ArticleCell reports. Medicine2025
Epigenetic biomarkers predict macrovascular events in individuals with type 2 diabetes.
Article in Cell reports. Medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Blood-Based DNA Methylation Models Improve Short-term Cardiovascular Risk Stratification in Individuals With Type 2 Diabetes.Diabetes care · 2026Article
- Associations between diet quality, epigenetic aging and epigenome in two population-based cohorts.Nature communications · 2026Article
- The changing epidemiology of human type 2 diabetes-associated atherosclerosis: Pathophysiological mechanisms and emerging treatment possibilities.Journal of internal medicine · 2026Review
- TiSMeD: A tissue-specific methylation and expression database for biomarker and translational applications.Molecular therapy. Nucleic acids · 2026Article
- Novel epigenetic marks of insulin resistance trajectories in a longitudinal study of childhood obesity.Cardiovascular diabetology · 2026Article
- Epigenetic regulation of cardiac physiology and pathophysiology: biological sex matters.The journal of cardiovascular aging · 2026Article
- Review
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Authors and funding
14 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Prediction of incident macrovascular events (iMEs) in individuals with type 2 diabetes (T2D) remains suboptimal. We aim to discover blood-based epigenetic biomarkers predicting iMEs in 752 newly diagnosed individuals with T2D, among whom 102 developed iMEs during follow-up. 461 DNA methylation sites, e.g., near ARID3A, GATA5, HDAC4, IRS2, and TMEM51, associate with iMEs. Using cross-validation, a methylation risk score (MRS) containing 87 sites predicts iMEs with an area under the curve (AUC) of 0.81 and an AUC of 0.84 for the combination of MRS and clinical risk factors, better than SCORE2-Diabetes (Systematic Coronary Risk Evaluation 2-Diabetes), UKPDS (United Kingdom Prospective Diabetes Study), Framingham, and polygenic risk scores (AUCs = 0.54-0.62). This epigenetic biomarker has a negative predictive value of 95.9% and improves the classification of iMEs with continuous net reclassification improvement (NRI) showing 90.2% improvement versus clinical factors. Atherosclerotic versus non-atherosclerotic aortas show 78 differentially methylated sites. We validate 32 sites in EPIC-Potsdam and 43 in OPTIMED cohorts, including an MRS (AUC = 0.80). Together, blood-based epigenetic biomarkers predict iMEs better than clinical risk factors, supporting its future clinical use.
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