Application of metabolite set enrichment analysis on untargeted metabolomics data prioritises relevant pathways and detects novel biomarkers for inherited metabolic disorders. Issue 4 (22nd May 2022)

• Record Type: Journal Article
• Authors: Hoegen, Brechtje; Hampstead, Juliet E.; Engelke, Udo F.H.; Kulkarni, Purva; Wevers, Ron A.; Brunner, Han G.; Coene, Karlien L. M.; Gilissen, Christian
• Is Part Of: Journal of inherited metabolic disease. Volume 45:Issue 4(2022)
• Page Start: 682
• Page End: 695
• Publication Date: 2022-05-22
• Subjects: biochemical pathways -- biomarkers -- cystathionine ß‐synthase -- inborn errors of metabolism -- inherited metabolic disorders -- mass spectrometry -- metabolite set enrichment analysis -- next‐generation metabolic screening -- untargeted metabolomics; Metabolism, Inborn errors of -- Periodicals; Metabolism -- Disorders -- Periodicals; 616.39042
• DOI: 10.1002/jimd.12522
• Languages: English
• ISSNs: 0141-8955

Abstract

Abstract: Untargeted metabolomics (UM) allows for the simultaneous measurement of hundreds of metabolites in a single analytical run. The sheer amount of data generated in UM hampers its use in patient diagnostics because manual interpretation of all features is not feasible. Here, we describe the application of a pathway‐based metabolite set enrichment analysis method to prioritise relevant biological pathways in UM data. We validate our method on a set of 55 patients with a diagnosed inherited metabolic disorder (IMD) and show that it complements feature‐based prioritisation of biomarkers by placing the features in a biological context. In addition, we find that by taking enriched pathways shared across different IMDs, we can identify common drugs and compounds that could otherwise obscure genuine disease biomarkers in an enrichment method. Finally, we demonstrate the potential of this method to identify novel candidate biomarkers for known IMDs. Our results show the added value of pathway‐based interpretation of UM data in IMD diagnostics context. Abstract :