Potential common genetic susceptibility traits shared by chronic and apical periodontitis: focus on SNPs assessment followed by bioinformatics analysis including clinical, microbiological and inflammatory/immunological data

Abstract

Chronic periodontitis and periapical diseases are the leading cause for tooth loss in adults. Both periodontal and periapical lesions seem to share a common pathogenesis in which the establishment of a pathogenic microbiota (either in the gingival sulcus or the periapical region) triggers the host´s immune inflammatory response, which is in turn is responsible for the destruction of the tooth supporting tissues. The extent and severity of the inflammatory response to bacterial infection is at least partially under genetic control. Over the last decades, several single nucleotide polymorphisms (SNPs) have been implicated with increased susceptibility to periodontal destruction, but most studies on the subject rely on the "candidate gene" strategy and are inconclusive or lack of the necessary confirmatory replication in different populations. Recently, a new approach for the selection of susceptibility genes has been proposed with the use of genome wide association studies (GWA)-derived data. This strategy has the advantage of offering a hypothesis-free screening of the whole genome, identifying susceptibility genes that otherwise would have never been investigated. In addition, the inclusion of additional data on SNPs-based analysis, such as microbiological and immunological/inflammatory readouts, allows the inclusion of important variables involved in lesions pathogenesis usually ignored by regular genetic association studies. In this context, we propose to investigate the correlation between the SNPs that have been associated with increased susceptibility to suffer periodontal infection (especially by red and orange bacterial clusters, plus the putative pathogen A. actinomycetemcomitans, most of them also prevalent in periapical infections) in GWA studies with the occurrence of chronic periodontitis and periapical periodontitis. In addition, we intend to correlate those SNPs with the clinical, microbiological and inflammatory/immunological features of chronic and apical periodontitis under robust bioinformatics analysis. This project will be conducted at the University of Texas Health Science Center at Houston's School of Dentistry (UTheath); taking advantage of the expertise and computational resources of Center for Computational Biomedicine (CCB) UTHealth School of Biomedical Informatics, which possesses the material and human resources to conduct statistical analysis of complex data sets. In addition, we will count with the expertise and extensive experience in conducting genetic studies of UThealth's supervisor, Prof. Ariadne Letra. Briefly, in the chronic periodontitis study, we will analyze samples and data from 75 cases and 50 healthy controls, including clinical data, DNA genotyping data, inflammatory biomarkers quantification, and DNA-DNA hybridization checkerboard microbiological data. In the periapical lesion study, we will analyze samples and data from 75 patients presenting apical periodontitis and 100 healthy periapical tissue controls, including microbiological profiling, DNA genotyping, and inflammatory biomarkers quantification. The sample size was determined with basis on previous studies of our research group and with the use of specific power calculation software for genetic studies (CATS). In order to capture the full complexity of the interrelation between genotype, microenvironment and clinical features we will analyze the data using cluster analysis and multilevel hierarchical models. The knowledge gained from this research will certainly contribute to deepen our understanding of chronic and apical periodontitis' pathogenesis, as well as facilitate the identification of susceptibility traits and susceptible subjects, opening the possibility for the development of new preventive and therapeutic strategies.