According to recent research, the genetic risk for autism is primarily associated with versions of genes commonly found in the population, as opposed to rare variants. These rare variants, or spontaneous glitches in DNA, only accounted for 2.6 percent of the genetic risk for autism, while common gene variants accounted to 52 percent of the risk. This recent study, published in the journal Nature Genetics, was funded by the National Institutes of Health. The study focused on data from Sweden’s universal health registry, using medical records from 3,000 people with autism compared with an age-matched control group.
Dr. Joseph Buxbaum of the Icahn School of Medicine at Mount Sinai in NYC, states, “Genetic variation likely accounts for roughly 60 percent of the liability for autism, with common variants comprising the bulk of its genetic architecture.” He continues, “Although each exerts just a tiny effect individually, these common variations in the genetic code add up to substantial impact, taken together”.
The research provides a better understanding of the genetic factors that drive autism. Dr. Buxbaum states, “Within a given family, the mutations could be a critical determinant that leads to the manifestation of ASD in a particular family member.” He continues, “The family may have common variation that puts it at risk, but if there is also a spontaneous mutation on top of that, it could push an individual over the edge.” Autism geneticists can better detect common and rare genetic variations associated with risk.
Studying the genetic code that is shared by most people has been challenging, as limitations of sample size and composition make it difficult to estimate the relative influence of common and rare spontaneous variation. As a result, researchers are focusing on new statistical methods to allow them to sort out the heritability of the disorder with more reliability. This recent study allowed investigators to compare quite a large sample of individuals on the spectrum with matched controls. Dr. Thomas Lehner, chief of NIMH’s Genomics Research Branch, states, “This is a different kind of analysis than employed in previous studies. Data from genome-wide association studies was used to identify a genetic model instead of focusing just on pinpointing genetic risk factors. The researchers were able to pick from all of the cases of illness within a population-based registry.”
With researchers getting a better grasp on the genetic framework, they are gaining a better understanding of which duplications of genetic material and spontaneous mutations are correlated to autism development. The researchers stated, “Even though such rare spontaneous mutations accounted for only a small fraction of autism risk, the potentially large effects of these glitches makes them important clues to understanding the molecular underpinnings of the disorder.”