Scientists said their research found a link between ASD and damage to proteins in blood plasma.
In addition to forming the basis of a diagnostic test, the researchers believe their findings suggest that the build-up of AGEs and oxidation may actually help account for the symptoms associated with autism. About 30-35% of cases of ASD are linked to genetic variants, but there is no exact formula for predicting autism.
This complexity extends all the way to how it's diagnosed: Children can start to show visible signs of autism by the age of 18 months, but there is no single medical test that can diagnose it, and it often takes years to confirm a suspected case, potentially delaying treatment.
Rabbini's team isn't the first to try looking for biomarkers of autism in the blood - similar research is ongoing elsewhere, with so far similarly encouraging results. These include speech disturbances, repetitive and/or compulsive behaviour, hyperactivity, anxiety, and difficulty to adapt to new environments, some with or without cognitive impairment.
"Our test is expected to improve the accuracy of ASD diagnosis from 60 - 70 per cent now achieved by experts in neurological disorders to approximately 90 per cent accuracy and potentially offered at all well-equipped hospitals with or without high level expertise in neurological disorders", lead author Naila Rabbani, a biologist at the University of Warwick in the United Kingdom, told Gizmodo via email.
By examining the protein, children with ASD were found to have higher levels of oxidation marker dityrosine (DT) and certain sugar-modified compounds called advanced glycation end products (AGEs).
One in every 100 people in the United Kingdom has ASD, with more boys more likely to be diagnosed than girls, according to estimates.
They then created four different predictive algorithms that tried to tell whether a child had ASD or not, based on the presence of these biomarkers.
"Our discovery could lead to earlier diagnosis and intervention", said Rabbani, "We hope the tests will also reveal new causative factors". Working with a further collaborator at the University of Birmingham, the changes in multiple compounds were combined together using artificial intelligence algorithm techniques to develop a mathematical equation to distinguish between ASD and healthy controls. With further testing we may reveal specific plasma and urinary profiles or "fingerprints" of compounds with damaging modifications. The outcome was a diagnostic test better than any method now available. "This may help us improve the diagnosis of ASD and point the way to new causes of ASD".
The next steps will be repeat studies with further groups to assess if the test can identify ASD at very early stages, indicate how it could develop further and assess if treatment is working.