Effect of short-term dietary interventions on molecular signatures in man

1. Effect of short-term dietary interventions on molecular signatures in man • S. Gaj1,2,3, C.T.A. Evelo2,3, R.P.Mensink1,2 Introduction The metabolic syndrome (MS) is described as a cluster of risk markers (abdominal obesity, hypertension, dyslipidemia and insulin resistance)related to an increased risk to develop cardiovascular diseases and type II diabetes. This syndrome is extremely prevalent in western countries, with obesity as a main risk factor. People displaying three of these markers are considered to have MS. • There is no uniform strategy to prevent or treat the MS, although most approaches are focused on modifying the subjects lifestyle through : • Dietary changes • Energy restriction • Physical activity • An initiator of MS is chronic metabolic stress, which relates to changes in gene expression, protein synthesis and plasma and/or cellular concentrations of metabolites, which might lead to the disruption of cellular function. The level of chronic metabolic stress is higher in persons with a high BMI. • Our focus will be on the identification of molecular signatures related to the early phase of MS. • Aims • Effect of high fat vs low fat diet on gene expression level (muscle) ? • Relation effects with gene expression in peripheral mononuclear blood cells (PMBCs) ? • Variability of gene expression in and between humans ? • To answer all these questions a nutrigenomics approach will be used. • Study Design • 11 male subjects divided into • Lean • (BMI < 23, n = 6) • Slight obese (BMI = 28-32, n = 5) • Guidelines for diet and physical activity • Postprandial test (4h): High Fat vs Low Fat diet • Cross-over design • Regular blood sampling for PBMC transcriptomics (and metabolomics). FIGURE 2 – STUDY DESIGN • Muscle biopsies at t=0h and t=4h for transcriptomics. For transcriptomics we’ll use the Affymetrix HG-U133 2.0 chips. • Some thoughts By using specific clustering techniques (neural network, k-means, …) we want to group interesting gene expression profiles coming out of the collected PBMC’s and muscle tissue. Furthermore, we want to validate whether the same clusters are present in subjects from the same group and see if they are different compared to the other group. Next to clustering, pathway-visualization tools (GeneGO, GenMAPP) will also be used to find out whether there are any specific gene-expression changes in adaptive or stress-related pathways. • Tell us about your experience in measuring blood gene expression profiles. • Tell us about your experience in measuring metabolic profiles. • Tell us about pathway visualization tools you’re having good experience with. • Tell us about good clustering techniques which we might use. FIGURE 1 – PREVALENCE OF OBESITY IN EUROPE (1999-2004) This picture was taken from the International Obesity Task Force who assessed the obesity prevalence in Europe. These data are based on published surveys or unpublished data. 1. WCFS 2. University Maastricht 3. BiGCaT BioInformatics P.O. Box 557 P.O. Box 616 P.O. Box 616 6700 AN WAGENINGEN 6200 MD Maastricht 6200 MD Maastricht The Netherlands The Netherlands The Netherlands Phone +31 317 485383 Phone +31 43 3882913 Phone +31 43 3881231 Fax +31 317 485384 Fax +31 43 381621 Fax +31 43 3884149 FOR CORRESPONDENCE S.Gaj@HB.Unimaas.NL