Usefulness of event-related potentials in the assessment of mild cognitive impairment

<p>Abstract</p> <p>Background</p> <p>The aim of this study was to determine if changes in latencies and amplitudes of the major waves of Auditory Event-Related Potentials (AERP), correlate with memory status of patients with mild cognitive impairment (MCI) and conversion to Alzheimer's disease (AD).</p> <p>91 patients with MCI (mean ± SD age = 66.6 ± 5.4, MMSE score = 27.7) and 30 age-matched healthy control (AMHC) subjects (mean ± SD age = 68.9 ± 9.9) were studied. 54 patients were re-examined after an average period of 14(± 5.2) months. During this time period 5 patients converted to AD. Between-group differences in latency and amplitude of the major AERP waves (N200, P300 and Slow Wave) were determined. Within each group, correlation coefficients (CC) between these characteristics of the different AERP waves were calculated. Finally, for patients, CCs were determined among each AERP wave and their age and MMSE scores. Confirmatory factor analysis (CFA) was used to examine the underlying structure of waveforms both in the control and the patient groups.</p> <p>Results</p> <p>Latencies of all major AERP components were prolonged in patients compared to controls. Patients presented with significantly higher N200 amplitudes, but no significant differences were observed in P300 amplitudes. Significant differences between follow-up and baseline measurements were found for P300 latency (p = 0.009), N200 amplitude (p < 0.001) and P300 amplitude (p = 0.05). MMSE scores of patients did not correlate with latency or amplitude of the AERP components. Moreover, the establishment of a N200 latency cut-off value of 287 ms resulted in a sensitivity of 100% and a specificity of 91% in the prediction of MCI patients that converted to AD.</p> <p>Conclusion</p> <p>Although we were not able to establish significant correlations between latencies and amplitudes of N200, P300 and SW and the patients' performance in MMSE, which is a psychometric test for classifying patients suffering from MCI, our results point out that the disorganization of the AERP waveform in MCI patients is a potential basis upon which a neurophysiologic methodology for identifying and "staging" MCI can be sought. We also found that delayed N200 latency not only identifies memory changes better than the MMSE, but also may be a potential predictor of the MCI patients who convert to AD.</p

Validity of a novel computerized cognitive battery for mild cognitive impairment

BACKGROUND: The NeuroTrax Mindstreams computerized cognitive assessment system was designed for widespread clinical and research use in detecting mild cognitive impairment (MCI). However, the capability of Mindstreams tests to discriminate elderly with MCI from those who are cognitively healthy has yet to be evaluated. Moreover, the comparability between these tests and traditional neuropsychological tests in detecting MCI has not been examined. METHODS: A 2-center study was designed to assess discriminant validity of tests in the Mindstreams Mild Impairment Battery. Participants were 30 individuals diagnosed with MCI, 29 with mild Alzheimer's disease (AD), and 39 healthy elderly. Testing was with the Mindstreams battery and traditional neuropsychological tests. Receiver operating characteristic (ROC) analysis was used to examine the ability of Mindstreams and traditional measures to discriminate those with MCI from cognitively healthy elderly. Between-group comparisons were made (Mann-Whitney U test) between MCI and healthy elderly and between MCI and mild AD groups. RESULTS: Mindstreams outcome parameters across multiple cognitive domains significantly discriminated among MCI and healthy elderly with considerable effect sizes (p < 0.05). Measures of memory, executive function, visual spatial skills, and verbal fluency discriminated best, and discriminability was at least comparable to that of traditional neuropsychological tests in these domains. CONCLUSIONS: Mindstreams tests are effective in detecting MCI, providing a comprehensive profile of cognitive function. Further, the enhanced precision and ease of use of these computerized tests make the NeuroTrax system a valuable clinical tool in the identification of elderly at high risk for dementia

Cerebral hypoperfusion accelerates cerebral amyloid angiopathy and promotes cortical microinfarcts

Cortical microinfarcts (CMIs) observed in brains of patients with Alzheimer’s disease tend to be located close to vessels afflicted with cerebral amyloid angiopathy (CAA). CMIs in Alzheimer’s disease are preferentially distributed in the arterial borderzone, an area most vulnerable to hypoperfusion. However, the causal association between CAA and CMIs remains to be elucidated. This study consists of two parts: (1) an observational study using postmortem human brains (n = 31) to determine the association between CAA and CMIs, and (2) an experimental study to determine whether hypoperfusion worsens CAA and induces CMIs in a CAA mouse model. In postmortem human brains, the density of CMIs was 0.113/cm2 in mild, 0.584/cm2 in moderate, and 4.370/cm2 in severe CAA groups with a positive linear correlation (r = 0.6736, p < 0.0001). Multivariate analysis revealed that, among seven variables (age, disease, senile plaques, neurofibrillary tangles, CAA, atherosclerosis and white matter damage), only the severity of CAA was a significant multivariate predictor of CMIs (p = 0.0022). Consistent with the data from human brains, CAA model mice following chronic cerebral hypoperfusion due to bilateral common carotid artery stenosis induced with 0.18-mm diameter microcoils showed accelerated deposition of leptomeningeal amyloid β (Aβ) with a subset of them developing microinfarcts. In contrast, the CAA mice without hypoperfusion exhibited very few leptomeningeal Aβ depositions and no microinfarcts by 32 weeks of age. Following 12 weeks of hypoperfusion, cerebral blood flow decreased by 26% in CAA mice and by 15% in wild-type mice, suggesting impaired microvascular function due to perivascular Aβ accumulation after hypoperfusion. Our results suggest that cerebral hypoperfusion accelerates CAA, and thus promotes CMIs

Amyloid Triggers Extensive Cerebral Angiogenesis Causing Blood Brain Barrier Permeability and Hypervascularity in Alzheimer's Disease

Evidence of reduced blood-brain barrier (BBB) integrity preceding other Alzheimer's disease (AD) pathology provides a strong link between cerebrovascular angiopathy and AD. However, the “Vascular hypothesis”, holds that BBB leakiness in AD is likely due to hypoxia and neuroinflammation leading to vascular deterioration and apoptosis. We propose an alternative hypothesis: amyloidogenesis promotes extensive neoangiogenesis leading to increased vascular permeability and subsequent hypervascularization in AD. Cerebrovascular integrity was characterized in Tg2576 AD model mice that overexpress the human amyloid precursor protein (APP) containing the double missense mutations, APPsw, found in a Swedish family, that causes early-onset AD. The expression of tight junction (TJ) proteins, occludin and ZO-1, were examined in conjunction with markers of apoptosis and angiogenesis. In aged Tg2576 AD mice, a significant increase in the incidence of disrupted TJs, compared to age matched wild-type littermates and young mice of both genotypes, was directly linked to an increased microvascular density but not apoptosis, which strongly supports amyloidogenic triggered hypervascularity as the basis for BBB disruption. Hypervascularity in human patients was corroborated in a comparison of postmortem brain tissues from AD and controls. Our results demonstrate that amylodogenesis mediates BBB disruption and leakiness through promoting neoangiogenesis and hypervascularity, resulting in the redistribution of TJs that maintain the barrier and thus, provides a new paradigm for integrating vascular remodeling with the pathophysiology observed in AD. Thus the extensive angiogenesis identified in AD brain, exhibits parallels to the neovascularity evident in the pathophysiology of other diseases such as age-related macular degeneration

A statistical framework for cross-tissue transcriptome-wide association analysis

Transcriptome-wide association analysis is a powerful approach to studying the genetic architecture of complex traits. A key component of this approach is to build a model to impute gene expression levels from genotypes by using samples with matched genotypes and gene expression data in a given tissue. However, it is challenging to develop robust and accurate imputation models with a limited sample size for any single tissue. Here, we first introduce a multi-task learning method to jointly impute gene expression in 44 human tissues. Compared with single-tissue methods, our approach achieved an average of 39% improvement in imputation accuracy and generated effective imputation models for an average of 120% more genes. We describe a summary-statistic-based testing framework that combines multiple single-tissue associations into a powerful metric to quantify the overall gene–trait association. We applied our method, called UTMOST (unified test for molecular signatures), to multiple genome-wide-association results and demonstrate its advantages over single-tissue strategies