In an effort to better understand the molecular basis of a complex inherited disorder, a group of researchers has developed a way to simultaneously study the effects of multiple mutations associated with the disorder (Proc. Natl. Acad. Sci. USA published online 24 May 2010; doi: 10.1073/pnas.1000219107). The team, led by Nicholas Katsanis of Duke University (Durham, NC), used zebrafish to analyze the functions of the 125 mutations known to be associated with Bardet-Biedl syndrome (BBS).

BBS is a ciliopathy, meaning that people who have BBS have defective cilia, finger-like projections that stick out of many types of cells. People with BBS can have a variety of symptoms, including damaged retinas, obesity, mental retardation and more than the usual number of toes or fingers. These traits vary greatly between people who have BBS, hinting at the syndrome's complex genetic underpinnings.

Katsanis and his team first carried out in vivo tests in zebrafish embryos to determine whether specific mutations would cause the zebrafish to develop specific defects. They then carried out in vitro tests on cells to find out if any of the unusual zebrafish embryo activity that they had observed in the in vivo tests could be explained by defective mammalian cell behavior. They found that mutations in 1 of 14 genes known to be associated with BBS are responsible for the disorder. Further analysis showed that common mutations in other genes, which researchers previously thought were benign, may modify the severity and diversity of the symptoms of BBS.

To determine the sensitivity and accuracy of their in vivo results, the researchers compared their data with results from previous clinical studies. They found that their tools predicted that 48 of 49 alleles previously known to be pathogenic were indeed pathogenic, suggesting their method had a sensitivity of 98%. Out of 17 mutations known to be benign, 14 showed up as benign in all of the in vivo assays, suggesting a false-positive rate of less than 10%.

According to Katsanis, their study shows that it is possible to use a vertebrate model to predict whether a specific mutation plays a role in a complex disease. “A next step is to develop similar tools to let us evaluate various human genetic mutations within the context of their functions,” Katsanis said in a press release. “Genotype must have a predictive value or it doesn't tell us much. Knowing all of the disease-related variants in a genome is only a starting point.”