bioRxiv Science⌕ Search

bioRxiv · 10.1101/2024.06.11.598410

Mutant HTT protein decreases with CAG repeat expansion: implications for therapeutics and bioassays.

Abstract

Huntingtons disease is an inherited neurodegenerative disorder caused by a CAG repeat expansion that encodes a polyglutamine tract in the HTT protein. The mutant CAG repeat is unstable and expands in specific brain cells and peripheral tissues throughout life. Genes involved in the DNA mismatch repair pathways, known to act on expansion, have been identified as genetics modifiers, therefore, it is the rate of somatic CAG repeat expansion that drives the age of onset and rate of disease progression. In the context of an expanded CAG repeat, the HTT pre-mRNA can be alternatively processed to generate the HTT1a transcript, that encodes the aggregation prone and highly pathogenic HTT1a protein. This may be a mechanism through which somatic CAG repeat expansion exerts its pathogenic effects, as the longer the CAG repeat, the more HTT1a and HTT1a is produced. The allelic series of knock-in mouse models: HdhQ20, HdhQ50, HdhQ80, HdhQ111, CAG140 and zQ175 with polyQ expansions of 20, 50, 80, 111 140 and [~]190 can be used to model the molecular and cellular consequences of CAG repeat expansion within a single neuron. By western blot of cortical lysates, we found that mutant HTT levels decreased with increasing CAG repeat length; mutant HTT was only 23% and 10% of wild-type levels in CAG140 and zQ175 cortices, respectively. To identify the optimal bioassays for detecting the full-length HTT and HTT1a isoforms, we interrogated the pairwise combinations of seven well-characterized antibodies on both the HTRF and MSD platforms. In total we tested 32 HTRF and 32 MSD assays to detect full-length mutant HTT, HTT1a, total mutant HTT (full-length HTT and HTT1a) and total full-length HTT (mutant and wild type). None of these assays recapitulated the full-length mutant HTT levels as measured by western blot. We recommend using isoform- and species-specific assays that detect either full-length mutant HTT, HTT1a or wild-type HTT as opposed to those that detect more than one isoform simultaneously. Our finding that as the CAG repeat expands, full-length mutant HTT levels decrease, whilst HTT1a and HTT1a levels increase has implications for therapeutic strategies. If mutant HTT levels in cells containing (CAG)200 are only 10% of wild-type, HTT-lowering strategies targeting full-length HTT at sequences 3 to intron 1 HTT will predominantly lower wild-type HTT, as mutant HTT levels in these cells are already depleted. These data support a therapeutic strategy that lowers HTT1a and depletes levels of the HTT1a protein.

Source connections

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Landles, C., Osborne, G. F., Phillips, J., Canibano Pico, M., Nita, I. M., Ali, N., Greene, J. R., Sathasivam, K., Bates, G. P.. 2024-06-11. Mutant HTT protein decreases with CAG repeat expansion: implications for therapeutics and bioassays.. https://doi.org/10.1101/2024.06.11.598410

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↗