ReviewJournal of neurology2025
Past, present, and future of genomic technologies in cerebellar ataxias.
Review in Journal of neurology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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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.
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6 authors.
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Abstract
Inherited cerebellar ataxias (ICA) are a group of rare, genetically and clinically heterogeneous neurodegenerative disorders, often caused by a broad spectrum of genetic variants, including single nucleotide variants, structural variations, and especially short tandem repeat (STR) expansions. Over time, advances in genomic technologies have profoundly reshaped the diagnostic approach and scientific understanding of ICA. This review traces the evolution of genomic tools, from first-generation methods, such as Sanger sequencing and southern blot, through the revolution brought by short-read second-generation sequencing, including gene panels, exome sequencing (ES), and genome sequencing (GS). These technologies significantly increased diagnostic yield and enabled the discovery of numerous ICA genes, although short-read sequencing remained limited in its ability to detect STR expansions and structural variants accurately. Recently, third-generation long-read sequencing (LRS) technologies, such as Single Molecule Real Time (SMRT) and nanopore sequencing, have emerged, offering reliable detection of all classes of variants, including complex and previously undetectable STR expansions. Optical genome mapping is also highlighted as a powerful, non-sequencing alternative for detecting large SVs and STRs. The manuscript underscores the reciprocal relationship between technological advances and medical knowledge in ICA. With LRS and integrated multi-omics approaches, the field stands at the cusp of a new era in diagnostics, enabling comprehensive variant detection and deeper insights into ICA pathophysiology. However, challenges related to cost, data interpretation, and population biases in reference databases remain.
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