Metabolomics to Improve the Diagnostic Efficiency of Inborn Errors of Metabolism

Dylan Mordaunt, David Cox, Maria Fuller

Research output: Contribution to journalReview articlepeer-review

9 Citations (Scopus)

Abstract

Early diagnosis of inborn errors of metabolism (IEM)—a large group of congenital disorders—is critical, given that many respond well to targeted therapy. Newborn screening programs successfully capture a proportion of patients enabling early recognition and prompt initiation of therapy. For others, the heterogeneity in clinical presentation often confuses diagnosis with more common conditions. In the absence of family history and following clinical suspicion, the laboratory diagnosis typically begins with broad screening tests to circumscribe specialised metabolite and/or enzyme assays to identify the specific IEM. Confirmation of the biochemical diagnosis is usually achieved by identifying pathogenic genetic variants that will also enable cascade testing for family members. Unsurprisingly, this diagnostic trajectory is too often a protracted and lengthy process resulting in delays in diagnosis and, importantly, therapeutic intervention for these rare conditions is also postponed. Implementation of mass spectrometry technologies coupled with the expanding field of metabolomics is changing the landscape of diagnosing IEM as numerous metabolites, as well as enzymes, can now be measured collectively on a single mass spectrometry-based platform. As the biochemical consequences of impaired metabolism continue to be elucidated, the measurement of secondary metabolites common across groups of IEM will facilitate algorithms to further increase the efficiency of diagnosis.

Original languageEnglish
Article number1195
Number of pages17
JournalInternational Journal of Molecular Sciences
Volume21
Issue number4
DOIs
Publication statusPublished - 2 Feb 2020
Externally publishedYes

Keywords

  • Diagnosis
  • Enzyme
  • Genetic disorder
  • Genetic variants
  • Inherited metabolic disease
  • Mass spectrometry
  • Metabolite
  • Screening
  • Substrate

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