Salivary molecular spectroscopy: a label free and non-invasive diagnostic tool for Obstructive Sleep Apnea

• Ano de defesa: 2020
• Autor(a) principal: Bacchin, Fernanda
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: eng
• Instituição de defesa: Universidade Federal de Uberlândia; Brasil; Programa de Pós-graduação em Odontologia
• Palavras-chave em Português: ATR-FTIR; Biomarkers; Biomarcadores; Crianças; Diagnóstico; AOS; Saliva; Children; Diagnosis; OSA; CNPQ::CIENCIAS DA SAUDE
• Link de acesso: https://repositorio.ufu.br/handle/123456789/29176

The aim of this study was to investigate whether specific biomarkers can be identified in the saliva of children with OSA, and whether the vibrational modes expressed differentially, can be predictors of diagnosis for OSA. Currently, the diagnosis of OSA is performed through PSG, which is an expensive test, difficult to perform and is not a reality in a public health system. Consequently, the search for a cheaper, more accessible and OSA specific diagnostic method is of great interest. To this end, this study investigated the potential application of Fourier transform infrared spectroscopy with attenuated total reflectance (ATR-FTIR) to discriminate children with OSA from paired controls using saliva. Saliva was collected from 40 children, 26 children with OSA and 14 healthy controls matched (without OSA). Clinical and physical examinations and the OSA-18 and SBQ questionnaires were applied to all 40 children. Only patients with OSA underwent polysomnography and all had their stimulated saliva samples collected after night sleep. The salivary profile was analysed by ATR-FTIR spectroscopy and the vibrational modes were evaluated for diagnostic capacity using the ROC curve. The salivary infrared spectrum of Non-OSA and OSA children showed several unique vibrational modes and, of these, five vibrational modes in 2962, 1670, 1638, 1548 and 1075 cmˉ¹ were pre-validated as potential diagnostic biomarkers by the analysis of the ROC curve with AUC greater than 0.8 in the analysis of the ROC curve. Thus, it is concluded that the salivary spectral biomarkers discovered using univariate analysis can provide a new robust alternative for OSA monitoring, using green and non-invasive technology.