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ICCS 2022: A Systems Biology Workflow to Support the Diagnosis of Pyrimidine and Urea Cycle Disorders

Sl, De ; Willighagen, Egon ; Hemel, Irene ; Evelo, Chris ; Bierau, Jörgen ; Steinbusch, Laura

figshare 2022

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  • Título:
    ICCS 2022: A Systems Biology Workflow to Support the Diagnosis of Pyrimidine and Urea Cycle Disorders
  • Autor: Sl, De ; Willighagen, Egon ; Hemel, Irene ; Evelo, Chris ; Bierau, Jörgen ; Steinbusch, Laura
  • Materias: Bioinformatics ; Cheminformatics ; Clinical Chemistry (diagnostics) ; FOS: Biological sciences ; FOS: Clinical medicine ; FOS: Computer and information sciences ; Systems Biology
  • Descripción: Presentation for ICCS conference (https://iccs-nl.org/general-information/scientific-program/) during session 'Dealing with Biological Complexity'. Abstract: Pyrimidine metabolism provides essential high-energy vehicles serving as fuel, building blocks, and messenger molecules. The pyrimidine pathway overlaps with the urea cycle through a common metabolite (carbamoyl phosphate), leading to substantial biomarker overlap for Inherited Metabolic Disorders (IMDs) within these pathways. We used these well-known overlapping pathways as a proof-of-concept for the developed of a a framework combining clinical and theoretical biomarkers with pathway models through network approaches and semantic web technologies. Our framework integrates literature and expert knowledge into machine-readable pathways. The top three pathways of interest were retrieved covering most unique markers and overlapping with theoretical marker data, which was used to visualize clinical data of 16 previously diagnosed patients with various pyrimidine and urea cycle disorders. Two expert laboratory scientists evaluated our approach. The number of relevant biomarkers for each patient varies greatly (five to 48), and the pathways covering most unique biomarkers differ for equivalent disorders. The two experts reached similar conclusions with our proposed framework as with their current workflow for nine patient samples, without knowledge about clinical symptoms or sex. For the remaining seven cases, four interpretations pointed in the direction of a subset of disorders, while three cases were found to be undiagnosable with the available data.The presented workflow is adaptable to analyze different types of IMDs, difficult patient cases, and functional assays in the future. Furthermore, the pathway models can be used as a basis to perform various other types of (omics) data analysis, e.g. transcriptomics, metabolomics, and fluxomics.
  • Editor: figshare
  • Fecha de creación: 2022
  • Idioma: Inglés
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