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Potential biomarkers for the clinical prognosis of severe dengue
Authors:Mayara Marques Carneiro da Silva  Laura Helena Vega Gonzales Gil  Ernesto Torres de Azevedo Marques  Júnior  Carlos Eduardo Calzavara-Silva
Affiliation:1. Laboratório de Virologia e Terapia Experimental, Departamento de Virologia, Centro de Pesquisas Aggeu Magalhães-Fiocruz, Recife, PE, Brasil;2. Department of Infectious Diseases and Microbiology, Center for Vaccine Research, University of Pittsburgh, Pittsburgh, PA, USA;3. Laboratório de Imunologia Celular e Molecular, Departamento de Imunologia, Centro de Pesquisas René Rachou-Fiocruz, Belo Horizonte, MG, Brasil
Abstract:Currently, several assays can confirm acute dengue infection at thepoint-of-care. However, none of these assays can predict the severity of thedisease symptoms. A prognosis test that predicts the likelihood of a denguepatient to develop a severe form of the disease could permit more efficientpatient triage and treatment. We hypothesise that mRNA expression of apoptosisand innate immune response-related genes will be differentially regulated duringthe early stages of dengue and might predict the clinical outcome. Aiming toidentify biomarkers for dengue prognosis, we extracted mRNA from the peripheralblood mononuclear cells of mild and severe dengue patients during the febrilestage of the disease to measure the expression levels of selected genes byquantitative polymerase chain reaction. The selected candidate biomarkers werepreviously identified by our group as differentially expressed in microarraystudies. We verified that the mRNA coding for CFD, MAGED1, PSMB9, PRDX4 andFCGR3B were differentially expressed between patients who developed clinicalsymptoms associated with the mild type of dengue and patients who showedclinical symptoms associated with severe dengue. We suggest that this geneexpression panel could putatively serve as biomarkers for the clinical prognosisof dengue haemorrhagic fever.
Keywords:dengue   biomarkers   apoptosis   innate immunity   quantitative real-time PCR
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