Autism First: Brain Patterns May Predict Treatment Response

Megan Brooks

November 16, 2016

It's possible to predict whether a young child with autism spectrum disorder (ASD) will respond to an evidence-based behavioral intervention by analyzing brain activity patterns with functional MRI (fMRI) prior to treatment, new research suggests.

Using fMRI, the researchers, led by senior investigator Pamela Ventola, PhD, of the Yale University Child Study Center in New Haven, Connecticut, found that patterns of activity in brain regions that support social perception before pivotal response treatment (PRT), a well-established behavioral therapy, predicted treatment response.

"For the first time in the field of ASD, we provide evidence that neural signatures in brain circuits implicated in social information processing and social motivation/reward can predict treatment effectiveness at the individual level in young boys and girls with ASD," the researchers write.

The study was published online November 15 in Translational Psychiatry.

Precision Medicine for Autism

"We [currently] have no way to predict a child's outcome and to match a child to a particular intervention or determine which children have the best chance to respond to a particular treatment," Dr Ventola told Medscape Medical News.

The researchers investigated the accuracy of fMRI neurobiomarkers in predicting response to PRT in seven girls and 13 boys with ASD (mean age, 5.9 years).

PRT includes parental training and uses motivational play activities to boost the development of social communications skills.

For the study, the researchers used a well-validated biological motion fMRI paradigm that "robustly" engages the neural circuits supporting social motivation and social information processing.

They discovered a brain network in which the pretreatment brain activities that are engaged during biological motion viewing predicted response to PRT.

"Specifically, the network includes key brain regions supporting social information processing (the superior temporal sulcus region, fusiform gyrus, superior parietal lobule) and social motivation (orbitofrontal cortex, putamen, ventral striatum)," the researchers report.

"Critically," they note, the results were supported by multivariate pattern analysis, which utilized a standard cross validation framework, "suggesting that the patterns of brain activities across these brain regions may serve as robust predictive biomarkers, generalizable to new, unseen participants."

"This discovery might lead to further development of precision medicine in ASD," lead author Daniel Y. J. Yang, PhD, previously of Yale University, now with the Autism and Neurodevelopmental Disorders Institute, the George Washington University and Children's National Health System, in Washington, DC, told Medscape Medical News.

For example, pretreatment fMRI or electroencephalography "may be used to facilitate the fitting process when families want to identify appropriate and effective treatments for their children," he explained.

"For children who might not be able to benefit immediately from the treatment, theoretically, if we can increase the pretreatment activation and their brain readiness to respond (eg, by oxytocin), we can increase the treatment effectiveness for these children," Dr Yang said.

A First Step

"Our findings move the field toward the goal of targeted, personalized treatment for individuals with ASD. The knowledge gained can be utilized in future work to tailor individualized treatment, refine PRT and develop novel interventions," the researchers write.

"If we can figure out what parts of the brain respond to treatment or what's predicting response based on brain activity, we can develop new treatments to fine-tune that response," said Dr Ventola.

"This is a first step. We are in the process of doing a follow-up study and applying for additional funding."

Primary funding for the study was provided by the Dietz Family, Esme Usdan and Family, Women's Health Research at Yale, and Autism Speaks. The authors have disclosed no relevant financial relationships.

Transl Psychiatry. Published online November 15, 2016. Full text

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