Molecular classification of outcomes from dengue virus -3 infections

Allan R. Brasier, Yingxin Zhao, John E. Wiktorowicz, Heidi Spratt, Eduardo J M Nascimento, Marli T. Cordeiro, Kizhake V. Soman, Hyunsu Ju, Adrian Recinos, Susan Stafford, Zheng Wu, Ernesto T A Marques, Nikos Vasilakis

Research output: Contribution to journalArticle

8 Citations (Scopus)

Abstract

Objectives: Dengue virus (DENV) infection is a significant risk to over a third of the human population that causes a wide spectrum of illness, ranging from sub-clinical disease to intermediate syndrome of vascular complications called dengue fever complicated (DFC) and severe, dengue hemorrhagic fever (DHF). Methods for discriminating outcomes will impact clinical trials and understanding disease pathophysiology. Study design: We integrated a proteomics discovery pipeline with a heuristics approach to develop a molecular classifier to identify an intermediate phenotype of DENV-3 infectious outcome. Results: 121 differentially expressed proteins were identified in plasma from DHF vs dengue fever (DF), and informative candidates were selected using nonparametric statistics. These were combined with markers that measure complement activation, acute phase response, cellular leak, granulocyte differentiation and viral load. From this, we applied quantitative proteomics to select a 15 member panel of proteins that accurately predicted DF, DHF, and DFC using a random forest classifier. The classifier primarily relied on acute phase (A2M), complement (CFD), platelet counts and cellular leak (TPM4) to produce an 86% accuracy of prediction with an area under the receiver operating curve of >0.9 for DHF and DFC vs DF. Conclusions: Integrating discovery and heuristic approaches to sample distinct pathophysiological processes is a powerful approach in infectious disease. Early detection of intermediate outcomes of DENV-3 will speed clinical trials evaluating vaccines or drug interventions.

Original languageEnglish (US)
Pages (from-to)97-106
Number of pages10
JournalJournal of Clinical Virology
Volume64
DOIs
StatePublished - Mar 1 2015

Fingerprint

Severe Dengue
Dengue Virus
Virus Diseases
Dengue
Proteomics
Clinical Trials
Acute-Phase Reaction
Complement Activation
Nonparametric Statistics
Viral Load
Platelet Count
Granulocytes
Communicable Diseases
Blood Vessels
Proteins
Vaccines
Phenotype
Pharmaceutical Preparations

Keywords

  • Acute phase reaction
  • Biomarker pipeline
  • Dengue
  • Selected reaction monitoring

ASJC Scopus subject areas

  • Virology
  • Infectious Diseases

Cite this

Molecular classification of outcomes from dengue virus -3 infections. / Brasier, Allan R.; Zhao, Yingxin; Wiktorowicz, John E.; Spratt, Heidi; Nascimento, Eduardo J M; Cordeiro, Marli T.; Soman, Kizhake V.; Ju, Hyunsu; Recinos, Adrian; Stafford, Susan; Wu, Zheng; Marques, Ernesto T A; Vasilakis, Nikos.

In: Journal of Clinical Virology, Vol. 64, 01.03.2015, p. 97-106.

Research output: Contribution to journalArticle

Brasier, AR, Zhao, Y, Wiktorowicz, JE, Spratt, H, Nascimento, EJM, Cordeiro, MT, Soman, KV, Ju, H, Recinos, A, Stafford, S, Wu, Z, Marques, ETA & Vasilakis, N 2015, 'Molecular classification of outcomes from dengue virus -3 infections', Journal of Clinical Virology, vol. 64, pp. 97-106. https://doi.org/10.1016/j.jcv.2015.01.011
Brasier, Allan R. ; Zhao, Yingxin ; Wiktorowicz, John E. ; Spratt, Heidi ; Nascimento, Eduardo J M ; Cordeiro, Marli T. ; Soman, Kizhake V. ; Ju, Hyunsu ; Recinos, Adrian ; Stafford, Susan ; Wu, Zheng ; Marques, Ernesto T A ; Vasilakis, Nikos. / Molecular classification of outcomes from dengue virus -3 infections. In: Journal of Clinical Virology. 2015 ; Vol. 64. pp. 97-106.
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