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Blood Test Can Predict Autism In Kids With 88 Percent Accuracy


Tom Hale


Tom Hale

Senior Journalist

Tom is a writer in London with a Master's degree in Journalism whose editorial work covers anything from health and the environment to technology and archaeology.

Senior Journalist

Approximately 1.7 percent of children are diagnosed with autism spectrum disorder. EvgeniiAnd/Shutterstock

In 2017, scientists claimed to have created a blood test for autism. It was pretty big news, but not everyone was totally convinced, with some health organizations arguing it was too soon to start singing its praises.

Now, the same research team is back with a new peer-reviewed study that has reaffirmed the success of their first results. Once again, it's still early days, but it could pave the way for a more effective way to diagnose autism in younger children.


“We are able to predict with 88 percent accuracy whether children have autism,” lead author Professor Juergen Hahn, head of the Rensselaer Polytechnic Institute Department of Biomedical Engineering, said in a statement“This is extremely promising.”

Approximately 1.7 percent of children are diagnosed with autism spectrum disorder (ASD), a range of lifelong conditions that affect a person's social interaction, communication, and behavior. It’s widely considered that an early diagnosis provides the best outcomes for people with ASD; however, symptoms are often tricky to identify in young children.

As reported in the journal Bioengineering & Translational Medicine, the test is essentially a fine-tuning of their 2017 research that correctly identified ASD with 97.6 percent of children.

The test uses an algorithm to sort through huge amounts of data on metabolites, the by-products of metabolism, present in blood samples. Firstly, it searches for different patterns of metabolites related to two connected cellular pathways thought to be associated with autism. It then uses a predictive algorithm to compare the different patterns of metabolites found in kids with ASD and those without ASD. For the follow-up study, the team tested this approach on the original 149 children from the 2017 study, then applied it to a new independent group of 154 children. The previous study used data on 24 metabolites, while the new method cut this down to just 22.


In sum, it was able to successfully predict whether a child had ASD with 88 percent accuracy.

“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 dataset,” said Hahn. “This is an approach that we would like to see move forward into clinical trials and ultimately into a commercially available test.”

A separate study in February of this year showed how the presence of certain proteins could also be used to identify ASD in children, with equally impressive results. It will certainly be a few years until a viable test will be in doctor’s surgeries; however, rest assured that progress is slowly but surely stomping forwards.


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