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Time since onset of disease and individual clinical markers associate with transcriptional changes in uncomplicated dengue.

van de Weg CA, van den Ham HJ, Bijl MA, Anfasa F, Zaaraoui-Boutahar F, Dewi BE, Nainggolan L, van IJcken WF, Osterhaus AD, Martina BE, van Gorp EC, Andeweg AC - PLoS Negl Trop Dis (2015)

Bottom Line: Sequential whole blood samples from DENV infected patients in Jakarta were profiled using affymetrix microarrays, which were analysed using principal component analysis, limma, gene set analysis, and weighted gene co-expression network analysis.Clinical diagnosis (according to the WHO classification) does not associate with differential gene expression.Overall, we see a shift in the transcriptome from immunity and inflammation to repair and recovery during the course of a DENV infection.

View Article: PubMed Central - PubMed

Affiliation: Department of Viroscience, Erasmus Medical Center, Rotterdam, The Netherlands.

ABSTRACT

Background: Dengue virus (DENV) infection causes viral haemorrhagic fever that is characterized by extensive activation of the immune system. The aim of this study is to investigate the kinetics of the transcriptome signature changes during the course of disease and the association of genes in these signatures with clinical parameters.

Methodology/principle findings: Sequential whole blood samples from DENV infected patients in Jakarta were profiled using affymetrix microarrays, which were analysed using principal component analysis, limma, gene set analysis, and weighted gene co-expression network analysis. We show that time since onset of disease, but not diagnosis, has a large impact on the blood transcriptome of patients with non-severe dengue. Clinical diagnosis (according to the WHO classification) does not associate with differential gene expression. Network analysis however, indicated that the clinical markers platelet count, fibrinogen, albumin, IV fluid distributed per day and liver enzymes SGOT and SGPT strongly correlate with gene modules that are enriched for genes involved in the immune response. Overall, we see a shift in the transcriptome from immunity and inflammation to repair and recovery during the course of a DENV infection.

Conclusions/significance: Time since onset of disease associates with the shift in transcriptome signatures from immunity and inflammation to cell cycle and repair mechanisms in patients with non-severe dengue. The strong association of time with blood transcriptome changes hampers both the discovery as well as the potential application of biomarkers in dengue. However, we identified gene expression modules that associate with key clinical parameters of dengue that reflect the systemic activity of disease during the course of infection. The expression level of these gene modules may support earlier detection of disease progression as well as clinical management of dengue.

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Related in: MedlinePlus

Differential gene expression analysis.Venn diagrams show the overlap between different sets of differentially expressed genes. FDR <0.05, all differentially expressed genes are at least 2-fold up- or down-regulated.
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pntd.0003522.g002: Differential gene expression analysis.Venn diagrams show the overlap between different sets of differentially expressed genes. FDR <0.05, all differentially expressed genes are at least 2-fold up- or down-regulated.

Mentions: To obtain insight into the transcriptional changes that are associated with disease severity and time since admission, we performed differential gene expression analysis and gene set analysis in dengue patient and control transcriptomes (FDR ≤ 0.05 and fold change ≥ 2). We used the 2009 WHO dengue case classification system to group patients and excluded the single case with severe disease from gene expression analysis. Combining data from all time points revealed that 161 genes were up- and 73 genes were downregulated in WS- patients compared to healthy controls (Fig. 2A, S1 Information). In WS+ dengue patients, 186 genes were up- and 100 genes were downregulated relative to healthy controls. There is considerable overlap (216 genes) of differentially expressed genes in both dengue groups, suggesting that similar biological processes are ongoing in both WS- and WS+ dengue patients. Indeed, no genes were differentially expressed when comparing WS- to WS+ dengue patients directly. Next, the transcriptome profiles of samples from day 0 and day 4 since admission were compared to identify genes differentially expressed over time, regardless of disease severity (Fig. 2B, S1 Information). More genes were differentially expressed in time since admission than between WS- and WS+ disease, confirming the PCA results that time since admission has the largest impact on the transcriptome. To study dengue disease effects independently of time since admission, we restricted our analysis to transcriptome profiles from WS-, WS+ and healthy controls at day 0 and day 4 of admission. On day 0, many genes were differentially expressed in each of both dengue groups compared to healthy controls, but no genes were differentially expressed when the severity groups were compared to each other (Fig. 2C). At day 4, the number of differentially expressed genes in WS- and WS+ dengue compared to healthy controls was lower than at day 0 (Fig. 2D, S1 Information). When severity groups were compared at day 4, again no genes were differentially expressed. Taken together, in our study, WS- and WS+ blood transcriptional profiles cannot be distinguished from each other.


Time since onset of disease and individual clinical markers associate with transcriptional changes in uncomplicated dengue.

van de Weg CA, van den Ham HJ, Bijl MA, Anfasa F, Zaaraoui-Boutahar F, Dewi BE, Nainggolan L, van IJcken WF, Osterhaus AD, Martina BE, van Gorp EC, Andeweg AC - PLoS Negl Trop Dis (2015)

Differential gene expression analysis.Venn diagrams show the overlap between different sets of differentially expressed genes. FDR <0.05, all differentially expressed genes are at least 2-fold up- or down-regulated.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4358925&req=5

pntd.0003522.g002: Differential gene expression analysis.Venn diagrams show the overlap between different sets of differentially expressed genes. FDR <0.05, all differentially expressed genes are at least 2-fold up- or down-regulated.
Mentions: To obtain insight into the transcriptional changes that are associated with disease severity and time since admission, we performed differential gene expression analysis and gene set analysis in dengue patient and control transcriptomes (FDR ≤ 0.05 and fold change ≥ 2). We used the 2009 WHO dengue case classification system to group patients and excluded the single case with severe disease from gene expression analysis. Combining data from all time points revealed that 161 genes were up- and 73 genes were downregulated in WS- patients compared to healthy controls (Fig. 2A, S1 Information). In WS+ dengue patients, 186 genes were up- and 100 genes were downregulated relative to healthy controls. There is considerable overlap (216 genes) of differentially expressed genes in both dengue groups, suggesting that similar biological processes are ongoing in both WS- and WS+ dengue patients. Indeed, no genes were differentially expressed when comparing WS- to WS+ dengue patients directly. Next, the transcriptome profiles of samples from day 0 and day 4 since admission were compared to identify genes differentially expressed over time, regardless of disease severity (Fig. 2B, S1 Information). More genes were differentially expressed in time since admission than between WS- and WS+ disease, confirming the PCA results that time since admission has the largest impact on the transcriptome. To study dengue disease effects independently of time since admission, we restricted our analysis to transcriptome profiles from WS-, WS+ and healthy controls at day 0 and day 4 of admission. On day 0, many genes were differentially expressed in each of both dengue groups compared to healthy controls, but no genes were differentially expressed when the severity groups were compared to each other (Fig. 2C). At day 4, the number of differentially expressed genes in WS- and WS+ dengue compared to healthy controls was lower than at day 0 (Fig. 2D, S1 Information). When severity groups were compared at day 4, again no genes were differentially expressed. Taken together, in our study, WS- and WS+ blood transcriptional profiles cannot be distinguished from each other.

Bottom Line: Sequential whole blood samples from DENV infected patients in Jakarta were profiled using affymetrix microarrays, which were analysed using principal component analysis, limma, gene set analysis, and weighted gene co-expression network analysis.Clinical diagnosis (according to the WHO classification) does not associate with differential gene expression.Overall, we see a shift in the transcriptome from immunity and inflammation to repair and recovery during the course of a DENV infection.

View Article: PubMed Central - PubMed

Affiliation: Department of Viroscience, Erasmus Medical Center, Rotterdam, The Netherlands.

ABSTRACT

Background: Dengue virus (DENV) infection causes viral haemorrhagic fever that is characterized by extensive activation of the immune system. The aim of this study is to investigate the kinetics of the transcriptome signature changes during the course of disease and the association of genes in these signatures with clinical parameters.

Methodology/principle findings: Sequential whole blood samples from DENV infected patients in Jakarta were profiled using affymetrix microarrays, which were analysed using principal component analysis, limma, gene set analysis, and weighted gene co-expression network analysis. We show that time since onset of disease, but not diagnosis, has a large impact on the blood transcriptome of patients with non-severe dengue. Clinical diagnosis (according to the WHO classification) does not associate with differential gene expression. Network analysis however, indicated that the clinical markers platelet count, fibrinogen, albumin, IV fluid distributed per day and liver enzymes SGOT and SGPT strongly correlate with gene modules that are enriched for genes involved in the immune response. Overall, we see a shift in the transcriptome from immunity and inflammation to repair and recovery during the course of a DENV infection.

Conclusions/significance: Time since onset of disease associates with the shift in transcriptome signatures from immunity and inflammation to cell cycle and repair mechanisms in patients with non-severe dengue. The strong association of time with blood transcriptome changes hampers both the discovery as well as the potential application of biomarkers in dengue. However, we identified gene expression modules that associate with key clinical parameters of dengue that reflect the systemic activity of disease during the course of infection. The expression level of these gene modules may support earlier detection of disease progression as well as clinical management of dengue.

Show MeSH
Related in: MedlinePlus