prof. dr. H.J. Lambers Heerspink
VENI project: A novel approach of personalized medicine: considering multiple effects of a single drug: 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.
DIAMETRIC Database: The aim of this project is to establish a large database with data from various clinical trials that have been conducted in patients with type 2 diabetes at various stages of renal disease in order to assess and compare the relationship between different risk markers (e.g. blood pressure albuminuria HbA1c) and the risk for renal and cardiovascular disease progression. Another major aim of the database is to assess the relationship between short-term changes in biomarkers and their relationship with changes in long-term risk for renal / CV events. Since the database comprises the whole spectrum of renal disease progression, the comparative performance of (changes in) several biomarkers will be tested at different stages of disease. Currently, the database includes data from the following trials: BENEDICT, IRMA-2, LIFE-type 2 diabetes, RENAAL, IDNT, PLANET, VITAL, RADAR, SUN-micro and SUN-overt trials, ALTITUDE trials.
Syskid: Approximately 40% of all chronic kidney diseases is of diabetic aetiology. Besides eventual progression towards end stage renal diseae, diabetic nephropathy impacts the patient quality of life including cardiovascular complications and bone metabolism disorders. The sysKID consortium aims to discover novel biomarkers for diabetic patients at risk for progression of renal disease. These biomarkers will provide the clinician with tools to evaluate the clinical evaluation for early stage diagnosis and prognosis and allows the clinical pharmacologist to assess individual therapy response and optimize personalized medicine.
|Last modified:||10 September 2018 12.24 p.m.|