Background: Early diagnosis of dengue virus infection during the febrile stage is essential for adjusting appropriate management. This study is to identify the predictive markers of clinical and laboratory findings in the acute stage of dengue infection during a major outbreak of dengue virus type 1 that occurred in southern Taiwan during 2007. A retrospective, hospital-based study was conducted at a university hospital in southern Taiwan from January to December, 2007. Patient who was reported for clinically suspected dengue infection was enrolled. Laboratory-positive dengue cases are confirmed by enzyme-linked immunosorbent assay of specific dengue IgM, fourfold increase of dengue-specific IgG titers in convalescent serum, or by reverse transcription-polymerase chain reaction (RT-PCR) of dengue virus. Results: The suspected dengue cases consist of 100 children (≤ 18 years) and 481 adults. Among the 581 patients, 67 (67%) children and 309 (64.2%) adults were laboratory-confirmed. Patients who had laboratory indeterminate were excluded. Most cases were uncomplicated and 3.8% of children and 2.9% of adults developed dengue hemorrhagic fever or dengue shock syndrome (DHF/DSS). The overall mortality rate in those with DHF/DSS was 7.1%, and the average duration of hospitalization was 20 days. The most common symptoms/signs at admission were myalgia (46.8%), petechiae (36.9%) and nausea/vomiting (33.5%). The most notable laboratory findings included leukopenia (2966 ± 1896/cmm), thrombocytopenia (102 ± 45 × 10³/cmm), prolonged activated partial thromboplastin time (aPTT) (45 ± 10 s), and elevated serum levels of aminotransferase (AST, 166 ± 208 U/L; ALT, 82 ± 103 U/L) and low C - reactive protein (CRP) (6 ± 11 mg/L). Based on the clinical features for predicting laboratory-confirmed dengue infection, the sensitivities of typical rash, myalgia, and positive tourniquet test are 59.2%, 46.8%, and 34.2%, while the specificities for above features are 75.4%, 53.5% and 100%, respectively. The positive predictive value (PPV) for combination of leukopenia, thrombocytopenia (< 150 × 10³/cmm), elevated aminotransferase (AST/ALT > 1.5) and low CRP (< 20 mg/L) is 89.5%, while the negative predictive value is 37.4%. Furthermore, the PPV of the combination was increased to 93.1% by adding prolonged aPTT (>38 secs). Conclusions: Leukopenia, thrombocytopenia, elevated aminotransferases, low CRP and prolonged aPTT, were useful predictive markers for early diagnosis of dengue infection during a large outbreak in southern Taiwan.

Dengue is the most common mosquito-transmitted viral infection for which an improved vaccine is still needed. Although nonstructural protein-1 (NS1) immunization can protect mice against dengue infection, molecular mimicry between NS1 and host proteins makes NS1-based vaccines challenging to develop. Based on the epitope recognized by the anti-NS1 monoclonal Ab (mAb) 33D2 which recognizes a conserved NS1 wing domain (NS1-WD) region but not host proteins, we synthesized a modified NS1-WD peptide to immunize mice. We found that both mAb 33D2 and modified NS1-WD peptide immune sera could induce complement-dependent lysis of dengue-infected but not un-infected cellsin vitro. Furthermore, either active immunization with the modified NS1-WD peptide or passive transfer of mAb 33D2 efficiently protected mice against all serotypes of dengue virus infection. More importantly, dengue patients with more antibodies recognized the modified NS1-WD peptide had less severe disease. Thus, the modified NS1-WD peptide is a promising dengue vaccine candidate.

Vascular leakage is one of the salient characteristics of severe dengue. Nonstructural protein 1 (NS1) of dengue virus (DENV) can stimulate endothelial cells to secrete endothelial hyperpermeability factor, macrophage migration inhibitory factor (MIF), and the glycocalyx degradation factor heparanase 1 (HPA-1). However, it is unclear whether MIF is directly involved in NS1-induced glycocalyx degradation. In this study, we observed that among NS1, MIF and glycocalyx degradation-related molecules, the HPA-1, metalloproteinase 9 (MMP-9) and syndecan 1 (CD138) serum levels were all increased in dengue patients, and only NS1 and MIF showed a positive correlation with the CD138 level in severe patients. To further characterize and clarify the relationship between MIF and CD138, we used recombinant NS1 to stimulate human cells in vitro and challenge mice in vivo. Our tabulated results suggested that NS1 stimulation could induce human endothelial cells to secrete HPA-1 and immune cells to secrete MMP-9, resulting in endothelial glycocalyx degradation and hyperpermeability. Moreover, HPA-1, MMP-9, and CD138 secretion after NS1 stimulation was blocked by MIF inhibitors or antibodies both in vitro and in mice. Taken together, these results suggest that MIF directly engages in dengue NS1-induced glycocalyx degradation and that targeting MIF may represent a possible therapeutic approach for preventing dengue-induced vascular leakage. DENV NS1 induces endothelial glycocalyx degradation and hyperpermeability via HPA-1 and MMP-9 activation in an MIF-dependent manner.

In recent decades, the global incidence of dengue has increased. Affected countries have responded with more effective surveillance strategies to detect outbreaks early, monitor the trends, and implement prevention and control measures. We have applied newly developed machine learning approaches to identify laboratory-confirmed dengue cases from 4,894 emergency department patients with dengue-like illness (DLI) who received laboratory tests. Among them, 60.11% (2942 cases) were confirmed to have dengue. Using just four input variables [age, body temperature, white blood cells counts (WBCs) and platelets], not only the state-of-the-art deep neural network (DNN) prediction models but also the conventional decision tree (DT) and logistic regression (LR) models delivered performances with receiver operating characteristic (ROC) curves areas under curves (AUCs) of the ranging from 83.75% to 85.87% [for DT, DNN and LR: 84.60% ± 0.03%, 85.87% ± 0.54%, 83.75% ± 0.17%, respectively]. Subgroup analyses found all the models were very sensitive particularly in the pre-epidemic period. Pre-peak sensitivities (<35 weeks) were 92.6%, 92.9%, and 93.1% in DT, DNN, and LR respectively. Adjusted odds ratios examined with LR for low WBCs [≤ 3.2 (x10³/μL)], fever (≥38°C), low platelet counts [< 100 (x10³/μL)], and elderly (≥ 65 years) were 5.17 [95% confidence interval (CI): 3.96–6.76], 3.17 [95%CI: 2.74–3.66], 3.10 [95%CI: 2.44–3.94], and 1.77 [95%CI: 1.50–2.10], respectively. Our prediction models can readily be used in resource-poor countries where viral/serologic tests are inconvenient and can also be applied for real-time syndromic surveillance to monitor trends of dengue cases and even be integrated with mosquito/environment surveillance for early warning and immediate prevention/control measures. In other words, a local community hospital/clinic with an instrument of complete blood counts (including platelets) can provide a sentinel screening during outbreaks. In conclusion, the machine learning approach can facilitate medical and public health efforts to minimize the health threat of dengue epidemics. However, laboratory confirmation remains the primary goal of surveillance and outbreak investigation.

Dengue virus (DENV) is the causative agent of dengue fever, dengue hemorrhagic fever, and dengue shock syndrome and is endemic to tropical and subtropical regions of the world. Our previous studies showed the existence of epitopes in the C-terminal region of DENV nonstructural protein 1 (NS1) which are cross-reactive with host Ags and trigger anti–DENV NS1 Ab–mediated endothelial cell damage and platelet dysfunction. To circumvent these potentially harmful events, we replaced the C-terminal region of DENV NS1 with the corresponding region from Japanese encephalitis virus NS1 to create chimeric DJ NS1 protein. Passive immunization of DENV-infected mice with polyclonal anti–DJ NS1 Abs reduced viral Ag expression at skin inoculation sites and shortened DENV-induced prolonged bleeding time. We also investigated the therapeutic effects of anti-NS1 mAb. One mAb designated 2E8 does not recognize the C-terminal region of DENV NS1 in which host–cross-reactive epitopes reside. Moreover, mAb 2E8 recognizes NS1 of all four DENV serotypes. We also found that mAb 2E8 caused complement-mediated lysis in DENV-infected cells. In mouse model studies, treatment with mAb 2E8 shortened DENV-induced prolonged bleeding time and reduced viral Ag expression in the skin. Importantly, mAb 2E8 provided therapeutic effects against all four serotypes of DENV. We further found that mAb administration to mice as late as 1 d prior to severe bleeding still reduced prolonged bleeding time and hemorrhage. Therefore, administration with a single dose of mAb 2E8 can protect mice against DENV infection and pathological effects, suggesting that NS1-specific mAb may be a therapeutic option against dengue disease.