Objective Genomic 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. Methods We 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. Results We 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. Interpretation Fibroblast‐based RNA‐seq in our selected cohort improved variant interpretation and offered a modest yield in patients without prior candidate variants. ANN NEUROL 2026
Saparov et al. (2026) studied this question.