Vol 21, No 6 (2024)

Introduction:Distinguishing between frontotemporal dementia (FTD) and Alzheimer’s disease (AD) in their early stages remains a significant clinical challenge. Cerebrospinal fluid (CSF) biomarkers (total Tau, phosphorylated Tau, and beta-amyloid) are promising candidates for identifying early differences between these conditions. This study investigates the relationship between grey matter density and CSF markers in the behavioural variant of frontotemporal dementia (bvFTD) and Alzheimer’s disease (AD).

Method:CSF and 3D T1-weighted magnetic resonance (MR) images were acquired from 14 bvFTD patients, 15 AD patients, and 13 cognitively normal (CN) matched subjects. The CSF markers and their relative ratios (total Tau/beta-amyloid, phosphorylated Tau/beta-amyloid) were compared across the three groups. Voxel-based morphometry (VBM) was performed to characterize the anatomical changes in bvFTD and AD patients compared to CN subjects. Grey matter density maps were obtained by automatic segmentation of 3.0 Tesla 3D T1-Weighted MR Images, and their correlation with CSF markers and relative ratios was investigated.

Results:Results demonstrated that, as compared to CN subjects, AD patients are characterised by higher CSF total Tau levels and lower beta-amyloid levels; however, beta-amyloid and relative ratios discriminated AD from bvFTD. In addition, AD and bvFTD patients showed different patterns of atrophy, with AD exhibiting more central (temporal areas) and bvFTD more anterior (frontal areas) atrophy. A correlation was found between grey matter density maps and CSF marker concentrations in the AD group, with total Tau and phosphorylated Tau levels showing a high association with low grey matter density in the left superior temporal gyrus.

Conclusion:Overall, while bvFTD lacks a CSF marker profile, CSF beta-amyloid levels are useful for differentiating AD from bvFTD. Furthermore, MR structural imaging can contribute significantly to distinguishing between the two pathologies.

Introduction:Alzheimer's disease (AD) is a complex neurological disorder that progressively worsens. Although its exact causes are not fully understood, new research indicates that genes related to non-neuronal cells change significantly with age, playing key roles in AD's pathology. METHOD: This study focuses on a protein network centered on Glial Fibrillary Acidic Protein (GFAP) and Protein Tyrosine Phosphatase Receptor Type C (PTPRC).

Method:This study focuses on a protein network centered on Glial Fibrillary Acidic Protein (GFAP) and Protein Tyrosine Phosphatase Receptor Type C (PTPRC).

The Key Findings of this Study Include:1. A significant correlation was observed between GFAP and PTPRC expression throughout AD progression, which links closely with clinical phenotypes and suggests their role in AD pathology. 2. A molecular network centered on GFAP and PTPRC, including Catenin Beta 1 (CTNNB1) and Integrin Beta 2 (ITGB2), showed distinct changes in interactions, highlighting its regulatory role in AD. 3. Analysis of GSE5281 data revealed a decline in the interaction strength within this network, pointing to potential desynchronization as a biomarker for AD. 4. SVM diagnostic models comparing GFAP expression and coupling values confirmed this desynchronization, suggesting it worsens with AD progression.

Result:Based on these findings, it is hypothesized that as AD progresses, the GFAP- and PTPRCcentered molecular framework undergoes significant changes affecting key biological pathways. These changes disrupt immune regulation and cellular functions, increasing immune cell activation and inflammation in the brain. This may impair neuronal communication and synaptic functionality, exacerbating AD's pathology.

Conclusion:To verify these findings, Support Vector Machine (SVM) diagnostic models and correlation analyses were used to examine changes in this network, indicating that its dysregulation significantly affects AD progression.

Introduction/Objective:Age-related cognitive decline has been linked with risk factors, including physical performance. Prior studies investigating such associations were typically conducted in clinical settings within Western populations with a frequent focus on late neurocognitive diagnostic stages (i.e., Alzheimer’s disease), reducing their generalizability to the Asian population and early neurocognitive stages. To address these knowledge gaps, our study investigated longitudinal associations between physical performance measures at baseline and cognitive change in global cognition, executive functioning (EF) based and non-executive functioning (non- EF) based cognitive domains within the Singaporean population. The moderating role of early neurocognitive status, namely mild cognitive impairment (MCI) and cognitively normal (CN), was also examined.

Methods:This paper examined data from 347 participants (CN = 284; MCI = 63) who participated in the Community Health and Intergenerational (CHI) study at baseline and follow-up. Data from a neurocognitive battery and three physical performance tests, namely the timed-up and go (TUG), fast gait speed (FGS) and 30-second chair-stand test (30s-CST), were analysed using multivariate linear regression models.

Results:Only one significant association between FGS scores and cognitive change in Semantic Fluency was observed; other associations were not significant. Cognitive status also significantly moderated associations between TUG/30s-CST tasks with several neurocognitive tests.

Conclusion:The lack of significant longitudinal associations between baseline physical performance measures and cognitive change differed from findings in the literature. Nevertheless, the moderating role of cognitive status further highlighted the need to account for cognitive status when exploring such associations within a heterogeneous group of older adults without dementia.