We hypothesize that patient populations may serve as a good model for the general population, with stronger relations between biomarkers and higher numbers and in time more nearby end-points, leading to higher efficiency of proof-of-principle studies for biomarkers. Omic-technologies, like NMR-metabolimics provide large amounts of data of which the predictive value for development of diabetes and for complications of diabetes is still in the beginning of its evaluation. We are currently generating such data in large cohorts of the general population, patient cohorts and in intervention studies in patients with diabetes.
The aim of this project is to evaluate omics biomarkers for:
- Prediction of the development of diabetes;
- For the development of complications of diabetes in general populations cohorts, patients population cohorts and intervention studies and to compare their performance;
- Prediction of drug response to commonly used and novel treatments.
Collectively these studies should foster individualization of treatment in patients with diabetes.