Work

Epigenetic biomarkers predict macrovascular events in individuals with type 2 diabetes

Year: 2025
Type: article
Study design: Observational Study
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. • Blood-based epigenetic biomarker predicts macrovascular events at type 2 diabetes diagnosis • The epigenetic biomarker tool outperforms established clinical cardiovascular risk scores • DNA methylation markers also show biological relevance in human aortic and carotid plaques • The epigenetic biomarker may support future precision medicine strategies in type 2 diabetes García-Calzón et al. identify a blood-based epigenetic biomarker tool that helps predict future cardiovascular disease, which individuals with type 2 diabetes are more likely to develop. Their findings support the use of epigenetic biomarkers to improve risk stratification and guide more personalized prevention strategies in diabetes care.
Language: English
Open Access status: gold
Estimated APC paid: $5,620
OpenAlex ID: W4413055626
FWCI: 2.268
Cites: 107
Cited by: 9
Related to: 10