ArticleEuropean heart journal2022
Targeted proteomics improves cardiovascular risk prediction in secondary prevention.
Article in European heart journal, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 66 papers, 2 of them syntheses that pooled it.
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Who cites it
66 citing papers in PubMed, 2 syntheses or guidelines pooled it, 125 citations in OpenAlex.
- Candidate Biomarkers Linking Periodontitis with Atherosclerotic and Related Cardiovascular Phenotypes: A Systematic Review Focused on Sex-Specific Evidence.International journal of molecular sciences · 2026Pooled it
- Growth differentiation factor 15 and cardiovascular risk: individual patient meta-analysis.European heart journal · 2023Pooled it
- Rationale and design of Dongzong CArdIovascuLar Bio-imaging RegistrY (DAILY) study: Bridging multiomics, imaging and cardiovascular disease.American journal of preventive cardiology · 2026Article
- Systolic blood pressure variability as a risk factor for abdominal aortic aneurysm: a prospective cohort study with genomic and proteomic profiling.European journal of epidemiology · 2026Article
- Multi-omics-driven precision medicine.iMeta · 2026Review
- ProLM: a plasma proteomics pretrained model for the general population.Nature communications · 2026Article
- Molecular damage associated with ageing drives inflammation in cardiovascular disease.Nature reviews. Cardiology · 2026Review
- Residual cardiovascular risk in coronary artery disease: from pathophysiology to established and novel therapies.Nature reviews. Cardiology · 2026Review
- Lipoprotein(a)-associated proteomic signature predicts cardiovascular disease in young adults.The Journal of clinical investigation · 2026Observational
- Enhanced Prediction of Peripheral Artery Disease Using Plasma Proteomics Among Individuals Without Diabetes.Journal of the American Heart Association · 2026Article
- Unraveling Atherosclerosis through Multi-omics: Systematic Insights into the Unique Applications and Clinical Perspectives.Current atherosclerosis reports · 2026Review
- Plasma Proteins Associated With Psychosocial Factors and Heart Disease: The Jackson Heart Study.Arteriosclerosis, thrombosis, and vascular biology · 2026Article
- Natural language processing of biomedical text to map and prioritize protein-disease associations in HFpEF.Computers in biology and medicine · 2026Article
- Clonal Hematopoiesis in Cardiovascular Risk: Focus on Inflammatory Mechanisms.Journal of clinical medicine · 2026Review
- Routine inflammatory indices modify clonal hematopoiesis-related prognostic risk in patients undergoing percutaneous coronary intervention: a real-world cohort study.BMC medicine · 2026Article
- From Exposure to Atherosclerosis: Mechanistic Insights into Phthalate-Driven Ischemic Heart Disease and Prevention Strategies.Life (Basel, Switzerland) · 2026Review
- Integrative metabolomics and proteomics reveal early cardiovascular risk signatures in PCOS female offspring.Journal of ovarian research · 2026Article
- Clinical subgroup-stratified plasma proteomic signatures improve risk prediction for myocardial infarction: SCORE2-Pro.Cardiovascular diabetology · 2026Article
- Precision medicine and personalized nursing in cardiovascular disease: clinical applications and frontier developments.Frontiers in cardiovascular medicine · 2026Review
- Article
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Authors and funding
16 authors at 4 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
aimsCurrent risk scores do not accurately identify patients at highest risk of recurrent atherosclerotic cardiovascular disease (ASCVD) in need of more intensive therapeutic interventions. Advances in high-throughput plasma proteomics, analysed with machine learning techniques, may offer new opportunities to further improve risk stratification in these patients. METHODS AND
resultsTargeted plasma proteomics was performed in two secondary prevention cohorts: the Second Manifestations of ARTerial disease (SMART) cohort (n = 870) and the Athero-Express cohort (n = 700). The primary outcome was recurrent ASCVD (acute myocardial infarction, ischaemic stroke, and cardiovascular death). Machine learning techniques with extreme gradient boosting were used to construct a protein model in the derivation cohort (SMART), which was validated in the Athero-Express cohort and compared with a clinical risk model. Pathway analysis was performed to identify specific pathways in high and low C-reactive protein (CRP) patient subsets. The protein model outperformed the clinical model in both the derivation cohort [area under the curve (AUC): 0.810 vs. 0.750; P < 0.001] and validation cohort (AUC: 0.801 vs. 0.765; P < 0.001), provided significant net reclassification improvement (0.173 in validation cohort) and was well calibrated. In contrast to a clear interleukin-6 signal in high CRP patients, neutrophil-signalling-related proteins were associated with recurrent ASCVD in low CRP patients.
conclusionA proteome-based risk model is superior to a clinical risk model in predicting recurrent ASCVD events. Neutrophil-related pathways were found in low CRP patients, implying the presence of a residual inflammatory risk beyond traditional NLRP3 pathways. The observed net reclassification improvement illustrates the potential of proteomics when incorporated in a tailored therapeutic approach in secondary prevention patients.
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