AI-enhanced precision medicine identifies novel autism subtype: study

Source: Xinhua| 2020-08-12 00:54:23|Editor: huaxia

A Palestinian swimming instructor teaches children with autism in a pool during a summer camp for autistic children in Gaza Strip, on Aug. 9, 2020. (Photo by Rizek Abdeljawad/Xinhua)

"The map and magnifier approach showcases a generalizable way of using multiple data modalities for subtyping autism and it holds the potential for many other genetically complex diseases to inform targeted clinical trials," says Luo.

CHICAGO, Aug. 11 (Xinhua) -- A novel precision medicine approach enhanced by artificial intelligence (AI) has laid the groundwork for what could be the first biomedical screening and intervention tool for a subtype of autism, according to a new study.

The subtype of the disorder studied by researchers from Northwestern University (NU), Ben Gurion University, Harvard University and the Massachusetts Institute of Technology is known as dyslipidemia-associated autism, which represents 6.55 percent of all diagnosed autism spectrum disorders in the United States.

"This discovery was like finding a needle in a haystack, as there are thousands of variants in hundreds of genes thought to underlie autism, each of which is mutated in less than 1 percent of families with the disorder. We built a complex map, and then needed to develop a magnifier to zoom in," said study co-first author Yuan Luo, associate professor of preventive medicine at NU's Feinberg School of Medicine.

Children with Autism Spectrum Disorder (ASD) watch a white whale performance with their parents at the Polarland in Harbin, capital of northeast China's Heilongjiang Province, April 2, 2019, the World Autism Awareness Day. (Xinhua/Wang Jianwei)

To build that magnifier, the researchers identified clusters of gene exons that function together during brain development. They then used a state-of-the-art AI algorithm graph clustering on gene expression data.

"The map and magnifier approach showcases a generalizable way of using multiple data modalities for subtyping autism and it holds the potential for many other genetically complex diseases to inform targeted clinical trials," said Luo.

Using the tool, the researcher also identified a strong association of parental dyslipidemia with autism spectrum disorder in their children. They further saw altered blood lipid profiles in infants later diagnosed with autism spectrum disorder.

The findings are leading the researchers to pursue subsequent studies, including clinical trials that aim to promote early screening and early intervention of autism.

People participate in the event Angels Walk for Autism in Pasay City, the Philippines, Feb. 5, 2017. (Xinhua/Rouelle Umali)

"Today, autism is diagnosed based only on symptoms, and the reality is when a physician identifies it, it's often when early and critical brain developmental windows have passed without appropriate intervention," said Luo. "This discovery could shift that paradigm."

Autism affects an estimated 1 in 54 children in the United States, according to the Centers for Disease Control and Prevention. Boys are four times more likely than girls to be diagnosed. Most children are diagnosed after age 4, although autism can be reliably diagnosed based on symptoms as early as age 2.

The findings were published Monday in Nature Medicine.

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