Perfil proteômico da urina para detecção de potenciais biomarcadores para a doença renal crônica

Detalhes bibliográficos
Ano de defesa: 2024
Autor(a) principal: Silva, Nathália Rabello
Orientador(a): Não Informado pela instituição
Banca de defesa: Não Informado pela instituição
Tipo de documento: Dissertação
Tipo de acesso: Acesso embargado
Idioma: por
Instituição de defesa: Universidade Federal de Uberlândia
Brasil
Programa de Pós-graduação em Ciências da Saúde
Programa de Pós-Graduação: Não Informado pela instituição
Departamento: Não Informado pela instituição
País: Não Informado pela instituição
Palavras-chave em Português:
Link de acesso: https://repositorio.ufu.br/handle/123456789/42078
http://doi.org/10.14393/ufu.di.2024.5040
Resumo: Introduction: The growing number of people with chronic kidney disease (CKD), caused mainly by changes in lifestyle and the aging of the population, demonstrates the need to identify new biomarkers that enable the monitoring of the progression of CKD and, consequently, the prediction for end-stage renal disease (ESRD). Objective: To analyze the proteomic profile in urine samples from healthy individuals and those in the final stage of the disease to identify potential biomarkers for CKD. Methodology: Urine samples were collected from 10 healthy individuals and 10 with end-stage CKD. These samples were analyzed according to the following steps of the shotgun methodology: protein precipitation, colorimetric detection and protein measurement, in-solution digestion and peptide desalting. Next, the peptides were analyzed using liquid chromatography equipment coupled to a tandem mass spectrometer and, finally, bioinformatics, gene ontology and protein interaction research was carried out. Results: 416 proteins were identified in the proteomic profile of the analyzed groups and 19 proteins showed statistically significant differences between the groups. Of these, five proteins (hemopexin, beta-2-microglobulin, retinol-binding protein 4, transthyretin and factor D) were considered potential biomarkers for CKD. Conclusion: The proteins found were able to characterize and differentiate the urinary proteomic profiles of the two groups. Also, the five selected proteins can be seen as potential candidates for CKD biomarkers.