Abstract
Dengue fever (DF) is a major global health burden with a pathophysiology that is still incompletely understood. Biomarkers that predict and explain susceptibility to DF and its progression to its more severe hemorrhagic form are much needed. DF is endemic in tropical and subtropical regions of the world, with a rapidly increasing incidence of disease severity. We conducted a clinical biomarker discovery study using both a case-control and longitudinal study design. Plasma proteome alterations in patients with DF (n = 12) and dengue hemorrhagic fever (DHF, n = 24) were analyzed in comparison to healthy controls (HCs, n = 16), using the isobaric tags for relative and absolute quantification (iTRAQ)-based quantitative proteomics methodology (false discovery rate of 1%, ≥2 peptides). Several proteins such as the alpha-2 macroglobulin, angiotensinogen, apolipoprotein B-100, serotransferrin, and ceruloplasmin were upregulated (fold change >1.2) in all DHF cases, and downregulated in DF (fold change <0.83), compared with HCs. Plasma cytokine profiling (8 DF, 8 DHF, and 8 HC) on two consecutive time points, at day 0 (day of admission) and days 5-7, found significant elevation in IL-1RA, IL-7, TNF-α, MCP1-MCAF, and MIP-1β levels, but only in the DHF cases, which is the severe disease, and not in DF, compared with HCs (p < 0.05). These new observations on changes in the plasma proteome and cytokine profiles in patients with dengue infection identify several putative molecular leads for future biomarker development and precision medicine in relation to forecasting DF disease severity.
Original language | English |
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Pages (from-to) | 665-677 |
Number of pages | 13 |
Journal | OMICS A Journal of Integrative Biology |
Volume | 21 |
Issue number | 11 |
Early online date | 01 Nov 2017 |
DOIs | |
Publication status | Early online date - 01 Nov 2017 |
Externally published | Yes |
Keywords
- Adolescent
- Adult
- Biomarkers/blood
- Case-Control Studies
- Cytokines/blood
- Dengue/blood
- Endemic Diseases
- Female
- Humans
- Incidence
- Longitudinal Studies
- Male
- Middle Aged
- Precision Medicine
- Proteomics/methods
- Severity of Illness Index
- Time Factors