Four-dimensional trapped ion mobility spectrometry lipidomics for high throughput clinical profiling of human blood samples

Raissa Lerner, Dhanwin Baker, Claudia Schwitter, Sarah Neuhaus, Tony Hauptmann, Julia M. Post, Stefan Kramer and Laura Bindila ()
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Raissa Lerner: University Medical Center
Dhanwin Baker: University Medical Center
Claudia Schwitter: University Medical Center
Sarah Neuhaus: University Medical Center
Tony Hauptmann: Johannes Gutenberg University Mainz
Julia M. Post: University Medical Center
Stefan Kramer: Johannes Gutenberg University Mainz
Laura Bindila: University Medical Center

Nature Communications, 2023, vol. 14, issue 1, 1-20

Abstract: Abstract Lipidomics encompassing automated lipid extraction, a four-dimensional (4D) feature selection strategy for confident lipid annotation as well as reproducible and cross-validated quantification can expedite clinical profiling. Here, we determine 4D descriptors (mass to charge, retention time, collision cross section, and fragmentation spectra) of 200 lipid standards and 493 lipids from reference plasma via trapped ion mobility mass spectrometry to enable the implementation of stringent criteria for lipid annotation. We use 4D lipidomics to confidently annotate 370 lipids in reference plasma samples and 364 lipids in serum samples, and reproducibly quantify 359 lipids using level-3 internal standards. We show the utility of our 4D lipidomics workflow for high-throughput applications by reliable profiling of intra-individual lipidome phenotypes in plasma, serum, whole blood, venous and finger-prick dried blood spots.

Date: 2023
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DOI: 10.1038/s41467-023-36520-1

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