Shared reference materials harmonize lipidomics across MS-based detection platforms and laboratories
Autor: | Bo Burla, Jayashree Selvalatchmanan, Markus R. Wenk, Peter J. Meikle, Alexander Triebl, Federico Torta, Natalie A. Mellet, Sock Hwee Tan, Jeongah Oh, Mark Y. Chan |
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Jazyk: | angličtina |
Rok vydání: | 2020 |
Předmět: |
0301 basic medicine
Normalization (statistics) Adult Male Computer science Sample (material) Medical laboratory QD415-436 030204 cardiovascular system & hematology computer.software_genre Biochemistry lipids 03 medical and health sciences Young Adult 0302 clinical medicine Endocrinology Lipidomics Methods Humans liquid chromatography Sample preparation plasma mass spectrometry quantitation business.industry Cell Biology Shotgun lipidomics Reference Standards National Institute of Standards and Technology standard reference material 1950 Healthy Volunteers 030104 developmental biology Reference sample harmonization NIST Female Data mining business computer |
Zdroj: | Journal of Lipid Research, Vol 61, Iss 1, Pp 105-115 (2020) Journal of Lipid Research |
ISSN: | 0022-2275 |
Popis: | Quantitative MS of human plasma lipids is a promising technology for translation into clinical applications. Current MS-based lipidomic methods rely on either direct infusion (DI) or chromatographic lipid separation methods (including reversed phase and hydrophilic interaction LC). However, the use of lipid markers in laboratory medicine is limited by the lack of reference values, largely because of considerable differences in the concentrations measured by different laboratories worldwide. These inconsistencies can be explained by the use of different sample preparation protocols, method-specific calibration procedures, and other experimental and data-reporting parameters, even when using identical starting materials. Here, we systematically investigated the roles of some of these variables in multiple approaches to lipid analysis of plasma samples from healthy adults by considering: 1) different sample introduction methods (separation vs. DI methods); 2) different MS instruments; and 3) between-laboratory differences in comparable analytical platforms. Each of these experimental variables resulted in different quantitative results, even with the inclusion of isotope-labeled internal standards for individual lipid classes. We demonstrated that appropriate normalization to commonly available reference samples (i.e., "shared references") can largely correct for these systematic method-specific quantitative biases. Thus, to harmonize data in the field of lipidomics, in-house long-term references should be complemented by a commonly available shared reference sample, such as NIST SRM 1950, in the case of human plasma. |
Databáze: | OpenAIRE |
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