Discovering the different genes that contribute to a complex disease is like searching in the proverbial haystack for an unknown number of needles--some much smaller than others, often blending into the background, and many of them widely separated from each other.
But if some needles are linked to each other by fine threads, you might pull out clumps of them together.
Using a novel approach that combines a statistical tool that identifies genes interacting on the same biological pathways with highly automated gene-hunting techniques that scan the whole genome, an international team of researchers has discovered new genes involved in Crohn's disease. Crohn's disease is a chronic and painful condition caused by inflammation of the gastrointestinal tract. The researchers, led by scientists at The Children's Hospital of Philadelphia, say their approach broadens the power of gene discovery studies to ferret out potential targets for disease treatments.
In a complex disorder such as Crohn's disease, many different genes interact to cause the illness. Research over the past few years have identified many of the genes with the strongest effects, but many other genes with important roles may produce weaker or ambiguous signals in the large-scale studies, and go overlooked. "Our pathway-based approach aggregates information from multiple sources to detect modest effects from genes associated with each other," said study leader Hakon Hakonarson, M.D., Ph.D., director of the Center for Applied Genomics at Children's Hospital.
The study appeared online today in the American Journal of Human Genetics . It will be published in the journal's print edition on March 13.
Currently the workhorse of gene-hunting is genome-wide association (GWA), which uses automated analytic equipment to sweep through the full range of all 23 human chromosomes and detect the most significant gene variants associated with a given disease. Those variants, each a change in a single DNA base, are called single nucleotide polymorphisms (SNPs).
However, individual GWA studies often do not have the statistical power to detect subtle but important variants that are involved in disease development. By using an algorithm developed by Kai Wang, Ph.D., at the Center for Applied Genomics, Hakonarson's study team created a pathway-based approach that seeks out interacting or related genes along the same biological pathway. "We applied our pathway-based approach to GWA data for Crohn's disease, but conducted the search without starting with a hypothesis focused on a specific suspected pathway," said Hakonarson. "Among hundreds of known biological pathways, the one that surfaced from the analysis as being most significant included genes already known to be relevant to the biology of Crohn's disease."