National Clinical Research Center for Geriatric Disorders, Department of Geriatrics, Xiangya Hospital & Center for Medical Genetics, School of Life Sciences, Central South University, Changsha, Hunan, 410008, China.
Xiangya School of Medicine, Central South University, Changsha, Hunan, 410013, China.
Nat Commun. 2024 Sep 15;15(1):8081. doi: 10.1038/s41467-024-52310-9.
The metabolomic profile of aging is complex. Here, we analyse 325 nuclear magnetic resonance (NMR) biomarkers from 250,341 UK Biobank participants, identifying 54 representative aging-related biomarkers associated with all-cause mortality. We conduct genome-wide association studies (GWAS) for these 325 biomarkers using whole-genome sequencing (WGS) data from 95,372 individuals and perform multivariable Mendelian randomization (MVMR) analyses, discovering 439 candidate "biomarker - disease" causal pairs at the nominal significance level. We develop a metabolomic aging score that outperforms other aging metrics in predicting short-term mortality risk and exhibits strong potential for discriminating aging-accelerated populations and improving disease risk prediction. A longitudinal analysis of 13,263 individuals enables us to calculate a metabolomic aging rate which provides more refined aging assessments and to identify candidate anti-aging and pro-aging NMR biomarkers. Taken together, our study has presented a comprehensive aging-related metabolomic profile and highlighted its potential for personalized aging monitoring and early disease intervention.
衰老的代谢组学特征十分复杂。在这里，我们分析了来自 250341 名英国生物库参与者的 325 个核磁共振（NMR）生物标志物，确定了 54 个与全因死亡率相关的具有代表性的衰老相关生物标志物。我们使用来自 95372 个人的全基因组测序（WGS）数据对这 325 个生物标志物进行全基因组关联研究（GWAS），并进行多变量孟德尔随机化（MVMR）分析，在名义显著性水平上发现了 439 对候选“生物标志物-疾病”因果对。我们开发了一种代谢组学衰老评分，在预测短期死亡率风险方面优于其他衰老指标，并具有很强的区分加速衰老人群和改善疾病风险预测的潜力。对 13263 个人的纵向分析使我们能够计算出代谢组学衰老率，从而提供更精细的衰老评估，并确定候选的抗衰和促衰 NMR 生物标志物。总之，我们的研究提出了一个全面的衰老相关代谢组学特征，并强调了其在个性化衰老监测和早期疾病干预方面的潜力。
