Conceived and designed the experiments: SD CS VD PB PCP. Performed the experiments: SD CS PCP. Analyzed the data: SD CS AB PR PCP. Contributed reagents/materials/analysis tools: VD SO PTL NC SN PB PCP. Wrote the paper: SD PCP. Contributed to obtainment of funding: HT.
The authors have declared that no competing interests exist.
Deciphering host responses contributing to dengue shock syndrome (DSS), the life-threatening form of acute viral dengue infections, is required to improve both the differential prognosis and the treatments provided to DSS patients, a challenge for clinicians.
Based on a prospective study, we analyzed the genome-wide expression profiles of whole blood cells from 48 matched Cambodian children: 19 progressed to DSS while 16 and 13 presented respectively classical dengue fever (DF) or dengue hemorrhagic fever grades I/II (DHF). Using multi-way analysis of variance (ANOVA) and adjustment of p-values to control the False Discovery Rate (FDR<10%), we identified a signature of 2959 genes differentiating DSS patients from both DF and DHF, and showed a strong association of this DSS-gene signature with the dengue disease phenotype. Using a combined approach to analyse the molecular patterns associated with the DSS-gene signature, we provide an integrative overview of the transcriptional responses altered in DSS children. In particular, we show that the transcriptome of DSS children blood cells is characterized by a decreased abundance of transcripts related to T and NK lymphocyte responses and by an increased abundance of anti-inflammatory and repair/remodeling transcripts. We also show that unexpected pro-inflammatory gene patterns at the interface between innate immunity, inflammation and host lipid metabolism, known to play pathogenic roles in acute and chronic inflammatory diseases associated with systemic vascular dysfunction, are transcriptionnally active in the blood cells of DSS children.
We provide a global while non exhaustive overview of the molecular mechanisms altered in of DSS children and suggest how they may interact to lead to final vascular homeostasis breakdown. We suggest that some mechanisms identified should be considered putative therapeutic targets or biomarkers of progression to DSS.
Acute dengue virus infections are a major public health problem for many tropical and sub-tropical countries and an increasing risk for the worldwide population
DSS is regarded as a vascular disease involving a complex interplay between virus, whole blood cells and microvascular territories
Efforts to identify soluble biomarkers of severe dengue differentiating uncomplicated dengue infections from severe ones has led to the identification of a diversity of cytokines, chemokines, endothelial agonists or soluble endothelial molecules
Understanding the molecular basis of DSS and identifying relevant DSS biomarkers thus remains a major challenge
Such a bench-to-bedside medical research has gained more and more interest in the recent years. Indeed, it allowed improving the understanding of pathophysiological processes underlying systemic critical illnesses such as sterile and non sterile systemic inflammatory responses syndromes (SIRS), allowing the identification of relevant disease biomarkers and of new putative therapeutic targets
Genome-wide expression studies aimed at deciphering molecular responses altered in the whole blood cells of adults
We report here the results of a prospective study comparing the whole blood genome-wide expression profiles of 48 matched Cambodian children recruited during the huge 2007 dengue outbreak who presented with classical dengue fever (DF), dengue hemorrhagic fever grades I/II (DHF) or dengue shock syndrome (DSS), according to the 1997 WHO classification of dengue severity
The global study and all protocols presented here were approved by the national Cambodian ethical committee. Written informed consent was obtained from the legal guardians of each child. To ensure strict anonymity regarding the patients, samples were encoded as PLxxx (Plasma Leakage).
Inclusion criteria retained were: age (1 to 15 years old); positive diagnosis of acute dengue infection assessed by different methods; absence of known chronic inflammatory disease or ongoing acute co-infection at the time of inclusion.
An eligible cohort of 83 dengue-infected children hospitalised at the Kampong Cham provincial hospital, Cambodia, was prospectively enrolled from July to September 2007 during the huge 2007 dengue outbreak in Cambodia, characterized by a high number of DSS cases.
Children diagnosed with acute dengue infections were classified at admission as classical dengue fever (DF), dengue hemorrhagic fever (DHF) or dengue shock syndrome (DSS) based on the 1997 WHO criteria
To increase the probability to identify gene signatures specific of DSS, we chose to include only symptomatic dengue-infected classified DF, DHF and DSS, but no healthy or non-dengue children in the present study. This is based on the rationale that comparing DF, DHF and DSS patients together should improve the probability to identify a DSS-specific gene signature, while including an external non dengue control group should increase the probability to identify a general dengue-related signature but should be less powerful at identifying a signature of severe dengue disease.
DF, DHF and DSS patients whole blood samples selected for the present study corresponded to comparable duration of illness after onset of fever: all were collected within a window of time comprised between 3 days and 7 days after onset of fever (being considered day 0). For most DSS patients, this generally corresponded to the day of cardiovascular decompensation (shock) or the day after, except for 3 (PL017, PL033, PL047) and 2 DSS (PL005, PL101) for whom blood was collected respectively 2 and 3 days after onset of shock.
Patients' samples selected for the present study were also carefully matched for age, gender, viral serotype (when identified) and immunological status (primary or secondary, according to reference assays described in diagnosis methods) towards dengue infection.
Diagnosis assays carried out as described thereafter, indicated that about 90% of all dengue-infected children had secondary infection.
All diagnosis assays were carried out at the Institut Pasteur in Cambodia, the National Reference Center for arboviral diseases in Cambodia. IgM capture ELISA and Hemagglutination-inhibition were performed on paired sera collected at admission and at discharge, and systematically tested for both dengue and Japanese Encephalitis virus, another flavivirus endemic in Cambodia, as described previously
Whole blood samples (2.5 ml) were collected on PAXgene™ Tubes (PreAnalytiX™) further stored at −80°C, before being sent to France in dry ice. Extraction of series of 24 matched samples (DF, DHF and DSS) was done using PAXgene™ Blood RNA kits (PreAnalytiX™) rapidly after collection. Purified total RNAs kept at −80°C were processed for hybridization on genome-wide DNA microarrays within one month.
All RNAs were checked for integrity using the 2100 BioAnalyzer (Agilent Technologies) and quantified using a ND-1000 spectrophotometer (NanoDrop Technologies). Cyanine-3-labeled cRNA was generated from 0.3 µg of RNA using the One-Color Low RNA Input Linear Amplification kit (Agilent) according to the manufacturer's instructions, followed by purification on RNAeasy column (QIAGEN). All amplified cRNAs were checked for dye incorporation, cRNA yield and amplification profile. Only those fitting all quality criteria were fragmented for further hybridization on microarrays. Samples from DF, DHF and DSS patients were then carefully matched and hybridized onto Agilent Whole Human Genome (4×44K) Oligo Microarrays (G4112F). Microarrays were scanned using an Agilent DNA microarray scanner G2505B.
All microarray data is MIAME compliant and the raw and normalized data have been deposited in the MIAME compliant database Gene Expression Omnibus
Individual microarray quality was evaluated based on QC report, pair-wise MA-plots, and box plots. Intra-array normalization of raw signals from the 48 microarrays was done using Feature Extraction software 9.1.3.1 (Agilent). Microarrays normalized data were further exported into the Limma package
Statistical analysis were was performed using the TIGR MeV (MultiExperiment Viewer) v 4.4 software (
Briefly, total RNA extracted from whole blood samples was reverse-transcripted using the High Capacity cDNA RT kit (Applied Biosystems Inc) and random primers. Real-time PCR were carried out using the FastStart Universal Probe Master (ROX) (Roche) and real-time PCR primers designed using the Universal Probe Library (UPL) Assay Design Center (Roche). Amplification products were run on an ABI-PRISM 7900HT (Applied Biosystems). Cycle threshold Ct values were automatically calculated and value obtained for each gene amplified was normalized by subtracting the Ct corresponding to amplification of the HPRT1 gene (ΔCt) for the same sample. Correlation between ΔCt values obtained by real-time PCR and corresponding expression values from microarrays was estimated using Spearman correlation coefficient.
Bio-informatics-based analysis using the demonstration version 7.1 of Ingenuity Pathway Analysis software (IPA; Ingenuity® Systems,
To identify gene patterns specifically altered in DSS patients, we compared three groups of carefully matched paediatric patients representing the main clinical forms of symptomatic dengue infections DF (n = 16), DHF (n = 13) and DSS (n = 19), according to the 1997 WHO classification criteria of dengue severity
DF ( |
DHF ( |
DSS ( |
|
Patients characteristics | |||
gender, male |
7 (43%) | 4 (31%) | 7 (37%) |
age, median (IQR), years | 8 (4–9) | 7 (5–8) | 8 (7–9) |
weight, median (IQR), kg | 18 (13–20) | 15 (14–18) | 19 (15–23) |
hospital admission, median (IQR), day after onset of fever (D0) | 2 (1–3) | 2 (2–3) | 4 (3–4) |
Dengue status | |||
viral serotype, |
4/2/8/1/1 | 1/1/10/1/0 | 1/1/10/0/7 |
immunological status, secondary infections, |
14 (88%) | 12 (92%) | 18 (95%) |
Clinical manifestations | |||
tourniquet test (pos/neg/not done) (%) | 56%/44%/0% | 54%/38%/8% | 37%/32%/31% |
hepatomegaly, |
3 (19%) | 6 (46%) | 17 (89%) |
gastro-intestinal bleeding, gingivorragy, hematemesis, melena, |
0 | 1 (8%) | 6 (32%) |
Blood pressure | |||
heart frequency, median (IQR), pulse per minute | 113 (100–124) ( |
120 (112–120) | Not perceptible ( |
pulse pressure, median (IQR ), mm Hg | 40 (30–45) | 30 (30–40) | 15 (10–20) ( |
Haematological parameters | |||
thrombocytopenia (platelet count <100000/mm3), % | 15% ( |
55% ( |
94% ( |
hematocrit, median (IQR), % | 36.5 (35–39) ( |
39.75 (38–42) ( |
42.5 (38–45) ( |
hemoconcentration (hematocrit >20%), |
1 (6%) | 3 (23%) | 17 (89%) |
white blood cells, median (IQR), number/mm3 | 6600 (5500–9900) ( |
6450 (6200–7400) ( |
6900 (4800–6900) ( |
neutrophils, median (IQR), number/mm3 | 3900 (2900–7600) ( |
3950 (3500–4200) ( |
2500 (2200–3800)( |
lymphocytes, median (IQR), number/mm3 | 1600 (1400–2100) ( |
1850 (1500–1900) ( |
2200 (1500–3200) ( |
Supportive medical care | |||
oxygen supplementation, |
0 | 0 | 15 (79%) |
perfusion of colloid (dextran 40), |
0 | 0 | 14 (74%) |
perfusion of human plasma, |
0 | 0 | 8 (42%) |
DENV, dengue virus; DF, dengue fever; DHF, dengue hemorrhagic fever; DSS, dengue shock syndrome; IQR, interquartile range; n, number.
n = x : with x : number of patients for which the data is available.
Since microarray data analysis can be affected by a number of bias
Based on ANOVA analysis, lists of genes differentially expressed between DF, DHF and DSS groups were generated using different false discovery rate (FDR) ranging from 0.05 up to 10%. Indeed, low FDR provide more stringent statistical filter while they reduce the number and thus the enrichment of genes differentially expressed. At the opposite, higher FDR, while statistically accepting a higher number of false positive genes, also provide larger and enriched gene lists that should be more informative when searching to identify molecular pathways. Based on this rationale, we chose to work using the gene list generated at FDR 10 after we verified by a different statistical method currently used for the analysis of microarrays data, SAM (Significant Analysis of Microarray)
The biological relevance of those differentially expressed genes was assessed using local ANOVA that allows evaluating the contribution of the main variable, disease phenotype, and that of other putative confounding variables related to patients (age, gender, day of blood sampling, viral serotype) and to technical steps (effect of independent RNA extractions, amplifications and hybridization) on variations of expression levels of those 2959 genes. This confirmed that the disease phenotype strongly influenced the variations of expression of the 2959 genes differentially expressed between the three patient groups, reinforcing the biological significance of this set of genes (
Unsupervised hierarchical clustering based on the 2959 gene signature identified was then applied to the 48 children gene expression profiles. This allows clustering the patients whose gene expression profiles are the more similar independently of their disease phenotype subtype. As a result, the 48 patients expression profiles were organized in two major subsets (
The clustering is based on the 2959 gene list (3515 clones, detailed in
We confirmed the robustness of the DSS-gene signature using the iterative Support Vector Machine (SVM) classifier learning method
To validate microarray data, we carried out real-time RT-PCR focusing on nine genes strongly associated with the DSS-gene signature, using 15 patients samples (five from each disease phenotype subtype: DF, DHF and DSS). Results obtained strongly correlate microarray data (
Filtering genes from those having the highest to the lowest statistical association with the disease phenotype variable (
Indeed, IPA analysis identified that 163 canonical pathways were significantly associated with those genes (data not shown) with a large proportion of immune-related pathways in the first top 30 (
The significance of the association between data set and canonical pathway was estimated by the p-value (Fischer's exact test; left axis) and the ratio (right axis) of genes that maps to each canonical pathway.
Genes in green and red are respectively under- and over-expressed in the DSS-gene signature. Genes in white are other genes present in the canonical pathway but absent from the DSS-gene signature. DSS: Dengue Shock Syndrome.
When comparing our results to those of colleagues who reported gene or protein signatures associated with DSS, we identified some transcripts encoding proteins considered putative markers of severe dengue. This includes non exhaustively the acute phase pentraxin-related protein PTX3
IFN type I-related transcripts, of which abundance was shown to be decreased in DSS patients by others
Integrative analysis of the most significant individual genes and canonical pathways extended the finding that a large and diverse set of genes related to T but also to NK lymphocyte activity is under-expressed in DSS patients compared to DF and DHF counterparts (
Function | Genes | P-value | Var. |
Th1 differentiation | RUNX3, STAT4, TBX21 | <0.00001 to 0.00242 | 25 to 42 |
Th2 differentiation | GATA3, STAT5A | 0.00003 to 0.00225 | 17 to 32 |
Cytotoxic T lymphocyte functions | CTSW, PRF1 | 0.00005 to 0.00231 | 21 to 33 |
T lymphocyte activation | IL2RB, IL2RG | 0.00014 to 0.00039 | 29 to 35 |
Cooperation with antigen-presenting cells | CD40LG | 0.00105 | 21 |
Recruitment and interaction of T lymphocytes with endothelium | ITGAL, XCL1, XCL2 | <0.00001 to 0.00214 | 20 to 33 |
Inhibitory NK cell receptors | KLRD1 | 0.00001 | 31 |
Activating NK cell receptors | NCR1, NCR3, CD160 | <0.00001 to 0.00069 | 28 to 39 |
Cytotoxic molecules | GZMM | <0.00001 | 32 |
Receptors for NK cells homing to peripheral tissues | S1PR5 | <0.00001 | 48 |
Differentiation factors of NK cells | FLT3LG, |
0.00088 to 0.00774 | 13 to 21 |
Suppression of T lymphocytes and NK cells response | <0.00001 | 60 to 63 | |
NFκB-related genes | 0.00001 to 0.00506 | 9 to 31 |
HUGO gene names are indicated. When genes were represented by several clones on the microarray, p-value and variance medians were calculated. Genes in regular and bold are respectively under- and over-expressed in dengue shock syndrome patients.
percentage of variance associated to disease phenotype.
Our analysis also revealed that DSS whole blood cells from children over-expressed an enriched pattern of anti-inflammatory and repair/tissue remodeling genes (
Function | Gene Symbol | P-value | Var. |
Anti-inflammatory genes | |||
immunoregulatory molecules | 0.00430 | 20 | |
anti-proteases | <0.00001 to 0.00081 | 19 to 49 | |
metalloproteinase inhibitor | 0.00183 | 19 | |
decoy receptor | 0.00077 | 30 | |
free-heme scavenger molecules | <0.00001 to 0.00064 | 26 to 46 | |
complement regulatory molecules | <0.00001 to 0.00096 | 24 to 60 | |
Tissue remodeling and repair genes | |||
metallopeptidase | 0.00001 | 33 | |
extracellular matrix components | <0.00001 to 0.00309 | 18 to 34 | |
pro-angiogenic factors | 0.00004 to 0.00236 | 25 to 30 | |
others | <0.00001 to 0.00054 | 18 to 44 |
HUGO gene names are indicated. When genes were represented by several clones on the microarray, p-value and variance medians were calculated. Genes in regular and bold are respectively under- and over-expressed in dengue shock syndrome patients.
percentage of variance associated to disease phenotype.
Danger-associated molecular pattern (DAMP) activity.
Thus, DSS children whole blood cells have a global decreased abundance of T and NK cell-related transcripts but an increased abundance of anti-inflammatory and repair/remodeling transcripts at the time of cardiovascular decompensation.
When searching for pro-inflammatory gene patterns that may be relevant to DSS pathophysiology and particularly to systemic inflammation and vascular dysfunction, we identified three major pro-inflammatory gene patterns. Interestingly, all are related to innate defense and host lipid metabolism, and considered major pathogenic mechanisms in other systemic inflammatory diseases.
As shown in
Function | Gene Symbol | P-value | Var. |
Main cellular origin | Ref |
microbicidal peptides | <0.00001 to 0.00007 | 0.25 to 0.44 | PMN neutro, EpC | ||
<0.00001 | 0.34 | PMN neutro, Mo, mast cells, EpC | |||
<0.00001 | 0.41 | PMN neutro, inflammed EpC | |||
calgranulin proteins | <0.00001 to 0.00014 | 0.18 to 0.38 | PMN neutro, Mo/Mac | ||
<0.00001 | 0.33 | PMN neutro | |||
granulocyte enzymes | 0.00017 | 0.25 | Mo/Mac, Eo, EpC, PMN neutro | ||
0.00024 | 0.25 | PMN neutro, Mo, subtypes of tissue Mac | |||
<0.00001 | 0.29 | Eo, Mo, PMN neutro | |||
<0.00001 | 0.49 | PMN neutro | |||
<0.00001 | 0.36 | PMN neutro | |||
<0.00001 | 0.39 | PMN neutro | |||
pro-inflammatory cytokines and related molecules | 0.00052 | 0.21 | Kupffer cells, activated Mac, Mo, DC, EpC | ||
IL18BP | 0.00710 | 0.20 | T cells, peripheral blood leukocytes, EC |
HUGO gene names are indicated. When genes were represented by several clones on the microarray, p-value and variance medians were calculated. Genes in regular and bold are respectively under- and over-expressed in dengue shock syndrome patients. DC, dendritic cell; EC, endothelial cell; Eo, eosinophil; EpC, epithelial cell; Mac, macrophage, Mo, monocyte; PMN neutro, polymorphonuclear neutrophil; RAGE, receptor for advanced glycation end products.
percentage of variance associated to disease phenotype.
Danger-associated molecular pattern (DAMP) activity.
The second pro-inflammatory gene pattern identified is typical of altered homeostasis of cholesterol in monocytes/macrophages that characterises inflammatory lipid-laden monocytes/macrophages (lipid-laden Mo/Mac), a subtype of foam cells initiating vascular lesions in metabolic inflammatory diseases
Function | Gene Symbol | P-value | Var. |
Disease | Ref |
Lipid-laden Mo/Mac-related genes | |||||
scavenger receptors of modified LDL in Mo/Mac | <0.00001 to 0.00013 | 0.21 to 0.32 | metabolic diseases | ||
lipid nuclear receptor/signalisation by lipids | 0.00007 to 0.00732 | 0.21 to 0.34 | metabolic diseases | ||
efflux of modified cholesterol from Mo/Mac | NPC1 | 0.00005 | 0.32 | Niemann-Pick disease, atherosclerosis | |
ABCA10 | 0.00016 | 0.14 | none | ||
migrating Mo/resident Mac chemokine receptors | 0.00001 to 0.00099 | 0.22 to 0.40 | atherosclerosis | ||
other lipid-laden-related Mo/Mac genes | <0.00001 to 0.00092 | 0.20 to 0.26 | metabolic diseases | ||
<0.00001 | 0.48 | Gaucher's disease, atherosclerosis | |||
0.00001 | 0.42 | familial hypercholesterolemia | |||
<0.00001 | 0.49 | metabolic and inflammatory diseases | |||
anti-oxydant enzymes | LCAT, PAFAH2 | 0.00196 to 0.00461 | 21 to 26 | metabolic diseases | |
Arachidonic acid pathway-related genes | |||||
phospholipase | 0.00003 | 0.21 | rheumatoid arthritis | ||
eicosanoid synthesis enzymes | <0.00001 to 0.00123 | 0.22 to 0.63 | metabolic and inflammatory diseases, asthma, cancer | ||
leukotrienes convertion enzyme | 0.00003 | 0.32 | none | ||
leukotriene transporter | 0.00010 | 0.31 | asthma | ||
lipid oxidation | 0.00011 | 0.33 | atherosclerosis | ||
cytochrome P450 superfamily enzymes | <0.00001 to 0.00686 | 10 to 32 | Vascular inflammation |
HUGO gene names are indicated. When genes were represented by several clones on the microarray, p-value and variance medians were calculated. Genes in regular and bold are respectively under- and over-expressed in dengue shock syndrome patients.
percentage of variance associated to disease phenotype.
Thus, a gene expression pattern similar to that characterizing lipid-laden monocytes, is activated in the whole blood cells of DSS children at the time of cardiovascular decompensation.
The third pro-inflammatory gene pattern associated with the DSS-gene signature is characteristic of the metabolic pro-inflammatory arachidonic-acid pathway, one of the lipid metabolic pathways identified through IPA. As shown in
Thus, a transcriptional signature related to the lipid-related metabolic arachidonic acid pathway is activated in the whole blood cells of DSS children at the time of cardiovascular decompensation.
Numerous studies have addressed the pathophysiology of DSS, the more frequent and severe complication of dengue infections. Despite important findings, only partial understanding of the cellular and molecular processes that may support this life-threatening syndrome has been obtained, and we still lack a comprehensive overview of the complete figure of alterations that contribute to – or reflect – the setting-up of the shock syndrome. This could allow the improvement of patients' management and treatment, a major challenge for clinicians. We designed a study aimed at analysing the quasi-global transcriptome of whole blood cells from dengue paediatric patients, looking at every modification that could make sense to the understanding of the pathogenic process. The capacity of such an exhaustive approach to identify relevant host responses, of which unsuspected pathways has been demonstrated in other systemic inflammatory syndromes such as human sepsis or post-trauma sterile SIRS
First, we identify a transcriptional signature of the DSS, differentiating DSS from the other forms of dengue infection and characterizing DSS as a unique and specific entity. Giving particular attention to study design and statistical analysis, we identify a large and robust gene expression profile of 2959 genes that discriminates DSS paediatric patients from other dengue patients, DF or DHF, who did not progress to shock, whatever the supportive treatment they received. Importantly, DSS children clustered together whatever they were considered as having primary or secondary dengue infection, while secondary infections represented the majority of DF, DHF and DSS children recruited (see
Two important questions arise about the DSS-associated transcriptional profile: are the observed modifications of genes expression the cause or the consequence of the pathology, and could these modifications have a predictive value? We cannot definitively answer these questions from the present study, in part because blood samples were collected at the onset of shock (14 out of the 19 DSS patients) or after (5 patients). Functional study of each individual pathway will be required to fully understand the role of each gene in a complex network of molecular interactions.
The ability of some genes transcripts or genes products to accurately predict progression to DSS should be evaluated by multivariate regression models
Second, while present results confirm some putative DSS-related biomarkers, it also reveals unreported alterations that make sense to hypovolemic shock pathophysiology. This reinforces the ability of a global and “open mind” approach to identify molecular processes relevant to the studied pathology. Blood cells transcriptional profiles clearly reveal alterations of different immune responses and the activation of a large pro-inflammatory response. A significant proportion of genes of which expression is modified are related to host innate immunity, lymphocyte functions and lipid metabolism in particular. This genome-wide expression analysis also confirms the over-expression of individual biomarkers previously associated with severe dengue, such as the acute phase pentraxin-related protein PTX3, the pro-inflammatory IL-18 cytokine or the anti-inflammatory IL-10 cytokine (
Our results differ however from those reported by Long
Third, unsuspected mechanisms identified in DSS patients could contribute importantly to the pathophysiology of this severe syndrome, as supported by similarities between those DSS-related alterations and other critical syndromes. Interestingly, a number of immune, repair-remodeling and metabolic-related related pathways are simultaneously altered in the blood cells of DSS children at the onset of shock. In particular, T and NK lymphocyte transcriptional responses are globally impaired while genes implicated in compensatory anti-inflammatory and repair/remodeling responses and in innate immune responses are over-expressed. This highlights the complexity of biological responses at the time of dengue shock syndrome, and points out similarities between DSS and other critical syndromes such as severe sepsis, or post-trauma SIRS that are similarly characterized by depressed T lymphocyte responses but over-expressed innate immunity
Reduced abundance of a number of T-lymphocyte related transcripts at the time of DSS may reflect a feed-back mechanism aimed at limiting an initial early T lymphocyte activation, reported to occur in patients who further progress to severe dengue
Over-expression in the blood of DSS children of several repair and remodeling genes encoding extracellular matrix proteins, vasoactive mediators and matrix metalloproteases such as the MMP9, likely reflects a compensatory response to inflammatory insults, and a number of those genes products are now considered putative biomarkers in systemic inflammatory syndromes such as severe sepsis
While previous transcriptional studies failed to identify pro-inflammatory gene patterns in the blood cells of DSS patients
Activation of a pro-inflammatory defence gene pattern in DSS patients' blood cells (
Alteration of a gene pattern related to homeostasis of cholesterol in monocytes/macrophages (Mo/Mac) in the blood cells of DSS children (
Recent knowledge has shown that those atypical monocytes produce a large array of pro-inflammatory mediators such as ROS, metalloproteases, eicosanoids, and pro-inflammatory adipokines, making these cells potent contributors to vascular damages, systemic inflammation and major metabolic changes such as insulin-resistance
Altered homeostasis of cholesterol in blood cells from DSS patients could also favour replication of dengue viruses into host cells
The factors contributing to altered homeostasis of cholesterol in the blood cells of DSS children at time of shock are numerous. Increased lipid peroxydation activity
Transcriptional activation of the lipid-related arachidonic acid pathway in the whole blood cells of DSS children at the time of shock was another pro-inflammatory mechanism relevant to the pathophysiology of DSS
Fourth, DAMPs and TLRs could be a link from primary to secondary inflammation, leading to DSS. Occurrence of DSS in only some patients at the late phase of infection is likely due to an inadequate control or an amplification of the primary inflammatory response aimed at fighting infection. The pro-inflammatory molecular responses activated in the blood cells of DSS children at time of shock involve a diversity of innate immune mediators that may amplify a first-line inflammatory response mediated by TNF, IL-6 or IL-1, thus contributing to a secondary inflammatory loop. Indeed, a number of repair/remodeling and of defence gene products over-expressed in DSS patients blood cells are considered endogenous danger signals or Danger-Associated Molecular Patterns (DAMPs) (
Amplification of inflammation during DSS through direct signalling by molecules harbouring DAMP activity via TLRs, is also supported by the increased abundance of DAMP-induced transcripts as those encoding the pro-inflammatory IL-18 cytokine or the NLRC4/CARD12 intracellular sensor
To summarize, we report the identification of a specific gene expression profile in the blood cells of DSS children at time of shock, characterizing DSS as a unique entity at the transcriptional level whatever the immunological status of children regarding primary or secondary infection. Major immunological alterations identified at the time of shock are characterized by an altered balance between depressed T lymphocyte responses and exacerbated compensatory and pro-inflammatory innate immune responses that may, finally, be detrimental to the host
Based on recent knowledge on molecular mechanisms altered in other systemic inflammatory diseases, DSS may result from a complex pro-inflammatory network involving a diversity of innate immune effectors sustaining a secondary systemic inflammatory loop, leading in turn to vascular homeostasis breakdown and systemic microcirculatory failure characterizing DSS (
After induction of a first inflammatory and anti-viral response to dengue virus, disease resolution generally occurs around time of defervescence for most dengue-infected patients. Some patients however progress towards a life-threatening dengue shock syndrome. Results obtained in this study suggest that in those patients, a second inflammatory amplification loop, which involves a diversity of pro-inflammatory responses related to innate immunity, occurs and leads to a major inflammatory systemic syndrome and to vascular homeostasis breakdown. The putative role of different markers identified in vascular endothelial dysfunction is indicated. Thin black arrow, release of; Bold black arrow, interaction between; Punctuated black arrow, chemotactic effect; Thin red arrow, biological activity; Bold red arrow, direct activity on endothelium. DAMPs, danger-associated molecular pattern; GAG, glycosaminoglycane; ROI, reactive oxygen intermediates; TLR, Toll-like receptor.
We suggest that drugs available to treat metabolic and other systemic chronic inflammatory diseases could be considered for the treatment of dengue-infected patients before shock occurs, and that a number of bio-markers found altered in DSS patients blood cells should be evaluated. as putative predictive markers of progression to DSS.
Validation of microarray results by RT-PCR. Pearson's correlation was calculated between microarray expression signals (horizontal axis) and Delta Ct values from real-time PCR (vertical axis) for nine genes highly associated to dengue shock syndrome. ** Correlation is significant at 0.01.
(4.94 MB TIF)
Clinical and biological characteristics of each DF, DHF and DSS patient
(0.04 MB XLS)
List of the 3515 clones corresponding to the 2959 genes differentially expressed between DF, DHF and DSS patients, identified using the multi-way ANOVA at a false discovery rate of 10. Clones corresponding to the 2959 genes are listed according to their association to DSS, the first one being the gene of which expression level variance is the most influenced by the clinical phenotype. HUGO gene names are indicated. The variation is the one related to the DSS group relatively to DF and DHF. ANOVA, analysis of variance; DF, dengue fever; DHF, dengue hemorrhagic fever; DSS, dengue shock syndrome; NA, not available. a percentage of variance associated to disease phenotype.
(0.90 MB XLS)
We greatly thank Pr Y. Buisson for supporting this program, I. Drouet and H. Puggelli for technical support and help in preparation of field work.
We thank Dr J. Desplans for help in using the Agilent microarrays platform.
We are also indebted to all doctors, nurses, patients and their families who participated to this study at the hospital of Kampong Cham, Cambodia, and to all technicians from the virology department of the Institut Pasteur in Cambodia who carried out dengue diagnosis assays.