Novel blood, urine tests may predict autism in kids

Novel blood, urine tests may predict autism in kids
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In a first of its kind, scientists have developed novel tests that can indicate autism in children, a finding that could lead to earlier diagnosis of the developmental disorder that impairs the ability to communicate and interact.

In a first of its kind, scientists have developed novel tests that can indicate autism in children, a finding that could lead to earlier diagnosis of the developmental disorder that impairs the ability to communicate and interact.

The new blood and urine tests searches for damage to proteins and could lead to earlier detection of autism and advance treatment.
"Our discovery could lead to earlier diagnosis and intervention,"said lead author Naila Rabbani, Reader at the University of Warwick in Britain.

"We hope the tests will also reveal new causative factors. With further testing we may reveal specific plasma and urinary profiles or 'fingerprints' of compounds with damaging modifications.

"This may help us improve the diagnosis of autism and point the way to new causes of autism spectrum disorders," Rabbani said.

Genetic causes have been found in 30-35 per cent of cases of autism and the remaining 65-70 per cent of cases are thought to be caused by a combination of environmental factors, multiple mutations, and rare genetic variants.

However, the researchers believe that the new tests could reveal yet to be identified causes of autism.
In the study, published in Molecular Autism, the team analysed blood and urine samples from children who were diagnosed with autism and a control group of healthy children.
Chemical differences were observed between the two groups.

They found a link between autism and damage to proteins in blood plasma by oxidation and glycation -- processes where reactive oxygen species (ROS) and sugar molecules spontaneously modify proteins.
Further, the changes in multiple chemical compounds were combined together using artificial intelligence algorithms techniques to develop a mathematical equation or "algorithm" to distinguish between autism and healthy controls.

The outcome was a diagnostic test better than any method currently available, the researchers said.

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