根据多核和表型特征预测减肥和体重增加:卡路里限制养试验结果
Lin Li1,2, Ruyi Li2, Zixin Qiu2
1School of Public Health, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Diabetes care
|June 30, 2025
概括
基线多组和表型数据准确地预测了减肥和恢复期间的体重和身体成分变化. 关键预测因素包括肠道微生物和便代谢物,提供个性化的体重管理见解.
科学领域:
- 代谢健康 代谢健康
- 肥胖问题研究研究
- 肠道微生物组研究研究
背景情况:
- 体重管理是复杂的,涉及损失和恢复阶段.
- 预测个体对饮食干预措施的反应对于有效的个性化至关重要.
- 多原子数据提供了对影响体重的生物因素的全面了解.
研究的目的:
- 为了确定体重和身体组成变化的基线多组和表型预测因素.
- 开发用于减肥和恢复体重的预测模型.
- 分析低碳水化合物饮食和时间限制饮食 (LEAN-TIME) 试验的数据.
主要方法:
- 对LEAN-TIME养试验数据的后期分析.
- 包括88名超重/肥胖的成年人在减肥阶段和79名在重量恢复阶段.
- 使用多变量回归和最小绝对收缩和选择操作员 (LASSO) 模型对饮食,代谢,便代谢和肠道微生物组数据.
主要成果:
- 多基因和表型模型显著优于仅表型模型 (P < 0.05).
- 在减肥 (R2:0.49-0.61) 和恢复 (R2:0.66-0.73) 期间的高预测性表现.
- 确定了包括肠道微生物 (如Ruminococcus callidus,Bifidobacterium adolescentis) 和便代谢物 (如N-乙-l-酸) 在内的关键预测因素.
结论:
- 基线多组和表型数据有效预测体重和身体组成的变化.
- 这些发现为个性化体重管理策略提供了宝贵的见解.
- 这项研究强调了肠道微生物组和代谢组在体重动态中的作用.
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