Project Details

Early Career

Status: Funded - Open

Predicting the development of severe dengue in children

Zhiyuan Yao, PhD


Dengue virus (DENV) infection is a global health threat infecting ~400 million people annually in over 100 countries, with a high incidence in children. Most symptomatic individuals present with dengue fever, yet 5-20% progress to severe dengue (SD), associated with morbidity and mortality. Children progress to SD more often than adults and have higher death rates, however, the factors causing increased severity in children remain unclear. Moreover, there are no effective clinically usable biomarkers to predict which patients will progress to SD. To overcome these challenges, we established a cohort of dengue patients who presented prior to the progression to SD in Colombia. Moreover, we developed a virus inclusive single cell RNA-Seq (viscRNA-Seq) platform to profile the host response in correlation with viral RNA abundance in PBMCs. In parallel, to capture real world heterogeneity, we applied a multi-cohort analysis of the publicly available gene expression data sets, discovered an 8-gene set that is highly predictive of SD prior to its onset, and showed its high predictive power in 184 patients from our cohort. This project’s main goals are to: i. decipher why children have worse disease outcome; ii. validate candidate biomarkers for early identification of patients at risk to progress to SD; iii. initiate the development of the first molecular dengue prognostic/diagnostic assay.

BACKGROUND: A major threat to children’s health is posed by dengue virus (DENV) infection, for which no treatment or effective vaccine are currently available.

GAP: The urgent need for novel strategies to identify patients who are at risk to develop severe dengue.

HYPOTHESIS: Hypotheses 1: CD163 and TMEM176B in monocytes, and additional cellular factors whose expression is misregulated prior to the progression to SD, as I discovered via viscRNA-seq analysis, play a role in SD pathogenesis and are potential cell-type specific biomarkers of severity. Hypotheses 2: The 8-gene set we discovered, already showing great promise in predicting SD, is composed of factors that contribute to SD pathogenesis, and can effectively predict SD in children.

METHODS: Our studies represent a broad range of activities from pilot validation of cell-type specific biomarkers to the initiation of development of the first prognostic assay for dengue. Both aims will utilize samples from our Colombia cohort: whole blood, serum and PBMC samples collected during the disease course and recovery from 288 children and 20 healthy controls.

RESULTS: Pending.

IMPACT: Once our transcriptomic signature is validated, we will develop a paradigm-shifting, high fidelity, molecular diagnostic and prognostic assay for prediction of severe dengue infection in children to improve resource allocation and guide future treatment decisions.