Quantitative Electroencephalography and genetics as biomarkers of dementia in Parkinson’s disease

The importance of cognitive decline in Parkinson’s disease (PD), which eventually progresses to dementia (PD-D) in the majority of surviving patients, has been widely recognised during the last decade. PD-D is associated with a twofold increase in mortality, increased caregiver strain and increased healthcare costs. Thus, early and correct identification of the PD patients with a risk of dementia is a challenging problem of neurology, which has led to the suggestion of various markers of cognitive decline in PD. If validated, these markers would offer the opportunity for disease modification and therapeutic intervention at a critical early stage of the illness, when the viable neuronal population is greater. The focus of this thesis was to assess how various factors - quantitative electroencephalography (qEEG) changes, genetics, deep brain stimulation (DBS), olfactory function, etc. – may be related with the risk of cognitive decline in PD patients. We performed four clinical studies with various design. These studies included PD patients who were dementia-free on inclusion, and control participants. Principal findings are the following: (1) increase of global median relative power theta (4–8 Hz), executive and working memory dysfunction are independent prognostic markers of severe cognitive decline in PD patients over a period of 3 years. (2) DBS of the subthalamic nuclei in a group of PD patients with mean age 63.2 years, in comparison with a group of younger patients (52.9 years), causes higher incidence of psychiatric events over 2 years of observation. However, these events were transient and did not outweigh the benefits of surgery. (3) Worsening of verbal fluency performance is an early cognitive outcome of DBS of the subthalamic nuclei in PD patients. (4) Among early appearing non-motor signs of Parkinson’s disease, alteration of olfaction but not EEG spectrum correlates with motor function. (5) A composite score approach seems to be a realistic goal in the search for biomarkers of severe cognitive decline

Quantitative EEG and Cognitive Decline in Parkinson’s Disease

Cognitive decline is common with the progression of Parkinson’s disease (PD). Different candidate biomarkers are currently studied for the risk of dementia in PD. Several studies have shown that quantitative EEG (QEEG) is a promising predictor of PD-related cognitive decline. In this paper we briefly outline the basics of QEEG analysis and analyze the recent publications addressing the predictive value of QEEG in the context of cognitive decline in PD. The MEDLINE database was searched for relevant publications from January 01, 2005, to March 02, 2015. Twenty-four studies reported QEEG findings in various cognitive states in PD. Spectral and connectivity markers of QEEG could help to discriminate between PD patients with different level of cognitive decline. QEEG variables correlate with tools for cognitive assessment over time and are associated with significant hazard ratios to predict PD-related dementia. QEEG analysis shows high test-retest reliability and avoids learning effects associated with some neuropsychological testing; it is noninvasive and relatively easy to repeat

Increase of EEG spectral theta power indicates higher risk of the development of severe cognitive decline in Parkinson’s disease after 3 years

Objective: We investigated quantitative electroencephalography (qEEG) and clinical parameters as potential risk factors of severe cognitive decline in Parkinson’s disease.Methods: We prospectively investigated 37 patients with Parkinson’s disease at baseline and follow-up (after 3 years). Patients had no severe cognitive impairment at baseline. We used a summary score of cognitive tests as the outcome at follow-up. At baseline we assessed motor, cognitive, and psychiatric factors; qEEG variables (global relative median power spectra) were obtained by a fully automated processing of high-resolution EEG (256-channels). We used linear regression models with calculation of the explained variance to evaluate the relation of baseline parameters with cognitive deterioration.Results: The following baseline parameters significantly predicted severe cognitive decline: global relative median power theta (4-8 Hz), cognitive task performance in executive functions and working memory.Conclusions: Combination of neurocognitive tests and qEEG improves identification of patients with higher risk of cognitive decline in PD

Phase lag index and spectral power as QEEG features for identification of patients with mild cognitive impairment in Parkinson's disease

To identify quantitative EEG frequency and connectivity features (Phase Lag Index) characteristic of mild cognitive impairment (MCI) in Parkinson's disease (PD) patients and to investigate if these features correlate with cognitive measures of the patients.; We recorded EEG data for a group of PD patients with MCI (n = 27) and PD patients without cognitive impairment (n = 43) using a high-resolution recording system. The EEG files were processed and 66 frequency along with 330 connectivity (phase lag index, PLI) measures were calculated. These measures were used to classify MCI vs. MCI-free patients. We also assessed correlations of these features with cognitive tests based on comprehensive scores (domains).; PLI measures classified PD-MCI from non-MCI patients better than frequency measures. PLI in delta, theta band had highest importance for identifying patients with MCI. Amongst cognitive domains, we identified the most significant correlations between Memory and Theta PLI, Attention and Beta PLI.; PLI is an effective quantitative EEG measure to identify PD patients with MCI.; We identified quantitative EEG measures which are important for early identification of cognitive decline in PD

Older Candidates for Subthalamic Deep Brain Stimulation in Parkinson's Disease Have a Higher Incidence of Psychiatric Serious Adverse Events.

OBJECTIVE To investigate the incidence of serious adverse events (SAE) of subthalamic deep brain stimulation (STN-DBS) in elderly patients with Parkinson's disease (PD). METHODS We investigated a group of 26 patients with PD who underwent STN-DBS at mean age 63.2 ± 3.3 years. The operated patients from the EARLYSTIM study (mean age 52.9 ± 6.6) were used as a comparison group. Incidences of SAE were compared between these groups. RESULTS A higher incidence of psychosis and hallucinations was found in these elderly patients compared to the younger patients in the EARLYSTIM study (p < 0.01). CONCLUSIONS The higher incidence of STN-DBS-related psychiatric complications underscores the need for comprehensive psychiatric pre- and postoperative assessment in older DBS candidates. However, these psychiatric SAE were transient, and the benefits of DBS clearly outweighed its adverse effects

Among Early Appearing Non-Motor Signs of Parkinson’s Disease, Alteration of Olfaction but Not Electroencephalographic Spectrum Correlates with Motor Function

Olfactory decline is a frequent and early non-motor symptom in Parkinson’s disease (PD), which is increasingly used for diagnostic purposes. Another early appearing sign of PD consists in electroencephalographic (EEG) alterations. The combination of olfactory and EEG assessment may improve the identification of patients with early stages of PD. We hypothesized that olfactory capacity would be correlated with EEG alterations and motor and cognitive impairment in PD patients. To the best of our knowledge, the mutual influence of both markers of PD—olfactory decrease and EEG changes—was not studied before. We assessed the function of odor identification using olfactory “Screening 12 Test” (“Sniffin’ Sticks®”), between two samples: patients with PD and healthy controls (HC). We analyzed correlations between the olfactory function and demographical parameters, Unified Parkinson’s Disease Rating Scale (UPDRS-III), cognitive task performance, and spectral alpha/theta ratio (α/θ). In addition, we used receiver operating characteristic-curve analysis to check the classification capacity (PD vs HC) of olfactory function, α/θ, and a combined marker (olfaction and α/θ). Olfactory capacity was significantly decreased in PD patients, and correlated with age, disease duration, UPDRS-III, and with items of UPDRS-III related to gait and axial rigidity. In HC, olfaction correlated with age only. No correlation with α/θ was identified in both samples. Combined marker showed the largest area under the curve. In addition to EEG, the assessment of olfactory function may be a useful tool in the early characterization and follow-up of PD