Coronary heart disease (CHD) is an extremely important medical and social issue. This disease is currently one of the leading causes of death and disability worldwide [1].

Acute coronary syndrome is often the first symptom of CHD. Intravascular thrombi are formed on the surface of a damaged atherosclerotic plaque, which leads to the development of myocardial infarction (MI) [2]. The median percent stenosis of the infarct-related artery is 48 % [3]. Thus, patients with unstable plaques can be spared angina and other myocardial ischemia symptoms, but are very likely to develop acute MI. In case the atherosclerotic plaque and CHD develop gradually, stable effort angina (SEA) often becomes the first manifestation of the disease.

The mechanism of unstable atherosclerotic plaque formation has not been fully studied. Some studies have shown that T-cadherin has an important role in the development of atherosclerosis and CHD [4, 5, 6, 7]. T-cadherin is a glycosylphosphatidylinositol-anchored protein; it belongs to the cadherin superfamily and is a receptor for low density lipoproteins (LDL) [8] and high molecular weight adiponectin, a hormone secreted by adipose tissue [9]. Many works describe the antiatherosclerotic effects of adiponectin resulting from the increased synthesis of high density lipoproteins in the liver, the reduction of cholesterol concentration in the atherosclerotic plaque [10, 11, 12] and the suppression of macrophage-to-foam-cell transformation [13]. M. M. Joosten et al. showed that low adiponectin was associated with atherosclerosis development: reduced adiponectin levels in blood serum correlated with the presence of multiple atherosclerotic vascular lesions [14, 15]. By contrast, X. J. Cai et al. demonstrated that adiponectin suppresses proliferation, migration and transformation of adventitial fibroblasts [16], which possibly causes cap thinning and increases the risk of MI. T-cadherin also functions as an LDL receptor [8, 17] and thus contributes to the build-up of an unstable atherosclerotic plaque independently of adiponectin.

Some studies showed that single nucleotide polymorphisms in T-cadherin gene (CDH13) can affect a diponectin concentrations in blood and thus be a part of the mechanism of cardiovascular disorder development. However, there are almost zero data on the CDH13 polymorphism association with CHD and MI. For this work we have selected four single nucleotide polymorphisms in CDH13 gene and investigated the connection between them and both CHD development and symptoms indicative of the disease onset. It was established that rs12051272 (G→T) and rs4783244 (G→T) polymorphisms [18, 19] are associated with the adiponectin level changes in blood serum. The single nucleotide polymorphism rs12444338 (G→T) is related to the changes in T-cadherin gene promoter activity [20] and to the carotid intima-media thickness [21], which indicates its possible impact on the atherogenesis. No similar data were obtained in relation to rs11646213 (А→Т) polymorphism [19, 22]; however, allele A is associated with the reduced risk of arterial hypertension (AH) and the increased risk of metabolic syndrome development [22, 23]. All polymorphisms studied in this work are associated with blood serum lipid levels [22, 24, 25, 26].

METHODS

The study enrolled 285 men aged 26 to 55. Blood samples and clinical data were obtained from the biobank of the Faculty of Fundamental Medicine of Lomonosov Moscow State University. All patients signed the informed consent as required by the Declaration of Helsinki. The control group consisted of 99 individuals: military air forces pilots without arterial hypertension, dyslipidemia and CHD signs according to cardiac stress test results. The group of patients with CHD included 186 individuals, with the age of onset being below 55. Based on the symptoms accompanying the disease onset, two subgroups were formed. For the first subgroup (n = 79), the inclusion criteria was SEA without MI confirmed by cardiac stress test or coronary angiography. The second subgroup (n = 107) included men in whom CHD first manifested itself as a clinically, laboratorially (elevated levels of myocardial necrosis markers) and instrumentally (electrocardiography, echocardiography, radionuclide diagnostics) confirmed MI without prior effort angina. Coronary angiography data were not used as a criterion for MI diagnosis; however, coronary angiography was performed on the patients with MI for deciding on the further treatment when the connection between MI and coronary atherosclerosis was not certain. Glucose tolerance defects and diabetes mellitus were exclusion criteria for all groups.

Patients were diagnosed with AH if their systolic blood pressure was higher than 140 mmHg and diastolic blood pressure was higher than 90 mmHg, or if they were undergoing the antihypertensive therapy. Patients were diagnosed with dyslipidemia if total blood cholesterol was over 5.3 mmol/l, LDL was over 3.0 mmol/l, or if patients were undergoing the antihyperlipidemic therapy at the time of CHD onset. Patients with body mass index over 30 were considered obese. For this study we used the data obtained from the first medical examination at the time of CHD diagnosis.

Genomic DNA was extracted using QIAamp DNA Blood Mini Kit (QIAGEN, Germany) and QIAcube robotic workstation (QIAGEN, Germany) for sample preparation of venous blood stabilized by EDTA. Genotyping was performed using TaqMan SNP Genotyping Assays (Applied Biosystems, USA).

For qualitative characteristics, the significance of differences between the groups was assessed by Yates chi-squared test. Distribution of qualitative characteristics was evaluated by Shapiro–Wilk test. Characteristics with near normal distribution were assessed using Student’s t-test; other qualitative characteristics were assessed by Mann–Whitney U-test. In all cases the difference was interpreted as statistically significant with p < 0.05. Genotyping data were analyzed using SNPStats software. To assess the probability of disease development with different genotypes, odds ratio (OR) and the corresponding 95 % confidence interval (CI) were calculated. Akaike information criterion (AIC) was used to detect the inheritance pattern (codominant, dominant, recessive, superdominant and log-additive) that best matched the obtained results [27].

RESULTS

Major risk factors and their prevalence in the individuals enrolled in the study are presented in tab. 1 and tab. 2. Differences between the group of patients with CHD and the controls based on the prevalence of major risk factors and age were accounted for in the mathematical models describing the obtained results. At the same time, no significant differences were observed in the prevalence of major risk factors of cardiovascular diseases between the subgroups of patients.

No statistically significant difference was found in the frequencies of different genotypes while comparing the controls with the group of patients who had CHD, and while comparing the controls with each of subgroups of patients who had stable effort angina and prior myocardial infarction.

However, while comparing the controls with the subgroup of patients with SEA disregarding such traditional risk factors as age, obesity, smoking, dyslipidemia and AH, differences in the frequencies of rs12051272 and rs11646213 polymorphisms were detected (see tab. 3, tab. 4).