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Peer reviewedOpen accessDengue

A multicenter prospective observational multi-omics study protocol to identify biomarkers for severe dengue: COMBAT study clinical protocol

BMC Infectious Diseases·

Piya Paul Mudgal, Silvia Patricia Zuniga Veliz, Magda Lourda, Trupti Satish Kadni, Muralidhar Varma, Anup Mazumder, Sandeep Budhiraja, Namita Jaggi, Chiranjay Mukhopadhyay, Sagar Sengupta, Arindam Maitra, Kristina Hug, Indranil Sinha, Anoop T. Ambikan, Iva Filipovic, Ujjwal Neogi, Matti Sällberg, Christian Giske, Soham Gupta, Gustaf Gustaf Ahlé, Jose Inzunza, Mukesh Varshney, Annika Charlotte Karlsson, Ali Mirazimi, Ákos Végvári, Sofja Poznakovs, Teresa Stellaccio, Surender Rawat, Birgitta Lindqvist, Panagiotis Andriopoulos, Dasja Pajkrt, Adithya Sridhar, Henk Marquering, Nina Johannesson, Amber Schotting, Renata Vieira de Sá, Balpreet Singh Ahluwalia, Vishesh Kumar Dubey, Rajkumar Savai, Soni Pullamsetti, Jonathan Andrew, Maurizio Aiello, Jacopo Furci, Elisabetta Palamà, Silvia Scaglione, Sarantis Chlamydas, Øystein Ivar Helle, Goran Josipovic, Irena Trbojevic-Akmacic, Edson Jose Adrian Bolanos Lima, Leticia Castillo Signor, Kamal Singh, Manjula Kalia, Arup Banerjee, Atul Thata, Nishi Raj Sharma, Varun Surolia, Priyanka Sharma

DOI
10.1186/s12879-026-14111-x
PMID
42538555
PMCID
OpenAlex
W7171988257
Study type
Journal article
Publisher
Springer Science and Business Media LLC
Article type
journal-article
Integrity
current

Why this research matters now

If biomarkers are successfully identified, findings may inform improved patient triage, early intervention strategies, and novel therapeutic targets for dengue management in endemic regions.

01

Structured evidence summary

Research question

The COMBAT study aims to identify predictive biomarkers for severe dengue progression by investigating host immune and metabolic pathways in dengue-endemic populations, addressing the clinical challenge of early risk stratification given overlapping clinical and laboratory features across dengue severity groups.

Study design

This is a prospective, multicenter, observational longitudinal study protocol using multi-omics analyses (transcriptomics, proteomics, glycomics, metabolomics) with discovery and independent validation cohorts, conducted across dengue-endemic sites in Guatemala and India.

Population and setting

Patients will be enrolled in Guatemala and India, classified by WHO 2009 criteria into three dengue severity groups (without warning signs, with warning signs, and severe dengue) with age- and sex-matched healthy controls.

Main findings

No findings are available; this is a study protocol with anticipated aims to identify biomarkers predictive of dengue severity progression and generate systems-level insights into host-virus interactions.

Public-health relevance

If biomarkers are successfully identified, findings may inform improved patient triage, early intervention strategies, and novel therapeutic targets for dengue management in endemic regions.

Important limitations

This summary is limited to the supplied single-article protocol abstract and requires the original paper for decision-grade interpretation; the study represents a protocol describing planned methodology rather than completed research with findings.

GIDS interpretation

This protocol describes biomarker discovery research in dengue; it does not constitute completed surveillance data or evidence of a live signal, but rather preparatory methodology to understand host factors associated with severe disease progression in endemic settings.

02

Related GIDS surveillance

Literature context does not validate, explain, or change a surveillance signal. Exact and contextual relationships are shown separately.

03

Evidence relationships

This article has 10 auditable classifier relationships to diseases, places, topics, and study design.

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