Shaoying Duan, Meiying Shao, Chenchen Zhang, Jialiang Zhao, Fangzhi Zhu, Nanyu Luo, Lei Lei, Ting Zhong, Tao Hu
{"title":"牙周状况和唾液微生物群是区分矽肺病的潜在指标:一项探索性研究。","authors":"Shaoying Duan, Meiying Shao, Chenchen Zhang, Jialiang Zhao, Fangzhi Zhu, Nanyu Luo, Lei Lei, Ting Zhong, Tao Hu","doi":"10.1186/s12866-024-03594-w","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Silicosis has always been a serious global occupational health problem. Oral microbiota plays important roles in the development of lung disease. However, few studies have investigated the relationship between periodontal conditions, oral bacteria and silicosis disease.</p><p><strong>Method: </strong>A single-center and cross-sectional study was conducted in 2019 in Sichuan Province, China, including a small sample of silicosis patient group and healthy control group. Demographic data and periodontal examinations measured by clinical attachment loss (CAL), bleeding on probing (BOP) and periodontal pocket (PD) were collected from each participant. Phenotypic changes were detected by histopathological staining. Next-generation sequencing targeting 16S ribosomal RNA was targeted to decipher the salivary microbiome of the two groups. Random forest, Least Absolute Shrinkage and Selection Operator (LASSO) logistic regression and multivariable logistic regression analysis were conducted to find potential indicators to distinguish silicosis.</p><p><strong>Results: </strong>In general, 29 male healthy controls and 24 male silicosis patients were included. The proportion of CAL ≥ 3 mm in silicosis group was greater than control group, while the proportion of BOP (+) and PD ≥ 4 mm was reduced in silicosis group. The α-smooth muscle actin and fibronectin expression increased in gingiva of patients. The composition of salivary microbiota exhibited significant differences between the two groups, with silicosis patients demonstrating a lower diversity of salivary microbiota. Genus of Aggregatibacter [odds ratio (OR) = 0.000, p = 0.003] and Catonella (OR = 0.000, p = 0.049) were identified as biomarkers to distinguish silicosis.</p><p><strong>Conclusions: </strong>The silicosis group exhibited worse CAL, improved BOP and PD, which may be related to the gingival fibrosis found in this study. The composition of the oral microbiota underwent significant changes, accompanied by a decrease in diversity, in patients with silicosis. Our study indicates that respirable crystalline silica exposure affects oral health, and alterations of oral microbiota might be implicated in silicosis. We primarily identified Aggregatibacter and Catonella as the potential indicators to distinguish silicosis patients from healthy controls.</p>","PeriodicalId":9233,"journal":{"name":"BMC Microbiology","volume":"24 1","pages":"438"},"PeriodicalIF":4.0000,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11514746/pdf/","citationCount":"0","resultStr":"{\"title\":\"Periodontal conditions and salivary microbiota are potential indicators to distinguish silicosis: an exploratory study.\",\"authors\":\"Shaoying Duan, Meiying Shao, Chenchen Zhang, Jialiang Zhao, Fangzhi Zhu, Nanyu Luo, Lei Lei, Ting Zhong, Tao Hu\",\"doi\":\"10.1186/s12866-024-03594-w\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Silicosis has always been a serious global occupational health problem. Oral microbiota plays important roles in the development of lung disease. However, few studies have investigated the relationship between periodontal conditions, oral bacteria and silicosis disease.</p><p><strong>Method: </strong>A single-center and cross-sectional study was conducted in 2019 in Sichuan Province, China, including a small sample of silicosis patient group and healthy control group. Demographic data and periodontal examinations measured by clinical attachment loss (CAL), bleeding on probing (BOP) and periodontal pocket (PD) were collected from each participant. Phenotypic changes were detected by histopathological staining. Next-generation sequencing targeting 16S ribosomal RNA was targeted to decipher the salivary microbiome of the two groups. Random forest, Least Absolute Shrinkage and Selection Operator (LASSO) logistic regression and multivariable logistic regression analysis were conducted to find potential indicators to distinguish silicosis.</p><p><strong>Results: </strong>In general, 29 male healthy controls and 24 male silicosis patients were included. The proportion of CAL ≥ 3 mm in silicosis group was greater than control group, while the proportion of BOP (+) and PD ≥ 4 mm was reduced in silicosis group. The α-smooth muscle actin and fibronectin expression increased in gingiva of patients. The composition of salivary microbiota exhibited significant differences between the two groups, with silicosis patients demonstrating a lower diversity of salivary microbiota. Genus of Aggregatibacter [odds ratio (OR) = 0.000, p = 0.003] and Catonella (OR = 0.000, p = 0.049) were identified as biomarkers to distinguish silicosis.</p><p><strong>Conclusions: </strong>The silicosis group exhibited worse CAL, improved BOP and PD, which may be related to the gingival fibrosis found in this study. The composition of the oral microbiota underwent significant changes, accompanied by a decrease in diversity, in patients with silicosis. Our study indicates that respirable crystalline silica exposure affects oral health, and alterations of oral microbiota might be implicated in silicosis. We primarily identified Aggregatibacter and Catonella as the potential indicators to distinguish silicosis patients from healthy controls.</p>\",\"PeriodicalId\":9233,\"journal\":{\"name\":\"BMC Microbiology\",\"volume\":\"24 1\",\"pages\":\"438\"},\"PeriodicalIF\":4.0000,\"publicationDate\":\"2024-10-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11514746/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"BMC Microbiology\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.1186/s12866-024-03594-w\",\"RegionNum\":2,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"MICROBIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"BMC Microbiology","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1186/s12866-024-03594-w","RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MICROBIOLOGY","Score":null,"Total":0}
引用次数: 0
摘要
背景:矽肺病一直是全球严重的职业健康问题。口腔微生物群在肺部疾病的发生发展中起着重要作用。然而,很少有研究调查牙周状况、口腔细菌与矽肺病之间的关系:方法:于2019年在中国四川省进行了一项单中心横断面研究,包括矽肺患者组和健康对照组的小样本。收集每位受试者的人口统计学数据和牙周检查结果,包括临床附着丧失(CAL)、探诊出血(BOP)和牙周袋(PD)。通过组织病理学染色检测表型变化。以 16S 核糖体 RNA 为目标的下一代测序用于解密两组患者的唾液微生物组。通过随机森林、最小绝对缩减和选择操作器(LASSO)逻辑回归和多变量逻辑回归分析,寻找区分矽肺的潜在指标:共纳入29名男性健康对照组和24名男性矽肺病患者。矽肺组 CAL ≥ 3 mm 的比例高于对照组,而 BOP (+) 和 PD ≥ 4 mm 的比例在矽肺组有所降低。患者牙龈中α-平滑肌肌动蛋白和纤连蛋白表达增加。两组患者唾液微生物群的组成存在显著差异,矽肺患者唾液微生物群的多样性较低。Aggregatibacter [odds ratio (OR) = 0.000, p = 0.003] 和 Catonella (OR = 0.000, p = 0.049)被确定为区分矽肺病的生物标志物:结论:矽肺病组的 CAL 更差,BOP 和 PD 改善,这可能与本研究中发现的牙龈纤维化有关。矽肺患者口腔微生物群的组成发生了显著变化,同时多样性也有所下降。我们的研究表明,接触可吸入结晶二氧化硅会影响口腔健康,而口腔微生物群的改变可能与矽肺病有关。我们主要发现,Aggregatibacter 和 Catonella 是区分矽肺病患者和健康对照组的潜在指标。
Periodontal conditions and salivary microbiota are potential indicators to distinguish silicosis: an exploratory study.
Background: Silicosis has always been a serious global occupational health problem. Oral microbiota plays important roles in the development of lung disease. However, few studies have investigated the relationship between periodontal conditions, oral bacteria and silicosis disease.
Method: A single-center and cross-sectional study was conducted in 2019 in Sichuan Province, China, including a small sample of silicosis patient group and healthy control group. Demographic data and periodontal examinations measured by clinical attachment loss (CAL), bleeding on probing (BOP) and periodontal pocket (PD) were collected from each participant. Phenotypic changes were detected by histopathological staining. Next-generation sequencing targeting 16S ribosomal RNA was targeted to decipher the salivary microbiome of the two groups. Random forest, Least Absolute Shrinkage and Selection Operator (LASSO) logistic regression and multivariable logistic regression analysis were conducted to find potential indicators to distinguish silicosis.
Results: In general, 29 male healthy controls and 24 male silicosis patients were included. The proportion of CAL ≥ 3 mm in silicosis group was greater than control group, while the proportion of BOP (+) and PD ≥ 4 mm was reduced in silicosis group. The α-smooth muscle actin and fibronectin expression increased in gingiva of patients. The composition of salivary microbiota exhibited significant differences between the two groups, with silicosis patients demonstrating a lower diversity of salivary microbiota. Genus of Aggregatibacter [odds ratio (OR) = 0.000, p = 0.003] and Catonella (OR = 0.000, p = 0.049) were identified as biomarkers to distinguish silicosis.
Conclusions: The silicosis group exhibited worse CAL, improved BOP and PD, which may be related to the gingival fibrosis found in this study. The composition of the oral microbiota underwent significant changes, accompanied by a decrease in diversity, in patients with silicosis. Our study indicates that respirable crystalline silica exposure affects oral health, and alterations of oral microbiota might be implicated in silicosis. We primarily identified Aggregatibacter and Catonella as the potential indicators to distinguish silicosis patients from healthy controls.
期刊介绍:
BMC Microbiology is an open access, peer-reviewed journal that considers articles on analytical and functional studies of prokaryotic and eukaryotic microorganisms, viruses and small parasites, as well as host and therapeutic responses to them and their interaction with the environment.