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REN Yifeng, MA Qiong, LI Fang, et al. Analysis of Salivary Microbiota Characteristics in Patients With Pulmonary Nodules: A Prospective Nonrandomized Concurrent Controlled Trial[J]. Journal of Sichuan University (Medical Sciences), 2023, 54(6): 1208-1218. DOI: 10.12182/20231160103
Citation: REN Yifeng, MA Qiong, LI Fang, et al. Analysis of Salivary Microbiota Characteristics in Patients With Pulmonary Nodules: A Prospective Nonrandomized Concurrent Controlled Trial[J]. Journal of Sichuan University (Medical Sciences), 2023, 54(6): 1208-1218. DOI: 10.12182/20231160103

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

  •   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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