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

May 8, 2026The journals of gerontology. Series A, Biological sciences and medical sciences

Biological Aging Linked to and May Predict Kidney Disease Risk in People with Diabetes in the UK and China

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Abstract

Each standard deviation increase in accelerated biological age is associated with a 31% higher risk of chronic kidney disease in the UK and 68% in China.

Accelerated biological age was quantified using the Klemera-Doubal method and phenotypic age.
Over median follow-ups of 13.3 years in the UK and 3.3 years in China, 1,676 and 709 new cases of chronic kidney disease were documented.
The risk of chronic kidney disease increased by 29% with accelerated phenotypic age in both populations.
Integrating accelerated biological age measures into conventional risk models improved predictive accuracy, although only modestly.
Leukocyte telomere length did not contribute to improved risk prediction.

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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.

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

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