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  • Title: Simultaneous profiling and quantification of 25 eicosanoids in human serum by ultrahigh-performance liquid chromatography coupled to tandem mass spectrometry.
    Author: Lu Y, Mai Z, Zhou H, Guan W, Wu S, Zou H, Shen M, Zhan Y, Ye F, Qiu M, Shen L, Zhao B, Yang Z.
    Journal: Anal Bioanal Chem; 2022 Dec; 414(29-30):8233-8244. PubMed ID: 36344666.
    Abstract:
    The eicosanoid metabolic pathway is responsible for mediating the production of various inflammatory factors that are closely related to the development and resolution of inflammation. In biological matrices, the major quantifying obstacles were shown to be the oxidation and low quantities of eicosanoids and their metabolites. This study aimed to develop a reliable, sensitive ultrahigh-performance liquid chromatography coupled to a tandem mass spectrometry (UPLC-MS/MS) method to quantify eicosanoids in human serum. Solid-phase extraction (SPE) was used for sample preparation. The approach employed continuous ionization polarity switching. The target eicosanoids showed good linearity over the investigated concentration range (r2 > 0.99). The recovery rates were over 64.5%, and the matrix effects ranged from 73.0 to 128.0%. The limits of quantification were 0.048 ~ 0.44 ng/mL. For the broad concentration range, the CV % for accuracy and precision were less than ± 20%. We successfully applied this method to rapidly analyse 74 serum samples from severe influenza pneumonia, severe bacterial pneumonia and healthy individuals. Eicosanoid-related metabolite concentrations were quantified within a range similar to those of previously published articles. Compared to healthy individuals, our application found that 20-HETE, 14,15-EET and 11,12-EET were upregulated in severe influenza pneumonia patients, while LTB4 was downregulated. 8-HETE and 5-HETE were upregulated in severe bacterial pneumonia patients, while LTE4 was downregulated. This approach provides a means for monitoring the low quantities of eicosanoids in biological matrices, and our finding that different characteristic metabolite profiles may help discriminate the induction of severe pneumonia patients.
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