Clinical Untargeted Metabolomics as a Functional Screen to Improve Variant Classification

Area of Science:

• Genomics
• Metabolomics
• Clinical Diagnostics

Background:

• Clinical exome and genome sequencing generate numerous variants of uncertain significance (VUS), complicating genetic diagnosis.
• Traditional biochemical testing for metabolic disorders is often narrow in scope, leading to diagnostic delays.

Purpose of the Study:

• To demonstrate the utility of untargeted metabolomic screening in classifying variants of uncertain significance (VUS) in metabolic disorders.
• To highlight how integrating metabolomics with genomic sequencing improves diagnostic outcomes.

Main Methods:

• Utilized untargeted metabolomic screening to analyze thousands of metabolites across various metabolic pathways.
• Integrated metabolomic data with exome or genome sequencing results.
• Presented representative cases illustrating the application of metabolomics in variant interpretation.

Main Results:

• Untargeted metabolomic screening provided functional validation for uncertain genetic findings.
• The integrated approach improved diagnostic yield and facilitated the classification of VUS.
• Metabolomics assays identified numerous metabolites, offering a broader diagnostic scope than traditional methods.

Conclusions:

• Untargeted metabolomic screening is a valuable tool for interpreting VUS in metabolic disorders.
• Integrating metabolomics with genomic sequencing enhances diagnostic accuracy and efficiency.
• This combined approach offers a more comprehensive and timely diagnosis for patients with metabolic conditions.