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肺结节患者唾液微生物菌群特征分析：一项前瞻性、非随机、同期对照试验

Analysis of Salivary Microbiota Characteristics in Patients With Pulmonary Nodules: A Prospective Nonrandomized Concurrent Controlled Trial

    摘要
  • 摘要:
      目的  发现并鉴定肺结节患者与健康人群唾液微生物菌群特征差异及其潜在作用，以期为肺结节早期预警提供新的候选生物标志物。
      方法  对肺结节（pulmonary nodule, PN）组（n=173）和健康对照（healthy control, HC）组（n=40）的唾液样本进行16S rRNA测序，比较两组人群唾液微生物群的多样性、组成和差异物种等特征，及其功能改变情况。使用随机森林算法识别唾液微生物标志物，并用曲线下面积（area under the curve, AUC）评估其对PN的预测效能。最后，基于PICRUSt2菌群功能预测分析，对唾液样本中差异基因的生物学功能及潜在作用机制进行初步探索。
      结果  与HC相比，PN组唾液样本的微生物α、β多样性较高（ P<0.05），且PN组唾液微生物的群落组成和丰度与HC组相比差异有统计学意义（P<0.05）。随机森林算法对差异微生物种进行筛选，Porphyromonas、Haemophilus和Fusobacterium构成了最优标志物集（AUC=0.79，95%置信区间：0.71～0.86），可有效区分PN。差异菌群的生物信息学功能显示，PN患者唾液微生物在免疫缺陷和氧化还原稳态相关的蛋白/分子功能表现出显著富集。群的生物信息学功能显示，PN患者唾液微生物在免疫缺陷和氧化还原稳态相关的蛋白/分子功能表现出显著富集。
      结论  唾液微生物群的变化与PN密切相关，其可能驱动了肺结节或肺“结癌转化”的发生，提示唾液微生物具有作为PN早期诊断新型无创体液标志物的潜力。

     

    Abstract:
      Objective  To uncover and identify the differences in salivary microbiota profiles and their potential roles between patients with pulmonary nodules (PN) and healthy controls, and to propose new candidate biomarkers for the early warning of PN.
      Methods  16S rRNA amplicon sequencing was performed with the saliva samples of 173 PN patients, or the PN group, and 40 health controls, or the HC group, to compare the characteristics, including diversity, community composition, differential species, and functional changes of salivary microbiota in the two groups. Random forest algorithm was used to identify salivary microbial markers of PN and their predictive value for PN was assessed by area under the curve (AUC). Finally, the biological functions and potential mechanisms of differentially-expressed genes in saliva samples were preliminarily investigated on the basis of predictive functional profiling of Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt2).
      Results  The α diversity and β diversity of salivary microbiota in the PN group were higher than those in the HC group (P<0.05). Furthermore, there were significant differences in the community composition and the abundance of oral microorganisms between the PN and the HC groups (P<0.05). Random forest algorithm was applied to identify differential microbial species. Porphyromonas, Haemophilus, and Fusobacterium constituted the optimal marker sets (AUC=0.79, 95% confidence interval: 0.71-0.86), which can be used to effectively identify patients with PN. Bioinformatics analysis of the differentially-expressed genes revealed that patients with PN showed significant enrichment in protein/molecular functions involved in immune deficiency and redox homeostasis.
      Conclusion  Changes in salivary microbiota are closely associated with PN and may induce the development of PN or malignant transformation of PN, which indicates the potential of salivary microbiota to be used as a new non-invasive humoral marker for the early diagnosis of PN.

     

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