Abstract

Autism spectrum disorders (ASD) are increasingly common neurodevelopmental disorders accompanied by dysregulation of amino acid (AA) metabolism, and for which there are currently no reliable early diagnostic biomarkers. This study evaluated whether specific AAs can serve as biomarkers for screening ASD patients by analyzing the abundance 21 plasma AAs in 70 ASD patients and 70 control subjects by liquid chromatography-tandem mass spectrometry. We found significant differences between the two groups for eight of the AAs-namely, arginine, cysteine, homocysteine, histidine, methionine, serine, tyrosine, and valine. However, only homocysteine level was positively correlated with ASD symptom severity. Arginine, cysteine, histidine, and methionine were used to generate a predictive model in the Fisher discriminant analysis; cross-validation of this model showed that 88.6% of individuals were correctly segregated into ASD and healthy subject groups with a sensitivity of 85.5% and specificity of 92.2%. The area under the receiver operating characteristic curve was 0.959 (0.927-0.991). Thus, detection of a combination of AAs is an effective method for distinguishing ASD patients from healthy subjects, which may be useful for the early diagnosis of ASD.

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