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Genome sequencing reanalysis increases the diagnostic yield in dystonia
Avi Fellner1, Gurusidheshwar M Wali2, Neil Mahant3
1Garvan Institute of Medical Research, Darlinghurst, NSW, Australia; The Neurogenetics Clinic, Raphael Recanati Genetics Institute, Rabin Medical Center, Beilinson Hospital, Petah Tikva, Israel.
Parkinsonism & Related Disorders
|May 21, 2024
Summary
Reanalyzing genomic data (GS) in dystonia patients significantly boosts diagnostic rates. Periodic re-evaluation of existing GS data offers new genetic diagnoses for previously undiagnosed individuals.
Area of Science:
- Genomics
- Neurogenetics
- Rare Diseases
Background:
- Dystonia is a heterogeneous neurological disorder with a significant genetic component.
- Prior genome sequencing (GS) has limitations in initial diagnostic yield for complex genetic conditions.
- Genomic data reanalysis offers a strategy to improve diagnostic outcomes.
Purpose of the Study:
- To assess the impact of genomic data reanalysis on the diagnostic yield in dystonia patients.
- To determine the effectiveness of gene-specific collaborations and systematic reanalysis in identifying genetic causes of dystonia.
- To evaluate the potential for reanalysis to uncover diagnoses missed by initial genome sequencing.
Main Methods:
- Retrospective analysis of genome sequencing (GS) data from 111 dystonia patients initially analyzed in 2019.
- Reanalysis conducted between 2020-2023 utilizing gene-specific discovery collaborations and systematic data review.
- Inclusion of patients with heterogeneous dystonia phenotypes and high phenotype-based dystonia scores (≥3).
Main Results:
- Initial GS identified a diagnosis in 11.7% (13/111) of cases.
- Reanalysis increased the diagnostic yield by an additional 7.2% (8/111), identifying variants in genes like VPS16, AOPEP, POLG, NUS1, and DDX3X.
- Further potential diagnoses were suggested by variants of uncertain significance and phenotypic expansion in genes such as FBXL4, EIF2AK2, SLC2A1, and TREX1.
Conclusions:
- Genomic data reanalysis significantly enhances the diagnostic yield for dystonia, increasing it from 11.7% to 18.9% (potentially up to 22.5%).
- Periodic re-interrogation of existing GS datasets is a valuable strategy for uncovering additional genetic diagnoses in dystonia.
- These findings have important implications for patient management and family genetic counseling.
