ArticleBiomolecules2019
The Effect of Anticoagulants, Temperature, and Time on the Human Plasma Metabolome and Lipidome from Healthy Donors as Determined by Liquid Chromatography-Mass Spectrometry.
Article in Biomolecules, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
27 citing papers in PubMed, 52 citations in OpenAlex.
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- Investigating Variability in Metabolomics: A Comparative Study of Analytical Platforms and Blood Matrices Using HPLC-HRMS.Molecules (Basel, Switzerland) · 2026Article
- Systematic evaluation of pre-analytical variables on synovial fluid metabolomic profiles using GC-ToF-MS and UHPLC-MS.The Analyst · 2026Article
- Multicohort assessment of plasma metabolic signatures of tuberculosis disease in children: a retrospective cross-sectional study.Scientific reports · 2026Article
- Standard Operating Procedures in Biorepositories and Biobanks.Methods in molecular biology (Clifton, N.J.) · 2026Article
- Multicohort assessment of plasma metabolic signatures of tuberculosis disease in children.Research square · 2025Article
- CE-MS-Based Clinical Metabolomics of Human Plasma.Methods in molecular biology (Clifton, N.J.) · 2025Article
- Sample Preparation for Metabolomic Analysis in Exercise Physiology.Biomolecules · 2024Review
- Choice of blood collection methods influences extracellular vesicles counts and miRNA profiling.Journal of extracellular biology · 2024Article
- An Overview of Pre-Analytical Factors Impacting Metabolomics Analyses of Blood Samples.Metabolites · 2024Review
- Serum protein profiling reveals mechanism of activated thrombus formation in patients with stroke and atrial fibrillation.Scientific reports · 2024Article
- Challenges in the Metabolomics-Based Biomarker Validation Pipeline.Metabolites · 2024Review
- Article
- The Influence of Preanalytical Biospecimen Handling on the Measurement of B Vitamers, Amino Acids, and Other Metabolites in Blood.Biopreservation and biobanking · 2023Article
- Study protocol for a randomized, controlled trial using a novel, family-centered diet treatment to prevent nonalcoholic fatty liver disease in Hispanic children.Contemporary clinical trials · 2023Article
- Detection and analysis of chiral molecules as disease biomarkers.Nature reviews. Chemistry · 2023Review
- Article
- Human bone marrow stromal cells: the impact of anticoagulants on stem cell properties.Frontiers in cell and developmental biology · 2023Article
- TCA cycle remodeling drives proinflammatory signaling in humans with pulmonary tuberculosis.PLoS pathogens · 2021Article
- Analytical considerations for reducing the matrix effect for the sphingolipidome quantification in whole blood.Bioanalysis · 2021Article
Corrections and comments
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Authors and funding
14 authors at 2 institutions in 1 country.
Funding
Abstract
Liquid-chromatography mass spectrometry is commonly used to identify and quantify metabolites from biological samples to gain insight into human physiology and pathology. Metabolites and their abundance in biological samples are labile and sensitive to variations in collection conditions, handling and processing. Variations in sample handling could influence metabolite levels in ways not related to biology, ultimately leading to the misinterpretation of results. For example, anticoagulants and preservatives modulate enzyme activity and metabolite oxidization. Temperature may alter both enzymatic and non-enzymatic chemistry. The potential for variation induced by collection conditions is particularly important when samples are collected in remote locations without immediate access to specimen processing. Data are needed regarding the variation introduced by clinical sample collection processes to avoid introducing artifact biases. In this study, we used metabolomics and lipidomics approaches paired with univariate and multivariate statistical analyses to assess the effects of anticoagulant, temperature, and time on healthy human plasma samples collected to provide guidelines on sample collection, handling, and processing for vaccinology. Principal component analyses demonstrated clustering by sample collection procedure and that anticoagulant type had the greatest effect on sample metabolite variation. Lipids such as glycerophospholipids, acylcarnitines, sphingolipids, diacylglycerols, triacylglycerols, and cholesteryl esters are significantly affected by anticoagulant type as are amino acids such as aspartate, histidine, and glutamine. Most plasma metabolites and lipids were unaffected by storage time and temperature. Based on this study, we recommend samples be collected using a single anticoagulant (preferably EDTA) with sample processing at <24 h at 4 °C.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.