Cross-Laboratory Standardization of Preclinical Lipidomics Using Differential Mobility Spectrometry and Multiple Reaction Monitoring

Mohan Ghorasaini, Yassene Mohammed, Jerzy Adamski, Lisa Bettcher, John A. Bowden, Matias Cabruja, Kévin Contrepois, Mathew Ellenberger, Bharat Gajera, Mark Haid, Daniel Hornburg, Christie Hunter, Christina M. Jones, Theo Klein, Oleg Mayboroda, Mina Mirzaian, Ruin Moaddel, Luigi Ferrucci, Jacqueline Lovett, Kenneth NazirMackenzie Pearson, Baljit K. Ubhi, Daniel Raftery, Fabien Riols, Rebekah Sayers, Eric J.G. Sijbrands, Michael P. Snyder, Baolong Su, Vidya Velagapudi, Kevin J. Williams, Yolanda B. De Rijke, Martin Giera*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

28 Citations (Scopus)
17 Downloads (Pure)


Modern biomarker and translational research as well as personalized health care studies rely heavily on powerful omics' technologies, including metabolomics and lipidomics. However, to translate metabolomics and lipidomics discoveries into a high-throughput clinical setting, standardization is of utmost importance. Here, we compared and benchmarked a quantitative lipidomics platform. The employed Lipidyzer platform is based on lipid class separation by means of differential mobility spectrometry with subsequent multiple reaction monitoring. Quantitation is achieved by the use of 54 deuterated internal standards and an automated informatics approach. We investigated the platform performance across nine laboratories using NIST SRM 1950-Metabolites in Frozen Human Plasma, and three NIST Candidate Reference Materials 8231-Frozen Human Plasma Suite for Metabolomics (high triglyceride, diabetic, and African-American plasma). In addition, we comparatively analyzed 59 plasma samples from individuals with familial hypercholesterolemia from a clinical cohort study. We provide evidence that the more practical methyl-tert-butyl ether extraction outperforms the classic Bligh and Dyer approach and compare our results with two previously published ring trials. In summary, we present standardized lipidomics protocols, allowing for the highly reproducible analysis of several hundred human plasma lipids, and present detailed molecular information for potentially disease relevant and ethnicity-related materials.

Original languageEnglish
Pages (from-to)16369-16378
Number of pages10
JournalAnalytical Chemistry
Issue number49
Publication statusPublished - 14 Dec 2021

Bibliographical note

Funding Information:
The authors would like to acknowledge Tracy Schock, Dan Bearden, and Yamil Simón-Manso for their help with material design and procurement. Niek Blomberg is acknowledged for assistance with Lipidyzer analysis. Part of the TOC graphic was created with . D.R. thanks the NIH (grants P30CA015704 and S10OD021562) for financial support. Mohan Ghorasaini (M.G.) is an early-stage researcher supported by the H2020 ITN consortium ArthritisHeal (#812890). Martin Giera (M.G.) was partially supported by the NWO XOmics project #184.034.019. This research was supported in part by the Intramural Research Program of the National Institute on Aging, NIH. This research was supported in part by NIH grants 5U54HG010426-03 (M.P.S.) and 1U2CCA233311-01 (M.P.S.). The FIMM Metabolomics Unit was supported by HiLIFE and Biocenter Finland.

Publisher Copyright:
© 2021 The Authors. Published by American Chemical Society.


Dive into the research topics of 'Cross-Laboratory Standardization of Preclinical Lipidomics Using Differential Mobility Spectrometry and Multiple Reaction Monitoring'. Together they form a unique fingerprint.

Cite this