Innovative Research Method Applied To Identify Changes In Gene Networks Linked To Obesity

Main Category: Obesity / Weight Loss / Fitness
Also Included In: Diabetes;  Genetics
Article Date: 19 Mar 2008 - 1:00 PDT

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Merck & Co., Inc. today announced the publication of two studies providing evidence that genetic susceptibility to obesity involves changes in entire networks of genes and is not limited to mutations in several specific genes. The work also showcases how genomic techniques may be used to understand the complex changes at the root of common diseases where multiple complex genetic changes are thought to be involved. The studies received advanced online publication in this week's issue of the peer-reviewed journal Nature.

Scientists at Merck Research Laboratories (MRL) and colleagues from the University of California 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 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 sign posts. 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 & Co., Inc. and underscores our ongoing commitment to translating breakthrough research into the development of safe and effective medicines."

About the Studies

In two related studies, MRL 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 MRL 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: lipoprotein lipase (Lpl), lactamase β (Lactb) and protein phosphatase 1-like (Ppm1l).

In the second study,2 which was based on methods developed in the mouse study, researchers from Merck & Co., Inc., 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 & Co., Inc.'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.

About Merck & Co., Inc.

Merck & Co., Inc. of Whitehouse Station, N.J., USA is a global research-driven pharmaceutical company dedicated to putting patients first. Established in 1891, Merck & Co., Inc. discovers, develops, manufactures and markets vaccines and medicines to address unmet medical needs. The Company devotes extensive efforts to increase access to medicines through far-reaching programs that not only donate Merck & Co., Inc. medicines but help deliver them to the people who need them. Merck & Co., Inc. also publishes unbiased health information as a not-for-profit service. For more information, visit http://www.merck.com.

Forward-Looking Statement
This press release contains "forward-looking statements" as that term is defined in the Private Securities Litigation Reform Act of 1995. These statements are based on management's current expectations and involve risks and uncertainties, which may cause results to differ materially from those set forth in the statements. The forward-looking statements may include statements regarding product development, product potential or financial performance. No forward-looking statement can be guaranteed and actual results may differ materially from those projected. Merck & Co., Inc. undertakes no obligation to publicly update any forward-looking statement, whether as a result of new information, future events, or otherwise. Forward-looking statements in this press release should be evaluated together with the many uncertainties that affect Merck & Co., Inc.'s business, particularly those mentioned in the risk factors and cautionary statements in Item 1A of Merck & Co., Inc.'s Form 10-K for the year ended Dec. 31, 2007, and in its periodic reports on Form 10-Q and current reports on Form 8-K, if any, which the Company incorporates by reference.

References

-- Chen Y., Zhu J. Lum PY, et al. Variations in DNA elucidate molecular networks that cause disease. Nature, published online March 16, 2008.

-- Emilsson V., Thorleifsson G., Leonardson AS, et al. Genetics of human gene expression and gene-gene transcriptional networks. Nature, published online March 16, 2008.