Department of Dentistry and Oral Surgery, Osaka Medical College.
Department of Microbiology and Infection Control, Osaka Medical College.
J Atheroscler Thromb. 2022 Mar 1;29(3):403-421. doi: 10.5551/jat.60608. Epub 2021 Feb 19.
AIMS: Oral bacteria have been reported to be associated with the pathogenesis of atherosclerosis; however, the relationship between the oral microbiota and atherosclerosis remains unclear. The present study aimed to investigate whether or not salivary microbiota of patients with atherosclerotic cardiovascular disease (ACVD) differs from that of subjects without ACVD, and to characterize the salivary microbiota of patients with ACVD. METHODS: This study included 43 patients with ACVD and 86 age- and sex-matched non-ACVD individuals. 16S rRNA metagenomic analysis were performed using DNA isolated from the saliva samples of the participants. To select unique operational taxonomic unit (OTU) sets of ACVD, we conducted the random forest algorithm in machine learning, followed by confirmation via 10-fold cross-validation Results: There was no difference in richness or evenness between the ACVD and non-ACVD groups (alpha diversity; observed OTU index, p=0.503; Shannon's index, p=0.478). However, significant differences were found in the overall salivary microbiota structure (beta diversity; unweighted UniFrac distances, p=0.001; weighted UniFrac distances, p=0.001). The Actinobacteria phylum was highly abundant in patients with ACVD, while the Bacteroidetes phylum was less abundant. The random forest classifier identified 43 OTUs as an optimal marker set of ACVD. In a 10-fold cross validation using the validation data, an area under the curve (AUC) of 0.933 (95% CI, 0.855-1.000) was obtained. CONCLUSIONS: The salivary microbiota in patients with ACVD was distinct from that of non-ACVD individuals, indicating that the salivary microbiota may be related to ACVD.
目的:已有研究报道口腔细菌与动脉粥样硬化的发病机制有关;然而,口腔微生物群与动脉粥样硬化之间的关系尚不清楚。本研究旨在探讨动脉粥样硬化性心血管疾病(ACVD)患者的唾液微生物群是否与非 ACVD 患者不同,并描述 ACVD 患者的唾液微生物群特征。
方法:本研究纳入了 43 例 ACVD 患者和 86 名年龄和性别匹配的非 ACVD 个体。使用从参与者唾液样本中提取的 DNA 进行 16S rRNA 宏基因组分析。为了选择 ACVD 的独特操作分类单位(OTU)集,我们在机器学习中使用随机森林算法,然后通过 10 倍交叉验证进行确认。
结果:ACVD 和非 ACVD 组之间的丰富度或均匀度没有差异(α多样性;观察到的 OTU 指数,p=0.503;香农指数,p=0.478)。然而,唾液微生物群结构的总体差异显著(β多样性;未加权 UniFrac 距离,p=0.001;加权 UniFrac 距离,p=0.001)。厚壁菌门在 ACVD 患者中高度丰富,而拟杆菌门则较少。随机森林分类器将 43 个 OTU 确定为 ACVD 的最佳标记集。在使用验证数据的 10 倍交叉验证中,获得了 0.933(95%CI,0.855-1.000)的曲线下面积(AUC)。
结论:ACVD 患者的唾液微生物群与非 ACVD 个体不同,表明唾液微生物群可能与 ACVD 有关。
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