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dc.contributor.authorGrijseels, Sietske
dc.contributor.authorVasskog, Terje
dc.contributor.authorHeinsvig, Pia J.
dc.contributor.authorMyhre, Torbjørn Norberg
dc.contributor.authorHansen, Terkel
dc.contributor.authorMardal, Marie
dc.date.accessioned2024-11-01T15:07:16Z
dc.date.available2024-11-01T15:07:16Z
dc.date.issued2024-08-06
dc.description.abstractUntargeted metabolomics by LCsingle bondHRMS is a powerful tool to enhance our knowledge of pathophysiological processes. Whereas validation of a bioanalytical method is customary in most analytical chemistry fields, it is rarely performed for untargeted metabolomics. This study aimed to establish and validate an analytical platform for a long-term, clinical metabolomics study. Sample preparation was performed with an automated liquid handler and four analytical methods were developed and evaluated. The validation study spanned three batches with twelve runs using individual serum samples and various quality control samples. Data was acquired with untargeted acquisition and only metabolites identified at level 1 were evaluated. Validation parameters were set to evaluate key performance metrics relevant for the intended application: reproducibility, repeatability, stability, and identification selectivity, emphasizing dataset intrinsic variance. Concordance of semi-quantitative results between methods was evaluated to identify potential bias. Spearman rank correlation coefficients (rs) were calculated from individual serum samples. Of the four methods tested, two were selected for validation. A total of 47 and 55 metabolites (RPLC-ESI+- and HILIC-ESI−-HRMS, respectively) met specified validation criteria. Quality assurance involved system suitability testing, sample release, run release, and batch release. The median repeatability and within-run reproducibility as coefficient of variation% for metabolites that passed validation on RPLC-ESI+- and HILIC-ESI−-HRMS were 4.5 and 4.6, and 1.5 and 3.8, respectively. Metabolites that passed validation on RPLC-ESI+-HRMS had a median D-ratio of 1.91, and 89 % showed good signal intensity after ten-fold dilution. The corresponding numbers for metabolites with the HILIC-ESI−-HRMS method was 1.45 and 45 %, respectively. The rs median ({range}) for metabolites that passed validation on RPLC-ESI+- was 0.93 (N = 9 {0.69–0.98}) and on HILIC-ESI−-HRMS was 0.93 (N = 22 {0.55–1.00}). The validated methods proved fit-for-purpose and the laboratory thus demonstrated its capability to produce reliable results for a large-scale, untargeted metabolomics study. This validation not only bolsters the reliability of the assays but also significantly enhances the impact and credibility of the hypotheses generated from the studies. Therefore, this validation study serves as a benchmark in the documentation of untargeted metabolomics, potentially guiding future endeavors in the field.en_US
dc.identifier.citationGrijseels, Vasskog, Heinsvig, Myhre, Hansen, Mardal. Validation of two LC–HRMS methods for large-scale untargeted metabolomics of serum samples: Strategy to establish method fitness-for-purpose. Journal of Chromatography A. 2024;1732en_US
dc.identifier.cristinIDFRIDAID 2289554
dc.identifier.doi10.1016/j.chroma.2024.465230
dc.identifier.issn0021-9673
dc.identifier.issn1873-3778
dc.identifier.urihttps://hdl.handle.net/10037/35404
dc.language.isoengen_US
dc.publisherElsevieren_US
dc.relation.journalJournal of Chromatography A
dc.relation.projectIDNorges forskningsråd: 312267en_US
dc.rights.accessRightsopenAccessen_US
dc.rights.holderCopyright 2024 The Author(s)en_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0en_US
dc.rightsAttribution 4.0 International (CC BY 4.0)en_US
dc.titleValidation of two LC–HRMS methods for large-scale untargeted metabolomics of serum samples: Strategy to establish method fitness-for-purposeen_US
dc.type.versionpublishedVersionen_US
dc.typeJournal articleen_US
dc.typeTidsskriftartikkelen_US
dc.typePeer revieweden_US


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Attribution 4.0 International (CC BY 4.0)
Except where otherwise noted, this item's license is described as Attribution 4.0 International (CC BY 4.0)