Investigating plasma amino acids for differentiating individuals with autism spectrum disorder and typically developing peers. (June 2018)

• Record Type: Journal Article
• Authors: Vargason, Troy; Kruger, Uwe; McGuinness, Deborah L.; Adams, James B.; Geis, Elizabeth; Gehn, Eva; Coleman, Devon; Hahn, Juergen
• Is Part Of: Research in autism spectrum disorders. Volume 50(2018:Jun.)
• Page Start: 60
• Page End: 72
• Publication Date: 2018-06
• Subjects: Autism spectrum disorder -- Plasma amino acids -- Fisher discriminant analysis -- Classification -- Multivariate statistics -- Cross-validation; Autism spectrum disorders -- Periodicals; 616.85882005
• DOI: 10.1016/j.rasd.2018.03.004
• Languages: English
• ISSNs: 1750-9467

Abstract

Highlights: Plasma amino acids from 64 children with ASD and 49 typically-developing (TD) peers were analyzed. No significant univariate differences were found between the ASD and TD cohorts. Multivariate analysis revealed poor ability to classify as ASD/TD with these data. Our findings suggest plasma amino acids are not a good predictor for ASD status. Abstract: Background: Plasma amino acid measurements have been extensively investigated in individuals with autism spectrum disorder (ASD). Results thus far have been inconclusive as studies generally disagree on which amino acids are different in individuals with ASD versus their typically developing (TD) peers, due in part to methodological limitations of several studies. Method: This paper investigates plasma amino acids in children and adults with ASD using data from Arizona State University's Comprehensive Nutritional and Dietary Intervention Study. Measurements from 64 individuals with ASD and 49 TD controls were analyzed using univariate and multivariate statistical techniques. Results: Univariate analysis indicated increased median levels of glutamate (+21%, p = 0.014) and serine (+8%, p = 0.043), and increased mean levels of hydroxyproline (+17%, p = 0.018) for the ASD cohort, although these differences were insignificant after correcting for multiple comparisons. A multivariate approach was used to classify study participants into ASD/TD cohorts using Fisher discriminant analysis (FDA) and its nonlinear extension, kernel Fisher discriminant analysis (KFDA). Model fitting with FDA using all available measurements produced Type I and Type II errors of 27.0% and 27.8%, respectively. KFDA was most effective when using hydroxyproline, leucine, and threonine as inputs; however, leave-one-out cross-validation with this nonlinear model only resulted in 70.3% sensitivity and 77.6% specificity. Conclusions: The finding of elevated glutamate in ASD is in agreement with several other studies. Overall, however, these results suggest that plasma amino acid measurements are of limited use for purposes of ASD classification, which may explain some of the inconsistencies in results presented in the literature.