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Record W4414524573 · doi:10.1101/2025.09.25.677871

Deciphering the circular RNAs landscape in amyotrophic lateral sclerosis

2025· preprint· en· W4414524573 on OpenAlexaff
Reza Ataei, Javad Amini, Nima Sanadgol, Anne F. Simon, Martin L. Duennwald

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2025
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCircular RNAs in diseases
Canadian institutionsWestern University
Fundersnot available
KeywordsAmyotrophic lateral sclerosisIn silicoGeneBiomarkermicroRNACircular RNAMultiple sclerosisDiseaseTranscriptome

Abstract

fetched live from OpenAlex

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

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.012
GPT teacher head0.218
Teacher spread0.205 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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