METABOLIC PROFILE OF PATIENTS WITH OROPOUCHE FEVER: IDENTIFICATION OF POTENTIAL PLASMA BIOMARKERS BY UNTARGETED METABOLOMICS

Kamila Pereira de Araujo 1, Valéria Silva Santos 1, Fernanda Oliveira do Nascimento1, Fábio César Sousa Nogueira2, Marina Amaral Alves 2,3, Felipe Gomes Naveca1,4, Priscila Ferreira de Aquino1

1. ILMD/Fiocruz Amazônia, Leonidas e Maria Deane Institute ; Terezina Street, 476 - Adrianópolis, Manaus- Amazonas, Brazil
2. UFRJ, Federal University of Rio de Janeiro; Antonio Barros de Castro Street, 119 - University City, Rio de Janeiro, Rio de Janeiro, Brazil
3. IPPN/UFRJ, Institute of Research on Natural Products; Antonio Barros de Castro Street, 373 – University City, Rio de Janeiro, Rio de Janeiro, Brazil
4. IOC, Oswaldo Cruz Institute ; Avenue Brasil, 4365 - Manguinhos, Rio de Janeiro, Rio de Janeiro, Brazil

Oropouche fever is an arbovirus caused by the Oropouche virus (OROV), belonging to the Orthobunyavirus genus. OROV is responsible for recurrent epidemic outbreaks but remains underreported and underdiagnosed due to the lack of systematic surveillance, and for its clinical presentation like other arboviruses. Despite the significant number of cases in Brazil, 13.782 confirmed cases in 2024 and more than 10.000 registered in 2025, this arbovirus continues to be classified as a neglected disease. In this scenario, the metabolomic approach can contribute to the investigation of biochemical alterations induced by this viral infection and expand knowledge about neglected arboviruses in the Amazon region. Therefore, herein we aim to analyze the metabolite profile of plasma from patients infected with OROV and identify possible biomarkers involved in the infection mechanism. For this, two groups were analyzed: 10 patients with Oropouche fever in the acute phase - OROV+, and 10 Control individuals, tested negative for arboviruses (CAAE: 7.2678.9238.0000.5016). We performed a liquid-liquid extraction   and analyzed by an Ultimate 3000 UHPLC system coupled to a Q Exactive Plus mass spectrometer (Thermo Scientific, USA). The spectral data obtained were analyzed in the MS-DIAL software for metabolite identification and subjected to multivariate statistical analysis in MetaboAnalyst 6.0. Principal Component Analysis (PCA) and Partial Least Squares Discriminant Analysis (PLS-DA) showed a clear separation between the Control and OROV+ groups. The Random Forest model showed excellent classification performance, with an overall error of only 4.76%. The heatmap, based on the normalized intensity values ​​and the results of the analysis of variance (ANOVA), showed metabolic discrimination between the OROV+ and Control groups, confirming the separations observed in the PCA, PLS-DA and Random Forest, allowing the identification of the most important metabolites responsible for the distinction between the sample groups, including the metabolites N-acetylneuraminic acid (Neu5Ac), involved in the regulation of cell-cell interactions and the immune response; uridine, related to intense viral replication and tissue damage; and Cer[NS] d36, whose significant reduction has already been described in patients with dengue during the febrile. Taken together, these findings indicate that OROV infection promotes metabolic remodeling and reinforce the potential of the metabolomic approach as a tool for identifying biomarkers and understanding the biochemical mechanisms involved in this infection.

Agradecimentos: CAPES - Finance Code 001, CNPQ- PAIC Program, ILMD/FIOCRUZ-Amazônia, UFRJ (Laboratory for the Support of Technological Development -LADETEC/IQ-UFRJ).