{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,10]],"date-time":"2026-06-10T18:12:01Z","timestamp":1781115121377,"version":"3.54.1"},"reference-count":53,"publisher":"Public Library of Science (PLoS)","issue":"4","license":[{"start":{"date-parts":[[2021,4,8]],"date-time":"2021-04-08T00:00:00Z","timestamp":1617840000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["www.plosone.org"],"crossmark-restriction":false},"short-container-title":["PLoS ONE"],"abstract":"\nIntroduction<\/jats:title>\nAnalysis of blood for the evaluation of clinically relevant biomarkers requires precise collection and sample handling by phlebotomists and laboratory staff. An important consideration for the clinical application of metabolomics are the different anticoagulants utilized for sample collection. Most studies that have characterized differences in metabolite levels in various blood collection tubes have focused on single analytes. We define analyte levels on a global metabolomics platform following blood sampling using five different, but commonly used, clinical laboratory blood collection tubes (i.e., plasma anticoagulated with either EDTA, lithium heparin or sodium citrate, along with no additive (serum), and EDTA anticoagulated whole blood).<\/jats:p>\n<\/jats:sec>\n\nMethods<\/jats:title>\nUsing an untargeted metabolomics platform we analyzed five sample types after all had been collected and stored at -80\u00b0C. The biochemical composition was determined and differences between the samples established using matched-pair t-tests.<\/jats:p>\n<\/jats:sec>\n\nResults<\/jats:title>\nWe identified 1,117 biochemicals across all samples and detected a mean of 1,036 in the sample groups. Compared to the levels of metabolites in EDTA plasma, the number of biochemicals present at statistically significant different levels (p<0.05) ranged from 452 (serum) to 917 (whole blood). Several metabolites linked to screening assays for rare diseases including acylcarnitines, bilirubin and heme metabolites, nucleosides, and redox balance metabolites varied significantly across the sample collection types.<\/jats:p>\n<\/jats:sec>\n\nConclusions<\/jats:title>\nOur study highlights the widespread effects and importance of using consistent additives for assessing small molecule levels in clinical metabolomics. The biochemistry that occurs during the blood collection process creates a reproducible signal that can identify specimens collected with different anticoagulants in metabolomic studies.<\/jats:p>\n<\/jats:sec>\n\nImpact statement<\/jats:title>\nIn this manuscript, normal\/healthy donors had peripheral blood collected using multiple anticoagulants as well as serum during a fasted blood draw. Global metabolomics is a new technology being utilized to draw clinical conclusions and we interrogated the effects of different anticoagulants on the levels of biochemicals from each of the donors. Characterizing the effects of the anticoagulants on biochemical levels will help researchers leverage the information using global metabolomics in order to make conclusions regarding important disease biomarkers.<\/jats:p>\n<\/jats:sec>","DOI":"10.1371\/journal.pone.0249797","type":"journal-article","created":{"date-parts":[[2021,4,8]],"date-time":"2021-04-08T18:25:26Z","timestamp":1617906326000},"page":"e0249797","update-policy":"https:\/\/doi.org\/10.1371\/journal.pone.corrections_policy","source":"Crossref","is-referenced-by-count":40,"title":["Global biochemical analysis of plasma, serum and whole blood collected using various anticoagulant additives"],"prefix":"10.1371","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5391-9457","authenticated-orcid":true,"given":"Adam 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