ABSTRACT
BACKGROUND: Seasonal outbreaks of dengue often result in hundreds of dengue-suspected cases where a clinical diagnosis cannot be confirmed. Usually, during large outbreaks of dengue and other pathogens that can cause acute febrile illnesses, the search for secondary pathogens with similar disease outcomes is rare. METHODS: Using total RNA sequencing and targeted diagnostic assays, we discovered an outbreak of parvovirus B19 in dengue-suspected patients that occurred from November 2013 to February 2014. RESULTS: Of the 182 cases investigated, 63% were viremic for the B19 virus. Moreover, we found that >43% of infected patients had no serological evidence of prior infection. Parvovirus B19 is a typical childhood infection, yet we observed that 82% of the infected patients were adults. Additionally, we perceived that infected adults had significantly higher presentations of myalgia than in children. We also obtained viral protein (VP) 1/VP2 gene nucleotide sequences from 43 patients. CONCLUSIONS: Our results support the utility of next-generation sequencing for symptomatic patients with unknown etiologies during seasonal outbreaks of dengue and other arborviruses. Our findings could improve the vigilance of hospitals and laboratories by raising awareness of co-circulating pathogens such as parvovirus B19 that may be hidden in plain sight.
Subject(s)
Coinfection/epidemiology , Dengue/epidemiology , Disease Outbreaks , Parvoviridae Infections/virology , Parvovirus B19, Human , Adolescent , Adult , Brazil/epidemiology , Child , Female , Humans , Male , Serologic Tests , Young AdultABSTRACT
Introduction: Dengue virus infection is a global health problem lacking specific therapy, requiring an improved understanding of DENV immunity and vaccine responses. Considering the recent emerging of new dengue vaccines, here we performed an integrative systems vaccinology characterization of molecular signatures triggered by the natural DENV infection (NDI) and attenuated dengue virus infection models (DVTs). Methods and results: We analyzed 955 samples of transcriptomic datasets of patients with NDI and attenuated dengue virus infection trials (DVT1, DVT2, and DVT3) using a systems vaccinology approach. Differential expression analysis identified 237 common differentially expressed genes (DEGs) between DVTs and NDI. Among them, 28 and 60 DEGs were up or downregulated by dengue vaccination during DVT2 and DVT3, respectively, with 20 DEGs intersecting across all three DVTs. Enriched biological processes of these genes included type I/II interferon signaling, cytokine regulation, apoptosis, and T-cell differentiation. Principal component analysis based on 20 common DEGs (overlapping between DVTs and our NDI validation dataset) distinguished dengue patients by disease severity, particularly in the late acute phase. Machine learning analysis ranked the ten most critical predictors of disease severity in NDI, crucial for the anti-viral immune response. Conclusion: This work provides insights into the NDI and vaccine-induced overlapping immune response and suggests molecular markers (e.g., IFIT5, ISG15, and HERC5) for anti-dengue-specific therapies and effective vaccination development.