New biomarker method may accurately identify autism in children

New biomarker method may accurately identify autism in children

A novel biomarker method could accurately assess if a child is on the autism spectrum, according to a new study.

Autism spectrum disorder is thought to affect around 1.5 percent of children, but diagnosis continues to prove difficult and currently relies on a multidisciplinary team of doctors. While past research has revealed distinctive metabolic processes in children on the autism spectrum, these have not previously been exploited in diagnosis.

Researchers Juergen Hahn, Daniel Howsmon and colleagues have now announced their successful development of an accurate diagnostic method for children based on blood sampling. The method detects substances in the blood produced by two metabolic processes known as the folate-dependent one-carbon (FOCM) metabolism and the transulfuration (TS) pathways, both of which are altered in children with autism.

The scientists compared blood sample data from children with autism and neurotypical children, all between 3 and 10 years old. Advanced modeling and statistical analysis tools allowed the researchers to correctly classify 97.6 percent of the children with autism and 96.1 percent of the neurotypical children based solely on their blood biomarkers.

“The method presented in this work is the only one of its kind that can classify an individual as being on the autism spectrum or as being neurotypical,” says study author Juergen Hahn. “We are not aware of any other method, using any type of biomarker, that can do this, much less with the degree of accuracy that we see in our work.”

While further research is needed to confirm the findings and to examine any impact of medications on the blood concentrations of the biomarkers, this study provides hope that in the future there might be a simple, accurate method to diagnose autism in children.

Research Article: Howsmon DP, Kruger U, Melnyk S, James SJ, Hahn J (2017) Classification and adaptive behavior prediction of children with autism spectrum disorder based upon multivariate data analysis of markers of oxidative stress and DNA methylation. PLoS Comput Biol 13(3): e1005385. doi:10.1371/journal.pcbi.1005385

Image Credit:  Daniel P. Howsmon


Beth works at PLOS as Journal Media Manager. She read Natural Sciences, specializing in Pathology, at the University of Cambridge before joining PLOS in 2013. She feels fortunate to be able to read and write about the exciting new research published by PLOS.


  • These findings are of little predictive value, it’s been known since 2004 at least (the cited paper by Sandra Jill James et al.) that there are metabolic biomarkers correlated to autism incidence, and the age group studied (3-10 years) is by and large older than the age at which ASD are usually diagnosed.

    Did no one ever think to perform a cohort study starting with a group of neonates? Of course, if these biomarkers can’t be found in infants, or can only be found at much lower incidences that draws the spotlight back onto early childhood environmental insults to the immune system as a cause of autism.

  • Pingback: A Biomarker Technique That May Detect Autism in Children | cbioyglee

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