Published: Sun, March 19, 2017
Medicine | By Megan Pierce

A blood test could be the key for earlier detection of Autism

A blood test could be the key for earlier detection of Autism

Autism Speaks states that "autism spectrum disorder" consists of varying conditions involving behavioural problems, issues with social skills, speech and nonverbal communication, and repetitive behavior.

While past research has revealed distinctive metabolic processes in children on the autism spectrum, these have not previously been exploited in diagnosis.

Although ASD affects about 1.5 percent of all children, its exact cause remains unknown, and diagnosis requires many doctors specialising in a number of different disciplines.

"Professor Hahn's innovative work to improve the diagnosis for Autism as well as other ongoing efforts to advance diagnostics and develop new treatments for Alzheimer's and neurodegenerative diseases at CBIS show how new breakthroughs in health care are possible when we focus our work at the interface between traditional boundaries", said Deepak Vashishth, director of the CBIS. However, the majority of diagnosis methods rely on behavioral factors and are not always accurate. But researchers have struggled to translate these into new diagnostic tools.

The study, led by Juergen Hahn and Daniel Howsmon, was published in the journal PLOS Computational Biology.

The Rensselaer Polytechnic Institute in NY, which created the algorithm, studied its efficiency through advanced data analysis and published the results in the journal PLOS Computational Biology.

The children were aged between 3 and 10.

An algorithm based on levels of metabolites found in a blood sample can accurately predict whether a child is on the Autism spectrum of disorder (ASD), based upon a recent study.

Both of these substances have previously been shown to become altered in people with an increased risk of ASD. Also, they developed some statistical models which looked at the neurological status of children and could tell who had autism.

"The models developed herein have much stronger predictability than any existing approaches from the scientific literature".

Using these tools, Hahn and team correctly identified 97.6 percent of the children that had autism, and 96.1 percent of those who were neurotypical.

NewsHub reported that this one of its kind methods can classify if an individual is on the autism spectrum or being neurotypical. "We are not aware of any other method, using any type of biomarker, that can do this, much less with the degree of accuracy that we see in our work".

The researchers also hope the identification of proteins predictive of ASD will further research into the cause of the disorders, and one day result in better treatments or a cure.

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