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Record W4415124179 · doi:10.1101/2025.10.10.25336355

Therapeutic targeting of alternative splicing caused by a lethal noncoding structural variant in X-linked dystonia parkinsonism

2025· preprint· en· W4415124179 on OpenAlexaff
Rachita Yadav, Christine A. Vaine, Aloysius Domingo, Sheldon C. Reed, Shivangi Shah, Dadi Gao, Kathryn O’Keefe, Monica Salani, John Lemanski, Riya Bhavsar, Moira A. McMahon, Michaela Jackson, Margo Courtney, Micaela G. Murcar, Cara Fernandez‐Cerado, G. Paul Legarda, Michelle Sy, M. Salvie Velasco-Andrada, Edwin L. Muñoz, Mark Angelo C. Ang, Cid Czarina E. Diesta, Serkan Erdin, Ellen B. Penney, Laurie J. Ozelius, Nutan Sharma, C. Frank Bennett, D. Cristopher Bragg, Michael E. Talkowski

Bibliographic record

VenuemedRxiv · 2025
Typepreprint
Languageen
FieldMedicine
TopicNeurological disorders and treatments
Canadian institutionsHealth Care Foundation
FundersNational Institutes of HealthMassachusetts General Hospital
KeywordsRNA splicingAlternative splicingParkinsonismCRISPRTranscriptomeNeural stem cell

Abstract

fetched live from OpenAlex

X-linked Dystonia-Parkinsonism (XDP) is a lethal adult-onset neurodegenerative disorder that exhibits features of dystonia and parkinsonism and is exclusively associated with a causal founder haplotype that is indigenous to the Philippines and affects Filipino males. Using patient-specific fibroblasts, neural stem cells (NSC), and other neuronal models, we discovered that cryptic alternative splicing caused by a novel SINE-VNTR-Alu (SVA) mobile element insertion into intron 32 of TAF1 is a mechanistic hallmark of XDP. We leveraged postmortem brain samples from an XDP-specific brain bank to demonstrate that the molecular hallmarks of XDP observed in neural stem cells (NSCs) mirror abnormalities observed in brain tissues from affected patients. Based on these findings that patient-specific NSCs reproduce mechanistic signatures found in the brain, we sought to develop a bespoke precision therapeutic for XDP and evaluate its relative efficacy in ameliorating transcriptomic signatures in neuronal models. We first used CRISPR-based excision of the SVA and demonstrated ablation of all aberrant splicing and dysregulation of TAF1 expression in NSCs across 30 independent clones. CRISPR-based correction of the XDP haplotype also restored the expression of 424 of 1,490 (30%) differentially expressed genes (DEGs) that were altered in XDP patient lines and greatly exceeded what would be expected by chance (p-value = 9.89e-87). While in vivo delivery of a gold standard CRISPR therapy is currently not feasible for XDP, we evaluated a tractable approach for Filipino patients by exploring the potential to modulate alternative splicing in XDP patients using antisense oligonucleotides (ASOs). To accomplish this, we developed a large-scale and well controlled functional genomics platform that screened eighty ASOs targeting intron 32 of XDP patients, followed by prioritization of lead ASOs based on attenuation of the alternative splicing signature. In transcriptome analyses across 1,550 libraries, we found that 8 of the 12 lead ASOs ameliorated the targeted XDP aberrant splicing. Moreover, we found that the two lead ASOs exhibited 38% and 43% rescue of XDP-specific DEGs that were also rescued by CRISPR excision of the SVA (enrichment p-values = 2.06e-13 and 2.27e-05, respectively). These rescues represented restoration of key molecular functions previously implicated in XDP, such as synaptic function, DNA-binding transcription factor activity, and gliogenesis. This study highlights a path to a potential targeted therapeutic for XDP and the capacity to exploit functional genomic signatures in patient-derived neural models to develop a scalable precision therapeutic platform for rare genetic disorders.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.029
GPT teacher head0.308
Teacher spread0.279 · 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 designBench or experimental
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

Citations1
Published2025
Admission routes1
Has abstractyes

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