Rensselaer Alumni Magazine - Fall 2017 - 14
Researchers Develop a Blood Test for Autism
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), according to
results of a recent study. The algorithm,
developed by researchers at Rensselaer, is the
first physiological test for autism and opens
the door to earlier diagnosis and potential
future development of therapeutics.
"Instead of looking at individual metabolites, we investigated patterns of several
metabolites and found significant differences
between metabolites of children with ASD
and those that are neurotypical. These differences allow us to categorize whether an
individual is on the Autism spectrum," says
systems biologist Juergen Hahn, professor
and head of the Department of Biomedical
Engineering. "By measuring 24 metabolites
from a blood sample, this algorithm can
tell whether or not an individual is on the
Autism spectrum, and even to some degree
where on the spectrum they land."
Big data techniques applied to biomedical
14 rensselAer/fAll 2017
data found different patterns in metabolites
a role. People with ASD "may
relevant to two connected cellular pathcommunicate, interact,
ways that have been hypothesized
behave, and learn in
to be linked to ASD: the
ways that are different from
methionine cycle and
most other people." According
to the CDC, the total economic costs
pathway. The methioper year for children
nine cycle is linked
with ASD in the
The algorithm, developed by researchers
to several cellular
United States are
at Rensselaer, is the first physiological
test for autism and opens the door to
earlier diagnosis and potential future
and epigenetics, and
and $60.9 billion.
development of therapeutics.
Research shows that
pathway results in the
production of the antioxidant glutathione,
can improve development, but diagnosis
decreasing oxidative stress.
currently depends on clinical observation of
Autism Spectrum Disorder is estimated to behavior, an obstacle to early diagnosis and
affect approximately 1.5 percent of individutreatment. Most children are not diagnosed
als and is characterized as "a developmental
with ASD until after age 4 years.
disability caused by differences in the brain,"
Researchers have looked at individual
according to the Centers for Disease Control metabolites produced by the methionine
and Prevention. The physiological basis for
cycle and the transsulfuration pathways
ASD is not known, and genetic and environ- and found possible links with ASD, but the
mental factors are both believed to play
correlation has been inconclusive. Hahn says
the more sophisticated techniques he applied
revealed patterns that would not have been
apparent with earlier efforts.
"A lot of studies have looked at one
biomarker, one metabolite, one gene, and
have found some differences, but most of the
time those differences weren't statistically
significant or the results could not be reliably
replicated," Hahn says. "Our contribution
is using big data techniques that are able to
look at a suite of metabolites that have been
correlated with ASD and make statistically
a much stronger case."
The full results of Hahn's work on ASD
diagnosis are publicly available and Hahn
is hopeful his work will lead to a widely available test that can support early diagnosis,
although he does not intend to commercialize his results. For Hahn, the next step is to
replicate the results with a new cohort working with his clinical collaborators. In the long
run, Hahn hopes the model and diagnostic
tool will aid in developing treatment options.
"If these pathways are different, what happens if I can manipulate the pathway so that
it works similarly to the neurotypical ones?"
says Hahn. "What do I need to prod? Which
molecules do I need to add or take away?"