Multi-domain Cognitive Testing: A Biomarker for Classifying the Cognitive Status of Mild Cognitive Impairment and Alzheimer's Disease.

Context: Cognition is impaired in Alzheimer's disease (AD) and patients with mild cognitive impairment (MCI) with varying levels of magnitude. Aim: The present study aimed to identify a biomarker for classifying MCI and AD using multi-domain cognitive testing. Settings and Design: This was a cross-sectional study. Methods and Materials: 26 AD patients, 28 MCI patients and 25 controls were recruited. Cognitive assessment of different domains was done using standard questionnaires and cognitive function tests. Statistical Analysis Used: Cognitive task scores were compared between the groups using multivariate analysis of variance (MANOVA). Results: Patients with AD had significantly lower MMSE, CDR, cognitive task scores compared to controls and MCI. Cognitive scores of all tasks for MCI were significantly less than controls, except MMSE and digits forward score. ROC analysis showed that picture memory had 100% sensitivity, 91.6% specificity for AD and 88.4% sensitivity, 92.5% specificity for MCI. Word memory had 92.3% specificity, 100% specificity for AD and 80.7% specificity, 84.6% specificity for MCI. Conclusions: The global cognitive tools are less specific in bringing out the differences especially between MCI and control. Limitation of MMSE, heterogeneity of MCI and differential impairment of various domains of cognition, demands the inclusion of multi-domain cognitive evaluation especially picture and word memory tasks with high sensitivity and specificity into the existing diagnostic protocol. ROC results also suggested the continuum of cognitive impairment and MCI as a transitional stage leaving more scope on the quantum of research required for intervention to halt the structural and functional decline.

Reduced Resting-State Cortical Alpha Connectivity Reflects Distinct Functional Brain Dysconnectivity in Alzheimer's Disease and Mild Cognitive Impairment.

Background: Emerging evidence suggests distinct abnormal activity patterns during resting state in intrinsic functional brain networks in patients with neurodegenerative diseases, including Alzheimer's disease (AD) and mild cognitive impairment (MCI). This study aimed to identify the changes in the resting-state intracortical lagged phase synchronization derived from dense array electroencephalography (EEG) in AD and MCI. Methods: Resting-state current source density (CSD) and lagged phase synchronization between 84 regions of interest defined by Brodmann areas (BAs) for seven EEG frequency bands were investigated between the study groups (AD, MCI, and age-matched controls) using 128-channel EEG. Results: Reduced CSD and connectivity (large effect size, Cohen's d > 0.8) were found in AD and MCI compared with controls at alpha frequency. However, a positive correlation (r = 0.433; p = 0.044) of mini-mental state examination scores was found with BA 32-33 connectivity values in AD only. Conclusion: Reduced resting-state alpha 1 source connectivity in patient groups and correlation between attenuation of resting-state alpha 1 connectivity with cognitive decline in AD could indicate the disruption of inhibitory function of alpha rhythm leading to tonic unselective cortical excitation that affects attention and controlled access to stored information.