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A Validated, Modifiable Proteomic Score from the EXSCEL Trial Predicts Cardiovascular Events in Diabetes
Kristin M Corey1, Maggie Nguyen1, Michael Y Mi2
1Duke Molecular Physiology Institute, Duke University School of Medicine, Durham, United States of America.
JCI Insight
|July 2, 2026
Summary
Identifying cardiovascular risk in type 2 diabetes mellitus (T2DM) is crucial. This study reveals plasma protein signatures can improve risk prediction and identify treatment-responsive biomarkers for better cardiovascular event prevention.
Area of Science:
- Cardiovascular Medicine
- Proteomics
- Diabetes Mellitus Research
Background:
- Adults with type 2 diabetes mellitus (T2DM) face elevated risks of stroke, myocardial infarction, and cardiovascular death.
- Existing clinical models incompletely capture the heterogeneous cardiovascular risk in T2DM patients.
Purpose of the Study:
- To investigate plasma proteomic signatures for enhanced cardiovascular risk stratification in T2DM.
- To identify potential treatment-responsive biomarkers for major adverse cardiovascular events (MACE).
Main Methods:
- High-throughput proteomics analysis of plasma samples from the EXSCEL trial (T2DM patients randomized to exenatide or placebo).
- Development and external validation of a multi-protein score using machine learning in independent cohorts (CHS and PROMISE).
- Association analysis of proteomic signatures with time-to-MACE and treatment effects.
Main Results:
- A multi-protein score demonstrated incremental improvement in cardiovascular risk discrimination beyond clinical factors.
- Several proteins, including tetranectin, were consistently prioritized and modified by GLP-1 RA treatment.
- A decreased protein score correlated with improved outcomes, suggesting modifiable MACE risk.
Conclusions:
- Plasma proteomic signatures can significantly enhance cardiovascular risk stratification in T2DM.
- Proteomic scores and specific proteins like tetranectin may serve as treatment-responsive biomarkers.
- These findings support the use of proteomic signatures in precision prevention strategies for T2DM patients.
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