Autism 'Signature' Detectable in the Blood?

Megan Brooks

June 23, 2020

Unique metabolic signatures in the blood can accurately identify more than 50% of children with autism spectrum disorder (ASD), a finding that researchers believe could lead to earlier diagnosis and perhaps tailored treatments.

The latest findings from the Children's Autism Metabolome Project (CAMP) show that an "optimized" test battery detected 53% of children who had ASD with 91% specificity.

"Our goal is to make this approach valuable to clinicians in determining which children should receive professional diagnostic assessment," senior author David G. Amaral, PhD, distinguished professor, University of California, Davis, and director, MIND Institute Autism Center of Excellence in Sacramento, told Medscape Medical News.

"A longer-term goal is to establish subtypes of autism that may benefit from more specialized metabolic treatment," he added.

The study was published online June 18 in Autism Research.

Testing at Birth?

The CAMP study is a large-scale effort to define autism biomarkers on the basis of metabolomic analyses of blood samples from young children.

As reported by Medscape Medical News, an earlier study of CAMP participants that examined a combination of three ASD-associated amino acid "metabotypes" detected about 17% of the children who had ASD.

In the latest study, CAMP researchers quantitatively assessed 39 metabolites associated with amino acid and energy metabolism in an attempt to expand the identification of metabolic subpopulations of children with ASD.

The analyses included 499 children aged 18 to 48 months who had ASD and 209 typically developing children.

The researchers identified 34 candidate metabotypes that differentiated subsets of children with ASD from the typically developing participants.

The 34 metabotypes formed six clusters related to amino acid and mitochondrial energy metabolism. These clusters constituted ratios containing lactate or pyruvate, succinate, α-ketoglutarate, glycine, ornithine, and 4-hydroxyproline in combination with other metabolites.

These clusters highlight potential dysregulation in amino acid and energy metabolism in children with ASD in comparison to typically developing children, the researchers note.

The "optimized" metabotype screening test battery had a sensitivity of 53% (95% confidence interval [CI], 48% – 57%) and a specificity of 91% (95% CI, 86% – 94%) in ASD detection.

"The implication of these results, which must be verified in a prospective study, is that this metabolomics-based test battery is potentially able to detect more than 50% of individuals at risk for ASD," the researchers write.

"While biomarkers of any kind cannot provide a definitive diagnosis, combining a metabolomics-based screen with a behavioral screening tool...increases the likelihood that those at risk for ASD can be detected as early as possible," they add.

Amaral cautioned that this research is "an evolving process. There are thousands of metabolites that could be analyzed in an attempt to find screening markers of risk for autism. Because we are doing these studies quantitatively, it takes a substantial amount of time to establish the analytic pipeline for each new group of metabolites," he said.

"We are currently analyzing additional metabolites and have promising initial findings that we will again be able to increase the percentage of detected participants," Amaral added.

He said his team is soliciting funding to move their approach forward and to test dried blood spots that are collected from most babies shortly after birth.

A Critical Endeavor

Commenting on this research for Medscape Medical News, Victoria Chen, MD, developmental behavioral pediatrician, Cohen Children's Hospital, New Hyde Park, New York, said that given the complexity of ASD and that there are often delays in evaluating children for ASD, it's "exciting to learn that there may be a biomarker that can help expedite this process.

"Metabolomic analysis to distinguish children with ASD from neurotypical children may be valuable in screening some children for ASD and to open up avenues of research into new biological treatments for ASD based on different metabolomic profiles," Chen said.

She cautioned that although the study had a robust sample of 708 children, most children in the sample (>70%) had ASD.

"Therefore, the clinical utility of using this screening test in the general population is unknown," Chen said.

She noted that the test may have a role in confirming a diagnosis if a child fails another screening test, such as the Modified Checklist for Autism in Toddlers–Revised with Follow Up (MCHAT R/F), which is commonly used to screen for ASD in pediatric primary care.

"Yet more research is needed to validate this test's use in conjunction with another clinical test like the MCHAT R/F," said Chen.

The test may also have a role in screening for ASD in high-risk populations, such as siblings of children with ASD or children for whom there is significant behavioral/developmental concern.

On the other hand, she said, the study population did not include any children with other neurodevelopmental disorders, so its utility in some high-risk populations, such as children with genetic disorders, is also unknown and remains to be determined in further studies, said Chen.

"Nevertheless," she noted, "research into biomarkers is a critical endeavor to improve screening for ASD as well as to explore new areas for ASD treatment, and this work in metabolomic analysis is an important step to reaching this overarching goal."

The research was supported by a grant from the National Institutes of Health and by donations from the Nancy Lurie Marks Family Foundation and the Robert E. Landreth and Donna Landreth Family Fund. Amaral is on the scientific advisory board of Stemina Biomarker Discovery, Inc, and serves as editor-in-chief of Autism Research. Chen has disclosed no relevant financial relationships.

Autism Res. Published online June 18, 2020. Full text

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