Sequential waves of gene expression in patients with clinically defined dengue illnesses reveal subtle disease phases and predict disease severity

Immunological signatures unveiled by integrative systems vaccinology characterization of dengue vaccination trials and natural infection

Introduction

Dengue virus infection is a global health problem lacking specific therapy, requiring an improved understanding of DENV immunity and vaccine responses. Considering the recent emerging of new dengue vaccines, here we performed an integrative systems vaccinology characterization of molecular signatures triggered by the natural DENV infection (NDI) and attenuated dengue virus infection models (DVTs).

Methods and results

We analyzed 955 samples of transcriptomic datasets of patients with NDI and attenuated dengue virus infection trials (DVT1, DVT2, and DVT3) using a systems vaccinology approach. Differential expression analysis identified 237 common differentially expressed genes (DEGs) between DVTs and NDI. Among them, 28 and 60 DEGs were up or downregulated by dengue vaccination during DVT2 and DVT3, respectively, with 20 DEGs intersecting across all three DVTs. Enriched biological processes of these genes included type I/II interferon signaling, cytokine regulation, apoptosis, and T-cell differentiation. Principal component analysis based on 20 common DEGs (overlapping between DVTs and our NDI validation dataset) distinguished dengue patients by disease severity, particularly in the late acute phase. Machine learning analysis ranked the ten most critical predictors of disease severity in NDI, crucial for the anti-viral immune response.

Conclusion

This work provides insights into the NDI and vaccine-induced overlapping immune response and suggests molecular markers (e.g., IFIT5, ISG15, and HERC5) for anti-dengue-specific therapies and effective vaccination development.

Interferome signature dynamics during the anti-dengue immune response: a systems biology characterization

Dengue virus (DENV) infection manifests as a febrile illness with three distinct phases: early acute, late acute, and convalescent. Dengue can result in clinical manifestations with different degrees of severity, dengue fever, dengue hemorrhagic fever, and dengue shock syndrome. Interferons (IFNs) are antiviral cytokines central to the anti-DENV immune response. Notably, the distinct global signature of type I, II, and III interferon-regulated genes (the interferome) remains uncharacterized in dengue patients to date. Therefore, we performed an in-depth cross-study for the integrative analysis of transcriptome data related to DENV infection. Our systems biology analysis shows that the anti-dengue immune response is characterized by the modulation of numerous interferon-regulated genes (IRGs) enriching, for instance, cytokine-mediated signaling (e.g., type I and II IFNs) and chemotaxis, which is then followed by a transcriptional wave of genes associated with cell cycle, also regulated by the IFN cascade. The adjunct analysis of disease stratification potential, followed by a transcriptional meta-analysis of the interferome, indicated genes such as IFI27, ISG15, and CYBRD1 as potential suitable biomarkers of disease severity. Thus, this study characterizes the landscape of the interferome signature in DENV infection, indicating that interferome dynamics are a crucial and central part of the anti-dengue immune response.

Integrated systems immunology approach identifies impaired effector T cell memory responses as a feature of progression to severe dengue fever

BACKGROUND

Typical symptoms of uncomplicated dengue fever (DF) include headache, muscle pains, rash, cough, and vomiting. A proportion of cases progress to severe dengue hemorrhagic fever (DHF), associated with increased vascular permeability, thrombocytopenia, and hemorrhages. Progression to severe dengue is difficult to diagnose at the onset of fever, which complicates patient triage, posing a socio-economic burden on health systems.

METHODS

To identify parameters associated with protection and susceptibility to DHF, we pursued a systems immunology approach integrating plasma chemokine profiling, high-dimensional mass cytometry and peripheral blood mononuclear cell (PBMC) transcriptomic analysis at the onset of fever in a prospective study conducted in Indonesia.

RESULTS

After a secondary infection, progression to uncomplicated dengue featured transcriptional profiles associated with increased cell proliferation and metabolism, and an expansion of ICOS⁺CD4⁺ and CD8⁺ effector memory T cells. These responses were virtually absent in cases progressing to severe DHF, that instead mounted an innate-like response, characterised by inflammatory transcriptional profiles, high circulating levels of inflammatory chemokines and with high frequencies of CD4^low non-classical monocytes predicting increased odds of severe disease.

CONCLUSIONS

Our results suggests that effector memory T cell activation might play an important role ameliorating severe disease symptoms during a secondary dengue infection, and in the absence of that response, a strong innate inflammatory response is required to control viral replication. Our research also identified discrete cell populations predicting increased odds of severe disease, with potential diagnostic value.

Thrombophilia and Immune-Related Genetic Markers in Long COVID

Aiming to evaluate the role of ten functional polymorphisms in long COVID, involved in major inflammatory, immune response and thrombophilia pathways, a cross-sectional sample composed of 199 long COVID (LC) patients and a cohort composed of 79 COVID-19 patients whose follow-up by over six months did not reveal any evidence of long COVID (NLC) were investigated to detect genetic susceptibility to long COVID. Ten functional polymorphisms located in thrombophilia-related and immune response genes were genotyped by real time PCR. In terms of clinical outcomes, LC patients presented higher prevalence of heart disease as preexistent comorbidity. In general, the proportions of symptoms in acute phase of the disease were higher among LC patients. The genotype AA of the interferon gamma (IFNG) gene was observed in higher frequency among LC patients (60%; p = 0.033). Moreover, the genotype CC of the methylenetetrahydrofolate reductase (MTHFR) gene was also more frequent among LC patients (49%; p = 0.045). Additionally, the frequencies of LC symptoms were higher among carriers of IFNG genotypes AA than among non-AA genotypes (Z = 5.08; p < 0.0001). Two polymorphisms were associated with LC in both inflammatory and thrombophilia pathways, thus reinforcing their role in LC. The higher frequencies of acute phase symptoms among LC and higher frequency of underlying comorbidities might suggest that acute disease severity and the triggering of preexisting condition may play a role in LC development.

Early peripheral blood MCEMP1 and HLA-DRA expression predicts COVID-19 prognosis

BACKGROUND

Mass vaccination has dramatically reduced the incidence of severe COVID-19, with most cases now presenting as self-limiting upper respiratory tract infections. However, those with co-morbidities, the elderly and immunocompromised, as well as the unvaccinated, remain disproportionately vulnerable to severe COVID-19 and its sequelae. Furthermore, as the effectiveness of vaccination wanes with time, immune escape SARS-CoV-2 variants could emerge to cause severe COVID-19. Reliable prognostic biomarkers for severe disease could be used as early indicator of re-emergence of severe COVID-19 as well as for triaging of patients for antiviral therapy.

METHODS

We performed a systematic review and re-analysis of 7 publicly available datasets, analysing a total of 140 severe and 181 mild COVID-19 patients, to determine the most consistent differentially regulated genes in peripheral blood of severe COVID-19 patients. In addition, we included an independent cohort where blood transcriptomics of COVID-19 patients were prospectively and longitudinally monitored previously, to track the time in which these gene expression changes occur before nadir of respiratory function. Single cell RNA-sequencing of peripheral blood mononuclear cells from publicly available datasets was then used to determine the immune cell subsets involved.

FINDINGS

The most consistent differentially regulated genes in peripheral blood of severe COVID-19 patients were MCEMP1, HLA-DRA and ETS1 across the 7 transcriptomics datasets. Moreover, we found significantly heightened MCEMP1 and reduced HLA-DRA expression as early as four days before the nadir of respiratory function, and the differential expression of MCEMP1 and HLA-DRA occurred predominantly in CD14+ cells. The online platform which we developed is publicly available at https://kuanrongchan-covid19-severity-app-t7l38g.streamlitapp.com/, for users to query gene expression differences between severe and mild COVID-19 patients in these datasets.

INTERPRETATION

Elevated MCEMP1 and reduced HLA-DRA gene expression in CD14+ cells during the early phase of disease are prognostic of severe COVID-19.

FUNDING

K.R.C is funded by the National Medical Research Council (NMRC) of Singapore under the Open Fund Individual Research Grant (MOH-000610). E.E.O. is funded by the NMRC Senior Clinician-Scientist Award (MOH-000135-00). J.G.H.L. is funded by the NMRC under the Clinician-Scientist Award (NMRC/CSAINV/013/2016-01). S.K. is funded by the NMRC under the Transition Award. This study was sponsored in part by a generous gift from The Hour Glass.

Longitudinal proteomic profiling of the inflammatory response in dengue patients

BACKGROUND

The immunopathogenesis of dengue virus (DENV) infection remains incompletely understood. To increase our understanding of inflammatory response in non-severe dengue, we assessed longitudinal changes in the inflammatory proteome in patients with an acute DENV infection.

METHODS

Using a multiplex proximity extension assay (PEA), we measured relative levels of 368 inflammatory markers in plasma samples from hospitalized patients with non-severe DENV infection in the acute (n = 43) and convalescence (n = 35) phase of the infection and samples of healthy controls (n = 10).

RESULTS

We identified 203 upregulated and 39 downregulated proteins in acute versus convalescent plasma samples. The upregulated proteins had a strong representation of interferon (IFN) and IFN-inducible effector proteins, cytokines (e.g. IL-10, IL-33) and cytokine receptors, chemokines, pro-apoptotic proteins (e.g. granzymes) and endothelial markers. A number of differentially expressed proteins (DEPs) have not been reported in previous studies. Functional network analysis highlighted a central role for IFNγ, IL-10, IL-33 and chemokines. We identified different novel associations between inflammatory proteins and circulating concentrations of the endothelial glycocalyx disruption surrogate marker syndecan-1. Conclusion: This unbiased proteome analysis provides a comprehensive insight in the inflammatory response in DENV infection and its association with glycocalyx disruption.

Identification of stage-related and severity-related biomarkers and exploration of immune landscape for Dengue by comprehensive analyses

Background

At present, there are still no specific therapeutic drugs and appropriate vaccines for Dengue. Therefore, it is important to explore distinct clinical diagnostic indicators.

Methods

In this study, we combined differentially expressed genes (DEGs) analysis, weighted co-expression network analysis (WGCNA) and Receiver Operator Characteristic Curve (ROC) to screen a stable and robust biomarker with diagnosis value for Dengue patients. CIBERSORT was used to evaluate immune landscape of Dengue patients. Gene Ontology (GO) enrichment, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis and Gene set enrichment analysis (GSEA) were applied to explore potential functions of hub genes.

Results

CD38 and Plasma cells have excellent Area Under the Curve (AUC) in distinguishing clinical stages for Dengue patients, and activated memory CD4+ T cells and Monocytes have good AUC for this function. ZNF595 has acceptable AUC in discriminating dengue hemorrhagic fever (DHF) from dengue fever (DF) in whole acute stages. Analyzing any serotype, we can obtain consistent results. Negative inhibition of viral replication based on GO, KEGG and GSEA analysis results, up-regulated autophagy genes and the impairing immune system are potential reasons resulting in DHF.

Conclusions

CD38, Plasma cells, activated memory CD4+ T cells and Monocytes can be used to distinguish clinical stages for dengue patients, and ZNF595 can be used to discriminate DHF from DF, regardless of serotypes.

Graphical abstract

Supplementary Information

The online version contains supplementary material available at 10.1186/s12985-022-01853-8.

An 8-gene machine learning model improves clinical prediction of severe dengue progression

BACKGROUND

Each year 3-6 million people develop life-threatening severe dengue (SD). Clinical warning signs for SD manifest late in the disease course and are nonspecific, leading to missed cases and excess hospital burden. Better SD prognostics are urgently needed.

METHODS

We integrated 11 public datasets profiling the blood transcriptome of 365 dengue patients of all ages and from seven countries, encompassing biological, clinical, and technical heterogeneity. We performed an iterative multi-cohort analysis to identify differentially expressed genes (DEGs) between non-severe patients and SD progressors. Using only these DEGs, we trained an XGBoost machine learning model on public data to predict progression to SD. All model parameters were "locked" prior to validation in an independent, prospectively enrolled cohort of 377 dengue patients in Colombia. We measured expression of the DEGs in whole blood samples collected upon presentation, prior to SD progression. We then compared the accuracy of the locked XGBoost model and clinical warning signs in predicting SD.

RESULTS

We identified eight SD-associated DEGs in the public datasets and built an 8-gene XGBoost model that accurately predicted SD progression in the independent validation cohort with 86.4% (95% CI 68.2-100) sensitivity and 79.7% (95% CI 75.5-83.9) specificity. Given the 5.8% proportion of SD cases in this cohort, the 8-gene model had a positive and negative predictive value (PPV and NPV) of 20.9% (95% CI 16.7-25.6) and 99.0% (95% CI 97.7-100.0), respectively. Compared to clinical warning signs at presentation, which had 77.3% (95% CI 58.3-94.1) sensitivity and 39.7% (95% CI 34.7-44.9) specificity, the 8-gene model led to an 80% reduction in the number needed to predict (NNP) from 25.4 to 5.0. Importantly, the 8-gene model accurately predicted subsequent SD in the first three days post-fever onset and up to three days prior to SD progression.

CONCLUSIONS

The 8-gene XGBoost model, trained on heterogeneous public datasets, accurately predicted progression to SD in a large, independent, prospective cohort, including during the early febrile stage when SD prediction remains clinically difficult. The model has potential to be translated to a point-of-care prognostic assay to reduce dengue morbidity and mortality without overwhelming limited healthcare resources.

Single-cell Temporal Analysis of Natural Dengue Infection Reveals Skin-Homing Lymphocyte Expansion One Day before Defervescence

Effective clinical management of acute dengue virus (DENV) infection relies on the timing of suitable treatments during the disease progression. We analyzed single-cell transcriptomic profiles of the peripheral blood mononuclear cell samples from two DENV patients, collected daily during acute phase and also at convalescence. Key immune cell types demonstrated different dynamic responses over the course of the infection. On the day before defervescence (Day −1), we observed the peak expression of several prominent genes in the adaptive immunological pathways. We also characterized unique effector T cell clusters that expressed skin-homing signature genes at Day −1, whereas upregulation of skin and gut homing genes was also observed in plasma cells and plasmablasts during the febrile period. This work provides an overview of unique molecular dynamics that signify the entry of the critical phase, and the findings could improve the patient management of DENV infection.

•

Time-course scRNA-seq reveals immune response dynamics during acute dengue infection

•

Rapid transcriptional switching was observed one day before fever subsided (Day -1)

•

Skin-homing signatures were observed in specific T cells during the febrile phase

•

Expansion of skin-homing CD69⁺ PD-1⁺ T cells at Day -1 was confirmed with FACS

Network meta-analysis of transcriptome expression changes in different manifestations of dengue virus infection

Background

Several studies have been performed to study transcriptome profiles after dengue virus infections with partly different results. Due to slightly different settings of the individual studies, different genes and enriched gene sets are reported in these studies. The main aim of this network meta-analysis was to aggregate a selection of these studies to identify genes and gene sets that are more generally associated with dengue virus infection, i.e. with less dependence on the individual study settings.

Methods

We performed network meta-analysis by different approaches using publicly available gene expression data of five selected studies from the Gene Expression Omnibus database. The study network includes dengue fever (DF), hemorrhagic fever (DHF), shock syndrome (DSS) patients as well as convalescent and healthy control individuals. After data merging and missing value imputation, study-specific batch effects were removed. Pairwise differential expression analysis and subsequent gene-set enrichment analysis were performed between the five study groups. Furthermore, mutual information networks were derived from the top genes of each group comparison, and the separability between the three patient groups was studied by machine learning models.

Results

From the 10 possible pairwise group comparisons in the study network, six genes (IFI27, TPX2, CDT1, DTL, KCTD14 and CDCA3) occur with a noticeable frequency among the top listed genes of each comparison. Thus, there is an increased evidence that these genes play a general role in dengue virus infections. IFI27 and TPX2 have also been highlighted in the context of dengue virus infection by other studies. A few of the identified gene sets from the network meta-analysis overlap with findings from the original studies. Mutual information networks yield additional genes for which the observed pairwise correlation is different between the patient groups. Machine learning analysis shows a moderate separability of samples from the DF, DHF and DSS groups (accuracy about 80%).

Conclusions

Due to an increased sample size, the network meta-analysis could reveal additional genes which are called differentially expressed between the studied groups and that may help to better understand the molecular basis of this disease.

Gene Expression Profiling of Early Acute Febrile Stage of Dengue Infection and Its Comparative Analysis With Streptococcus pneumoniae Infection

Infectious diseases are the disorders caused by organisms such as bacteria, viruses, fungi, or parasites. Although many of them are permentantly hazardous, a number of them live in and on our bodies and they are normally harmless or even helpful. Under certain circumstances, some organisms may cause diseases and these infectious diseases may be passed directly from person to person or via intermediate vectors including insects and other animals. Dengue virus and Streptococcus pneumoniae are the critical and common sources of infectious diseases. So, it is critical to understand the gene expression profiling and their inferred functions in comparison to the normal and virus infected conditions. Here, we have analyzed the gene expression profiling for dengue hemorrhagic fever, dengue fever, and normal human dataset. Similar to it, streptococcus pneumoniae infectious data were analyzed and both the outcomes were compared. Our study leads to the conclusion that the dengue hemorrhagic fever arises in result to potential change in the gene expression pattern, and the inferred functions obviously belong to the immune system, but also there are some additional potential pathways which are critical signaling pathways. In the case of pneumoniae infection, 19 pathways were enriched, almost all these pathways are associated with the immune system and 17 of the enriched pathways were common with dengue infection except platelet activation and antigen processing and presentation. In terms of the comparative study between dengue virus and Streptococcus pneumoniae infection, we conclude that cell adhesion molecules (CAMs), MAPK signaling pathway, natural killer cell mediated cytotoxicity, regulation of actin cytoskeleton, and cytokine-cytokine receptor interaction are commonly enriched in all the three cases of dengue infection and Streptococcus pneumoniae infection, focal adhesion was enriched between classical dengue fever — dengue hemorrhagic fever, dengue hemorrhagic fever—normal samples, and SP, and antigen processing and presentation and Leukocyte transendothelial migration were enriched in classical dengue fever —normal samples, dengue hemorrhagic fever—normal samples, and Streptococcus pneumoniae infection.

Specific Interaction of DDX6 with an RNA Hairpin in the 3' UTR of the Dengue Virus Genome Mediates G1 Phase Arrest

The extent to which viral genomic RNAs interact with host factors and contribute to host response and disease pathogenesis is not well known. Here, we report that the human RNA helicase DDX6 specifically binds to the viral most conserved RNA hairpin in the A3 element in the dengue 3' UTR, with nanomolar affinities. DDX6 CLIP confirmed the interaction in HuH-7 cells infected by dengue virus serotype 2. This interaction requires three conserved residues-Lys³⁰⁷, Lys³⁶⁷, and Arg³⁶⁹-as well as the unstructured extension in the C-terminal domain of DDX6. Interestingly, alanine substitution of these three basic residues resulted in RNA-independent ATPase activity, suggesting a mechanism by which RNA-binding and ATPase activities are coupled in DEAD box helicases. Furthermore, we applied a cross-omics gene enrichment approach to suggest that DDX6 is functionally related to cell cycle regulation and viral pathogenicity. Indeed, infected cells exhibited cell cycle arrest in G₁ phase and a decrease in the early S phase. Exogenous expression of intact DDX6, but not A3-binding-deficient mutants, alleviated these effects by rescue of the DNA preinitiation complex expression. Disruption of the DDX6-binding site was found in dengue and Zika live-attenuated vaccine strains. Our results suggested that dengue virus has evolved an RNA aptamer against DDX6 to alter host cell states and defined DDX6 as a new regulator of G₁/S transition. IMPORTANCE Dengue virus (DENV) is transmitted by mosquitoes to humans, infecting 390 million individuals per year globally. About 20% of infected patients shows a spectrum of clinical manifestation, ranging from a mild flu-like syndrome, to dengue fever, to life-threatening severe dengue diseases, including dengue hemorrhagic fever and dengue shock syndrome. There is currently no specific treatment for dengue diseases, and the molecular mechanism underlying dengue pathogenesis remains poorly understood. In this study, we combined biochemical, bioinformatics, high-content analysis and RNA sequencing approaches to characterize a highly conserved interface of the RNA genome of DENV with a human factor named DDX6 in infected cells. The significance of our research is in identifying the mechanism for a viral strategy to alter host cell fates, which conceivably allows us to generate a model for live-attenuated vaccine and the design of new therapeutic reagent for dengue diseases.

Innate Immune Cytokine Profiling and Biomarker Identification for Outcome in Dengue Patients

Background

Early biomarkers of progression to severe dengue are urgently required to enable effective patient management and control treatment costs. Innate immune cells, which comprise the earliest responders to infection and along with the cytokines and chemokines they secrete, play a vital role in orchestrating the subsequent adaptive immune response and have been implicated in the enhancement of infection and “cytokine storm” associated with dengue severity. We investigated the early innate immune cytokine profile of dengue patients during acute phase of disease in a prospective blinded study that included subjects with acute dengue and febrile controls from four major hospitals in Bengaluru, India along with healthy controls. We used intracellular cytokine staining and flow cytometry to identify innate immune biomarkers that can predict progression to severe dengue.

Results

Dengue infection resulted in enhanced secretion of multiple cytokines by all queried innate immune cell subsets, dominated by TNF-α from CD56⁺CD3⁺ NKT cells, monocyte subsets, and granulocytes along with IFN-γ from CD56⁺CD3⁺ NKT cells. Of note, significantly higher proportions of TNF-α secreting granulocytes and monocyte subsets at admission were associated with mild dengue and minimal symptoms. Dengue NS1 antigenemia used as a surrogate of viral load directly correlated with proportion of cytokine-secreting innate immune cells and was significantly higher in those who went on to recover with minimal symptoms. In patients with secondary dengue or those with bleeding or elevated liver enzymes who revealed predisposition to severe outcomes, early activation as well as efficient downregulation of innate responses were compromised.

Conclusion

Our findings suggested that faulty/delayed kinetics of innate immune activation and downregulation was a driver of disease severity. We identified IFN-γ⁺CD56⁺CD3⁺ NKT cells and IL-6⁺ granulocytes at admission as novel early biomarkers that can predict the risk of progression to severity (composite AUC = 0.85–0.9). Strong correlations among multiple cytokine-secreting innate cell subsets revealed that coordinated early activation of the entire innate immune system in response to dengue virus infection contributed to resolution of infection and speedy recovery.

Immunotranscriptomic profiling the acute and clearance phases of a human challenge dengue virus serotype 2 infection model

About 20-25% of dengue virus (DENV) infections become symptomatic ranging from self-limiting fever to shock. Immune gene expression changes during progression to severe dengue have been documented in hospitalized patients; however, baseline or kinetic information is difficult to standardize in natural infection. Here we profile the host immunotranscriptome response in humans before, during, and after infection with a partially attenuated rDEN2Δ30 challenge virus (ClinicalTrials.gov NCT02021968). Inflammatory genes including type I interferon and viral restriction pathways are induced during DENV2 viremia and return to baseline after viral clearance, while others including myeloid, migratory, humoral, and growth factor immune regulation factors pathways are found at non-baseline levels post-viremia. Furthermore, pre-infection baseline gene expression is useful to predict rDEN2Δ30-induced immune responses and the development of rash. Our results suggest a distinct immunological profile for mild rDEN2Δ30 infection and offer new potential biomarkers for characterizing primary DENV infection.

Innate Lymphoid Cells Activation and Transcriptomic Changes in Response to Human Dengue Infection

Background

Dengue virus (DENV) infection has a global impact on public health. The clinical outcomes (of DENV) can vary from a flu-like illness called dengue fever (DF), to a more severe form, known as dengue hemorrhagic fever (DHF). The underlying innate immune mechanisms leading to protective or detrimental outcomes have not been fully elucidated. Helper innate lymphoid cells (hILCs), an innate lymphocyte recently discovered, functionally resemble T-helper cells and are important in inflammation and homeostasis. However, the role of hILCs in DENV infection had been unexplored.

Methods

We performed flow cytometry to investigate the frequency and phenotype of hILCs in peripheral blood mononuclear cells from DENV-infected patients of different disease severities (DF and DHF), and at different phases (febrile and convalescence) of infection. Intracellular cytokine staining of hILCs from DF and DHF were also evaluated by flow cytometry after ex vivo stimulation. Further, the hILCs were sorted and subjected to transcriptome analysis using RNA sequencing. Differential gene expression analysis was performed to compare the febrile and convalescent phase samples in DF and DHF. Selected differentially expressed genes were then validated by quantitative PCR.

Results

Phenotypic analysis showed marked activation of all three hILC subsets during the febrile phase as shown by higher CD69 expression when compared to paired convalescent samples, although the frequency of hILCs remained unchanged. Upon ex vivo stimulation, hILCs from febrile phase DHF produced significantly higher IFN-γ and IL-4 when compared to those of DF. Transcriptomic analysis showed unique hILCs gene expression in DF and DHF, suggesting that divergent functions of hILCs may be associated with different disease severities. Differential gene expression analysis indicated that hILCs function both in cytokine secretion and cytotoxicity during the febrile phase of DENV infection.

Conclusions

Helper ILCs are activated in the febrile phase of DENV infection and display unique transcriptomic changes as well as cytokine production that correlate with severity. Targeting hILCs during early innate response to DENV might help shape subsequent immune responses and potentially lessen the disease severity in the future.

Assessing the risk of dengue severity using demographic information and laboratory test results with machine learning

BACKGROUND

Dengue virus causes a wide spectrum of disease, which ranges from subclinical disease to severe dengue shock syndrome. However, estimating the risk of severe outcomes using clinical presentation or laboratory test results for rapid patient triage remains a challenge. Here, we aimed to develop prognostic models for severe dengue using machine learning, according to demographic information and clinical laboratory data of patients with dengue.

METHODOLOGY/PRINCIPAL FINDINGS

Out of 1,581 patients in the National Cheng Kung University Hospital with suspected dengue infections and subjected to NS1 antigen, IgM and IgG, and qRT-PCR tests, 798 patients including 138 severe cases were enrolled in the study. The primary target outcome was severe dengue. Machine learning models were trained and tested using the patient dataset that included demographic information and qualitative laboratory test results collected on day 1 when they sought medical advice. To develop prognostic models, we applied various machine learning methods, including logistic regression, random forest, gradient boosting machine, support vector classifier, and artificial neural network, and compared the performance of the methods. The artificial neural network showed the highest average discrimination area under the receiver operating characteristic curve (0.8324 ± 0.0268) and balance accuracy (0.7523 ± 0.0273). According to the model explainer that analyzed the contributions/co-contributions of the different factors, patient age and dengue NS1 antigenemia were the two most important risk factors associated with severe dengue. Additionally, co-existence of anti-dengue IgM and IgG in patients with dengue increased the probability of severe dengue.

CONCLUSIONS/SIGNIFICANCE

We developed prognostic models for the prediction of dengue severity in patients, using machine learning. The discriminative ability of the artificial neural network exhibited good performance for severe dengue prognosis. This model could help clinicians obtain a rapid prognosis during dengue outbreaks. However, the model requires further validation using external cohorts in future studies.

Measurement of Cellular Immune Response to Viral Infection and Vaccination

Combined cellular and humoral host immune response determine the clinical course of a viral infection and effectiveness of vaccination, but currently the cellular immune response cannot be measured on simple blood samples. As functional activity of immune cells is determined by coordinated activity of signaling pathways, we developed mRNA-based JAK-STAT signaling pathway activity assays to quantitatively measure the cellular immune response on Affymetrix expression microarray data of various types of blood samples from virally infected patients (influenza, RSV, dengue, yellow fever, rotavirus) or vaccinated individuals, and to determine vaccine immunogenicity. JAK-STAT1/2 pathway activity was increased in blood samples of patients with viral, but not bacterial, infection and was higher in influenza compared to RSV-infected patients, reflecting known differences in immunogenicity. High JAK-STAT3 pathway activity was associated with more severe RSV infection. In contrast to inactivated influenza virus vaccine, live yellow fever vaccine did induce JAK-STAT1/2 pathway activity in blood samples, indicating superior immunogenicity. Normal (healthy) JAK-STAT1/2 pathway activity was established, enabling assay interpretation without the need for a reference sample. The JAK-STAT pathway assays enable measurement of cellular immune response for prognosis, therapy stratification, vaccine development, and clinical testing.

Current Challenges in Vaccinology

The development of vaccines, which prime the immune system to respond to future infections, has led to global declines in morbidity and mortality from dreadful infectious communicable diseases. However, many pathogens of public health importance are highly complex and/or rapidly evolving, posing unique challenges to vaccine development. Several of these challenges include an incomplete understanding of how immunity develops, host and pathogen genetic variability, and an increased societal skepticism regarding vaccine safety. In particular, new high-dimensional omics technologies, aided by bioinformatics, are driving new vaccine development (vaccinomics). Informed by recent insights into pathogen biology, host genetic diversity, and immunology, the increasing use of genomic approaches is leading to new models and understanding of host immune system responses that may provide solutions in the rapid development of novel vaccine candidates.

Towards Predicting Progression to Severe Dengue

There is an urgent need for prognostic assays to predict progression to severe dengue infection, which is a major global threat. While the majority of symptomatic dengue patients experience an acute febrile illness, 5-20% progress to severe infection associated with significant morbidity and mortality. Early monitoring and administration of supportive care reduce mortality and clinically usable biomarkers to predict severe dengue are needed. Here, we review recent discoveries of gene sets, anti-dengue antibody properties, and inflammatory markers with potential utility as predictors of disease progression. Upon larger scale validation and development of affordable sample-to-answer technologies, some of these biomarkers may be utilized to develop the first prognostic assay for improving patient care and allocating healthcare resources more effectively in dengue endemic countries.

Transcriptomic immune profiles of human flavivirus-specific T-cell responses

The Flavivirus genus of viruses includes dengue (DENV), Zika (ZIKV), yellow fever (YFV), Japanese encephalitis (JEV), and West Nile (WNV) viruses. Infections with these species combined are prevalent in tropical and sub-tropical areas, affecting millions of people and ranging from asymptomatic to severe forms of the disease. They therefore pose a serious threat to global public health. Several studies imply a role for T cells in the protection but also pathogenesis against the different flavivirus species. Identifying flavivirus-specific T-cell immune profiles and determining how pre-exposure of one species might affect the immune response against subsequent infections from other species is important to further define the role of T cells in the immune response against infection. Understanding the immune profiles of the flavivirus-specific T-cell response in natural infection is important to understand the T-cell response in the context of vaccination. In this review, we summarize the current knowledge on human immune profiles of flavivirus-specific T-cell reactivity, comparing natural infection with the acute form of the disease and vaccination in different flavivirus infections.

Identification and Characterization at the Single-Cell Level of Cytokine-Producing Circulating Cells in Children With Dengue

In this study, we identified, at the single-cell level, naturally induced cytokine-producing circulating cells (CPCCs) in children with dengue virus (DENV) infection ranging clinically from mild to severe disease. Tumor necrosis factor alpha (TNF-α) and interleukin 6 (IL-6) CPCCs were detected in children with primary or secondary acute dengue virus (DENV) infection, and the pattern of these cytokines was similar to that seen in the supernatant of cultured peripheral blood mononuclear cells and partially comparable to that found in plasma. Monocytes, B cells, and myeloid dendritic cells (mDCs) were the primary CPCCs detected, and the frequency of mDCs was significantly higher in severe disease. B cells isolated from children with dengue spontaneously secreted TNF-α, IL-6, and interleukin 10, and supernatants from cultures of purified B cells induced activation of allogeneic T cells, supporting an antibody-independent function of these cells during DENV infection. Thus, CPCCs could be a new immune parameter with potential use to evaluate pathogenesis in this infection.

Dengue-specific CD8+ T cell subsets display specialized transcriptomic and TCR profiles

Accumulating evidence demonstrates that CD8+ T cells contribute to protection from severe dengue virus (DENV) disease and vaccine efficacy. Nevertheless, molecular programs associated with DENV-specific CD8+ T cell subsets have not been defined. Here, we studied the transcriptomic profiles of human DENV-specific CD8+ T cells isolated after stimulation with DENV epitopes from donors who had been infected with DENV multiple times and would therefore be expected to have significant levels of adaptive immunity. We found that DENV-specific CD8+ T cells mainly consisted of effector memory subsets, namely CD45RA-CCR7- effector memory (Tem) and CD45RA+CCR7- effector memory re-expressing CD45RA (Temra) cells, which enacted specific gene expression profiles upon stimulation with cognate antigens. DENV-specific CD8+ T cell subsets in general, and Temra cells in particular, were fully activated and polyfunctional, yet associated with relatively narrow transcriptional responses. Furthermore, we found that DENV-specific CD8+ Tem and Temra cells showed some unique T cell receptor features in terms of overlap and variable (V) gene usage. This study provides a transcriptomic definition of DENV-specific activated human CD8+ T cell subsets and defines a benchmark profile that vaccine-specific responses could aim to reproduce.

Control of Acute Arboviral Infection by Natural Killer Cells

The recent explosive pandemic of chikungunya virus (CHIKV) followed by Zika (ZIKV) virus infections occurring throughout many countries represents the most unexpected arrival of arthropod-borne viral diseases in the past 20 years. Transmitted through the bite of Aedes mosquitoes, the clinical picture associated with these acute arbovirus infections, including Dengue (DENV), CHIKV and ZIKV, ranges from classical febrile illness to life-threatening disease. Whereas ZIKV and CHIKV-mediated infections have previously been recognized as relatively benign diseases, in contrast to Dengue fever, recent epidemic events have brought waves of increased morbidity and mortality leading to a serious public health problem. Although the host immune response plays a crucial role in controlling infections, it may also promote viral spread and immunopathology. Here, we review recent developments in our understanding of the immune response, with an emphasis on the early antiviral immune response mediated by natural killer cells and emphasize their Janus-faced effects in the control of arbovirus infection and pathogenesis. Improving our understanding knowledge on of the mechanisms that control viral infection is crucial in the current race against the globalization of arbovirus epidemics.

A 20-Gene Set Predictive of Progression to Severe Dengue

There is a need to identify biomarkers predictive of severe dengue. Single-cohort transcriptomics has not yielded generalizable results or parsimonious, predictive gene sets. We analyzed blood samples of dengue patients from seven gene expression datasets (446 samples, five countries) using an integrated multi-cohort analysis framework and identified a 20-gene set that predicts progression to severe dengue. We validated the predictive power of this 20-gene set in three retrospective dengue datasets (84 samples, three countries) and a prospective Colombia cohort (34 patients), with an area under the receiver operating characteristic curve of 0.89, 100% sensitivity, and 76% specificity. The 20-gene dengue severity scores declined during the disease course, suggesting an infection-triggered host response. This 20-gene set is strongly associated with the progression to severe dengue and represents a predictive signature, generalizable across ages, host genetic factors, and virus strains, with potential implications for the development of a host response-based dengue prognostic assay.

T-Cell Response to Viral Hemorrhagic Fevers

Viral hemorrhagic fevers (VHF) are a group of clinically similar diseases that can be caused by enveloped RNA viruses primarily from the families Arenaviridae, Filoviridae, Hantaviridae, and Flaviviridae. Clinically, this group of diseases has in common fever, fatigue, dizziness, muscle aches, and other associated symptoms that can progress to vascular leakage, bleeding and multi-organ failure. Most of these viruses are zoonotic causing asymptomatic infections in the primary host, but in human beings, the infection can be lethal. Clinical and experimental evidence suggest that the T-cell response is needed for protection against VHF, but can also cause damage to the host, and play an important role in disease pathogenesis. Here, we present a review of the T-cell immune responses to VHF and insights into the possible ways to improve counter-measures for these viral agents.

A longitudinal systems immunologic investigation of acute Zika virus infection in an individual infected while traveling to Caracas, Venezuela

Zika virus (ZIKV) is an emerging mosquito-borne flavivirus linked to devastating neurologic diseases. Immune responses to flaviviruses may be pathogenic or protective. Our understanding of human immune responses to ZIKV in vivo remains limited. Therefore, we performed a longitudinal molecular and phenotypic characterization of innate and adaptive immune responses during an acute ZIKV infection. We found that innate immune transcriptional and genomic responses were both cell type- and time-dependent. While interferon stimulated gene induction was common to all innate immune cells, the upregulation of important inflammatory cytokine genes was primarily limited to monocyte subsets. Additionally, genomic analysis revealed substantial chromatin remodeling at sites containing cell-type specific transcription factor binding motifs that may explain the observed changes in gene expression. In this dengue virus-experienced individual, adaptive immune responses were rapidly mobilized with T cell transcriptional activity and ZIKV neutralizing antibody responses peaking 6 days after the onset of symptoms. Collectively this study characterizes the development and resolution of an in vivo human immune response to acute ZIKV infection in an individual with pre-existing flavivirus immunity.

Zika virus (ZIKV) is an emerging flaviviral infection that causes significant clinical disease. It is estimated that approximately one half of the world’s population is at risk for ZIKV infection. There are only a limited number of studies describing the human immune response to ZIKV infection. Carlin et al. combined conventional and genomic approaches to longitudinally analyze the innate and adaptive immune responses to acute ZIKV infection and its resolution in a person who was infected while traveling in Venezuela during the 2016 ZIKV epidemic year. Genome-wide sequencing in individual cell types revealed that although many populations respond to interferon stimulation, only specific cell populations within peripheral blood mononuclear cells upregulate important inflammatory cytokine gene expression. Additionally, analysis of open chromatin using ATAC-seq suggests that chromatin remodeling at sites containing cell-type specific transcription factor binding motifs may help us understand changes in gene expression. Consistent with previous reports, this individual with prior exposure to dengue virus (DENV), rapidly developed neutralizing anti-ZIKV responses that were cross-reactive with multiple DENV serotypes. Collectively this study combines traditional and genomic approaches to characterize the cell-type specific development of an in vivo human immune response to acute ZIKV infection.

Dengue drug discovery: Progress, challenges and outlook

In the context of the only available vaccine (DENGVAXIA) that was marketed in several countries, but poses higher risks to unexposed individuals, the development of antivirals for dengue virus (DENV), whilst challenging, would bring significant benefits to public health. Here recent progress in the field of DENV drug discovery made in academic laboratories and industry is reviewed. Characteristics of an ideal DENV antiviral molecule, given the specific immunopathology provoked by this acute viral infection, are described. New chemical classes identified from biochemical, biophysical and phenotypic screens that target viral (especially NS4B) and host proteins, offer promising opportunities for further development. In particular, new methodologies ("omics") can accelerate the discovery of much awaited flavivirus specific inhibitors. Challenges and opportunities in lead identification activities as well as the path to clinical development of dengue drugs are discussed. To galvanize DENV drug discovery, collaborative public-public partnerships and open-access resources will greatly benefit both the DENV research community and DENV patients.

Suppression of Type I Interferon Signaling by Flavivirus NS5

Type I interferon (IFN-I) is the first line of mammalian host defense against viral infection. To counteract this, the flaviviruses, like other viruses, have encoded a variety of antagonists, and use a multi-layered molecular defense strategy to establish their infections. Among the most potent antagonists is non-structural protein 5 (NS5), which has been shown for all disease-causing flaviviruses to target different steps and players of the type I IFN signaling pathway. Here, we summarize the type I IFN antagonist mechanisms used by flaviviruses with a focus on the role of NS5 in regulating one key regulator of type I IFN, signal transducer and activator of transcription 2 (STAT2).

Early Transcriptional Responses After Dengue Vaccination Mirror the Response to Natural Infection and Predict Neutralizing Antibody Titers

Background

Several promising live attenuated dengue vaccines are in development, but information about innate immune responses and early correlates of protection is lacking.

Methods

We characterized human genome-wide transcripts in whole blood from 10 volunteers at 11 time points after immunization with the dengue virus type 3 (DENV-3) component of the National Institutes of Health dengue vaccine candidate TV003 and from 30 hospitalized children with acute primary DENV-3 infection. We compared day-specific gene expression patterns with subsequent neutralizing antibody (NAb) titers.

Results

The transcriptional response to vaccination was largely confined to days 5-20 and was dominated by an interferon-associated signature and a cell cycle signature that peaked on days 8 and 14, respectively. Changes in transcript abundance were much greater in magnitude and scope in symptomatic natural infection than following vaccination (maximum fold-change >200 vs 21 postvaccination; 3210 vs 286 transcripts with significant fold-change), but shared gene modules were induced in the same sequence. The abundances of 131 transcripts on days 8 and 9 postvaccination were strongly correlated with NAb titers measured 6 weeks postvaccination.

Conclusions

Live attenuated dengue vaccination elicits early transcriptional responses that mirror those found in symptomatic natural infection and provide candidate early markers of protection against DENV infection.

Clinical Trials Registration

NCT00831012.

KLRD1-expressing natural killer cells predict influenza susceptibility

BACKGROUND

Influenza infects tens of millions of people every year in the USA. Other than notable risk groups, such as children and the elderly, it is difficult to predict what subpopulations are at higher risk of infection. Viral challenge studies, where healthy human volunteers are inoculated with live influenza virus, provide a unique opportunity to study infection susceptibility. Biomarkers predicting influenza susceptibility would be useful for identifying risk groups and designing vaccines.

METHODS

We applied cell mixture deconvolution to estimate immune cell proportions from whole blood transcriptome data in four independent influenza challenge studies. We compared immune cell proportions in the blood between symptomatic shedders and asymptomatic nonshedders across three discovery cohorts prior to influenza inoculation and tested results in a held-out validation challenge cohort.

RESULTS

Natural killer (NK) cells were significantly lower in symptomatic shedders at baseline in both discovery and validation cohorts. Hematopoietic stem and progenitor cells (HSPCs) were higher in symptomatic shedders at baseline in discovery cohorts. Although the HSPCs were higher in symptomatic shedders in the validation cohort, the increase was statistically nonsignificant. We observed that a gene associated with NK cells, KLRD1, which encodes CD94, was expressed at lower levels in symptomatic shedders at baseline in discovery and validation cohorts. KLRD1 expression in the blood at baseline negatively correlated with influenza infection symptom severity. KLRD1 expression 8 h post-infection in the nasal epithelium from a rhinovirus challenge study also negatively correlated with symptom severity.

CONCLUSIONS

We identified KLRD1-expressing NK cells as a potential biomarker for influenza susceptibility. Expression of KLRD1 was inversely correlated with symptom severity. Our results support a model where an early response by KLRD1-expressing NK cells may control influenza infection.

CEMiTool: a Bioconductor package for performing comprehensive modular co-expression analyses

Background

The analysis of modular gene co-expression networks is a well-established method commonly used for discovering the systems-level functionality of genes. In addition, these studies provide a basis for the discovery of clinically relevant molecular pathways underlying different diseases and conditions.

Results

In this paper, we present a fast and easy-to-use Bioconductor package named CEMiTool that unifies the discovery and the analysis of co-expression modules. Using the same real datasets, we demonstrate that CEMiTool outperforms existing tools, and provides unique results in a user-friendly html report with high quality graphs. Among its features, our tool evaluates whether modules contain genes that are over-represented by specific pathways or that are altered in a specific sample group, as well as it integrates transcriptomic data with interactome information, identifying the potential hubs on each network. We successfully applied CEMiTool to over 1000 transcriptome datasets, and to a new RNA-seq dataset of patients infected with Leishmania, revealing novel insights of the disease’s physiopathology.

Conclusion

The CEMiTool R package provides users with an easy-to-use method to automatically implement gene co-expression network analyses, obtain key information about the discovered gene modules using additional downstream analyses and retrieve publication-ready results via a high-quality interactive report.

Electronic supplementary material

The online version of this article (10.1186/s12859-018-2053-1) contains supplementary material, which is available to authorized users.

Immune Response to Dengue and Zika

Flaviviruses such as dengue (DENV), yellow fever (YFV), West Nile (WNV), and Zika (ZIKV) are human pathogens of global significance. In particular, DENV causes the most prevalent mosquito-borne viral diseases in humans, and ZIKV emerged from obscurity into the spotlight in 2016 as the etiologic agent of congenital Zika syndrome. Owing to the recent emergence of ZIKV as a global pandemic threat, the roles of the immune system during ZIKV infections are as yet unclear. In contrast, decades of DENV research implicate a dual role for the immune system in protection against and pathogenesis of DENV infection. As DENV and ZIKV are closely related, knowledge based on DENV studies has been used to prioritize investigation of ZIKV immunity and pathogenesis, and to accelerate ZIKV diagnostic, therapeutic, and vaccine design. This review discusses the following topics related to innate and adaptive immune responses to DENV and ZIKV: the interferon system as the key mechanism of host defense and viral target for immune evasion, antibody-mediated protection versus antibody-dependent enhancement, and T cell-mediated protection versus original T cell antigenic sin. Understanding the mechanisms that regulate the balance between immune-mediated protection and pathogenesis during DENV and ZIKV infections is critical toward development of safe and effective DENV and ZIKV therapeutics and vaccines.

Identifying therapeutic targets by combining transcriptional data with ordinal clinical measurements

The immense and growing repositories of transcriptional data may contain critical insights for developing new therapies. Current approaches to mining these data largely rely on binary classifications of disease vs. control, and are not able to incorporate measures of disease severity. We report an analytical approach to integrate ordinal clinical information with transcriptomics. We apply this method to public data for a large cohort of Huntington’s disease patients and controls, identifying and prioritizing phenotype-associated genes. We verify the role of a high-ranked gene in dysregulation of sphingolipid metabolism in the disease and demonstrate that inhibiting the enzyme, sphingosine-1-phosphate lyase 1 (SPL), has neuroprotective effects in Huntington’s disease models. Finally, we show that one consequence of inhibiting SPL is intracellular inhibition of histone deacetylases, thus linking our observations in sphingolipid metabolism to a well-characterized Huntington’s disease pathway. Our approach is easily applied to any data with ordinal clinical measurements, and may deepen our understanding of disease processes.

Identifying gene subsets affecting disease phenotypes from transcriptome data is challenge. Here, the authors develop a method that combines transcriptional data with disease ordinal clinical measurements to discover a sphingolipid metabolism regulator involving in Huntington’s disease progression.

Dengue Virus Induces NK Cell Activation through TRAIL Expression during Infection

Dengue is an acute febrile illness with a wide spectrum of signs and symptoms ranging from mild to severe forms characterized by plasma leakage that can be fatal. NK cells are one of the main effectors in early infection and may play an important role in dengue pathogenesis. We investigated NK cell involvement during dengue infection. A higher frequency of NK cell subsets and TRAIL+NK cells was found in mild DF cases when compared to that in severe cases or healthy donors. NK activation markers such as CD107a and TLR3 were upregulated in patients' cells compared to those in healthy donors. In addition, IL12 related to NK cell activation were upregulated in mild DF cases. In vitro PBMC culture models show that DENV-stimulated and IFNα-stimulated NK cells were able to express TRAIL, suggesting an indirect activation of cells, regarding TRAIL expression. Type I IFN receptor blockage on DENV-stimulated PBMCs showed TRAIL expression on NK cells is partially IFNα dependent. In addition, during PBMC stimulation, TRAIL expression on NK cells was inversely correlated with DENV-positive monocytes. Therefore, we observed DENV-induced activation of NK cell populations. A higher activation of NK cells would promote limited viral spread, resulting in decreased inflammatory response, contributing to protection against dengue severity.

Transcriptional Profiling Confirms the Therapeutic Effects of Mast Cell Stabilization in a Dengue Disease Model

There are no approved therapeutics for the treatment of dengue disease despite the global prevalence of dengue virus (DENV) and its mosquito vectors. DENV infections can lead to vascular complications, hemorrhage, and shock due to the ability of DENV to infect a variety of immune and nonimmune cell populations. Increasingly, studies have implicated the host response as a major contributor to severe disease. Inflammatory products of various cell types, including responding T cells, mast cells (MCs), and infected monocytes, can contribute to immune pathology. In this study, we show that the host response to DENV infection in immunocompetent mice recapitulates transcriptional changes that have been described in human studies. We found that DENV infection strongly induced metabolic dysregulation, complement signaling, and inflammation. DENV also affected the immune cell content of the spleen and liver, enhancing NK, NKT, and CD8⁺ T cell activation. The MC-stabilizing drug ketotifen reversed many of these responses without suppressing memory T cell formation and induced additional changes in the transcriptome and immune cell composition of the spleen, consistent with reduced inflammation. This study provides a global transcriptional map of immune activation in DENV target organs of an immunocompetent host and supports the further development of targeted immunomodulatory strategies to treat DENV disease.IMPORTANCE Dengue virus (DENV), which causes febrile illness, is transmitted by mosquito vectors throughout tropical and subtropical regions of the world. Symptoms of DENV infection involve damage to blood vessels and, in rare cases, hemorrhage and shock. Currently, there are no targeted therapies to treat DENV infection, but it is thought that drugs that target the host immune response may be effective in limiting symptoms that result from excessive inflammation. In this study, we measured the host transcriptional response to infection in multiple DENV target organs using a mouse model of disease. We found that DENV infection induced metabolic dysregulation and inflammatory responses and affected the immune cell content of the spleen and liver. The use of the mast cell stabilization drug ketotifen reversed many of these responses and induced additional changes in the transcriptome and immune cell repertoire that contribute to decreased dengue disease.

Immune-mediated cytokine storm and its role in severe dengue

Dengue remains one of the most important mosquito-borne diseases worldwide. Infection with one of the serologically related dengue viruses (DENVs) can lead to a wide range of clinical manifestations and severity. Severe dengue is characterized by plasma leakage and abnormal bleeding that can lead to shock and death. There is currently no specific treatment for severe dengue due to gaps in understanding of the underlying mechanisms. The transient period of vascular leakage is usually followed by a rapid recovery and is suggestive of the effects of short-lived biological mediators. Both the innate and the adaptive immune systems are activated in severe dengue and contribute to the cytokine production. We discuss the immunological events elicited during a DENV infection and identify candidate cytokines that may play a key role in the severe manifestations of dengue and possible interventions.

Principal Components Analysis Based Unsupervised Feature Extraction Applied to Gene Expression Analysis of Blood from Dengue Haemorrhagic Fever Patients

Dengue haemorrhagic fever (DHF) sometimes occurs after recovery from the disease caused by Dengue virus (DENV), and is often fatal. However, the mechanism of DHF has not been determined, possibly because no suitable methodologies are available to analyse this disease. Therefore, more innovative methods are required to analyse the gene expression profiles of DENV-infected patients. Principal components analysis (PCA)-based unsupervised feature extraction (FE) was applied to the gene expression profiles of DENV-infected patients, and an integrated analysis of two independent data sets identified 46 genes as critical for DHF progression. PCA using only these 46 genes rendered the two data sets highly consistent. The application of PCA to the 46 genes of an independent third data set successfully predicted the progression of DHF. A fourth in vitro data set confirmed the identification of the 46 genes. These 46 genes included interferon- and heme-biosynthesis-related genes. The former are enriched in binding sites for STAT1, STAT2, and IRF1, which are associated with DHF-promoting antibody-dependent enhancement, whereas the latter are considered to be related to the dysfunction of spliceosomes, which may mediate haemorrhage. These results are outcomes that other type of bioinformatic analysis could hardly achieve.

Characterization of Human CD8 T Cell Responses in Dengue Virus-Infected Patients from India

Epidemiological studies suggest that India has the largest number of dengue virus infection cases worldwide. However, there is minimal information about the immunological responses in these patients. CD8 T cells are important in dengue, because they have been implicated in both protection and immunopathology. Here, we provide a detailed analysis of HLA-DR⁺ CD38⁺ and HLA-DR^- CD38⁺ effector CD8 T cell subsets in dengue patients from India and Thailand. Both CD8 T cell subsets expanded and expressed markers indicative of antigen-driven proliferation, tissue homing, and cytotoxic effector functions, with the HLA-DR⁺ CD38⁺ subset being the most striking in these effector qualities. The breadth of the dengue-specific CD8 T cell response was diverse, with NS3-specific cells being the most dominant. Interestingly, only a small fraction of these activated effector CD8 T cells produced gamma interferon (IFN-γ) when stimulated with dengue virus peptide pools. Transcriptomics revealed downregulation of key molecules involved in T cell receptor (TCR) signaling. Consistent with this, the majority of these CD8 T cells remained IFN-γ unresponsive even after TCR-dependent polyclonal stimulation (anti-CD3 plus anti-CD28) but produced IFN-γ by TCR-independent polyclonal stimulation (phorbol 12-myristate 13-acetate [PMA] plus ionomycin). Thus, the vast majority of these proliferating, highly differentiated effector CD8 T cells probably acquire TCR refractoriness at the time the patient is experiencing febrile illness that leads to IFN-γ unresponsiveness. Our studies open novel avenues for understanding the mechanisms that fine-tune the balance between CD8 T cell-mediated protective versus pathological effects in dengue.

IMPORTANCE

Dengue is becoming a global public health concern. Although CD8 T cells have been implicated both in protection and in the cytokine-mediated immunopathology of dengue, how the balance is maintained between these opposing functions remains unknown. We comprehensively characterized CD8 T cell subsets in dengue patients from India and Thailand and show that these cells expand massively and express phenotypes indicative of overwhelming antigenic stimulus and tissue homing/cytotoxic-effector functions but that a vast majority of them fail to produce IFN-γ in vitro Interestingly, the cells were fully capable of producing the cytokine when stimulated in a T cell receptor (TCR)-independent manner but failed to do so in TCR-dependent stimulation. These results, together with transcriptomics, revealed that the vast majority of these CD8 T cells from dengue patients become cytokine unresponsive due to TCR signaling insufficiencies. These observations open novel avenues for understanding the mechanisms that fine-tune the balance between CD8-mediated protective versus pathological effects.

Transcriptome meta-analysis reveals a dysregulation in extra cellular matrix and cell junction associated gene signatures during Dengue virus infection

Dengue Viruses (DENVs) cause one of the most prevalent arthropod-borne viral diseases affecting millions of people worldwide. Identification of genes involved in DENV pathogenesis would help in deciphering molecular mechanisms responsible for the disease progression. Here, we carried out a meta-analysis of publicly available gene expression data of dengue patients and further validated the meta-profile using in-vitro infection in THP-1 cells. Our findings reveal that DENV infection modulates expression of several genes and signalling pathways including interferons, detoxification of ROS and viral assembly. Interestingly, we have identified novel gene signatures comprising of INADL/PATJ and CRTAP (Cartilage Associated Protein), which were significantly down-regulated across all patient data sets as well as in DENV infected THP-1 cells. PATJ and CRTAP genes are involved in maintaining cell junction integrity and collagen assembly (extracellular matrix component) respectively, which together play a crucial role in cell-cell adhesion. Our results categorically reveal that overexpression of CRTAP and PATJ genes restrict DENV infection, thereby suggesting a critical role of these genes in DENV pathogenesis. Conclusively, these findings emphasize the utility of meta-analysis approach in identifying novel gene signatures that might provide mechanistic insights into disease pathogenesis and possibly lead towards the development of better therapeutic interventions.

Genomic Signatures of Emerging Viruses: A New Era of Systems Epidemiology

Compared to classical epidemiologic methods, genomics can be used to precisely monitor virus evolution and transmission in real time across large, diverse populations. Integration of pathogen genomics with data about host genetics and global transcriptional responses to infection allows for comprehensive studies of population-level responses to infection and provides novel methods for predicting clinical outcomes. As genomic technologies become more accessible, these methods will redefine how emerging viruses are studied and outbreaks are contained. Here we review the existing and emerging genomic technologies that are enabling systems epidemiology and systems virology and making it possible to respond rapidly to emerging viruses such as Zika.

Genomic approaches for understanding dengue: insights from the virus, vector, and host

The incidence and geographic range of dengue have increased dramatically in recent decades. Climate change, rapid urbanization and increased global travel have facilitated the spread of both efficient mosquito vectors and the four dengue virus serotypes between population centers. At the same time, significant advances in genomics approaches have provided insights into host–pathogen interactions, immunogenetics, and viral evolution in both humans and mosquitoes. Here, we review these advances and the innovative treatment and control strategies that they are inspiring.

Metabolomics-Based Discovery of Small Molecule Biomarkers in Serum Associated with Dengue Virus Infections and Disease Outcomes

BACKGROUND

Epidemic dengue fever (DF) and dengue hemorrhagic fever/dengue shock syndrome (DHF/DSS) are overwhelming public health capacity for diagnosis and clinical care of dengue patients throughout the tropical and subtropical world. The ability to predict severe dengue disease outcomes (DHF/DSS) using acute phase clinical specimens would be of enormous value to physicians and health care workers for appropriate triaging of patients for clinical management. Advances in the field of metabolomics and analytic software provide new opportunities to identify host small molecule biomarkers (SMBs) in acute phase clinical specimens that differentiate dengue disease outcomes.

METHODOLOGY/PRINCIPAL FINDINGS

Exploratory metabolomic studies were conducted to characterize the serum metabolome of patients who experienced different dengue disease outcomes. Serum samples from dengue patients from Nicaragua and Mexico were retrospectively obtained, and hydrophilic interaction liquid chromatography (HILIC)-mass spectrometry (MS) identified small molecule metabolites that were associated with and statistically differentiated DHF/DSS, DF, and non-dengue (ND) diagnosis groups. In the Nicaraguan samples, 191 metabolites differentiated DF from ND outcomes and 83 differentiated DHF/DSS and DF outcomes. In the Mexican samples, 306 metabolites differentiated DF from ND and 37 differentiated DHF/DSS and DF outcomes. The structural identities of 13 metabolites were confirmed using tandem mass spectrometry (MS/MS). Metabolomic analysis of serum samples from patients diagnosed as DF who progressed to DHF/DSS identified 65 metabolites that predicted dengue disease outcomes. Differential perturbation of the serum metabolome was demonstrated following infection with different DENV serotypes and following primary and secondary DENV infections.

CONCLUSIONS/SIGNIFICANCE

These results provide proof-of-concept that a metabolomics approach can be used to identify metabolites or SMBs in serum specimens that are associated with distinct DENV infections and disease outcomes. The differentiating metabolites also provide insights into metabolic pathways and pathogenic and immunologic mechanisms associated with dengue disease severity.

Recent advances in understanding dengue

Dengue is an emerging threat to billions of people worldwide. In the last 20 years, the incidence has increased four-fold and this trend appears to be continuing. Caused by one of four viral serotypes, dengue can present as a wide range of clinical phenotypes with the severe end of the spectrum being defined by a syndrome of capillary leak, coagulopathy, and organ impairment. The pathogenesis of severe disease is thought to be in part immune mediated, but the exact mechanisms remain to be defined. The current treatment of dengue relies on supportive measures with no licensed therapeutics available to date. There have been recent advances in our understanding of a number of areas of dengue research, of which the following will be discussed in this review: the drivers behind the global dengue pandemic, viral structure and epitope binding, risk factors for severe disease and its pathogenesis, as well as the findings of recent clinical trials including therapeutics and vaccines. We conclude with current and future dengue control measures and key areas for future research.

Dengue NS1 antigen contributes to disease severity by inducing interleukin (IL)-10 by monocytes

Both dengue NS1 antigen and serum interleukin (IL)-10 levels have been shown to associate with severe clinical disease in acute dengue infection, and IL-10 has also been shown to suppress dengue-specific T cell responses. Therefore, we proceeded to investigate the mechanisms by which dengue NS1 contributes to disease pathogenesis and if it is associated with altered IL-10 production. Serum IL-10 and dengue NS1 antigen levels were assessed serially in 36 adult Sri Lankan individuals with acute dengue infection. We found that the serum IL-10 levels correlated positively with dengue NS1 antigen levels (Spearman's r = 0·47, P < 0·0001), and NS1 also correlated with annexin V expression by T cells in acute dengue (Spearman's r = 0·63, P = 0·001). However, NS1 levels did not associate with the functionality of T cell responses or with expression of co-stimulatory molecules. Therefore, we further assessed the effect of dengue NS1 on monocytes and T cells by co-culturing primary monocytes and peripheral blood mononuclear cells (PBMC), with varying concentrations of NS1 for up to 96 h. Monocytes co-cultured with NS1 produced high levels of IL-10, with the highest levels seen at 24 h, and then declined gradually. Therefore, our data show that dengue NS1 appears to contribute to pathogenesis of dengue infection by inducing IL-10 production by monocytes.

Dengue: an update on treatment options

Dengue is the most important mosquito-borne viral pathogen globally, with approximately 100 million cases of acute dengue annually. Infection can result in severe, life-threatening disease. Currently, there is no effective vaccine or licensed antiviral. Management is primarily supportive with fluids. Direct antiviral therapies that reduce dengue severity could be useful although these would need to inhibit all four viral serotypes effectively. This review focuses on the interventions that currently considered the gold standard in case management as well as exploratory therapies that have been studied in clinical trials. Although antiviral drug and therapeutic antibodies for dengue remain a work in progress, these studies have produced some promising results and may have the potential to be future drugs.

Biomarkers of severe dengue disease - a review

Dengue virus infection presents a wide spectrum of manifestations including asymptomatic condition, dengue fever (DF), or severe forms, such as dengue hemorrhagic fever (DHF) and dengue shock syndrome (DSS) in affected individuals. The early prediction of severe dengue in patients without any warning signs who may later develop severe DHF is very important to choose appropriate intensive supportive therapy since available vaccines for immunization are yet to be approved. Severe dengue responses include T and B cell activation and apoptosis, cytokine storm, hematologic disorders and complement activation. Cytokines, complement and other unidentified factors may transiently act on the endothelium and alter normal fluid barrier function of the endothelial cells and cause plasma leakage. In this review, the host factors such as activated immune and endothelial cells and their products which can be utilized as biomarkers for severe dengue disease are discussed.

Monocyte-plasmablast crosstalk during dengue

Dengue virus infection induces a dramatic expansion of B cell plasmablasts. In this issue, Kwissa et al. (2014) begin with transcriptomic analysis and then integrate studies in human clinical samples, nonhuman primates, and coculture of primary human cells to identify a role for CD14(+)CD16(+) monocytes in generating plasmablast responses during dengue virus infection.

Assessment of immune status using blood transcriptomics and potential implications for global health

The immune system plays a key role in health maintenance and pathogenesis of a wide range of diseases. Leukocytes that are present in the blood convey valuable information about the status of the immune system. Blood transcriptomics, which consists in profiling blood transcript abundance on genome-wide scales, has gained in popularity over the past several years. Indeed, practicality and simplicity largely makes up for what this approach may lack in terms of cell population-level resolution. An extensive survey of the literature reveals increasingly widespread use across virtually all fields of medicine as well as across a number of different animal species, including model organisms but also animals of economical importance. Dissemination across such a wide range of disciplines holds the promise of adding a new perspective, breadth or context, to the considerable depth afforded by whole genome profiling of blood transcript abundance. Indeed, it is only through such contextualization that a truly global perspective will be gained from the use of systems approaches. Also discussed are opportunities that may arise for the fields of immunology and medicine from using blood transcriptomics as a common denominator for developing interactions and cooperation across fields of research that have traditionally been and largely remain compartmentalized. Finally, an argument is made for building immunology research capacity using blood transcriptomics platforms in low-resource and high-disease burden settings.

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

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.