| Title: | Large-scale plasma proteomics for predicting future cardiovascular and all-cause mortality among individuals with cardiovascular-kidney-metabolic syndrome stage 0-3 |
| Journal: | Metabolism |
| Published: | 24 Mar 2026 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/41887398/ |
| DOI: | https://doi.org/10.1016/j.metabol.2026.156600 |
Publication 18219
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Abstract
BACKGROUND: Identifying high-risk individuals for cardiovascular and all-cause mortality among individuals with cardiovascular-kidney-metabolic (CKM) syndrome stage 0-3 can guide the implementation of targeted interventions. This study aimed to evaluate the predictive value of plasma proteins for future cardiovascular and all-cause mortality.</p>
METHODS: This study included 39,007 participants from the UK Biobank (UKB) with CKM stage 0-3 and available proteomic data. Associations between plasma proteins and future risks of cardiovascular and all-cause mortality were assessed using Cox proportional hazards models. Key proteins were identified through an ensemble machine learning approach integrating support vector machine (SVM), random forest (RF), and extreme gradient boosting (XGBoost) algorithms. Subsequently, Cox models were applied to evaluate the incremental predictive value of these key proteins and their ability to enhance risk stratification for mortality outcomes. Furthermore, temporal trajectories of protein levels were examined in the years preceding death.</p>
RESULTS: During a median follow-up of 15.2 years, 505 participants died from cardiovascular causes and 3368 from any cause. 56 and 269 out of 2911 plasma proteins were significantly associated with cardiovascular and all-cause mortality, respectively (Bonferroni-adjusted P < 0.05). Incorporating seven and eight key proteins into conventional model significantly improved long-term predictive performance (C-statistics: 0.812 versus 0.782 for cardiovascular mortality; 0.772 versus 0.739 for all-cause mortality; both P < 0.001), and also provided incremental predictive value for 5- and 10-year mortality risks. Notably, participants died during follow-up exhibited markedly elevated certain protein levels over a decade before deaths, with progressively increasing trajectories over time. Stratification based on optimal predicted risk thresholds further revealed distinct cumulative mortality risks across groups.</p>
CONCLUSIONS: In individuals with CKM stage 0-3, plasma proteins combined with traditional risk factors may predict future cardiovascular and all-cause mortality.</p>
14 Keywords
- Aged
- Biomarkers
- Blood Proteins
- Cardio-Renal Syndrome
- Cardiovascular Diseases
- Cause of Death
- Female
- Humans
- Male
- Metabolic Syndrome
- Middle Aged
- Proportional Hazards Models
- Proteomics
- Risk Factors
8 Authors
- Bingtao Weng
- Jiahe Wei
- Han Chen
- Yuyan Zhao
- Ningjian Wang
- Hongliang Feng
- Sizhi Ai
- Xiao Tan
1 Application
| Application ID | Title |
|---|---|
| 55177 | Role of sleep and circadian rhythm in treatment efficacy of antidiabetics |
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