Fibroblast Transcriptomics in Molecular Diagnostics of a Comprehensive Dystonia Cohort

Area of Science:

• Genomic Medicine
• Molecular Biology
• Neurogenetics

Background:

• Genomic sequencing alone diagnoses less than 50% of dystonia cases.
• Integrating multiomics data is crucial for advancing genome interpretation in genetic disorders.
• Dystonia diagnosis remains challenging due to the complexity of genetic underpinnings.

Purpose of the Study:

• To evaluate the utility of RNA sequencing (RNA-seq) in diagnosing dystonia by analyzing gene expression and splicing aberrations.
• To improve genome interpretation by integrating multiomics data in a cohort of dystonia patients.
• To identify novel diagnostic variants and pathogenic mechanisms in individuals with undiagnosed dystonia.

Main Methods:

• RNA sequencing (RNA-seq) was performed on skin fibroblast biopsies from 167 dystonia patients.
• An RNA-seq analysis pipeline focused on identifying expression and splicing aberrations.
• Patients included those with early-onset, non-focal dystonia, and coexisting features, with varying prior genomic findings.

Main Results:

• Fibroblast RNA-seq detected over 80% of known dystonia-associated genes.
• Expression and splicing aberration analyses identified significant RNA defects in dystonia-associated genes.
• A 6.9% diagnostic uplift was achieved in previously undiagnosed patients, identifying novel splice-region and intronic variants.

Conclusions:

• Fibroblast-based RNA-seq enhances variant interpretation for dystonia.
• The study demonstrated a modest diagnostic yield in patients lacking prior candidate variants.
• Integration of RNA-seq data offers a valuable complementary approach to genomic sequencing for dystonia diagnosis.