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

Several beta-blockers are metabolized by the polymorphic enzyme cytochrome P450 2D6 (CYP2D6). CYP2D6*4 is the main polymorphism leading to decreased enzyme activity. The clinical significance of impaired elimination of beta-blockers is controversial, and most studies suffer from inclusion of small numbers of poor metabolizers (PMs) of CYP2D6. In this study, the association between CYP2D6*4 and blood pressure or heart rate was examined in 1,533 users of beta-blockers in the Rotterdam Study, a population-based cohort study. In CYP2D6 *4/*4 PMs, the adjusted heart rate in metoprolol users was 8.5 beats/min lower compared with *1/*1 extensive metabolizers (EMs) (P < 0.001), leading to an increased risk of bradycardia in PMs (odds ratio = 3.86; 95% confidence interval 1.68-8.86; P = 0.0014). The diastolic blood pressure in PMs was 5.4 mm Hg lower in users of beta-blockers metabolized by CYP2D6 (P = 0.017) and 4.8 mm Hg lower in metoprolol users (P = 0.045) compared with EMs. PMs are at increased risk of bradycardia.

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.

Human metapneumovirus (HMPV) encodes a small hydrophobic (SH) protein of unknown function. HMPV from which the SH open reading frame was deleted (HMPVΔSH) was viable and displayed similar replication kinetics, cytopathic effect and plaque size compared with wild type HMPV in several cell-lines. In addition, no differences were observed in infection efficiency or cell-to-cell spreading in human primary bronchial epithelial cells (HPBEC) cultured at an air-liquid interphase. Host gene expression was analyzed in A549 cells infected with HMPV or HMPVΔSH using microarrays and mass spectrometry (MS) based techniques at multiple time points post infection. Only minor differences were observed in mRNA or protein expression levels. A possible function of HMPV SH as apoptosis blocker, as proposed for several members of the family Paramyxoviridae, was rejected based on this analysis. So far, a clear phenotype of HMPV SH deletion mutants in vitro at the virus and host levels is absent.

BackgroundDengue 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 FindingsSequential 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/SignificanceTime 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.