Emwas Abdul-Hamid, Zacharias Helena U, Alborghetti Marcos Rodrigo, Gowda G A Nagana, Raftery Daniel, McKay Ryan T, Chang Chung-Ke, Saccenti Edoardo, Gronwald Wolfram, Schuchardt Sven, Leiminger Roland, Merzaban Jasmeen, Madhoun Nour Y, Iqbal Mazhar, Alsiary Rawiah A, Shivapurkar Rupali, Pain Arnab, Shanmugam Dhanasekaran, Ryan Danielle, Roy Raja, Schirra Horst Joachim, Morris Vanessa, Zeri Ana Carolina, Alahmari Fatimah, Kaddurah-Daouk Rima, Salek Reza M, LeVatte Marcia, Berjanskii Mark, Lee Brian, Wishart David S
King Abdullah University of Science and Technology (KAUST), Core Labs, Thuwal, 23955-6900, Kingdom of Saudi Arabia.
Peter L. Reichertz Institute for Medical Informatics of TU Braunschweig and Hannover Medical School, Hannover Medical School, 30625, Hannover, Germany.
Metabolomics. 2025 May 10;21(3):66. doi: 10.1007/s11306-025-02259-7.
BACKGROUND: Metabolic profiling of blood metabolites, particularly in plasma and serum, is vital for studying human diseases, human conditions, drug interventions and toxicology. The clinical significance of blood arises from its close ties to all human cells and facile accessibility. However, patient-specific variables such as age, sex, diet, lifestyle and health status, along with pre-analytical conditions (sample handling, storage, etc.), can significantly affect metabolomic measurements in whole blood, plasma, or serum studies. These factors, referred to as confounders, must be mitigated to reveal genuine metabolic changes due to illness or intervention onset. REVIEW OBJECTIVE: This review aims to aid metabolomics researchers in collecting reliable, standardized datasets for NMR-based blood (whole/serum/plasma) metabolomics. The goal is to reduce the impact of confounding factors and enhance inter-laboratory comparability, enabling more meaningful outcomes in metabolomics studies. KEY CONCEPTS: This review outlines the main factors affecting blood metabolite levels and offers practical suggestions for what to measure and expect, how to mitigate confounding factors, how to properly prepare, handle and store blood, plasma and serum biosamples and how to report data in targeted NMR-based metabolomics studies of blood, plasma and serum.
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