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‘Quantum leap’ in autism research could lead to better diagnosis, treatments

| | February 26, 2018
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This article or excerpt is included in the GLP’s daily curated selection of ideologically diverse news, opinion and analysis of biotechnology innovation.

A new computational method has connected several target genes to autism, according to new research. The findings, along with other recent discoveries, could lead to screening tools for young children—and help doctors choose the best intervention when making a diagnosis.

“In this study we started with more than 2,591 families who had only one child with autism and neither the parents nor the siblings had been diagnosed with autism,” says Chi-Ren Shyu, professor of electrical engineering and computer science at the University of Missouri and director of the Informatics Institute.

Using advanced computational techniques, Shyu and colleagues were able to identify 286 genes they then collected into 12 subgroups that exhibited commonly seen characteristics of children on the spectrum. Of these genes, 193 potentially new genes not found in previous autism studies were discovered.

“The methods developed by Dr. Shyu and the results our team identified are giving geneticists a wealth of targets we’d not considered before—by narrowing down the genetic markers, we may be able to develop clinical programs and methods that can help diagnose and treat the disease. These results are a quantum leap forward in the study of the genetic causes of autism,” [said professor Judith Miles].

Read full, original post: Tying target genes to autism could lead to better treatment

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