Serum proteome and cytokine analysis in a longitudinal cohort of adults with primary dengue infection reveals predictive markers of DHF - PubMed (original) (raw)
Serum proteome and cytokine analysis in a longitudinal cohort of adults with primary dengue infection reveals predictive markers of DHF
Yadunanda Kumar et al. PLoS Negl Trop Dis. 2012.
Abstract
Background: Infections caused by dengue virus are a major cause of morbidity and mortality in tropical and subtropical regions of the world. Factors that control transition from mild forms of disease such as dengue fever (DF) to more life-threatening forms such as dengue hemorrhagic fever (DHF) are poorly understood. Consequently, there are no reliable methods currently available for early triage of DHF patients resulting in significant over-hospitalization.
Methodology/principal findings: We have systematically examined the proteome, cytokines and inflammatory markers in sera from 62 adult dengue patients (44 DF; 18 DHF) with primary DENV infection, at three different times of infection representing the early febrile, defervescence and convalescent stages. Using fluorescent bioplex assays, we measured 27 cytokines in these serum samples. Additionally, we used multiple mass spectrometry methods for iTRAQ-based comparative analysis of serum proteome as well as measurements of protein adducts- 3-nitrotyrosine and 3-chlorotyrosine as surrogate measures of free radical activity. Using multiple methods such as OPLS, MRMR and MSVM-RFE for multivariate feature selection and classification, we report molecular markers that allow prediction of primary DHF with sensitivity and specificity of >80%.
Conclusions/significance: This report constitutes a comprehensive analysis of molecular signatures of dengue disease progression and will help unravel mechanisms of dengue disease progression. Our analysis resulted in the identification of markers that may be useful for early prediction of DHF during the febrile phase. The combination of highly sensitive analytical methods and novel statistical approaches described here forms a robust platform for biomarker discovery.
Conflict of interest statement
Yadunanda Kumar, Steven Tannenbaum, EngEong Ooi and Jagath Rajapakse have applied for a patent on some of the markers identified in the study. This does not alter the authors' adherence to all the PLOS policies on sharing data and materials.
Figures
Figure 1. Clinical laboratory features and cytokine responses in primary dengue infections.
A–C Hematological analysis of patient blood samples (DF (n = 44) and DHF (n = 18)) showing platelet count (A), white blood cell count (B) and lymphocyte count (C). Mean (with upper standard deviation shown in error bars). Statistical confidence was analyzed by ANOVA kruskall-wallis test (DF vs DHF: *p<0.05, **p<0.01, NS- not significant). (D) Viral titers measured by RT-PCR in the febrile stage shown as mean of genomic copies per ml with p values from two-sided student's T-test. E. K-means clustering analysis of temporal profile of 23 cytokines measured at different stages of infection in 62 dengue patients (44 DF+18 DHF). F. Identity of cytokines in each cluster. Cluster-1 consisted of a single cytokine- IP-10, and is not shown in the figure. Cytokines that clustered differently in DF and DHF groups are labeled by asterisk in F.
Figure 2. Early cytokine responses distinguish DF and DHF patients.
A subset of eight cytokines that exhibited different clustering between DF and DHF patient groups were examined individually. Mean values of IFN-ϒ (A), IP-10 (B), IL-4 (C), IL-1b (D), IL-17 (E), G-CSF (F), VEGF (G) and PDGF-BB (H) from patients (44 DF; 18 DHF) are plotted. Statistical confidence (p<0.05) was analyzed by ANOVA kruskall-wallis test (DF vs DHF: *p<0.05, **p<0.01, ***p<0.001, NS- not significant); dengue (DF or DHF) vs. healthy control: §§§p<0.001, §§p<0.01, §p<0.05, # not significant). Standard deviation from mean across populations is shown in the error bars (upper deviation only).
Figure 3. Analysis of serum protein flux at different stages of dengue infections.
A. Functional grouping of proteins identified in the proteomics analysis (see Table 2) shown as a pie chart with percent of total proteins (n = 35) identified within each group. B–F. Levels of 9 acute phase reactants measured in sera from 24 DF, 10 DHF patients and 10 healthy control samples using a multiplex assay. Levels of serum amyloid A2 (SAA), haptoglobin (HPT), C-reactive protein (CRP), ferritin (FT) and alpha-2-macroglobulin (A2M) shown in picogram per ml. ANOVA Kruskall-Wallis test- dengue (DHF or DF) vs. Control (*p<0.05, **p<0.01, ***p<0.001, NS- not significant), DHF vs. DF within each time point (§ p<0.05, # not significant). Febrile (visit-1), Deferv. (visit-2) Conval. (visit-3).
Figure 4. Markers of macrophage and neutrophil activity are in dengue patient sera.
Total serum CT (A) and NT (B) levels in dengue patients during febrile, defervescence and convalescence stages. Levels of CT and NT measured in 15 healthy samples was found to be below detection limit (not shown). Statistical confidence was analyzed by ANOVA kruskall wallis-test, DF vs DHF (**p<0.01, NS- not significant).
Figure 5. Multivariate statistics reveals predictive serum markers for early classification of DHF.
A. Receiver operator characteristic curve (ROC) analysis of subset groups A (cytokines only), B (cytokines+clinical indicators) and C (cytokines+clinical indicators+protein adducts) (see table-3 for subsets) is shown. Area under curve (AUC), values of >0.85, indicated good performance (see methods) with high sensitivity and specificity.
References
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The study was funded by the Singapore-MIT Alliance for Research and Technology (SMART) Center, Singapore. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
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