Early diagnosis of Alzheimer's disease : focus on quantitative EEG in relation to genetic, biochemical and neuroimaging markers

Abstract: The main aims of this thesis were to explore whether quantitative EEG (qEEG) variables could be considered as positive markers of Alzheimer's disease (AD) and sensitive indices of disease progression and treatment effects, as well as to determine their relation to currently existing genetic, biochemical and neuroimaging markers. The main findings of seven subsequent studies are summarized as follows: 1) Combined alpha and theta relative power and temporo-parietal alpha band coherence were the best combination of qEEG variables for the discrimination of mild to moderate AD patients and healthy controls, giving 89% overall correct classification accuracy. Subjects with mild cognitive impairment (MCI), either objective or subjective, that have been misclassified as AD patients on the basis of these EEG variables might be at risk for developing the disease. 2) The APOE [epsilon]4 allele did not influence disease severity as measured by alpha/theta ratio, an index of EEG slowing, and by the cerebral metabolic rate of glucose (CMRGlu) as measured by Positron Emission Tomography (PET). 3) The APOE [epsilon]4 allele was associated with selective decreases in functional connectivity as assessed by EEG coherence in postrolandic derivations. This finding generated a new hypothesis of coexisting subclinical vascular pathology, since postrolandic EEG coherence was reported to be reduced in vascular dementia and related to white matter hyperintensities. 4) There was an association between EEG slowing and CSF tau as an indirect marker of tau-related pathology in AD patients. The pattern of inverse correlation suggested a complex dynamic change in CSF tau levels: increases in early stages and decreases with longer duration of illness following massive neuronal death. 5) A strong tendency towards reduced alpha/theta ratio was observed in subjects with only mild cognitive dysfunction, while CSF tau levels in this group did not differ from healthy controls. 6) Longitudinal changes in qEEG variables during long-term treatment with the acetylcholinesterase (AChE) inhibitor tacrine showed two main effects with separate time courses. There was an early decrease in delta and theta Global Field Power (GFP) after 3 and 6 months, with a shift towards baseline values after 12 months of treatment. After 12 months a significant reduction in beta 1 and beta 2 GFP was observed which may be an early indicator of declining treatment efficiency possibly caused by AChE promoted feedback following long-term tacrine treatment. 7) Quantitative EEG and PET have comparable overall discrimination accuracies for mild AD patients and controls, of 80 and 85%, respectively. PET correctly classified all controls while a single EEG variable (theta relative power) misclassified 4 of 14 controls. However, the discriminating accuracy of qEEG may be higher since controls misclassified as AD patients performed significantly worse than correctly classified controls on tests representing visuospatial functions and attention. 8) A longitudinal study of 27 subjects with MCI showed that 54% developed AD after a mean follow-up period of 21 months. Subjects who deteriorated had significantly higher theta relative power and lower mean frequency after the follow-up. This means that these variables are sensitive state markers of the progression of the disease in its early stages. Combined alpha and theta relative power and the mean frequency, controlled for the baseline MMSE in a logistic regression model, were the best predictors of MCI outcome, giving 85% classification accuracy. In conclusion, our results support the inclusion of qEEG in the diagnostic work-up of AD. qEEG variables combined with the clinical judgment and other available biomarkers could increase diagnostic accuracy. They can also be used in initial staging of the disease severity, monitoring the course and predicting the outcome in subjects at risk of developing the disease. When included in the initial assessment qEEG could provide a baseline for the evaluation of treatment efficiency.