Investigation of Genetic Polymorphisms in BMP2, BMP4, SMAD6, and RUNX2 and Persistent Apical Periodontitis

• Published in: Journal of endodontics Vol. 47; no. 2; pp. 278 - 285
• Main Authors: Küchler, Erika Calvano, Hannegraf, Natascha Douat, Lara, Rafaela Mariana, Reis, Caio Luiz Bitencourt, Oliveira, Daniela Silva Barroso de, Mazzi-Chaves, Jardel Francisco, Ribeiro Andrades, Kesly Mary, Lima, Lorena Ferreira de, Salles, Alessandro Guimarães, Antunes, Livia Azeredo Alves, Sousa-Neto, Manoel Damião, Antunes, Leonardo Santos, Baratto-Filho, Flares
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 01-02-2021
• Subjects: Apical periodontitis; Bone Morphogenetic Protein 2 - genetics; Bone Morphogenetic Protein 2 - metabolism; Bone Morphogenetic Protein 4; Core Binding Factor Alpha 1 Subunit - genetics; genetic polymorphism; Genetic Predisposition to Disease; genetics; Humans; Periapical Periodontitis - diagnostic imaging; Periapical Periodontitis - genetics; Polymorphism, Single Nucleotide - genetics; Smad6 Protein - genetics; genetic polymorphism; genetics; Apical periodontitis
• ISSN: 0099-2399; 1878-3554
• DOI: 10.1016/j.joen.2020.11.014

This study aimed to evaluate the interplay among single-nucleotide polymorphisms (SNPs) in the encoding genes BMP2, BMP4, SMAD6, and RUNX2 in persistent apical periodontitis (PAP).
In this multicentric study, 272 patients diagnosed with pulp necrosis with apical periodontitis before root canal therapy who attended regular follow-up visits for at least 1 year were screened. Periapical radiographs and clinical aspects were evaluated, and the participants were classified as PAP (n = 110) or repaired (n = 162). Genomic DNA was used for the genotyping of the following SNPs: rs1005464 and rs235768 in bone morphogenetic protein 2 (BMP2), rs17563 in bone morphogenetic protein 4 (BMP4), rs2119261 and rs3934908 in SMAD family member 6 (SMAD6), and rs59983488 and rs1200425 in runt-related transcription factor 2 (RUNX2). The chi-square test was used to compare genotype distributions between groups. The multifactor dimensionality reduction method was applied to identify SNP-SNP interactions. The alpha for all the analysis was 5%.
The multifactor dimensionality reduction suggested the rs235768 in BMP2 and rs59983488 in RUNX2 as the best SNP-SNP interaction model (cross-validation = 10/10, testing balanced accuracy = 0.584, P = .026) followed by rs17563 in BMP4 and rs2119261 in SMAD6 (cross validation = 10/10, testing balanced accuracy = 0.580, P = .031). In the rs235768 in BMP2 and rs59983488 in RUNX2 model, the high-risk genotype was TT + TT (odds ratio = 4.36; 95% confidence interval, 0.44–42.1). In model rs17563 in BMP4 and rs2119261 in SMAD6, GG + TT (odds ratio = 2.63; 95% confidence interval, 0.71–11.9) was the high-risk genotype.
The interactions between rs235768 in BMP2 and rs59983488 in RUNX2 and between rs17563 in BMP4 and rs2119261 in SMAD6 are associated with PAP, suggesting that an interplay of these SNPs is involved in the higher risk of developing PAP.