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Developmental biology - Brain

Predicting Autism Risk For Pregnant Mothers?

In a number of recent studies, researchers have made enormous strides toward ASD prediction and diagnosis...


Researchers at Rensselaer Polytechnic Institute led by Juergen Hahn, professor and head of biomedical engineering, are continuing to make remarkable progress on autism spectrum disorder (ASD). A recent paper authored by Hahn and Jill James from the University of Arkansas for Medical Sciences (UAMS), appears in the journal Research in Autism Spectrum Disorders.
The Hahn/James paper announces their success in predicting, with about 90 percent accuracy, if a pregnant mother has a 1.7 percent or a tenfold increase in her risk for having a child with ASD.

Recent estimates indicate that if a mother gave birth previously to a child with ASD, her risk for having a second child with ASD is approximately 18.7 percent. Whereas that risk in the general population is approximately 1.7 percent.

"However," says Hahn, a member of the Rensselaer Center for Biotechnology and Interdisciplinary Studies, "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."

Hahn's work in developing a physiologic test to predict autism risk is part of a larger emphasis on Alzheimer's and neurodegenerative diseases at the Center for Biotechnology and Interdisciplinary Studies. The work is an example of how life science and engineering interface at Rensselaer to offer new solutions for improving human health.
Researchers measured small molecules in a mother's blood that metablolize folate-dependent methyl groups which transfer one metablolite into another to create the metabolic pathway between cysteine and homocysteine. Her metabolic profile, thereby, determining her risk for having a child with autism.

Pregnant mothers who have had a child with autism before, were separated into two groups based on the diagnosis of their child whether the child actually developed autism (ASD) or not (TD). These mothers were then compared to a control group of mothers who had no prior autistic children.

The researchers concluded that while it is not yet possible to determine during pregnancy if a child by the age of 3 will be diagnosed with ASD, they can identify differences in maternal blood plasma metabolites indicating her relative risk (18.7 percent vs 1.7 percent) for having a child with ASD.
"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."

Juergen Hahn PhD, Department of Biomedical Engineering; Center for Biotechnology and Interdisciplinary Studies; Department of Chemical & Biological Engineering, Rensselaer Polytechnic Institute, Troy, NY, USA.

This new research follows an earlier study published in 2017, which developed an algorithm based on levels of metabolites found in blood samples of ASD children. The algorithm can accurately predict where a child is on the autism spectrum. A follow-up study this spring was also highly promising in assessing where a child is on the autism spectrum. These results have the potential for earlier diagnosis for ASD, and efforts are underway to develop a commercially available test based upon them.

Highlights
Metabolites from blood samples of pregnant mothers who have a child with autism (High Risk) and pregnant mothers who do not (Low Risk) were analyzed.

High Risk mothers were divided into two subgroups based on the presence (ASD) or absence (TD) of a diagnosis of autism at age 3 of the yet unborn child.

Metabolites did not show significant differences among the two subgroups (ASD vs. TD) of the High Risk group.

Significant differences exist in metabolites of High Risk vs. Low Risk mothers.

Background
Currently there is no test for pregnant mothers that can predict the probability of having a child that will be diagnosed with autism spectrum disorder (ASD). Recent estimates indicate that if a mother has previously had a child with ASD, the risk of having a second child with ASD is ~18.7% (High Risk) whereas the risk of ASD in the general population is ~1.7% (Low Risk).

Methods
In this study, metabolites of the folate-dependent transmethylation and transsulfuration biochemical pathways of pregnant mothers were measured to determine whether or not the risk of having a child with autism could be predicted by her metabolic profile. Pregnant mothers who have had a child with autism before were separated into two groups based on the diagnosis of their child whether the child had autism (ASD) or not (TD). Then these mothers were compared to a group of control mothers who have not had a child with autism before. A total of 107 mothers were in the High Risk category and 25 mothers in the Low Risk category. The High Risk category was further separated into 29 mothers in the ASD group and 78 mothers in the TD group.

Results
The metabolic results indicated that among High Risk mothers, it was not possible to predict an autism pregnancy outcome. However, the metabolic profile was able to predict with approximately 90% sensitivity and specificity whether a mother fell into the High Risk group (18.7% risk) or Low Risk group (1.7% risk).

Conclusions
Based upon these measurements it is not possible to determine during a pregnancy if a child will be diagnosed with ASD by age 3. However, differences in the folate-dependent transmethylation and transsulfuration metabolites are indicative of the risk level (High Risk of 18.7% vs. Low Risk of 1.7%) of the mother for having a child with ASD.

Authors
Kathryn Hollowood, Stepan Melnyk, Oleksandra Pavlivc, Teresa Evans, Ashley Sides, Rebecca J. Schmidt, Irva Hertz-Picciotto, William Elms, Elizabeth Guerrero, Uwe Kruger, Juergen Hahn, S. Jill James.


Acknowledgements
Important research like this exemplifies the vision of The New Polytechnic, an emerging paradigm for higher education which recognizes that global challenges and opportunities are so great they cannot be adequately addressed by even the most talented person working alone. Rensselaer serves as a crossroads for collaboration--working with partners across disciplines, sectors, and geographic regions--to address complex global challenges, using the most advanced tools and technologies, many of which are developed at Rensselaer. Research at Rensselaer addresses some of the world's most pressing technological challenges - from energy security and sustainable development to biotechnology and human health.

About Rensselaer Polytechnic Institute
Rensselaer Polytechnic Institute, founded in 1824, is America's first technological research university. For nearly 200 years, Rensselaer has been defining the scientific and technological advances of our world. Rensselaer faculty and alumni represent 86 members of the National Academy of Engineering, 18 members of the National Academy of Sciences, 26 members of the American Academy of Arts and Sciences, 8 members of the National Academy of Medicine, 8 members of the National Academy of Inventors, and 5 members of the National Inventors Hall of Fame, as well as 6 National Medal of Technology winners, 5 National Medal of Science winners, and a Nobel Prize winner in Physics. With 7,000 students and nearly 100,000 living alumni, Rensselaer is addressing the global challenges facing the 21st century--to change lives, to advance society, and to change the world. To learn more, go to http://www.rpi.edu.

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Sep 25, 2018   Fetal Timeline   Maternal Timeline   News   News Archive




Currently there is no test for pregnant mothers that can predict her probability of having
a child that will be diagnosed with ASD. Image: Medical News Today


Phospholid by Wikipedia