study of neurobiological predictors of response to non-invasive neurostimulation and genetic susceptibility to dementia in patients with amnestic mild cognitive impairment

Conditions: Mild Cognitive Impairment

Summary: transcranial direct current stimulation is a non-invasive neuromodulatory technique that results in the clinical improvement of patients with mild cognitive impairment, a prodromal condition for the onset of dementia. the responses to treatment depend on the characteristics of the patients and the parameters adjusted in the equipment, which makes the modeling of electric fields imperative to maximize the safety profile and therapeutic potential of the technique. the study of neurobiological predictors of response to non-invasive neurostimulation and genetic susceptibility can elucidate current effects according to the individual's profile. the objectives of this study are to observe the effects of transcranial direct current stimulation with optimized/customized parameters in patients with amnestic ccl, considering the subjects' genetic susceptibility to alzheimer's disease and neurobiological markers. this is a randomized, triple-blind, sham-controlled clinical trial. neuropsychological tests and a sociodemographic and clinical questionnaire will be used to assess and characterize the subjects. participants captured by the laboratory of studies in aging and neuroscience at the federal university of paraíba will be divided into 02 groups, each with 25 patients, totaling 50 volunteers: active - participants who will receive real current; sham - participants who will receive simulated stimulation. participants entered through the eligibility criteria will be randomly allocated in a simple way, at a rate of 1:1. payment parameters will be customized by computational modeling with the aid of the simnibs program and nuclear magnetic resonance. the electroencephalogram and evaluation of polymorphisms of the gene encoding apolipoprotein e examined as predictors of response. data will be processed from the statistical package for social sciences® (20.0) software, applying the student test for continuous variables or chi-square for categorical variables. predictive analysis will be conducted from machine learning. it is expected to find improvements in the scores of memory and general cognition tests after the intervention protocol with tdcs with individualized dose in the group that will receive an intervention, compared to the simulated neurostimulation group. these obtained results optimize the practice, elucidating issues still present due to the different applications of the technique produced in the literature on the subject.

neuropsychological tests and a sociodemographic and clinical questionnaire will be used to assess and characterize the subjects. participants captured by the laboratory of studies in aging and neuroscience at the federal university of paraíba will be divided into 02 groups, each with 25 patients, totaling 50 volunteers: active - participants who will receive real current; sham - participants who will receive simulated stimulation. participants entered through the eligibility criteria will be randomly allocated in a simple way, at a rate of 1:1. payment parameters will be customized by computational modeling with the aid of the simnibs program and nuclear magnetic resonance. the electroencephalogram and evaluation of polymorphisms of the gene encoding apolipoprotein e examined as predictors of response.

Eligibility criteria:
inclusion criteria: * individuals diagnosed with mild cognitive impairment (mci); * both sexes; * aged 65 years or older, without a diagnosis of dementia will be included. exclusion criteria: * unstable medical conditions; * patients with metallic implants and pacemakers; * epileptics; * using drugs/alcohol, regular use of hypnotics and benzodiazepines up to two weeks before the start of the study; * people who have been using medication with cholinergic inhibitors for more than two months before this clinical trial

Keywords: mild cognitive impairment tdcs computational modeling