基于蛋白质组学的生物学年龄与肿瘤的发病死亡和预后的关联研究

doi:10.3969/j.issn.1003-9198.2025.07.008

Abstract

Abstract: Objective To explore the association between proteomics-based biological age and the incidence, mortality due to tumors and prognostic outcomes of cancers. Methods A total of 52 680 participants from the proteomics cohort of the UK Biobank were enrolled in this study. Eighteen types of cancers with more than 100 new cases were analyzed. The biological age was calculated using ProtAge-204 based on proteomics and machine learning. The association between chronological age and biological age was evaluated using linear correlation. The associations between biological age and the incidence, mortality due to tumors, and prognosis of all tumors and each individual tumor were analyzed using the Cox proportional hazards model. Results The ProtAge-204 biological age was highly associated with chronological age in the validation set (R²=0.84), which could be used as a biomarker of biological age. Biological age was significantly associated with the risk of overall cancer incidence (HR_{per year}=1.03, 95%CI: 1.02－1.04), the risk of overall cancer mortality (HR_{per year}=1.09, 95%CI: 1.07－1.11), and prognostic outcomes (HR_{per year}=1.05, 95%CI: 1.02－1.17). Moreover, in terms of mortality risk (HR_chronage=1.02)and prognostic outcomes(HR_chronage=0.99), biological age performed better than the traditional chronological age. Subsequently, in the analysis of each cancer type, biological age was significantly associated with the incidence risk of 8 types of cancers and the tumor-related mortality of 7 types of cancers, which was better than chronological age (6 types for incidence and 2 types for mortality). In terms of prognostic outcomes, neither age type showed a widespread association trend. Conclusions In this study, biological age constructed by proteomic biomarkers is significantly associated with cancer incidence, tumor-related mortality, and prognostic outcomes. Compared with chronological age, it has certain advantages and is recommended as a biomarker of aging.

Key words: biological age, proteomics, cancer, population cohort

CLC Number:

WANG Guanrong, BAO Yunying, ZHANG Lulu, LU Shengnan, SHEN Sipeng. Association between proteomics-based biological age and the incidence, mortality and prognosis of cancers[J]. Practical Geriatrics, 2025, 39(7): 686-692.

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Association between proteomics-based biological age and the incidence, mortality and prognosis of cancers

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