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SYRACUSE, NY (November 9, 2018) – Newly published research shows that a saliva-based biomarker panel and badociated algorithm could improve the ability to respond to autism spectrum disorder (ASD) in its earliest stages, advertised by Quadrant Biosciences Inc. RNAs could differentiate children with autism from children exhibiting typical development or non-ASD developmental delay with 85% accuracy. This test is validated during the development and validation of the test in a separate set of children.
The publication, entitled "Validation of a salivary RNA test for childhood autism spectrum disorder," was published online in Frontiers in Genetics by researchers Steven Hicks, M.D., Ph.D., of the Pennsylvania State College of Medicine, and Frank Middleton, Ph.D., of SUNY Upstate Medical University in collaboration with scientists from Quadrant Biosciences.
Following a pilot study demonstrating that many of these RNA elements could be detected in the saliva of children with ASD, the researchers determined that saliva-based testing could provide the means to broadly interrogate genomic, physiologic, microbiome, and environmental factors implicated in ASD. a single, non-invasive, high-throughput badysis.
"Growing evidence suggests that autism arises from interactions between children and the environment," said Dr. Hicks. RNA factors in their saliva could be different from those of peers without autism. Given this array of ASD risk factors, we believe in RNA-based poly-omics. approach that integrates genetic, epigenetic, and metagenomics methods would be suitable for the development of an objective biomarker-based test. "
The Study
The multi-center study included 456 children recruited during the past three years. The authors compared saliva samples from 238 children with ASD to 218 children without ASD (including 84 children with developmental delay and 134 with typical development). Levels of human and bacterial RNAs were measured in the saliva samples using comprehensive next-generation sequencing. The top RNAs were identified using robust machine-learning algorithms and the results were used in the machine learning. Notably, this validation is also included at the University of California, Irvine, to verify that the RNA algorithm performed accurately in different regions.
Need for Earlier Autism Diagnosis
Screening for autism typically relates to a parent-based questionnaire called the Modified Checklist for Autism in Toddlers Revised (MCHAT-R). Children with a positive MCHAT-R score for diagnosis. However, due to the high number of false-positive results on the MCHAT-R While diagnosis is possible in children as young as 24 months, the average age of ASD diagnosis in the United States today is greater than 4 years. Early diagnosis is important because it has been shown to be more effective than other symptoms.
Daniel Coury, MD, Professor of Clinical Pediatrics and Psychiatry at the Ohio State University College of Medicine and a member of the Section of Developmental and Behavioral Pediatrics at Nationwide Children's Hospital, sees the benefit of this RNA biomarker-based test in a clinical setting. "Frequent autism-specific interventions are often made to be diagnosed with autism," he explained. "M-CHAT-positive into high likelihood of autism or low likelihood of autism could help to streamline waitlists and allow for earlier diagnosis and enrollment in autism treatment."
Dr. Middleton from SUNY Upstate Medical University agreed. "The ability to accurately discriminate between children with autism and their ASD developmental delay is of paramount importance in the field.While the algorithm is not designed as a screening tool, it can provide valuable information in children with a positive MCHAT- R screen, over 80% of whom will not have ASD In this way, it can be used to prioritize specialist referral or to provide an objective to an autism diagnosis.
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