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Analysis of fragmented oxidized phosphatidylcholines in human plasma using mass spectrometry: Comparison with immune assays.

Maria Philippova | Olga V Oskolkova | Wolfgang Bicker | Andreas W Schoenenberger | Therese J Resink | Paul Erne | Valery N Bochkov
Free radical biology & medicine | 2019

Circulating oxidized phospholipids are increasingly recognized as biomarkers of atherosclerosis. Clinical association studies have been mainly performed using an immune assay based on monoclonal antibody E06, which recognizes a variety of molecular species of oxidized phosphatidylcholine (OxPC) in lipoproteins, cell membranes or covalently bound to plasma proteins. Accumulating evidence shows that individual molecular species of OxPC demonstrate different biological activities and have different half-life times. Therefore, it is likely that certain molecular species can be associated with pathology more strongly than others. This hypothesis can only be tested using LC-MS/MS allowing quantification of individual molecular species of OxPCs. In order to ensure that laborious LC-MS/MS methods do not simply replicate the results of a technically simpler E06-OxPCs assay, we have performed relative quantification of 8 truncated molecular species of OxPCs in plasma of 132 probands and compared the data with the results of the E06-OxPCs and OxLDL assays. We have found a strong correlation between individual molecular species of OxPCs but only a weak correlation of LC-MS/MS-OxPCs data with the E06-OxPCs assay and no correlation with the OxLDL assay. Furthermore, in contrast to the results of E06-OxPCs or OxLDL assays, 7 out of 8 OxPC species were associated with hypertension. The data suggest that the results of the LC-MS/MS-OxPCs assay do not replicate the results of two ELISA-based lipid oxidation tests and therefore may produce additional diagnostic information. These findings necessitate development of simplified mass spectrometric procedures for high-throughput and affordable analysis of selected molecular species of OxPCs.

Pubmed ID: 31141712

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THIS RESOURCE IS NO LONGER IN SERVICE, documented on February 1st, 2022. Software application for genetic analysis of classical biometric traits like blood pressure or height that are caused by a combination of polygenic inheritance and complex environmental forces. (entry from Genetic Analysis Software)

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