Literature DB >> 32138910

Which is the urine sample material of choice for metabolomics-driven biomarker studies?

Xinyu Liu1, Peiyuan Yin1, Yaping Shao1, Zhichao Wang1, Bohong Wang1, Rainer Lehmann2, Guowang Xu3.   

Abstract

Urine-based metabolomics-driven strategies for the discovery of biomarkers are increasingly developed and applied in analytical chemistry. But valid, data-based recommendations for a urine sample material of choice are lacking. We investigated first and second morning urine (MU), which are the most commonly used urine specimens. Potential major factors biasing metabolomics biomarker results in these sample materials were studied. First, 35 1st and 2nd MU samples were collected from healthy, young men after an overnight fast. Subsequently, two subgroups were built, one having fast food at lunch and dinner (n = 17), the other vegetarian meals (n = 18). Again 1st and 2nd MU were collected. Non-targeted liquid chromatography-mass spectrometry was applied for analyses. More than half of the >5400 urinary ion features showed a significant difference between 1st and 2nd MU. Just two fast food meals on previous day significantly affected around 30% of all metabolites in 1st and 2nd MU. In contrast, the effects of two vegetarian meals in 2nd MU were only minor. Additionally, we describe 47 metabolites in urine, possible hits in biomarker studies, which are susceptible to the diet the day before sample collection. They should be handled with caution until validation in diet-controlled studies. Based on our results we think the second MU, ideally collected after standardized vegetarian meals and drinking only water on the previous day, is most suitable for valid analysis of biomarkers in urine.
Copyright © 2020 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Biobank; Diet; First morning urine; Metabolomics; Preanalytical; Second morning urine

Year:  2020        PMID: 32138910     DOI: 10.1016/j.aca.2020.01.028

Source DB:  PubMed          Journal:  Anal Chim Acta        ISSN: 0003-2670            Impact factor:   6.558


  3 in total

1.  Biomarkers of Metabolomics in Inflammatory Bowel Disease and Damp-Heat Syndrome: A Preliminary Study.

Authors:  Xingxing Wu; Kexin Liu; Qi Wu; Mao Wang; Xuelian Chen; Yuge Li; Lin Qian; Changyin Li; Guoliang Dai; Qide Zhang; Genglin Mu; Jing Wu; Zhaowei Shan
Journal:  Evid Based Complement Alternat Med       Date:  2022-07-01       Impact factor: 2.650

2.  Diagnostic Performance of Sex-Specific Modified Metabolite Patterns in Urine for Screening of Prediabetes.

Authors:  Zaifang Li; Yanhui Zhang; Miriam Hoene; Louise Fritsche; Sijia Zheng; Andreas Birkenfeld; Andreas Fritsche; Andreas Peter; Xinyu Liu; Xinjie Zhao; Lina Zhou; Ping Luo; Cora Weigert; Xiaohui Lin; Guowang Xu; Rainer Lehmann
Journal:  Front Endocrinol (Lausanne)       Date:  2022-07-14       Impact factor: 6.055

Review 3.  From bedside to bench-practical considerations to avoid pre-analytical pitfalls and assess sample quality for high-resolution metabolomics and lipidomics analyses of body fluids.

Authors:  Rainer Lehmann
Journal:  Anal Bioanal Chem       Date:  2021-06-22       Impact factor: 4.142

  3 in total

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