Detecting the Genetic Causes of the Metabolic Syndrome
The patients have a number of disorders that have a negative influence on each other including obesity, hypertension, insulin resistance, and dyslipidemia. These risk factors increase the chance for suffering from type II diabetes, heart attack, and stroke. In addition to an unhealthy diet too little exercise, genetic risk factors, too, are considered triggers for the very complex clinical picture of the metabolic syndrome.
Using a novel approach Professor Norbert Hübner (Max Delbrück Center for Molecular Medicine, MDC, Berlin-Buch, Germany) and Timothy J. Aitman (Imperial College, London, UK), as well as researchers in the Czech Republic and the U.S., have launched a search for possible susceptibility genes which predispose individuals to the metabolic syndrome. They combined two different analysis techniques, the DNA chip technique (microarray) and linkage analysis, to identify genes which may contribute to the pathogenesis of the metabolic syndrome. With the aid of the DNA chips, they could identify which genes are transcribed or expressed in order to produce proteins. Linkage analysis allowed them to establish a relationship between particular traits, such as hypertension, and particular genes. Using both techniques, they studied fat and kidney tissue of laboratory rats. Both tissues play an important role in the development of the metabolic syndrome. At loci where the analysis results overlap, the researchers discovered 73 so-called candidate genes for hypertension. This data is expected to provide new insights into the regulatory mechanisms of genes and signal pathways and, thus, into the cause of metabolic disorders and cardiovascular diseases. The scientists, whose research has just been published in the renowned journal Nature Genetics* (online doi: 10.1038/ng1522), plan to extend the search for genetic risk factors to patients with metabolic syndrome.
*Integrated transcriptional profiling and linkage analysis for identification of genes underlying disease
Norbert Hubner1, Caroline A Wallace2*, Heike Zimdahl1*, Enrico Petretto2*, Herbert Schulz1, Fiona Maciver2, Michael Mueller2, Oliver Hummel1, Jan Monti1, Vaclav Zidek3, Alena Musilova3, Vladimir Kren3,4, Helen Causton2, Laurence Game2, Gabriele Born1, Sabine Schmidt1, Anita Müller1, Stuart A Cook2, Theodore W Kurtz5, John Whittaker6, Michal Pravenec3,4 & Timothy J Aitman2
*These authors contributed equally to this work
Correspondence should be addressed to N.H. (nhuebner@mdc-berlin.de), M.P. (pravenec@biomed.cas.cz) or T.J.A. (t.aitman@csc.mrc.ac.uk)
1Max-Delbrück-Center for Molecular Medicine (MDC), Berlin-Buch 13125, Germany 2MRC Clinical Sciences Centre, Faculty of Medicine, Imperial College, London W12 0NN, UK 3Institute of Physiology, Czech Academy of Sciences and Centre for Applied Genomics, 142 20 Prague 4, Czech Republic 4Institute of Biology and Medical Genetics, Charles University, 120 00 Prague 2, Czech Republic 5University of California, San Francisco, California 94143-0134, USA 6Department of Epidemiology and Public Health, Imperial College, London W2 1PG, UK
Barbara Bachtler
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