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Cell Rep. 2019 Jan 29;26(5):1104-1111.e4. doi: 10.1016/j.celrep.2019.01.033.

A 20-Gene Set Predictive of Progression to Severe Dengue.

Author information

1
Department of Medicine, Division of Infectious Diseases and Geographic Medicine, Stanford University, Stanford, CA, USA; Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford, CA, USA.
2
Institute for Immunity, Transplantation, and Infection, Department of Medicine, Stanford University, Stanford, CA, USA; Department of Medicine, Division of Biomedical Informatics Research, Stanford University, Stanford, CA, USA.
3
Department of Medicine, Division of Infectious Diseases and Geographic Medicine, Stanford University, Stanford, CA, USA.
4
Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA.
5
Clinical Research Center, Fundación Valle del Lili, Cali, Colombia.
6
Pathology and Laboratory Department, Fundación Valle del Lili, Cali, Colombia.
7
Clinical Research Center, Fundación Valle del Lili, Cali, Colombia; Department of Internal Medicine, Division of Infectious Diseases, Fundación Valle del Lili, Cali, Colombia.
8
Department of Medicine, Division of Infectious Diseases and Geographic Medicine, Stanford University, Stanford, CA, USA; Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA.
9
Institute for Immunity, Transplantation, and Infection, Department of Medicine, Stanford University, Stanford, CA, USA; Department of Medicine, Division of Biomedical Informatics Research, Stanford University, Stanford, CA, USA. Electronic address: pkhatri@stanford.edu.
10
Department of Medicine, Division of Infectious Diseases and Geographic Medicine, Stanford University, Stanford, CA, USA; Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford, CA, USA. Electronic address: seinav@stanford.edu.

Abstract

There is a need to identify biomarkers predictive of severe dengue. Single-cohort transcriptomics has not yielded generalizable results or parsimonious, predictive gene sets. We analyzed blood samples of dengue patients from seven gene expression datasets (446 samples, five countries) using an integrated multi-cohort analysis framework and identified a 20-gene set that predicts progression to severe dengue. We validated the predictive power of this 20-gene set in three retrospective dengue datasets (84 samples, three countries) and a prospective Colombia cohort (34 patients), with an area under the receiver operating characteristic curve of 0.89, 100% sensitivity, and 76% specificity. The 20-gene dengue severity scores declined during the disease course, suggesting an infection-triggered host response. This 20-gene set is strongly associated with the progression to severe dengue and represents a predictive signature, generalizable across ages, host genetic factors, and virus strains, with potential implications for the development of a host response-based dengue prognostic assay.

KEYWORDS:

biomarkers; multi-coherent analysis; prognostics; severe dengue; transcriptomics

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