New Biomarker Panel Could Accelerate Autism Diagnoses

Affected individuals vary enormously in the severity of their autistic characteristics as well as in the occurrence of many co-morbid conditions.

No biomarker tests for autism spectrum disorder (ASD) currently exist. Children are diagnosed based on their altered behaviors, which may not become evident until children are two to four years old. Families often must wait over a year or more for an appointment with a specialist, delaying diagnosis even further.

A team of scientists working with those at the University of California Davis (Davis, CA, USA) recruited children, ages 18 to 48 months, from eight centers across the USA. Each participant underwent physical, neurological and behavioral examinations. Metadata was obtained about the children's birth, developmental, medical and immunization histories, dietary supplements and medications. Parents’ medical histories were also obtained. Blood was collected from subjects after at least a 12 hour fast by venipuncture into 6 mL sodium heparin tubes on wet ice.

The investigators used the Waters AccQTag Ultra kit, which employs derivatization of amine moieties with 6-aminoquinolyl-N-hydroxysuccinimidyl carbamate and was employed for all samples prior to multiple reaction monitoring (MRM) on a liquid chromatography (LC) mass spectrometry (MS) system consisting of an Agilent 1290 ultra-high performance liquid chromatograph (UHPLC) coupled to an Agilent G6490 Triple Quadrupole Mass Spectrometer.

The team compared blood metabolites, specifically, amino acids, in 516 children with ASD and 164 children showing typical development. They found that 17% of the ASD children had unique concentrations of specific amino acids, known as metabotypes, in their blood. Though a 17% subgroup may seem small, it is actually quite significant. The combination of glutamine, glycine, and ornithine Amino Acid Dysregulation Metabotypes (AADMs) identified a dysregulation in amino acid/ branch chain amino acid (AA/BCAA) metabolism that is present in 16.7% of the ASD subjects and is detectable with a specificity of 96.3% and a positive predictive value (PPV) of 93.5%.

The author demonstrates one approach to analyzing the metabolism of ASD to successfully identify reproducible metabotypes. Analysis of the study samples is ongoing and there will be additional metabotypes, which will be diagnostic for subsets of children with ASD. Stratifying ASD based on metabotypes offers an opportunity to identify efficacious interventions within metabotypes that can lead to more precise and individualized treatment.

David G. Amaral, PhD, a professor of psychiatry and lead investigator of the study, said, “With this panel of alterations in amino acid metabolism, we can detect about 17% of kids with ASD. This is the first of hopefully many panels that will identify other subsets of kids with autism.” The study was published on September 6, 2018, in the journal Biological Psychiatry.

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University of California Davis