Search bioRxiv⌕ Search

bioRxiv · 10.1101/2022.10.24.513188

Localized APP pathology in the hippocampus is sufficient to result in progressive disorganization of the timing of neuronal firing patterns

Abstract

Deficits in spatial navigation are among the early symptoms in Alzheimers disease patients, consistent with the hippocampal formation as the site for spatial computations and disease onset. Although the correspondence between the early symptoms and brain regions that are affected early in the disease has been recognized, it is not clear whether progressive cognitive decline is solely caused by a spreading pathology or whether a focal pathology can by itself cause aberrant neuronal activity in a larger network. These possibilities cannot be distinguished in standard disease models which broadly express APP across brain regions. We therefore generated a mouse model in which the expression of mutant human APP was limited to hippocampal CA3 cells (CA3-APP mice). We first asked whether the limited pathology in CA3 can result in memory deficits and found impaired performance of CA3-APP mice in a hippocampus-dependent memory task. By then recording in the CA1 region, we asked to what extent neuronal activity patterns emerged in a brain region which received projections from APP-expressing CA3 cells, but did itself not show any primary pathology. While the spatial firing patterns of CA1 cells were preserved, we observed a reduced theta oscillation frequency in the local field potential and in a subpopulation of principal cells in CA1. Furthermore, CA1 interneurons showed decreased theta oscillation frequencies, and this effect was even more pronounced in CA3 interneurons, which also do not directly express APP. Pathology that is highly localized and limited to presynaptic cells is thus sufficient to cause aberrant firing patterns in postsynaptic neuronal networks, which indicates that disease progression is not only from a spreading molecular pathology but also mediated by progressive physiological dysfunction.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Viana da Silva, S., Haberl, M. G., Gaur, K., Patel, R., Narayan, G., Ledakis, M., Fu, M. L., Koo, E. H., Leutgeb, J. K., Leutgeb, S.. 2022-10-25. Localized APP pathology in the hippocampus is sufficient to result in progressive disorganization of the timing of neuronal firing patterns. https://doi.org/10.1101/2022.10.24.513188

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↗