GeroScience ( IF 5.3 ) Pub Date : 2024-10-31 , DOI: 10.1007/s11357-024-01411-w Renjia Zhao, Heyang Lu, Huangbo Yuan, Shuaizhou Chen, Kelin Xu, Tiejun Zhang, Zhenqiu Liu, Yanfeng Jiang, Chen Suo, Xingdong Chen
Individual’s aging rates vary across organs. However, there are few methods for assessing aging at organ levels and whether they contribute differently to mortalities remains unknown. We analyzed data from 45,821 adults in the UK Biobank, using plasma proteomics and machine learning to estimate biological ages for 12 major organs. The differences between biological age and chronological age, referred to as “age gaps,” were calculated for each organ. Partial correlation analyses were used to assess the association between age gaps and modifiable factors. Adjusted multivariable Cox regression models were applied to examine the association of age gaps with all-cause mortality, cause-specific mortalities, and cancer-specific mortalities. We reveal a complex network of varied associations between multi-organ aging and modifiable factors. All age gaps increase the risk of all-cause mortality by 6–60%. The risk of death varied from 5.54 to 29.18 times depending on the number of aging organs. Cause-specific mortalities are associated with certain organs’ aging. For mental diseases mortality, and nervous system mortality, only brain aging exhibited a significant increased risk of HR 2.38 (per SD, 95% CI: 2.06–2.74) and 1.99 (per SD, 95% CI: 1.84–2.16), respectively. Age gaps of stomach were also a specific indicator for gastric cancer. Eventually, we find that an organ’s biological age selectively influences the aging of other organ systems. Our study demonstrates that accelerated aging in specific organs increases the risk of mortality from various causes. This provides a potential tool for early identification of at-risk populations, offering a relatively objective method for precision medicine.
中文翻译:
基于血浆蛋白质组学的器官特异性衰老对全因死亡率和原因特异性死亡率的影响:一项前瞻性队列研究
个体的衰老速度因器官而异。然而,在器官水平评估衰老的方法很少,它们是否对死亡率的贡献不同仍然未知。我们分析了英国生物样本库中 45,821 名成年人的数据,使用血浆蛋白质组学和机器学习来估计 12 个主要器官的生物年龄。计算每个器官的生物年龄和实际年龄之间的差异,称为“年龄差距”。采用偏相关分析评估年龄差距与可改变因素之间的关联。应用调整后的多变量 Cox 回归模型来检查年龄差距与全因死亡率、特定原因死亡率和癌症特异性死亡率的相关性。我们揭示了多器官衰老和可改变因素之间不同关联的复杂网络。所有年龄差距都会使全因死亡的风险增加 6-60%。死亡风险从 5.54 到 29.18 倍不等,具体取决于衰老器官的数量。特定原因的死亡率与某些器官的衰老有关。对于精神疾病死亡率和神经系统死亡率,只有大脑衰老表现出 HR 2.38(根据 SD,95% CI:2.06-2.74)和 1.99(根据 SD,95% CI:1.84-2.16)的显著增加。胃的年龄差距也是胃癌的一个特异性指标。最终,我们发现器官的生物年龄选择性地影响其他器官系统的衰老。我们的研究表明,特定器官的加速衰老会增加各种原因导致的死亡风险。这为早期识别高危人群提供了潜在工具,为精准医疗提供了一种相对客观的方法。