bioRxiv Science⌕ Search

bioRxiv · 10.1101/2025.04.10.645950

Anti-Aβ immunotherapy-mediated amyloid clearance attenuates microglial activation without inducing exhaustion at residual plaques

Abstract

Anti-amyloid {beta}-peptide (A{beta}) immunotherapy was developed to reduce amyloid plaque pathology and slow cognitive decline during progression of Alzheimers disease. Efficient amyloid plaque clearance has been proven in clinical trials testing anti-A{beta} antibodies, with the impact on cognitive endpoints correlating with the extent of plaque removal. However, treatment is associated with adverse side-effects, such as oedema and haemorrhages, which are potentially linked to the induced immune response. To improve the safety profile of these molecules, it is imperative to understand the consequences of anti-A{beta} antibody treatment on immune cell function. Here, we investigated the effects of long-term chronic anti-A{beta} treatment on amyloid plaque pathology and microglial response in the APP-SAA triple knock-in mouse model. Mice were treated weekly with anti-A{beta} antibody from 4-8 months of age. Long-term treatment with anti-A{beta} results in a robust and dose-dependent removal of amyloid plaque pathology, with a higher efficiency for removing diffuse over dense-core plaques. Analysis of the CSF proteome indicates a reduction of markers for neurodegeneration including Tau and -Synuclein, as well as immune cell related proteins. Bulk RNA-seq revealed a dose-dependent decrease in brain-wide disease-associated microglial (DAM) and glycolytic gene expression, which is supported by a parallel decrease of glucose uptake and protein levels of Triggering receptor of myeloid cells 2 (Trem2) protein, a major immune receptor involved in DAM activation of microglia. In contrast, DAM activation around remaining plaques remains high regardless of treatment dose. In addition, microglia surrounding remaining plaques display a dose-dependent increase in microglial clustering and a selective increase in antigen presenting and immune signalling proteins. These findings demonstrate that long-term chronic anti-A{beta} mediated removal of A{beta} leads to a dose dependent decrease in brain-wide microglial DAM activation and neurodegeneration, while microglia at residual plaques display a combined DAM and antigen presenting phenotype that suggests a continued treatment response. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=161 SRC="FIGDIR/small/645950v1_ufig1.gif" ALT="Figure 1"> View larger version (46K): org.highwire.dtl.DTLVardef@6d1a49org.highwire.dtl.DTLVardef@d8c14dorg.highwire.dtl.DTLVardef@7ae330org.highwire.dtl.DTLVardef@1d96cc3_HPS_FORMAT_FIGEXP M_FIG Graphical abstract: Schematic overview of the effects of chronic long-term anti-A treatment in APP-SAA mice Schematic was created with BioRender.com C_FIG

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

de Weerd, L., Hummel, S., Mueller, S. A., Paris, I., Sandmann, T., Eichholtz, M., Gröger, R., Englert, A., Wagner, S., Ha, C., Davis, S. S., Warkins, V., Xia, D., Nuscher, B., Berghofer, A., Reich, M., Feiten, A. F., Schlepckow, K., Willem, M., Lichtenthaler, S. F., Lewcock, J. W., Monroe, K. M., Brendel, M., Haass, C.. 2025-04-17. Anti-Aβ immunotherapy-mediated amyloid clearance attenuates microglial activation without inducing exhaustion at residual plaques. https://doi.org/10.1101/2025.04.10.645950

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

The Unreasonable Effectiveness of Cell Types in Describing Neuronal Physiological Features

Single-cell RNA sequencing (scRNA-seq) captures detailed gene expression profiles at scale, while patch-clamp recordings measure intrinsic neuronal electrophysiological properties. Modeling the relations between these two modalities remains a challenge. Here, we compare how well electrophysiological features can be predicted by traditional transcriptomic cell type classification, representations derived from a foundational model (scGPT) pretrained on large-scale scRNA-seq datasets, ion channel-coding genes, and highly variable genes. Using paired transcriptomic and electrophysiological patch-sequencing data from 495 human neurons from neurosurgical tissue, we find that cluster-level cell type representations consistently outperform highly variable gene selection, ion channel gene selection, and context-enriched scGPT embeddings. Notably, performance varies across model architectures and initializations, and the best results are obtained by combining the outputs of separate cell type and scGPT-based models. Together, these findings suggest that traditional discrete cellular classification is highly effective in predicting physiological features. For maximum performance it can be complemented by pretrained transformer models.

neuroscience↗

A nonlinear inhibition pathway underlying cortical responses to tuned holographic optogenetic perturbations

Optogenetics enables causal manipulation of cortical activity. Perturbation responses can be counterintuitive due to network interactions, making theory essential for predicting them. Existing approaches often rely on linear approximations, which fail for many biologically relevant perturbations. Here we develop a nonlinear theory of responses to holographic perturbations in cell-type-specific recurrent networks with structured connectivity. We fit a nonlinear model to mouse V1 data, which shows cotuned-ensemble suppression: perturbing spatially clustered neurons with similar preferred orientations yields markedly stronger short-range suppression than perturbing untuned ensembles. We show that cotuned-ensemble suppression arises from a feature-tuned, nonlinear inhibition pathway implicating somatostatin-positive (SST) interneurons. The theory predicts that cotuned ensembles suppress parvalbumin-positive (PV) neurons but facilitate SST neurons, and links the degree of cotuned-ensemble suppression or facilitation to the variance of the SST response. This framework identifies mechanisms by which nonlinear inhibition sculpts cortical dynamics and establishes a predictive basis for targeted optogenetic interventions.

neuroscience↗

Proteomic signatures of APOE ε4 across human tissues and cell types in Alzheimers disease

The apolipoprotein E {varepsilon}4 (APOE {varepsilon}4) allele is the strongest genetic risk factor for late-onset Alzheimers disease (AD). However, the underlying molecular mechanisms remain unclear. This study included 1691 participants from the Religious Orders Study and Rush Memory and Aging Project (ROSMAP), 1226 participants from the Accelerating Medicines Partnership - Alzheimers Disease (AMP-AD) Diverse Cohorts Study, and 735 participants from the Alzheimers Disease Neuroimaging Initiative (ADNI). To characterise APOE {varepsilon}4 molecular effects, we analysed proteomic data from plasma, cerebrospinal fluid (CSF), and induced pluripotent stem cell (iPSC)-derived astrocytes and neurons, as well as transcriptomic and proteomic data from multiple brain regions. The association of APOE {varepsilon}4 with AD neuropathology was also examined. APOE {varepsilon}4 carriers shared a plasma proteomic signature enriched for immune processes, irrespective of AD diagnosis. A machine learning classifier trained on this signature discriminated APOE {varepsilon}4 carriers from non-carriers in an independent cohort using CSF proteomics. APOE {varepsilon}4 carriage was associated with higher Braak stages and Consortium to Establish a Registry for Alzheimers Disease (CERAD) score. However, only limited APOE {varepsilon}4-associated transcriptomic and proteomic changes were observed in bulk brain tissue, with poor cross-layer concordance. Proteomic analyses of iPSC-derived astrocytes and neurons further revealed cell-type-specific APOE {varepsilon}4-associated changes. APOE {varepsilon}4 is associated with a consistent proteomic signature across plasma and CSF. Its molecular effects in the brain differ across cell types, brain regions and molecular layers. These findings support the need for cell-type-resolved multi-omic studies to elucidate how APOE {varepsilon}4 confers AD risk.

neuroscience↗