Liver Proteome in Diabetes Type 1 Rat Model: Insulin-Dependent and -Independent Changes

• Autor(a) principal: Braga, Camila Pereira [UNESP]
• Data de Publicação: 2016
• Outros Autores: Boone, Cory H. T., Grove, Ryan A., Adamcova, Dana, Henrique Fernandes, Ana Angelica [UNESP], Adamec, Jiri, Padilha, Pedro de Magalhaes [UNESP]
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Institucional da UNESP
• DOI: 10.1089/omi.2016.0135
• Texto Completo: http://dx.doi.org/10.1089/omi.2016.0135; http://hdl.handle.net/11449/162279
• topic: biomarkers; bioinformatics; proteomics; personalized medicine

Diabetes mellitus type 1 (DM1) is a major public health problem that continues to burden the healthcare systems worldwide, costing exponentially more as the epidemic grows. Innovative strategies and omics system diagnostics for earlier diagnosis or prognostication of DM1 are essential to prevent secondary complications and alleviate the associated economic burden. In a preclinical study design that involved streptozotocin (STZ)-induced DM1, insulin-treated STZ-induced DM1, and control rats, we characterized the insulin-dependent and -independent changes in protein profiles in liver samples. Digested proteins were subjected to LC-MSE for proteomic data. Progenesis QI data processing and analysis of variance were utilized for statistical analyses. We found 305 proteins with significantly altered abundance among the control, DM1, and insulin-treated DM1 groups (p<0.05). These differentially regulated proteins were related to enzymes that function in key metabolic pathways and stress responses. For example, gluconeogenesis appeared to return to control levels in the DM1 group after insulin treatment, with the restoration of gluconeogenesis regulatory enzyme, FBP1. Insulin administration to DM1 rats also restored the blood glucose levels and enzymes of general stress and antioxidant response systems. These observations are crucial for insights on DM1 pathophysiology and new molecular targets for future clinical biomarkers, drug discovery, and development. Additionally, we underscore that proteomics offers much potential in preclinical biomarker discovery for diabetes as well as common complex diseases such as cancer, dementia, and infectious disorders.