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.
We will further analyze an available integrated database that includes demographic, clinical, microbiological, serological, genomic and epigenetic data from 120 patients with moderate/severe periodontal disease, in a systems biology approach to the study of the pathobiology and classification of human periodontitis.
| Sawle, A D; Kebschull, M; Demmer, R T et al. (2016) Identification of Master Regulator Genes in Human Periodontitis. J Dent Res 95:1010-7 |
| Kebschull, Moritz; Papapanou, Panos N (2015) Mini but mighty: microRNAs in the pathobiology of periodontal disease. Periodontol 2000 69:201-20 |
| Papapanou, Panos N (2015) Systemic effects of periodontitis: lessons learned from research on atherosclerotic vascular disease and adverse pregnancy outcomes. Int Dent J 65:283-91 |
