学习食物的分子指纹来解码饮食摄入量
Pieter Dorrestein1, Harsha Gouda1, Julius Agongo1
1University of California San Diego.
Research square
|November 24, 2025
概括
这项研究引入了一种新的代谢学方法,以客观地从便和尿液等生物样本中评估饮食. 这种方法提供了准确的饮食见解,有助于个性化的营养和疾病研究.
科学领域:
- 生物化学 生物化学
- 营养科学 营养科学
- 代谢学 代谢学 代谢学
背景情况:
- 客观的饮食评估对于理解营养和健康至关重要.
- 目前用于评估饮食摄入量的方法存在局限性.
- 生物样本为客观的饮食分析提供了一个有希望的来源.
研究的目的:
- 开发和验证基于参考的代谢学策略,以估计生物样本的相对食成分.
- 用这种方法确定最佳的生物标本以评估饮食摄入量.
- 创建一个用户友好的工具来应用这种新的方法.
主要方法:
- 利用非目标代谢学来识别特定于食物的分子离子特征.
- 雇员监督分类和歧视性分析来学习这些特征.
- 开发了一种方法来提取相应的MS1强度,以获得比例的,离子溶解的饮食读数.
- 验证了使用各种样本类型和研究设计的方法,包括NIST标准,小鼠模型和人类临床试验.
主要成果:
- 便,尿液和血液/血被确定为饮食评估的最佳生物样本.
- 离子分解读数准确地反映了各种验证研究中已知的饮食模式.
- 在类风湿性关节炎患者的MS/MS特征中得出的饮食分数与临床结果相关.
- 开发了一个基于Web的应用程序,以促进该方法的采用.
结论:
- 这份以参考为基础的代谢学策略为评估饮食摄入量提供了一个客观且互补的方法.
- 这种方法在推进个性化营养和营养流行病学方面具有重大潜力.
- 开发的工具提高了饮食研究代谢洞察力的可访问性和适用性.
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