Despite improvements in hemodynamic monitoring, antibiotics, and other supportive therapies, septicemia remains the most common cause of death in intensive care units. Although there have been modest successes in treating sepsis in animal models, little progress has been made in human studies. Possible reasons for this failure include heterogeneity of the patient population and the complex redundancy of pathways of inflammation by different microbial pathogens.

One pilot study examining only eight patients with diverse degrees of concomitant disease, variable sources of infection, and a broad range of sepsis severity addressed the question whether gene expression profiling may be a helpful tool for diagnosis of sepsis [5]. The patient group was deliberately selected to be heterogeneous in age, sources of infection, and diagnosis in order to identify robust sepsis-related expression signatures. As a control, four patients were included who had undergone spine surgery. For gene expression analysis, mRNA from whole blood was analyzed using a microarray comprising 340 probes for human genes relevant to inflammation and related processes. A list of 19 upregulated and 31 downregulated genes was found with most significant changes. A strong similarity of the expression pattern of these genes was found in all patients. For example, genes such as TGF-b1, DUSP-9 and 10, IL-18, S100A8, and S100A12 were upregulated while TNF, TIMP-1, and GILZ were downregulated. The unity of the responses suggests that the principle of this approach can be adapted to diagnosis of the early stage of sepsis. Moreover, the authors claimed a striking correlation between the conventional diagnostic classification and the gene expression analysis. Therefore, such approaches may be helpful if larger cohorts of patients are used to identify marker genes which can predict the outcome of sepsis at an early phase of the disease and provide clinicians with a tool by which to optimize individual therapeutic strategies.

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