García-Calzón Sonia, Maguolo Alice, Eichelmann Fabian, Edsfeldt Andreas, Perfilyev Alexander, Maziarz Marlena, Lindström Axel, Sun Jiangming, Briviba Monta, Schulze Matthias B, Klovins Janis, Ahlqvist Emma, Gonçalves Isabel, Ling Charlotte
Epigenetics and Diabetes Unit, Department of Clinical Sciences Malmö, Lund University, Skåne University Hospital, 20502 Malmö, Sweden; Department of Food Sciences and Physiology, Centre for Nutrition Research, IdiSNA, University of Navarra, 31008 Pamplona, Spain; Centro de Investigación Biomédica en Red de Fisiopatología de la Obesidad y Nutrición (CIBERobn), Instituto Salud Carlos III, 28029 Madrid, Spain.
Epigenetics and Diabetes Unit, Department of Clinical Sciences Malmö, Lund University, Skåne University Hospital, 20502 Malmö, Sweden.
Cell Rep Med. 2025 Aug 19;6(8):102290. doi: 10.1016/j.xcrm.2025.102290. Epub 2025 Aug 7.
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.
2型糖尿病(T2D)患者发生大血管事件(iMEs)的预测效果仍不尽人意。我们旨在发现基于血液的表观遗传生物标志物,以预测752例新诊断的T2D患者中的iMEs,其中102例在随访期间发生了iMEs。461个DNA甲基化位点,如靠近ARID3A、GATA5、HDAC4、IRS2和TMEM51的位点,与iMEs相关。通过交叉验证,一个包含87个位点的甲基化风险评分(MRS)对iMEs的预测曲线下面积(AUC)为0.81,MRS与临床风险因素联合预测的AUC为0.84,优于SCORE2-糖尿病(系统性冠状动脉风险评估2-糖尿病)、英国前瞻性糖尿病研究(UKPDS)、弗雷明汉研究和多基因风险评分(AUC = 0.54-0.62)。这种表观遗传生物标志物的阴性预测值为95.9%,通过连续净重新分类改善(NRI)改善了iMEs的分类,与临床因素相比显示出90.2%的改善。动脉粥样硬化主动脉与非动脉粥样硬化主动脉显示出78个差异甲基化位点。我们在EPIC-波茨坦队列中验证了32个位点,在OPTIMED队列中验证了43个位点,包括一个MRS(AUC = 0.80)。总之,基于血液的表观遗传生物标志物比临床风险因素能更好地预测iMEs,支持其未来的临床应用。