Unraveling the Pathogenesis of Crimean-Congo Hemorrhagic Fever: A Novel Approach via Non-Targeted Metabolomics by NMR Spectroscopy

Crimean-Congo Hemorrhagic Fever (CCHF) is a severe tick-borne viral disease with high mortality rates and significant public health implications. Despite its global prevalence, the mechanisms underlying its pathogenesis remain poorly understood, and effective diagnostic and therapeutic tools are limited. Metabolomics, as a powerful tool for exploring host-pathogen interactions, offers a promising avenue for identifying biomarkers and elucidating disease mechanisms. In this study, we investigated the metabolic alterations in CCHF patients using non-targeted metabolomics to enhance understanding of disease pathogenesis, improve diagnostic capabilities, and identify potential therapeutic targets. A nationwide analysis was conducted on the blood serum of 29 CCHF patients and 10 healthy controls, employing Nuclear Magnetic Resonance (NMR) spectroscopy. Serum samples were collected over four consecutive days, and metabolic profiling was performed using Partial Least Squares Discriminant Analysis (PLS-DA) and Variable Importance in Projection (VIP) scoring to identify key metabolic pathways and compounds. Significant disruptions in metabolic pathways were observed in CCHF patients, particularly in purine and pyrimidine metabolism, the TCA cycle, and redox-related processes. Elevated levels of metabolites such as S-adenosyl homocysteine (SAH), guanosine triphosphate (GTP), inosine monophosphate (IMP), adenosine monophosphate (AMP), carnosine, 2-deoxyuridine, nicotinamide adenine dinucleotide phosphate (NADP+), and maleate were identified. These metabolites demonstrated potential as biomarkers for disease severity and progression, with distinct metabolic profiles observed between moderate and severe cases. This study provides the first comprehensive metabolomic analysis of CCHF, highlighting critical metabolic pathways disrupted during infection. The findings underscore the utility of NMR-based metabolomics for identifying biomarkers that facilitate early diagnosis, prognosis, and therapeutic development. These results pave the way for future research to validate the identified biomarkers and explore targeted treatment strategies to improve patient outcomes in this severe viral infection.