Use of electroencephalography for the discovery of a functional marker of MCI converting to dementia. The AlzSM project.
Dr F Tamagnini
Prof G J Stephens
Dr G Stothart
Applications accepted all year round
Self-Funded PhD Students Only
Dementia is the main chronic disease leading to disability amongst the elder population worldwide and it currently represents a healthcare emergency at a global level. According to the data collected by the World Health Organization in the World Alzheimer’s Report 2015, the number of people with dementia worldwide was 47.47 million in 2015 and it was predicted that they will become 75.65 million by 2030 and 135 million by 2050. The prevalence of dementia worldwide increases with age, going from 1%-2% in 65 year-old people up to 30% at 85 year-old people.
Dementia and Mild Cognitive Impairment (MCI) have clinical syndromic features characterized by the deterioration of one or more cognitive domains (memory, attention, language, etc.). In the case of dementia, such impairments are such to cause a significant reduction of the ability to carry out day-to-day activities, while in patients with MCI there is no interference with the ability to carry out such activities. However, the MCI is a clinical state of great interest as it is considered the pre-clinical state leading to dementia.
The most frequent cause of dementia is Alzheimer’s Disease (AD) and MCI represents the prodromal phase of AD. Even if the pathogenesis of AD is unknown, its neuropathology hallmarks are represented by neurofibrillary tangles (expression of tauopathy) and senile plaques (expression of amyloidopathy). Several research groups have investigated the relationship between electrophysiological alterations (both at single cell and network level) and amyloidopathy or tauopathy, but these research efforts have been mainly carried out on animal models of AD.
Recently, George Stohtart et al (2015) characterized altered electrographic dynamics of people with AD or MCI versus control subjects, showing a potential relationship between such alterations and the different stages of the disease. In particular, people with AD showed a significant reduction of the amplitude of visually evoked potential (VEP) peaks P1 and N1 compared to the control group whereas people with MCI only showed a reduction of the N1 peak. In addition, the amplitude of the visual mismatch negativity (vMMN) potential highlighted a correlation with the progression of the disease. These findings raise the possibility of identifying electrophysiological markers that can be used in order to predict the progression towards a specific form of dementia.
Aim of the study
The main aim of the present study is to characterize and describe the alterations of clinical, instrumental and electrophysiological in AD, MCI and healthy controls.
The most innovative hypothesis of this study consists in the possible correlation between electrophysiological alterations and the disease progression (measured with longitudinal neuropsychological evaluation) in MCI patients. One further aim is to isolate predictive electrophysiological parameters, which could be used as early markers of the disease.
Role of the PhD candidate.
All the data for this study are being collected at the State Hospital of the Republic of San Marino. The role of the candidate will be to perform data analysis of the EEG and the VEP traces from patients included in each one of the 3 cohorts. The aim of the work is to identify an EEG/VEP based functional signature predictive of dementia and MCI, quantifying both the sensitivity (true positive rate) and specificity (true negative rate) of these measures for the diagnosis of the patient’s cognitive state.
• Applicants should hold or expect to gain a minimum of a 2:1 Bachelor Degree or equivalent.
• For informal enquiries please email Francesco Tamagnini at [Email Address Removed]
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