Although there’s still so much we don’t know about autism, we do know that early intervention is key. Typically, autism and other neurodevelopmental disorders often aren’t diagnosed until a child is a few years old. By that age, behavioral interventions and speech/occupational therapy have already become less effective.
But new research from Boston Children’s Hospital discovered two simple measurements that might help predict neurodevelopmental disorders much earlier: pupil dilation and heart rate. The study, which was published in Proceedings of the National Academy of Sciences, found that when pupil dilation was analyzed by AI, they could find abnormalities that predicted autism spectrum disorder (ASD) in mouse models, as well as signal if a girl has Rett syndrome, which is a genetic disorder that impairs cognitive, sensory, motor, and autonomic function that starts at ages 6 to 18 months. The researchers predict that in addition to finding early signs of Rett syndrome and autism, this could also be used to track patients’ responses to treatments.
“We want to have some readout of what’s going on in the brain that is quantitative, objective, and sensitive to subtle changes,” Michela Fagiolini, PhD, the study co-author, has said. “More broadly, we are lacking biomarkers that are reflective of brain activity, easy to quantify, and not biased. A machine could measure a biomarker and not be affected by subjective interpretations of how a patient is doing.”
Fagiolini and her team of researchers started with theory that people on the autism spectrum have different behavioral states and that the brain’s cholinergic circuits, which are connected to arousal, are especially affected, and that affects both spontaneous pupil dilation and constriction, as well as heart rate. They measured pupil fluctuations in several mouse models with ASD, including mice with the mutations that cause Rett syndrome, and found that spontaneous pupil dilation and constriction were different even before the mice started showing symptoms of autism.
Eventually, Fagiolini hopes that this research can lead to effective but affordable screening tools for infants and toddlers to help warn of potential neurodevelopmental issues and follow their progress. She has said, “If we have biomarkers that are non-invasive and easily evaluated, even a newborn baby or non-verbal patient could be monitored across multiple timepoints.”