Gene networks underlie disease?

An international group of researchers have developed a novel method for identifying entire networks of genes and their association to disease, providing a more accurate picture of the genetic risks associated with specific diseases than single genes can provide.

Photo: linkurl:Joanna Servaes;http://joanna-servaes.magix.net via Wikimedia Commons

In the proof-of-concept paper published today (8th September) in __Nature__, the researchers used an integrated genomics approach to identify a network of inflammatory and anti-viral genes, present in both rats and humans, that seems to play a role in autoimmune diseases such as type 1 diabetes. "It is an important discovery," said linkurl:Constantin Polychronakos,;http://www.montreal-diabetes-research-center.org/en/polychronakos/polychronakos.asp an endocrinologist at the McGill University Health Center who was not involved in the study. "Instead of looking at individual genes and trying to make sense out of it, they were looking at whole networks of genes." Many common diseases have an exceedingly complex genetic architecture, with a multitude of genes interacting with each other and the environment to result in disease. Genome-wide association (GWA) studies, however, a widely-used method for unraveling the genetic underpinnings of disease, focus on the incredibly small portion of the DNA -- the less than 1 percent of the genome that varies among individuals. This approach identifies genetic variants that seem to be associated with particular diseases, but these variants often play only a minor role in the development of disease, and their physiological effects remain largely unknown. "You have a relationship between a genetic variant and the associated disease, but you don't really know what it's doing," explained linkurl:Norbert Hubner,;http://www.mdc-berlin.de/en/bimsb/MDC_groups/Huebner/index.html a geneticist at Max Delbrück Center for Molecular Medicine (MDC) in Berlin and one of the authors of the paper. Hubner and his colleagues examined seven different rat tissues for individual variations in the expression levels of various transcription factors. Then, using a predictive statistical approach, they could identify which gene variants likely led to those differences in transcription factor expression. They identified one particular transcription factor that they decided to investigate further. Interferon regulatory factor 7 (IRF7) was active in the majority of the rat tissues studied and is known to be a key regulator of inflammatory processes. It seemed to be the central player of a network of more than 300 genes involved in inflammatory processes and which appeared to be active in macrophages -- immune cells known to be critical participants in inflammation and the development of autoimmune disorders -- as as well as their precursors, monocytes. The team thus dubbed this network IRF7-driven inflammatory network, or IDIN for short. To determine whether a similar network was operating in human monocytes, the researchers used previously collected data on gene expression and GWA studies in humans to identify an analogous network. "We found the same network in both human populations [we looked at]," said coauthor linkurl:Enrico Petretto,;http://www.csc.mrc.ac.uk/Research/Groups/GMC/IntegrativeGenomicsMedicine/ a computational biologist at Imperial College London. "There was very significant overlap between rats and humans." Notably, many of the human genes were known factors in type 1 diabetes (T1D). Type 1 diabetes is very similar in humans and mice, mostly because both species have very similar immune systems, explained Polychronakos. So the discovery that this inflammatory network is highly conserved in rats and humans is no surprise, he said. But because most genetic studies of T1D have focused on single genes, and humans and rats don't share many of these risk genes, translating studies from animal models to humans has been challenging. "How can you have a very similar disease when the genes involved are very different?" asked Polychronakos. "It's because the genes affect a certain pathway...a certain biological process that depends on a chain of events. If we look at networks instead of individual genes, then the picture becomes much clearer." M. Heinig, et al., "A trans-acting locus regulates an anti-viral expression network and type 1 diabetes risk," Nature, doi:10.1038/nature09386, 2010
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[August 2010]