Autism and other neurodevelopmental disorders often aren’t diagnosed until a child is a few years of age, when behavioral interventions and speech/occupational therapy become less effective.
But new research this week in PNAS suggests that two simple, quantifiable measures – spontaneous fluctuations in pupil dilation or heart rate – could enable much earlier diagnosis of Rett syndrome and possibly other disorders with autism-like features.
The study, led by Boston Children’s Hospital neuroscientist Michela Fagiolini, Ph.D., and postdoctoral fellow Pietro Artoni, Ph.D., unveils a machine-learning algorithm that can spot abnormalities in pupil dilation that are predictive of autism spectrum disorder (ASD) in mouse models.
It further shows that the algorithm can accurately detect if a girl has Rett syndrome, a genetic disorder that impairs cognitive, sensory, motor, and autonomic function starting at 6 to 18 months of age, as well as autism-like behaviors.
Fagiolini and colleagues hope this system could provide an early warning signal not just for Rett syndrome but for ASD in general.
In the future, they believe it could also be used to monitor patients’ responses to treatments; currently, a clinical trial is testing the drug ketamine for Rett syndrome, and a gene therapy trial is planned.
“We want to have some readout of what’s going on in the brain that is quantitative, objective, and sensitive to subtle changes,” says Fagiolini.
“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.”
Altered arousal in autism
Fagiolini and Artoni, in close collaboration with Takao Hensch, Ph.D., and Charles Nelson, Ph.D., at Boston Children’s, began with the idea that people on the autism spectrum have altered behavioral states. Prior evidence indicates that the brain’s cholinergic circuits, which are involved in arousal, are especially perturbed, and that altered arousal affects both spontaneous pupil dilation/constriction and heart rate.
Fagiolini’s team, supported by the IRCN at Boston Children’s F.M. Kirby Neurobiology Center, set out to measure pupil fluctuations in several mouse models of ASD, including mice with the mutations causing Rett syndrome or CDKL5 disorder, as well as BTBR mice. Spontaneous pupil dilation and constriction were altered even before the animals began showing ASD-like symptoms, the team found.
Moreover, in mice lacking MeCP2, the gene mutated in Rett syndrome, restoring a normal copy of the gene, in cholinergic brain circuits only, prevented the onset of pupillary abnormalities as well as behavioral symptoms.
Predicting Rett syndrome in girls
To systematically link the observed arousal changes to the cholinergic system, the team took advantage of an earlier discovery by Hensch: mice lacking the LYNX1 protein exhibit enhanced cholinergic signaling.
Based on about 60 hours of observation of these mice, the investigators “trained” a deep learning algorithm to recognize abnormal pupillary patterns. The same algorithm accurately estimated cholinergic dysfunction in the BTBR, CDKL5, and MeCP2-deficient mice.
The team then brought this algorithm to 35 young girls with Rett syndrome and 40 typically developing controls.
Instead of measuring the girls’ pupils (as patients may fidget), they used heart rate fluctuations as the measure of arousal.
The algorithm nonetheless successfully identified the girls with Rett, with an accuracy of 80 percent in the first and second year of life.
“These two biomarkers fluctuate in a similar way because they are proxies of the activity of autonomic arousal,” says Artoni. “It is the so-called ‘fight or flight response.”
Autonomic arousal, a property of the brain that is strongly preserved across different species, is a robust indicator of an altered developmental trajectory, Fagiolini and Artoni found.
Biomarkers for babies?
In a previous study with Nelson, Fagiolini showed that visual evoked potentials, an EEG measure of visual processing in the brain, could also serve as a potential biomarker for Rett syndrome.
She believes that together, such biomarkers could offer robust yet affordable screening tools for infants and toddlers, warning of impending neurodevelopmental problems and helping to follow the progression of their development or treatment.
“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,” Fagiolini says.
In 1954, Andreas Rett, a pediatric neurologist in Vienna, first recognized the characteristic features of the syndrome which later came to bear his name.
His publication in the German medical literature in 1966 [Rett, 1966], however, remained largely unnoticed.
In the large textbook series on Neurology by Vincken and Bruyn, A. Rett wrote a chapter under the misleading heading of ‘Cerebral Atrophy and Hyperammonaemia’ in a series of 21 girls and women [Rett, 1977].
Other child neurologists observed the same clinical presentation in Japanese girls [Ishikawa et al., 1978].
It was, however, Bengt Hagberg from Gothenburg who shared his clinical observations in a Swedish survey at the Manchester Meeting on Child Neurology in 1981 and revealed this unique syndrome to the international medical world in 1983 [Hagberg et al., 1983].
Very soon a well-organized parental support group started and the International Rett Syndrome Association has now become one of the largest research and parent support foundations in the world, continuously encouraging the medical researchers and clinicians to seek for keys to unlock the biological riddle of this disorder. Meanwhile, parents all over the world have organized their continental and national parental support and advocacy groups.
Collaboration between physicians and such groups has contributed to the improvement of knowledge by research, developing appropriate information for patients, health professionals and the general public, and promoting access to screening and diagnostic testing as well as to quality treatment and social benefits [Dan, 2008].
Rett syndrome (RTT) is a clinical diagnosis based on internationally accepted diagnostic criteria that were developed and adapted over the years as a useful tool for the clinicians who are involved in the diagnostic work-up and for researchers in RTT-related science [Hagberg et al., 2002; Neul et al., 2010].
It is considered to be one of the most common causes of complex disability in girls. In the late 1990s, researchers from Huda Zoghbi’s laboratory suggested that the MECP2 gene, located on the X chromosome, was a good candidate gene for RTT based on some unexpected experimental results from an unrelated project and then demonstrated MECP2mutations in a number of patients with RTT [Amir et al., 1999]. RTT was thus the first neurodevelopmental disorder related to a defective transcription of methylated DNA. Some of the variant phenotypes initially thought to be very similar to RTT are now known to be caused by mutations in other genes.
The congenital variant of RTT is related to FOXG1 and the infantile seizure onset variant (Hanefeld variant) is related to CDKL5. Others disorders with overbreathing include the Pitt-Hopkins syndrome, related to TCF4 haploinsufficiency and the CNTNAP2- and NRXN1-related disorders with severe intellectual disability, autism and breathing abnormalities resembling Pitt-Hopkins syndrome [Zweier et al., 2009].
The prevalence of the syndrome in males with a normal karyotype and no family history of an affected female is certainly very low. For this purpose, here, only the female phenotype will be described.Go to:
Clinical Features
More information: Pietro Artoni et al, Deep learning of spontaneous arousal fluctuations detects early cholinergic defects across neurodevelopmental mouse models and patients, Proceedings of the National Academy of Sciences (2019). DOI: 10.1073/pnas.1820847116
Journal information: Proceedings of the National Academy of Sciences
Provided by Children’s Hospital Boston
