Desenvolvimento de genossensor eletroquímico e aplicativo para o diagnóstico de transtorno depressivo maior em idosos baseado na detecção do microRNA-184 em plasma humano

• Ano de defesa: 2019
• Autor(a) principal: Guedes, Pedro Henrique Gonçalves
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Uberlândia; Brasil; Programa de Pós-graduação em Genética e Bioquímica
• Palavras-chave em Português: Depressão maior; Biossensor eletroquímico; TDM; Diagnóstico de depressão; VPD; EIE; Aplicativo DEPSENSOR; CNPQ::CIENCIAS BIOLOGICAS::BIOQUIMICA::BIOLOGIA MOLECULAR; CNPQ::CIENCIAS BIOLOGICAS::GENETICA
• Link de acesso: https://repositorio.ufu.br/handle/123456789/37734; http://dx.doi.org/10.14393/ufu.di

Depression consists of a ubiquitous psychiatric disorder and, in elderly, is the most common disease, causing serious consequences. The genetic mechanisms involved in major depressive disorder (MDD) are complex and involve inumerous genes. MicroRNAs (miRNAs) are small molecules involved in the post-transcriptional regulation of gene expression. Elderly diagnosed with MDD present down regulation of miRNA-184 expression compared to healthy elderly, then, this miRNA can be used as a biomarker for the MDD diagnosis. The MDD diagnostic methods depend primarily on clinical subjective identification, based on symptoms and variable scales. The present work introduces a new approach for the MDD diagnosis in elderly based on the development of an electrochemical biosensor, monitoring responses using differential pulse voltammetry (DPV) and electrochemical impedance spectroscopy (EIS) in human plasma samples. The DPV results, used for miRNA quantification, presented an increase of about twice in the peak current value of the samples for healthy patients, compared to patients with MDD when monitoring the DNA intercalator peak, ethidium bromide. For EIS, a 1.5 times increase in charge transfer resistance for healthy elderly subjects was observed compared to depressed patients. In addition, the analytical parameters of the biosensor were evaluated using DPV, obtaining an experimental detection limit of 10 amol L-1; the current response remained around 72% during the evaluated 50 days of stability; also it exhibited a great regeneration capacity, it was regenerated 10 times after the initial use of the bioelectrode. Moreover, the DEPSENSOR app was developed in Java in order to assist the sensor and it contains information about depression. Thus, the biosensor developed in the present study proved to be efficient in the diagnosis of MDD in elderly, as well as the accurate quantification of miRNA-184 in real plasma samples of healthy and depressed patients.