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Updated: Oct 5, 2025

Multi-step Preparation Technique to Recover Multiple Metabolite Compound Classes for In-depth and Informative Metabolomic Analysis
Published on: July 11, 2014
Impact of the pre-examination phase on multicenter metabolomic studies
Veronica Ghini1, Peter M Abuja2, Ozren Polasek3
1Consorzio Interuniversitario Risonanze Magnetiche di Metallo Proteine (CIRMMP), via Luigi Sacconi 6, 50019, Sesto Fiorentino (FI), Italy; Center of Magnetic Resonance (CERM), University of Florence, via Luigi Sacconi 6, 50019, Sesto Fiorentino (FI), Italy; Department of Chemistry, University of Florence, via della Lastruccia 3, 50019, Sesto Fiorentino (FI), Italy.
Abstract:
The development of metabolomics in clinical applications has been limited by the lack of validation in large multicenter studies. Large population cohorts and their biobanks are a valuable resource for acquiring insights into molecular disease mechanisms. Nevertheless, most of their collections are not tailored for metabolomics and have been created without specific attention to the pre-analytical requirements for high-quality metabolome assessment. Thus, comparing samples obtained by different pre-analytical procedures remains a major challenge. Here, 1H NMR-based analyses are used to demonstrate how human serum and plasma samples collected with different operating procedures within several large European cohort studies from the Biobanking and Biomolecular Resources Infrastructure - Large Prospective Cohorts (BBMRI-LPC) consortium can be easily revealed by supervised multivariate statistical analyses at the initial stages of the process, to avoid biases in the downstream analysis. The inter-biobank differences are discussed in terms of deviations from the validated CEN/TS 16945:2016 / ISO 23118:2021 norms. It clearly emerges that biobanks must adhere to the evidence-based guidelines in order to support wider-scale application of metabolomics in biomedicine, and that NMR spectroscopy is informative in comparing the quality of different sample sources in multi cohort/center studies.

