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.
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.
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.
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.
血液代谢物的代谢谱分析,尤其是血浆和血清中的代谢谱分析,对于研究人类疾病、健康状况、药物干预和毒理学至关重要。血液的临床意义源于其与所有人体细胞的紧密联系以及易于获取性。然而,患者特异性变量,如年龄、性别、饮食、生活方式和健康状况,以及分析前条件(样本处理、储存等),会显著影响全血、血浆或血清研究中的代谢组学测量。这些因素,即混杂因素,必须加以缓解,以揭示因疾病或干预开始而导致的真正代谢变化。
本综述旨在帮助代谢组学研究人员收集基于核磁共振的血液(全血/血清/血浆)代谢组学的可靠、标准化数据集。目标是减少混杂因素的影响,提高实验室间的可比性,使代谢组学研究产生更有意义的结果。
本综述概述了影响血液代谢物水平的主要因素,并针对测量内容及预期结果、如何减轻混杂因素、如何正确制备、处理和储存血液、血浆和血清生物样本,以及如何在基于核磁共振的血液、血浆和血清靶向代谢组学研究中报告数据提供了实用建议。