NMR metabolomic modeling of age and lifespan: A multicohort analysis.
NMR metabolomic modeling of age and lifespan: A multicohort analysis.
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DOI：
10.1111/acel.14164
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发表时间：
2024-04
期刊：
影响因子：
7.8
通讯作者：
Chung-Ho E Lau;Maria Manou;Georgios Markozannes;Mika Ala-Korpela;Y. Ben-Shlomo;Nishi Chaturvedi
中科院分区：
文献类型：
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作者：
Chung-Ho E Lau;Maria Manou;Georgios Markozannes;Mika Ala-Korpela;Y. Ben-Shlomo;Nishi Chaturvedi
代谢组学年龄模型已被提出用于研究生物衰老，然而，它们尚未得到广泛验证。我们的目的是评估新开发的和现有的核磁共振波谱（NMR）代谢组学年龄模型预测的实际年龄（CA），死亡率和年龄相关疾病的性能。在9项英国和芬兰队列研究（N = 31，000人，年龄范围24-86岁）的血液中测量了98个代谢变量。我们使用非线性和惩罚回归模型CA和时间全因死亡率。我们研究了四个新的和两个以前发表的代谢组学年龄模型与衰老风险因素和表型的关系。在英国生物样本库（102，000）中，我们测试了CA、偶发疾病（心血管疾病（CVD）、2型糖尿病、癌症、痴呆和慢性阻塞性肺病）和全因死亡率的预测。在训练组群集中，代谢组学年龄模型和CA之间的7倍交叉验证Pearson's r范围在0.47和0.65之间（平均绝对误差：8-9岁）。代谢组学年龄模型，校正CA，与C-反应蛋白，与肾小球滤过率呈负相关。正相关的风险因素包括肥胖、糖尿病、吸烟和缺乏体育锻炼。在英国生物库中，代谢组学年龄与CA的相关性是适度的（r = 0.29-0.33），但所有代谢组学模型评分预测死亡率（风险比为1.01至1.06/代谢组学年龄年）和CVD，校正CA后。虽然代谢组年龄模型在独立人群中与CA仅中度相关，但它们提供了对CA本身的发病率和死亡率的额外预测，表明其适用性更广泛。
Metabolomic age models have been proposed for the study of biological aging, however, they have not been widely validated. We aimed to assess the performance of newly developed and existing nuclear magnetic resonance spectroscopy (NMR) metabolomic age models for prediction of chronological age (CA), mortality, and age-related disease. Ninety-eight metabolic variables were measured in blood from nine UK and Finnish cohort studies (N ≈31,000 individuals, age range 24-86 years). We used nonlinear and penalized regression to model CA and time to all-cause mortality. We examined associations of four new and two previously published metabolomic age models, with aging risk factors and phenotypes. Within the UK Biobank (N ≈102,000), we tested prediction of CA, incident disease (cardiovascular disease (CVD), type-2 diabetes mellitus, cancer, dementia, and chronic obstructive pulmonary disease), and all-cause mortality. Seven-fold cross-validated Pearson's r between metabolomic age models and CA ranged between 0.47 and 0.65 in the training cohort set (mean absolute error: 8-9 years). Metabolomic age models, adjusted for CA, were associated with C-reactive protein, and inversely associated with glomerular filtration rate. Positively associated risk factors included obesity, diabetes, smoking, and physical inactivity. In UK Biobank, correlations of metabolomic age with CA were modest (r = 0.29-0.33), yet all metabolomic model scores predicted mortality (hazard ratios of 1.01 to 1.06/metabolomic age year) and CVD, after adjustment for CA. While metabolomic age models were only moderately associated with CA in an independent population, they provided additional prediction of morbidity and mortality over CA itself, suggesting their wider applicability.