doiSerbia

The correlation between metabolic syndrome quantification scores and numerous laboratory parameters related to this syndrome

Srećković Branko (Clinical Center “Bežanijska kosa”, Belgrade, Serbia)
Mrdović Igor (Clinical Centre of Serbia, Clinic for Emergency Internal Medicine, Belgrade, Serbia + University of Belgrade, Faculty of Medicine, Belgrade, Serbia)
Soldatović Ivan (University of Belgrade, Faculty of Medicine, Institute for Medical Statistics and Informatics, Belgrade, Serbia)
Resan Mirko (Miltary Medical Academy, Clinic for Ophthalmology, Belgrade, Serbia + University of Defence, Faculty of Medicine of the Military Medical Academy, Belgrade, Serbia)
Janeski Nenad (Clinical Centre Zemun, Belgrade, Serbia)
Čolak Emina (Clinical Centre of Serbia, Institute of Medical Biochemistry, Belgrade, Serbia)
Janeski Hristina (University Childrens Hospital, Belgrade, Serbia)
Šumarac-Dumanović Mirjana (University of Belgrade, Faculty of Medicine, Belgrade, Serbia + Clinical Centre of Serbia, Clinic for Endocrinology, Diabetes and Metabolic Diseases, Belgrade, Serbia)
Joković Miloš (University of Belgrade, Faculty of Medicine, Belgrade, Serbia + Clinical Centre of Serbia, Clinic for Neurosurgery, Belgrade, Serbia )
Ivanović Nebojša (Clinical Center “Bežanijska kosa”, Belgrade, Serbia + University of Belgrade, Faculty of Medicine, Belgrade, Serbia)
Gačić Jasna (Clinical Center “Bežanijska kosa”, Belgrade, Serbia + University of Belgrade, Faculty of Medicine, Belgrade, Serbia)
Dimitrijević-Srećković Vesna (University of Belgrade, Faculty of Medicine, Belgrade, Serbia + Clinical Centre of Serbia, Clinic for Endocrinology, Diabetes and Metabolic Diseases, Belgrade, Serbia)

Background/Aim. Metabolic syndrome (MS) is characterized by basic cluster risk factors – waist circumference (WC), glucoregulation disorders, hypertension, hypertriglyceridemia, low HDL-cholesterol followed by associated factors such as insulin resistance (IR), C-reactive protein (CRP), uric acid, plasminogen activator inhibitor-1 (PAI-1), fibrinogen, hyperhomocysteinemia (HHcy), nonalcoholic fatty liver disease (NAFLD) and microalbuminuira. The aim of this study was to analyze basic and associated factors of MS in patients with and without MS as well as correlation of siMS score, siMS risk score with basic and confounding factors of MS. Methods. The study included 148 overweight [body mass index (BMI) 25–30 kg/m2 and obese patients (BMI > 30 kg/m2)], age 30–75 years, classified into two groups: I – with MS (68 patients); II – without MS (80 patients). For quantification of MS, siMS score was used as a method, and siMS risk score was used as atherosclerotic complications risk indicator. Results. Patients with MS had statistically higher values of WC, hypertension, triglycerides (p < 0.001), glycemia (p = 0.006), as well as values of associated factors of MS [homeostatic model assessment (HOMA-IR)] (p = 0.002), CRP (p = 0.01), uric acid (p < 0.001), alanin transaminase (ALT) (p = 0.007) i gammaglutamyl transferase (GGT) (p = 0.001) and lower values of HDL-cholesterol (p < 0.001) compared to patients without MS. siMS score has shown correlation with associated factors of MS (log HOMA IR, logCRP, uric acid, (p < 0.001), fibrinogen (p = 0.005), liver enzymes logALT (p = 0.001) and log GGT (p < 0.001) and renal parametars (creatinine (p = 0.013) and serum protein (p = 0.006). siMS risk score correlated significantly with homocysteine, platelets, uric acid, blood urea nitrogen, albumins and proteins. Conclusion. In our study we found that patients with MS had higher values of associated factors of MS (HOMA-IR, CRP, uric acid, ALT, GGT), which was confirmed by correlation with siMS score. siMS score further indicated that IR, CRP, fibrinogen, uric acid and NAFLD are associated factors of MS. siMS risk score is another score that indicated that obesity and hyperprotein diet aggravates HHCy with age, increasing the risk for renal dysfunction and promoting atherosclerotic complications.

Keywords: biomarkers, homocysteine, metabolic syndrome, risk assessment, risk factors