| Grant number: | 19/00213-0 |
| Support Opportunities: | Scholarships in Brazil - Scientific Initiation |
| Start date: | June 01, 2019 |
| End date: | May 31, 2020 |
| Field of knowledge: | Health Sciences - Medicine - Medical Clinics |
| Principal Investigator: | Iscia Teresinha Lopes Cendes |
| Grantee: | Alexandre Barcia de Godoi |
| Host Institution: | Faculdade de Ciências Médicas (FCM). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil |
| Associated research grant: | 13/07559-3 - BRAINN - The Brazilian Institute of Neuroscience and Neurotechnology., AP.CEPID |
Abstract Epilepsies are defined as a set of chronic disorders characterized by changes in the pattern of electrical discharges generated by the brain. Among the most diverse types of epilepsies, Mesial Temporal Lobe Epilepsy (MTLE) stands out due to its prevalence and the high presence of resistance to pharmacological treatments. Because of the difficulty in predicting which patients will be resistant to drug therapy, alternative treatments to reduce seizures, such as surgeries, may take many years to be indicated. Therefore, the search for new biomarkers of pharmacological resistance is necessary. The metabolomic approach allows us to access the metabolic products of the phenotypic state and to analyze the drug metabolism profile. It also has high sensitivity and specificity in the detection of these analytes. The aim of this project is to analyze the plasma metabolic profile of controls (individuals without a background of epilepsy) and patients with MTLE, divided into two treatment response groups: responsive and resistant, in order to identify biomarkers that may aid in the prediction of pharmacoresistance. The metabolome of patients will be analyzed using the Nuclear Magnetic Resonance Spectroscopy of H¹ (NMR-H) technique, which allows the analysis of complex samples without the need for chromatographic techniques and allows a simpler quantitative analysis of metabolite concentrations. The profiles obtained from both groups of patients will be compared using MestreNova, Matlab, Metaboanalyst and HMDB databases to identify metabolites that may help in the prediction of drug refractoriness in patients with MTLE. | |
| News published in Agência FAPESP Newsletter about the scholarship: | |
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