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A test for autism is on the horizon, powered by AI – Big Think

Autism spectrum disorder (ASD) is a very broad set of neurodevelopmental conditions. Around 1 in 160 children have it worldwide. It’s a much larger ratio in the U.S. at 1 in 68. While symptoms vary significantly, those who experience ASD often have trouble communicating, managing their emotions or developing social skills.

Some with autism develop speech problems. Others have difficulty reading social situations or adapting to new environments. Others still exhibit anxiety, hyperactivity or other compulsive behaviors. ASD sometimes comes with cognitive impairment, but not always.

Children usually start showing signs of autism at 18 months of age or so. Research has shown that early intervention can help make the condition more manageable. Unfortunately, no one knows what causes it, although it’s thought to have both genetic and environmental components. What’s more, no reliable diagnostic is currently in place (here is how the disease is currently diagnosed). But thanks to work by an international team of scientists, an autism test is now on the horizon.

Researchers at the University of Warwick in the UK, partnering with colleagues at the University of Bologna, in Italy, have identified a number of different biomarkers present in those with autism, that’s absent in those who don’t. Their discovery should lead to a medical test for the condition—either a blood or urine test—a first of its kind. The results of the study were published in the journal Molecular Autism.

For the study, scientists compared blood samples from 38 Italian children diagnosed autism (29 boys and 9 girls) to 31 children without the diagnosis (23 boys and 8 girls). The children were all between the ages of 7 and 12. With help from colleagues at the University of Birmingham, U.K., researchers used artificial intelligence algorithms to compare and contrast the proteins in the two groups’ samples. This allowed for the development of an algorithm that could tell which children have ASD with 90% accuracy, and which children didn’t, with 87% accuracy.

The algorithm kept an eye on higher levels of a molecule known as dityrosine (DT), which is present when proteins are damaged during oxidation or advanced glycation end products (AGE). The latter occurs when proteins or fats come into contact with glucose and are altered by it. Those with autism showed higher levels of protein damage.

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