Investigation of the association of genetic variation regarding susceptibility to chronic periodontal disease by OpenArray

Abstract

Studies have reported that polymorphisms in genes, such as those encoding cytokines, may affect susceptibility to PD. To optimize the analysis of various single nucleotide (SNPs), high performance technologies, such as microarrays, have currently been employed. Although there are several studies focusing on the association of genetic polymorphisms with PD, further studies are still necessary because there were not identified polymorphisms that may be considered genetic markers of PD in the Brazilian population, beside the fact that many other genes with biological functions key (not just the immune system) were rarely or never studied. The objective of this study is to investigate SNPs in candidate genes in a Brazilian population composed of individuals with chronic periodontitis compared to healthy individuals, aiming to identify SNPs that may influence susceptibility to chronic PD. According to the sample size calculation, after detailed and complete periodontal examination, a total of at least 722 patients will be selected and divided into two groups according to the criteria defined by the CDC / AAP (Centers for Disease Control and Prevention / American Academy of Periodontology): (i) Group A (n = 361) patients with moderate or severe periodontitis; Group B (n = 361): patients with mild periodontitis and healthy patients. Each individual will undergo a mouth rinse with a glucose solution to be used for DNA extraction. For the selection of the SNPs, HAPLOVIEW program was used from the data bank of the International HapMap Project. 81 SNPs distributed among genes with Meta-analysis for PD, candidate genes from previous GWAS (Genome-Wide Association Study) or Bioinformatics studies, and genes related to the Th17 response and oxidative process will be investigated. Each SNP will be investigated through PCR reactions (Polymerase Chain Reaction) Real-Time, using the TaqMan® genotyping system OpenArrayTM (Applied Biosystems). The processing of data from genotyping and the calculation of allele frequencies (Minimum Frequency Allele - MAF) of the SNPs will be performed, as well as the Hardy-Weinberg equilibrium, and the degree of linkage disequilibrium between the SNPs. A multivariate logistic regression will be performed to adjust the results to variables such as age, gender and smoking habits, using the program R. The statistical results are corrected for multiple testing using the Bonferroni correction. It is expected that this work will have validation (or not) in our population of polymorphisms previously associated with PD, and novel results related to polymorphisms in our population not yet investigated. By detailed clinical examination and after robust statistical analysis, SNPs may be associated (or not) to the susceptibility and / or severity of PD. These results can effectively contribute to the quest of genetic markers for PD in our population. (AU)