The Effect of Anticoagulants, Temperature, and Time on the Human Plasma Metabolome and Lipidome from Healthy Donors as Determined by Liquid Chromatography-Mass Spectrometry

• Type of Material: Article
• Authors: Manoj Khadka, Emory University; Andrei Todor, Emory University; Kristal M. Maner-Smith, Emory University; Jennifer K. Colucci, Emory University; ViLinh Tran, Emory University; David A. Gaul, Georgia Institute of Technology; Evan Anderson, Emory University; Muktha S. Natrajan, Emory University; Nadine Rouphael, Emory University; Mark Mulligan, Emory University; Circe E. McDonald, Emory University; Mehul Suthar, Emory University; Shuzhao Li, Emory University; Eric Ortlund, Emory University
• Language: English
• Date: 2019-05-23
• Publisher: MDPI
• Publication Version: Final Published Version
• Copyright Statement: © 2019 by the authors.
• License: Creative Commons Attribution 4.0 International
• Final Published Version (URL): http://dx.doi.org/10.3390/biom9050200
• Title of Journal or Parent Work: Biomolecules
• ISSN: 2218-273X
• Volume: 9
• Issue: 5
• Start Page: 200
• Grant/Funding Information: This study was supported in part by the Emory Integrated Lipidomics Core (EILC), which is subsidized by the Emory University School of Medicine and is one of the Emory Integrated Core Facilities.; This work was supported by awards from the Division of Microbiology and Infectious Diseases, National Institute of Allergy and Infectious Diseases at the National Institutes of Health to Emory Vaccine and Treatment Evaluation Unit, contract HHSN272201300018I.; This work was supported by the Georgia Institute of Technology’s Mass Spectrometry Core Facility.; Additional support was provided by the Georgia Clinical and Translational Science Alliance of the National Institutes of Health under Award Number UL1TR002378.
• Keywords: lipidomics; storage conditions; metabolomics; vaccine; anticoagulants; sample collection
• Research Categories: Chemistry, Biochemistry; Chemistry, Physical

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.