bioRxiv Science⌕ Search

bioRxiv · 10.1101/2025.09.25.677871

Deciphering the circular RNAs landscape in amyotrophic lateral sclerosis

Abstract

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disorder characterized by the progressive loss of motor neurons, with most cases lacking a clear genetic basis. Emerging evidence highlights the involvement of non-coding RNAs, particularly circular RNAs (circRNAs), in disease onset and progression. In this study, we investigated circRNAs implicated in ALS and related motor neuron diseases (MNDs). First, we conducted a systematic review to identify ALS-associated circRNAs, followed by in silico analyses of 15 selected candidates. Our results revealed that hsa_circ_0000099, hsa_circ_0001017, hsa_circ_004846, and hsa_circ_0034880 regulate a high number of ALS-related genes through miRNA sponging. Pathway enrichment analysis indicated that hsa_circ_0000099 is particularly involved in unfolded protein response, oxidative stress, cell cycle regulation, and apoptosis. Protein-RNA interaction analysis further showed that ALS-related circRNAs can sponge 20 RNA-binding proteins, with FMR1, ELAVL1, EIF4A3, and SRSF1 exhibiting the highest number of interactions. Additionally, molecular docking analysis demonstrated that FUS mutations significantly alter its binding affinity to hsa_circ_0000567 and hsa_circ_0060762. RNA-seq data from ALS patients confirmed significant alterations in the expression of host genes of ALS-related circRNAs and hub proteins across affected tissues, including the spinal cord and multiple brain regions. Collectively, these findings support circRNAs as active contributors to ALS pathogenesis. In particular, the host gene of hsa_circ_0000099, which is expressed in the spinal cord and hippocampus, emerges as a potential biomarker for tissue-specific impairment in ALS. Moreover, its regulatory role in key ALS-related cellular pathways underscores its promise as a candidate for biomarker development and therapeutic targeting. Further experimental validation is warranted to confirm its role in ALS pathology. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=110 SRC="FIGDIR/small/677871v1_ufig1.gif" ALT="Figure 1"> View larger version (37K): org.highwire.dtl.DTLVardef@15d0389org.highwire.dtl.DTLVardef@1934327org.highwire.dtl.DTLVardef@11ddd3aorg.highwire.dtl.DTLVardef@1a74c09_HPS_FORMAT_FIGEXP M_FIG C_FIG

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Ataei, R., Amini, j., Sanadgol, N., Simon, A. F., Duennwald, M. L.. 2025-09-25. Deciphering the circular RNAs landscape in amyotrophic lateral sclerosis. https://doi.org/10.1101/2025.09.25.677871

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↗