Atheroscelerotic Cardiovascular Disease Altered Concentrations Of Serum Adipocytokines Biology Essay

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Cardiovascular disease remains one of the leading causes of death in the UK accounting for 37% of deaths in 2004 (Bakhai, 2008). The underlying factor for these deaths have been attributed to atherosclerosis, and it is estimated that atherosclerosis would be the leading cause of morbidity worldwide by 2020 (Balla et al., 2004). Thus, there is a need to identify atherosclerosis during early onset. Biomarkers continue to be sought for this purpose, and this is the remit of this study.

1.2 Pathogenesis of atherosclerosis

Atherosclerosis is a complex vascular disorder with a multifaceted pathogenesis involving, almost sequentially, repetitive vascular injury, platelet and fibrin deposition, cellular migration and proliferation, and lipid accumulation and atherosclerotic plaque formation (Figure). Several outcomes are possible. A disruption of the atherosclerotic plaque may lead to occlusive thrombosis in the coronary vessels, which is the immediate cause of most acute coronary syndromes (Eitzman et al., 2000). A similar episode in the cerebral vessels may lead to stroke. Both events can cause sudden death or severe pathological sequelae among affected patients (Martín-Ventura et al., 2009). Subocclusive thrombosis may also occur, contributing to plaque growth, as evidenced by the presence of extensive fibrin deposition in most complex atherosclerotic lesions (Eitzman et al., 2000). Currently, medical knowledge is unable to effectively predict who is at risk of developing these problems. A significant challenge of cardiovascular medicine is to find a way to predict unambiguous risk of an acute thrombotic event (Martín-Ventura et al., 2009).

1.3 Current risk prediction for cardiovascular events

General cardiovascular risk factors (Table) have been used for many years to predict the risk of cardiovascular events in the general population. This has been supplemented by other data such as the cardiac ejection fraction. In patients with symptomatic atherosclerosis, for instance ischaemic heart disease, techniques such as coronary angiography have been employed to assess the extent of the disease. However, despite these measures and advancing technology, there continues to be a high incidence of unexpected acute ischaemic events, both in the population with known atherosclerosis and in subjects thought to be healthy but with the disease in subclinical form (Martín-Ventura et al., 2009).

1.4 Adipocytokines in the aetiology of atherosclerosis

Recent evidence has suggested that fat-secreted biomolecules, so called adipocytokines or adipokines, may play an important role in the development of atherosclerosis in otherwise healthy individuals and in disease states (Al et al., 2009). Multiple roles in metabolic and inflammatory responses have been assigned to adipocytokines (Table) (Wozniack et al., 2008). Due to the connection of adipocytokines with adipose tissue, this led to the development of a novel concept that the pathogenesis of atherosclerosis can be associated with low-degree inflammation accompanying slow (auto) immune attack of the endothelial wall of arteries. This model considers therefore adipocytokines as the bridge between atherosclerosis, inflammation and immunity (Matarese et al., 2007).

1.5 Adipose tissue and adipocytokines

The adipocyte is a remarkable cell type in several respects. It stores excess energy in the form of lipids and is thus able to dramatically change its size in accordance with changing metabolic needs (Rajala and Scherer, 2003). This ability gives adipose tissue an almost unlimited capacity for growth, making it perhaps the only tissue in the body with the ability to drastically increase its size without an underlying transformed cellular phenotype (Rajala and Scherer, 2003).

In the last decade, adipose tissue was recognised as an active endocrine organ responsive to both central and peripheral metabolic signals and is itself capable of secreting a range of bioactive proteins called adipocytokines (see Fig. 1) ( Rajala and Scherer,2003; Bahkai, 2008). Recent studies have implicated these molecules as not only playing a role in the genesis of the metabolic syndrome, but also in altering endothelial function.

Adipocytokines, also known as adipokines, have diverse signalling effects with autocrine/paracrine mechanisms (Al et al, 2009) that modulate insulin resistance, hepatic lipoprotein production, and vascular inflammation (Qasim et al., 2008). Since altered endothelial function is one of the earliest manifestations of atherosclerosis, such effects further support a role of adipokines in the development of atherosclerosis (Burnett et al., 2005).

Moreover, adipocytokines have a direct effect on the structure and function of the heart and on the cardiovascular system as a whole (González-Juanatey et al., 2009) and they are associated with atherothrombosis and could provide a new therapeutic target for reducing cardiovascular risk (González-Juanatey et al., 2009).

Figure 1: Schematic overview of the altered secretory profile associated with terminal fat cell differentiation. A few representative examples are indicated for each category (Rajala and Scherer, 2003).

Altered pattern of adipocyte-derived hormones is deeply involved in the chronic proinflammatory state especially in patients with central obesity and partially accounts for their increased cardiovascular risk. Changes in adipocyte-derived factors enhance oxidative stress by activating oxidases, interfere with NO availability and influence cell proliferation and apoptosis (Anfossi et al., 2010). Several evidences indicated that adipocytokines influence platelet production and responses and VSMC function that are critical in the development of atherogenesis and atherothrombosis (Anfossi et al., 2010).

Several proinflammatory adipocytokines are also secreted by the adipose tissue, such TNF-alpha, IL-6 and leptin, as well as acute phase proteins, such as PAI-1 and CRP ( ref 4, Bahkai, 2009). Plasma levels of these adipocytokines increase along with increasing adipose mass. Although the evidence for low-level expression of CRP in adipose tissue is inconclusive, its expression in the liver is further up-regulated by IL-6, which is secreted in increased amounts in obesity (Bakhai, 2008).

Three adipocytokines in particular, interleukin-6 (IL-6), plasminogen activator inhibitor 1 (PAI-1) and resistin have been proposed as biomarkers of adipose function that may add values in predicting cardiovascular disease (CVD) risk and provide targets for therapeutic interventions ( Qasim et al., 2008).


Resistin belongs to a class of cysteine-rich proteins collectively termed resistin-like molecules (RELM) (Kusminski et al., 2005) or FIZZ (found in inflammatory zones) proteins (Reilly et al., 2004). Resistin mRNA encodes a 114-amino acid polypeptide that contains a 20-amino acid signal sequence (Verma et al., 2003). This peptide has a molecular weight (MW) of 12 kDa and mostly circulates as a high-molecular-weight hexamer but also has a distinct, more active low-molecular-weight complex (Patel et al., 2004; Rajala and Scherer, 2003).

Resistin, named for its ability to cause insulin resistance to insulin and link obesity to diabetes (Verma et al., 2003), is an important regulator of glucose homeostasis, adipogenesis, and, potentially, inflammation [317]; in particular, it can induce insulin resistance by regulating adipose tissue deposition through a negative feedback mechanism [317], and exerts proinflammatory effects through activation of the transcription factor NF-κ B [318] ( Anfossi et al., 2010). The interplay between resistin and vascular wall cells can potentially contribute to the development of atherosclerotic lesions (Figure 6): in particular, it favours angiogenesis by inducing endothelial cell growth activation and migration, mainly by increasing ET-1 release [319, 320], and potentiating the effect of CD40L [321]; furthermore, it is involved in lipid storage in macrophages [317, 322] ( Anfossi et al., 2010).

Despite resistin has been found first in adipocytes, in humans, it is expressed primarily in inflammatory cells.22-25, more precisely in mononuclear cells [10] D.B. Savage, C.P. Sewter and E.S. Klenk et al., Resistin/Fizz3 expression in relation to obesity and peroxisome proliferators-activated receptor-γ action in humans, Diabetes 50 (2001), pp. 2199-2202. Full Text via CrossRef | View Record in Scopus | Cited By in Scopus (392)[10]. These are the cells that infiltrate arteries and initiate or promote atherogenesis by secreting various pro-inflammatory cytokines ( 26) (Jung et al., 2006) suggesting that resistin may be importantly involved in inflammation and/or immune modulation (Burnett et al., 2005). Moreover, recombinant resistin upregulates cytokines such as IL-1, IL-6, and IL-12 and TNF through a nuclear factor kappa B (NF-j-B)-dependent pathway [22-24] and also reduces endothelial cell production of intercellular adhesion molecule-1 (ICAM-1), vascular cell-adhesion molecule-1 (VCAM-1), and CC chemokine ligand-2 (CCL-2) [25),27,28 and monocyte chemoattractant protein-1 (MCP-1) expression, and impairs tumour necrosis factor receptor-associated factor-3 (TRAF-3) expression.

These activities support the hypothesis that resistin is linked to cardiovascular disease, and exerts its effects, at least in part, through activation of the endothelium ( Burnett et al., 2005). However, the relationship of resistin to inflammation, insulin resistance, and atherosclerosis in humans remains largely unexplored.

1.1.2 Interleukin 6

Interleukin (IL)-6 is a pleiotropic cytokine with a broad range of humoral and cellular immune effects relating to inflammation, host defense, and tissue injury.1 2 Interleukin-6 (IL-6) is produced by different cell types, including those present in adipose tissue [174, 182]: adipose tissue, in particular, contributes to up to 35% of circulating IL-6 levels [174]( Anfossi et al., 2010). This adipocytokine is produced in response to several factors, including infection, IL-1, interferon-, and tumor necrosis factor,3 4 5 IL-6 is a central mediator of the acute-phase response and a primary determinant of hepatic production of C-reactive protein.6 7

Although elevated levels of IL-6 have been reported in some chronic inflammatory conditions,2 epidemiological data evaluating the potential role of IL-6 in early atherogenesis are sparse. However, experimental studies indicate that vascular endothelial and smooth muscle cells from normal and aneurysmal arteries produce IL-6,8 9 10 that IL-6 gene transcripts are expressed in human atherosclerotic lesions,11 12 and that IL-6 may have procoagulant effects.13 14 15 Furthermore, prospective studies of apparently healthy16 17 as well as high-risk18 19 20 individuals indicate that elevated levels of C-reactive protein, a potential surrogate for IL-6 activity,21 are associated with first coronary and cerebrovascular events. Finally, elevated levels of IL-6 and other acute-phase proteins have been reported among patients with acute coronary syndromes,22 23 24 25 even among those without overt plaque rupture or acute tissue trauma.26 ( Redker et al., 2000).

Increased IL-6 expression and circulating levels have been associated with a variety of diseases, including metabolic and vascular diseases, such as central obesity, the metabolic syndrome, type 2 diabetes mellitus, atherosclerosis and, in particular, atherosclerotic coronary artery disease [182, 183].

IL-6-together with other cytokines-is a key risk factor for the development of atherothrombotic diseases due to its effect in plaque development and destabilization via release of other proinflammatory cytokines, oxidation of lipoproteins by phospholipases, stimulation of acute phase protein secretion, release of prothrombotic mediators, and activation of MMPs [183, 184]. Moreover, the increased ROS formation by vascular enzyme systems under proinflammatory conditions may play a critical role in the cross talk between IL-6 and other vasoactive substances, such as Ang II and catecholamines [185-187].

IL-6 acts synergistically with thrombopoietin (TPO), other interleukins, and growth factors in promoting the maturation of megakaryocyte precursors [188-192]; actually, in vivo administration of IL-6 to humans increases circulating platelet counts [190, 192]. This effect may explain the association between the increased markers of chronic inflammation and the elevated platelet count in obese women [193]: this phenomenon has been considered prothrombotic, since higher platelet counts are associated with adverse clinical outcomes in patients with acute coronary events [194].

IL-6 influences both vessel wall cells and their progenitors; beyond its effects on resident endothelial cells, IL-6 exerts pro-angiogenic actions by stimulating migration and proliferation of circulating endothelial progenitors [196]. As far as VSMC are concerned, proinflammatory mediators increase in these cells synthesis and release of IL-6 [197]. Additionally, IL-6 exerts specific effects on VSMC: in particular, it is involved in growth factor-dependent VSMC migration, by interplaying with VEGF and TNF-α [198-200], and stimulates VSMC proliferation with PDGF-dependent and -independent mechanisms [201, 202]. These effects explain the clinical observation that increased IL-6 levels both in coronary and systemic circulation are a risk factor for restenosis after angioplasty [203, 204] ( Anfossi et al., 2010).

IL-6 is a circulating cytokine known to be secreted from a number of different cells including activated macrophages and lymphocytes. The biological activities of IL-6 are initiated by binding to a high-affinity receptor complex, consisting of two membrane glycoproteins [10]. The 80 kDa ligand binding component (IL-6R) binds IL-6 with low-affinity, while a second 130 kDa signal-transducing component (gp130), although not binding free IL-6, is required for high-affinity binding of gp80-bound IL-6. The cDNAs for both IL-6R and gp130, have been cloned and sequenced. A soluble form of the IL-6R with a molecular weight of approximately 50 kDa has been found, apparently arising from proteolytic cleavage of the membrane-bound IL-6R. Recombinant soluble IL-6R (IL-6Rs) has been shown to bind IL-6 in solution and to augment the activity of the IL-6 as a result of the binding of the IL-6/IL-6Rs complex to the membrane-bound gp130. It has been suggested that elevated levels of IL-6 are associated with increased production of IL-6Rs. Recently, evidence has been found also for a soluble form of the gp130 receptor, which may have antagonist properties. However, neither the regulation, in-vivo, of soluble receptor release, nor their functional significance, are clearly understood [10] ( Yudkin et al., 2000).

IL-6 might play a key role in the development of coronary disease through a number of different mechanisms; metabolic, endothelial and coagulant. IL-6 increases basal glucose uptake, alters insulin sensitivity, increases the release of adhesion molecules by the endothelium and increases the hepatic release of fibrinogen, as well as having procoagulant effects on platelets. There is a close relationship between circulating concentrations of CRP, IL-6 and TNF-α, with the components of the insulin resistance syndrome - insulin sensitivity, high triglyceride and low HDL-cholesterol concentration, and elevated blood pressure, with a correlation of r=0.52 between a summary score of the two clusters [19]. There is also a significant correlation between these acute phase markers and indicators of endothelial activation. Both IL-6 and TNF-α inhibit lipoprotein lipase and stimulate lipolysis [20], [21] and [22]. Over-expression of TNF-α in adipose tissue of obese subjects is associated with reduced activity of the insulin receptor, perhaps consequent upon abnormal phosphorylation of insulin receptor substrate-1 and of the insulin receptor itself [23]. Whether IL-6 also shares these actions on insulin signalling is currently being investigated, but IL-6 has been found to inhibit glycogen synthesis consequent upon insulin stimulation of isolated hepatocytes [24]. TNF-α is known to influence endothelial cell function [25] and a recent study suggests that IL-6 may also induce endothelial expression of chemokines and adhesion molecules [26]. The effects of these cytokines on triglyceride metabolism might further impair endothelial generation of nitric oxide, consequent upon raised circulating concentrations of non-esterified fatty acids [27] and [28]. Finally, the effect of IL-6 on platelets, fibrinogen concentrations and coagulation [29], and of TNF-α on expression of plasminogen activator inhibitor by hepatocytes, endothelial cells and adipose tissue [30] and [31], will lead to a procoagulant state in such subjects( Yudkin et al., 2003).

It is thus clear that IL-6 is elevated in the presence of systemic infection or inflammation, that elevated IL-6 may induce the raised CRP seen in patients at risk of CHD and that there are several mechanisms by which IL-6 might promote atherogenesis in infection. The question remains as to whether conditions other than inflammation and infection alter IL-6 (Yudkin et al., 2003).

1.1.3 Plasminogen Activator Inhibitor 1

Plasminogen Activator Inhibitor 1 (PAI-1) has a MW of 50 kDa and is a member of the serpin superfamily of proteinase inhibitors 15. Its name pertains to its capacity to inhibit plasminogen activators (PA), including tissue-type plasminogen activator (t-PA) and urokinase-type plasminogen activator (u-PA) and appears to have a major clinical relevance. Their inhibition limits the dissolution of fibrin and consequently clots by the fibrinolytic system in the blood. PAI-1 is known to play a key role in the regulation of the fibrinolytic system. Decreased fibrinolytic capacity has been suggested to accelerate the process of arterial atherogenesis by facilitating thrombosis and fibrin deposition within developing atherosclerotic lesions. Type 1 plasminogen activator inhibitor (PAI-1) is the primary inhibitor of tissue-type plasminogen activator and has been found to be increased in a number of clinical conditions generally defined as prothrombotic such as acute coronary syndromes.5 Moreover, upregulation of PAI-1 expression was demonstrated in human atherosclerotic lesions and inflammatory (pro-atherosclerotic) mediators increased PAI-1 expression in human endothelial cells in culture.6 Taken together, these observations suggest that the atherosclerotic process may involve overexpression of PAI-1, which could contribute to the formation of atherosclerosis (Peng et al., 2008). Therefore, PAI-1 has been proposed as one of the most important in vivo markers of the endothelial cell injury.4

Increased PAI-1 levels have been shown to enhance thrombosis, and antibodies directed against PAI-1 prevented the progression of thrombosis.18-22 Clinical studies have demonstrated an association between high PAI-1 levels and MI or CAD, recurrence of MI, or CVEs in the metabolic syndrome.23-27 Schneiderman et al28 have reported increased PAI-1 gene expression in human atherosclerotic arteries, and there was a clear trend with the degree of atherosclerosis. All of these factors point to the crucial role of PAI-1 in atherothrombosis in humans.18-28 It has been proposed that increased PAI-1 in the vessel wall can promote formation of plaques with lipid-laden cores and thin fibrous caps, which are more prone to rupture.29 Furthermore, PAI-1 deficiency protects against atherosclerotic progression in the mouse carotid artery.30 Recent exciting data demonstrate that transgenic mice that express a stable form of human PAI-1 develop coronary arterial thrombosis.31

Although PAI-1 is known to be synthesized in vascular tissues (including the endothelium), liver and adipose tissue, the source and mechanisms of increased PAI-1 in obesity are incompletely understood. Increased plasma PAI-1 in obesity might be derived directly from the cellular constituents of fat (adipocytes, stromal cells or vascular tissue) or indirectly through the effects of other adipose-derived factors (peptides, cytokines, hormones or lipids) that stimulate local and systemic PAI-1 production. Recent data suggest that PAI-1 contributes directly to the complications of obesity, including coronary arterial thrombi and the development of type 2 diabetes mellitus independent of insulin resistance, and may even influence the accumulation of visceral fat( Taeye et al., 2005).

Plasma PAI-1 is derived from several sources, including the vascular endothelium, adipose tissue and liver. Platelets are known to store large quantities of PAI-1 that are secreted following platelet aggregation, and recent evidence indicates that platelets retain the capacity to synthesize and secrete active PAI-1.). the expression and secretion of PAI-1 by adipocytes, both rodents and humans, is well documented ( Lundgren et al., 1996;Erisson et al., 1998; Cigolini et al., 1999; Mutch et al., 2001). The circulating levels of PAI-1 in obesity and synthesis in WAT is also raised ( Alessi et al., 2000). This has led to the view that the adipose tissue is the major source of elevated PAI-1 levels in the obese (Lundgren et al., 1996;Samad et al., 1996; Alessi et al., 2000). PAI-1 is also an acute-phase response protein, the levels rising in inflammation ( Gabay and Kushner, 1999).

2. Hypotheses

The study proposes that serum/plasma concentrations of 3 adipocytokines, namely interleukin-6 (IL-6), resistin, and plasminogen activating inhibitor (PAI) -1, may have significant differences between patients with and without atherosclerotic CVD disease.

IL-6, a pleiotropic cytokine, is reported to have multiple effects including inflammation and vascular tissue injury (Mohamed-Ali and Pinkney, 1998); and the stimulation of hepatic production of C-reactive protein (CRP) which is a suggested predictor of atherosclerosis; and the modulation of glucose tolerance through regulation of visfatin - an adipocytokine with insulin-mimetic effects which decreases plasma glucose levels (Ronti et al., 2006). Furthermore, high concentrations of IL-6 are predictive of type 2 diabetes and myocardial infarction (MI) (Bastard et al., 2000), which are implicated in atherosclerotic CVD. IL-6 therefore requires further investigation as a potential marker for atherosclerotic CVD in this study.

Resistin is a plasma protein which induces insulin resistance in murine subjects. The use of recombinant human resistin is shown to induce increased expression of mRNA of vascular cell adhesion molecules (VCAM-1), inter-cellular adhesion molecules (ICAM-1), and pentraxin-3 from endothelial cells (Kawanami et al., 2004) resulting in a biochemical fingerprint of dysfunctional endothelium. Significantly, even in asymptomatic patients with a family history of coronary heart disease, plasma resistin levels have been suggested to be predictive of coronary atherosclerosis even after control of other established risk factors (Ronti et al., 2006). Resistin therefore requires further investigation as a potential marker for atherosclerotic CVD in this study.

PAI-1 is an anti-clotting factor which inhibits fibrin clot breakdown and therefore promotes thrombus formation on ruptured atherosclerotic plaques (Alessi et al., 1997). Thus, elevated plasma PAI-1 levels have been linked to atherosclerotic events and particularly coronary artery disease for which it is considered an independent risk factor. Furthermore PAI-1 is increased in hyperglycaemia, obesity and hypertriglyceridaemia (Ronti et al., 2007), all of whom are associated with atherosclerotic CVD. PAI-1 therefore requires further investigation as a potential marker for atherosclerotic CVD in this study.

3. Aims

The study intends to determine the clinical importance of serum IL-6, resistin, and PAI-1, either individually or as combination algorithms, in screening for individuals at marked risk of atherosclerotic cardiovascular disease. The study also intends to determine, where relevant, the diagnostic cut-off levels associated with these adipocytokines. Furthermore, the study will seek to determine which of these adipocytokines is the strongest predictor of atherosclerosis. Comparisons of the predictive values would be made with traditionally employed biomarkers such as CRP. The study also intends to compare variations in serum levels of adipocytokines in ethnically diverse individuals.

4. Methods:

4.1. Samples:

Serum/plasma samples will be obtained from patients of the coronary care unit of Whittington Hospital NHS Trust. Samples for analyses will be residual sera from those collected for routine investigation. The target group are a statistically determined minimum of 90 patients with diagnosed atherosclerosis among whom data will be collected on the presence of obesity, and diabetes mellitus. The control group would be 30 patients without CVD. To identify the population of patients for the study, a query will be run on the Winpath computer system, in the clinical pathology laboratory in Whittington Hospital, for patients with stroke and myocardial infarction (MI). The first patient is to be chosen randomly, and subsequently, every second patient selected till the minimum quota for the dataset is obtained. This process is repeated for the controls. Patients and controls will be fully anonymised using randomly generated numbers from Microsoft Excel. Data and results will not be traced back to the patient. The anonymised samples will be stored in a designated rack at -20oC in the secure clinical biochemistry laboratory of Whittington Hospital.

4.2. ELISA Assays:

Serum/plasma levels of adipocytokines (resistin, PAI-1, and IL-6) will be measured using ELISA kits (direct sandwich enzyme immunoassay, Abnova Corporation). To assay resistin, 100 µl of diluted serum (diluted x3 in buffer, Abnova) is pipetted into wells containing capture antibody and incubated for 1 hour at room temperature in a microplate shaker (300 rpm). Each well is washed with 0.35 ml wash solution and repeated twice. 100 µl of biotin-labelled antibody solution is pipetted into each well and incubated, and washed as previously. 100 µl of Streptavidin-horse radish peroxidase (HRP) conjugate is pipetted into each well and incubated, and washed as previously. 100 µl of substrate solution is added to each well, incubated for 10 minutes, and 100 µl Stop solution added. The absorbance of each well is read using a microplate reader at 450 nm. Wells containing standards are used to produce a standard curve for determining resistin concentration in ng/ml. A similar ELISA procedure is repeated for PAI-1 and IL-6 according to manufacturer instructions (Abnova, UK). PAI-1 and IL-6 concentrations (pg/ml) are determined from absorbances read at 450 nm.

4.3. Automated photometric Assays:

Serum cholesterol, HDL, triglycerides and CRP will be assayed on the automated analyser platform (Roche modular system). The methods will be adaptations from previous works (Sugiuchi et al., 1995; Matsuzaki et al., 1996; Price et al., 1987; Eda et al., 1998; Siedal et al., 1993). CRP will be measured using the Roche Tina-Quant CRP (Latex) turbidimetric kit (CRPLX code 3002039) in conjunction with the Roche/Hitachi Modular PP analyser (leased 2002). Immune complexes formed scatter light, the turbidity of which is measured photometrically at 340 nm. Cholesterol, triglycerides, and HDL assays involve the use of specific kits which lead to the release of H2O2 and subsequently coloured complexes, which are measured photometrically at 525 nm.

4.4 Statistical analyses

Results of the assays will be recorded on work sheet charts (Microsoft excel 2010). Results will be analysed using statistical methods (generated by StatsDirect software version 2.7.8) including box-whisker plots and receiver operator curves (ROC) to identify significant differences in serum/plasma concentrations of adipocytokines (resistin, PAI-1, IL-6) between atherosclerotic CVD and controls, and patterns in pre-major event atherosclerotic-related conditions - diabetes mellitus, obesity, and hyperlipidaemia - and in major atherosclerotic CVD - MI and stroke. Dataset distributions will be analysed for skewness to determine whether means or medians of adipocytokine concentrations should be used to compare differences between test subjects and controls. The relevant 2 sample T-test (comparing means) or Mann-Whitney test (non-parametric data) will be employed. All-pairwise differences using Kruskal-Wallis tests could be performed to see if significant differences of adipocyte concentrations exist between various atherosclerotic-related clinical conditions - diabetes mellitus, obesity, hyperlipidaemia, MI, stroke, and controls. ROC curve analyses would enable comparison of the diagnostic value of potential markers (adipocytokines) and traditional markers (CRP). Promising adipocytokines could then be combined in novel algorithms to evaluate (using ROC curves) whether significant diagnostic advantages are conferred.

4.5 Ethical considerations

Ethical approval is required for the study to be carried out and is expected to be obtained within a period of two months. Patient consent is not required since samples are fully anonymised and are not obtained specifically for the study. Samples for analyses are residual sera deemed surplus to that obtained for routine investigations. Patient confidentiality is assured due to total anonymity. Samples would be labelled using randomly generated numbers obtained from the random function on Microsoft excel. Samples would be stored only for the duration of the study which is due to end within 3 months, and then discarded. To eliminate bias, selection of patients for the study would be randomised. The first is chosen at random, and subsequently, every alternate patient chosen till the minimum quota for the dataset sample size is fulfilled.

5. Benefits of the study

The study would help corroborate the potential relevance of adipocytokines as markers of atherosclerotic cardiovascular disease. The possibility of an early stage predictive risk value for serious and morbidity-related pathology such as MI could be important to help clinicians in diagnosing individuals at risk at a primary preventive stage of the process. The study would also contribute knowledge to the field by determining diagnostic-cut off values between disease and controls, which to date are not available in literature.

2. Aims

This review will focus on the role of adipokines in cardionetabolic risk and explore management options that reduce the levels of adipokines, either directly or via weight loss.

All mentioned biomarkers exert a combined effect on cardiovascular disease [7] so that assessing these markers together is crucial. The aim of this work is to find objective ways for comparing the performance of typical cardiovascular markers represented by corresponding laboratory tests with regard to their performance in diagnosing the cardiovascular risk.

These markers have been dentified as emerging risk factors,1a which could be used as an optional risk factor measurement to adjust estimates of absolute risk obtained using standard risk factors ( Pearson et al., 2003).

Indication of cardiovascular risk is based on laboratory analysis of cardiovascular markers in blood. Assessment of diagnostic performance of traditionally used as well as new cardiovascular markers is the main goal of this paper ( Ballas et al., 2004).

Examine the association of plasma levels of C-reactive peptide (CRP), resistin, interleukin (IL)-6, and PAI, as well as metabolic syndrome, with coronary artery calcification (Qasim et al., 2008).

The objectives of this study were to evaluate leptin, adiponectin and ghrelin concentrations in patients with cardiovascular disease and to correlate these concentrations with measures of disease activity , serum lipid concentrations, measures of insulin resistance and serum homocysteine concentrations ( Al et al., 2007).

The primary aim of this study was to evaluate leptin, adiponectin and ghrelin concentrations in a cohort of patients with known atherosclerotic cardiovascular disease. Additional aims were to correlate these concentrations with measures of disease activity, treatment , serum lipid concentrations, measures if insulin resistance and serum homocysteine ( Al et al., 2009).

The goals of this workshop were to determine which of the currently available tests should be used; what results should be used to define high risk; which patients should be tested; and the indications for which the tests would be most useful. These determinations should assist the clinician in selecting tests judiciously and appropriately and should assist healthcare payers in making decisions about the support of such tests in clinical practice.

To achieve this goal, the workshop set down five objectives:

(1) To review the scientific evidence from diverse sources to examine the association between several inflammatory markers (high-sensitivity C-reactive protein [hs-CRP], serum amyloid A [SAA], white blood cell [WBC] count, fibrinogen, etc) and CVDs, including the strength, consistency, independence, and generalizability of the data.

(2) To consider the clinical chemistry and various assays of inflammatory markers, to identify which may be the best assays to use in identifying persons at risk.

(3) To identify areas in which questions persist in order to foster additional research on inflammatory markers and CVD.

(4) To recommend which tests should be performed for which patients and in which clinical settings, for the purpose of risk stratification, therapeutic monitoring, and other clinical applications, on the basis of the scientific evidence.

(5) To explore the public health implications of an association between inflammatory markers and CVD. ( Pearson et al., 2003).

Another area in need of investigation is the use of combinations of inflammatory markers in the classification of CVD risk. Different analytes might be measured concurrently or sequentially to improve the sensitivity or specificity of the screening process. Another need is to identify markers or combinations of markers with greater specificity for atherosclerotic risk. Current assays are not specific for atherosclerosis and thus are not useful in the setting of other systemic inflammatory or infectious processes ( Pearson et al., 2003).

An objective way for the appropriate selection of the cut-off (critical) value on the axis of a single laboratory test or a linearly combined multicomponent is based on the selection of the maximum of efficiency defined by Eq. (1). The cut-off values for nine cardiovascular markers as well as their optimum linear combinations were determined in this way and are collected in Table 3. ( Balla et al., 2004).

The first aim of this study was therefore to investigate the independent relationships of different adipokines (leptin, adiponectin, tumor necrosis factor-α, resistin, visfatin), and ghrelin, with blood pressure and insulin resistance. The second aim was to evaluate the interrelationships of the adipokines and ghrelin in concert with a range of cardiometabolic markers ( Schutte et al., 2010).

3. Methods

Subjects and samples

Following informed consent 120 serum samples were collected from N number of patients with known atherosclerotic disease. The cohort consisted of N males ( %) and N females ( %) with mean age of _____ years who attended the Coronary Care Unit at Whittington Hospital. This work was approved by the Research Ethics ­­­­_____ ( Al et al., 2009).

Study participants

Hundred and twenty samples from 120 patients with cardiovascular disease and 30 samples from healthy individuals controls were evaluated by ELISA to measure leptin, adiponectin and ghrelin ( Al et al., 2009).Participants were adults with cardiovascular disease 30 to 75 years ( Qasim et al., 2008). Students' t-test was used for analysis. Concentrations of adipocytokines were correlated with disease activity, serum lipids, insulin resistance and homocysteine ( Al et al., 2009).

Evaluated parameters

Study subjects were evaluated in a fasting state at the Whittington Hospital NHS Trust. Plasma levels of PAI, leptin,,,, were measured by enzyme-linked immunosorbent assays.

The CRP levels were assayed as described ( 21) (Qasim et al., 2008).


The following cardiovascular markers were studied: Apo A1-apolipoprotein A1, Apo B-apolipoprotein B, hs-CRP-C-reactive protein determined by a highly sensitive analytical technique enabling determination of low CRP concentrations, HDLc-high density lipoprotein cholesterol, LDLc-low density lipoprotein cholesterol, tChol-total cholesterol, TG-triacylglycerols. In addition, two marker ratios were used: aterogenity index AI=(tChol−HDLc)/HDLc, and the apolipoprotein ratio B/A1=Apo B/Apo A1 ( Balla et al., 2004).

Traditional lipid markers were analysed in a common way by an automatic analyser Hitachi 917 using appropriate diagnostic kits (Roche). For hs-CRP the immunoturbidimetric method was used enabling a highly sensitive analysis. This way of the CRP determination differs from that applied to the CRP inflammation marker where much higher CRP concentration is expected. Altogether 114 patients were investigated and were categorised according to their previous clinical treatment into two classes: 84 with the cardiovascular risk, 30 without the risk [11 and 12] ( Balla et al., 2004).

Several software packages were used for multivariate data analysis (mainly PCA, LDA, cluster analysis and logistic regression) of the respective data sets but mainly STAGRAPHICS Plus ver. 4.0 [18] and SYSTAT ver. 9.0 [19. SYSTAT, ver. 9.0, SPSS Inc., Chicago, IL, USA, 1998.19]. The selection of the cut-off values and construction of the ROC curves were enabled by GraphROC for Windows ver. 2.0 [14], NCSS 2000 [20] and CBstat [21] ver. 4.1.0 ( Balla et al., 2004).

Statistical analysis

Performance of studied laboratory tests was evaluated by using the area below the corresponding receiver operating characteristic (ROC) curve. Application of an objective procedure for the determination of critical values of laboratory tests was based on maximum of efficiency ( Balla et al., 2004).

2.1. Study design and subject selection

The study formed part of the POWIRS (Profiles of Obese Women with the Insulin Resistance Syndrome) study which involved 115 Caucasian women volunteers from the North West Province, South Africa. More detail regarding the methods of this study is described elsewhere [34]. The inclusion criteria were apparently healthy women aged between 19 and 56 years. Subjects were recruited based on their body mass index as measured at the Metabolic Clinic at the University. To ensure a wide range of obesity levels, three groups of women were selected based on guidelines of the Report of a World Health Organization Consultation on Obesity [35]: i) normal range (lean) with BMI: 18.5-24.9 kg/m2 (N = 41); ii) overweight (pre-obese) with BMI: 25-29.9 kg/m2 (N = 32); and iii) obese with BMI ≥ 30 kg/m2 (N = 42). Pregnant and lactating women and those with oral temperatures above 37 °C were excluded.

2.2. Ethical considerations

The study protocol conforms to the ethical guidelines of the Declaration of Helsinki and was approved by the Ethics Committee of the North-West University. All subjects signed an informed consent form prior to inclusion in the study.

2.3. Organisational procedures

All participants were accommodated at a Metabolic Unit Facility. Upon arrival the experimental procedures were explained to them, demographic questionnaires were filled out and anthropometric measurements were taken. All participants received a similar light supper which excluded alcohol and caffeine. From 06:00 in the morning cardiovascular measurements and fasting blood samples were taken.

2.4. Anthropometric measurements

Measurements of height (stature), weight and waist circumferences (WC) were taken of subjects in their underwear with calibrated instruments (Precision Health Scale, A & D Company, Japan; Invicta Stadiometer, IP 1465, UK; Holtain unstretchable metal tape; John Bull calipers). Measurements were done using standard methods [36]. The measurements were taken in triplicate.

2.5. Cardiovascular measurements

One trained researcher took duplicate blood pressure readings by making use of a single-headed stethoscope and a table-model mercury sphygmomanometer (Model ALPK2). Systolic blood pressure (SBP) was based on the appearance of Korotkoff Phase I and diastolic blood pressure (DBP) on Korotkoff Phase V. Appropriate cuff sizes were used for obese women. Afterwards the same researcher monitored cardiovascular variables by making use of the Finometer™ device (FMS, Finapres Medical Systems, Amsterdam, Netherlands) [37] and [38]. This entailed a 7 minute continuous recording of each participant's cardiovascular variables under resting, yet awake, conditions. After the first 2 min, the finger pressure was calibrated with the upper arm (brachial) pressure (i.e. return-to-flow systolic calibration). This optimised the accuracy of the readings taken. The last 2 min of each recording were used to calculate the total peripheral resistance (TPR) and Windkessel arterial compliance (Cw).

2.6. Blood, serum and plasma samples

A fasting blood sample was drawn from the brachial branches using a sterile winged infusion set and syringes. All biochemical analyses were performed later in the laboratory, but blood glucose was directly measured in the Metabolic Unit with an enzymatic method to screen for diabetes mellitus (LifeScan SureStep® Blood Glucose Monitoring System, LifeScan Inc., Milputas Ca 9535, 1995, USA). Serum and plasma samples were prepared according to the appropriate methods, and were immediately stored at −80 °C in the laboratory.

2.7. Biochemical analyses

Serum lipids were measured on a Vitros DT60 II Chemistry System with Vitros DT slides. We measured high sensitivity C-reactive protein (hs CRP) levels with a high sensitivity C-Reactive Protein Kit from Immage® Immunochemistry Systems (Cat. No. 474630, Beckman Coulter, Inc.), and serum TNF-α with a Quantikine High Sensitivity Human TNF-α/TNFSF1A Immunoassay (ELISA) (Cat. No. HSTA00C, R&D Systems, Minneapolis, MN). Plasma glucose was measured with the hexokinase method. Analysis of insulin levels were performed by enzyme immunoassay (BioSource EUROPE S.A. Belgium). Insulin resistance was estimated by the homeostasis model assessment (HOMA-IR index) calculated as the product of fasting glucose and insulin, divided by 22.5. We measured serum leptin with a 125I IRMA kit (Diagnostic Systems Laboratories, Inc., Cat. No. DSL-23100), plasma adiponectin levels with the Human Adiponectin ELISA kit (BioCat GmbH, Heidelberg, Germany), which detects all forms of the adiponectin molecule and total plasma ghrelin levels with a Human 125I RIA kit (Phoenix Pharmaceuticals, Inc., Belmont, CA). Resistin was determined by means of a Resistin Human recombinant EIA kit (Cat. No. EK-028-36, Phoenix Pharmaceuticals, Burlingame, CA) and serum visfatin concentrations with a Human Visfatin (extracellular Nampt / PBEF) ELISA kit by AdipoGen Inc. (Seoul, Korea). ET-1 was determined by means of a 125I RIA kit (AEC Amersham (PTY) LTD, Cat No. RPA 545) and the vWf concentration in the participant's serum was measured with an enzyme-linked immuno-adsorbent assay (ELISA) as described previously [39]. Plasma fibrinogen was measured with a modified method of Clauss [40], using the ACL-200 automated coagulation analyser and reagents from Instrumentation Laboratories (IL) Milan, Italy. PAI-1 was measured with an indirect enzymatic method (Spectrolyse pL, Bipool, Umeå, Sweden, Cat. No. 101201).

2.8. Statistical analysis

Statistica version 8 (StatSoft, Inc., Tulsa, OK) was used to perform the statistical analyses. Variables with a non-Gaussian distribution were logarithmically transformed and the central tendency and spread represented by the geometric mean and the 5th and 95th percentile intervals. The means of the lean, overweight and obese women were compared by analyses of variance (ANOVA) or χ2 test. Single linear regression analyses were used to determine the associations between adipokines and mean arterial blood pressure or insulin resistance (HOMA). We plotted quartiles of adipokines (log) against mean arterial pressure and insulin resistance (HOMA), whilst adjusting for age, body mass index and waist circumference (ANCOVA). Lastly, the obtained data were subjected to factor analyses. The main applications of factor analytic techniques are to reduce the number of variables and to detect structure in the relations between variables. Factor analysis is thus applied as a data reduction or structure detection method [41] I.T. Joliffe and B.J. Morgan, Principal component analysis and exploratory factor analysis, Stat Methods Med Res 1 (1992), pp. 69-95. Full Text via CrossRef | View Record in Scopus | Cited By in Scopus (97)[41]. It is therefore a suitable technique to determine the interrelationships of adipokines with known cardiometabolic risk markers. The number of factors to be extracted is determined by using Kaiser's criterion, which chooses only factors explaining more than the average variance of factors (which is always one). Only factors that have variances explained (also called eigenvalues) > 1 were extracted. Variables with factor loadings ≥ 0.30 were used for interpretation [42]. The varimax raw rotation method was chosen (Schutte et al 2010).