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Status |
Public on Aug 29, 2023 |
Title |
A Proteomic Atlas of Atherosclerosis: The Contribution of Proteoglycans to Sex Differences, Plaque Phenotypes and Outcomes |
Organism |
Homo sapiens |
Experiment type |
Expression profiling by high throughput sequencing
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Summary |
Background. Using proteomics, we aimed to reveal molecular types of humanatherosclerotic lesions and study their associations with histology, imaging andcardiovascular outcomes. Methods. 219 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 and myeloperoxidase, while 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 four 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 55 patient groups with distinct outcomes, identifying subgroups of male and female patients with elevated risk of future cardiovascular events.
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Overall design |
Visium for formalin-fixed paraffin-embedded (FFPE) spatial gene expression slide and reagent kit was used according to manufacturer instructions (PN: 1000338; 10X Genomics). Each capture area (6.5 x 6.5 mm2) contains 5,000 barcoded spots that are 55 μm in diameter (100 μm center-to-center distance) providing an average resolution of 1 to 10 cells. A 5μm tissue section from one carotid plaque sample was placed onto one capture area of a Visium Spatial Gene Expression slide. Two carotid plaque samples were selected from Asymptomatic male patients who undergone carotid endrarterectomy for spatial RNA-seq. Deparaffinization, DAPI immunofluorescence staining, image acquisition and decrosslinking were performed as specified in the Visium Spatial Gene Expression for FFPE – Deparaffinization, Decrosslinking, Immunofluorescence Staining & Imaging protocol (CG000410) and performed at the Core Facility Imaging, Medical University of Vienna. Fluorescent images were acquired with an Olympus IX83 microscope equipped with a Hamamathsu Orca FLash camera for fluorescence image capture. and parameters following those specified in the Visium Spatial Gene Expression Reagent Kits for FFPE User Guide sequencing instructions (read 1: 28 cycles; i7 index read: 10 cycles; i5 index read: 10 cycles; and read 2: 50 cycles) yielding 149 million sequenced reads. The FASTQ files and the manually aligned histology images were analyzed with Space Ranger 1.3.1 and the human probeset provided by 10X genomics (Visium Human Transcriptome Probe Set v1.0 GRCh38-2020-A). Visualization of spatial cluster output from Space Ranger as well as differential gene expression analysis to determine cluster- pecific up- or downregulated genes was performed on Loupe Browser 6.0.0 (10X Genomics).
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Web link |
https://pubmed.ncbi.nlm.nih.gov/37646165/
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Contributor(s) |
Theofilatos K, Stojkovic S, Hasman M, van der Laan S, Baig F, Barallobre-Barreiro J, Schmidt L, Yin S, Yin X, Burnap S, Singh B, Popham J, Harkot O, Kampf S, Nackenhorst MC, Strassl A, Loewe C, Demyanets S, Neumayer C, Huber K, Pasterkamp G, Wojta J, Myr M |
Citation(s) |
37646165 |
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Submission date |
Aug 21, 2023 |
Last update date |
Jan 20, 2024 |
Contact name |
Konstantinos Theofilatos |
E-mail(s) |
konstantinos.theofilatos@kcl.ac.uk
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Organization name |
King's CollegeLondon
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Street address |
125 Coldharbour Lane
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City |
London |
ZIP/Postal code |
SE5 9NU |
Country |
United Kingdom |
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Platforms (1) |
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Samples (2) |
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Relations |
BioProject |
PRJNA1007728 |
Supplementary file |
Size |
Download |
File type/resource |
GSE241346_RAW.tar |
13.4 Mb |
(http)(custom) |
TAR (of CSV, JPG, JSON, MTX, PNG, TSV) |
SRA Run Selector |
Raw data are available in SRA |
Processed data provided as supplementary file |
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