Background: 1) Temporal lobe Epilepsy and Alzheimer¿s disease (AD) show similarities of clinical interest. In AD, the incidence of convulsive seizures is 10 times higher than in the age-matched general population; 2) epilepsy is 87 times more frequent in AD patients with early- than late-onset disease and occurs particularly early in familial AD; 3) cognitive decline starts 5.5 years earlier in AD patients with epilepsy than AD controls; 4) cortical resting state eyes-closed electroencephalographic (EEG) activities at delta (about 2-4 Hz) and alpha (about 8-12 Hz) rhythms are abnormal in patients with dementia (ADD) and mild cognitive impairment (ADMCI) due to AD.
Aim: The present study will test the working hypothesis that compared with AD patients with mild cognitive impairment (ADMCI) and without EEG epileptiform activity (ADMCI-noEpil), those with EEG epileptiform activity (ADMCI-Epil) may be characterized by greater abnormalities in typical cortical rsEEG activity altered in AD patients with dementia such as delta and alpha rhythms.
Methods: We will recruit 40 ADMCI subjects: 20 ADMCI-noEpil and 20 ADMCI-Epil. Forty demographic matched healthy elderly (Nold) subjects will also be available in UNIROMA1 archive. eLORETA will estimate the rsEEG cortical sources from delta to gamma. Statistical analysis at the group level (i.e. statistical comparisons among Nold ADMCI-noEpil and ADMCI-Epil groups) will be carried out by the commercial tool STATISTICA 10 (StatSoft Inc, www.statsoft.com). Receiver operating characteristic curve (ROCC) will classify rsEEG sources across ADMCI-noEpil and ADMCI-Epil individuals. These classifications will be performed by GraphPad Prism software (GraphPad Software, Inc, California, USA).
World Alzheimer's Association Report 2018 stated that: (i) 47 million people live with dementia worldwide and will increase to 131 million by 2050; the large majority of them (60-80%) suffer from AD; (ii) the estimated worldwide cost of dementia is US$ 818 billion, and it will become a trillion-dollar disease by 2018. Therefore, if only 10% of AD patients suffer from epileptiform seizures related to some interference with cognitive information processing, 470,000 AD patients might benefit from anti-epileptic treatments already available based on standard EEG diagnostic criteria.
As a novel approach, the present project will implement an advanced methodological approach. For the first time, we will use the rsEEG data for the characterization of cortical source activities in AD patients with MCI (ADMCI) and clinical diagnosis of epilepsy. The expected results of the present project may open new avenues in understanding the relationship among epileptiform seizures, cognitive status, and disease evolution in ADMCI patients, clarifying cortical source activities related to the regulation of cerebral excitability and cognitive functions in those patients.
The originality of this project steams on probing neurophysiological mechanisms of neural hyper-synchronization of rsEEG sources at given frequencies as a neural underpinning of an over-excitation causing epileptiform seizures in ADMCI subjects, namely a new dimension of AD biomarkers that may guide an effective anti-epileptic regimen.
Furthermore, the expected findings may support heuristically the hypothesis that the presence of epilepsy should be routinely screened in ADMCI patients to be treated with possible beneficial effects on cognitive status and quality of life. The present rsEEG biomarkers may be used as surrogate neural endpoints to develop effective anti-epileptic treatments for ADMCI patients, thus improving drug discovery pathway.