A prospective trial comparing programmable targeted long-read sequencing and short-read genome sequencing for genetic diagnosis of cerebellar ataxia
- PMID: 40015980
- PMCID: PMC12047251
- DOI: 10.1101/gr.279634.124
A prospective trial comparing programmable targeted long-read sequencing and short-read genome sequencing for genetic diagnosis of cerebellar ataxia
Abstract
The cerebellar ataxias (CAs) are a heterogeneous group of disorders characterized by progressive incoordination. Seventeen repeat expansion (RE) loci have been identified as the primary genetic cause and account for >80% of genetic diagnoses. Despite this, diagnostic testing is limited and inefficient, often utilizing single gene assays. This study evaluates the effectiveness of long- and short-read sequencing as diagnostic tools for CA. We recruited 110 individuals (48 females, 62 males) with a clinical diagnosis of CA. Short-read genome sequencing (SR-GS) was performed to identify pathogenic RE and also non-RE variants in 356 genes associated with CA. Independently, long-read sequencing with adaptive sampling (LR-AS) was performed to identify pathogenic RE. SR-GS provided a genetic diagnosis for 38% of the cohort (40/110) including seven non-RE pathogenic variants. RE causes disease in 33 individuals, with the most common condition being SCA27B (n = 24). In comparison, LR-AS identified pathogenic RE in 29 individuals. RE identification for the two methods was concordant apart from four SCA27B cases not detected by LR-AS due to low read depth. For both technologies manual review of the RE alignment enhances diagnostic outcomes. Orthogonal testing for SCA27B revealed a 15% and 0% false positive rate for SR-GS and LR-AS, respectively. In conclusion, both technologies are powerful screening tools for CA. SR-GS is a mature technology currently used by diagnostic providers, requiring only minor changes in bioinformatic workflows to enable CA diagnostics. LR-AS offers considerable advantages in the context of RE detection and characterization but requires optimization before clinical implementation.
© 2025 Rafehi et al.; Published by Cold Spring Harbor Laboratory Press.
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