基于血清类固醇激素的多囊卵巢综合征的生物化学分类诊断
Min Wang1, Shuhan Zhang2, Jun He3
1Department of Pharmacy, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, Jiangsu 210008, China.
The Journal of steroid biochemistry and molecular biology
|October 24, 2024
概括
多囊性卵巢综合征 (PCOS) 诊断可以通过分析类固醇激素配置文件来改进. 一个机器学习模型准确地区分PCOS与高雄激素血症 (HA-PCOS),没有高雄激素血症 (NA-PCOS) 和对照,减少误诊.
科学领域:
- 内分泌学和新陈代谢学
- 生物化学 生物化学
- 计算生物学 计算生物学
背景情况:
- 多囊卵巢综合征 (PCOS) 是一种异质的代谢障碍.
- 非高雄性PCOS (NA-PCOS) 病例可能因缺乏特定的诊断标志物而被误诊.
- 在PCOS亚型和对照组中,类固醇激素的特征显著不同.
研究的目的:
- 系统地分析高雄性双胞胎综合征 (HA-PCOS),NA-PCOS和非PCOS女性之间的类固醇激素水平差异.
- 为准确的PCOS分类开发和选机器学习模型.
- 确定关键的类固醇激素,以改善PCOS诊断.
主要方法:
- 从54名HA-PCOS,79名NA-PCOS和60名对照女性 (年龄在18-35岁) 的血清样本使用LC-MS/MS进行了分析,用于类固醇激素量化.
- 八个机器学习算法被评估为PCOS分类.
- 在训练集上进行了十倍交叉验证,随后在独立集上进行了验证.
主要成果:
- 从胆固醇到下游类固醇激素的整体代谢流在PCOS中显著增加,特别是在HA-PCOS中.
- 随机森林 (RF) 模型实现了高精度 (0.938),AUC (0.989) 和kappa (0.906) 的HA-PCOS,NA-PCOS和非PCOS分类.
- 使用,二,总二甲基,总四甲基和自由雌激素的简化射频模型显示出高诊断灵敏度 (100%的HA-PCOS,93.3%的NA-PCOS,91.7%的非PCOS).
结论:
- 在HA-PCOS,NA-PCOS和非PCOS妇女之间存在不同的类固醇激素配置文件.
- 基于特定的雄激素和雌激素的简化射频模型有效地分类PCOS亚型.
- 这种方法可以显著降低NA-PCOS错过诊断率.
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