{"title":"A multicenter prospective observational multi-omics study protocol to identify biomarkers for severe dengue: COMBAT study clinical protocol.","authors":"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","doi":"10.1186/s12879-026-14111-x","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Discussion: </strong>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.</p><p><strong>Trial registration: </strong>ClinicalTrials.gov ID NCT06751836 Registration Date: December 13, 2024, CTRI/2022/10/046293 (MAHE) Registration Date: October 10, 2022.</p>","PeriodicalId":8981,"journal":{"name":"BMC Infectious Diseases","volume":"26 1","pages":""},"PeriodicalIF":3.2000,"publicationDate":"2026-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13428414/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"BMC Infectious Diseases","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1186/s12879-026-14111-x","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"INFECTIOUS DISEASES","Score":null,"Total":0}
引用次数: 0
Abstract
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.
背景：登革热病毒（DENV）感染是一项重大的全球公共卫生负担，特别是在反复接触会增加严重疾病风险的流行地区。尽管世界卫生组织（WHO）对登革热分类进行了修订，但由于临床和实验室特征重叠，早期预测进展为严重登革热仍然具有挑战性。目前的管理策略主要依赖于支持性护理和反应性监测，强调需要预测性生物标志物来实现早期风险分层和及时干预。方法：COMBAT是一项在危地马拉和印度登革热流行地区开展的前瞻性、多中心、观察性纵向研究。将根据世卫组织2009年的标准将患者分为无警告信号登革热、有警告信号登革热和严重登革热，并与年龄和性别匹配的健康对照进行对照。非住院患者采集一份血样，每位参与者住院期间采集两份血样，出院时采集一份血样。多组学分析，包括转录组学、蛋白质组学、糖组学和代谢组学，将在发现队列中进行，并在独立队列中进行验证。综合系统生物学方法将用于识别与登革热严重程度相关的宿主免疫和代谢途径，这是一种基于机制的预后生物标志物发现。讨论：本研究旨在对驱动登革热严重程度的宿主-病毒相互作用产生全面的系统级见解，并确定预测疾病进展的生物标志物。研究结果可能有助于改善患者分诊、早期干预策略和确定新的治疗靶点。试验注册：ClinicalTrials.gov ID NCT06751836注册日期：2024年12月13日，CTRI/2022/10/046293 （MAHE）注册日期：2022年10月10日。
期刊介绍：
BMC Infectious Diseases is an open access, peer-reviewed journal that considers articles on all aspects of the prevention, diagnosis and management of infectious and sexually transmitted diseases in humans, as well as related molecular genetics, pathophysiology, and epidemiology.
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