Seed-based morphometry of nodes in the default mode network among patients with Alzheimer’s disease in Klang Valley, Malaysia

Abstract

The default mode network (DMN) is a prominent neural network in the human brain that exhibits a substantial association with Alzheimer's disease (AD). Functional connectivity (FC) and grey matter volume (GMV) were reported to differ between AD and healthy controls (HC). Nevertheless, available evidence is scarce regarding the structural and functional alterations observed in individuals diagnosed with Alzheimer's disease (AD) within the context of Malaysia. A prospective cross-sectional study was conducted in the Klang Valley region of Malaysia. A total of 22 participants were enlisted for the study, following a thorough clinical assessment completed by geriatricians. The participants underwent a series of neuropsychological tests, including the Montreal Cognitive Assessment (MoCA), Mini-Mental State Examination (MMSE), and Clinical Dementia Rating (CDR). The participants were classified into two groups, namely AD (Alzheimer's disease) and HC (healthy controls), before the acquisition of resting-state functional magnetic resonance imaging (Rs-fMRI) images. The analysis of voxel-based morphometry (VBM) was conducted using SPM 12, a widely used software package in the field of neuroimaging, implemented in MATLAB. The primary objective of this analysis was to assess the grey matter volume (GMV). The CONN toolbox was employed to assess the functional connectivity (FC) and activation patterns of the nodes inside the default mode network (DMN). In this pilot project, a cohort of 22 participants was enlisted, consisting of 11 individuals with Alzheimer's disease (AD) with an age range of 64-84 years and 11 healthy controls (HC) with an age range of 64-79 years. In the Alzheimer's disease (AD) group, there was a reduction in grey matter volume (GMV) observed in several brain regions when compared to the healthy control (HC) group. Specifically, decreased GMV was found in the right and left inferior temporal gyrus, left superior frontal gyrus, right superior frontal gyrus medial segment, right gyrus rectus, right temporal lobe, left putamen, and right precuneus, respectively. The significance level for the Rs-FC analysis was established at a cluster-size corrected p-value of less than 0.05. A notable reduction in the activation of the nodes within the default mode network (DMN) was observed in individuals with Alzheimer's disease (AD) compared to healthy controls (HC). This drop was notably evident in the functional connectivity of the precuneus and anterior cingulate cortex in both AD and HC groups, as well as in the comparison between AD and HC groups. Resting-state functional magnetic resonance imaging (fMRI) can identify specific imaging biomarkers associated with Alzheimer's disease by analysing grey matter volume (GMV) and default mode network (DMN) functional connectivity (FC) profiles. Consequently, there is promise for utilising resting-state fMRI as a non-invasive approach to enhance the detection and diagnosis of Alzheimer's disease within the Malaysian community.