Untargeted Metabolomics-Based Screening Method for Inborn Errors of Metabolism using Semi-Automatic Sample Preparation with an UHPLC- Orbitrap-MS Platform

Abstract

Routine diagnostic screening of inborn errors of metabolism (IEM) is currently performed by different targeted analyses of known biomarkers. This approach is time-consuming, targets a limited number of biomarkers and will not identify new biomarkers. Untargeted metabolomics generates a global metabolic phenotype and has the potential to overcome these issues. We describe a novel, single platform, untargeted metabolomics method for screening IEM, combining semi-automatic sample preparation with pentafluorophenylpropyl phase (PFPP)-based UHPLC- Orbitrap-MS. We evaluated analytical performance and diagnostic capability of the method by analysing plasma samples of 260 controls and 53 patients with 33 distinct IEM. Analytical reproducibility was excellent, with peak area variation coefficients below 20% for the majority of the metabolites. We illustrate that PFPP-based chromatography enhances identification of isomeric compounds. Ranked z-score plots of metabolites annotated in IEM samples were reviewed by two laboratory specialists experienced in biochemical genetics, resulting in the correct diagnosis in 90% of cases. Thus, our untargeted metabolomics platform is robust and differentiates metabolite patterns of different IEMs from those of controls. We envision that the current approach to diagnose IEM, using numerous tests, will eventually be replaced by untargeted metabolomics methods, which also have the potential to discover novel biomarkers and assist in interpretation of genetic data.

Keywords: HRAM-MS; IEM; LC-MS; Orbitrap; PFPP; PKU; inborn errors of metabolism; metabolomics; organic aciduria; urea cycle defects.

Figure 1

Variation in peak area across the chromatographic run. Box-plots of within batch CVs in peak areas from all eight batches are shown containing all metabolites annotated in the QC samples, binned by retention time (bin width: 1 min); see text. Top panel: positive ion mode, bottom panel: negative ion mode.

Figure 2

Separation of isomeric compounds using pentafluorophenylpropyl-based UHPLC. Panel (A) XIC (mass tolerance: 1 ppm, ionization: ESI(-)) of 172.09792 m/z in an aminoacylase I deficiency sample showing peaks of N-acetylisoleucine (RT: 4.533 min) and N-acetylleucine (RT: 4.628 min). Panel (B): XIC (mass tolerance: 1 ppm, ionization: ESI(-)) of 172.09792 m/z in a medium chain acyl-CoA dehydrogenase deficiency sample showing peaks of N-acetylleucine (RT: 4.598 min), isohexanoylglycine (RT: 4.686 min) and hexanoylglycine (RT: 4.752 min).

Figure 3

Metabolomics test result of a hyperargininemia sample. The top 45 of ranked z-scores are depicted with arrows highlighting metabolites relevant to the diagnosis. Red diamonds: average z-score of the patient triplicate >20, red dots: z-scores of the patient triplicate, grey dots: reference values (n = 15).