Short-latency afferent inhibition as a biomarker of cholinergic degeneration compared to PET imaging in Parkinson's disease.

INTRODUCTION: Short-latency afferent inhibition (SAI) is a relatively cheap and non-invasive method that has been proposed as a cholinergic marker in Parkinson's disease (PD). We aim to verify the clinical feasibility of SAI as a cholinergic marker in PD using positron emission tomography (PET) with the tracer (2R,3R)-5-(2-[18F]fluoroethoxy)benzovesamicol ([18F]FEOBV) as a reference. METHODS: We examined relations between SAI and [18F]FEOBV PET using linear regression analysis, with the primary motor cortex (M1) as primary region of interest. Additionally, we examined relations of both measures with clinical features. RESULTS: 30 PD patients with varying degrees of cognitive dysfunction and 10 healthy controls (HC) were included in the analysis. SAI was not related to tracer uptake in M1 in the PD group (p = .291) or the HC group (p = .206). We could not replicate the previously published relations between SAI and cholinergic symptoms, such as cognition, psychotic experiences and olfactory function. CONCLUSION: SAI was not related to [18F]FEOBV imaging parameters, nor to clinical measures of cholinergic dysfunction. Therefore, SAI may not be feasible as a clinically applied cholinergic marker in PD.

Cholinergic innervation topography in GBA-associated de novo Parkinson's disease patients.

The most common genetic risk factors for Parkinson's disease are GBA1 mutations, encoding the lysosomal enzyme glucocerebrosidase. Patients with GBA1 mutations (GBA-PD) exhibit earlier age of onset and faster disease progression with more severe cognitive impairments, postural instability and gait problems. These GBA-PD features suggest more severe cholinergic system pathologies. PET imaging with the vesicular acetylcholine transporter ligand 18F-F-fluoroethoxybenzovesamicol (18F-FEOBV PET) provides the opportunity to investigate cholinergic changes and their relationship to clinical features in GBA-PD. The study investigated 123 newly diagnosed, treatment-naïve Parkinson's disease subjects-with confirmed presynaptic dopaminergic deficits on PET imaging. Whole-gene GBA1 sequencing of saliva samples was performed to evaluate GBA1 variants. Patients underwent extensive neuropsychological assessment of all cognitive domains, motor evaluation with the Unified Parkinson's Disease Rating Scale, brain MRI, dopaminergic PET to measure striatal-to-occipital ratios of the putamen and 18F-FEOBV PET. We investigated differences in regional cholinergic innervation between GBA-PD carriers and non-GBA1 mutation carriers (non-GBA-PD), using voxel-wise and volume of interest-based approaches. The degree of overlap between t-maps from two-sample t-test models was quantified using the Dice similarity coefficient. Seventeen (13.8%) subjects had a GBA1 mutation. No significant differences were found in clinical features and dopaminergic ratios between GBA-PD and non-GBA-PD at diagnosis. Lower 18F-FEOBV binding was found in both the GBA-PD and non-GBA-PD groups compared to controls. Dice (P < 0.05, cluster size 100) showed good overlap (0.7326) between the GBA-PD and non-GBA-PD maps. GBA-PD patients showed more widespread reduction in 18F-FEOBV binding than non-GBA-PD when compared to controls in occipital, parietal, temporal and frontal cortices (P < 0.05, FDR-corrected). In volume of interest analyses (Bonferroni corrected), the left parahippocampal gyrus was more affected in GBA-PD. De novo GBA-PD show a distinct topography of regional cholinergic terminal ligand binding. Although the Parkinson's disease groups were not distinguishable clinically, in comparison to healthy controls, GBA-PD showed more extensive cholinergic denervation compared to non-GBA-PD. A larger group is needed to validate these findings. Our results suggest that de novo GBA-PD and non-GBA-PD show differential patterns of cholinergic system changes before clinical phenotypic differences between carriers versus non-carrier groups are observable.

Cholinesterase Inhibitors for Treatment of Psychotic Symptoms in Alzheimer Disease and Parkinson Disease: A Meta-analysis.

Importance: Psychotic symptoms greatly increase the burden of disease for people with neurodegenerative disorders and their caregivers. Cholinesterase inhibitors (ChEIs) may be effective treatment for psychotic symptoms in these disorders. Previous trials only evaluated neuropsychiatric symptoms as a secondary and an overall outcome, potentially blurring the outcomes noted with ChEI use specifically for psychotic symptoms. Objective: To quantitatively assess the use of ChEIs for treatment of individual neuropsychiatric symptoms, specifically hallucinations and delusions, in patients with Alzheimer disease (AD), Parkinson disease (PD), and dementia with Lewy bodies (DLB). Data Sources: A systematic search was performed in PubMed (MEDLINE), Embase, and PsychInfo, without year restrictions. Additional eligible studies were retrieved from reference lists. The final search cutoff date was April 21, 2022. Study Selection: Studies were selected if they presented the results of placebo-controlled randomized clinical trials, including at least 1 donepezil, rivastigmine, or galantamine treatment arm in patients with AD, PD, or DLB; if they applied at least 1 neuropsychiatric measure including hallucinations and/or delusions; and if a full-text version of the study was available in the English language. Study selection was performed and checked by multiple reviewers. Data Extraction and Synthesis: Original research data were requested on eligible studies. A 2-stage meta-analysis was then performed, using random-effects models. Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines were followed for extracting data and assessing the data quality and validity. Data extraction was checked by a second reviewer. Main Outcomes and Measures: Primary outcomes were hallucinations and delusions; secondary outcomes included all other individual neuropsychiatric subdomains as well as the total neuropsychiatric score. Results: In total, 34 eligible randomized clinical trials were selected. Individual participant data on 6649 individuals (3830 [62.6%] women; mean [SD] age, 75.0 [8.2] years) were obtained from 17 trials (AD: n = 12; PD: n = 5; individual participant data were not available for DLB). An association with ChEI treatment was shown in the AD subgroup for delusions (-0.08; 95% CI, -0.14 to -0.03; P = .006) and hallucinations (-0.09; 95% CI, -0.14 to -0.04; P = .003) and in the PD subgroup for delusions (-0.14; 95% CI, -0.26 to -0.01; P = .04) and hallucinations (-0.08, 95% CI -0.13 to -0.03; P = .01). Conclusions and Relevance: The results of this individual participant data meta-analysis suggest that ChEI treatment improves psychotic symptoms in patients with AD and PD with small effect sizes.

The effectiveness of off-label dopamine stimulating agents in depressive disorder: A systematic review and meta-analysis.

The chronicity of depressive disorders is a major problem. Dopamine stimulating agents (DSA) are suggested to hold a promising potential in depression management, particularly in older adults, in whom dopamine deficiency due to aging may be an underlying cause. More evidence is needed to support these drugs in the management of depression. Therefore, we conducted a systematic literature review and meta-analysis. Data was extracted from eighteen randomized-controlled-trials and eight open-label-studies. Additional meta-regression-analyses were performed to examine superiority of monotherapy versus augmentation, and to rule out a putative age effect. DSA were found to reduce depressive symptoms (SMD=-0.26, 95%CI[-0.43;-0.10]). Heterogeneity was high and a significant Egger's test indicated publication bias. Adjustment for missing studies, using trim-and-fill-methodology, reduced the effect size (SMD=-0.17, 95%CI[-0.39;0.05]), which lost statistical significance. Removing the outlier study from the analysis, the effect size remained marginally small, but was statistically-significant (SMD=-0.17, 95%CI[-0.31;-0.02]). Neither augmentation nor monotherapy was superior. No age effect was found. It can be concluded that off-label DSA are overall effective in reducing depressive symptoms. However, the evidence is weak, regarding the publication bias, and modest-to-weak treatment effects. Well-designed high-quality trials are highly needed, before dopamine stimulating agents can be adequately positioned in future depression treatment protocols.

Rapid annotation of seizures and interictal-ictal-injury continuum EEG patterns.

BACKGROUND: Manual annotation of seizures and interictal-ictal-injury continuum (IIIC) patterns in continuous EEG (cEEG) recorded from critically ill patients is a time-intensive process for clinicians and researchers. In this study, we evaluated the accuracy and efficiency of an automated clustering method to accelerate expert annotation of cEEG. NEW METHOD: We learned a local dictionary from 97 ICU patients by applying k-medoids clustering to 592 features in the time and frequency domains. We utilized changepoint detection (CPD) to segment the cEEG recordings. We then computed a bag-of-words (BoW) representation for each segment. We further clustered the segments by affinity propagation. EEG experts scored the resulting clusters for each patient by labeling only the cluster medoids. We trained a random forest classifier to assess validity of the clusters. RESULTS: Mean pairwise agreement of 62.6% using this automated method was not significantly different from interrater agreements using manual labeling (63.8%), demonstrating the validity of the method. We also found that it takes experts using our method 5.31 ±â€¯4.44 min to label the 30.19 ±â€¯3.84 h of cEEG data, more than 45 times faster than unaided manual review, demonstrating efficiency. COMPARISON WITH EXISTING METHODS: Previous studies of EEG data labeling have generally yielded similar human expert interrater agreements, and lower agreements with automated methods. CONCLUSIONS: Our results suggest that long EEG recordings can be rapidly annotated by experts many times faster than unaided manual review through the use of an advanced clustering method.

Rapid Annotation of Seizures and Interictal-ictal Continuum EEG Patterns.

Seizures, status epilepticus, and seizure-like rhythmic or periodic activities are common, pathological, harmful states of brain electrical activity seen in the electroencephalogram (EEG) of patients during critical medical illnesses or acute brain injury. Accumulating evidence shows that these states, when prolonged, cause neurological injury. In this study we developed a valid method to automatically discover a small number of homogeneous pattern clusters, to facilitate efficient interactive labelling by EEG experts. 592 time domain and spectral features were extracted from continuous EEG (cEEG) data of 369 ICU (intensive care unit) patients. For each patient, feature dimensionality was reduced using principal component analysis (PCA), retaining 95% of the variance. K-medoids clustering was applied to learn a local dictionary from each patient, consisting of k=100 exemplars/words. Changepoint detection (CPD) was utilized to break each EEG into segments. A bag-of-words (BoW) representation was computed for each segment, specifically, a normalized histogram of the words found within each segment. Segments were further clustered using the BoW histograms by Affinity Propagation (AP) using a χ2 distance to measure similarities between histograms. The resulting 30 50 clusters for each patient were scored by EEG experts through labeling only the cluster medoids. Embedding methods t-SNE (t-distributed stochastic neighbor embedding) and PCA were used to provide a 2D representation for visualization and exploration of the data. Our results illustrate that it takes approximately 3 minutes to annotate 24 hours of cEEG by experts, which is at least 60 times faster than unaided manual review.