Two new studies by scientists in the US, Iceland and France suggest susceptibility to obesity, and by implication other common diseases, involves changes in entire networks of highly connected genes and is not just a case of variations in specific individual genes. Thus the genetic predisposition to obesity and other common diseases appears to make more sense when scientists examine the emergent properties, the “macro-level” effects, of gene networks rather than the individual “micro-level” effects of disease-susceptibility genes.

The studies are the work of researchers at Merck & Co in the US, deCODE Genetics in Iceland, and academic centres in the US and France, and are published in the 16 March advance online issue of Nature.

Merck said that the studies also demonstrated how genomic techniques can be used to shed light on the complexity of common disease causes where multiple genetic changes are involved.

Identifying DNA variants that increase a person’s susceptibility to disease is one of the main goals of genetic studies that use a “forward genetics approach”, wrote the researchers.

But studies that focus on finding individual disease-susceptibility genes don’t really tell us much about how the genes lead to disease, they added. In fact, at the “functional” level there is very little new information, which stops scientists making a definitive identification that says this is how this set of genes causes this set of disease traits.

In these two studies the researchers developed what they describe as an “alternative to the classic forward genetics approach”. They analysed DNA variations, patterns of gene expression in disease tissue, and clinical data on a large scale to identify which gene networks linked to metabolic disorders (a range of symptoms that are thought to cause obesity, diabetes and atherosclerosis or heart disease).

In the first study, researchers from Merck and the University of California at Los Angeles (UCLA) took liver and fat tissue from mice to find genes that might be linked to obesity, diabetes and heart disease.

They created gene networks and located highly connected sub-networks of core genes that were known to be linked to obesity, diabetes and heart disease. They also identified, and validated at the experimental level, three new genes thought to cause obesity: Lpl, Pmp1l and Lactb.

The researchers concluded that:

“Our analysis provides direct experimental support that complex traits such as obesity are emergent properties of molecular networks that are modulated by complex genetic loci and environmental factors.”

In the second study researchers from Merck, deCODE Genetics and the National University, Iceland, used methods developed in the first study to create a gene expression network of obesity traits, except this time they used blood and fat tissue samples and other clinical data given by more than 1,000 people in Iceland.

The researchers also found, as they did in the first study on mice, a network of core genes thought to cause obesity, that showed significant overlap with the same network in mice.

They concluded that:

“A core network module in humans and mice was identified that is enriched for genes involved in the inflammatory and immune response and has been found to be causally associated to obesity-related traits.”

The unique combination of DNA analysis and bioinformation processing in Merck’s new technique is the main reason this research was successful, said Merck. These “powerful computational models” helped to improve “understanding of disease by integrating different types of biological data sets into a coherent whole”, said the company in a press statement.

“Variations in DNA elucidate molecular networks that cause disease.”
Yanqing Chen, Jun Zhu, Pek Yee Lum, Xia Yang, Shirly Pinto, Douglas J. MacNeil, Chunsheng Zhang, John Lamb, Stephen Edwards, Solveig K. Sieberts, Amy Leonardson, Lawrence W. Castellini, Susanna Wang, Marie-France Champy, Bin Zhang, Valur Emilsson, Sudheer Doss, Anatole Ghazalpour, Steve Horvath, Thomas A. Drake, Aldons J. Lusis & Eric E. Schadt.
Nature advance online publication 16 March 2008.
doi:10.1038/nature06757

Click here for Abstract.

“Genetics of gene expression and its effect on disease.”
Valur Emilsson, Gudmar Thorleifsson, Bin Zhang, Amy S. Leonardson, Florian Zink, Jun Zhu, Sonia Carlson, Agnar Helgason, G. Bragi Walters, Steinunn Gunnarsdottir, Magali Mouy, Valgerdur Steinthorsdottir, Gudrun H. Eiriksdottir, Gyda Bjornsdottir, Inga Reynisdottir, Daniel Gudbjartsson, Anna Helgadottir, Aslaug Jonasdottir, Adalbjorg Jonasdottir, Unnur Styrkarsdottir, Solveig Gretarsdottir, Kristinn P. Magnusson, Hreinn Stefansson, Ragnheidur Fossdal, Kristleifur Kristjansson, Hjortur G. Gislason, Tryggvi Stefansson, Bjorn G. Leifsson, Unnur Thorsteinsdottir, John R. Lamb, Jeffrey R. Gulcher, Marc L. Reitman, Augustine Kong, Eric E. Schadt & Kari Stefansson.
Nature advance online publication 16 March 2008.
doi:10.1038/nature06758

Click here for Abstract.

Sources: Journal abstracts, Merck press statement.

Written by: Catharine Paddock, PhD