Dengue viremia kinetics and effects on platelet count and clinical outcomes: An analysis of 2340 patients from Vietnam

Circulating lncRNAs as biomarkers for severe dengue using a machine learning approach

OBJECTIVES

Dengue virus (DENV) infection is a significant global health concern, causing severe morbidity and mortality. While many cases present as a mild febrile illness, some progress to life-threatening severe dengue (SD). Early intervention is essential to improve outcomes, but current predictive methods lack specificity, burdening healthcare systems in endemic regions. Circulating long non-coding RNAs (lncRNAs) have emerged as stable and promising biomarkers. This study explored the use of lncRNAs as predictive markers for SD.

METHODS

Differential expression and qPCR arrays were employed to identify lncRNAs associated with SD. Candidate lncRNAs were validated, and their plasma levels were measured in a cohort of Vietnamese dengue patients (n =377) and healthy controls (n=128) at admission. Machine learning algorithms were applied to predict the probability of SD progression.

RESULTS

The predictive model demonstrated high sensitivity and specificity, with an area under the curve (AUC) of 0.98 (95% CI: 0.96-1.0). At admission, it accurately identified 17 of 18 patients who later died as high-risk, compared to traditional warning signs, which flagged only 9 of these cases.

CONCLUSIONS

Our findings suggest that this panel of lncRNAs has the potential to predict SD, which could help reduce healthcare burden and improve patient management in endemic countries.

Dengue severity by serotype and immune status in 19 years of pediatric clinical studies in Nicaragua

BACKGROUND

Dengue virus, a major global health threat, consists of four serotypes (DENV1-4) that cause a range of clinical manifestations from mild to severe and potentially fatal disease.

METHODS

This study, based on 19 years of data from the Pediatric Dengue Cohort Study and Pediatric Dengue Hospital-based Study in Managua, Nicaragua, investigates the relationship of serotype and immune status with dengue severity. Dengue cases were confirmed by molecular, serological, and/or virological methods, and study participants 6 months to 17 years old were followed during their hospital stay or as ambulatory patients.

RESULTS

We enrolled a total of 15,833 participants, of whom 3,308 (21%) were positive for DENV infection. Of 2,644 cases with serotype result by RT-PCR, 559 corresponded to DENV1, 1,002 to DENV2, 760 to DENV3 and 323 to DENV4. Severe disease was more prevalent among secondary DENV2 and DENV4 cases, while similar disease severity was observed in both primary and secondary DENV1 and DENV3 cases. According to the 1997 World Health Organization (WHO) severity classification, both DENV2 and DENV3 caused a higher proportion of severe disease compared to other serotypes, whereas DENV3 caused the greatest percentage of severity according to the WHO-2009 classification. DENV2 was associated with increased odds of pleural effusion and low platelet count, while DENV3 was associated with both hypotensive and compensated shock.

CONCLUSIONS

These findings demonstrate differences in dengue severity by serotype and immune status and emphasize the critical need for a dengue vaccine with balanced effectiveness against all four serotypes, particularly as existing vaccines show variable efficacy by serotype and serostatus.

In-host modeling of dengue virus and non-structural protein 1 and the effects of ivermectin in patients with acute dengue fever

The increased incidence of dengue poses a substantially global public health challenge. There are no approved antiviral drugs to treat dengue infections. Ivermectin, an old anti-parasitic drug, had no effect on dengue viremia, but reduced the dengue non-structural protein 1 (NS1) in a clinical trial. This is potentially important, as NS1 may play a causal role in the pathogenesis of severe dengue. This study established an in-host model to characterize the plasma kinetics of dengue virus and NS1 with host immunity and evaluated the effects of ivermectin, using a population pharmacokinetic-pharmacodynamic (PK-PD) modeling approach, based on two studies in acute dengue fever: a placebo-controlled ivermectin study in 250 adult patients and an ivermectin PK-PD study in 24 pediatric patients. The proposed model described adequately the observed ivermectin pharmacokinetics, viral load, and NS1 data. Bodyweight was a significant covariate on ivermectin pharmacokinetics. We found that ivermectin reduced NS1 with an EC50 of 67.5 μg/mL. In silico simulations suggested that ivermectin should be dosed within 48 h after fever onset, and that a daily dosage of 800 μg/kg could achieve substantial NS1 reduction. The in-host dengue model is useful to assess the drug effect in antiviral drug development for dengue fever.

Race against dengue

Understanding the kinetics of dengue viruses in the bloodstream can provide insights into the clinical outcomes of the disease.