An unbiased algorithm for objective separation of Alzheimer's, Alzheimer's mixed with cerebrovascular symptomology, and healthy controls from one another using electrovestibulography (EVestG)

Using principal component analysis to determine which vestibular stimuli provide best biomarkers for separating Alzheimer's from mixed Alzheimer's disease

Alzheimer's disease (AD) is often mixed with cerebrovascular disease (AD-CVD). Heterogeneity of dementia etiology and the overlapping of neuropathological features of AD and AD-CVD make feature identification of the two challenging. Separation of AD from AD-CVD is important as the optimized treatment for each group may differ. Recent studies using vestibular responses recorded from electrovestibulography (EVestG™) have offered promising results for separating these two pathologies. An EVestG measurement records responses to several different physical stimuli (called tilts). In previous research, the number of EVestG features from different tilts was selected based on physiological intuition to classify AD from AD-CVD. As the number of potential characteristic features from all tilts can be very large, in this study, we used an algorithm based on principal component analysis (PCA) to rank the most effective vestibular stimuli for differentiating AD from AD-CVD. Analyses were performed on the EVestG signals of 28 individuals with AD and 24 with AD-CVD. The results of this study showed that tilts simulating the otolithic organs (utricle and saccule) generated the most characteristic features for separating AD from AD-CVD.

Repetitive transcranial magnetic stimulation as a treatment for Alzheimer's disease: A randomized placebo-controlled double-blind clinical trial

We report results of a large multisite double-blind randomized trial investigating the short and long-term efficacy of repetitive transcranial magnetic stimulation (rTMS) applied to patients with Alzheimer's disease (AD) at mild to moderate stages, in doses of either 2 or 4 weeks of treatment (5 days/week), whilst compared with 4 weeks of sham rTMS. Randomization to treatment group was stratified based on age and severity. The objectives of this study were to: 1) investigate the efficacy of active rTMS versus sham, 2) investigate the effect of dose of treatment (2 or 4 weeks), and 3) investigate the length of benefits from treatment. The rTMS pulses (20 ​Hz, 30 pulses/train, 25 trains, 10-s intertrain interval) were applied serially to the left and right dorsolateral prefrontal cortex using neuro-navigation. We compared the primary outcome measure's (ADAS-Cog) score changes from pre- to post-treatment, with assessments at baseline and 4 more times up to 6 months post-treatment. Data of 135 patients were analyzed. The mean total ADAS-Cog score at baseline did not differ between the active and sham treatment groups, nor across the three study sites. The overall results show significant cognitive improvement after treatment up to two months post-treatment with either sham or active coils. The results show both short and long-term benefits of active rTMS treatment but also show similar benefits for sham coil treatment of mild/moderate AD. We discuss this finding in the context of the existing literature on rTMS therapy for AD, as well as evidence of the sham coil's potential to induce a low-level current in the brain. TRIAL REGISTRATION: https://clinicaltrials.gov/ct2/show/NCT02908815.

Gray and White Matter Voxel-Based Morphometry of Alzheimer's Disease With and Without Significant Cerebrovascular Pathologies

Alzheimer's disease (AD) is the most common type of dementia, and AD individuals often present significant cerebrovascular disease (CVD) symptomology. AD with significant levels of CVD is frequently labeled mixed dementia (or sometimes AD-CVD), and the differentiation of these two neuropathologies (AD, AD-CVD) from each other is challenging, especially at early stages. In this study, we compared the gray matter (GM) and white matter (WM) volumes in AD (n = 83) and AD-CVD (n = 37) individuals compared with those of cognitively healthy controls (n = 85) using voxel-based morphometry (VBM) of their MRI scans. The control individuals, matched for age and sex with our two dementia groups, were taken from the ADNI. The VBM analysis showed widespread patterns of significantly lower GM and WM volume in both dementia groups compared to the control group (P < .05, family-wise error corrected). While comparing with AD-CVD, the AD group mainly demonstrated a trend of lower volumes in the GM of the left putamen and right hippocampus and WM of the right thalamus (uncorrected P < .005 with cluster threshold, K = 10). The AD-CVD group relative to AD tended to present lower GM and WM volumes, mainly in the cerebellar lobules and right brainstem regions, respectively (uncorrected P < .005 with cluster threshold, K = 10). Although finding a discriminatory feature in structural MRI data between AD and AD-CVD neuropathologies is challenging, these results provide preliminary evidence that demands further investigation in a larger sample size.

Evaluating the Diagnostic Value of Electrovestibulography (EVestG) in Alzheimer's Patients with Mixed Pathology: A Pilot Study

Background and Objectives: Diagnosis of dementia subtypes caused by different brain pathophysiologies, particularly Alzheimer's disease (AD) from AD mixed with levels of cerebrovascular disease (CVD) symptomology (AD-CVD), is challenging due to overlapping symptoms. In this pilot study, the potential of Electrovestibulography (EVestG) for identifying AD, AD-CVD, and healthy control populations was investigated. Materials and Methods: A novel hierarchical multiclass diagnostic algorithm based on the outcomes of its lower levels of binary classifications was developed using data of 16 patients with AD, 13 with AD-CVD, and 24 healthy age-matched controls, and then evaluated on a blind testing dataset made up of a new population of 12 patients diagnosed with AD, 9 with AD-CVD, and 8 healthy controls. Multivariate analysis was run to test the between population differences while controlling for sex and age covariates. Results: The accuracies of the multiclass diagnostic algorithm were found to be 85.7% and 79.6% for the training and blind testing datasets, respectively. While a statistically significant difference was found between the populations after accounting for sex and age, no significant effect was found for sex or age covariates. The best characteristic EVestG features were extracted from the upright sitting and supine up/down stimulus responses. Conclusions: Two EVestG movements (stimuli) and their most informative features that are best selective of the above-populations' separations were identified, and a hierarchy diagnostic algorithm was developed for three-way classification. Given that the two stimuli predominantly stimulate the otholithic organs, physiological and experimental evidence supportive of the results are presented. Disruptions of inhibition associated with GABAergic activity might be responsible for the changes in the EVestG features.