20.500.12556/RUL-165284 COVID-19 and cholesterol biosynthesis towards innovative decision support systems With COVID-19 becoming endemic, there is a continuing need to find biomarkers characterizing the disease and aiding in patient stratification. We studied the relation between COVID-19 and cholesterol biosynthesis by comparing 10 intermediates of cholesterol biosynthesis during the hospitalization of 164 patients (admission, disease deterioration, discharge) admitted to the University Medical Center of Ljubljana. The concentrations of zymosterol, 24-dehydrolathosterol, desmosterol, and zymostenol were significantly altered in COVID-19 patients. We further developed a predictive model for disease severity based on clinical parameters alone and their combination with a subset of sterols. Our machine learning models applying 8 clinical parameters predicted disease severity with excellent accuracy (AUC = 0.96), showing substantial improvement over current clinical risk scores. After including sterols, model performance remained better than COVID-GRAM. This is the first study to examine cholesterol biosynthesis during COVID-19 and shows that a subset of cholesterol-related sterols is associated with the severity of COVID-19. assessment in health technology lipid bioinformatics COVID-19 holesterol biosinteza steroli lipidi bioinformatika ocenjevanje v zdravstveni tehnologiji true false true Angleški jezik Slovenski jezik Članek v reviji 2024-11-29 09:02:18 2024-11-29 09:02:20 2025-11-11 14:19:52 0000-00-00 00:00:00 2023 0 0 17 str. iss. 10, art. 107799 Vol. 26 2023 0000-00-00 Zaloznikova Objavljeno NiDoloceno 0000-00-00 0000-00-00 0000-00-00 61:60:578 2589-0042 10.1016/j.isci.2023.107799 165467907 RAZ_Kocar_Eva_2023.pdf RAZ_Kocar_Eva_2023.pdf 1 9EBEBF34D68A55371CF48F3197F329B4 45ef5102ad8a3673f0e8ab6fd65c957e909907dde794e7283bbd64b980d01ac1 6b11e9b4-ae28-11ef-b232-0050569b8976 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=196362 https://www.sciencedirect.com/science/article/pii/S258900422301876X 0 34e55a4a-befd-11f0-9328-0050569b8976 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=221780 https://www.cell.com/iscience/fulltext/S2589-0042(23)01876-X 0 63eab9e7-befd-11f0-9328-0050569b8976 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=221782 Medicinska fakulteta Fakulteta za računalništvo in informatiko 0 0 0