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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

Correlations between genes (y axis) and clinical parameters (x-axis).Genes are annotated with a gene symbol; those depicted in (a-d) are from module T-lightyellow; (e-j) are from module X-darkorange. Icons depict the class of the sample (see Fig. 1). Spearman’s Rho correlations and p-values are given in the plot.
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pntd.0003522.g006: Correlations between genes (y axis) and clinical parameters (x-axis).Genes are annotated with a gene symbol; those depicted in (a-d) are from module T-lightyellow; (e-j) are from module X-darkorange. Icons depict the class of the sample (see Fig. 1). Spearman’s Rho correlations and p-values are given in the plot.

Mentions: In order to identify genes that may serve as a marker of immune activation in the early phase of disease, we focused on modules with a strong negative correlation with time after admission. These modules contain genes that are upregulated specifically in the earliest phase of disease that could represent biomarkers for disease progression, including modules M-salmon4, R-cyan, T-lightyellow, U-orange, and X-darkorange. By correlating genes contained in these modules with clinical parameters that mark disease severity, genes associated with can be identified. Five genes in the module T-lightyellow showed a significant direct association with the platelet count (Fig. 6), including two that play a role in immunological processes. The IL-18 receptor accessory protein (IL-18RAP, Fig. 6A) forms the receptor complex with IL-18Rα and is needed for IL-18 signalling. Cytidine deaminase (CDD, gene CDA) is highly expressed by activated granulocytes and serves as a negative feedback mechanism of these cells by inhibiting the function of granulocyte-macrophage colony formation in the bone marrow [23] (Fig. 6B). KCNJ15 and G-protein coupled receptor 27 (GPR27) (Fig. 6C-D) are both described to play a role in insulin secretion [24,25]. In the module X-darkorange, the gene Tropomodulin 1 (TMOD1) was directly associated with the platelet count (Fig. 6E) and the genes Mical2 and dematin (gene EBP49) with SGOT (Fig. 6F-G) all play a role in actin regulation of the cell [26–28]. Seven other genes with an inverse association with SGOT play a role in metabolic processes, including sestrin 3 (SESN3), adiponectin receptor 1 (ADIPOR1) and STE20-related kinase adaptor beta (STRADB) (Fig. 6H-J). Sestrin 3 is required for regulation of the blood glucose levels [29] and sestrins can reduce the levels of reactive oxygen and protect cells against cell death [30]. Adiponectin acts through the adiponectin receptor 1, which results in increased fatty acid oxidation in the liver [31]. Adiponectin activates serine/threonine kinase 1 via its receptor (LKB1) [31]. Interestingly, the gene STE20-related kinase adaptor beta was also significantly associated with the SGOT and is part of a complex involved in the activation of LKB-1. LKB-1 is important in maintaining cell polarity of hepatocytes, which is essential in the formation and maintenance of the bile canalicular network [32]. In summary, we find genes that correlate with clinical parameters and that can be related to either dengue pathogenesis or tissue physiology, suggesting that these genes may be directly associated with the ongoing biological processes in dengue infection.


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)

Correlations between genes (y axis) and clinical parameters (x-axis).Genes are annotated with a gene symbol; those depicted in (a-d) are from module T-lightyellow; (e-j) are from module X-darkorange. Icons depict the class of the sample (see Fig. 1). Spearman’s Rho correlations and p-values are given in the plot.
© Copyright Policy
Related In: Results  -  Collection

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

pntd.0003522.g006: Correlations between genes (y axis) and clinical parameters (x-axis).Genes are annotated with a gene symbol; those depicted in (a-d) are from module T-lightyellow; (e-j) are from module X-darkorange. Icons depict the class of the sample (see Fig. 1). Spearman’s Rho correlations and p-values are given in the plot.
Mentions: In order to identify genes that may serve as a marker of immune activation in the early phase of disease, we focused on modules with a strong negative correlation with time after admission. These modules contain genes that are upregulated specifically in the earliest phase of disease that could represent biomarkers for disease progression, including modules M-salmon4, R-cyan, T-lightyellow, U-orange, and X-darkorange. By correlating genes contained in these modules with clinical parameters that mark disease severity, genes associated with can be identified. Five genes in the module T-lightyellow showed a significant direct association with the platelet count (Fig. 6), including two that play a role in immunological processes. The IL-18 receptor accessory protein (IL-18RAP, Fig. 6A) forms the receptor complex with IL-18Rα and is needed for IL-18 signalling. Cytidine deaminase (CDD, gene CDA) is highly expressed by activated granulocytes and serves as a negative feedback mechanism of these cells by inhibiting the function of granulocyte-macrophage colony formation in the bone marrow [23] (Fig. 6B). KCNJ15 and G-protein coupled receptor 27 (GPR27) (Fig. 6C-D) are both described to play a role in insulin secretion [24,25]. In the module X-darkorange, the gene Tropomodulin 1 (TMOD1) was directly associated with the platelet count (Fig. 6E) and the genes Mical2 and dematin (gene EBP49) with SGOT (Fig. 6F-G) all play a role in actin regulation of the cell [26–28]. Seven other genes with an inverse association with SGOT play a role in metabolic processes, including sestrin 3 (SESN3), adiponectin receptor 1 (ADIPOR1) and STE20-related kinase adaptor beta (STRADB) (Fig. 6H-J). Sestrin 3 is required for regulation of the blood glucose levels [29] and sestrins can reduce the levels of reactive oxygen and protect cells against cell death [30]. Adiponectin acts through the adiponectin receptor 1, which results in increased fatty acid oxidation in the liver [31]. Adiponectin activates serine/threonine kinase 1 via its receptor (LKB1) [31]. Interestingly, the gene STE20-related kinase adaptor beta was also significantly associated with the SGOT and is part of a complex involved in the activation of LKB-1. LKB-1 is important in maintaining cell polarity of hepatocytes, which is essential in the formation and maintenance of the bile canalicular network [32]. In summary, we find genes that correlate with clinical parameters and that can be related to either dengue pathogenesis or tissue physiology, suggesting that these genes may be directly associated with the ongoing biological processes in dengue infection.

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