Prediction of coronary artery disease using urinary proteomics.
Atherosclerosis
Collagen turnover
Coronary artery diseases
Proteomics
Urine
Journal
European journal of preventive cardiology
ISSN: 2047-4881
Titre abrégé: Eur J Prev Cardiol
Pays: England
ID NLM: 101564430
Informations de publication
Date de publication:
10 10 2023
10 10 2023
Historique:
received:
12
01
2023
revised:
13
03
2023
accepted:
20
03
2023
medline:
23
10
2023
pubmed:
22
3
2023
entrez:
21
3
2023
Statut:
ppublish
Résumé
Coronary artery disease (CAD) is multifactorial, caused by complex pathophysiology, and contributes to a high burden of mortality worldwide. Urinary proteomic analyses may help to identify predictive biomarkers and provide insights into the pathogenesis of CAD. Urinary proteome was analysed in 965 participants using capillary electrophoresis coupled with mass spectrometry. A proteomic classifier was developed in a discovery cohort with 36 individuals with CAD and 36 matched controls using the support vector machine. The classifier was tested in a validation cohort with 115 individuals who progressed to CAD and 778 controls and compared with two previously developed CAD-associated classifiers, CAD238 and ACSP75. The Framingham and SCORE2 risk scores were available in 737 participants. Bioinformatic analysis was performed based on the CAD-associated peptides. The novel proteomic classifier was comprised of 160 urinary peptides, mainly related to collagen turnover, lipid metabolism, and inflammation. In the validation cohort, the classifier provided an area under the receiver operating characteristic curve (AUC) of 0.82 [95% confidence interval (CI): 0.78-0.87] for the CAD prediction in 8 years, superior to CAD238 (AUC: 0.71, 95% CI: 0.66-0.77) and ACSP75 (AUC: 0.53 and 95% CI: 0.47-0.60). On top of CAD238 and ACSP75, the addition of the novel classifier improved the AUC to 0.84 (95% CI: 0.80-0.89). In a multivariable Cox model, a 1-SD increment in the novel classifier was associated with a higher risk of CAD (HR: 1.54, 95% CI: 1.26-1.89, P < 0.0001). The new classifier further improved the risk reclassification of CAD on top of the Framingham or SCORE2 risk scores (net reclassification index: 0.61, 95% CI: 0.25-0.95, P = 0.001; 0.64, 95% CI: 0.28-0.98, P = 0.001, correspondingly). A novel urinary proteomic classifier related to collagen metabolism, lipids, and inflammation showed potential for the risk prediction of CAD. Urinary proteome provides an alternative approach to personalized prevention. A biomarker that can predict coronary artery disease (CAD) is urgently in need. We developed and validated a urinary proteomic classifier for the prediction of CAD. The proteomic classifier involved in atherosclerosis improved the risk reclassification on top of the clinical risk score.
Autres résumés
Type: plain-language-summary
(eng)
A biomarker that can predict coronary artery disease (CAD) is urgently in need. We developed and validated a urinary proteomic classifier for the prediction of CAD. The proteomic classifier involved in atherosclerosis improved the risk reclassification on top of the clinical risk score.
Identifiants
pubmed: 36943304
pii: 7082480
doi: 10.1093/eurjpc/zwad087
doi:
Substances chimiques
Proteome
0
Biomarkers
0
Peptides
0
Collagen
9007-34-5
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
1537-1546Commentaires et corrections
Type : CommentIn
Informations de copyright
© The Author(s) 2023. Published by Oxford University Press on behalf of the European Society of Cardiology.
Déclaration de conflit d'intérêts
Conflict of interest: The authors have no conflicts of interest to declare.