Modelling of interaction between biomarkers in neurodegenerative diseases and nutrients
Date Issued
September 6, 2022
Type
Διδακτορική Διατριβή
Abstract
This current thesis is based on Bioinformatics and the use of computational tools to incorporate the nutrition data into proteomics and lipidomics research related to progression of Alzheimer’s disease (AD).Secondly, computational tools allow us to verify and better understanding the action of novel food molecules as promoters of medicinal activity. Initially, data were collected from literature to investigate how nutrients are associated with Alzheimer’s disease.Proteomic and lipidomic analysis revealed a significantly different expression of several proteins and lipids between AD,Mild cognitively impairment (MCI) and cognitively normal subjects.We then identified nutrients that potentially alter the proteomic and lipidomic profile as indicated from in vitro, animal and human studies. In the aspect of the reaseach the neuroprotective effects of polyphenols were displayed. Numerous polyphenolic compounds, maily flavonoids acted as amyloid β and AchE inhibitors with significant antioxidant and anti-inflammatory actions.With the aid of toxicity prediction models, toxicological end points of certain polyphenols were revealed through access on median lethal dose in rats and on toxicology classification of these molecules.Advanced softwares have been applied such as Swiss ADME web tool, the egan-BOILED EGG predictive model, the SwissTarget prediction software, the ProTox and the admet-SAR software. Among molecules tested, some flavonoids, melatonin, DHA and β-hydroxubutyrate presented no toxicity risk and high druglike nature with respect to ADMET properties and QSAR analysis.Then, a six- month personalized nutrition intervention was analysed and the results obtained were interpreted. Finally, the main findings of the research were summarized and future directions have been proposed.
Subjects