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dc.creatorOliveira, Francine Vilma-
dc.date.accessioned2026-02-05T13:25:51Z-
dc.date.available2026-02-05T13:25:51Z-
dc.date.issued2025-12-09-
dc.identifier.citationOLIVEIRA, Francine Vilma. Replicação da associação do rs79882996 no gene RANK com periodontite e análise epidemiológica endodôntica, com suporte da inteligência artificial, em uma mesma população. Orientadora: Tatiane de Oliveira Teixeira Muniz Carletto; Coorientadora: Camila Alexandrina Figueiredo. 2025. 137 f. Tese (Doutorado em Processos Interativos dos Órgãos e Sistemas) - Instituto de Ciências da Saúde, Universidade Federal da Bahia, Salvador (BA), 2025.pt_BR
dc.identifier.urihttps://repositorio.ufba.br/handle/ri/44004-
dc.description.abstractIntroduction: Periodontitis and apical periodontitis are multifactorial inflammatory diseases that result in bone resorption. In periodontitis, there is the destruction of the supporting tissues of the teeth. Environmental, behavioral, and especially genetic factors can influence its susceptibility and progression. Among the genes studied, RANK has stood out for its role in regulating bone remodeling. In apical periodontitis, there is resorption of periapical bone tissue, associated with infection and treated through endodontic therapy. Due to its frequently asymptomatic nature, screening by radiographs is essential, together with the analysis of the epidemiological profile of the population. In this scenario, artificial intelligence stands out as a promising tool in aiding diagnosis. Objective: To investigate genetic factors associated with periodontitis and epidemiological factors related to apical periodontitis and endodontic treatments in the same population. Material and Methods: The study included 527 adult individuals living in the Recôncavo Baiano, Bahia State, Brazil. Genotyping of rs79882996 was performed on 323 blood samples, using the GoTaq® Probe qPCR Master Mix kit (Promega) and TaqMan® SNP Genotyping Assays (Thermo Scientific™) probe, in a QuantStudio™ 12K Flex equipment (Applied Biosystems). Association analysis was conducted using the Plink 1.9 software, using multivariate logistic regression, with adjustment for age. Panoramic radiographs of all participants were analyzed to identify periapical lesions, endodontic treatment, or tooth absence, using the consensus of two experts and the AI software (DIO platform). A descriptive analysis of the population was performed and the diagnostic accuracy of the AI was evaluated using the parameters of sensitivity, specificity, positive predictive value, negative predictive value, accuracy, Receiver Operating Characteristic curves, and area under the curve. Results: rs79882996, located in the RANK gene, showed a significant association with periodontitis. In the additive model, each additional T allele was associated with a 64% increase in the chance of occurrence of periodontitis, while in the dominant model the presence of at least one T allele was associated with a 69% increase in the chance of developing the disease. The prevalence of periapical lesions was 30.85% and of endodontic treatments, 16.13%. The presence of these lesions was associated with worse oral health conditions. On the other hand, endodontic treatment was significantly related to higher education, higher income, previous guidance on oral hygiene, and flossing. In the diagnosis of periapical lesions, the area under the curve was 0.661 (95% CI = 0.606 – 0715), indicating low diagnostic accuracy on the part of AI; The sensitivity was 31.4%, the specificity 90.1%, the positive predictive value was 58.54%, while the negative predictive value reached 74.69%. AI showed high agreement with specialists in the identification of teeth with endodontic treatment (85.8%) and moderate agreement in the detection of periapical lesions (58.7%). Conclusion: This study reinforced the role of the RANK gene in periodontitis and highlighted its potential as a target for future therapies. In addition, this study showed the vulnerability of a population with limited access to dental treatment. AI has shown potential in tracking population oral health, but it still requires improvement, especially in the identification of periapical lesions.pt_BR
dc.description.sponsorshipConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), Chamada CNPq/MCTI/FNDCT Nº 18/2021 – UNIVERSALpt_BR
dc.description.sponsorshipNúcleo de Apoio Integrado à Pesquisa (NAIPe), edital FADBA/NAIPE nº1/2021, Cuidados à Saúde e Bem-estar da População Negra do Recôncavo Baiano, Portaria Institucional nº106, 14 de setembro de 2021, do Centro Universitário Adventista de Ensino do Nordeste (UNIAENE)pt_BR
dc.languageporpt_BR
dc.publisherUNIVERSIDADE FEDERAL DA BAHIApt_BR
dc.rightsAcesso Abertopt_BR
dc.subjectRANK ligantept_BR
dc.subjectPeriodontitept_BR
dc.subjectPeriodontite apicalpt_BR
dc.subjectInteligência artificialpt_BR
dc.subject.otherLigand RANKpt_BR
dc.subject.otherPeriodontitispt_BR
dc.subject.otherApical periodontitispt_BR
dc.subject.otherArtificial intelligencept_BR
dc.titleReplicação da associação do rs79882996 no gene RANK com periodontite e análise epidemiológica endodôntica, com suporte da inteligência artificial, em uma mesma populaçãopt_BR
dc.title.alternativeEvaluation of the association of the rs79882996 in the RANK gene with periodontitis and endodontic epidemiological analysis, with the support of artificial intelligence, in the same populationpt_BR
dc.typeTesept_BR
dc.publisher.programPrograma de Pós-Graduação em Processos Interativos dos Órgãos e Sistemas (PPGORGSISTEM) pt_BR
dc.publisher.initialsUFBApt_BR
dc.publisher.countryBrasilpt_BR
dc.subject.cnpqCNPQ::CIENCIAS DA SAUDE::ODONTOLOGIApt_BR
dc.contributor.advisor1Carletto, Tatiane de Oliveira Teixeira Muniz-
dc.contributor.advisor1IDhttps://orcid.org/0000-0001-7998-2569pt_BR
dc.contributor.advisor1Latteshttp://lattes.cnpq.br/4215212379864482pt_BR
dc.contributor.advisor-co1Figueiredo, Camila Alexandrina-
dc.contributor.advisor-co1IDhttps://orcid.org/0000-0003-1356-6188pt_BR
dc.contributor.advisor-co1Latteshttp://lattes.cnpq.br/4758550783703417pt_BR
dc.contributor.referee1Carletto, Tatiane de Oliveira Teixeira Muniz-
dc.contributor.referee1IDhttps://orcid.org/0000-0001-7998-2569pt_BR
dc.contributor.referee1Latteshttp://lattes.cnpq.br/4215212379864482pt_BR
dc.contributor.referee2Martins, Gabriela Botelho-
dc.contributor.referee2IDhttps://orcid.org/0000-0002-0917-4598pt_BR
dc.contributor.referee2Latteshttp://lattes.cnpq.br/0714029268066739pt_BR
dc.contributor.referee3Costa, Ryan dos Santos-
dc.contributor.referee3IDhttps://orcid.org/0000-0003-3075-0729pt_BR
dc.contributor.referee3Latteshttp://lattes.cnpq.br/5160677682637662pt_BR
dc.contributor.referee4Caponi, Lívia Silva Figueiredo e Ribeiro-
dc.contributor.referee4Latteshttp://lattes.cnpq.br/3905694837352790pt_BR
dc.contributor.referee5Ribeiro, Marlos Barbosa-
dc.contributor.referee5Latteshttp://lattes.cnpq.br/1953193517646332pt_BR
dc.creator.Latteshttp://lattes.cnpq.br/5432867735174709pt_BR
dc.description.resumoIntrodução: A periodontite e a periodontite apical são doenças inflamatórias multifatoriais que resultam em reabsorção óssea. Na periodontite, há a destruição dos tecidos de suporte dos dentes. Fatores ambientais, comportamentais e especialmente genéticos podem influenciar sua suscetibilidade e progressão. Entre os genes estudados, o RANK tem se destacado por seu papel na regulação da remodelação óssea. Já na periodontite, apical há a reabsorção do tecido ósseo periapical, associada à infecção e tratada por meio da terapia endodôntica. Devido à sua natureza frequentemente assintomática, torna-se essencial o rastreamento por radiografias, aliado à análise do perfil epidemiológico da população. Nesse cenário, a inteligência artificial se destaca como ferramenta promissora no auxílio ao diagnóstico. Objetivo: Investigar fatores genéticos associados à periodontite e fatores epidemiológicos relacionados à periodontite apical e tratamentos endodônticos, em uma mesma população. Material e Métodos: O estudo incluiu 527 indivíduos adultos, residentes no Recôncavo Baiano, Bahia, Brasil. A genotipagem do rs79882996 foi feita em 323 amostras de sangue, utilizando-se o kit GoTaq® Probe qPCR Master Mix (Promega) e sonda TaqMan® SNP Genotyping Assays (Thermo Scientific™), em equipamento QuantStudio™ 12K Flex (Applied Biosystems). A análise de associação foi conduzida no software Plink 1.9, por meio de regressão logística multivariada, com ajuste para idade. Analisaram-se radiografias panorâmicas de todos os participantes para identificação de lesão periapical, tratamento endodôntico ou ausência dentária, por meio do consenso de dois especialistas e do software de IA (plataforma DIO). Realizou-se análise descritiva da população e a precisão diagnóstica da IA foi avaliada por meio dos parâmetros de sensibilidade, especificidade, valor preditivo positivo, valor preditivo negativo, acurácia, curvas Receiver Operating Characteristic e área sob a curva. Resultados: O rs79882996, localizado no gene RANK, mostrou associação significativa com a periodontite. No modelo aditivo, cada alelo T adicional foi associado a um aumento de 64% na chance de ocorrência de periodontite, enquanto no modelo dominante a presença de pelo menos um alelo T esteve associada a um aumento de 69% na chance de desenvolvimento da doença. A prevalência de lesões periapicais foi de 30,85% e de tratamentos endodônticos, 16,13%. A presença destas lesões esteve associada a piores condições de saúde bucal. Já a realização de tratamento endodôntico foi significativamente relacionada à maior escolaridade, maior renda, orientação prévia sobre higiene bucal e uso de fio dental. No diagnóstico das lesões periapicais, a área sob a curva foi de 0,661 (IC 95% = 0,606 – 0715), indicando baixa acurácia diagnóstica por parte da IA; a sensibilidade foi de 31,4%, a especificidade 90,1%, o valor preditivo positivo foi de 58,54%, enquanto o valor preditivo negativo atingiu 74,69%. A IA mostrou alta concordância com os especialistas na identificação de dentes com tratamento endodôntico (85,8%) e concordância moderada na detecção de lesões periapicais (58,7%). Conclusão: Este estudo reforçou o papel do gene RANK na periodontite e destacou seu potencial como alvo para futuras terapias. Além disso, este estudo mostrou a vulnerabilidade de uma população com acesso limitado ao tratamento odontológico. A IA mostrou potencial no rastreamento da saúde bucal populacional, mas ainda requer aprimoramento, sobretudo na identificação de lesões periapicais.pt_BR
dc.publisher.departmentInstituto de Ciências da Saúde - ICSpt_BR
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