Summary: A new study reports that a blood-based metabolic test can identify roughly 17% of young children on the autism spectrum.
Source: UC Davis
Researchers at the UC Davis MIND Institute, in collaboration with NeuroPointDX (a division of Stemina Biomarker Discovery), have identified a set of blood metabolites that may help detect a subset of children with autism spectrum disorder (ASD). These results come from the Children’s Autism Metabolome Project (CAMP), the largest metabolomic study of ASD to date, and represent an important step toward an objective biomarker test for autism. The study was published in the journal Biological Psychiatry on September 6.
“Using this panel of altered amino acid metabolism markers, we can detect about 17 percent of children with ASD,” said David G. Amaral, founding director of research at the MIND Institute and senior author of the study. “This is the first of what we hope will be multiple panels identifying different subgroups of children with autism.”
Currently, no blood-based biomarker exists to diagnose ASD. Diagnosis relies on observing behavioral differences, which often do not become clear until age 2–4. Families may wait a year or longer for specialist evaluation, further delaying intervention.
CAMP investigators focused on the metabolome — the small molecules that remain after larger biomolecules are broken down. Metabolomics reflects both genetic predispositions and environmental influences, making it well suited to capture the varied causes of ASD.
“Metabolomics tells you how the body is functioning in real time, not just which genes are present,” Amaral explained.
The team’s goal is to use metabolomic signatures like these to shorten the time to diagnosis and allow children to access intensive behavioral therapies earlier, therapies that have been shown to improve outcomes. CAMP collected blood from approximately 1,100 children between 18 months and 4 years of age; about two-thirds of these children have ASD. This paper is the first major publication reporting results from that effort.
Amaral noted that the project represents an effective academic–industry partnership and emphasized that a single marker is unlikely to detect all forms of autism. “This study shows that altered metabolic profiles can identify meaningful subgroups of individuals with ASD. Our hope is to build a panel of biomarkers that together detect a large proportion of children at risk, and to reveal metabolic pathways that might be targeted by interventions.”
In this study, researchers compared plasma amino acid levels in 516 children diagnosed with ASD and 164 typically developing children of the same age range. They found that about 17 percent of the ASD group displayed distinctive concentrations of specific amino acids — patterns the authors call metabotypes. Although 17 percent may seem modest, ASD is a highly heterogeneous condition; the researchers anticipated that multiple distinct biomarker panels would be required to capture different ASD subtypes.
“Our long-term vision is to analyze all CAMP data and build a series of panels,” Amaral said. “Each panel would detect a particular subset of children with autism. Over time, metabolomics could potentially identify most children with ASD.”
Beyond earlier detection, identifying metabotypes could enable targeted interventions for defined ASD subgroups. The research team noted phenylketonuria (PKU) as an instructive example: a metabolic disorder where dietary changes can prevent severe cognitive impairment. The hope is that identifying specific metabolic imbalances in ASD might lead to similarly effective, targeted treatments for some children.
The CAMP team will continue validating these findings and searching for additional metabotypes. “I’m optimistic this isn’t an isolated result,” Amaral said. “We expect to find other panels that detect additional groups of children with ASD.”
Other authors on the study include Alan M. Smith, Joseph J. King, Paul R. West, Michael A. Ludwig, Elizabeth L. R. Donley, and Robert E. Burrier from Stemina.
Funding: This research was supported by the National Institutes of Health (grants NIH 5 R44 MH107124-03 and 1R01MH103371), the Nancy Lurie Marks Family Foundation, and The Robert E. and Donna Landreth Family Fund.
David G. Amaral receives research funding from Stemina and serves on the Scientific Advisory Boards of Stemina Biomarker Discovery, Inc. and Axial Therapeutics.
Source: Dorsey Griffith — UC Davis
Publisher: NeuroscienceNews.com (organized coverage)
Original research: “Amino acid dysregulation metabotypes: potential biomarkers for diagnosis and individualized treatment for subtypes of autism spectrum disorder,” published in Biological Psychiatry on September 6, 2018. DOI: 10.1016/j.biopsych.2018.08.016
Amino acid dysregulation metabotypes: potential biomarkers for diagnosis and individualized treatment for subtypes of autism spectrum disorder
Background
Autism spectrum disorder is both behaviorally and biologically heterogeneous and likely reflects multiple underlying genetic, metabolic, and environmental causes. No validated diagnostic biomarkers for ASD currently exist. Based on prior evidence that dysregulation of branched-chain amino acids (BCAAs) may contribute to ASD-related behaviors, the study tested whether broader amino acid dysregulation occurs in individuals with ASD. This publication reports initial results from the Children’s Autism Metabolome Project (CAMP), a large-scale effort to discover blood-based metabolomic biomarkers in young children.
Methods
Plasma amino acid metabolites were compared between 516 children with ASD and 164 age-matched typically developing children enrolled in CAMP. Researchers stratified ASD participants into subgroups based on shared metabolic phenotypes associated with BCAA dysregulation.
Results
The team identified groups of amino acids whose levels correlated positively with each other and negatively with BCAA levels in ASD participants. Imbalances between these amino acid groups defined three ASD-associated Amino Acid Dysregulation Metabotypes (AADM). A combination of glutamine, glycine, and ornithine metabotypes revealed an amino acid/BCAA dysregulation present in 16.7% of the CAMP ASD subjects, with a reported specificity of 96.3% and a positive predictive value of 93.5% in this cohort.
Conclusions
Defining metabotypes in ASD can lead to actionable metabolic tests that support earlier diagnosis and enable stratification for targeted therapeutic interventions.