Authors:	Lerner, Raissa Baker, Dhanwin Schwitter, Claudia Neuhaus, Sarah Hauptmann, Tony Post, Julia M. Kramer, Stefan Bindila, Laura
Title:	Four-dimensional trapped ion mobility spectrometry lipidomics for high throughput clinical profiling of human blood samples
Online publication date:	18-Aug-2023
Year of first publication:	2023
Language:	english
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.
DDC:	610 Medizin 610 Medical sciences
Institution:	Johannes Gutenberg-Universität Mainz
Department:	FB 04 Medizin
Place:	Mainz
ROR:	https://ror.org/023b0x485
DOI:	http://doi.org/10.25358/openscience-9422
Version:	Published version
Publication type:	Zeitschriftenaufsatz
Document type specification:	Scientific article
License:	CC BY
Information on rights of use:	https://creativecommons.org/licenses/by/4.0/
Journal:	Nature Communications 14
Pages or article number:	937
Publisher:	Nature Publishing Group
Publisher place:	London
Issue date:	2023
ISSN:	2041-1723
Publisher DOI:	10.1038/s41467-023-36520-1
Appears in collections:	DFG-491381577-G