A Novel UHPLC-MS Method Targeting Urinary Metabolomic Markers for Autism Spectrum Disorder

Dominika Olesova1, Jaroslav Galba2, Juraj Piestansky2

  • 1Institute of Neuroimmunology, Slovak Academy of Sciences, Dubravska cesta 9, 84510 Bratislava, Slovakia.

Metabolites
|November 5, 2020
PubMed

Insights

Researchers developed a new lab test to detect autism spectrum disorder (ASD) earlier using urine biomarkers. This method identifies specific metabolites linked to oxidative stress and gut bacteria, aiding in early diagnosis and treatment.

Area of Science:

  • Biochemistry
  • Neuroscience
  • Analytical Chemistry

Background:

  • Autism spectrum disorder (ASD) is a complex neurodevelopmental condition with no established biomarkers.
  • Current diagnostic methods rely on behavioral observation and clinical assessment, often leading to delayed diagnoses.
  • Early diagnosis is crucial for timely intervention and improved outcomes in children with ASD.

Purpose of the Study:

  • To develop a sensitive and reliable laboratory method for early detection of autism spectrum disorder.
  • To identify and quantify potential urinary metabolomic biomarkers for ASD diagnosis and subtyping.
  • To investigate disturbances in arginine and purine metabolism, and gut bacteria-associated metabolites in children with ASD.

Main Methods:

  • Developed an ultra-high performance liquid chromatography-tandem triple quadrupole mass spectrometry (UHPLC-MS/MS) method for simultaneous analysis of six urinary metabolites.
  • Utilized reversed-phase liquid chromatography with gradient elution on a Phenomenex Luna® Omega Polar C18 column.
  • Analyzed urine samples from children with ASD and age-matched controls.

Main Results:

  • The method successfully quantified methylguanidine, N-acetyl arginine, inosine, indole-3-acetic acid, indoxyl sulfate, and xanthurenic acid.
  • Elevated levels of oxidative stress markers (methylguanidine, N-acetylarginine) and gut bacteria products (indoxyl sulfate, indole-3-acetic acid) were observed in children with ASD.
  • The developed method demonstrated speed, sensitivity, and reliability for biomarker quantification.

Conclusions:

  • The novel UHPLC-MS/MS method is well-suited for quantifying potential ASD biomarkers in urine.
  • Metabolomic profiling reveals significant alterations in arginine and purine metabolism, and gut microbiota activity in children with ASD.
  • This approach holds promise for earlier ASD detection and characterization.

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