Individualizing immunosuppression to prevent infection in transplant recipients

Transplantation is a life-saving procedure for patients with end-stage organ disease, but requires life-long immunosuppressive medications to prevent rejection. This increases risk and severity of infections that don’t normally affect healthy individuals, which contribute significantly to morbidity and mortality. Despite advances in transplantation, dosing of immunosuppression remains crude and empirical, with no reliable biomarkers and limited individualization between patients. Currently, dosing is based on donor-recipient HLA matching, weight, time post-transplant and calcineurin inhibitor levels. Measuring immune function more precisely would be extremely useful as dosing could be modified to give patients just enough to prevent rejection but not so much that they develop infections. Several biomarkers of immune function are currently being explored as measures of the net state immunosuppression. The Quantiferon®-Monitor (QFM) is a novel assay that measures blood levels of markers of immunity. We recently performed a prospective cohort study of 80 lung transplant recipients and found that QFM results correlated with intensity of immunosuppression, and patients with low values experienced more serious opportunistic infections. This is promising early data but before we can proceed to a randomized trial that incorporates QFM into decision making about dosing of immunosuppression, we need to understand in greater detail the relationships between QFM values and infections beyond the first post-transplant year. We also need to compare it to other immune markers alone and in combination, then develop a system for integrating these results with current practices that can be easily applied in future trials and ultimately into routine clinical decision making. This project aims to improve our ability to individualize immunosuppression management minimizing both under-immunosuppression leading to rejection and over-immunosuppression resulting in infections and drug toxicity. It will be a clinical research project involving retrospective data (some of which is already collected and some will need to be collected from electronic medical records) and statistical analyses. There is no laboratory component. Previous experience using R is desirable but not essential. It is a collaborative project involving both the infectious diseases department (Dr Bradley Gardiner, Professor Anton Peleg) and lung transplant department (Professor Glen Westall). The scope of work can be adapted to suit the interests of the student.