AI-enhanced precision medicine identifies novel autism subtype
Tool lays groundwork for autism early diagnosis and intervention

Date:
August 11, 2020
Source:
Northwestern University
Summary:
A novel precision medicine approach enhanced by artificial
intelligence has laid the groundwork for what could be the first
biomedical screening and intervention tool for a subtype of autism,
reports a new study.



FULL STORY ==========================================================================
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, reports a
new study from Northwestern University, Ben Gurion University, Harvard University and the Massachusetts Institute of Technology.


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The approach is believed to be the first of its kind in precision
medicine.

"Previously, autism subtypes have been defined based on symptoms only -
- autistic disorder, Asperger syndrome, etc. -- and they can be hard
to differentiate as it is really a spectrum of symptoms," said study
co-first author Dr. Yuan Luo, associate professor of preventive medicine: health and biomedical informatics at the Northwestern University Feinberg School of Medicine. "The autism subtype characterized by abnormal levels identified in this study is the first multidimensional evidenced-based
subtype that has distinct molecular features and an underlying cause."
Luo is also chief AI officer at the Northwestern University Clinical
and Translational Sciences Institute and the Institute of Augmented Intelligence in Medicine. He also is a member of the McCormick School
of Engineering.

The findings were published August 10 in Nature Medicine.

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 subtype of the disorder studied by Luo and colleagues is known as dyslipidemia-associated autism, which represents 6.55% of all diagnosed
autism spectrum disorders in the U.S.

"Our study is the first precision medicine approach to overlay an
array of research and health care data -- including genetic mutation
data, sexually different gene expression patterns, animal model data, electronic health record data and health insurance claims data -- and
then use an AI-enhanced precision medicine approach to attempt to define
one of the world's most complex inheritable disorders," said Luo.

The idea is similar to that of today's digital maps. In order to get
a true representation of the real world, the team overlaid different
layers of information on top of one another.

"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% of families with the disorder. We built a complex map, and then needed to develop a magnifier to zoom in,"
said Luo.

To build that magnifier, the research team identified clusters of gene
exons that function together during brain development. They then used
a state-of-the- art AI algorithm graph clustering technique on gene
expression data. Exons are the parts of genes that contain information
coding for a protein. Proteins do most of the work in our cells and
organs, or in this case, the brain.

"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 research team 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. These findings have led the
team to pursue subsequent studies, including clinical trials that aim
to promote early screening and early intervention of autism.

"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."

========================================================================== Story Source: Materials provided by Northwestern_University. Original
written by Roger Anderson. Note: Content may be edited for style and
length.


========================================================================== Journal Reference:
1. Yuan Luo, Alal Eran, Nathan Palmer, Paul Avillach, Ami
Levy-Moonshine,
Peter Szolovits, Isaac S. Kohane. A multidimensional precision
medicine approach identifies an autism subtype characterized
by dyslipidemia.

Nature Medicine, 2020; DOI: 10.1038/s41591-020-1007-0 ==========================================================================

Link to news story: https://www.sciencedaily.com/releases/2020/08/200811153921.htm

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