通过H-NMR与机器学习工具结合,绘制血栓塞瘤标记物的地图
Lucas G Martins1, Bruna M Manzini2, Silmara Montalvão2
1Laboratory of Biological Chemistry, Department of Organic Chemistry, Institute of Chemistry, Universidade Estadual de Campinas, Campinas 13083-862, SP, Brazil.
Molecules (Basel, Switzerland)
|January 8, 2025
概括
机器学习识别了针对血栓栓塞 (VTE) 和抗脂综合征 (APS) 的鲜明血清代谢物配置文件. 希斯蒂丁,3-基酸盐和三氨酸显示出作为生物标志物的潜力,可以将这些条件与健康对照区分开来.
科学领域:
- 生物化学 生物化学
- 代谢学 代谢学 代谢学
- 人工智能的人工智能
背景情况:
- 抗脂综合征 (APS) 和静脉血栓栓塞 (VTE) 是具有重大健康影响的复杂疾病.
- 了解这些疾病的代谢基础对于开发有效的诊断和治疗策略至关重要.
研究的目的:
- 通过机器学习,研究血清代谢物在识别血栓栓塞 (VTE) 和抗脂综合征 (APS) 的歧视潜力.
- 确定与APS和VTE病原发生相关的特定代谢途径和生物标志物.
主要方法:
- 利用基于H-NMR的代谢学,对来自VTE患者 (n=32),血栓性初级APS患者 (n=32) 和健康对照患者 (HCs,n=32) 的血清样本进行分析.
- 应用机器学习和人工智能工具来分析独特的代谢概况.
- 在糖解,TCA循环,脂质和分支链氨基酸 (BCAA) 代谢中发现了显著的变化.
主要成果:
- 在VTE和HC,APS和HC以及VTE和三重阳性APS组之间观察到不同的代谢概况.
- 伊斯蒂丁,3-基酸盐和三氨酸成为影响模型预测的前三大代谢物.
- 这些代谢物对区分APS,VTE和HC产生了重大影响.
结论:
- 糖解,TCA循环,脂质和BCAA代谢中的代谢途径变化与APS和VTE的发病有关.
- 伊斯蒂丁,3-基酸盐和三氨酸被确定为潜在的关键生物标志物,用于区分APS和VTE患者与健康个体.
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