基于微生物组学和机器学习构建咽喉反流唾液菌群诊断模型

The Salivary Microbiota Diagnostic Model for Laryngopharyngeal Reflux Based on Microbiome and Machine Learning

周林熙;尹龙龙;崔小缓;毕欣欣;张延平;蒋兴旺;李丽娜

1:河北北方学院

2:中国人民解放军总医院第六医学中心耳鼻咽喉头颈外科医学部派驻解放军总医院第八医学中心耳鼻咽喉头颈外科

3:国家耳鼻咽喉疾病临床医学中心

摘要
目的 探索使用微生物组学技术和机器学习的方法构建咽喉反流(laryngopharyngeal reflux, LPR)唾液菌群诊断模型的可能性。方法 以2022年2~11月就诊的经8周质子泵抑制剂治疗显效的34例LPR患者为病例组,与病例组年龄、性别和体重指数相匹配的47例健康志愿者为对照组,留取用药前的唾液标本,提取DNA,扩增16S片段后进行测序,对测序结果进行生物学信息分析,比较菌属水平物种差异。选择病例组24例、对照组33例作为训练集,其余作为测试集,随机森林法分类数据,进行十折交叉验证,选择最优菌属组合构建诊断模型,计算疾病概率指数(probability of disease, POD),绘制ROC曲线,使用SPSS 18.0软件对数据进行统计学分析。结果 病例组和对照组相比,唾液中22个属相对丰度存在统计学差异(P<0.05),构建由6个菌属组成的诊断模型,即乳酸杆菌属、芽孢杆菌属、新鞘氨醇杆菌属、假交替单胞菌属、罗尔斯通菌属和Phocaeicola属,测试集ROC曲线下面积为0.843,诊断模型灵敏度为60.0%,特异度为87.71%,Kappa值为0.470。结论 由唾液菌群构建的菌属组合诊断模型可以区分LPR患者与健康人,具有潜在的临床应用价值。
关键词
咽喉反流;唾液菌群;16S rDNA测序;疾病诊断模型
基金项目(Foundation):
北京市自然科学基金(7242136)
作者
周林熙;尹龙龙;崔小缓;毕欣欣;张延平;蒋兴旺;李丽娜
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