PLoS ONE · 2009 · 96 citations · 41 references
Life SciencesInfectious DiseasesMolecular BiologyGene ExpressionGene Expression AnalysisInnate ImmunityDifferential Expression AnalysisDifferential Gene Expression AnalysisGene Expression ProfilingInflammation In Infectious DiseaseInflammatory BiomarkersInnate Immune ActivationAcute Febrile IllnessClinical Outcome MeasurementDengue FeverDengue Hemorrhagic FeverGene Expression SignaturesImmune Gene Expression SignaturesInflammation-related Gene ExpressionInflammatory Response Genes
BACKGROUND: We report the detailed development of biomarkers to predict the clinical outcome under dengue infection. Transcriptional signatures from purified peripheral blood mononuclear cells were derived from whole-genome gene-expression microarray data, validated by quantitative PCR and tested in independent samples. METHODOLOGY/PRINCIPAL FINDINGS: The study was performed on patients of a well-characterized dengue cohort from Recife, Brazil. The samples analyzed were collected prospectively from acute febrile dengue patients who evolved with different degrees of disease severity: classic dengue fever or dengue hemorrhagic fever (DHF) samples were compared with similar samples from other non-dengue febrile illnesses. The DHF samples were collected 2-3 days before the presentation of the plasma leakage symptoms. Differentially-expressed genes were selected by univariate statistical tests as well as multivariate classification techniques. The results showed that at early stages of dengue infection, the genes involved in effector mechanisms of innate immune response presented a weaker activation on patients who later developed hemorrhagic fever, whereas the genes involved in apoptosis were expressed in higher levels. CONCLUSIONS/SIGNIFICANCE: Some of the gene expression signatures displayed estimated accuracy rates of more than 95%, indicating that expression profiling with these signatures may provide a useful means of DHF prognosis at early stages of infection.
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DAVID: Database for Annotation, Visualization, and Integrated Discovery
Glynn Dennis, Brad T. Sherman, Douglas A Hosack et al. · Genome biology · 2003 · 9.5K citations · Full text
A Gene-Expression Signature as a Predictor of Survival in Breast Cancer
Marc J. van de Vijver, Yudong D. He, Laura van ‘t Veer et al. · New England Journal of Medicine · 2002 · 6.5K citations · Full text
Medicine, Bioinformatics, Oncology +17