As we wrap up 2014 and look towards 2015, one final study from last year has recently shed a new light on better understanding the genetic roots of autism and identifying those individuals most at risk for being diagnosed with autism later in life. While there have been a number of advances in better understanding the neurology and causation behind autism, scientists have long believed that unlocking the genetic code is the best bet for helping to treat and someday eliminate autism. This is because autism is an extremely heritable disorder that effects one in sixty-eight children and thus much of the research into better understanding autism has focused on genetics.

Traditionally, scientists have taken what is called a “gene-by-gene” approach to identifying the genes associated with autism by taking an inventory of all the genes present. Then they would typically identify those genes that appeared abnormal and try to link them with certain symptoms of autism.

However, the main issue with the gene-by-gene approach has been that it has identified too many potential genetic suspects without providing researchers with the insight they need to truly pinpoint specific autism-related genes. “What’s special about autism is that it doesn’t seem like it’s a one-gene thing,” said Stanford University School of Medicine geneticist Michael Snyder. Snyder went on to say that the gene-by-gene approach might take too long and be too tough to produce real results and thus proposed taking a broader look at the “normal” biological landscape and seeing how individuals with genes mutated by autism map onto the landscape.

This led Synder and his team to undertake the monumental task of computationally identifying protein modules bound by their inter-related functions_, over which they then laid a map of gene variants that had been previously implicated in autism. In all, there were 383 suspect genes that the team of researchers hoped to gain better insight into and while at first there weren’t any obvious correlations, as the team probed further they were able to notice a few modules that very clearly had direct connections with autism.

One module involved molecular activity that goes on all over the brain, particularly involving synapses, the tiny spaces where electrochemical signals cross for one neuron to another. This helps explain why so much autism research points toward problems with synapses. Another module that was rich in autism correlations was found in the corpus callosum—the thick band of fibers that connects the brain’s two hemispheres—an area where researchers had found links with certain developmental disorders, but not with autism in particular.

Overall, the study uncovered twenty-eight previously unknown links to autism in addition to confirming some previously indicated links. While the study did not find one particular smoking gun, the researchers found this methodology far more productive and efficient than the traditional gene-by-gene approach, paving the way for far greater insight into the genetic make-up of autism. The team hopes their research will allow them to learn how to alter the genetic activity in ways that will eliminate specific symptoms of autism. But for the time being, scientists and therapists alike are praising both these new discoveries and methods, which will now allow them to identify those at risk for the disorder far earlier.