Serum biomarkers and anti-flavivirus antibodies at presentation as indicators of severe dengue

• Type of Material: Article
• Authors: Cynthia Bernal, Universidad Nacional de Asunción; Sara Ping, Emory University; Alejandra Rojas, Universidad Nacional de Asunción; Oliver Caballero, Universidad Nacional de Asunción; Victoria Stittleburg, Emory University; Yvalena de Guillen, Universidad Nacional de Asunción; Patricia Langjahr, Universidad Nacional de Asunción; Benjamin A. Pinsky, Stanford University; Marta Von-Horoch, Hospital Central—Instituto de Previsión Social; Patricia Luraschi, Hospital Central—Instituto de Previsión Social; Sandra Cabral, Hospital Central—Instituto de Previsión Social; Maria Cecilia Sanchez, Hospital Central—Instituto de Previsión Social; Aurelia Torres, Hospital Central—Instituto de Previsión Social; Fatima Cardozo, Universidad Nacional de Asunción; Jesse Waggoner, Emory University
• Language: English
• Date: 2023-02-01
• Publisher: PUBLIC LIBRARY SCIENCE
• Publication Version: Final Published Version
• Copyright Statement: © 2023 Bernal et al
• License: Creative Commons Attribution 4.0 International
• Final Published Version (URL): http://dx.doi.org/10.1371/journal.pntd.0010750
• Title of Journal or Parent Work: PLOS NEGLECTED TROPICAL DISEASES
• Volume: 17
• Issue: 2
• Start Page: e0010750
• End Page: e0010750
• Grant/Funding Information: Research was supported by the Doris Duke Charitable Foundation (Clinical Scientist Development Award 2019089 to JJW); National Institute of Allergy and Infectious Diseases (R21 AI146443 to AR, BAP, and JJW); and the Consejo Nacional de Ciencia y Tecnología (CONACYT) with support from the Fondo para la Excelencia de la Educación y la Investigación, both in Paraguay (PINV18-1295 to AR and POSG17-59 to CB). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
• Keywords: Life Sciences & Biomedicine; RISK-FACTORS; VIRUS; LABORATORY FEATURES; Tropical Medicine; HEMORRHAGIC-FEVER; INFECTION; Parasitology; REVERSE TRANSCRIPTION-PCR; VIRAL LOAD; DISEASE SEVERITY; NONSTRUCTURAL PROTEIN-1; Science & Technology; DEPENDENT ENHANCEMENT; Infectious Diseases
• Research Categories: Biology, Virology; Biology, Cell; Biology, Parasitology

Abstract

Background Dengue is the most common vector-borne viral disease worldwide. Most cases are mild, but some evolve into severe dengue (SD), with high lethality. Therefore, it is important to identify biomarkers of severe disease to improve outcomes and judiciously utilize resources. Methods/Principal findings One hundred forty-five confirmed dengue cases (median age, 42; range <1–91 years), enrolled from February 2018 to March 2020, were selected from an ongoing study of suspected arboviral infections in metropolitan Asunción, Paraguay. Cases included dengue virus types 1, 2, and 4, and severity was categorized according to the 2009 World Health Organization guidelines. Testing for anti-dengue virus IgM and IgG and serum biomarkers (lipopolysaccharide binding protein and chymase) was performed on acute-phase sera in plate-based ELISAs; in addition, a multiplex ELISA platform was used to measure anti-dengue virus and anti-Zika virus IgM and IgG. Complete blood counts and chemistries were performed at the discretion of the care team. Age, gender, and pre-existing comorbidities were associated with SD vs. dengue with/without warning signs in logistic regression with odds ratios (ORs) of 1.07 (per year; 95% confidence interval, 1.03, 1.11), 0.20 (female; 0.05,0.77), and 2.09 (presence; 1.26, 3.48) respectively. In binary logistic regression, for every unit increase in anti-DENV IgG in the multiplex platform, odds of SD increased by 2.54 (1.19–5.42). Platelet count, lymphocyte percent, and elevated chymase were associated with SD in a combined logistic regression model with ORs of 0.99 (1,000/μL; 0.98,0.999), 0.92 (%; 0.86,0.98), and 1.17 (mg/mL; 1.03,1.33) respectively. Conclusions Multiple, readily available factors were associated with SD in this population. These findings will aid in the early detection of potentially severe dengue cases and inform the development of new prognostics for use in acute-phase and serial samples from dengue cases.