The Impact of Race/Ethnicity on Inflammation Regulation and Microbiome Interactions in Periodontitis

项目总结/摘要 在美国，牙周炎的患病率在墨西哥裔美国人（59.7%）和非西班牙裔美国人中最高。 黑人（56.6%）。严重牙周炎在这些人群中也更普遍;非西班牙裔黑人（14.7%） 墨西哥裔美国人（13.4%）。虽然种族和民族与牙周病有关 尽管这些疾病的发病率和严重程度不同，但缺乏令人信服的证据来说明生物因素的差异。 特异性促消退介质（SPMs）通过主动调节细胞内炎症反应， 免疫细胞和基质细胞通过特异性G蛋白偶联受体进行信号传导的活性。解决 SPMs诱导的炎症逆转实验性牙周炎中口腔微生物群的生态失调 模型SPM和SPM途径标记物与临床牙周炎和SPM异常相关 牙周炎的产生和功能不成比例地影响某些种族/族裔群体。的 还没有研究种族/民族对严重牙周炎炎症消退的影响。 本研究旨在调查墨西哥裔美国人严重急性炎症反应的分子特征， 牙周炎将招募四个受试者组：墨西哥裔美国人和白色严重 牙周炎（全身性，III/ IV期，B/C级），墨西哥裔美国人和白色美国人健康对照。 我们的初步数据支持这一假设，即患有严重牙周炎的墨西哥裔美国人 表现出不同的促进炎症的脂质介质，包括SPM，SPM途径标志物， 以及促炎脂质介质、SPM受体和相关的龈下微生物群落失调， 与白色美国人相比。提出了以下具体目标： 墨西哥裔美国人的SPM、SPM通路标记物、SPM受体和龈下微生物组的概况 和患有严重牙周炎的白色美国人。我们计划分析脂质介质水平，SPM受体 表达和龈下微生物组在多个生物样本中，包括牙龈，血浆，血清， 中性粒细胞、单核细胞和龈下菌斑。脂质介质水平和受体表达之间的相关性 和相对细菌丰度将通过生物标志物发现的数据集成分析进行分析 使用潜在成分（DIABLO）方法，该方法可以识别相关的关键分子或微生物 解决了传统统计方法不能识别的牙周炎症。 我们希望局部和全身的炎症反应和龈下组织的成分 墨西哥裔美国人的微生物组将不同于白色美国人。相关签名 这些受试者的脂质介质、SPM受体和牙龈下微生物组之间的关系也将是不同的。这些 结果将促进对炎症在疾病差异中的作用的理解。的 在相关性分析中鉴定的分子或微生物可以作为新疗法开发的目标。

Project Summary/ Abstract In the United States, the prevalence of periodontitis is greatest in Mexican Americans (59.7%) and non-Hispanic Blacks (56.6%). Severe periodontitis is also more prevalent in these populations; non-Hispanic Blacks (14.7%) and Mexican Americans (13.4%). Although race and ethnicity are associated with periodontal disease prevalence and severity, there is lack of convincing evidence of biological factors explaining the differences. Specialized pro-resolving mediators (SPMs) induce resolution of inflammation by actively regulating cellular activity of immune cells and stromal cells signaling through specific G protein–coupled receptors. Resolution of inflammation induced by SPMs reverses dysbiotic shifts of the oral microbiota in experimental periodontitis models. SPMs and SPM pathway markers are associated with clinical periodontitis and abnormalities in SPM production and function in forms of periodontitis disproportionately affecting certain racial/ethnic groups. The impact of race/ethnicity in resolution of inflammation in severe periodontitis has not been investigated. This study aims to investigate molecular profiles of resolution of inflammation in Mexican Americans with severe periodontitis. Four subject groups will be recruited; Mexican Americans and White Americans with severe periodontitis (generalized, stage III/ IV, grade B/C), Mexican American and White American healthy controls. The hypothesis, supported by our preliminary data, is that Mexican Americans with severe periodontitis will exhibit distinct profiles of lipid mediators that promote inflammation, including SPMs, SPM pathway markers as well as pro-inflammatory lipid mediators, SPM receptors, and an associated subgingival microbiome dysbiosis, compared to White Americans. The following specific aim is proposed: Characterize the local and systemic profiles of SPMs, SPM pathway markers, SPM receptors and the subgingival microbiome in Mexican Americans and White Americans with severe periodontitis. We plan to analyze lipid mediator levels, SPM receptor expression and the subgingival microbiome in multiple biological specimens including gingiva, plasma, serum, neutrophils, monocytes and subgingival plaque. Correlations between lipid mediator levels, receptor expression and relative bacterial abundance will be analyzed with the Data Integration Analysis for Biomarker discovery using a Latent compOnents (DIABLO) method, which can identify key molecules or microorganisms associated with resolution of periodontal inflammation which cannot be identified by traditional statistical methods. We expect that local and systemic resolution of inflammation profiles and composition of the subgingival microbiome in Mexican Americans will be different from those in White Americans. The correlation signatures between lipid mediator, SPM receptor and subgingival microbiome in these subjects will also be distinct. These results will advance the understanding of the role of resolution of inflammation in disease disparities. The identified molecules or microorganisms in the correlation analysis can be targeted for novel therapy development.