Getting to the root of autism
Getting to the root of autism
To hear Stephen Scherer tell it, his path to becoming director of The Centre for Applied Genomics at Toronto’s Hospital for Sick Children (SickKids) and one of the world’s most accomplished autism researchers was pure serendipity.
It was the late 1990s, and Scherer was a staff scientist at SickKids working as part of the Human Genome Project, mapping and sequencing chromosome 7, a region that soon after was shown to hold genes linked to autism. “I didn’t know what autism was at the time, but I learned our hospital was seeing hundreds of these kids each year,” says Scherer. “I realized this was something I should be working on.”
A Canada Foundation for Innovation (CFI) grant allowed SickKids to purchase the latest gene-chip technology (a gene chip is a tool used to identify mutations in specific genes), which enabled Scherer to study DNA from autistic kids at a higher resolution. (SickKids was the second research group in North America to get the technology after the Houston, Texas, team that helped create it.) Scherer’s work demonstrated for the first time that errors in the way cells replicate DNA can result in some individuals getting more or less than one gene from each parent — a phenomenon known as copy number variation (CNV) — and it’s this variation that may underlie conditions like autism.
“That was groundbreaking,” says Scherer. “Until we published that in 2004, these types of genetic variants were not included in any genetic studies at all because people didn’t know they existed. Now, studying CNVs in genetic-disease research is done across the board, not just in human studies but in every animal study too.” In September, Scherer was listed by Thomson Reuters as a potential winner of the Nobel Prize in Physiology or Medicine for his work on CNV.
Between 2007 and 2013, Scherer’s lab produced many papers using ever higher-resolution technology looking at the DNA of kids with autism. By the summer of 2013, Scherer’s team was able to provide an explanation of what genetic factors were involved in a child’s autism to roughly 50 percent of all families it studied, up from about 10 percent in 2007.
In May of this year, Scherer collaborated with a computational biologist who was able to develop a computer algorithm to predict the likelihood that a genetic mutation causes (or does not cause) autism. “Now,” says Scherer, “diagnostic laboratories are using this algorithm when they’re doing their genetic testing in families with autism.”
The one constant in Scherer’s career has been the support of the CFI (“I’ve quite possibly had the most CFI grants of any Canadian,” he quips), with most of the funding supporting the purchase of technology and hardware, including several next-generation sequencing machines currently at work in his lab, and the high-performance, in-house computing capacity required to analyze the massive datasets his team generates. “Genomics is really an information science, so the most competitive scientists are the ones who have access to the most information,” says Scherer. “Information is generated using state-of-the-art technologies, and that’s why we’ve done so well. It’s kept me in Canada.”
This story was originally published in November 2014.