Transcriptome assists prognosis of disease severity in respiratory syncytial virus infected infants.

Respiratory syncytial virus (RSV) causes infections that range from common cold to severe lower respiratory tract infection requiring high-level medical care. Prediction of the course of disease in individual patients remains challenging at the first visit to the pediatric wards and RSV infections may rapidly progress to severe disease. In this study we investigate whether there exists a genomic signature that can accurately predict the course of RSV. We used early blood microarray transcriptome profiles from 39 hospitalized infants that were followed until recovery and of which the level of disease severity was determined retrospectively. Applying support vector machine learning on age by sex standardized transcriptomic data, an 84 gene signature was identified that discriminated hospitalized infants with eventually less severe RSV infection from infants that suffered from most severe RSV disease. This signature yielded an area under the receiver operating characteristic curve (AUC) of 0.966 using leave-one-out cross-validation on the experimental data and an AUC of 0.858 on an independent validation cohort consisting of 53 infants. A combination of the gene signature with age and sex yielded an AUC of 0.971. Thus, the presented signature may serve as the basis to develop a prognostic test to support clinical management of RSV patients.

DC immunotherapy in HIV-1 infection induces a major blood transcriptome shift.

OBJECTIVE: This study aimed to evaluate the effect of dendritic cell (DC) vaccination against HIV-1 on host gene expression profiles. DESIGN: Longitudinal PBMC samples were collected from participants of the DC-TRN trial for immunotherapy against HIV. Microarray-assisted gene expression profiling was performed to evaluate the effects of vaccination and subsequent interruption of antiretroviral therapy on host genome expression. Data from the DC-TRN trial were compared with results from other vaccination trials. METHODS: We used Affymetrix GeneChips for microarray gene expression analysis. Data were analyzed by principal component analysis and differential gene expression was assessed using linear modeling. Gene ontology enrichment and gene set analysis were used to characterize differentially expressed genes. Transcriptome analysis included comparison with PBMCs obtained from DC-vaccinated melanoma patients and of healthy individuals who received seasonal influenza vaccination. RESULTS: DC-TRN immunotherapy in HIV-infected individuals resulted in a major shift in the transcriptome. Longitudinal analysis demonstrated that changes in the transcriptome sustained also during interruption of antiretroviral therapy. After DC-vaccination, the transcriptome was enriched for cellular immunity associated genes that were also induced in healthy adults who received live attenuated influenza virus vaccination. These beneficial responses were accompanied by detrimental signals of general immune activation. CONCLUSIONS: The DC-TRN induced changes in the transcriptome were profound, lasting, and consisted of both protective signals and signatures of inflammation and immune exhaustion, with a net result of decreased viral load, without clinical benefit. Thus transcriptome analysis provides useful information, dissecting both positive and negative effects, for the evaluation of safety and efficacy of immunotherapeutic strategies.

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.

Metagenomic survey for viruses in Western Arctic caribou, Alaska, through iterative assembly of taxonomic units.

Pathogen surveillance in animals does not provide a sufficient level of vigilance because it is generally confined to surveillance of pathogens with known economic impact in domestic animals and practically nonexistent in wildlife species. As most (re-)emerging viral infections originate from animal sources, it is important to obtain insight into viral pathogens present in the wildlife reservoir from a public health perspective. When monitoring living, free-ranging wildlife for viruses, sample collection can be challenging and availability of nucleic acids isolated from samples is often limited. The development of viral metagenomics platforms allows a more comprehensive inventory of viruses present in wildlife. We report a metagenomic viral survey of the Western Arctic herd of barren ground caribou (Rangifer tarandus granti) in Alaska, USA. The presence of mammalian viruses in eye and nose swabs of 39 free-ranging caribou was investigated by random amplification combined with a metagenomic analysis approach that applied exhaustive iterative assembly of sequencing results to define taxonomic units of each metagenome. Through homology search methods we identified the presence of several mammalian viruses, including different papillomaviruses, a novel parvovirus, polyomavirus, and a virus that potentially represents a member of a novel genus in the family Coronaviridae.

HeatMapper: powerful combined visualization of gene expression profile correlations, genotypes, phenotypes and sample characteristics.

BACKGROUND: Accurate interpretation of data obtained by unsupervised analysis of large scale expression profiling studies is currently frequently performed by visually combining sample-gene heatmaps and sample characteristics. This method is not optimal for comparing individual samples or groups of samples. Here, we describe an approach to visually integrate the results of unsupervised and supervised cluster analysis using a correlation plot and additional sample metadata. RESULTS: We have developed a tool called the HeatMapper that provides such visualizations in a dynamic and flexible manner and is available from http://www.erasmusmc.nl/hematologie/heatmapper/. CONCLUSION: The HeatMapper allows an accessible and comprehensive visualization of the results of gene expression profiling and cluster analysis.

Mutations in nucleophosmin (NPM1) in acute myeloid leukemia (AML): association with other gene abnormalities and previously established gene expression signatures and their favorable prognostic significance.

Mutations in nucleophosmin NPM1 are the most frequent acquired molecular abnormalities in acute myeloid leukemia (AML). We determined the NPM1 mutation status in a clinically and molecularly well-characterized patient cohort of 275 patients with newly diagnosed AML by denaturing high-performance liquid chromatography (dHPLC). We show that NPM1 mutations are significantly underrepresented in patients younger than 35 years. NPM1 mutations positively correlate with AML with high white blood cell counts, normal karyotypes, and fms-like tyrosine kinase-3 gene (FLT3) internal tandem duplication (ITD) mutations. NPM1 mutations associate inversely with the occurrence of CCAAT/enhancer-binding protein-alpha (CEBPA) and NRAS mutations. With respect to gene expression profiling, we show that AML cases with an NPM1 mutation cluster in specific subtypes of AML with previously established gene expression signatures, are highly associated with a homeobox gene-specific expression signature, and can be predicted with high accuracy. We demonstrate that patients with intermediate cytogenetic risk AML without FLT3 ITD mutations but with NPM1 mutations have a significantly better overall survival (OS) and event-free survival (EFS) than those without NPM1 mutations. Finally, in multivariable analysis NPM1 mutations express independent favorable prognostic value with regard to OS, EFS, and disease-free survival (DFS).