Workshop report - interdisciplinary metabolomic epidemiology: the pathway to clinical translation.

Metabolomic epidemiology studies are complex and require a broad array of domain expertise. Although many metabolite-phenotype associations have been identified; to date, few findings have been translated to the clinic. Bridging this gap requires understanding of both the underlying biology of these associations and their potential clinical implications, necessitating an interdisciplinary team approach. To address this need in metabolomic epidemiology, a workshop was held at Metabolomics 2023 in Niagara Falls, Ontario, Canada that highlighted the domain expertise needed to effectively conduct these studies -- biochemistry, clinical science, epidemiology, and assay development for biomarker validation -- and emphasized the role of interdisciplinary teams to move findings towards clinical translation.

Metabolomics 2023 workshop report: moving toward consensus on best QA/QC practices in LC-MS-based untargeted metabolomics.

INTRODUCTION: During the Metabolomics 2023 conference, the Metabolomics Quality Assurance and Quality Control Consortium (mQACC) presented a QA/QC workshop for LC-MS-based untargeted metabolomics. OBJECTIVES: The Best Practices Working Group disseminated recent findings from community forums and discussed aspects to include in a living guidance document. METHODS: Presentations focused on reference materials, data quality review, metabolite identification/annotation and quality assurance. RESULTS: Live polling results and follow-up discussions offered a broad international perspective on QA/QC practices. CONCLUSIONS: Community input gathered from this workshop series is being used to shape the living guidance document, a continually evolving QA/QC best practices resource for metabolomics researchers.

Establishing a framework for best practices for quality assurance and quality control in untargeted metabolomics.

BACKGROUND: Quality assurance (QA) and quality control (QC) practices are key tenets that facilitate study and data quality across all applications of untargeted metabolomics. These important practices will strengthen this field and accelerate its success. The Best Practices Working Group (WG) within the Metabolomics Quality Assurance and Quality Control Consortium (mQACC) focuses on community use of QA/QC practices and protocols and aims to identify, catalogue, harmonize, and disseminate current best practices in untargeted metabolomics through community-driven activities. AIM OF REVIEW: A present goal of the Best Practices WG is to develop a working strategy, or roadmap, that guides the actions of practitioners and progress in the field. The framework in which mQACC operates promotes the harmonization and dissemination of current best QA/QC practice guidance and encourages widespread adoption of these essential QA/QC activities for liquid chromatography-mass spectrometry. KEY SCIENTIFIC CONCEPTS OF REVIEW: Community engagement and QA/QC information gathering activities have been occurring through conference workshops, virtual and in-person interactive forum discussions, and community surveys. Seven principal QC stages prioritized by internal discussions of the Best Practices WG have received participant input, feedback and discussion. We outline these stages, each involving a multitude of activities, as the framework for identifying QA/QC best practices. The ultimate planned product of these endeavors is a "living guidance" document of current QA/QC best practices for untargeted metabolomics that will grow and change with the evolution of the field.

Effects of Preanalytical Sample Collection and Handling on Comprehensive Metabolite Measurements in Human Urine Biospecimens.

Epidemiology studies evaluate associations between the metabolome and disease risk. Urine is a common biospecimen used for such studies due to its wide availability and non-invasive collection. Evaluating the robustness of urinary metabolomic profiles under varying preanalytical conditions is thus of interest. Here we evaluate the impact of sample handling conditions on urine metabolome profiles relative to the gold standard condition (no preservative, no refrigeration storage, single freeze thaw). Conditions tested included the use of borate or chlorhexidine preservatives, various storage and freeze/thaw cycles. We demonstrate that sample handling conditions impact metabolite levels, with borate showing the largest impact with 125 of 1,048 altered metabolites (adjusted P < 0.05). When simulating a case-control study with expected inconsistencies in sample handling, we predicted the occurrence of false positive altered metabolites to be low (< 11). Predicted false positives increased substantially (³63) when cases were simulated to undergo alternate handling. Finally, we demonstrate that sample handling impacts on the urinary metabolome were markedly smaller than those in serum. While changes in urine metabolites incurred by sample handling are generally small, we recommend implementing consistent handling conditions and evaluating robustness of metabolite measurements for those showing significant associations with disease outcomes.