bioRxiv Science⌕ Search

bioRxiv · 10.1101/2023.04.30.538872

Transcriptomic Characterization Reveals Disrupted Medium Spiny Neuron Trajectories in Huntington's Disease and Possible Therapeutic Avenues

Abstract

Huntingtons disease (HD) is a neurodegenerative disorder caused by an expansion of CAG repeats in exon 1 of the HTT gene, ultimately resulting in the generation of a mutant HTT (mHTT) protein. Although mHTT is expressed in various tissues, it significantly affects medium spiny neurons (MSNs) in the striatum, resulting in their loss and the subsequent motor function impairment in HD. While HD symptoms typically emerge in midlife, disrupted MSN neurodevelopment has an important role. To explore the effects of mHTT on MSN development, we differentiated HD induced pluripotent stem cells (iPSC) and isogenic controls into neuronal stem cells, and then generated a developing MSN population encompassing early, intermediate progenitors, and mature MSNs. Single-cell RNA sequencing revealed that the developmental trajectory of MSNs in our model closely emulated the trajectory of fetal striatal neurons. However, in the HD MSN cultures, the differentiation process downregulated several crucial genes required for proper MSN maturation, including Achaete-scute homolog 1 and members of the DLX family of transcription factors. Our analysis also uncovered a progressive dysregulation of multiple HD-related pathways as the MSNs matured, including the NRF2-mediated oxidative stress response and mitogen-activated protein kinase signaling. Using the transcriptional profile of developing HD MSNs, we searched the L1000 dataset for small molecules that induce the opposite gene expression pattern. Our analysis pinpointed numerous small molecules with known benefits in HD models, as well as previously untested novel molecules. A top novel candidate, Cerulenin, partially restored the DARPP-32 levels and electrical activity in HD MSNs, and also modulated genes involved in multiple HD-related pathways.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Galicia Aquirre, C., Tshilenge, K.-T., Battistoni, E., Lopez-Ramirez, A., Naphade, S., Perez, K., Song, S., Mooney, S. D., Melov, S., Ehrlich, M. E., Ellerby, L. M.. 2023-05-01. Transcriptomic Characterization Reveals Disrupted Medium Spiny Neuron Trajectories in Huntington's Disease and Possible Therapeutic Avenues. https://doi.org/10.1101/2023.04.30.538872

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↗