New research is offering stronger proof that a blood test may be able to accurately predict whether or not a child has autism.

A study published in the June edition of the journal Bioengineering & Translational Medicine is offering further evidence that an algorithm assessing metabolites in blood can distinguish kids with autism.

The method first showed promising results in a paper published last year. In that study of 83 children with autism and 76 neurotypical children, researchers said they were able to correctly determine in 97.6 percent of cases which blood samples came from those on the spectrum.

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The latest study relied on an separate sample in an effort to validate the initial findings.

Researchers used a set of existing data from 154 children with autism that was collected for studies at the Arkansas Children’s Research Institute. The data set included information on 22 of the 24 metabolites that were involved in the original algorithm.

Ultimately, the approach was able to predict autism with 88 percent accuracy, the study found.

“This is extremely promising,” said Juergen Hahn of the Rensselaer Polytechnic Institute in Troy, N.Y. who led the research.

Currently, autism is diagnosed through clinical assessments. Though the developmental disorder can be flagged in children as young as age 2, government data indicates that most kids are not diagnosed until after age 4.

If researchers are able to identify a biomarker in blood or otherwise, the hope is that children could be identified at earlier ages when treatment is considered to be most effective.

“The most meaningful result is the high degree of accuracy we are able to obtain using this approach on data collected years apart from the original data set,” Hahn said. “This is an approach that we would like to see move forward into clinical trials and ultimately into a commercially available test.”