Clinical significance of differential serum-signatures for early prediction of severe dengue among Eastern Indian patients

差异血清特征对东印度患者重症登革热早期预测的临床意义

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作者:Saikat Mukherjee, Bibhuti Saha, Anusri Tripathi

Abstract

Dengue infection can result in simple dengue fever or life-threatening severe dengue. Early identification of severe patients is needed for proper disease management. Dengue infection was screened among 168 symptomatic patients by qRT-PCR, anti-dengue IgM, and IgG ELISA. Dengue patients were categorized according to WHO classification. Viral load and dengue serotypes were determined by qRT-PCR. Levels of acute-phase-proteins (SAP, SAA2; CRP and ApoA1), endothelial (Ang2, VEGF), coagulation (fibrinogen) markers were determined by sandwich ELISA/immunoturbidimetry/western-blotting. Hepatic (ALT, AST, ALP) and other blood biochemical parameters were studied by autoanalyzer and haematology cell counter. Statistical analysis and protein-protein-interaction network were performed by GraphPad-Prism and STRINGS database, respectively. Among 87 dengue patients, significantly higher levels of Ang2, VEGF, CRP, SAA2, ApoA1, AST, ALT, and AST/ALT ratio and low level of fibrinogen were detected in severe-dengue cases compared to dengue without warning-signs, with seven of them severely altered during febrile-phase. Higher fold-change of Ang2 and VEGF as well as decreased fibrinogen were observed among patients with haemorrhagic-manifestation, clinical-fluid accumulation and thrombocytopenia. Functional network analysis predicted Ang2, VEGF, and CRP to be functionally and physically connected and SAA2 and ApoA1 to be functioning together. Correlation analyses also validated this connectivity by a strong positive correlation between Ang2, VEGF, and CRP. PCA analysis followed by hierarchical clustering heatmap analysis segregated severe-dengue patients from the rest, with VEGF, Ang2, ApoA1, AST, and ALT clearly distinguishing the severe-dengue group. Thus, serum levels of VEGF, Ang2, ApoA1, AST, and ALT might act as potential biomarkers for predicting dengue severity during the early stage.

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