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Updated: Aug 5, 2026

Protocol for Dengue Infections in Mosquitoes (A. aegypti) and Infection Phenotype Determination
Published on: July 4, 2007
A multicenter prospective observational multi-omics study protocol to identify biomarkers for severe dengue: COMBAT
Piya Paul Mudgal1, Silvia Patricia Zuniga Veliz2, Magda Lourda3
1Manipal Institute of Virology, Manipal Academy of Higher Education, Manipal, India.
Background:
Dengue virus (DENV) infection poses a major global public health burden, particularly in endemic regions where repeated exposure increases the risk of severe disease. Despite revisions to the World Health Organization (WHO) dengue classification, early prediction of progression to severe dengue remains challenging due to overlapping clinical and laboratory features. Current management strategies rely primarily on supportive care and reactive monitoring, underscoring the need for predictive biomarkers that enable early risk stratification and timely intervention.
Methods:
COMBAT is a prospective, multicenter, observational longitudinal study conducted in dengue-endemic regions of Guatemala and India. Patients will be classified according to WHO 2009 criteria into dengue without warning signs, dengue with warning signs, and severe dengue, alongside age- and sex-matched healthy controls. A single blood sample will be collected from non-hospitalized patients while two blood samples per participant will be collected during hospitalization and one at discharge. Multi-omics analyses, including transcriptomics, proteomics, glycomics and metabolomics, will be performed in a discovery cohort and validated in an independent cohort. Integrated systems biology approaches will be used to identify host immune and metabolic pathways associated with dengue severity in a mechanism-based prognostic biomarker discovery.
Discussion:
This study aims to generate comprehensive systems-level insights into host-virus interactions driving dengue severity and to identify biomarkers predictive of disease progression. The findings may inform improved patient triage, early intervention strategies, and the identification of novel therapeutic targets.
Trial Registration:
ClinicalTrials.gov ID NCT06751836 Registration Date: December 13, 2024, CTRI/2022/10/046293 (MAHE) Registration Date: October 10, 2022.
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