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Quality Assurance and Quality Control in the Lipidomic Quantitation Using Lipid Class Separation - Mass Spectrometry

Autoři: Holčapek Michal | Wolrab Denise | Chocholoušková Michaela | Jirásko Robert | Peterka Ondřej

Rok: 2019

Druh publikace: ostatní - přednáška nebo poster

Strana od-do: nestránkováno

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Jazyk	Název	Abstrakt	Klíčová slova
eng	Quality Assurance and Quality Control in the Lipidomic Quantitation Using Lipid Class Separation - Mass Spectrometry	Many lipidomic studies report potential disease biomarkers, but there are often difficulties to reproduce these finding in other laboratories or even to translate into the routine clinical use. Reasons behind these problems are rather complex, and it is important to identify key aspects involved in the reproducibility issues of the lipidomic quantitation among different laboratories, different analytical approaches, and during longer period of time. Various factors may play a role, such as the lack of full method validation in line with recommendations of authoritative organizations, such as FDA and EMA, the missing use of quality control samples, problems during pre-analytical phase, etc. We will present examples with the recommended way of analytical validation and the use of quality control samples for high-throughput and large-scale lipidomic quantitation using 2 approaches: hydrophilic interaction liquid chromatography – mass spectrometry (HILIC/MS) and ultrahigh-performance supercritical fluid chromatography - mass spectrometry (UHPSFC/MS). The first step is careful optimization of the whole methodology including preanalytical phase, sample extraction, MS analysis, data processing, and statistical evaluation. The typical steps included in the analytical method validation will be presented and illustrated on examples of HILIC/MS and UHPSFC/MS. The optimized and validated methods are then applied for the reference material SRM 1950 human plasma from NIST, and concentrations are compared with published data in the literature [1, 2]. The final step is the application to real clinical cohorts.

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