Platelet density per monocyte predicts adverse events in patients after percutaneous coronary intervention.

Monocyte recruitment to damaged endothelium is enhanced by platelet binding to monocytes and contributes to vascular repair. Therefore, we studied whether the number of platelets per monocyte affects the recurrence of adverse events in patients after percutaneous coronary intervention (PCI). Platelet-monocytes complexes with high and low median fluorescence intensities (MFI) of the platelet marker CD42b were isolated using cell sorting. Microscopic analysis revealed that a high platelet marker MFI on monocytes corresponded with a high platelet density per monocyte while a low platelet marker MFI corresponded with a low platelet density per monocyte (3.4 ± 0.7 vs 1.4 ± 0.1 platelets per monocyte, P=0.01). Using real-time video microscopy, we observed increased recruitment of high platelet density monocytes to endothelial cells as compared with low platelet density monocytes (P=0.01). Next, we classified PCI scheduled patients (N=263) into groups with high, medium and low platelet densities per monocyte and assessed the recurrence of adverse events. After multivariate adjustment for potential confounders, we observed a 2.5-fold reduction in the recurrence of adverse events in patients with a high platelet density per monocyte as compared with a low platelet density per monocyte [hazard ratio=0.4 (95% confidence interval, 0.2-0.8), P=0.01]. We show that a high platelet density per monocyte increases monocyte recruitment to endothelial cells and predicts a reduction in the recurrence of adverse events in patients after PCI. These findings may imply that a high platelet density per monocyte protects against recurrence of adverse events.

Response of human skin to esthetic scarification.

This study was undertaken to investigate changes in RNA expression in previously healthy adult human skin following thermal injury induced by contact with hot metal that was undertaken as part of esthetic scarification, a body modification practice. Subjects were recruited to have pre-injury skin and serial wound biopsies performed. 4 mm punch biopsies were taken prior to branding and 1 h, 1 week, and 1, 2 and 3 months after injury. RNA was extracted and quality assured prior to the use of a whole-genome based bead array platform to describe expression changes in the samples using the pre-injury skin as a comparator. Analysis of the array data was performed using k-means clustering and a hypergeometric probability distribution without replacement and corrections for multiple comparisons were done. Confirmatory q-PCR was performed. Using a k of 10, several clusters of genes were shown to co-cluster together based on Gene Ontology classification with probabilities unlikely to occur by chance alone. OF particular interest were clusters relating to cell cycle, proteinaceous extracellular matrix and keratinization. Given the consistent expression changes at 1 week following injury in the cell cycle cluster, there is an opportunity to intervene early following burn injury to influence scar development.

NetWeAvers: an R package for integrative biological network analysis with mass spectrometry data.

SUMMARY: The discovery of functionally related groups in a set of significantly abundant proteins from a mass spectrometry experiment is an important step in a proteomics analysis pipeline. Here we describe NetWeAvers (Network Weighted Averages) for analyzing groups of regulated proteins in a network context, e.g. as defined by clusters of protein-protein interactions. NetWeAvers is an R package that provides a novel method for analyzing proteomics data integrated with biological networks. The method includes an algorithm for finding dense clusters of proteins and a permutation algorithm to calculate cluster P-values. Optional steps include summarizing quantified peptide values to single protein values and testing for differential expression, such that the data input can simply be a list of identified and quantified peaks. AVAILABILITY AND IMPLEMENTATION: The NetWeAvers package is written in R, is open source and is freely available on CRAN and from netweavers.erasmusmc.nl under the GPL-v2 license. CONTACT: e.mcclellan@erasmusmc.nl

The hypoxia-inducible microRNA cluster miR-199a∼214 targets myocardial PPARδ and impairs mitochondrial fatty acid oxidation.

Peroxisome proliferator-activated receptor δ (PPARδ) is a critical regulator of energy metabolism in the heart. Here, we propose a mechanism that integrates two deleterious characteristics of heart failure, hypoxia and a metabolic shift toward glycolysis, involving the microRNA cluster miR-199a∼214 and PPARδ. We demonstrate that under hemodynamic stress, cardiac hypoxia activates DNM3os, a noncoding transcript that harbors the microRNA cluster miR-199a∼214, which shares PPARδ as common target. To address the significance of miR-199a∼214 induction and concomitant PPARδ repression, we performed antagomir-based silencing of both microRNAs and subjected mice to biomechanical stress to induce heart failure. Remarkably, antagomir-treated animals displayed improved cardiac function and restored mitochondrial fatty acid oxidation. Taken together, our data suggest a mechanism whereby miR-199a∼214 actively represses cardiac PPARδ expression, facilitating a metabolic shift from predominant reliance on fatty acid utilization in the healthy myocardium toward increased reliance on glucose metabolism at the onset of heart failure.

iFUSE: integrated fusion gene explorer.

UNLABELLED: We present iFUSE (integrated fusion gene explorer), an online visualization tool that provides a fast and informative view of structural variation data and prioritizes those breaks likely representing fusion genes. This application uses calculated break points to determine fusion genes based on the latest annotation for genomic sequence information, and where relevant the structural variation (SV) events are annotated with predicted RNA and protein sequences. iFUSE takes as input a Complete Genomics (CG) junction file, a FusionMap fusion detection report file or a file already analysed and annotated by the iFUSE application on a previous occasion. RESULTS: We demonstrate the use of iFUSE with case studies from tumour-normal SV detection derived from Complete Genomics whole-genome sequencing results. AVAILABILITY: iFUSE is available as a web service at http://ifuse.erasmusmc.nl.

Huvariome: a web server resource of whole genome next-generation sequencing allelic frequencies to aid in pathological candidate gene selection.

BACKGROUND: Next generation sequencing provides clinical research scientists with direct read out of innumerable variants, including personal, pathological and common benign variants. The aim of resequencing studies is to determine the candidate pathogenic variants from individual genomes, or from family-based or tumor/normal genome comparisons. Whilst the use of appropriate controls within the experimental design will minimize the number of false positive variations selected, this number can be reduced further with the use of high quality whole genome reference data to minimize false positives variants prior to candidate gene selection. In addition the use of platform related sequencing error models can help in the recovery of ambiguous genotypes from lower coverage data. DESCRIPTION: We have developed a whole genome database of human genetic variations, Huvariome, determined by whole genome deep sequencing data with high coverage and low error rates. The database was designed to be sequencing technology independent but is currently populated with 165 individual whole genomes consisting of small pedigrees and matched tumor/normal samples sequenced with the Complete Genomics sequencing platform. Common variants have been determined for a Benelux population cohort and represented as genotypes alongside the results of two sets of control data (73 of the 165 genomes), Huvariome Core which comprises 31 healthy individuals from the Benelux region, and Diversity Panel consisting of 46 healthy individuals representing 10 different populations and 21 samples in three Pedigrees. Users can query the database by gene or position via a web interface and the results are displayed as the frequency of the variations as detected in the datasets. We demonstrate that Huvariome can provide accurate reference allele frequencies to disambiguate sequencing inconsistencies produced in resequencing experiments. Huvariome has been used to support the selection of candidate cardiomyopathy related genes which have a homozygous genotype in the reference cohorts. This database allows the users to see which selected variants are common variants (> 5% minor allele frequency) in the Huvariome core samples, thus aiding in the selection of potentially pathogenic variants by filtering out common variants that are not listed in one of the other public genomic variation databases. The no-call rate and the accuracy of allele calling in Huvariome provides the user with the possibility of identifying platform dependent errors associated with specific regions of the human genome. CONCLUSION: Huvariome is a simple to use resource for validation of resequencing results obtained by NGS experiments. The high sequence coverage and low error rates provide scientists with the ability to remove false positive results from pedigree studies. Results are returned via a web interface that displays location-based genetic variation frequency, impact on protein function, association with known genetic variations and a quality score of the variation base derived from Huvariome Core and the Diversity Panel data. These results may be used to identify and prioritize rare variants that, for example, might be disease relevant. In testing the accuracy of the Huvariome database, alleles of a selection of ambiguously called coding single nucleotide variants were successfully predicted in all cases. Data protection of individuals is ensured by restricted access to patient derived genomes from the host institution which is relevant for future molecular diagnostics.

Deep proteome profiling of circulating granulocytes reveals bactericidal/permeability-increasing protein as a biomarker for severe atherosclerotic coronary stenosis.

Coronary atherosclerosis represents the major cause of death in Western societies. As atherosclerosis typically progresses over years without giving rise to clinical symptoms, biomarkers are urgently needed to identify patients at risk. Over the past decade, evidence has accumulated suggesting cross-talk between the diseased vasculature and cells of the innate immune system. We therefore employed proteomics to search for biomarkers associated with severe atherosclerotic coronary lumen stenosis in circulating leukocytes. In a two-phase approach, we first performed in-depth quantitative profiling of the granulocyte proteome on a small pooled cohort of patients suffering from chronic (sub)total coronary occlusion and matched control patients using stable isotope peptide labeling, two-dimensional LC-MS/MS and data-dependent decision tree fragmentation. Over 3000 proteins were quantified, among which 57 candidate biomarker proteins remained after stringent filtering. The most promising biomarker candidates were subsequently verified in the individual samples of the discovery cohort using label-free, single-run LC-MS/MS analysis, as well as in an independent verification cohort of 25 patients with total coronary occlusion (CTO) and 19 matched controls. Our data reveal bactericidal/permeability-increasing protein (BPI) as a promising biomarker for severe atherosclerotic coronary stenosis, being down-regulated in circulating granulocytes of CTO patients.