Lipid analysis is a powerful tool that can elucidate the pathogenic roles of lipids in metabolic diseases, and facilitate the development of potential biomarkers. Lipid analysis by large-scale lipidomics requires a high-speed and high-throughput analytical platform. In the present study, a high-speed analytical method for lipid analysis using nanoflow ultrahigh-performance liquid chromatography-electrospray ionisation-tandem mass spectrometry (nUHPLC-ESI-MS/MS) was optimised by investigating the effects of column flow rate, pump flow rate, dwell time, initial binary mobile phase composition, and gradient duration on the separation efficiency of standard lipid mixtures. The minimum gradient time for high-speed lipid separation was determined by examining the time-based separation efficiency and spectral overlap of isobaric lipid species during selected reaction monitoring-based quantification of sphingomyelin and a second isotope of phosphatidylcholine, which differ in molecular weight by only 1 Da. Finally, the optimised nUHPLC-ESI-MS/MS method was applied to analyse 200 plasma samples from patients with liver, gastric, lung, and colorectal cancer to evaluate its performance by measuring previously identified candidate lipid biomarkers. About 73% of the reported marker candidates (6 out of 7 in liver, 5/9 in gastric, 4/6 in lung, and 6/7 in colorectal cancer) could be assigned using the optimised method, supporting its use for high-throughput lipid analysis.
|Journal||Journal of Chromatography B: Analytical Technologies in the Biomedical and Life Sciences|
|Publication status||Published - 2021 Jun 15|
Bibliographical noteFunding Information:
This study was supported by the grant (NRF-2018R1A2A1A05019794 and NRF-2021R1A2C2003171 in part) of the Ministry of Science, ICT & Future Planning through the National Research Foundation (NRF) of Korea.
The biospecimens for this study were provided by the Ajou University Human Bio-Resource Bank(AHBB), a member of Korea Biobank Network. This study was supported by the grant (NRF-2018R1A2A1A05019794 and NRF-2021R1A2C2003171 in part) of the Ministry of Science, ICT & Future Planning through the National Research Foundation (NRF) of Korea.
© 2021 Elsevier B.V.
All Science Journal Classification (ASJC) codes
- Analytical Chemistry
- Clinical Biochemistry
- Cell Biology