Genomic approaches to the pathobiology and classification of periodontitis

描述(由申请者提供)：在过去的十年中，我们小组研究了牙龈组织的转录图谱。基于120名系统健康的中/重度牙周炎患者的样本，我们开发了第一个全面的牙周组织基因在牙周健康和疾病状态以及目前公认的两种牙周炎形式(慢性和侵袭性)中的表达目录。同时，我们开发了一个全面的表型数据库，包括人口统计数据、健康史、全口临床牙周数据、龈下细菌图谱和血清中几种口腔细菌的抗体水平，包括已确定和推定的病原体和与健康相关的物种。此外，我们还研究了参与转录数据库的同一牙龈组织样本中microRNAs的表达，并确定了这些microRNAs在健康组织和疾病组织中的靶基因。最后，我们刚刚完成了对这些样本中DNA甲基化模式的分析，将另一个表观遗传调控元素添加到同一数据库中。在这个对现有基因组数据进行二次分析的提案中，我们首先计划使用去卷积算法重新分析我们的转录数据集，以识别针对牙龈组织个别细胞成分的基因表达特征。下一步，我们将整合相同组织样本中的mRNA表达数据和miRNA表达以及DNA甲基化情况，以确定牙周病的分子亚型。我们的最后一步将是开发一种系统生物学方法来研究牙周炎的发病机制，通过使用算法来重建调控网络，然后可以询问这些调控网络来识别控制牙龈健康和疾病以及不同牙周炎亚型中表现的分子过程的主要调控基因。总而言之，我们的研究将增强我们对破坏性牙周炎的病理生物学的理解，并将为开发一种新的、分子分类的疾病铺平道路。

DESCRIPTION (provided by applicant): Over the past decade, our group has studied transcriptomic profiles in gingival tissues. Based on a sample of 120 systemically healthy patients with moderate/severe periodontitis, we have developed the first comprehensive cataloguing of gingival tissue gene expression in states of periodontal health and disease and in the two currently recognized forms of periodontitis (chronic and aggressive). In parallel, we have developed a comprehensive phenotypic database comprising demographic data, health history, full-mouth clinical periodontal data, subgingival bacterial profiles and serum levels of IgG antibodies to several oral bacteria including established and putative pathogens and health-associated species. In addition, we have studied the expression of microRNAs in the same gingival tissue samples involved in the transcriptomic database and have identified the target genes of these microRNAs in healthy and diseased tissues. Lastly, we have just completed the analyses of DNA-methylation patterns in these samples, appending another element of epigenetic regulation to the same database. In this proposal for secondary analyses of existing genomic data, we first plan to reanalyze our transcriptomic dataset using deconvolution algorithms to identify gene expression signatures that are specific to individual cellular components of the gingival tissues. Next, we will integrate mRNA expression data with miRNA expression and DNA methylation profiles in the same tissue samples, to identify molecular subtypes of periodontal disease. Our final step will be to develop a systems biology approach to the study of the pathogenesis of periodontitis, by using algorithms to reconstruct regulatory networks that can then be interrogated to identify master regulatory genes that control the molecular processes manifested in gingival health and disease and in different subtypes of periodontitis. Collectively, our studies will enhance our understanding of the pathobiology of destructive periodontitis, and will pave the way for the development of a novel, molecular classification of the disease.