ArticleAnnals of neurology2026
Fibroblast Transcriptomics in Molecular Diagnostics of a Comprehensive Dystonia Cohort.
Article in Annals of neurology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- Collaborative Genomics for Dystonia in Central and Eastern Europe: Successes Achieved, New Frontiers Ahead.Movement disorders : official journal of the Movement Disorder Society · 2026Article
- Neurodevelopmental Disorder with Dystonia and Chorea Linked to De Novo Variants in the Splicing Regulator SRRM4.Movement disorders : official journal of the Movement Disorder Society · 2026Article
- RNA Sequencing Resolves Cryptic Pathogenic Variants in Mitochondrial Disease.Annals of clinical and translational neurology · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
43 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveGenomic sequencing leaves >50% of dystonia-affected individuals without a diagnosis. Where DNA-oriented approaches remain insufficient, integrating multiomics is essential to advance genome interpretation. Herein, we incorporated RNA sequencing (RNA-seq) data from 167 patients with dystonia across a range of ages and presentations.
methodsWe leveraged an RNA-seq analysis pipeline, focused on the identification of expression and splicing aberrations, on RNA-seq from skin biopsies. The recruited patients had early-onset dystonia in 85.0%, non-focal dystonia in 92.2%, and coexisting features in 76.0%. Thirty-six patient samples with pre-identified variants (36/167, 21.6%) and 131 samples with no previously prioritized diagnostic candidates from genomic sequencing (131/167, 78.4%) were evaluated.
resultsWe found that >80% of dystonia-associated genes were detected by fibroblast RNA-seq. Expression and splicing aberration analyses produced a manageable number of significant RNA defects affecting dystonia-associated genes. The approach was especially successful in validating pathogenic effects of loss-of-function variants, with disease-relevant RNA-underexpression detected for 66.7% (10/15). Studying aberrant expression and splicing in the context of other pre-identified variant types yielded relevant results in 28.6% (6/21 samples). We obtained a 6.9% (9/131) diagnostic uplift for patients without prior candidates, all of whom exhibited combined dystonia with autosomal recessive inheritance. The new diagnoses from RNA-seq and genomic reanalysis were based on previously neglected splice-region (3/9) and deep(er) intronic (6/9) variants. For the observed events, integration of new machine-learning scores predicted corresponding aberrant gene expression in the brain.
interpretationFibroblast-based RNA-seq in our selected cohort improved variant interpretation and offered a modest yield in patients without prior candidate variants. ANN NEUROL 2026;99:1363-1378.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.