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

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, collisi...

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Detalles Bibliográficos
Autores principales: Lerner, Raissa, Baker, Dhanwin, Schwitter, Claudia, Neuhaus, Sarah, Hauptmann, Tony, Post, Julia M., Kramer, Stefan, Bindila, Laura
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9941096/
https://www.ncbi.nlm.nih.gov/pubmed/36806650
http://dx.doi.org/10.1038/s41467-023-36520-1
Descripción
Sumario: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.