Development of a cell-based metabolic test for the identification of individuals with autism spectrum disorder. (July 2021)

• Record Type: Journal Article
• Authors: Pauly, Rini; Cascio, Lauren; Srikanth, Sujata; Jones, Kelly; Sorrow, Skylar; Cubillan, Rossana; Chen, Chin-Fu; Skinner, Cindy D.; Champaigne, Kevin; Stevenson, Roger E.; Schwartz, Charles E.; Boccuto, Luigi
• Is Part Of: Research in autism spectrum disorders. Volume 85(2021)
• Publication Date: 2021-07
• Subjects: Autism spectrum disorder (ASD) -- Tryptophan -- Metabolism -- Diagnostic test -- Screening test; Autism spectrum disorders -- Periodicals; 616.85882005
• DOI: 10.1016/j.rasd.2021.101790
• Languages: English
• ISSNs: 1750-9467

Abstract

Highlights: Autism spectrum disorder (ASD) diagnosis is challenging and based on behavioral evaluations because there are no specific laboratory tests. Metabolic profiles can distinguish patients with ASD from typically developing individuals by differential utilization of tryptophan. A specific protocol improved the discrimination of the test, optimized the test parameters, and minimized background noise. The protocol exposes cells to a more challenging metabolic environment, enhancing the disruption of certain metabolic pathways in ASD cells. This improved platform can highlight pathogenic mechanisms and molecular biomarkers for ASD, and validate the clinical diagnosis of ASD. Abstract: Autism spectrum disorder (ASD) is a common neurodevelopmental condition with a tremendous impact on society and families. The biological basis of ASD has yet to be completely understood and there are no laboratory tests for this condition. Phenotype Mammalian Microarrays (PM-Ms) can distinguish patients with ASD from typically developing (TD) individuals by differential utilization of the amino acid tryptophan. By assessing several parameters of the assay utilizing customized tryptophan-containing PM-M plates, we improved the discrimination of the test, optimized test parameters, and minimized background noise by normalization while controlling for false discoveries. This improved platform can provide the first cell-based metabolic test to validate the clinical diagnosis of ASD and possibly identify individuals at risk even before the occurrence of neuro-behavioral symptoms.