Center for Clinical Big Data and Analytics of the Second Affiliated Hospital and Department of Big Data in Health Science School of Public Health, Zhejiang Key Laboratory of Intelligent Preventive Medicine, Zhejiang University School of Medicine, Hangzhou, 310058, China.
Department of General Practice, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, 310016, China.
Adv Sci (Weinh). 2024 Nov;11(43):e2406670. doi: 10.1002/advs.202406670. Epub 2024 Sep 27.
Existing metabolomic clocks exhibit deficiencies in capturing the heterogeneous aging rates among individuals with the same chronological age. Yet, the modifiable and non-modifiable factors in metabolomic aging have not been systematically studied. Here, a new aging measure-MetaboAgeMort-is developed using metabolomic profiles from 239,291 UK Biobank participants for 10-year all-cause mortality prediction. The MetaboAgeMort showed significant associations with all-cause mortality, cause-specific mortality, and diverse incident diseases. Adding MetaboAgeMort to a conventional risk factors model improved the predictive ability of 10-year mortality. A total of 99 modifiable factors across seven categories are identified for MetaboAgeMort. Among these, 16 factors representing pulmonary function, body composition, socioeconomic status, dietary quality, smoking status, alcohol intake, and disease status showed quantitatively stronger associations. The genetic analyses revealed 99 genomic risk loci and 271 genes associated with MetaboAgeMort. The tissue-enrichment analysis showed significant enrichment in liver. While the external validation of the MetaboAgeMort is required, this study illuminates heterogeneous metabolomic aging across the same age, providing avenues for identifying high-risk individuals, developing anti-aging therapies, and personalizing interventions, thus promoting healthy aging and longevity.
现有的代谢时钟在捕捉具有相同年龄的个体之间不同的衰老率方面存在缺陷。然而,代谢老化的可调节和不可调节因素尚未得到系统研究。在这里,我们使用来自 239291 名英国生物库参与者的代谢组学图谱开发了一种新的衰老衡量标准——代谢年龄 Mort,并将其用于预测 10 年全因死亡率。代谢年龄 Mort 与全因死亡率、特定原因死亡率和多种疾病的发生均有显著关联。将代谢年龄 Mort 添加到传统的危险因素模型中,可以提高 10 年死亡率的预测能力。总共确定了代谢年龄 Mort 的七个类别中的 99 个可调节因素。其中,代表肺功能、身体成分、社会经济地位、饮食质量、吸烟状况、饮酒量和疾病状况的 16 个因素与代谢年龄 Mort 的关联更强。遗传分析显示,有 99 个基因组风险位点和 271 个基因与代谢年龄 Mort 相关。组织富集分析显示,肝脏明显富集。虽然需要对代谢年龄 Mort 进行外部验证,但本研究阐明了相同年龄人群中代谢组学的异质性衰老,为识别高风险个体、开发抗衰老疗法和个性化干预提供了途径,从而促进健康衰老和长寿。