在冠状动脉微血管疾病中以生物信息学为重点的代谢标记物的识别
Qing Su1, Wenting Liu1, Xiaoyan Liu1
1Department of Cardiology, Cardiovascualr Imaging Center, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China.
Computers in biology and medicine
|March 11, 2025
概括
研究人员使用先进的生物信息学确定了用于诊断冠状动脉微血管疾病 (CMVD) 的关键血液代谢物. 这种代谢学方法提供了比目前的侵入性方法更具成本效益的诊断替代方案.
科学领域:
- 心血管研究研究心血管研究
- 生物标志物发现发现
- 计算生物学 计算生物学
背景情况:
- 冠状动脉微血管疾病 (CMVD) 的诊断是具有挑战性的,因为复杂和昂贵的程序,如微循环阻力指数 (IMR).
- 目前的CMVD诊断方法缺乏成本效益和可访问性.
- 需要改进,减少CMVD的入侵性诊断工具.
研究的目的:
- 在冠状动脉样本中识别新陈代谢生物标志物,用于CMVD诊断.
- 开发成本高效的,基于血液的CMVD诊断方法.
- 利用先进的生物信息学来发现生物标志物和预测建模.
主要方法:
- 对68名接受冠状动脉血管造影的患者进行前性研究.
- 使用液态染色体质谱法对血样本进行非向的代谢学分析.
- 应用随机森林算法用于代谢物特征选择和通用线性模型 (GLMs) 用于预测建模,通过ROC曲线分析验证.
主要成果:
- 随机森林分析确定了10个关键代谢物,使CMVD区分开来.
- GLM实现了高的诊断准确性 (AUC 0.984发现,0.938验证).
- 数学建模提高了生物标志物选择的稳定性和可解释性.
结论:
- 先进的生物信息学有效地确定了关键的CMVD相关代谢物.
- 这种使用冠状动脉血液样本的代谢学方法是IMR的更实用和更具成本效益的替代方案.
- 这项研究为改善CMVD诊断策略提供了一个有希望的途径.
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