Reproducible Determination of High-Density Lipoprotein Proteotypes.

cardiovascular disease clinical proteotype analysis data-independent acquisition (DIA) high-density lipoprotein (HDL) mass spectrometry peptidoforms post-translational modifications spectral library type 2 diabetes

Journal

Journal of proteome research
ISSN: 1535-3907
Titre abrégé: J Proteome Res
Pays: United States
ID NLM: 101128775

Informations de publication

Date de publication:
05 11 2021
Historique:
pubmed: 23 10 2021
medline: 26 2 2022
entrez: 22 10 2021
Statut: ppublish

Résumé

High-density lipoprotein (HDL) is a heterogeneous mixture of blood-circulating multimolecular particles containing many different proteins, lipids, and RNAs. Recent advancements in mass spectrometry-based proteotype analysis show promise for the analysis of proteoforms across large patient cohorts. In order to create the required spectral libraries enabling these data-independent acquisition (DIA) strategies, HDL was isolated from the plasma of more than 300 patients with a multiplicity of physiological HDL states. HDL proteome spectral libraries consisting of 296 protein groups and more than 786 peptidoforms were established, and the performance of the DIA strategy was benchmarked for the detection of HDL proteotype differences between healthy individuals and a cohort of patients suffering from diabetes mellitus type 2 and/or coronary heart disease. Bioinformatic interrogation of the data using the generated spectral libraries showed that the DIA approach enabled robust HDL proteotype determination. HDL peptidoform analysis enabled by using spectral libraries allowed for the identification of post-translational modifications, such as in APOA1, which could affect HDL functionality. From a technical point of view, data analysis further shows that protein and peptide quantities are currently more discriminative between different HDL proteotypes than peptidoforms without further enrichment. Together, DIA-based HDL proteotyping enables the robust digitization of HDL proteotypes as a basis for the analysis of larger clinical cohorts.

Identifiants

pubmed: 34677978
doi: 10.1021/acs.jproteome.1c00429
doi:

Substances chimiques

Lipoproteins, HDL 0
Peptides 0
Proteome 0

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

4974-4984

Auteurs

Sandra Goetze (S)

Institute of Translational Medicine (ITM), Department of Health Sciences and Technology (D-HEST), ETH Zurich, Zurich 8093, Switzerland.
Swiss Multi-Omics Center (SMOC), PHRT-CPAC, ETH Zurich, Zurich 8093, Switzerland.
Swiss Institute of Bioinformatics (SIB), Lausanne 1015, Switzerland.

Kathrin Frey (K)

Institute of Translational Medicine (ITM), Department of Health Sciences and Technology (D-HEST), ETH Zurich, Zurich 8093, Switzerland.

Lucia Rohrer (L)

Institute for Clinical Chemistry, University Hospital Zurich, Zurich 8091, Switzerland.

Silvija Radosavljevic (S)

Institute for Clinical Chemistry, University Hospital Zurich, Zurich 8091, Switzerland.

Jan Krützfeldt (J)

Division of Endocrinology, Diabetes and Clinical Nutrition, University Hospital Zurich, Zurich 8091, Switzerland.

Ulf Landmesser (U)

Department of Cardiology, Charité - Universitätsmedizin Berlin, Berlin 12203, Germany.

Marco Bueter (M)

Department of Surgery and Transplantation, University Hospital Zurich, Zurich 8091, Switzerland.

Patrick G A Pedrioli (PGA)

Institute of Translational Medicine (ITM), Department of Health Sciences and Technology (D-HEST), ETH Zurich, Zurich 8093, Switzerland.
Swiss Multi-Omics Center (SMOC), PHRT-CPAC, ETH Zurich, Zurich 8093, Switzerland.
Swiss Institute of Bioinformatics (SIB), Lausanne 1015, Switzerland.

Arnold von Eckardstein (A)

Institute for Clinical Chemistry, University Hospital Zurich, Zurich 8091, Switzerland.

Bernd Wollscheid (B)

Institute of Translational Medicine (ITM), Department of Health Sciences and Technology (D-HEST), ETH Zurich, Zurich 8093, Switzerland.
Swiss Multi-Omics Center (SMOC), PHRT-CPAC, ETH Zurich, Zurich 8093, Switzerland.
Swiss Institute of Bioinformatics (SIB), Lausanne 1015, Switzerland.

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Classifications MeSH