|| Type 2 diabetes is a major and rapidly growing health problem worldwide and is associated with considerable morbidity. Recent novel therapeutic strategies were not very successful in improving renal and cardiovascular protection. The explanation may lie, at least partly, in that drug therapy is not being optimized to the individual patient, but rather to a group of patients. Yet many drugs have multiple effects that vary across patients. Each of those drug effects may in turn affect the ultimate outcome in its own way. Hence, one may observe within a patient a drug-induced change in one parameter that may benefit a patient in the long term, but a drug-induced change in another parameter induces more renal and/or cardiovascular risk. These opposite effects (discordant responses) need to be taken into account. To enhance end-organ protection, the responses in multiple parameters in individual patients should be targeted and optimized. I propose integrating epidemiology and molecular biology approaches to investigate the clinical implications and underlying molecular mechanisms of the responses in multiple parameters in individual patients and to determine ways of optimizing them. |
The project consists of two parts:
1. Data from large clinical trials with different drugs will be analyzed to investigate the consequences of different response patterns in individual patients on clinical outcomes.
2. Plasma and urine samples from a prospective study will be analyzed for an integrated computation system biology approach. Patient characteristics as well as proteomic/metabolomic measurements will be combined to dissect the underlying mechanisms of discordant treatment responses and to find ways to optimize them.