DNA Methylation-derived biological age and long-term mortality risk in subjects with type 2 diabetes.

IF 8.5 1区 医学 Q1 CARDIAC & CARDIOVASCULAR SYSTEMS Cardiovascular Diabetology Pub Date : 2024-07-13 DOI:10.1186/s12933-024-02351-7
Jacopo Sabbatinelli, Angelica Giuliani, Katarzyna Malgorzata Kwiatkowska, Giulia Matacchione, Alessia Belloni, Deborah Ramini, Francesco Prattichizzo, Valeria Pellegrini, Francesco Piacenza, Elena Tortato, Anna Rita Bonfigli, Davide Gentilini, Antonio Domenico Procopio, Paolo Garagnani, Fabiola Olivieri, Giuseppe Bronte
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Abstract

Background: Individuals with type 2 diabetes (T2D) face an increased mortality risk, not fully captured by canonical risk factors. Biological age estimation through DNA methylation (DNAm), i.e. the epigenetic clocks, is emerging as a possible tool to improve risk stratification for multiple outcomes. However, whether these tools predict mortality independently of canonical risk factors in subjects with T2D is unknown.

Methods: Among a cohort of 568 T2D patients followed for 16.8 years, we selected a subgroup of 50 subjects, 27 survived and 23 deceased at present, passing the quality check and balanced for all risk factors after propensity score matching. We analyzed DNAm from peripheral blood leukocytes using the Infinium Human MethylationEPIC BeadChip (Illumina) to evaluate biological aging through previously validated epigenetic clocks and assess the DNAm-estimated levels of selected inflammatory proteins and blood cell counts. We tested the associations of these estimates with mortality using two-stage residual-outcome regression analysis, creating a reference model on data from the group of survived patients.

Results: Deceased subjects had higher median epigenetic age expressed with DNAmPhenoAge algorithm (57.49 [54.72; 60.58] years. vs. 53.40 [49.73; 56.75] years; p = 0.012), and accelerated DunedinPoAm pace of aging (1.05 [1.02; 1.11] vs. 1.02 [0.98; 1.06]; p = 0.012). DNAm PhenoAge (HR 1.16, 95% CI 1.05-1.28; p = 0.004) and DunedinPoAm (HR 3.65, 95% CI 1.43-9.35; p = 0.007) showed an association with mortality independently of canonical risk factors. The epigenetic predictors of 3 chronic inflammation-related proteins, i.e. CXCL10, CXCL11 and enRAGE, C-reactive protein methylation risk score and DNAm-based estimates of exhausted CD8 + T cell counts were higher in deceased subjects when compared to survived.

Conclusions: These findings suggest that biological aging, as estimated through existing epigenetic tools, is associated with mortality risk in individuals with T2D, independently of common risk factors and that increased DNAm-surrogates of inflammatory protein levels characterize deceased T2D patients. Replication in larger cohorts is needed to assess the potential of this approach to refine mortality risk in T2D.

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2 型糖尿病患者的 DNA 甲基化衍生生物年龄与长期死亡风险。
背景:2 型糖尿病(T2D)患者面临着更高的死亡风险,而典型的风险因素并不能完全反映这种风险。通过DNA甲基化(DNAm)估算生物年龄,即表观遗传时钟,正在成为改善多种结果风险分层的可能工具。然而,这些工具是否能独立于典型风险因素预测终末期糖尿病患者的死亡率还不得而知:方法:在一组追踪 16.8 年的 568 名 T2D 患者中,我们选择了 50 人作为亚组,其中 27 人存活,23 人目前已死亡,他们都通过了质量检查,并在倾向得分匹配后平衡了所有风险因素。我们使用 Infinium Human MethylationEPIC BeadChip(Illumina)分析了外周血白细胞中的 DNAm,通过之前验证的表观遗传时钟评估生物衰老,并评估了 DNAm 估算的特定炎症蛋白水平和血细胞计数。我们使用两阶段残差结果回归分析检验了这些估计值与死亡率的关系,并根据存活患者组的数据创建了一个参考模型:结果:用 DNAmPhenoAge 算法表示的死亡受试者的中位表观遗传年龄较高(57.49 [54.72; 60.58] 岁 vs. 53.40 [49.73; 56.75] 岁;p = 0.012),而且 DunedinPoAm 的衰老速度加快(1.05 [1.02; 1.11] vs. 1.02 [0.98; 1.06];p = 0.012)。DNAm PhenoAge(HR 1.16,95% CI 1.05-1.28;p = 0.004)和 DunedinPoAm(HR 3.65,95% CI 1.43-9.35;p = 0.007)与死亡率的关系独立于典型风险因素。3种慢性炎症相关蛋白(即CXCL10、CXCL11和enRAGE)的表观遗传学预测因子、C反应蛋白甲基化风险评分和基于DNAm的CD8 + T细胞数量估计值在死亡受试者中高于存活受试者:这些研究结果表明,通过现有的表观遗传学工具估测的生物老化与 T2D 患者的死亡风险有关,而与常见的风险因素无关。需要在更大的队列中进行复制,以评估这种方法在完善 T2D 死亡率风险方面的潜力。
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来源期刊
Cardiovascular Diabetology
Cardiovascular Diabetology 医学-内分泌学与代谢
CiteScore
12.30
自引率
15.10%
发文量
240
审稿时长
1 months
期刊介绍: Cardiovascular Diabetology is a journal that welcomes manuscripts exploring various aspects of the relationship between diabetes, cardiovascular health, and the metabolic syndrome. We invite submissions related to clinical studies, genetic investigations, experimental research, pharmacological studies, epidemiological analyses, and molecular biology research in this field.
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