Su Chengxun, Wang Peter, Foo Nigel, Ho Dean
The Institute for Digital Medicine (WisDM), National University of Singapore, Singapore, Singapore.
The N.1 Institute for Health (N.1), National University of Singapore, Singapore, Singapore.
NPJ Aging. 2025 Mar 24;11(1):20. doi: 10.1038/s41514-025-00211-6.
A hallmark of subclinical metabolic decline is impaired metabolic flexibility, which refers to the ability to switch fuel utilization between glucose and fat according to energy demand and substrate availability. Herein, we propose optimizing metabolic health with digital twins that model an individual's metabolic flexibility profile to gamify the process of health optimization and predict long-term health outcomes. We explore key characteristics of this approach from technological and socioeconomical perspectives, with the objective of reducing the burden from metabolic disorders through driving behavior change and early detection of metabolic decline.
亚临床代谢衰退的一个标志是代谢灵活性受损，代谢灵活性是指根据能量需求和底物可用性在葡萄糖和脂肪之间切换燃料利用的能力。在此，我们建议使用数字孪生优化代谢健康，数字孪生可模拟个体的代谢灵活性概况，以使健康优化过程游戏化并预测长期健康结果。我们从技术和社会经济角度探索这种方法的关键特征，目的是通过推动行为改变和早期发现代谢衰退来减轻代谢紊乱带来的负担。
