New research suggests that determining whether or not a child likely has autism could one day be as simple as spitting in a cup.

By looking at RNA in saliva, researchers say they can identify kids on the spectrum with 85 percent accuracy.

The findings come from a study of 456 children ages 19 months to 6 years from various locations across the country, 238 of whom had autism, 84 with developmental delay and 134 who were typically developing. RNA levels were measured from each child’s saliva sample. Then, researchers used machine-learning algorithms to identify the top RNAs in 372 of the samples, which were validated in the other 84 samples.

“Though children with autism have diverse genetic backgrounds, we found that a set of 32 RNA factors in their saliva could accurately distinguish them from peers without autism,” said Dr. Steven Hicks of the Pennsylvania State College of Medicine who led the study published this month in the journal Frontiers in Genetics.

“Given this array of ASD risk factors, we believe a ‘poly-omics’ RNA-based approach that integrates genetic, epigenetic and metagenomics methods would be well suited to the development of an objective biomarker-based test,” Hicks said.

Currently, children who are flagged for autism through standard screenings often wait over a year to see a specialist for a diagnostic evaluation.

The researchers said their saliva test is not designed to be a screening tool, but rather could be used to help determine which children who are identified by screenings should be prioritized by specialists.

Accordingly, the test could help speed up diagnosis, researchers said, and get children in treatment earlier when it’s considered most effective.

“The ability to accurately discriminate between children with autism and their peers with non-ASD developmental delay is of paramount importance in the field,” said Frank Middleton of SUNY Upstate Medical University who also worked on the study.