New VAAST software tool can identify disease-causing mutations in rare genetic disorders

Harnessing the new generation of rapid, highly accurate gene-sequencing techniques, a research team has identified the disease-causing mutation in a newly characterized rare genetic disease, by analyzing DNA from just a few individuals. The power and speed of the innovative bioinformatics tool marks a step toward personalized genomics—discovering causative mutations in individual patients.

"Our research is proof-of-principle that a new software tool called VAAST can identify disease-causing mutations with greater accuracy, using DNA from far fewer individuals, more rapidly, than was previously possible," said study leader Gholson J. Lyon, M.D., Ph.D., a psychiatrist and principal investigator in the Center for Applied Genomics at The Children's Hospital of Philadelphia. He added, "VAAST is a probabilistic disease-mutation finder for personal genomes; it can sort through the millions of gene variants in an individual's DNA to identify mutations that cause disease."

VAAST, an acronym for variant annotation, analysis and search tool, was developed by Mark Yandell, Ph.D., of the University of Utah and Martin G. Reese, Ph.D., of the informatics company Omicia, Inc. (Yandell is also a co-author on the current study). Lyon began the research at the University of Utah, where he collaborated with Yandell and clinical geneticist Alan Rope, M.D.

The study appeared online today in The American Journal of Human Genetics. In a separate paper published today in Genome Research, Yandell and Reese detail the development and applications of VAAST.

Although several of the existing software tools for analysis of personal genome sequences have been shown to be sufficiently powered to identify mutations underlying previously known disorders, Lyon notes that the current report is one of the first times a personal genome analysis tool has identified a previously unknown syndrome.

Calling VAAST "a major advance in the field," Eric J. Topol, M.D., director of the Scripps Translational Science Institute, said, "One of the most important and exciting opportunities in genomic medicine is the newfound ability to pinpoint the root cause of an unknown disease in an individual. The VAAST tool fulfills a significant unmet need of interpreting whole genome sequences and will have a remarkable impact on accurate genomic diagnosis of many individuals." Topol, a prominent expert in genomics and personalized medicine, had no involvement in the VAAST research.

Lethal Mutation Struck Baby Boys in Two Families

Lyon's team used VAAST to identify the cause of an extremely rare X-linked genetic disorder that is lethal in infancy. The disease-causing mutation is in a gene called NAA10. Affecting only males, it causes an aged appearance, facial abnormalities, developmental delay, and cardiac arrhythmias, among other conditions. Lyon and colleagues studied a family in Utah with a history of several boys with these symptoms who died in infancy, and analyzed DNA from five boys in the family. The researchers are tentatively calling the disease Ogden syndrome, reflecting the family's city of residence.

Although the detailed biological mechanisms remain to be investigated, the mutation alters an enzyme involved in a process called N-terminal acetylation, in which one end of a protein is modified by the addition of a chemical called an acetyl group. N-terminal acetylation occurs in 80 percent of human proteins, but abnormalities in this specific protein modification have not previously been shown to give rise to a human disorder. In this case, disrupting N-terminal acetylation results in symptoms ultimately causing death in infancy.

While the authors were preparing their manuscript, a second research group at the National Human Genome Research Institute notified them that they too had identified the same NAA10 mutation in a second family with three boys who had similar symptoms to those found in the Utah family. Further analysis showed the two families were unrelated—indicating that the disorder is a syndrome and not an isolated condition found only in one family.

In retrospect, said Lyon, the VAAST algorithm identified the causative mutation using data from just two individuals—an affected boy in one family and a mother (who was a carrier and not affected) in the unrelated family. This demonstrates that VAAST can identify disease-causing mutations based on DNA from only two unrelated individuals. "Based on this fact, we believe that VAAST will likely accelerate the discovery of disease-causing mutations in both common, complex disorders such as ADHD and autism, and in rare Mendelian disorders," said Lyon.