Quantim
Quantification of Innate Immune Function in Whole Blood Infection Assays
Leibniz Institute for Natural Product Research and Infection Biology – Hans Knöll Institute
Leibniz Institute for Natural Product Research and Infection Biology – Hans Knöll Institute
Department of Anesthesiology and Intensive Care Medicine, Jena University Hospital
Sepsis – i.e. a severe infection associated with organ dysfunction – is a common and lethal syndrome. Despite the availability of a wide range of data on cellular and molecular processes involved in systemic inflammation, little progress has been made in pharmacologically modulating the inflammatory dysregulation in sepsis to reduce concomitant pathologies and improve outcome. A major reason for this is the heterogeneity of sepsis as a clinical syndrome, resulting from highly diverse pathological conditions and showing variable disease kinetics in individual patients. Therefore, it is of central importance to develop tools that enable categorization of septic patients and predict efficacies for tailor-made therapeutic interventions. Within the QUANTIM project, a human whole blood model of infection will be used in combination with advanced mathematical modeling to quantify the dynamic global organization of innate immune responses to infection. For a broad panel of pathogens blood samples from healthy volunteers will be used to provide a comparative analysis of regulatory networks governing inflammation and pathogen elimination. These data will then be compared to analyses of clinical samples from septic patients and patients who have survived sepsis despite adverse prognosis. The main objective of this project is to identify patterns of dysregulation specific for groups of patients with defined disease patterns and immunological alterations in post-sepsis patients. For this, we will integrate knowledge on the clinical course of these patients, which are provided from close cooperation with projects of our partners in the Center for Sepsis Control and Care (CSCC). The identification of functional classifiers will allow differentiation of sepsis patients, which can form a basis for future patient stratification.