Reduction in GABAB on glia induce Alzheimer\u27s disease related changes.

Alzheimer’s Disease (AD) is a neurodegenerative disorder characterized by beta-amyloid plaques (Aβ), neuro- fibrillary tangles (NFT), and neuroinflammation. Data have demonstrated that neuroinflammation contributes to Aβ and NFT onset and progression, indicating inflammation and glial signaling is vital to understanding AD. A previous investigation demonstrated a significant decrease of the GABAB receptor (GABABR) in APP/PS1 mice (Salazar et al., 2021). To determine if changes in GABABR restricted to glia serve a role in AD, we developed a mouse model with a reduction of GABABR restricted to macrophages, GAB/CX3ert. This model exhibits changes in gene expression and electrophysiological alterations similar to amyloid mouse models of AD. Crossing the GAB/CX3ert mouse with APP/PS1 resulted in significant increases in Aβ pathology. Our data demonstrates that decreased GABABR on macrophages leads to several changes observed in AD mouse models, as well as exacer- bation of AD pathology when crossed with existing models. These data suggest a novel mechanism in AD pathogenesis

Clinical and biological relevance of glial fibrillary acidic protein in Alzheimer’s disease

Abstract Introduction There is a tremendous need for identifying reliable blood-based biomarkers for Alzheimer’s disease (AD) that are tied to the biological ATN (amyloid, tau and neurodegeneration) framework as well as clinical assessment and progression. Methods One hundred forty-four elderly participants underwent 18F-AV45 positron emission tomography (PET) scan, structural magnetic resonance imaging (MRI) scan, and blood sample collection. The composite standardized uptake value ratio (SUVR) was derived from 18F-AV45 PET to assess brain amyloid burden, and the hippocampal volume was determined from structural MRI scans. Plasma glial fibrillary acidic protein (GFAP), phosphorylated tau-181 (ptau-181), and neurofilament light (NfL) measured by single molecular array (SIMOA) technology were assessed with respect to ATN framework, genetic risk factor, age, clinical assessment, and future functional decline among the participants. Results Among the three plasma markers, GFAP best discriminated participants stratified by clinical diagnosis and brain amyloid status. Age was strongly associated with NfL, followed by GFAP and ptau-181 at much weaker extent. Brain amyloid was strongly associated with plasma GFAP and ptau-181 and to a lesser extent with plasma NfL. Moderate association was observed between plasma markers. Hippocampal volume was weakly associated with all three markers. Elevated GFAP and ptau-181 were associated with worse cognition, and plasma GFAP was the most predictive of future functional decline. Combining GFAP and ptau-181 together was the best model to predict brain amyloid status across all participants (AUC = 0.86) or within cognitively impaired participants (AUC = 0.93); adding NfL as an additional predictor only had a marginal improvement. Conclusion Our findings indicate that GFAP is of potential clinical utility in screening amyloid pathology and predicting future cognitive decline. GFAP, NfL, and ptau-181 were moderately associated with each other, with discrepant relevance to age, sex, and AD genetic risk, suggesting their relevant but differential roles for AD assessment. The combination of GFAP with ptau-181 provides an accurate model to predict brain amyloid status, with the superior performance of GFAP over ptau-181 when the prediction is limited to cognitively impaired participants