Despite the magnitude of the problem, surprisingly little is known of the molecular basis of metabolic syndrome and the way in which the different clinical symptoms are connected with each other and with type 2 diabetes and cardiovascular disease. Epidemiological studies in patient populations and in twins have shown that both genetic and environmental factors play a role in the development of metabolic syndrome and its progression to the various clinical symptoms. This complex interplay between genes and environment (e.g. diet, activity pattern) has been further supported by studies in animal models.

Strikingly, epidemiological data suggest that some individuals may respond quite well to life style changes and/or pharmaceutical intervention prior to the development of irreversible complications. However, at this point it is not possible to predict which individual will benefit from which intervention. The challenge of the current program is to identify biomarkers that will guide and predict the selection of the intervention strategy and to identify those individuals at greatest risk.

CMSB employs a dual genetics-genomics approach to identify individuals at risk, select intervention strategies and develop biomarkers of disease progression.

Genetics
Novel genes involved in the initiation and progression of metabolic syndrome and associated conditions will be identified using genetic approaches. For this purpose, a unique collection of affected families, isolated populations, various affected and non-affected unrelated individuals, sets of siblings and a very large collection of twins have been brought together within CMSB. These resources serve as an exquisite source for genetic linkage and mapping studies. In addition to human studies, mouse models for metabolic syndrome will be studied as well to identify susceptibility genes (QTL mapping) and biomarkers (systems biology) of disease onset and progression.

Genomics and Systems Biology
In parallel to the genetics program, CMSB provides the infrastructure for a genomics-based analysis of metabolic syndrome both in humans and in mouse models. Technologies and know-how are available for high-throughput gene expression analysis (transcriptomics), protein levels (proteomics) and protein metabolite levels (metabolomics). The integrated analysis of these complementary molecular aspects of life, called Systems Biology, requires extensive bioinformatics and biostatistics support. In order to manage and analyze these extremely large sets of data, a specific data integration, analysis and logistics (DIAL) platform has been established within CMSB.

Validation in animal models
Both the genetics- and genomics-based approaches are anticipated to deliver candidate genes and pathways involved in development and progression of metabolic syndrome. To validate candidate genes, a platform for the generation and analysis of a variety of animal models is fully operational. The animal models are extensively studied with the full repertoire of genomics technology. Importantly, the metabolic scutinization of the models is a crucial corner stone for a syndrome with such many metabolic faces.

The overall aim of the program is to elucidate the genetic, biochemical and environmental pathways that are involved in the development and progression of metabolic syndrome and are associated with type 2 diabetes and premature atherosclerosis. Understanding this integrated molecular network will enable the development of evidence-based intervention and prevention of metabolic syndrome and its serious complications. In this regard, better animal readout systems will be useful for validating potential new drug targets and drug candidates. It should also become possible to better tailor intervention strategies to individual risk profiles, allowing improved counseling of at-risk persons for suitable lifestyle measures.

Epidemiology: (patient)-populations for gene finding

1. FCH families. 39 multigeneration families with more than 600 members. Collaboration with prof.dr. Stalenhoef, Nijmegen.
2. LUMC Hyperlipidemia cohorts. Well-characterized patients with FH (>500), FD (>120), HTG (>300). Collaboration with Dr. Smelt.
3. Mouse strains with various forms of transgenesis of naturally induced phenotypes (hyperlipidemia, obesity, insulin resistance etc.) related to syndrome X.

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