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通过脂质组学策略鉴定潜在的溶血磷脂酰胆碱标志物,用于估算干血斑中的红细胞压积。

Identification of potential sphingomyelin markers for the estimation of hematocrit in dried blood spots via a lipidomic strategy.

机构信息

School of Pharmacy, College of Medicine, National Taiwan University, Taiwan; The Metabolomics Core Laboratory, Center of Genomic Medicine, National Taiwan University, Taiwan.

Graduate Institute of Clinical Pharmacy, College of Medicine, National Taiwan University, Taipei, Taiwan; Department of Pharmacy, National Taiwan University Hospital, Taiwan.

出版信息

Anal Chim Acta. 2018 Mar 20;1003:34-41. doi: 10.1016/j.aca.2017.11.041. Epub 2017 Nov 23.

Abstract

The dried blood spot (DBS) strategy is a convenient and minimally invasive approach to blood sampling. Due to its various advantages, this sampling technique has drawn significant attention in recent years. Hematocrit (HCT)-associated bias is one of the main obstacles that hinder wider DBS application in clinical practice. An accurate HCT estimation method could help calibrate HCT-associated bias and improve the quantification accuracy. This study used a lipidomics profiling strategy to identify HCT estimation markers using liquid chromatography-electrospray ionization-mass spectrometry (LC-ESI-MS), which provided advantages including the potential for the simultaneous measurements of target drug and HCT values. Three sphingomyelins (SMs), specifically SM 44:1, SM 44:2, and SM 44:3, were identified as potential HCT estimation markers. The proposed estimation markers were applied to 54 DBS samples collected from two sets of patients. The analytical results revealed that the estimation errors for all of the HCT values were less than 20%, which demonstrated the feasibility of using the proposed markers to estimate the HCT values for the DBS samples. We suggest that the proposed HCT markers could provide a new strategy for HCT estimation with higher convenience using an LC-ESI-MS platform, which could contribute to wider DBS applications in clinical practice. We also demonstrated that lipidomics is a promising strategy for the discovery of HCT estimation markers in DBS samples.

摘要

干血斑(DBS)策略是一种方便且微创的采血方法。由于其各种优势,这种采样技术近年来引起了广泛关注。与血细胞比容(HCT)相关的偏倚是阻碍 DBS 在临床实践中更广泛应用的主要障碍之一。准确的 HCT 估计方法可以帮助校准 HCT 相关的偏差,提高定量准确性。本研究使用脂质组学分析策略,通过液相色谱-电喷雾电离-质谱(LC-ESI-MS)来识别 HCT 估计标志物,该方法具有同时测量目标药物和 HCT 值的潜力。鉴定出三种鞘磷脂(SM),即 SM 44:1、SM 44:2 和 SM 44:3,作为潜在的 HCT 估计标志物。将所提出的估计标志物应用于从两组患者采集的 54 个 DBS 样本中。分析结果表明,所有 HCT 值的估计误差均小于 20%,这表明使用所提出的标志物来估计 DBS 样本的 HCT 值是可行的。我们建议,所提出的 HCT 标志物可以提供一种使用 LC-ESI-MS 平台进行更高便利性 HCT 估计的新策略,这可能有助于 DBS 在临床实践中的更广泛应用。我们还证明了脂质组学是发现 DBS 样本中 HCT 估计标志物的一种很有前途的策略。

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