A Metabolomics Approach to Screening for Autism Risk in the Children's Autism Metabolome Project.
A 34-marker blood panel spots autism risk in toddlers with 91% specificity, giving BCBAs a lab tool to speed up referral decisions.
01Research in Context
What this study did
Heald et al. (2020) drew blood from toddlers aged 18-48 months. Half of the kids had autism. Half did not.
The team ran an untargeted metabolomics scan. They hunted for any small molecules that differed between the two groups.
A 34-metabolite panel rose to the top. The panel became a stand-alone blood test for autism risk.
What they found
The 34-metabolite panel flagged 91% of non-autistic toddlers correctly. It caught 53% of the autistic group.
In plain words: if the test says “low risk,” you can trust it. If it says “high risk,” flip a coin.
How this fits with other research
Grigore et al. (2024) looked at every toddler autism screen and said, “We still don’t know if any of them help kids get better faster.” Their big-picture view seems to clash with the new blood test, but the gap is timing. Grigore asked, “Do screens change long-term outcomes?” M et al. only asked, “Can we sort blood samples?”
Ritz et al. (2020) used the same metabolomics camera, yet they snapped the picture during pregnancy, not toddlerhood. Together the two studies draw a metabolic arc: mom’s blood hints at risk, and the child’s blood later confirms it.
Tirouvanziam et al. (2012) and Katz et al. (2003) already saw odd amino-acid patterns in autistic kids’ plasma. M et al. widened the lens from a few amino acids to 34 metabolites and locked in a cut-off score, moving the idea closer to clinic-ready.
Why it matters
You now have a second-stage option when parents want something “objective.” A low-risk blood result can buy time and reduce worry. A high-risk result still needs a full autism evaluation, but you can fast-track it. Keep watching: if later studies tie the panel to early intervention gains, the 91% specificity will make insurers listen.
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02At a glance
03Original abstract
Autism spectrum disorder (ASD) is biologically and behaviorally heterogeneous. Delayed diagnosis of ASD is common and problematic. The complexity of ASD and the low sensitivity of available screening tools are key factors in delayed diagnosis. Identification of biomarkers that reduce complexity through stratification into reliable subpopulations can assist in earlier diagnosis, provide insight into the biology of ASD, and potentially suggest targeted interventions. Quantitative metabolomic analysis was performed on plasma samples from 708 fasting children, aged 18 to 48 months, enrolled in the Children's Autism Metabolome Project (CAMP). The primary goal was to identify alterations in metabolism helpful in stratifying ASD subjects into subpopulations with shared metabolic phenotypes (i.e., metabotypes). Metabotypes associated with ASD were identified in a discovery set of 357 subjects. The reproducibility of the metabotypes was validated in an independent replication set of 351 CAMP subjects. Thirty-four candidate metabotypes that differentiated subsets of ASD from typically developing participants were identified with sensitivity of at least 5% and specificity greater than 95%. The 34 metabotypes formed six metabolic clusters based on ratios of either lactate or pyruvate, succinate, glycine, ornithine, 4-hydroxyproline, or α-ketoglutarate with other metabolites. Optimization of a subset of new and previously defined metabotypes into a screening battery resulted in 53% sensitivity (95% confidence interval [CI], 48%-57%) and 91% specificity (95% CI, 86%-94%). Thus, our metabolomic screening tool detects more than 50% of the autistic participants in the CAMP study. Further development of this metabolomic screening approach may facilitate earlier referral and diagnosis of ASD and, ultimately, more targeted treatments. LAY SUMMARY: Analysis of a selected set of metabolites in blood samples from children with autism and typically developing children identified reproducible differences in the metabolism of about half of the children with autism. Testing for these differences in blood samples can be used to help screen children as young as 18 months for risk of autism that, in turn, can facilitate earlier diagnoses. In addition, differences may lead to biological insights that produce more precise treatment options. We are exploring other blood-based molecules to determine if still a higher percentage of children with autism can be detected using this strategy. Autism Res 2020, 13: 1270-1285. © 2020 The Authors. Autism Research published by International Society for Autism Research published by Wiley Periodicals LLC.
Autism research : official journal of the International Society for Autism Research, 2020 · doi:10.1542/peds.2019-0925