Global biochemical analysis of plasma, serum and whole blood collected using various anticoagulant additives.
Global biochemical analysis of plasma, serum and whole blood collected using various anticoagulant additives.
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DOI：
10.1371/journal.pone.0249797
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发表时间：
2021
期刊：
影响因子：
3.7
通讯作者：
Toal DR
中科院分区：
文献类型：
--
作者：
Kennedy AD;Ford L;Wittmann B;Conner J;Wulff J;Mitchell M;Evans AM;Toal DR
用于评估临床相关生物标志物的血液分析需要抽血师和实验室工作人员精确收集和样本处理。代谢组学临床应用的一个重要考虑因素是用于样本采集的不同抗凝剂。大多数表征不同采血管中代谢物水平差异的研究都集中在单一分析物上。我们使用五种不同但常用的临床实验室采血管（即，用EDTA、肝素锂或柠檬酸钠抗凝的血浆，沿着无添加剂（血清），和EDTA抗凝的全血）。使用非靶向代谢组学平台，我们分析了五种样品类型，所有样品都已收集并储存在-80 ° C下。测定生化组成，并使用配对t检验建立样品之间的差异。我们在所有样本中鉴定了1，117种生化物质，并在样本组中检测到平均1，036种。与EDTA血浆中的代谢物水平相比，以统计学显著不同水平（p<0.05）存在的生化物质的数量范围为452（血清）至917（全血）。与罕见病筛查试验相关的几种代谢物，包括酰基肉毒碱、胆红素和血红素代谢物、核苷和氧化还原平衡代谢物，在样本采集类型中差异显著。我们的研究强调了在临床代谢组学中使用一致的添加剂评估小分子水平的广泛影响和重要性。血液采集过程中发生的生物化学产生了可重现的信号，可以识别代谢组学研究中使用不同抗凝剂采集的标本。在本手稿中，正常/健康供体在空腹采血期间使用多种抗凝剂以及血清采集外周血。全球代谢组学是一项用于得出临床结论的新技术，我们询问了不同抗凝剂对每个供体生化物质水平的影响。表征抗凝剂对生化水平的影响将有助于研究人员利用全球代谢组学的信息，以便得出有关重要疾病生物标志物的结论。
Analysis 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). Using an untargeted metabolomics platform we analyzed five sample types after all had been collected and stored at -80°C. The biochemical composition was determined and differences between the samples established using matched-pair t-tests. We 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. Our 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. In 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.
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影响因子：
3.6
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Dunn, Warwick B.;Lin, Wanchang;Broadhurst, David;Begley, Paul;Brown, Marie;Zelena, Eva;Vaughan, Andrew A.;Halsall, Antony;Harding, Nadine;Knowles, Joshua D.;Francis-McIntyre, Sue;Tseng, Andy;Ellis, David I.;O'Hagan, Steve;Aarons, Gill;Benjamin, Boben;Chew-Graham, Stephen;Moseley, Carly;Potter, Paula;Winder, Catherine L.;Potts, Catherine;Thornton, Paula;McWhirter, Catriona;Zubair, Mohammed;Pan, Martin;Burns, Alistair;Cruickshank, J. Kennedy;Jayson, Gordon C.;Purandare, Nitin;Wu, Frederick C. W.;Finn, Joe D.;Haselden, John N.;Nicholls, Andrew W.;Wilson, Ian D.;Goodacre, Royston;Kell, Douglas B.
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DOI：
10.1016/j.jpba.2021.113942
发表时间：
2021-02-16
影响因子：
3.4
作者：
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通讯作者：
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影响因子：
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