Search bioRxivSearch

bioRxiv · 10.1101/639914

Synaptic Proteome Alterations in the Primary Auditory Cortex of Schizophrenia

Abstract

ImportanceFindings from unbiased genetic studies have consistently implicated synaptic protein networks in Schizophrenia (Sz), but the molecular pathology at these networks and their potential contribution to the synaptic and circuit deficits thought to underlie disease symptoms remain unknown.\n\nObjectiveTo determine if protein levels are altered within synapses from primary auditory cortex (A1) of subjects with Sz; and if so, are these differences restricted to the synapse or present throughout the grey matter?\n\nDesignA paired case-control design was utilized for this study. Biochemical fractional - targeted Mass Spectrometry (MS) was used to measure the levels of >350 proteins in A1 grey matter homogenate and synaptosome preparations, respectively. All experimenters were blinded to diagnosis at every stage of sample preparation, MS analysis, and raw data processing. The effects of postmortem interval (PMI) and antipsychotic drug treatment on protein levels were assessed in mouse and monkey models, respectively.\n\nSettingAll cases were recruited from a single site, The Allegheny County Office of the Medical Examiner, and all tissues were processed at the University of Pittsburgh.\n\nParticipantsBrain specimens from all subjects were obtained during autopsies conducted at the Allegheny County Office of the Medical Examiner after receiving consent from the next-of-kin. An independent panel of experienced clinicians made consensus Diagnostic and Statistical Manual of Mental Disorders Fourth Edition diagnoses. Unaffected comparison subjects underwent identical assessments and were determined to be free of lifetime psychiatric illness. Each Sz subject was matched by sex, and as closely as possible for age and PMI, with one unaffected comparison subject.\n\nMain Outcomes and MeasuresPrimary measures were homogenate and synaptosome protein levels and their co-regulation network features. Prior to data collection we hypothesized: 1. That levels of canonical postsynaptic proteins in A1 synaptosome preparations would differ between Sz and control subjects; and 2. That these differences would not be explained by changes in total A1 homogenate protein levels.\n\nResultsMean subject age was 48 years for both groups with a range of 17-83; each group included 35 males and 13 females; mean PMI was 17.7 hours in controls and 17.9 in Sz. We observed robust alterations (q < 0.05) in synaptosome levels of canonical mitochondrial and postsynaptic proteins that were highly co-regulated and not readily explained by postmortem interval, antipsychotic drug treatment, synaptosome yield, or underlying alterations in homogenate protein levels.\n\nConclusions and RelevanceOur findings indicate a robust and highly coordinated rearrangement of the synaptic proteome likely driven by aberrant synaptic, not cell-wide, proteostasis. In line with unbiased genetic findings, our results identified alterations in synaptic levels of postsynaptic proteins, providing a road map to identify the specific cells and circuits that are impaired in Sz A1.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

MacDonald, M., Garver, M., Newman, J., Sun, Z., Kannarkat, J., Salisbury, R., Glausier, J., Ding, Y., Lewis, D. A., Yates, N., Sweet, R. A.. 2019-05-16. Synaptic Proteome Alterations in the Primary Auditory Cortex of Schizophrenia. https://doi.org/10.1101/639914

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