根据基线循环代谢物估计的生物年龄与发生糖尿病和死亡率有关
La-Or Chailurkit1, Nisakron Thongmung2, Prin Vathesatogkit1
1Department of Medicine, Faculty of Medicine, Ramathibodi Hospital, Mahidol University, Bangkok, Thailand.
The journal of nutrition, health & aging
|February 22, 2024
概括
血清代谢资料可以预测泰国人口的糖尿病和死亡率,为评估生物衰老提供了一种新方法. 这项研究强调了不同种族群体的代谢年龄的潜力.
科学领域:
- 生物化学和衰老研究研究.
- 代谢学和机器学习应用程序
- 人口健康研究 人口健康研究
背景情况:
- 评估生物衰老及其对非白人人口糖尿病和死亡率等健康结果的预测能力仍然不清楚.
- 血清代谢学与机器学习相结合,为评估生物衰老提供了一种新的方法.
- 了解不同族群中的这些关联对于个性化医学至关重要.
研究的目的:
- 评估血清代谢学和机器学习在预测泰国人口中发生糖尿病和死亡率方面的实用性.
- 评估代谢年龄与时间年龄相比在预测健康结果方面的表现.
- 为了确定与死亡率相关的关键代谢物.
主要方法:
- 分析了454名泰国参与者的血清样本和11年死亡率数据,这些参与者的快餐血葡萄糖水平升高.
- 使用液体染色学/质谱学进行非向血清代谢.
- 一个深层的人工神经网络根据代谢物概况和时间年龄预测了生物年龄 (代谢年龄).
主要成果:
- 代谢年龄与时间年龄有很强的相关性 (r = 0.71,P < 0.001).
- 代谢年龄,但不是时间年龄,显著预测了发生糖尿病和11年死亡率,独立于BMI和性别.
- 特定的代谢物,包括β-D-mannosylphosphodecaprenyl和酸素,与死亡率有很强的关联.
结论:
- 血清代谢概况与泰国人口的发生糖尿病和死亡率有关.
- 代谢年龄显示出作为评估生物衰老和预测不良健康结果的工具的潜力.
- 这种方法可能对风险分层和个性化卫生干预措施在不同人群中有价值.
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