Association and Predictive Value of Biological Aging for Chronic Kidney Disease Risk in Diabetes: Cross-Cohort Validation across UK and China.

Yiting Wu, Hao Xiang, Yu Huang, Yuanyuan Zhang, Ziliang Ye, Yanjun Zhang, Sisi Yang, Xiaoqin Gan, Yiwei Zhang, Chen Dan, Xianglian Cai, Xiaolong Liang, Sheng Nie, Fan Fan Hou, Xianhui Qin
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Abstract

Background: Biological aging (BA) may influence chronic kidney disease (CKD) development. We evaluated the association of accelerated BA-quantified using Klemera-Doubal method biological age (KDM-BA) and phenotypic age (PhenoAge)-with incident CKD, and assessed its predictive value beyond conventional risk factors (CKD Prediction Consortium [CKD-PC] model) in participants with diabetes.

Methods: This two-country cohort study included 14,274 participants with diabetes from the UK Biobank and 7,900 from the China Renal Data System (CRDS). KDM-BA and PhenoAge were calculated from clinical biomarkers, and their acceleration (deviation from chronological age) was evaluated. Cox regression assessed associations with incident CKD, while C-index, net reclassification improvement (NRI), and integrated discrimination improvement (IDI) evaluated predictive performance.

Results: Over median follow-ups of 13.3 (UK Biobank) and 3.3 (CRDS) years, 1,676 and 709 incident CKD cases were documented. Each standard deviation increase in KDM-BA acceleration was associated with 31% (95%CI: 23-39%) (UK) and 68% (95%CI: 58-80%) (China) higher CKD hazard. PhenoAge acceleration similarly increased CKD risk (29% and 28%, respectively). In the UK Biobank, adding KDM-BA or PhenoAge acceleration to the CKD-PC model (C-index = 0.770) led to modest but statistically significant improvements in prediction (C-index increase = 0.004 [95%CI: 0.002-0.006] and 0.003 [0.001-0.005], respectively), while leukocyte telomere length (LTL) provided no benefit (0.0001 [-0.0004, 0.0005]). Both BA measures enhanced reclassification (NRI: 0.034-0.076; IDI: 0.002-0.003). CRDS analyses yielded consistent results.

Conclusion: Accelerated BA is consistently associated with higher CKD hazard in diabetes across European and Asian populations. KDM-BA and PhenoAge offer practical tools for refining CKD risk stratification.

生物衰老与糖尿病慢性肾脏疾病风险的关联及预测价值:英国和中国的交叉队列验证
背景:生物老化(BA)可能影响慢性肾脏疾病(CKD)的发展。我们评估了加速ba(使用klemera - double方法量化的生物年龄(KDM-BA)和表型年龄(PhenoAge))与CKD事件的关系,并评估了其在糖尿病参与者中的预测价值,超出了传统的危险因素(CKD预测联盟[CKD- pc]模型)。方法:这项两国队列研究包括来自英国生物银行的14274名糖尿病患者和来自中国肾脏数据系统(CRDS)的7900名糖尿病患者。根据临床生物标志物计算KDM-BA和PhenoAge,并评估其加速(与实足年龄的偏差)。Cox回归评估与CKD事件的关联,而c指数、净重分类改善(NRI)和综合判别改善(IDI)评估预测性能。结果:中位随访时间分别为13.3年(UK Biobank)和3.3年(CRDS),记录了1676例和709例CKD事件。KDM-BA加速每增加一个标准差,CKD风险增加31% (95%CI: 23-39%)(英国)和68% (95%CI: 58-80%)(中国)。表型加速同样增加CKD风险(分别为29%和28%)。在UK Biobank中,在CKD-PC模型中加入KDM-BA或PhenoAge加速(C-index = 0.770)导致了适度但具有统计学意义的预测改善(C-index分别增加= 0.004 [95%CI: 0.002-0.006]和0.003[0.001-0.005]),而白细胞端粒长度(LTL)没有提供任何益处(0.0001[-0.0004,0.0005])。两种BA指标均增强了再分类(NRI: 0.034-0.076; IDI: 0.002-0.003)。CRDS分析得出了一致的结果。结论:在欧洲和亚洲人群中,加速BA一直与糖尿病患者较高的CKD风险相关。KDM-BA和PhenoAge为细化CKD风险分层提供了实用的工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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