| Title: | Proteomics mediates the effects of biological aging on the progression of cardio-renal-metabolic comorbidity: a UK biobank cohort study |
| Journal: | Cardiovascular Diabetology |
| Published: | 9 Dec 2025 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/41366404/ |
| DOI: | https://doi.org/10.1186/s12933-025-03035-6 |
Publication 17157
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Abstract
BackgroundCardio-renal-metabolic (CRM) comorbidity, including cardiovascular disease, chronic kidney disease, and type 2 diabetes mellitus, is prevalent in the population and closely associated with biological aging. However, longitudinal evidence and potential proteomics mediator remain limited.MethodsWe studied 330,177 UK Biobank participants free of CRM diseases at baseline. Biological aging was measured by KDM-BA, PhenoAge, their accelerations, and frailty status, and its effects on CRM progression, including no CRM disease to first, double, and triple CRM diseases, were evaluated using multistate proportional hazards model. In the subpopulation with proteomics data (n = 35,118), 2911 plasma proteins were profiled, and mediation analyses were performed to identify potential mediators.ResultsAll five biological aging indicators significantly predicted CRM progression. For example, each standard deviation increase in PhenoAge was associated with hazard ratios of 1.42 [95% confidence interval (CI) 1.40-1.44], 1.26 (95% CI 1.22-1.31), and 1.24 (95% CI 1.12-1.37) for the transitions to first, double, and triple CRM disease, respectively. Mediation analyses identified nine circulating key proteins that statistically mediated the associations between biological aging and CKM progression, with GDF15, ADM, and HAVCR1 showing the largest mediated proportion (13.10-43.23%). The neutralizing antibody ponsegroumab for GDF15 is currently undergoing clinical evaluation.ConclusionBiological aging was strongly associated with the progression of CRM comorbidity, and these associations were partly accounted for by specific circulating proteins. These findings highlight the potential of aging-centered strategies and proteomic biomarkers for improving the risk prediction of CRM health and identifying therapeutic targets.</p>
5 Authors
- Zhijie Lin
- Changxi Wang
- Zhennan Lin
- Kaiyang Lin
- Yansong Guo
1 Application
| Application ID | Title |
|---|---|
| 105322 | Multi-angle exploration of chronic diseases in the elderly |
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