in vitro Characterisation of the Complement Cascade for Predicting Patient Outcome Post-operatively
Date: 30 September 2019
University of Exeter
PhD in Medical Studies
The identification of surgical patients at higher risk of infection enables targeted allocation of critical care resources to improve patient mortality. The Complement cascade of the innate immune system is known to increase risk of infection if compromised and can be tested in vitro as a potential method for stratification of high-risk ...
The identification of surgical patients at higher risk of infection enables targeted allocation of critical care resources to improve patient mortality. The Complement cascade of the innate immune system is known to increase risk of infection if compromised and can be tested in vitro as a potential method for stratification of high-risk patients. Existing assays of Complement function are laboratory bound and require trained personnel to operate and interpret. This thesis describes the development of novel immunoassays for C3, C5a, TCC and TNFα, based on a multiplex biosensor platform with a duty cycle of <15 minutes. The assays for C3 and C5a were validated for use with serum samples with a CV of 23% and 21% respectively, within a dynamic range of 3.2-12.5 nM. When combined with automated data analysis presented here, the biosensor assays provide a step towards easy functional testing of Complement biomarkers at point-of-care. A new technique for assessing the monomeric purity of antibody samples is also presented for quality control in future immunoassay development. A hypothesis-driven selection of candidate biomarker tests, denoting a compromised immune state, is possible with a mathematical model. Prerequisite techniques for optimising nonlinear models with unknown parameters are presented in a systems biology study of IgG binding to protein A/G to determine reaction kinetics and stoichiometry. The same techniques were used to fit a 187parameter model of in vitro Complement activation to ELISA data from pooled human serum, with a mean absolute error of 14%. Sensitivity and flux analyses verified that the optimised model was consistent with existing knowledge of the system: regulation via Properdin and Factor H was predicted quantitatively. The optimised model predicted the effect of Complement depletion on the concentration-time profiles of proteins following activation: new phenotypes of immune state. Model predictions for the variation in C5a and TCC formation rate phenotypes in healthy adults showed no significant difference (P>0.05) from the serum data of 22 volunteers. The model and cohort data provide an initial estimate of effect size for future clinical studies investigating the ability of these Complement activation phenotypes to identify high-risk surgical patients or identify the onset of infection.
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