bioRxiv Science⌕ Search

bioRxiv · 10.1101/2024.06.20.599774

Cortical synaptic vulnerabilities revealed in a α-synuclein aggregation model of Parkinson's disease

Abstract

-Synuclein aggregates characterize -synucleinopathies, including Parkinsons disease and Dementia with Lewy bodies. A majority of people with these disorders experience cognitive decline, and its extent correlates with cortical -synuclein pathology. Mechanisms by which pathology targets cortical circuits remain to be understood so that the debilitating non-motor impairments can be addressed. Overt neuronal loss is not a major feature of cortical pathology, but a reduction of presynaptic sites has been reported at late stages of PD. We here define excitatory synapses as neuronal loci affected by -synuclein aggregation, showing that they are progressively lost, and identify temporal and spatial patterns of synaptic vulnerability. Results were obtained in a mouse model using intrastriatal injection of pre-formed -synuclein fibrils to template the aggregation of endogenous -synuclein in cortical neurons. Lewy neurite-like aggregates were predominantly observed in axons. Super-resolved imaging showed -synuclein aggregation within cortical synapses and revealed that synaptic aggregation is most severe proximal to Lewy neurite-like structures and linked to the earliest detectable loss of excitatory synapses. Excitatory synapses also exhibited ultrastructural aberrations, including a redistribution of pre- and post-synaptic protein clusters away from contact sites and reduced synaptic vesicle size. As pathology advanced, VGLUT1-positive intracortical synapses, enriched in -synuclein, were progressively vulnerable in this striatal seeding model, while VGLUT2-positive long-range synapses with minimal -synuclein were spared. Inhibitory synapses were not affected. In agreement with a disruptive role of synaptic -synuclein aggregation, super-resolved mesoscale imaging determined that synaptic but not non-synaptic -synuclein pathology is correlated with excitatory synapse loss. Physiological recordings confirmed impaired excitatory neurotransmission. Pathology propagation tracked cortical connectivity, with intra-column synapse loss correlated between interconnected layers V and II/III. Contralateral areas receiving projections from pathologic layer V also exhibited synapse loss. These findings reveal synapses as principal cellular loci of -synuclein pathology and define how molecular and circuit-based mechanisms underlie the cortical progression of synaptic pathology in -synucleinopathies.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Sah, S., Sauerbeck, A. D., Gupta, J., Perez-Acuna, D., Reiber, J. E., Russell, D., Goralski, T., Henderson, M., Volpicelli-Daley, L. A., Higley, M. J., Kummer, T. T., Biederer, T.. 2024-06-21. Cortical synaptic vulnerabilities revealed in a α-synuclein aggregation model of Parkinson's disease. https://doi.org/10.1101/2024.06.20.599774

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↗