume changes in patients that are considered high-risk for vascular disease according to other, more applicable laboratory biomarkers such as dyslipidemia and inflammation.

Objectives of the thesis:

1. To observe the changes in platelet count (PLT) and Mean platelet volume (MPV) values in patients with high risk of atherosclerosis and the relationship between their PLT, MPV, lipids and CRP values by gender.

2. To observe the changes in PLT and MPV values in patients with high risk of atherosclerosis and the relationship between their PLT, MPV, lipids and CRP values by age.

3. To analyze the changes and correlations in PLT, MPV, CRP, LDL, High Density Lipoproteins (HDL), Triglycerides (TG) and Total cholesterol values in patients with high risk of atherosclerosis by gender and age.

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1. LITERATURE REVIEW

1.1 Pathogenesis of atherosclerosis.

The mechanism of atherosclerosis is complex and involves numerous factors and steps. The initial process begins with the presence of risk factors, such as, dyslipidemia, high blood pressure, chronic inflammatory states, family history and genetic disorders. This mechanism includes participation of numerous mediators and cells, such as oxidized LDL particles, endothelial cells, lymphocytes, monocytes, macrophages, platelets and cytokines [7, 8].

1.1.1 Causes of Hyperlipidemia

Hyperlipidemia can be classified as primary or secondary. Primary is mainly caused by genetic abnormalities. Secondary dyslipidemia is mostly modifiable and caused by complication of other diseases. The most notable cause of secondary dyslipidemia is: Diabetes Mellitus type 2, obesity, tobacco smoke, chronic renal failure, nephrotic syndrome, cholestatic liver disease, excessive alcohol consumption and as side effect of medications [9]. According to studies [9, 10] in diabetic patients was found that greater the insulin resistance larger the very low-density lipoprotein (VLDL) particle size and smaller particle size of LDL and HDL. In nephrotic syndrome the loss of plasma protein leads to increased hepatic production of lipoproteins in order to preserve the plasma oncotic pressure. Smoking is highly associated with lowering the plasma HDL cholesterol and induction of insulin resistance. Obesity increases LDL and VLDL levels and decrease HDL cholesterol. Excessive alcohol consumption can lead to increase in triglyceride levels and among the secondary causes numerous drugs have side effects that affect the plasma cholesterol levels, e.g.; Beta-blockers, thiazide diuretics, oral estrogens.

All this factors described above, if not managed can lead to hyperlipidemia and as a result will lead to atherosclerotic changes [9].

1.1.2 Endothelial injury

Endothelial injury is another very important event in the pathogenesis of atherosclerosis. This injury can be caused by numerous risk factors, such as, diabetes mellitus, hypertension, smoking, aging, obesity and dyslipidemia [11].

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One of most important initiators of injury is the Reactive Oxygen Species (ROS) which leads to impaired endothelial function and consequently vascular dysfunction [12]. ROS derived damage can be caused by all the risk factors described earlier. The free radical formation leads to disbalance between endothelium-derived relaxing factors, such as, Nitric Oxide (NO), Prostaglandin I2 (PGI2),

and Hydrogen Sulfide (H2S) and accentuation of endothelium-derived constricting factors, such as,

Endothelin 1 (ET-1) and Angiotensin II (AT-II). In addition, free radical formation mediates increase in local mediators. All these changes lead to vasoconstriction, proteolysis, accentuation of cell adhesion molecules such as, Vascular cell adhesion molecules 1 (VCAMs) and Intracellular adhesion molecules 1 (ICAMs), release of various cytokines and growth factors and more importantly the platelet adhesion and their activation [13, 14].

During the inflammatory process with intact endothelium there is also overexpression of adhesion molecule such as P-selectins, E-selectins, ICAM-1 and VCAM-1 on the endothelium that enhance the margination and rolling of leukocytes that will lead to their recruitment to inflamed area.

When the endothelial damage occurred, with no importance of the cause, platelets aggregate on the damaged sites where collagen fibers are reachable – this process is known as primary homeostasis (Fig. 1).

Figure 1 Schematic presentation of platelet plug formation.

The uncovered Von Willebrand factor (vWF), fibronectin and laminin on the collagen fibers in tunica intima will attract platelets in order to form platelet plug. The glycoprotein 1b (Gp1b) that found on the platelets will interact with the uncovered vWFs on collagen fibers and this will activate platelets and they will release α and dense granules. α granules contain hundreds of proteins, among them are, p-selectins, integrins, vWF, fibrinogen, platelet factor 4 and others, of which fibrinogen is

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involved in making bonds between platelets and their aggregation, as it interacts with GpIIb/GpIIIa complex. Dense granules consist of Adenosine diphosphate (ADP), Adenosine triphosphate (ATP), histamine, serotonin and ionized calcium, among which calcium and ADP necessary for coagulation cascade, and ADP furthermore enhances platelets adherence to the endothelium (Fig. 1.1). ADP exerts it is effect through binding to P2Y12 and P2Y1 found on the platelets and promote aggregation [15]. All

these steps result in platelet plug formation that is unstable and its’ main function is to maintain the healing process [16]. Healing process involves endothelial progenitor cells that originate from the bone marrow. This process is accompanied by inflammatory response mechanisms that can as a result aid in atherosclerotic plaque formation [17].

CRP is good diagnostic factor for acute or chronic inflammation and is associated with an 8-fold increase in cardiovascular mortality [18]. It is role in the process of atherogenesis is also important. CRP has numerous effects on inflammatory processes, especially complement activation, apoptosis, monocytes recruitment and activation and vascular cell activation [19]. It was found that CRP acts as opsonin by itself. It opsonizes LDL particles for uptake by macrophages, that is why formation of foam cells is highly dependent on CRP levels [20]

1.1.3 Role of LDL in atherosclerosis

During prolonged state of endothelial injury, inflammatory processes that accompany the healing process will increase the risk of atherogenesis by mechanism that will be discussed further. In such individuals the levels of cholesterol is also important factor that in addition to inflammation and endothelial dysfunction will further increase the risk of atherosclerosis [21]. All these mechanism are interconnected and will be discussed in more details.

One concept of oxidized LDL particles is widely discussed over 25 years. The state of hyperlipidemia can lead to LDL particles oxidation by free radicals and their damage by lipases that will release positively charged lysine and arginine amino acids. These forms Oxidized LDL (Ox-LDL) that contains modified protein components that presumably formed by aldehyde products. The lipoproteins may contain varying amounts of phospholipids and cholesterol ester hydroperoxides [22].

Some oxidation enzymes were described in studies [22-25], such as, myeloperoxidases, lipoxygenases, Nicotineamide adenine dinucleotide phosphate (NADPH) oxidases and NO synthases. Ox-LDL particles trigger activation of inflammatory cascade, increases gene expression and activity of matrix metalloproteinases. Modified LDL particles can interact with endothelial cells, macrophages and smooth muscle cells. This interaction is mediated through scavenger receptors, such as, Steroid receptor RNA activator (SR-A1/2), fatty acid translocase (CD36), Scavenger receptor class B member

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1 (SR-B1) and CD68. These receptors are less pronounced on the endothelial cells. According to few authors [24,26,27] Oxidized low-density lipoprotein receptor 1 (LOX-1) found to be most important among all other scavenger receptors in the process of LDL uptake. LOX-1 levels found to be elevated in atherosclerotic plaque and nowadays researches investigate it as possible vascular disease marker and as a target for drugs [24]. According to this explanation it is understandable that without oxidation LDL particles will not initiate the atherosclerotic process [23]. After the process of ox-LDL uptake the macrophages will become foam cells that are less mobile.

Macrophages play also an important role in the process of atherogenesis. Macrophages derived from monocytes that originate from the bone marrow and according to other studies [28-30] well regulated by cellular content of cholesterol. Defective transporters on the monocyte progenitor cells show decreased efflux of cholesterol and increase in circulating monocyte count [28]. Monocytes are able to adhere to the endothelium through interaction between P selectin glycoprotein ligand (PSGL-1) on monocytes and endothelial selectins. They further will be differentiated into macrophages by numerous growth factors and cytokines, such as, Macrophage colony-stimulating factor (M-CSF) and other cytokines that derived from platelets that already found on damaged endothelium. Macrophages will phagocytize Ox-LDL particles and will either become foam cells or will undergo apoptosis (Fig. 2). The phagocytosis is mediated through scavenger receptors that were discussed earlier [28].

Figure 2 Schematic presentation of atherosclerotic plaque formation.

When macrophages become foam cells they are less mobile and can accumulate and proliferate within the smooth muscle cells and release cytokines and inflammatory mediators that will

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phenotypic change from contractile form to active synthetic state that will migrate from the media into the intima. This process is mediated by Transforming growth factor (TGF), vascular endothelial growth factor (VEGF), AT-II and more importantly Platelet derived growth factor (PDGF). Neighboring SMCs are activated in paracrine manner what enable large area of SMCs to migrate and differentiate (Fig. 1.2) [31, 32].

Matrix metalloproteinases are endopeptidases that belong to the family of proteases and they also play significantly important role in the process of SMC migration. They remove the basement membrane around the SMC and enhance their contact with the interstitial matrix. Then with the help of growth factors the SMC form the atherosclerotic plaque (Fig. 1.2). Nowadays they are highly studied as potential drug targets [33-35].

After plaque formation, the atherosclerotic lesion can be classified into 6 histological types. Type 1 contains lipoproteins and leukocytes, type 2 contains macrophages/foam cells with SMC infiltration, type 3 contains scattered coarse lipid granules that disrupt the integrity of SMCs, type 4 characterized by atheromas that contain large extracellular lipid core and growing atherosclerotic lesion, type 5 also characterized by atheromas and lipid core with the development of fibrous caps, and type 6 lesion has ruptured atherosclerotic plaque with hematoma in the arterial lumen [36].

1.2 Platelets’ role in atherosclerosis and inflammation

Beside the function of primary homeostasis platelets have other functions related to inflammation and atherosclerosis. When the platelet plug is formed, platelets are activated and the recruitment of additional platelets is amplified. As it was explained before this process requires mediators such as, ADP, thromboxane A2 or thrombin. Thrombin is a potent activator of platelets, two

thrombin-activated G protein coupled receptors PAR1 and PAR4 are found on platelet surface. PAR1 and PAR4 activation leads to activation of Gαq, which activates 1-Phosphatidylinositol-4,5-biphosphate phosphodiesterase beta-1 (PLCβ). This activation will lead to hydrolization of Phosphatidylinositol 4,5-bisphosphate (PIP2) to generate Diacyl-glycerol (DAG) and Inositol triphosphate (IP3), these will activate Protein kinase C (PKC) and will increase Ca2+ mobilization. This pathway results in activation of integrin αIIbβ3 and finally leads to platelet activation and aggregation [15].

All other mediators act also through G protein-coupled receptors such as, Gq, G13 and Gi [37].

In response to these mediators platelets change their shape by reorganization of cytoskeleton, this change is regulated by myosin light chain phosphorylation that is controlled through Ca2+/calmodulin complex and by myosin phosphatase that is mediated through Rho/Rho-kinase.

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Numerous cytoskeleton related proteins involved in this process. Androgen-binding protein (ABP) is one example that exert it’s effect through polymerization and depolymerization of actin filaments at their ends in response to cellular conditions [38, 39]. Another example of cytoskeleton related proteins that are involved in platelet changes are: Calpain, Spectrin, Dystrophin and Dynamin-1-like protein (DRP), Talin, Moesin, Skelemin and Myosin.

Wide variety of structures assembled into actin cytoskeleton, such as filopodia, lamellipodia, stress-fibers, podosomes, spreading initiation centres and actin comets. One possible function of these related structures is severing and uncapping of actin filaments by gelsolin that provides free filament ends for ARP2/3 complex dependent actin polymerization leading to a rapid increase in the F-actin content of platelets. Regulation and organization of ARP2/3-dependent polymerization occurs downstream of members of the Rho GTPases and nucleation promoting factors (NPFs) [40]. During this process, platelets extend filopodia and generate lamellipodia, resulting in a dramatic increase in the platelet surface area [41]. As a result they change from discoid to spherical shape. This new shape will aid in more efficient degranulation and adhesion to ECM and each other [37].

Activated platelets have the ability to secrete numerous cytokines and chemokines, such as CXCL7, CCL5, CXCL4, CXCL4L1, CXCL1 and others [42,43]that attract immune cells. Synthesis of many of these proteins is controlled by the nuclearfactor κB (NF-κB) transcriptional regulatory system [44]. Platelets are able to modulate endothelial cell permeability by means of endothelial barrier-enhancing factors such as, angiopoietin-1 and sphingosine-1-phosphate. This will lead to leukocyte infiltration and can result even in edema formation [45].

As they undergo structural changes, they secrete pro-inflammatory cytokines and activate leukocytes and endothelial cells. This process is mediated through P-selectins, and integrins that form the cell-to-cell bridges and Extracellular matrix (ECM) interactions [7, 46]. Activated platelets release CCL5 (RANTES) that will lead to monocyte recruitment to the vascular wall and CXCL4 (platelet factor 4) that will promote monocyte differentiation to macrophages or specialized antigen-presenting cells in the presence of Interleukin 4 and/or Granulocyte macrophage colony-stimulating factor (GM-CSF). CXCL4-driven macrophages may lack of HLA-DR and has high CD86 surface expression. Furthermore, CXCL4 induces higher phagocytic capacity as compared to GM-CSF induced macrophages. As a result, CXCL4 may enhance atherogenesis by promoting differentiation of monocytes into macrophages and foam cells [43]. CXCL7 may promote synthesis of matrix components such as hyaluronic acid or glycosaminoglycanes by fibroblasts [43]. CXCL12 is found to have an interesting role beside its effect on recruitment of progenitor cells to the sites of vascular injury that it aids in atherosclerosis; it maintains the atherosclerotic lesion by accumulation of Smooth muscle progenitor cells (SMPs) that make the plaque stable. It is a possible target for therapeutic drugs for treatment of thromboembolic events [47].

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Platelets release also PDGF and TGF-ß that enhance the formation of inflammatory cells and fibroblasts [48] (Fig. 1.2). PDGF activates Proto-oncogene tyrosine-proteinkinase Src (Src), which reduces levels of the microRNAs by inhibiting p53. One of p53's tasks is spurring production of miR-143 and miR-145 that was proved by other studies that these two microRNAs, miR-miR-143 and miR-145 prevent cells from switching to the mobile form, this is one of possible variants how smooth muscle cells transform to mobile form that forms the atherosclerotic plaque [49].

It is found that in addition to secretion of several types of cytokines and chemokines platelets have receptors for them along with FcγRII and Toll-like receptors (TLRs). Numerous TLRs were discovered on platelets, such as, TLR1, TLR2, TLR4, TLR6, TLR8 and TLR9 [50].According to this they can participate in immune response by recognition of infectious pathogens and sequestering them while secreting immunomodulatory factors that will enhance the immune response against the infection [51].Recent studies showed that platelets from several species bind or respond to bacterial lipopolysaccharide (LPS), and it amplifies the response triggered via Fc receptors that lead to platelet aggregation and serotonin secretion [44].

On the surface of platelets there are numerous glycoproteins, such asCD40-Ligand (CD154) that bridges the innate and adaptive immunity [52], P-selectins that binds PSGL-1 on neutrophils, monocytes, microparticles, and T-helper 1 (Th1) cells, ICAM-2 that binds Lymphocyte function-associated antigen 1 (LFA-1) on neutrophils and monocytes and others that discussed before [53]. Adaptive immunity is modulated through dendritic cells. During the initial stage of atherosclerosis, dendritic cells are able to interact with platelets. Interaction and activation of dendritic cells is mediated through CD11b/CD18 (Mac-1) and platelet functional adhesion molecule C. This interaction bridges and directs the progenitor and dendritic cells to the sites of damaged endothelial cells, thereby, dendritic cells will co-stimulate more T-cells and the response will be stronger and more rapid [50].

In a study that was performed in 2010 [54, 55], It was proved that platelet-induced atherosclerosis is mediated by activation of leukocytes through CD40L. After CD40L and CD40 interact on the endothelial surface, thrombomodulin expression is decreased, and there is a facilitation of thrombin generation [56]. In addition, CD40L induces endothelial dysfunction with decreased NO synthesis and augmented oxidative stress [56].

Other study [57] suggests that, JAM-A a member of the immunoglobulin superfamily adhesion molecules involved in the process of platelet induced atherosclerosis. These molecules first were identified on platelets, but now it is found that it exist on other cells as well. On leukocytes, it mediates cell migration by regulating integrin de-adhesion. On epithelial and endothelial cells, JAM-A is a component of the tight junctions and regulates cell layer permeability and leukocyte extravasation. During inflammatory states, JAM-A is translocated from the intercellular space and is exposed on the apical surface, thereby becoming available for the interaction with blood cells. Those, endothelial

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expression of JAM-A will promote plaque formation by guiding monocytes to sites of plaque formation. During investigation by other researchers [58] molecular and immunofluorescence determinations revealed very high levels of JAM-A mRNA and JAM-A protein in the atherosclerotic plaques of patients with cardiovascular disease. However, this role of JAM-A is still under investigations and not fully understood [59].

Platelets can also be activated by chemokines and cytokines that released by the leukocytes. Platelet-activating factor (PAF), Interferon gamma (IFN-γ), IL-2, CXCL12 and CCL22 are examples of inflammatory mediators that can activate platelets [60]. Chemokine receptors that are found on platelets: CXCR1 and CCR1, 2, 3, 5 [53].

When platelets are activated and the process above takes place, such markers as, P-selectins, CD40 ligands and CRP will be elevated, it may provide further insight into prediction markers of possible cardiovascular event and as potential therapeutic targets [61]. In addition according to other study performed in 2013 [62], platelets undergo changes in Golgi apparatus; vesicles and tubules become thickened and enlarged, α granules significantly decrease in number. When during this study the Golgi apparatus was blocked, flow cytometry revealed decreased amount of CD40L expression, what can prove us that CD40L is synthesized in the Golgi apparatus of platelets.

Now, we can conclude that during the process of atherogenesis, platelets undergo morphological changes and they are involved in the initial step of atherosclerosis, but how this influences their count. PLT and MPV are simple diagnostic laboratory tests, standard part in CBC test that performed well often on almost every patient either in hospitals or outpatient clinics. Abnormal platelet count can indicate wide range of disorders and the question about their change in vascular disease is not fully understood and known. Assessment of MPV values can indicate the functional status of platelets, that it’s role in vascular disease is still not well understood. According to other study [63] it is found that patients with acute coronary syndrome found to have low platelet count as compared with patients with normal population (p<0.001). Other very old study [4] suggests that in 981 patients with stable angina pectoris platelet count was no changed but the MPV was increased comparing with a control group (p<0.01). Increased values correlate with more large and reactive platelets because of their increased turnover [5].In other study [6] was concluded that with the help of MPV severity of atherosclerosis can be assessed.

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2. RESEARCH METHODOLOGY AND METHODS

In this study the purpose is to assess if PLT and MPV values will be changed in patients with high risk for atherosclerotic disease. The risk is assessed according to hyperlipidemia and inflammatory state that can be asses by lipid profile and CRP values [64, 65].

Such markers as platelet count and MPV is cheaper and performed quite more often than other more expensive tests and if according to other authors they proved to be changed in patients with cardiovascular diseases in this study they will be assessed in patients with unknown disease status [4, 6, 3].

2.1 Study population

A sample of 99 patients ages 20–90 was collected from the Department of Laboratory Medicine at the Hospital of Lithuanian University of Health Sciences (LSMU). The sample was collected randomly from three departments: Endocrinology, Cardiology and Nephrology and subdivided by gender and age. The population consists of patients with elevated CRP (>7.5mg/l), total cholesterol (>5.2mmol/l) and LDL (>2.59mmol/l) values.

In order to prevent selection bias the sample consists only of adults older than 18 years old, with randomization of their economic, educational and health status, and the patients’ diseases, medical records, place of work or other conditions are unkown to the researcher. A test sample size and test scheme are presented in Figure 3.

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2.2 Procedure and Instruments

In the Department of Laboratory Medicine at the Hospital of Lithuanian University of Health Sciences (LSMU) Total cholesterol, HDL, LDL, TG and CRP values are evaluated with the use of Beckman Coulter (Beckman Coulter, Inc., 250 S. Kraemer Blvd., Brea USA) SYNCHRON UniCel® DxC 800. PLT and MPV values are evaluated with the use of SYSMEX CORPORATION (Sysmex Corporation, Kobe, Japan) SYSMEX XE-5000.

2.2.1 Total cholesterol

CHOL reagent is used to measure cholesterol concentration by a timed-endpoint method. In the reaction, cholesterol esterase (CE) hydrolyzes cholesterol esters to free cholesterol and fatty acids. Free cholesterol is oxidized to cholestene-3-one and hydrogen peroxide by cholesterol oxidase (CO). Peroxidase catalyzes the reaction of hydrogen peroxide with 4-aminoantipyrine (4-AAP) and phenol to produce a colored quinoneimine product. The SYNCHRON System(s) automatically proportions the appropriate sample and reagent volumes into the cuvette. The ratio used is one part sample to 100 parts reagent. The system monitors the change in absorbance at 520 nanometers. This change in absorbance is directly proportional to the concentration of CHOL in the sample and is used by the System to calculate and express CHOL concentration.

2.2.2 Low density lipoprotein

Direct LDL Cholesterol method is a homogeneous assay without the need for any off-line pretreatment or centrifugation steps. The method depends on a unique detergent, which solubilizes only the non-LDL lipoprotein particles and releases cholesterol to react with cholesterol esterase and cholesterol oxidase to produce a non-color forming reaction. A second detergent solubilizes the remaining LDL particles, and a chromogenic coupler allows for color formation.

LDL reagent is used to measure the cholesterol concentration by a timed-endpoint method. The SYNCHRON® System(s) automatically proportions the appropriate LDL cholesterol sample and reagent volumes into a cuvette. The ratio used is one part sample to 93 parts reagent. The System monitors the change in absorbance at 560 nanometers. This change in absorbance is directly proportional to the concentration of LDL cholesterol in the sample and is used by the System to calculate and express the LDL cholesterol concentration.

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2.2.3 Hight density lipoprotein

HDL cholesterol test is a two reagent homogenous system for the selective measurement of serum or plasma HDL cholesterol in the presence of other lipoprotein particles. The assay is comprised of two distinct phases. In phase one, free cholesterol in non-HDL-lipoproteins is solubilized and consumed by cholesterol oxidase, peroxidase, and DSBmT to generate a colorless end product. In phase two, a unique detergent selectively solubilizes HDL. The HDL cholesterol is released for reaction with cholesterol esterase and cholesterol oxidase, in the presence of chromogens, to produce a colour product. The HDL reagent measures the HDL cholesterol concentration by a timed-endpoint method. 6 The system automatically proportions the appropriate HDL cholesterol sample and reagent volumes into a cuvette. The ratio used is one part sample to 93 parts reagent. The system monitors the change in absorbance at 560 nanometers. This change in absorbance is directly proportional to the concentration of cholesterol in the sample and is used by the system to calculate and express the HDL cholesterol concentration.

2.2.4 Triglycerides

Triglycerides GPO reagent is used to measure the triglycerides concentration by a timed endpoint method. 1,2 Triglycerides in the sample are hydrolyzed to glycerol and free fatty acids by the action of lipase. A sequence of three coupled enzymatic steps using glycerol kinase (GK), glycerophosphate oxidase (GPO), and horseradish peroxidase (HPO) causes the oxidative coupling of 3,5-dichloro-2-hydroxybenzenesulfonic acid (DHBS) with 4-aminoantipyrine to form a red quinoneimine dye. The triglycerides-blanked assay parameters are an alternate parameter set designed to be used with the Triglycerides GPO (TG) reagent. The triglycerides-blanked assay reduces the effects of free glycerol in serum, which may be seen with the triglycerides assay parameters. The triglycerides-blanked assay employs the use of a reaction trigger cycle for glycerol blanking. The blanking step in the triglycerides-blanked assay reduces the sample throughput when compared to the nonblanked triglycerides assay. In some cases, free glycerol can have a clinically significant effect on the final result. 3,4 The SYNCHRON System(s) automatically proportions the appropriate sample and reagent volumes into the cuvette. The ratio used is one part sample to 100 parts reagent. The System monitors the change in absorbance at 520 nanometers just prior to the addition of lipase and for a fixed time interval after lipase addition. This change in absorbance is directly proportional to the concentration of triglycerides in the sample and is used by the System to calculate and express the triglycerides concentration.

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2.2.5 C-reactive protein

CRP reagent is used to measure the C-reactive protein concentration by a turbidimetric method. In the reaction, C-reactive protein combines with specific antibody to form insoluble antigen-antibody complexes. The SYNCHRON System(s) automatically proportions the appropriate sample and reagent volumes into a cuvette. The ratio used is one part sample to 26 parts reagent. The system monitors the change in absorbance at 340 nanometers. This change in absorbance is proportional to the concentration of reactive protein in the sample and is used by the System to calculate and express C-reactive protein concentration based upon a single-point adjusted, pre-determined calibration curve.

2.2.6 PLT and MPV

The Sysmex XE-5000 performs analyses using the following methods: RF/DC detection method, Sheath Flow DC detection method, and Flow Cytometry methods using a Semiconductor Laser. The RF/DC detection method detects the size of the cells by changes in direct-current resistance and the density of the cell interior by changes in radio-frequency resistance. Cells pass through the aperture of the detector surrounded by sheath fluid using the sheath flow method. The principle of flow cytometry is also used. A semiconductor laser beam is emitted to the cells passing through the flow cell. The forward scattered light is received by the photodiode, and the lateral scattered light and lateral fluorescent light are received by photo multiplier tube. This light is converted into electrical pulses, thus making it possible to obtain cell information.

Platelets are counted accurately by the impedance method. In some pathological samples, the fluorescence count is given priority as it reflects the RNA content and not ony the size that can aid in MPV establishment and is therefore more accurate.

2.3 Analysis of the results

Data is expressed as mean ± standard deviation (SD) or as number (N; n) and percent. Analysis of variance (ANOVA) was used to analyze the relationship between groups. Pearson’s test of correlations (r) was used to evaluate relationships between values of laboratory tests. A probability values (p) of <0.05 were considered statistically significant. Statistical analysis was performed using software SPSS 22.0.

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3. RESULTS

3.1 Relations between PLT, MPV, Lipids and CRP by gender

99 patients (53 men and 46 women; mean age 63±15.1 years) were enrolled in the study. In the subgroup of gender, the mean male age is 58.2±14. Mean female age is 68.6±14.5.

Because normal range of PLT and MPV varies between males and females, each gender was analyzed separately.

The descriptive statistics for the laboratory results are represented in Table 1 for the total sample.

Table 1 Lipids, CRP, platelets and MPV values according to 99 patients

Mean ± SD Normal Values

Total Cholesterol, mmol/l 6.2±0.8 <5.2

HDL, mmol/l 1.15±0.3 >1.55

LDL, mmol/l 3.8±0.8 <2.59

TG, mmol/l 1.8±1.05 <1.95

CRP, mg/l 42.4±63 <7.5

Platelets, x109/l Male 244.87±84.88 Male 166–308

Female 265.2±85.88 Female 173–390

MPV, fl

Male 10.54±0.87 Male 9.3–12.1

Female 10.63±0.91 Female 9.1–11.9

SD, Standard deviation; CRP, C-reactive protein; HDL, High-density lipoproteins; LDL, Low-density lipoproteins; TG, Triglycerides; MPV, Mean platelet volume.

According to descriptive statistics we can analyze that the PLT and MPV mean values are within normal ranges both in males and females.

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Figure 4 Pearson correlation between MPV and Platelets

During laboratory data analysis it was found that CRP values were higher in males than in females (p<0.05). PLT values were lower in males than in females (p<0.05) (Tab. 2). Difference in PLT values is not relevant even if it is statistically significant as the normal reference range of PLT for females is higher than for males and their values are within the reference range.

Table 2 Lipids, CRP, platelets and MPV values between men and women

Mean ± SD Males n=53 Females n=46

Total Cholesterol, mmol/l 6.13±0.6 6.26±0.9

HDL, mmol/l 1.08±0.3 1.23±0.3 LDL, mmol/l 3.74±0.6 3.91±0.9 TG, mmol/l 1.87±1.2 1.87±0.8 CRP, mg/l 45.88±68.4* 38.46±56.6* Platelets, x109/l 244.87±84.8* 265.20±85.8* MPV, fl 10.53±0.8 10.63±0.9 *p<0.05.

SD, Standard deviation; CRP, C-reactive protein; HDL, High-density lipoproteins; LDL, Low-density lipoproteins; TG, Triglycerides; MPV, Mean platelet volume; n, Sample size.

In male group significant negative correlation observed between the HDL and CRP values; (r=-0.309, p<0.05). With increase in age the values of HDL decrease (r=-0.279, p<0.05). Positive

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and TG (r=0.385, p<0.01).

In female group the same negative correlation observed between HDL and CRP as in males (r=-0.331, p<0.05) and positive correlation was observed only between total cholesterol and LDL (r=0.819, p<0.01).

3.2 Relations between PLT, MPV, Lipids and CRP by age

In this group PLT and MPV values were found to be in the reference range as well.

During the analysis it was found that the highest Total cholesterol was in patients between 56 and 65 years old 6.28±0.8 mmol/l and the lowest was in patients between 75 and 90 years old 6.08±0.6 mmol/l (p<0.05), and the lowest HDL values were in patients between 66 and 75 years old in comparison with patients of age group between 20 and 55 (p<0.05) (Tab. 3).

Table 3 Lipids, CRP, platelets and MPV values divided by age groups

Mean ± SD of age groups

20–55 y.o 56–65 y.o 66–75 y.o 75–90 y.o

n=24 n=32 n=20 n=23 Total Cholesterol, mmol/l 6.18±0.8 6.28±0.8* 6.18±0.9 6.08±0.6* HDL, mmol/l 1.28±0.4* 1.08±0.3 1.03±0.3* 1.21±0.2 LDL, mmol/l 3.66±0.6 3.93±0.8 3.82±0.9 3.83±0.8 TG, mmol/l 2.26±1.5 1.68±0.8 1.99±0.9 1.62±0.6 CRP, mg/l 32.95±43.1 48.23±69.9 42.38±75 44.3±61.9 Platelets, x109/l 266.21±100.4 243.69±72.7 269.55±97.9 243.43±75.1 MPV, fl 10.45±0.9 10.55±0.7 10.63±0.8 10.71±0.9 Age, y.o 42±9 60±2 70±2 81±3 *p<0.05.

SD, Standard deviation; CRP, C-reactive protein; HDL, High-density lipoproteins; LDL, Low-density lipoproteins; TG, Triglycerides; MPV, Mean platelet volume; y.o., Years old; n, Sample size.

In 20–55 years old group negative correlation observed between LDL and MPV (r=-0.436, p<0.05), and negative correlation between HDL and CRP (r=-0.506, p<0.05), positive correlation between Total cholesterol and LDL (r=0.714, p<0.01) and Total cholesterol and TG (r=0.458, p<0.05). In 56–65 years old group negative correlation observed between TG and PLT values (r=-0.410, p<0.05), and between MPV and PLT (r=-0.366, p<0.05). In contrast to previous age group, these patients found to have positive correlation only between Total cholesterol and LDL values

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(r=0.768, p<0.01).

In 66–75 years old group positive correlation observed between TG and MPV (r=0.518, p<0.05). Negative correlation observed between CRP and HDL (r=-0.480, p<0.05) and positive correlation between Total cholesterol and LDL (r=0.887, p<0.01). And in 75–90 years old group the only positive correlation found between Total cholesterol and the LDL values (r=0.688, p<0.01).

3.3 Changes and relations in PLT, MPV, CRP, and Lipids by gender and age

In gender and age group it is found that mean PLT of females between 66 and 75 years old (n=12) found to be the highest between the others (p<0.05), but this value is still within the normal reference range (Tab. 4).

Table 4 Lipids, CRP, platelets and MPV values divided by age and gender groups

Mean ± SD of age and gender groups

20–55 y.o 56–65 y.o 66–75 y.o 75–90 y.o Males

n=16 n=24 n=8 n=5

Total Cholesterol, mmol/l 6.3±0.9 6±0.5*†† 5.8±0.2 6.2±0.6

HDL, mmol/l 1.2±0.4 1±0.3 0.8±0.1 1.1±0.2 LDL, mmol/l 3.2±0.7 3.7±0.6 3.6±0.3 3.8±0.8 TG, mmol/l 2.2±1.8 1.6±0.8 1.8±1.1 1.5±0.4 CRP, mg/l 34.5±50.1 56±79.1 27.1±24.2 68.5±109.5*† Platelets, x109/l 263.8±100.1 238±70.7 231.8±92.7 238±100.4 MPV, fl 10.5±1 10.50±0.7 10.4±0.9 10.6±1 Age, y.o 41±10 60±2 70±3 80±2 Females n=8 n=8 n=12 n=18

Total Cholesterol, mmol/l 5.9±0.4 6.9±1.1*†† 6.3±1.2 6±0.7

HDL, mmol/l 1.3±0.5 1.2±0.3 1.1±0.3 1.2±0.2 LDL, mmol/l 3.5±0.5 4.3±1 3.9±1.1 3.8±0.8 TG, mmol/l 2.2±1 1.7±0.9 2±0.8 1.6±0.6 CRP, mg/l 29.8±26.6 27.96±20.6 52.5±95.2 37.5±43.8 Platelets, x109/l 271±107.6 260.7±80.9 294.6±96.8*‡ 244.9±70 MPV, fl 10.2±0.7 10.5±1 10.7±0.8 10.7±0.9 Age, y.o 43.5±8 61±2.7 70±2 81±4

*p<0.05; †, difference between all the rest groups except males 56–65 and females 66–75 age groups; ‡, difference between all groups; ††, difference between males and females in age group 56–65.

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CRP values found to be highest in males above 75 years old in comparison with all the rest groups except males 56–65 and females 66–75 age groups (p<0.05). And Total cholesterol found to be higher in females in comparison to males in age group 56–65 (p<0.05).

Males 20–55 years old were found to have negative correlation between LDL and MPV values (r=-0.515, p<0.05), positive correlation between Total cholesterol and LDL (r=0.791, p<0.01), and between Total cholesterol and TG values (r=0.523, p<0.05). In female population of this age group negative correlation found between CRP and PLT values (r=-0.821, p<0.05), and between CRP and HDL values (r=-0.810, p<0.05).

Males 56–65 years old were found to have negative correlation between HDL and PLT values (r=-0.419, p<0.05). No significant relations in females of this age group were observed.

Males 66–75 years old were analysis showed negative correlation between CRP and LDL (r=-0.942, p<0.01), and positive association between age and TG values (r=0.726, p<0.05). In female patients of the same age group negative correlation observed between HDL and CRP values (r=-0.656, p<0.05), between TG and PLT values 0.754, p<0.05), and between PLT and MPV values (r=-0.613, p<0.05).

In the last subgroup of patient 75–90 years old, males found to have positive correlation between age and PLT values (r=0.902, r<0.05), and females showed no significant correlations.

DISCUSSION OF THE RESULTS

According to statistical results it is found that during inflammatory state in dyslipidemic patients in total sample population and in subgroups mean PLT and MPV values were within refence ranges of normal. And no significant correlations were found between MPV or platelets and CRP or LDL and Total cholesterol that were discussed in pathogenetical role of platelets in atherosclerosis. This result can be interpretaded such as, no relationship that exist during early stages of atherosclerosis, or it can be as a result of selection bias or procedure bias.

It is found that with elevations in PLT, MPV values drop-off, this change in MPV is possible in conditions such as infection, inflammation or malignancy [66]. CRP can confirm the state of inflammation, but it can be elevated in other pathological conditions such as infection and malignancy. Because the studied population’s disease status is unknown these conditions cannot be excluded.

Theories for the phenomenon of increase in platelets and decrease in MPV are not found in any resources, but according to [67] it is found that in patients with confirmed Acute Myocardial Infarction (AMI) values of MPV and platelets were increased. According to the results in this work no

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correlation was found between CRP and MPV values, which mean that degree of CRP elevation will not influence the MPV values.

According to the literature it is found that high MPV values are related to more reactive platelets that are more likely increase the risk of atherogenesis [4]. But according to the statistical analysis this phenomenon was not observed.

Few scientific works that performed earlier showed increase in MPV values in patients that already have confirmed vascular disease, [3,4] however in this work the status of patients was unknown, we can conclude that this method of risk assessment is not statistically significant, or for instance, the population that was collected has no atherosclerotic process at all, but this can’t be proved based on the study population, technique and methods used in this work. In order to confirm that, we would need to collect a sample based on angiography confirmed atherosclerotic changes, even if the patient is asymptomatic. With the help of angiography based results we would be able to investigate the changes that proved by other works during different stages of atherosclerosis.

Till now, most of the articles were dealing with a sample of patients that have confirmed coronary artery disease or MI, by other markers and diagnostic tools.

During the analysis it was found that as triglycerides values were increased, PLT was reduced. This phenomenon is also has no literature based explanation, because according to other studies hypertriglyceridemia increases platelet activation status, which means that aggregation shall take place and number of mature platelets must increase [68].

During results interpretation it was observed that LDL and TG values increase with the increase in total cholesterol values in all groups. When the HDL values low, CRP values are high. When HDL values low, there are no protective effects of HDL particles and that can lead to inflammation [69]. This can confirm that HDL is protective and when HDL values are significantly high it protects against inflammation and CRP values accordingly will be between the reference ranges [69]. In male patients the HDL values start to decline with the age, this phenomenon can explain that age is unmodifiable risk factor for atherosclerosis.

During the analysis it was found that the highest Total cholesterol values were observed in patients between 56 and 65 years old and the lowest was in patients who older than 75 years old, this findings can be hypothesized by explanation that older patients are more likely to administer lipid-lowering medications.

The patients that were selected either have no atherosclerotic changes at all or the severity is not high enough to significantly effect the PLT and MPV values. It was statistically proved that there is a reverse relation between the PLT and MPV. Based on these results we can’t conclude that markers such as PLT and MPV can be used in the assessment of pre-atherosclerotic risk. In order to conclude that, a sample of patients need to be assessed by higher methods of investigations, like angiography to

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confirm that they do or don’t have atherosclerotic changes. This method will be more precise, and according to this the relationship between these markers can be established.

Based on theory and other authors platelets play significant role in the process of atherosclerosis. But according to statistical analysis of population with hyperlipidemia and inflammation these changes were not observed. For instance, there is a tendency to have lower MPV values when the Platelet count increase that reject the theoretical theory.

CONCLUSIONS

1. In dyslipidemic patients it was found that in females and males negative association observed between PLT and MPV values and CRP and HDL values.

2. In the age groups 20–55 and 66–75 negative relation was observed between CRP and HDL values, and between PLT and MPV in age group 56–65.

3. Negative association was observed in the analysis in age and gender group between CRP and HDL values and PLT and MPV values in females, especially in age group 66–75. In group of males between 56 and 65 years old negative association was observed between PLT and HDL values.

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PLATELET CHANGES IN ATHEROSCLEROSIS

PLATELET CHANGES IN ATHEROSCLEROSIS

TABLE OF CONTENTS

SUMMARY

ACKNOWLEDGMENTS

CONFLICTS OF INTEREST

ABBREVIATIONS

INTRODUCTION

AIM AND OBJECTIVES

1. LITERATURE REVIEW

2. RESEARCH METHODOLOGY AND METHODS

3. RESULTS

DISCUSSION OF THE RESULTS

CONCLUSIONS

REFERENCES