对T2DM队列的生物特征进行深入分析,使用集成向LC-MS平台
Shurong Ma1,2, Lu Yang3, Jinwen Lai1,2
1Laboratory of Integrative Medicine, The First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, 116000, P. R. China.
Scientific data
|March 4, 2025
概括
这项研究提出了一个优化的向代谢平台,用于分析血清中的1609个小分子. 该平台在2型糖尿病患者 (T2DM) 中发现了氨基酸,脂肪酸和脂质的显著代谢障碍.
科学领域:
- 代谢学 代谢学 代谢学
- 生物化学 生物化学
- 临床诊断 临床诊断 临床诊断
背景情况:
- 代谢物分析为疾病诊断和预后提供了至关重要的生理洞察力,特别是糖尿病.
- 早期发现和了解2型糖尿病 (T2DM) 等疾病中的代谢变化至关重要.
研究的目的:
- 开发和验证一个优化的,深入的向代谢组平台,用于全面的血清小分子分析.
- 从健康个体和新诊断的T2DM患者在中国北部生成一个新的代谢数据集.
主要方法:
- 整合了六种分离条件,包括正常相,前列衍生和四种逆相方法.
- 用同位素标记的内部标准对血清中32个子类的1609个小分子进行量化.
- 方法验证和与非目标代谢策略进行比较.
主要成果:
- 从200名健康人群和100名T2DM患者中生成了一个强大的向代谢组数据集.
- 在T2DM患者中观察到显著的代谢障碍,特别是在氨基酸,脂肪酸,溶脂酸胆和三糖醇代谢中.
- 该平台表现出针对性代谢组分析的高灵敏度和稳定性.
结论:
- 开发的目标代谢组平台是全面分析的灵敏和强大的工具.
- 这项研究为T2DM的代谢失调提供了宝贵的见解.
- 数据集和验证结果是公开可用的,以推进代谢学研究和疾病诊断.
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