Multiple Hypothesis Testing in Microarray Experiments

DNA microarrays are a new and promising biotechnology which allows the monitoring of expression levels in cells for thousands of genes simultaneously. An important and common question in microarray experiments is the identification of differentially expressed genes, i.e., genes whose expression levels are associated with a response or covariate of interest. The biological question of differential expression can be restated as a problem in multiple hypothesis testing: the simultaneous test for each gene of the null hypothesis of no association between the expression levels and the responses or covariates. As a typical microarray experiment measures expression levels for thousands of genes simultaneously, large multiplicity problems are generated. This article discusses different approaches to multiple hypothesis testing in the context of microarray experiments and compares the procedures on microarray and simulated datasets

Role of interleukin 6 in myocardial dysfunction of meningococcal septic shock

Background Myocardial failure has a central role in the complex pathophysiology of septic shock and contributes to organ failure and death. During the sepsis-induced inflammatory process, specific factors are released that depress myocardial contractile function. We aimed to identify these mediators of myocardial depression in meningococcal septic shock. Methods We combined gene-expression profiling with protein and cellular methods to identify a serum factor causing cardiac dysfunction in meningococcal septic shock. We identified genes that were significantly upregulated in blood after exposure to meningococci. We then selected for further analysis those genes whose protein products had properties of a myocardial depressant factor—specifically a 12–25 kDa heat-stable protein that is released into serum shortly after onset of meningococcal infection. Findings We identified 174 significantly upregulated genes in meningococcus-infected blood: six encoded proteins that were of the predicted size and had characteristics of a myocardial depressant factor. Of these, interleukin 6 caused significant myocardial depression in vitro. Removal of interleukin 6 from serum samples of patients with meningococcaemia and from supernatants of inflammatory cells stimulated by meningococci in vitro abolished the negative inotropic activity. Furthermore, concentrations in serum of interleukin 6 strongly predicted degree of myocardial dysfunction and severity of disease in children with meningococcal septic shock. Interpretation Interleukin 6 is a mediator of myocardial depression in meningococcal disease. This cytokine and its downstream mediators could be a target for future treatment strategies

Gene Expression-Based Classifiers Identify <em>Staphylococcus aureus</em> Infection in Mice and Humans

<div><p><em>Staphylococcus aureus</em> causes a spectrum of human infection. Diagnostic delays and uncertainty lead to treatment delays and inappropriate antibiotic use. A growing literature suggests the host’s inflammatory response to the pathogen represents a potential tool to improve upon current diagnostics. The hypothesis of this study is that the host responds differently to <em>S. aureus</em> than to <em>E. coli</em> infection in a quantifiable way, providing a new diagnostic avenue. This study uses Bayesian sparse factor modeling and penalized binary regression to define peripheral blood gene-expression classifiers of murine and human <em>S. aureus</em> infection. The murine-derived classifier distinguished <em>S. aureus</em> infection from healthy controls and <em>Escherichia coli</em>-infected mice across a range of conditions (mouse and bacterial strain, time post infection) and was validated in outbred mice (AUC>0.97). A <em>S. aureus</em> classifier derived from a cohort of 94 human subjects distinguished <em>S. aureus</em> blood stream infection (BSI) from healthy subjects (AUC 0.99) and <em>E. coli</em> BSI (AUC 0.84). Murine and human responses to <em>S. aureus</em> infection share common biological pathways, allowing the murine model to classify <em>S. aureus</em> BSI in humans (AUC 0.84). Both murine and human <em>S. aureus</em> classifiers were validated in an independent human cohort (AUC 0.95 and 0.92, respectively). The approach described here lends insight into the conserved and disparate pathways utilized by mice and humans in response to these infections. Furthermore, this study advances our understanding of <em>S. aureus</em> infection; the host response to it; and identifies new diagnostic and therapeutic avenues.</p> </div