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 ADD patients without a clinical diagnosis of epilepsy (ADD-noEpilepsy), those with a clinical diagnosis of epilepsy (ADD-Epilepsy) are characterized by greater abnormalities in typical cortical rsEEG activity altered in ADD patients such as delta and alpha rhythms.
Methods: We will recruit 40 ADD subjects: 20 ADD-noEpilepsy and 20 ADD-Epilepsy. Forty demographic matched healthy elderly (Nold) subjects will also be available in UNIROMA1 archive. The rsEEG data will be collected from 19 scalp electrodes placed following 10¿20 System. Individual alpha frequency peak (IAF) will be used to determine the delta, theta, alpha1, alpha2, and alpha3 frequency band ranges. Fixed beta1, beta2, and gamma bands will also be considered. eLORETA will estimate the rsEEG cortical sources. Statistical analysis at the group level (i.e. statistical comparisons among Nold ADD-noEpilepsy and ADD-Epilepsy 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 ADD-noEpilepsy and ADD-Epilepsy 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 ADD patients with MCI 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 ADD 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 ADD 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 ADD 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 ADD patients, thus improving drug discovery pathway.