Quantitative EEG After Brain Stimulation and Cognitive Training in Alzheimer Disease.

PURPOSE: Medications are the currently accepted symptomatic treatment of Alzheimer disease (AD), but their impact on delaying the progression of cognitive deficits and functional impairment is limited. The authors aimed to explore long-term electrophysiological effects of repetitive transcranial magnetic stimulation interlaced with cognitive training on quantitative electroencephalography (EEG) in patients with AD. METHODS: Quantitative EEG was assessed on non-repetitive transcranial magnetic stimulation interlaced with cognitive training treatment days before treatment and after each treatment phase in seven patients with mild AD. RESULTS: After 4.5 months (54 sessions) of treatment, a significant increase of delta activity over the temporal region was found compared with pretreatment values. Nonsignificant increases of the log EEG power were found for alpha band over the frontal and temporal regions, beta band over the frontal region, theta band over the frontal, temporal, and parieto-occipital regions, and delta band over the frontal and parieto-occipital regions. Nonsignificant decreases were found for alpha over the parieto-occipital region, and for beta over the temporal and parieto-occipital regions. A positive correlation was found between log alpha power over the frontal and temporal regions at 6 weeks and Mini-Mental State Examination (MMSE) scores at 6 weeks and 4.5 months, and between log alpha power over the parieto-occipital regions and MMSE scores at 6 weeks. A negative correlation was found between log alpha power over the frontal and temporal regions at 6 weeks and baseline Alzheimer's Disease Assessment Scale-cognitive subscale scores. CONCLUSIONS: Repetitive transcranial magnetic stimulation interlaced with cognitive training has long-term effects on quantitative EEG in patients with mild AD. Further research on the quantitative EEG long-term effects of transcranial magnetic stimulation interlaced with cognitive training is required to confirm the authors' data.

A molecular signature in blood identifies early Parkinson's disease.

BACKGROUND: The search for biomarkers in Parkinson's disease (PD) is crucial to identify the disease early and monitor the effectiveness of neuroprotective therapies. We aim to assess whether a gene signature could be detected in blood from early/mild PD patients that could support the diagnosis of early PD, focusing on genes found particularly altered in the substantia nigra of sporadic PD. RESULTS: The transcriptional expression of seven selected genes was examined in blood samples from 62 early stage PD patients and 64 healthy age-matched controls. Stepwise multivariate logistic regression analysis identified five genes as optimal predictors of PD: p19 S-phase kinase-associated protein 1A (odds ratio [OR] 0.73; 95% confidence interval [CI] 0.60-0.90), huntingtin interacting protein-2 (OR 1.32; CI 1.08-1.61), aldehyde dehydrogenase family 1 subfamily A1 (OR 0.86; 95% CI 0.75-0.99), 19 S proteasomal protein PSMC4 (OR 0.73; 95% CI 0.60-0.89) and heat shock 70-kDa protein 8 (OR 1.39; 95% CI 1.14-1.70). At a 0.5 cut-off the gene panel yielded a sensitivity and specificity in detecting PD of 90.3 and 89.1 respectively and the area under the receiving operating curve (ROC AUC) was 0.96. The performance of the five-gene classifier on the de novo PD individuals alone composing the early PD cohort (n = 38), resulted in a similar ROC with an AUC of 0.95, indicating the stability of the model and also, that patient medication had no significant effect on the predictive probability (PP) of the classifier for PD risk. The predictive ability of the model was validated in an independent cohort of 30 patients at advanced stage of PD, classifying correctly all cases as PD (100% sensitivity). Notably, the nominal average value of the PP for PD (0.95 (SD = 0.09)) in this cohort was higher than that of the early PD group (0.83 (SD = 0.22)), suggesting a potential for the model to assess disease severity. Lastly, the gene panel fully discriminated between PD and Alzheimer's disease (n = 29). CONCLUSIONS: The findings provide evidence on the ability of a five-gene panel to diagnose early/mild PD, with a possible diagnostic value for detection of asymptomatic PD before overt expression of the disorder.