Now that we’ve finally established that autism spectrum disorder (ASD) is not caused by vaccinations, it’s time to uncover its real origins inside our DNA. And thanks to a first-of-its-kind machine-learning program from Princeton University and the Simons Foundation in New York City, scientists have a “highly enriched” gene pool that helps them better pin down the 400-1,000 genes that have already been identified as risk factors for the disorder. 

To gather the impressive pool of genes, scientists conducted an in-depth analysis of the human genome, starting with a functional brain network they constructed a little more than a year ago. This helped depict how genes work together in the brain’s molecular circuits. The team also used data from previous experiments that focused on how genes work throughout the whole body.

Taken together, scientists could better see the genes that are “turned on” in any given cell at certain points both in our development, as well as the genetic disruptions that occur in the brain of someone with ASD. The machine was then able to efficiently analyze more than 100 million gene interactions and pick out those which corresponded to ASD, landing on a pool of 2,500 genes that may be potential causes of autism.

dna New scientific discovery might make it easier to diagnose autism spectrum disorder. Photo Courtesy of Pixabay

Following up on these leads will help scientists delve deeper into autism's genetic basis and may also possibly lead to new diagnostic and treatment techniques.

"Geneticists can now focus on the top-ranked autism-risk gene predictions from our machine-learning program, both to direct future genome sequencing studies and to prioritize individual genes for experimental studies," said co-lead author Arjun Krishnan said in a recent statement.

While it’s likely that not all of the 2,500 top gene candidates are actually related to ASD, the findings help to bring forward several genes which were previously not linked to the disorder. Rather, Krishnan said, "these novel genes for autism risk are great candidates for further study."

Source: Krishnan A, Zhang R, Yao V, et al. Genome-Wide Prediction and Functional Characterization of the Genetic Basis of Autism Spectrum Disorder. Nature Neuroscience. 2016.

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