EMERGING TESTS

Metabolite Panel May ID Kids With Autism Spectrum Disorder

A group of blood metabolites help detect some children with autism spectrum disorder (ASD), according to a study published Sept. 6 in Biological Psychiatry.

This panel may indicate alterations in amino acid (AA) metabolism and can detect about 17 percent of kids with ASD.

“It is unlikely that a single marker will detect all autism,” said senior author David Amaral, Ph.D., from University of California, Davis, in a statement. “The long-term vision is, once we’ve been able to analyze all the data from [the] Children’s Autism Metabolome Project, we would have a series of panels. Each of these would be able to detect a subset of kids with autism. Ultimately, metabolomics may be able to identify most children with autism.”

ASD presents heterogeneously both behaviorally and biologically. Experts believe it may arise from a complex interplay of environmental, metabolic, and genetic factors. Currently, there is no reliable biomarker that can identify children at risk for ASD or definitively diagnose children. Diagnosis is based on behavioral evaluation.

Plasma metabolites were analyzed for 516 children with ASD (aged 18 to 48 months) and 164 age-matched, typically developing (TYP) children using liquid chromatography mass spectrometry. The training set included 338 (ASD, 253 and TYP, 85) and the test set included 342 (ASD, 263; TYP, 79). In the training set, diagnostic thresholds were established to identify a subpopulation with at least 10 percent of the ASD population.

The researchers found that a simple analysis of the mean concentrations of free plasma amines did not reveal meaningful differences between the ASD and TYP populations of children. However, they identified three ASD-associated amino acid dysregulation metabotypes (AADM). The combination of glutamine, glycine, and ornithine AADMs identified a dysregulation in AA metabolism that is present in 16.7 percent of the study’s ASD subjects, with a specificity of 96.3 percent and a positive predictive value (PPVs) of 93.5 percent.

While there is substantial overlap of children identified by each of the metabotypes, each of the metabotypes also identifies a unique group of subjects. The AADMglutamine identified 7.9 percent of the ASD subjects in the total CAMP population, AADMglycine 9.7 percent, and the AADMornithine 9.1 percent, with PPVs of 97.6 percent, 94.3 percent, and 92.2 percent, respectively. However, taken together, the three AADM subtypes identified 16.7 percent of all ASD subjects with a specificity of 96.3 percent and a PPV of 93.5 percent.

“Metabotypes of ASD can be useful in stratifying the broad autism spectrum into more biochemically homogeneous and clinically significant subtypes,” writes Amaral. “Stratifying ASD based on metabotypes offers an opportunity to identify efficacious interventions within metabotypes that can lead to more precise and individualized treatment. The hope is that by combining the established metabotypes into a more comprehensive diagnostic system, that a substantial percentage of children at risk for ASD will be identifiable at a very early age.”

Takeaway: Blood-based metabolite analysis may offer a way to meaningfully identify subpopulations of children with ASD and can inform more personalized intervention.

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