Autism spectrum disorder (ASD) is a continuum of neurodevelopmental characteristics that includes deficits in communication and social interaction, as well as restrictive, repetitive interests and behaviors. ASD is an increasing public health concern, with about 1 in 45 American children diagnosed with ASD in 2014, a 10-fold increase in prevalence over the past 40 years. The effect of ASD on both society and the economy is a large burden, estimated at more than $286 billion per year in the U.S. alone. While a single direct link to ASD diagnosis has not been determined, studies have identified genetic, epigenetic, neurological, hormonal, and environmental factors that affect outcomes for patients with ASD. In order to effectively treat patients with ASD, timely detection is crucial for implementation of early treatment options. Using knowledge of these preexisting factors for ASD, doctors can begin treatment while the patient is still young, even if the child has not begun to exhibit typical ASD symptoms. Studies suggest that earlier treatment results in better functional outcomes and reductions in symptoms of ASD. These models, medications and programs have proven to be effective in managing the symptoms of ASD, and may remove some patients from the ASD spectrum entirely. Unfortunately, current diagnostic methods for ASD are not very accurate for young children; the average age of diagnosing ASD is three years old, and about half of those are false positives. Development of accurate diagnostic biomarkers for ASD would thus represent a valuable addition to patient care. Motion Intelligence is developing an approach to diagnose ASD by measuring brain-related micro ribonucleic acids (miRNAs) in saliva. Extracellular transport of miRNA via exosomes and other microvesicles is an established epigenetic mechanism for cells to alter gene expression in nearby cells. The microvesicles are extruded into the extracellular space, where they can dock and enter neighboring cells, and alter gene expression. These microvesicles are present in various bodily fluids, such as saliva. This has enabled Motion Intelligence to measure genetic material that may have originated from the central nervous system simply by collecting saliva. This method minimizes many of the limitations associated with analysis of post-mortem brain tissue (e.g., anoxic brain injury, RNA degradation, post-mortem interval, agonal state), or peripheral leukocytes (relevance of expression changes, painful blood draws) employed in previous studies. Thus, extracellular miRNA quantification in saliva provides an attractive and minimally invasive technique for biomarker identification in children with ASD. This Phase I study will include a prospective clinical trial that will characterize the expression pattern of salivary miRNAs in children with ASD and age- and gender-matched controls with typical development. Data from half of the subjects will be used as a training dataset to create an algorithm of relevant miRNA biomarkers, and the other half will be used in a validation study to determine the efficacy of this algorithm.
This project will result in the first autism spectrum disorder (ASD) diagnostic that will identify the disorder at a young age with high accuracy. The average age of diagnosing ASD is three years old, and about half of those are false positives. Treating patients earlier makes it more likely that they will develop normally and exhibit fewer symptoms of ASD. As such, Motion Intelligence's ASD diagnostic has potential to help the hundreds of thousands of American children not yet diagnosed with ASD and potentially reduce the disorder's more than $286 billion annual economic impact on society.
| Hicks, Steven D; Rajan, Alexander T; Wagner, Kayla E et al. (2018) Validation of a Salivary RNA Test for Childhood Autism Spectrum Disorder. Front Genet 9:534 |
