ARTIFICIAL NEURONAL NETWORK ANALYSIS IN INVESTIGATING THE RELATIONSHIP BETWEEN OXIDATIVE STRESS AND ENDOPLASMIC RETICULUM STRESS TO ADDRESS BLOCKED VESSELS IN CARDIOVASCULAR DISEASE ANALIZA VE[TA^KE NEURONALNE MRE@E U ISTRA@IVANJU ODNOSA IZME U OKSIDATIVNOG STRESA I STRESA ENDOPLAZMI^KOG RETIKULUMA U RE[AVANJU BLOKIRANIH SUDOVA KOD KARDIOVASKULARNE BOLESTI

Abstract

© 2022 Sciendo. All rights reserved.Background: Cardiovascular disease is the leading cause of death in the world and is associated with significant morbidity. Atherosclerosis is the main cause of cardiovascular disease (CVD), including myocardial infarction (MI), heart failure, and stroke. The mechanism of atherosclerosis has not been well investigated in different aspects, such as the relationship between oxidative stress and endothelial function. This project aims to investigate whether an oxidative enzyme vascular peroxidase 1 (VPO1) and activating transcription factor 4 (ATF4) can be used as biomarkers in highlighting the pathogenesis of the disease and in evaluating the prognosis of the relationship with endoplasmic reticulum and oxidative stress. This paper used artificial neural network analysis to predict cardiovascular disease risk based on new generation biochemical markers that combine vascular inflammation, oxidative and endoplasmic reticulum stress. Methods: For this purpose, 80 patients were evaluated according to the coronary angiography results. hs-CRP, lipid parameters and demographic characteristics, VPO1, ATF4 and Glutathione peroxidase 1(GPx1) levels were measured. Results: We found an increase in VPO1 and hs-CRP levels in single-vessel disease as compared to controls. On the contrary, ATF4 and GPx1 levels were decreased in the same group, which was not significant. Our results showed a significant positive correlation between ATF4 and lipid parameters. A statistically significant positive correlation was also observed for VPO1 and ATF4 (r=0.367, P<0.05), and a negative correlation was found for ATF4 and GPx1 (r=-0.467, P<0.01). A significant negative relationship was noted for GPx1 and hs-CRP in two/three-vessel disease (r=-0.366, P<0.05). Artificial neural network analysis stated that body mass index (BMI) and smoking history information give us an important clue as compared to age, gender and alcohol consumption parameters when predicting the number of blocked vessels. Conclusions: VPO1 and ATF4 might be potential biomarkers associated with coronary artery disease, especially in the follow-up and monitoring of treatment protocols, in addition to traditional risk factors.