Objectives, background and description of work in WP

Research of coronary heart disease (CHD) in the past has not been fully rewarding in its goal to classify patients on the basis of genetic profiles. Here we hypothesize that molecular profiles (integrated patterns of gene variants, expression levels and metabolites) mined from a biobank representing a disturbed lipid and fatty acid metabolism contribute to CHD risk and will provide tools for classification of CHD patients better than those based solely on genetic variation or classical risk factors (serum lipid and glucose levels).

We will use a distributed biobank (RIVM Bilthoven, UMC Maastricht, Wageningen University, Leiden University Medical Centre) and mining technology to find profiles associating with CHD risk. We will study diseased subjects (negative effects) but also moderately healthy subjects, and extremely long-living subjects (positive effects). We will connect to a novel BBMRI metabolomics initiative which is being planned to link all existing metabolomics datasets in NL cohorts for the purpose of establishing which profiles predict CHD and which genetic background influences such profiles.

The goal of this project is the set-up of the right biobank infrastructure to make mining of the combined CHD data possible. The data is distributed and database technology is needed to set up a federated data repository. We have to deal with distributed local data, data management and privacy-preservation. For the mining meta data has to be added to allow for data fusion, and the diversity of data requires new methods and algorithms.

The distributed biobank contains for a start the following studies:

1. Morgen study (Monitoring Project on Risk Factors and Health in the Netherlands),RIVM, concerns a sample of people from Amsterdam, Doetinchem and Maastricht in the age of 20-59 years. The study was conducted in the years 1993 to 1997, with the primary aim of collecting data on risk factors and health. It is a Health Survey Questionnaire for measuring quality of life.
2. Carema study, UMC Maastricht. The CAREMA study consists of 21,148 participants, born in 1927-1977 and randomly sampled from Maastricht and surrounding communities in 1987-1997. At baseline, all participants completed a self-administered questionnaire. Height, weight, blood pressure, total and HDL cholesterol levels were measured during a physical examination.
3. Leiden Longevity Study, Leiden University. One of the world's biggest and the most extended series of families that are genetically enriched for longevity. Includes sophisticated phenotypes and bio-materials, genomic, proteomic, and metabolomic data. (Netherlands Center for Healthy Ageing NCHA and Biobanking and Biomolecular Resources Research Infrastructure BBMRI)