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基于英国生物库的前瞻性、纵向、观察性队列研究:使用核磁共振代谢组学分析的代谢生物标志物预测与衰老相关的疾病风险和死亡率。

Metabolic biomarkers using nuclear magnetic resonance metabolomics assay for the prediction of aging-related disease risk and mortality: a prospective, longitudinal, observational, cohort study based on the UK Biobank.

机构信息

Department of Diagnostic Radiology, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Room 406, Block K, Queen Mary Hospital, Pokfulam Road, Hong Kong, SAR, China.

出版信息

Geroscience. 2024 Apr;46(2):1515-1526. doi: 10.1007/s11357-023-00918-y. Epub 2023 Aug 30.

Abstract

The identification of metabolic biomarkers for aging-related diseases and mortality is of significant interest in the field of longevity. In this study, we investigated the associations between nuclear magnetic resonance (NMR) metabolomics biomarkers and aging-related diseases as well as mortality using the UK Biobank dataset. We analyzed NMR samples from approximately 110,000 participants and used multi-head machine learning classification models to predict the incidence of aging-related diseases. Cox regression models were then applied to assess the relevance of NMR biomarkers to the risk of death due to aging-related diseases. Additionally, we conducted survival analyses to evaluate the potential improvements of NMR in predicting survival and identify the biomarkers most strongly associated with negative health outcomes by dividing participants into health, disease, and death groups for all age groups. Our analysis revealed specific metabolomics profiles that were associated with the incidence of age-related diseases, and the most significant biomarker was intermediate density lipoprotein cholesteryl (IDL-CE). In addition, NMR biomarkers could provide additional contributions to relevant mortality risk prediction when combined with conventional risk factors, by improving the C-index from 0.813 to 0.833, with 17 NMR biomarkers significantly contributing to disease-related death, such as monounsaturated fatty acids (MUFA), linoleic acid (LA), glycoprotein acetyls (GlycA), and omega-3. Moreover, the value of free cholesterol in very large HDL particles (XL-HDL-FC) in the healthy control group demonstrated significantly higher values than the disease and death group across all age groups. This study highlights the potential of NMR metabolomics profiling as a valuable tool for identifying metabolic biomarkers associated with aging-related diseases and mortality risk, which could have practical implications for aging-related disease risk and mortality prediction.

摘要

在长寿领域,鉴定与衰老相关疾病和死亡率相关的代谢生物标志物具有重要意义。在这项研究中,我们使用英国生物库数据集研究了核磁共振(NMR)代谢组学生物标志物与衰老相关疾病和死亡率之间的关系。我们分析了大约 110000 名参与者的 NMR 样本,并使用多头机器学习分类模型来预测衰老相关疾病的发生。然后应用 Cox 回归模型来评估 NMR 生物标志物与因衰老相关疾病导致的死亡风险的相关性。此外,我们还进行了生存分析,以评估 NMR 在预测生存方面的潜在改善,并通过将参与者分为健康、疾病和死亡组,为所有年龄段的参与者确定与负面健康结果最相关的生物标志物。我们的分析揭示了与年龄相关疾病发生相关的特定代谢组学特征,其中最重要的生物标志物是中间密度脂蛋白胆固醇(IDL-CE)。此外,当与传统风险因素结合使用时,NMR 生物标志物可以为相关死亡率预测提供额外的贡献,通过将 C 指数从 0.813 提高到 0.833,17 个 NMR 生物标志物对疾病相关死亡有显著贡献,如单不饱和脂肪酸(MUFA)、亚油酸(LA)、糖蛋白乙酰基(GlycA)和 omega-3。此外,在所有年龄段的健康对照组中,超大 HDL 颗粒(XL-HDL-FC)中的游离胆固醇值明显高于疾病和死亡组。这项研究强调了 NMR 代谢组学分析作为一种鉴定与衰老相关疾病和死亡率相关的代谢生物标志物的有价值工具的潜力,这可能对衰老相关疾病风险和死亡率预测具有实际意义。

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