Proteomic Atlas of Atherosclerosis: The Contribution of Proteoglycans to Sex Differences, Plaque Phenotypes, and Outcomes.

atherosclerosis inflammation machine learning neutrophils proteoglycans proteomics smooth muscle cells

Journal

Circulation research
ISSN: 1524-4571
Titre abrégé: Circ Res
Pays: United States
ID NLM: 0047103

Informations de publication

Date de publication:
15 09 2023
Historique:
medline: 18 9 2023
pubmed: 30 8 2023
entrez: 30 8 2023
Statut: ppublish

Résumé

Using proteomics, we aimed to reveal molecular types of human atherosclerotic lesions and study their associations with histology, imaging, and cardiovascular outcomes. Two hundred nineteen carotid endarterectomy samples were procured from 120 patients. A sequential protein extraction protocol was employed in conjunction with multiplexed, discovery proteomics. To focus on extracellular proteins, parallel reaction monitoring was employed for targeted proteomics. Proteomic signatures were integrated with bulk, single-cell, and spatial RNA-sequencing data, and validated in 200 patients from the Athero-Express Biobank study. This extensive proteomics analysis identified plaque inflammation and calcification signatures, which were inversely correlated and validated using targeted proteomics. The inflammation signature was characterized by the presence of neutrophil-derived proteins, such as S100A8/9 (calprotectin) and myeloperoxidase, whereas the calcification signature included fetuin-A, osteopontin, and gamma-carboxylated proteins. The proteomics data also revealed sex differences in atherosclerosis, with large-aggregating proteoglycans versican and aggrecan being more abundant in females and exhibiting an inverse correlation with estradiol levels. The integration of RNA-sequencing data attributed the inflammation signature predominantly to neutrophils and macrophages, and the calcification and sex signatures to smooth muscle cells, except for certain plasma proteins that were not expressed but retained in plaques, such as fetuin-A. Dimensionality reduction and machine learning techniques were applied to identify 4 distinct plaque phenotypes based on proteomics data. A protein signature of 4 key proteins (calponin, protein C, serpin H1, and versican) predicted future cardiovascular mortality with an area under the curve of 75% and 67.5% in the discovery and validation cohort, respectively, surpassing the prognostic performance of imaging and histology. Plaque proteomics redefined clinically relevant patient groups with distinct outcomes, identifying subgroups of male and female patients with elevated risk of future cardiovascular events.

Sections du résumé

BACKGROUND
Using proteomics, we aimed to reveal molecular types of human atherosclerotic lesions and study their associations with histology, imaging, and cardiovascular outcomes.
METHODS
Two hundred nineteen carotid endarterectomy samples were procured from 120 patients. A sequential protein extraction protocol was employed in conjunction with multiplexed, discovery proteomics. To focus on extracellular proteins, parallel reaction monitoring was employed for targeted proteomics. Proteomic signatures were integrated with bulk, single-cell, and spatial RNA-sequencing data, and validated in 200 patients from the Athero-Express Biobank study.
RESULTS
This extensive proteomics analysis identified plaque inflammation and calcification signatures, which were inversely correlated and validated using targeted proteomics. The inflammation signature was characterized by the presence of neutrophil-derived proteins, such as S100A8/9 (calprotectin) and myeloperoxidase, whereas the calcification signature included fetuin-A, osteopontin, and gamma-carboxylated proteins. The proteomics data also revealed sex differences in atherosclerosis, with large-aggregating proteoglycans versican and aggrecan being more abundant in females and exhibiting an inverse correlation with estradiol levels. The integration of RNA-sequencing data attributed the inflammation signature predominantly to neutrophils and macrophages, and the calcification and sex signatures to smooth muscle cells, except for certain plasma proteins that were not expressed but retained in plaques, such as fetuin-A. Dimensionality reduction and machine learning techniques were applied to identify 4 distinct plaque phenotypes based on proteomics data. A protein signature of 4 key proteins (calponin, protein C, serpin H1, and versican) predicted future cardiovascular mortality with an area under the curve of 75% and 67.5% in the discovery and validation cohort, respectively, surpassing the prognostic performance of imaging and histology.
CONCLUSIONS
Plaque proteomics redefined clinically relevant patient groups with distinct outcomes, identifying subgroups of male and female patients with elevated risk of future cardiovascular events.

Identifiants

pubmed: 37646165
doi: 10.1161/CIRCRESAHA.123.322590
pmc: PMC10498884
doi:

Substances chimiques

Versicans 126968-45-4
alpha-2-HS-Glycoprotein 0

Types de publication

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

Langues

eng

Sous-ensembles de citation

IM

Pagination

542-558

Subventions

Organisme : British Heart Foundation
ID : CH/16/3/32406
Pays : United Kingdom
Organisme : British Heart Foundation
ID : RG/F/21/110053
Pays : United Kingdom
Organisme : British Heart Foundation
ID : PG/20/10387
Pays : United Kingdom
Organisme : British Heart Foundation
ID : FS/19/33/34328
Pays : United Kingdom

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Auteurs

Konstantinos Theofilatos (K)

King's British Heart Foundation Centre, Kings College London, United Kingdom (K.T., M.H., F.B., J.B.B., L.E.S., S.Y., X.Y., S.B., B.S., J.P., M.M.).

Stefan Stojkovic (S)

Division of Cardiology, Department of Internal Medicine II (S.S., O.H., C.H., J.W., M.M.), Medical University of Vienna, Austria.

Maria Hasman (M)

King's British Heart Foundation Centre, Kings College London, United Kingdom (K.T., M.H., F.B., J.B.B., L.E.S., S.Y., X.Y., S.B., B.S., J.P., M.M.).

Sander W van der Laan (SW)

Central Diagnostics Laboratory, Division Laboratories, Pharmacy, and Biomedical Genetics, University Medical Center Utrecht, Utrecht University, the Netherlands (S.W.v.d.L., G.P.).

Ferheen Baig (F)

King's British Heart Foundation Centre, Kings College London, United Kingdom (K.T., M.H., F.B., J.B.B., L.E.S., S.Y., X.Y., S.B., B.S., J.P., M.M.).

Javier Barallobre-Barreiro (J)

King's British Heart Foundation Centre, Kings College London, United Kingdom (K.T., M.H., F.B., J.B.B., L.E.S., S.Y., X.Y., S.B., B.S., J.P., M.M.).

Lukas Emanuel Schmidt (LE)

King's British Heart Foundation Centre, Kings College London, United Kingdom (K.T., M.H., F.B., J.B.B., L.E.S., S.Y., X.Y., S.B., B.S., J.P., M.M.).

Siqi Yin (S)

King's British Heart Foundation Centre, Kings College London, United Kingdom (K.T., M.H., F.B., J.B.B., L.E.S., S.Y., X.Y., S.B., B.S., J.P., M.M.).

Xiaoke Yin (X)

King's British Heart Foundation Centre, Kings College London, United Kingdom (K.T., M.H., F.B., J.B.B., L.E.S., S.Y., X.Y., S.B., B.S., J.P., M.M.).

Sean Burnap (S)

King's British Heart Foundation Centre, Kings College London, United Kingdom (K.T., M.H., F.B., J.B.B., L.E.S., S.Y., X.Y., S.B., B.S., J.P., M.M.).

Bhawana Singh (B)

King's British Heart Foundation Centre, Kings College London, United Kingdom (K.T., M.H., F.B., J.B.B., L.E.S., S.Y., X.Y., S.B., B.S., J.P., M.M.).

Jude Popham (J)

King's British Heart Foundation Centre, Kings College London, United Kingdom (K.T., M.H., F.B., J.B.B., L.E.S., S.Y., X.Y., S.B., B.S., J.P., M.M.).

Olesya Harkot (O)

Division of Cardiology, Department of Internal Medicine II (S.S., O.H., C.H., J.W., M.M.), Medical University of Vienna, Austria.

Stephanie Kampf (S)

Division of Vascular Surgery, Department of Surgery (S.K., C.N.), Medical University of Vienna, Austria.

Maja Carina Nackenhorst (MC)

Department of Pathology (M.C.N.), Medical University of Vienna, Austria.

Andreas Strassl (A)

Division of Cardiovascular and Interventional Radiology, Department of Biomedical Imaging and Image-Guided Therapy (A.S., C.L.), Medical University of Vienna, Austria.

Christian Loewe (C)

Division of Cardiovascular and Interventional Radiology, Department of Biomedical Imaging and Image-Guided Therapy (A.S., C.L.), Medical University of Vienna, Austria.

Svitlana Demyanets (S)

Department of Laboratory Medicine (S.D.), Medical University of Vienna, Austria.

Christoph Neumayer (C)

Division of Vascular Surgery, Department of Surgery (S.K., C.N.), Medical University of Vienna, Austria.

Martin Bilban (M)

Core Facilities (M.B.), Medical University of Vienna, Austria.

Christian Hengstenberg (C)

Division of Cardiology, Department of Internal Medicine II (S.S., O.H., C.H., J.W., M.M.), Medical University of Vienna, Austria.

Kurt Huber (K)

Third Medical Department, Wilhelminenspital, and Sigmund Freud University, Medical Faculty, Vienna, Austria (K.H.).

Gerard Pasterkamp (G)

Central Diagnostics Laboratory, Division Laboratories, Pharmacy, and Biomedical Genetics, University Medical Center Utrecht, Utrecht University, the Netherlands (S.W.v.d.L., G.P.).

Johann Wojta (J)

Division of Cardiology, Department of Internal Medicine II (S.S., O.H., C.H., J.W., M.M.), Medical University of Vienna, Austria.
Ludwig Boltzmann Institute for Cardiovascular Research, Vienna, Austria (J.W.).

Manuel Mayr (M)

King's British Heart Foundation Centre, Kings College London, United Kingdom (K.T., M.H., F.B., J.B.B., L.E.S., S.Y., X.Y., S.B., B.S., J.P., M.M.).
Division of Cardiology, Department of Internal Medicine II (S.S., O.H., C.H., J.W., M.M.), Medical University of Vienna, Austria.

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