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Crimean-Congo Hemorrhagic Fever Disease: Relationship Between Clinical Course and Apoptosis
Mehmet Samet Demirel1, Çigdem Kader1, Emine Yeşilyurt2
1Department of Infectious Diseases and Clinical Microbiology, Yozgat Bozok University School of Medicine, Yozgat, Türkiye.
Objective:
Crimean-Congo hemorrhagic fever (CCHF) is a zoonotic disease that causes significant morbidity and mortality. This study aimed to evaluate the levels of apoptosis biomarkers-clusterin, tumor necrosis factor-related apoptosis-inducing ligand (TRAIL), caspase-8, cytochrome C, and apoptotic protease-activating factor 1 (Apaf-1)-in patients with mild and severe clinical presentations of CCHF, and to assess their relationship with disease severity.
Materials And Methods:
The study included adult patients admitted to our hospital with a confirmed diagnosis of CCHF. Patients were divided into two groups (mild and severe) based on the Severity Grading Score. Blood samples were analyzed for apoptosis markers using the enzyme-linked immunosorbent assay (ELISA) method. Apoptosis protein levels were measured separately during the acute and convalescent periods of the disease for both mild and severe cases.
Results:
A total of 49 patients were included in the study. In patients with a mild disease course, TRAIL levels were significantly higher during the acute period compared to the convalescent period (p<0.001). Similarly, in patients with severe disease, TRAIL levels were also higher in the acute period than in the convalescent period (p=0.05). During the acute period, clusterin, TRAIL, caspase-8, and Apaf-1 levels were higher in patients with severe disease than in those with mild disease. When comparing median apoptosis protein levels during the convalescent period, TRAIL levels were significantly higher in patients with severe disease (p=0.009).
Conclusions:
Apoptosis and apoptosis-related proteins play an important role in the pathogenesis of CCHF. In particular, clusterin and TRAIL may serve as useful indicators of disease severity. Their early detection could improve clinical management by enabling timely intervention for patients at risk of severe disease.
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