Merck Scientists Apply Innovative Research Method to Identify Changes in Gene Networks Linked to Obesity
Scientists at Merck Research Laboratories (MRL) and their collaborators performed genetic and gene expression analysis of tissues from a model of metabolic syndrome (a group of conditions that increases the risk of cardiovascular disease and diabetes) and a human population known to be susceptible to obesity. The resulting data were analyzed using powerful computational methods that integrate data from several sources to identify networks of gene interactions altered in individuals susceptible to obesity.
"These studies strongly support the theory that common diseases such as obesity result from genetic and environmental disturbances in entire networks of genes rather than in a handful of genes," said Eric E. Schadt, scientific executive director of Genetics at MRL and a senior author on both studies. "If diseases like obesity are the result of complex networks of genes, the accurate reconstruction of these networks will be critical to identifying the best therapeutic targets."
Much of the emphasis of biomedical research today is directed towards advancing knowledge of the genetic basis of disease and understanding whether DNA variations associated with certain conditions actually contribute to disease or merely act as signposts. The novel approach pioneered by MRL scientists advances the understanding of how multiple; complex DNA variations lead to alterations in entire gene networks that increase an individual's susceptibility to disease.
"The combination of scientific excellence and a focus on patients is the foundation of our work at Merck Research Laboratories," said Kathleen M. Metters, senior vice president, World Wide Basic Research, MRL. "The publication of this important research builds on our history of innovation at Merck and underscores our ongoing commitment to translating breakthrough research into the development of safe and effective medicines."
About the Studies
In two related studies, Merck researchers and collaborators used large-scale analyses of data on DNA variations, gene expression patterns in disease-relevant tissues and clinical data to identify molecular networks underlying metabolic disorders. In the first study,(1) Merck researchers and colleagues from the University of California at Los Angeles used liver and fat tissue samples from mice to identify genetic variations associated with obesity, diabetes and atherosclerosis. The authors then constructed gene networks and identified core groups of genes in these networks (highly interrelated sub-networks) that were causally related to relevant traits associated with obesity, diabetes and heart disease. Based on various analyses, the authors identified and experimentally validated three novel genes causally related to obesity-associated traits: Lpl, Pmp1l and Lactb.
In the second study,(2) which was based on methods developed in the mouse study, researchers from Merck, deCODE Genetics and the National University, Iceland, constructed gene expression networks associated with obesity traits using blood and fat tissue samples and clinical data from more than 1,000 people in Iceland. A gene expression network constructed from human fat tissue contained a similar core group of genes found to be causally related to obesity in the mouse study.
Merck's novel research approach is based on the ability to obtain and analyze high-quality gene expression data from tissues that are relevant to disease, coupled with the Company's unique bioinformatics capabilities that enable improved understanding of disease by integrating different types of biological data sets into a coherent whole.
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(1) Chen Y., Zhu J. Lum PY, et al. Variations in DNA elucidate molecular networks that cause disease. Nature, published online March 16, 2008.
(2) Emilsson V., Thorleifsson G., Leonardson AS, et al. Genetics of human gene expression and gene-gene transcriptional networks. Nature, published online March 16, 2008.
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Posted: March 2008