Introduction
Despite cardiovascular mortality trend gradually decreases, coronary heart disease still remains one of the most frequent causes of death, especially in developed countries. The reduction in coronary heart disease mortality rates is most indicated in Western countries and is connected either with primary prevention strategies implemented by authorities and health care professionals, or improvements in medical treatment [1–3]. The amount of deaths caused by coronary heart disease has decreased since 1980’s in these countries. Statistical data concerning Eastern Europe are more differentiated. In some countries, such as Poland, Czech Republic, Slovakia, Hungary and Slovenia the decline in coronary heart disease mortality can be observed since the beginning of economic and market transformation in 1990’s, while in other countries, such as Russia, Bulgaria, and Romania cardiovascular death rates have not significantly changed and still remain high [2]. The reduction in total cholesterol plasma level, such as blood pressure values lowers the risk of cardiovascular death, while diabetes prevalence, body mass index and smoking are positively correlated with coronary disease mortality rate [1, 3]. Furthermore, essential changes in food consumption, such as reduced animal fat intake and increased consumption of n-3 fatty acids results in recent decline of cardiovascular deaths prevalence [2]. Coronary heart disease is the important manifestation of atherosclerosis, however, it is known that atherosclerotic lesions may also form in arterial vessels in other locations, thus leading to numerous complications, such as brain stroke, aortic aneurysm formation, peripheral arterial disease, abdominal angina, or renal failure.
It has been proved that endothelial dysfunction is the early stage of atherosclerosis development. The endothelium is the internal layer of blood vessels, that plays crucial role in vascular tone regulation by the secretion of vasodilators, such as NO, prostacyclines and vasoconstrictors (angiotensin, endotelin-1, tromboxane A2 and superdioxide anion). Moreover, the endothelium prevents from thrombus forming due to the synthesis and secretion of anticoagulative substances, such as antithrombin III, tissular factor inhibitor, and protein S, platelets antiadherents (NO and prostacyclin), and fibrinolitic factors (tissue plasminogen activator), which in healthy people outweighs endothelial synthesis and secretion of procoagulative substances (von Willenbrand factor, fibronectin and thrombospondine). In the presence of atherosclerosis risk factors, the balance between different endothelium actions is disrupted. Such status, called endothelium dysfunction, comprises not only reduced vasodilatating and anticoagulative endothelial actions, but also enhanced proinflammatory molecules synthesis, that enables leucocytes migration into the intima [4–6]. Moreover, recent findings suggest that endothelial dysfunction has an impact on energy generation in mitochondria. It has been shown that disrupted endothelium functions result in the Krebs cycle inhibition and enhanced glycolytic pathway of pyruvate usage, similarly to the hypoxia conditions, and due to it the Krebs cycle inhibition seems to be an early marker of endothelium dysfunction [7]. One of the Krebs cycle intermediates is α-ketoglutarate, which is subsequently converted in mitochondria to succinyl-CoA by α-ketoglutarate dehydrogenase [8]. There is growing evidence that cardiovascular risk factors not only disrupt endothelium functions, but also enhance the production of reactive oxygen species (ROS) by either endothelium or located in blood vessel walls leucocytes. Oxidative stress, described as an imbalance between reactive oxygen species (ROS) production and elimination, in favor the former, is known to be characteristic to diabetes, hypertension and atherosclerosis. On the other hand the level of oxidative stress may be influenced by the lifestyle modification. According to recent data people, who regularly perform aerobic and anaerobic exercises, have lower levels of blood oxidative stress biomarkers than people avoiding training [9]. Excessive ROS production not only damages proteins and DNA, but also results in lipids peroxidation. It has been proved that circulating oxidized low-density lipoproteins (LDL) enable foam cells formation in atherosclerotic plaques. Furthermore, both ROS and oxidized LDL enhance disruptions in mitochondrial processes [4, 6, 10, 11]. Excessive production of ROS leads to the apoptosis of either vascular smooth muscle cells, or macrophages in atherosclerotic lesions, and thus results in atherosclerotic plaques rupture [12]. The destabilization of atherosclerotic lesions enables thrombus forming, which rapidly limits the flow of blood, produces acute heart ischemia symptoms and leads to myocardial infarction. Ischemia affects processes of energy generating in heart tissue mitochondria by triggering anaerobic metabolic pathways, such as anaerobic glycolysis and fatty acids utilization, enhanced glucose uptake and the decrease of heart muscle contractility. Moreover, it has been established that ROS productions increases rapidly during ischemia, such as after the reperfusion [13, 14].
Located in mitochondrial matrix α-ketoglutarate is known to be an intermediate in the Krebs cycle, while the origin and functions of plasma α-ketoglutarate have not been completely established yet. According to the concept of anaplerosis and cataplerosis, some of the Krebs cycle metabolites may pass through mitochondrial and cell membranes, and due to it excessive amounts of the Krebs cycle intermediates can be removed from cells (kataplerosis), while some other substances can be used to restore necessary concentrations of intermediates (anaplerosis). One of these substances is glutamate, which is converted to α-ketoglutarate in reactions catalysed by glutamate dehydrogenase and aminotransferases [8]. However, the issue of possible links between plasma levels of α-ketoglutarate and atherosclerosis in people still needs further investigations. The aim of the study was to evaluate the influence of cardiac ischemia on plasma concentrations of α-ketoglutarate in people with stable, symptomatic coronary heart disease.
Material and methods
The study group included 53 men, aged 42–87 years, with coronary heart disease confirmed in coronarography, who were admitted to the hospital due to persistent angina despite pharmacological treatment, without elevated cardiac enzyme blood level. The control group included 20 healthy men aged 56–70 years. The study was approved by the local Ethic Committee. Patient blood samples were collected in the morning, after 8 hours of fasting, in the second day of hospitalization, and control blood samples were also obtained in the morning, after 8-hour fasting period. Blood samples were collected for EDTA, with the use of Sarstedt’s Microvette Capillary Blood Collection Systems, spun at 5 thousands of revolutions for a 10 minutes and kept frozen in -25oC until further analysis. Subsequently plasma samples were defrosted and deproteinised by filtration through 10 kDa molecular weight cut-off filters (Pall Life Sciences, Ann Arbor, MI, USA) for 2 hours at 14 thousands of revolutions. Concentrations of α-ketoglutarate in plasma samples were determined using an high-performance liquid chromatography (HPLC) system, that consisted of an LC-10AD isocratic pump (Shimadzu, Kyoto, Japan), a Basic Marathon Plus autosampler (Spark Holland, Emmen, Netherlands), a Mistral Column Oven (Spark Holland) and a SPD-10A VP UV detector (Shimadzu). Samples were separated on an RSpak KC-811 column (Shodex, Kawasaki, Japan) using 25 mM perchloric acid as a mobile phase (ISO-grade, Sigma Aldrich, Stockholm, Sweden) with a flow rate of 0.6 ml/min for 100 minutes. Separation was carried out at 50°C and α-ketoglutarate was detected at a wavelength of 210 nm. The system was calibrated against a standard series of α-ketoglutarate dissolved in Millipore grade H2O which was then used to calculate plasma levels of α-ketoglutarate.
Standard blood samples were collected for EDTA, serum and Lithium-heparin and spun at 2,5 thousands of revolutions for 10 minutes to obtain data about blood count parameters, such as plasma concentrations of glucose, total cholesterol, low-density lipoproteins (LDL), high-density lipoproteins (HDL), triglycerides, sodium, potassium, chloride, urea, creatinine, bilirubin and transaminases. Subsequently samples analysis was performed on the Cobas Integra System (Roche).
Patients’ height and weight were estimated the same day that blood samples were collected. Body mass index (BMI) values were evaluated using BMI formula. Glomerular filtration rates (GFR) values were calculated using Modification of Diet in Renal Disease formula.
The statistical analysis was conducted with Sigma Plot 11.0 software (Systat Software, Inc.). The distribution of the variable was estimated using Shapiro-Wilk test. Student’s T-test was used to verify differences between both populations in case of data with normal distribution, while Mann-Whitney test was applied to compare data with abnormal distribution. Results were considered statistically significant if the p-value was below 0.05 (Tab. I).
Table 1. Patients’ characteristic in both groups
Tabela 1. Charakterystyka pacjentów obu grup
Parameter/ Parametr | Study group | Control group |
Age (years)/Wiek (lata) | ||
Range/Zakres | 42−87 | 56−70 |
Mean ± SD/Średnia ± SD | 70.9 ± 10.5 | 65.5 ± 4.7 |
Number of patients/Liczba pacjentów | 53 | 20 |
BMI value [kg/m2]/Wartość BMI [kg/m2] | ||
Range/Zakres | 23.0−49.0 | 23.0−36.0 |
Mean ± SD/Średnia ± SD | 30.7 ± 5.6 | 29.0−3.9 |
Red blood cell count [mln/mm3]/Liczba erytrocytów [mln/mm3] | ||
Range/Zakres | 3.0−5.0 | 4.02−4.27 |
Mean ± SD/Średnia ± SD | 4.2 ± 0.5 | 4.3 ± 0.1 |
Hemoglobin (Hb) concentration [g/dl]/Stężenie hemoglobiny (Hb) [g/dl] | ||
Range/Zakres | 9.3−17.0 | 12.1−13.6 |
Mean ± SD/Średnia ± SD | 12.7 ± 1.6 | 13.3 ± 0.6 |
Mean cell volume [fl]/Średnia objętość erytrocytu [fl] | ||
Range/Zakres | 60.0−107.0 | 86.0−97.0 |
Mean ± SD/Średnia ± SD | 93.3 ± 6.0 | 92.3 ± 3.9 |
White blood cell count [103/mm3]/Liczba leukocytów [103/mm3] | ||
Range/Zakres | 3.5−10.1 | 5.9−10.8 |
Mean ± SD/Średnia ± SD | 7.0 ± 1.8 | 7.8 ± 1.3 |
Platelet count [103/mm3]/Liczba płytek krwi [103/mm3] | ||
Range/Zakres | 71.00−408.0 | 150.0−340.0 |
Mean ± SD/Średnia ± SD | 241.6 ± 77.9 | 252.6 ± 55.7 |
Glucose plasma concentration [mg/dl]/Stężenie glukozy w osoczu [mg/dl] | ||
Range/Zakres | 71.0−99.0 | 86.0−98.0 |
Mean ± SD/Średnia ± SD | 88.0 ± 6.23 | 93.9 ± 4.0 |
Urea plasma concentration [mg/dl]/Stężenie mocznika w osoczu [mg/dl] | ||
Range/Zakres | 23.0−45.0 | 23.0−39.0 |
Mean ± SD/Średnia ± SD | 40.0 ± 9.5 | 33.0 ± 5.0 |
GFR value [ml/min/1.73 m2]/Wartość GFR [ml/min/1,73 m2] | ||
Range/Zakres | 60.0−116.0 | 60.0−79.0 |
Mean ± SD/Średnia ± SD | 74.3 ± 12.7 | 65.0 ± 4.3 |
Total cholesterol plasma concentration [mg/dl]/Stężenie cholesterol całkowitego w osoczu [mg/dl] | ||
Range/Zakres | 86.0–303.0 | 143.0–253.0 |
Mean ± SD/Średnia ± SD | 165.7 ± 39.5 | 180.4 ± 27.7 |
LDL plasma concentration [mg/dl]/Stężenie cholesterolu frakcji LDL w osoczu [mg/dl] | ||
Range/Zakres | 42.0–220.0 | 86.0–134.0 |
Mean ± SD/Średnia ± SD | 97.3 ± 31.9 | 108.0 ± 15.0 |
HDL plasma concentration [mg/dl]/Stężenie cholesterolu frakcji HDL w osoczu [mg/dl] | ||
Range/Zakres | 24.0–77.0 | 32.0–50.0 |
Mean ± SD/Średnia ± SD | 43.3 ± 10.7 | 42.2 ± 4.2 |
Triglycerides plasma concentration [mg/dl]/Stężenie triglicerydów w osoczu [mg/dl] | ||
Range/Zakres | 50.0–308.0 | 110.0–170.0 |
Mean ± SD/Średnia ± SD | 125.5 ± 50.7 | 134.5 ± 16.0 |
Sodium plasma concentration [mmol/l]/Stężenie sodu w osoczu [mmol/l] | ||
Range/Zakres | 130.0–146.0 | 131.0–142.0 |
Mean ± SD/Średnia ± SD | 139.4 ± 3.0 | 138.2–2.6 |
Potassium plasma concentration [mmol/l]/Stężenie potasu w osoczu [mmol/l] | ||
Range/Zakres | 3.7–5.4 | 3.8–5.0 |
Mean ± SD/Średnia ± SD | 4.5 ± 0.4 | 4.4 ± 0.4 |
Chloride plasma concentration [mmol/l]/Stężenie chlorków w osoczu [mmol/l] | ||
Range/Zakres | 92.0–110.0 | 98.0–110.0 |
Mean ± SD/Średnia ± SD | 103.1 ± 3.5 | 102.9 ± 3.7 |
SD (standard deviation) – odchylenie standardowe; BMI (body mass index) – wskaźnik masy ciała; GFR (glomerular filtration rate) – wskaźnik przesączania kłębuszkowego; LDL (low-density lipoprotein) – lipoproteiny o niskiej gęstości; HDL (high-density lipoprotein) – lipoproteiny o wysokiej gęstości
Results
Patients with stable coronary heart disease, admitted to the hospital due to persistent angina despite treatment, without concomitant cardiac enzymes elevation, had significantly lower α-ketoglutarate plasma concentrations (0.91 ± 0.29 ng/ml) compared to healthy controls (1.07 ± 0.14 ng/ml), p < 0.05. There were no statistically significant differences in other examined parameters between groups (Fig. I).
Alpha-ketoglutarate plasma level in patients with coronary heart disease (study group) and health people (control group).
Figure 1. Plasma α-ketoglutarate level in patients with coronary heart disease (study group) and health people (control group)
Rycina 1. Stężenie α-ketoglutaranu w osoczu pacjentów z chorobą wieńcową (grupa badana) i osób zdrowych (grupa kontrolna)
Discussion
Our study revealed differences in α-ketoglutarate levels between healthy people and patients with stable, symptomatic coronary heart disease. Inflammatory processes located in arterial walls of patients with atherosclerosis significantly disrupt tissue metabolism, which leads to the increase of ROS formation. Results of experimental studies suggest that citric acid cycle disturbances are early indicators of endothelial dysfunction. Chronic decrease of endothelial NO synthase activity in mice leads not only to the increase of endothelial dysfunction markers concentrations, such as sICAM-1 (soluble intracellular adhesive molecule-1), VCAM-1 (vascular adhesive molekule-1) and MMP-9 (matrix metalloproteinase-9), but also selective inhibition of aconitase activity, such as the decrease of mitochondrial mass. These results suggest that endothelial dysfunction may lead to the inhibition of Krebs cycle enzymes activity and it may switch cellular metabolism to obtain energy from pyruvate through glycolysis, similarly to cellular metabolism under hypoxia conditions [15]. It has been also proved that α-ketoglutarate dehydrogenase, which catalyses the convertion of α-ketoglutarate into succinylo-Co-A reveals disturbed activity under significant level of oxidative stress. The synthesis of succinylo-CoA, which is catalysed by α-ketoglutarate dehydrogenase leads under physiological conditions to the prodyction of NADH, such as supplies respiratory chain with electrons. However in case of increased ROS production α-ketoglutarate dehydrogenase decreases the synthesis of NADH and may also act as a source of ROS when NADH/NAD+ ratio is increased [16].
Mitochondrial dysfunction may lead to further increase of ROS and RNS (reactive nitrogen species) generation, which enhances inflammatory processes located in arterial walls, decreases the activity of endothelial NO synthase, such as deepens endothelial dysfunction and consequently enables atherosclerotic plaques formation in blood vessel walls. Inflammatory cytokines, such as tumor necrosis factor-α (TNF-α) are proved to enhance macrophages NADPH oxidase activity, which results in the increase of ROS production and further disturbances in mitochondrial functions [17]. Experimental data suggest that NO may influence mitochondrial oxidative stress through peroxisome proliferators-activated receptor γ coactivator 1-γ (PGC-1γ). It has been proved that endothelial NO synthase knockout mice reveal decreased levels of PGC-1γ, such as impaired gene expression of enzymes involved in antioxidant defence, such as catalase, superoxide dismutase, peroxiredoxins III and V, thioredoxin 2 and thioredoxin reductase [18]. Results of experimental studies mentioned above suggest possible links between evoked by oxidative stress citric acid cycle disturbances, endothelial dysfunction and inflammatory processes located in vascular walls. However, there are no clinical data available that could verify these hypotheses.
The other experimental model that investigates the influence of enhanced ROS generation on citric acid cycle may be ischemia and reperfusion conditions. Results of these studies also confirm the link between excessive ROS production and disrupted the Krebs cycle flux. The treatment of isolated rat heart mitochondria with hydrogen peroxide results in significant inhibition of enzymes involved in the citric acid cycle, such as α-ketoglutarate dehydrogenase, succinate dehydrogenase and aconitase [18]. Moreover, the treatment of isolated nerve terminals with hydrogen peroxide revealed that aconitase is most sensitive to inhibition by free radicals, while α-ketoglutarate dehydrogenase is inactivated partially only by higher concentrations of hydrogen peroxide. The decrease of glutamate content in nerve terminals was observed in conditions of aconitase activity inhibition, which suggests, that glutamate fuels the citric acid cycle when aconitase is inactivated, and the generation of NADH remains unaltered while α-ketoglutarate dehydrogenase inactivation at higher concentrations of hydrogen peroxide limits the amount of NADH available for the respiratory chain [19]. The inhibition of aconitase activity leads to the decrease of isocitrate content, which consequently limits the production of other intermediates, including α-ketoglutarate. The level of oxidative stress has not been established in our study. However, it is possible, that ROS generation in patients with cardiac ischemia was great enough to inhibit aconitase activity, but not sufficient to limit the activity of α-ketoglutarate dehydrogenase, thus leading to the decrease of α-ketoglutarate plasma concentrations observed in this study. Another experiment with in vivo animal model of coronary occlusion/reperfusion confirmed that aconitase and α-ketoglutarate dehydrogenase are most susceptible to inactivation caused by ROS [20]. On the contrary, proteomic analysis of canine model of ischemia-reperfusion injury followed by acute heart failure showed that the amount of isocitrate dehydrogenase subunit α, the enzyme, which converts isocitrate into α-ketoglutarate, is significantly increased in reperfused ischemic heart tissue zone [21]. Data suggest that the Krebs cycle enzymes have different sensitivity to individual ROS. The incubation of rat heart mitochondria with hydrogen peroxide, hydroxyl radical and superoxide anion revealed that aconitase activity is limited particularly by superoxide anion, while α-ketoglutarate dehydrogenase is more sensitive to hydrogen peroxide and hydroxyl radical [22]. Furthermore, some findings suggest that the Krebs cycle enzymes susceptibility to inactivation by ROS increases with age. It has been shown that during the reperfusion period, α-ketoglutarate dehydrogenase activity is inhibited in higher degree in heart tissue isolated from older rats than senescent ones [23]. Another study revealed that ischemia leads to the stimulation of glutamate dehydrogenase and glutamate-oxaloacetate-transaminase activity in brain tissue of aged rats in compare to adolescent ones. Reactions catalyzed by these two enzymes may led to the formation of α-ketoglutarate [24], which may partially balance the decrease in α-ketoglutarate content caused by inhibited aconitase activity. There is a lack of data about these enzymes activity in aged people, however the population in this study was too small to reveal possible differences in α-ketoglutarate plasma level that depend on patients age.
Conclusions
Patients with myocardial ischemia have lower plasma concentrations of α-ketoglutarate comparing to healthy controls.
The decrease of plasma α-ketoglutarate concentrations in these patients may be a consequence of the Krebs cycle disruption due to the influence of endothelial dysfunction and inflammatory processes involved in the development of atherosclerosis, however further investigations are required.
Acknowledgement
We thank dr Janusz Dubejko for help in the study organizing.