| Title: | Proteomic aging clock (PAC) predicts age-related outcomes in middle-aged and older adults |
| Journal: | Aging Cell |
| Published: | 15 May 2024 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/38747160/ |
| DOI: | https://doi.org/10.1111/acel.14195 |
| URL: | https://onlinelibrary.wiley.com/doi/pdfdirect/10.1111/acel.14195 |
| Citations: | 2 (2 in last 2 years) as of 8 Aug 2024 |
Publication 12072
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Abstract
Beyond mere prognostication, optimal biomarkers of aging provide insights into qualitative and quantitative features of biological aging and might, therefore, offer useful information for the testing and, ultimately, clinical use of gerotherapeutics. We aimed to develop a proteomic aging clock (PAC) for all-cause mortality risk as a proxy of biological age. Data were from the UK Biobank Pharma Proteomics Project, including 53,021 participants aged between 39 and 70 years and 2923 plasma proteins assessed using the Olink Explore 3072 assay®. 10.9% of the participants died during a mean follow-up of 13.3 years, with the mean age at death of 70.1 years. The Spearman correlation between PAC proteomic age and chronological age was 0.77. PAC showed robust age-adjusted associations and predictions for all-cause mortality and the onset of various diseases in general and disease-free participants. The proteins associated with PAC proteomic age deviation were enriched in several processes related to the hallmarks of biological aging. Our results expand previous findings by showing that biological age acceleration, based on PAC, strongly predicts all-cause mortality and several incident disease outcomes. Particularly, it facilitates the evaluation of risk for multiple conditions in a disease-free population, thereby, contributing to the prevention of initial diseases, which vary among individuals and may subsequently lead to additional comorbidities.</p>
8 Authors
- Chia-Ling Kuo
- Zhiduo Chen
- Peiran Liu
- Luke C. Pilling
- Janice L. Atkins
- Richard H. Fortinsky
- George A. Kuchel
- Breno S. Diniz
1 Application
| Application ID | Title |
|---|---|
| 92647 | Research to Inform the Field of Precision Gerontology |
Enabling scientific discoveries that improve human health