Introduction: The enzyme 11β-hydroxysteroid dehydrogenase type 1 (11β-HSD1) catalyzes the conversion of the hormonally inactive cortisone to active cortisol, thus facilitating glucocorticoid receptor activation in target tissues. Increased expression of 11β-HSD1 in adipose tissue has been associated with obesity and insulin resistance. In this study, we investigated the association of two 11β-HSD1 gene (HSD11B1) polymorphisms with the metabolic syndrome (MetS) and its characteristics in the Bosnian population. Materials and methods: The study included 86 participants: 43 patients diagnosed with MetS and 43 healthy controls. Subjects were genotyped for two HSD11B1 gene polymorphisms: rs846910: G>A and rs45487298: insA, by the high resolution melting curve analysis. Genotype distribution and an influence of genotypes on clinical and biochemical parameters were assessed. Results: There was no significant difference in the mutated allele frequencies for the two HSD11B1 gene polymorphisms between MetS patients and controls. In MetS patients, no significant associations between disease-associated traits and rs45487298: insA were found. Regarding rs846910: G>A variant, heterozygous patients (G/A) had significantly lower systolic (P = 0.017) and diastolic blood pressure (P = 0.015), lower HOMA-IR index (P = 0.011) and higher LDL-cholesterol levels (P = 0.049), compared to the wild-type homozygotes. In the control group, rs45487298: insA polymorphism was associated with lower fasting plasma insulin levels (P = 0.041), lower homeostasis model assessment insulin resistance (HOMA-IR) index (P = 0.041) and lower diastolic blood pressure (P = 0.048). Significant differences between rs846910: G>A genotypes in controls were not detected. Haplotype analysis confirmed the association of rs45487298: insA with markers of insulin resistance in the control subjects. Conclusions: Our results indicate that a common rs45487298: insA polymorphism in HSD11B1 gene may have a protective effect against insulin resistance.

Aim: To study correlation of IgE level and C-reactive protein (CRP) for exacerbation of the disease in asthmatic patients. Methods: Asthmatic subject were examined for achieving of asthma control according to GINA recommendation. Numbers of exacerbation of asthma during one month were analyzed. The patients were followed in six month period (since first January to 30th of Jun. Average monthly days of exacerbations was calculated. IgE level in the blood was measured using Enzyme-linked Immunoassay (ELISA), and CRP was measured by immunotubidimetry. Assessment of asthma control was considered using Asthma Quality of Life Questionnaire (AQLQ). Results: The study includes 63 patients with asthma. Average level of IgE was 674 IU/mL (SD 167), range 56-3785 IU/mL, 1 IU=3,2 ng; average level of CRP was 16,4 mg/mL (SD 6,3), range 5-48; Average number of days in exacerbation during one month was 3,6 (SD 2,4), and varied from zero, patients with no exacerbation, to 21. Using test of multiple correlation it was shown statistical significant correlation (level p<0,05) between IgE and CRP from one side, and number of days with exacerbation from the other. Patients with higher level of CRP were most likely to have exacerbation, than those with higher level of IgE. AQLQ was worse in those with higher level of CRP, than in those with higher level of IgE. Conclusion: In this study CRP was shown as stronger predictor of asthma exacerbation and worse quality of life than total IgE level in asthmatic subjects.

This is the first study performed in population from Bosnia & Herzegovina (BH), in which we analysed a significance of genetic variations in drug-metabolising enzyme, cytochrome P450 (CYP), in pathogenesis of Type 2 diabetes. We have determined allele frequencies for CYP2C9*2, CYP2C19*2, and CYP2D6*4 in diabetic patients and nondiabetic controls. Genomic DNA was extracted from blood samples collected from 37 diabetic and 44 nondiabetic subjects. A real-time polymerase chain reaction was used for the detection of specific CYP polymorphisms, with the application of the specific TaqMan® SNP genotyping tests (Applied Biosystems). Interestingly, results from this study have demonstrated that frequencies of CYP2C19*2 and CYP2D6*4 variants were in line, while frequency of CYP2C9*2 polymorphism seemed to be lower in this sample of BH population as compared to the Caucasians genotype data. Furthermore, no significant difference in allele frequencies for CYP2C9*2, CYP2C19*2, and CYP2D6*4 was demonstrated between diabetic and nondiabetic subjects. Thus, results form this study seem to indicate no relationship between CYP2C9, CYP2C19, and CYP2D6 genotype and diabetes susceptibility in Bosnian population. This in part may reflect a limited study population included in our study and would require larger cohorts to reveal potential relationships between analysed CYP genetic variants and diabetes risk. In addition, it would be pertinent to further explore possible effects of CYP genetic variations on therapeutic and adverse outcomes of oral antidiabetics, which might be the key in optimising therapy for individual patient with Type 2 diabetes.

Recent studies have introduced serum uric acid (UA) as a potential risk factor for developing diabetes, hypertension, stroke, and cardiovascular diseases. The value of elevated levels of UA in serum as a risk factor for diabetes development is still under scrutiny. Recent data suggest that clearance of UA is being reduced with increase in insulin resistance and UA as a marker of prediabetes period. However, conflicting data related to UA in serum of patients with Type 2 diabetes prompted us to study the urine/serum ratio of UA levels (USRUA) in these patients and healthy controls. All subjects included in the study were free of evidence of hepatitis B or C viral infection or active liver and kidney damage. Patients receiving drugs known to influence UA levels were also excluded from this study. Analysis of glucose and uric acid were performed on Dade Behring analyzer using standard IFCC protocols. Interestingly, our data demonstrated about 2.5 fold higher USRUA values in diabetic patients as compared to control subjects. Furthermore, there was a trend of correlation of USRUA value with the blood glucose levels in diabetic patients, which was more prominent in diabetic men than in women. With aging, levels of uric acid increased in serum of diabetic patients, and this effect was also more profound in male than in female diabetics. In conclusion, this study showed significantly elevated USRUA levels in patients with Type 2 diabetes, a negative USRUA correlation with the blood glucose levels in diabetic patients, and an effect of sex and age on the uric acid levels. Since literature data suggest a strong genetic effect on UA levels, it would be pertinent to perform further, possibly genetic studies, in order to clarify gender and ethnic differences in UA concentrations.