Genomic approaches to the pathobiology and classification of periodontitis

牙周炎病理学和分类的基因组学方法

• 批准号: 8804756
• 负责人: PANOS N PAPAPANOU
• 金额: $ 24万
• 依托单位: COLUMBIA UNIVERSITY HEALTH SCIENCES
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-04-01 至 2017-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8804756
• 关键词: Algorithms; Anti-Bacterial Agents; Antibodies; Biopsy; Cataloging; Catalogs; Cells; Chronic; Chronic Disease; Classification; Clinical; Clinical assessments; Complex; Connective Tissue; DNA Methylation; Data; Data Set; Databases; Development; Differential Diagnosis; Disease; Elements; Epigenetic Process; Epithelial Cells; Fibroblasts; Funding; Gene Expression; Gene Expression Profile; Gene Expression Profiling; Gene Targeting; Genetic; Genome; Genomic approach; Genomics; Gingiva; Health; Heterogeneity; Homeostasis; Human; Immunoglobulin G; Individual; Inflammatory; Invaded; Knowledge; Lesion; MicroRNAs; Molecular; Molecular Diagnosis; Molecular Profiling; National Institute of Dental and Craniofacial Research; Oral cavity; Pathogenesis; Pathology; Patients; Pattern; Periodontal Diseases; Periodontitis; Phenotype; Physiological; Procedures; Process; Publications; Recording of previous events; Regulator Genes; Relative (related person); Sampling; Serological; Serum; Severities; Systems Biology; Tissue Sample; Tissues; Work; anticancer research; base; cell type; cohort; differential expression; disease classification; disorder subtype; epigenetic regulation; health data; insight; mRNA Expression; methylation pattern; novel; oral bacteria; pathogen; public health relevance; transcriptomics

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.

描述（由申请人提供）：在过去的十年中，我们的小组研究了牙龈组织中的转录组学概况。基于120例全身健康的中/重度牙周炎患者的样本，我们开发了第一个全面的牙龈组织基因表达的牙周健康和疾病的状态，并在目前公认的两种形式的牙周炎（慢性和侵略性）的编目。同时，我们已经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，龈下细菌概况和血清IgG抗体水平的几个口腔细菌，包括建立和推定的病原体和健康相关的物种。此外，我们还研究了转录组学数据库中涉及的相同牙龈组织样本中microRNA的表达，并确定了健康和患病组织中这些microRNA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，在同一数据库中添加了另一个表观遗传调控元素。在对现有基因组数据进行二次分析的建议中，我们首先计划使用去卷积算法重新分析我们的转录组数据集，以识别牙龈组织单个细胞成分特有的基因表达特征。接下来，我们将整合相同组织样本中的mRNA表达数据与miRNA表达和DNA甲基化谱，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，以确定控制牙龈健康和疾病以及牙周炎不同亚型的分子过程的主调控基因。总的来说，我们的研究将提高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疾病分子分类铺平道路。