A new paper published in the journal Research in Autism Spectrum Disorders reveals that an unborn child’s risk for autism may be associated with certain measurable metabolic processes in the pregnant mother.
The risk of having a child with autism spectrum disorder (ASD) in the general population is approximately 1.7 percent. However, if a woman has previously had a child with ASD, the risk of having a second child with ASD is increased more than tenfold — approximately 18.7 percent. Currently, there is no test for pregnant women which can predict the probability of having a child with ASD.
“However, it would be highly desirable if a prediction based upon physiological measurements could be made to determine which risk group a prospective mother falls into,” said lead researcher Dr. Juergen Hahn, professor and head of biomedical engineering at Rensselaer Polytechnic Institute in New York.
Hahn, who is also a member of the Rensselaer Center for Biotechnology and Interdisciplinary Studies, authored the paper with Dr. Jill James from the University of Arkansas for Medical Sciences (UAMS).
In the study, the researchers measured metabolites in blood samples taken from a group of high-risk moms (had previously had a child with autism) and a group of low-risk moms (never had a child with autism). The high-risk moms were later divided into two subgroups based on the presence or absence of a diagnosis of autism at age 3 of the yet unborn child.
Although the findings showed no significant differences among the metabolites in the two high-risk subgroups, the researchers found significant differences in the metabolites of the high-risk versus low-risk mothers.
The researchers conclude that while it is not yet possible to determine during a pregnancy if a child will be diagnosed with ASD by age 3, they did find that differences in the plasma metabolites are indicative of the relative risk (18.7 percent vs 1.7 percent) for having a child with ASD. Based on the metabolic profile of the mother, the researchers’ accuracy was about 90 percent.
“These are exciting results as they hint at differences in some metabolic processes that potentially play a role in increasing the risk of having a child with ASD,” said Hahn.
The researchers are continuing to make significant progress with their ASD studies. This new study follows previous work published in 2017, which developed an algorithm based on levels of metabolites found in a blood sample that can accurately predict whether a child is on the autism spectrum.
This work also included collaborators from Rensselaer, the University of Arkansas for Medical Sciences, and the MIND Institute at University of California (UC) Davis. Hahn’s research on autism risk is part of a larger emphasis on Alzheimer’s and neurodegenerative diseases at the Rensselaer’s Center for Biotechnology and Interdisciplinary Studies.
The new findings have the potential for earlier diagnosis for ASD, and efforts are under way to develop a commercially available test based upon these findings.
Source: Rensselaer Polytechnic Institute