Early Markers of Aggressive Periodontitis

描述（由申请人提供）：局部侵袭性牙周炎影响了70，000名美国儿童，主要来自服务不足的社区。如果不及时治疗，可能会发生因牙齿脱落而导致的社会和心理耻辱。本研究旨在确定侵袭性牙周炎（eMAPs）的早期标志物。将随着时间的推移检查风险标志物，包括伴放线菌聚集菌（Aa）、其他微生物和宿主反应元素。青少年将进行筛选，以选择一个平衡的队列，250个aa阳性和250个aa阴性牙周健康的学生将被招募和随访2年。本研究的目的是检测骨丢失（BL）临床证据之前的微生物和宿主生物标志物，旨在开发一种椅旁诊断系统，用于快速识别易感受试者。到目前为止，我们已经开发了一种测试，允许立即椅边鉴定受试者与Aa，和测试相关的BL趋化因子。然而，我们的数据表明，Aa单独是不够的诊断，巨噬细胞炎症蛋白1-α（MIP-1？）而新的和与BL相关的可以通过发现鉴定早期事件的标记物来改进。将每3个月进行一次颊上皮细胞（BEC）、唾液、牙菌斑和裂隙液的临床测量和采样。将前瞻性分析储存样本，以评估BL（Aa和MIP-1？）之前的宿主和微生物生物标志物（唾液、龈沟和微生物元素）并预测受试者（AIM 1a）和部位（AIM 1b）的骨丢失，然后当受试者（AIM 2a）和部位出现BL的放射学体征（AIM 2b）时，回顾性地确定早于BL的新生物标志物。目的1a评估口腔细胞上的Aa与唾液MIP-1（一种破骨细胞启动子）结合是否可以作为个体发展成牙周炎的预测诊断标志物。AIM 1b评估了以下水平：1）拟议的拮抗剂（龈下细菌的集合体，包括Aa，S。parasanguinis和F. alocis），和2）宿主反应元件（裂隙MIP-1作为6-9个月内牙齿部位BL时间依赖性风险的预测标志物。AIM 2检查比AIM 1中检测的标记物更早出现的宿主和微生物标记物。检测BL后，将检测3、6、9和12个月前采集的样本中的唾液和微生物因子，这些因子可促进受试者水平上BEC上聚生体的定殖（AIM 2a）。在研究中心层面，我们将研究组成龈下细菌联合体的单个细菌的编排和时间，以确定以前未检测到的细菌（使用NextGen测序）是否也可能参与疾病的发生。此外，将分析早期、中期和晚期宿主细胞因子在缝隙液中出现的顺序时间，以确定 生物标志物（AIM 2b）在AIM 1中研究的标志物之前出现在BL位点。我们的前提是，所获得的知识可以提供敏感和特异的生物标志物，可以取代目前在实践中使用的诊断工具。以这种方式，可以在疾病的最早阶段识别处于风险中的受试者，使得可以制定成本有效的策略， 减少口腔健康差距。

DESCRIPTION (provided by applicant): Localized aggressive periodontitis (LAP) affects 70,000 US children, largely from underserved communities. If untreated social and psychological stigma resulting from tooth loss can occur. This study is designed to identify early markers of aggressive periodontitis (eMAPs). Risk markers that include Aggregatibacter actinomycetemcomitans (Aa), other microbes, and host response elements will be examined over time. Adolescents will be screened to select a balanced cohort of 250 Aa-positive and 250 Aa-negative periodontally healthy students who will be enrolled and followed for 2 years. The purpose of this study is to detect microbial and host biomarkers that precede clinical evidence of bone loss (BL) with the aim of developing a chair-side diagnostic system for rapid identification of susceptible subjects. Thus far, we have developed a test that permits immediate chair-side identification of subjects with Aa, and a test for chemokines related to BL. However, our data indicates that Aa alone is not sufficient for diagnosis, and macrophage inflammatory protein 1-alpha (MIP-1?) while novel and related to BL can be improved upon by finding markers that identify earlier events. Clinical measurements and sampling of buccal epithelial cells (BECs), saliva, plaque, and crevice fluid will be performed every 3 months. Stored samples will be analyzed prospectively to assess host and microbial biomarkers (salivary, crevicular and microbial elements) that predate BL (Aa and MIP-1?) and predict bone loss in a subject (AIM 1a) and at a site (AIM 1b), and then to retrospectively determine new biomarkers that predate BL when a subject (AIM 2a) and a site develops radiographic signs of BL (AIM 2b). AIM 1a assesses whether Aa on buccal cells in combination with salivary MIP-1�an osteoclast promoter, can serve as predictive diagnostic markers for individuals who will develop LAP. AIM 1b assesses levels of: 1) the proposed antagonists (a consortium of subgingival bacteria including Aa, S. parasanguinis and F. alocis), and 2) host response element (crevicular MIP-1� as predictive markers of time-dependent risk for BL at a tooth sites within 6-9 months. AIM 2 examines host and microbial markers that appear earlier than markers tested in AIM 1. After detection of BL, samples taken 3, 6, 9, and 12 months earlier will be tested for salivary and microbial factors that could promote colonization of the consortium on BECs at the subject level (AIM 2a). At the site level we will study the orchestration and timing of individual bacteria that make up the subgingival LAP consortium to determine if previously undetected bacteria (using NextGen sequencing) may also be involved in disease initiation. Further, sequential timing of early, middle, and late host cytokines as they appear in crevice fluid will be analyzed to identify biomarkers (AIM 2b) appearing at a BL site in advance of markers studied in AIM 1. Our premise is that the knowledge gained can provide sensitive and specific biomarkers that can supplant diagnostic tools used currently in practice. In this manner, subjects at risk can be identified in the earliest stages of disease so that cost-effective strategies can be instituted to reduce oral health disparities.