Abstract
The ability to sequence entire exomes and genomes has revolutionized molecular testing in rare movement disorders, and genomic sequencing is becoming an integral part of routine diagnostic workflows for these heterogeneous conditions. However, interpretation of the extensive genomic variant information that is being generated presents substantial challenges. In this Perspective, we outline multidimensional strategies for genetic diagnosis in patients with rare movement disorders. We examine bioinformatics tools and computational metrics that have been developed to facilitate accurate prioritization of disease-causing variants. Additionally, we highlight community-driven data-sharing and case-matchmaking platforms, which are designed to foster the discovery of new genotype-phenotype relationships. Finally, we consider how multiomic data integration might optimize diagnostic success by combining genomic, epigenetic, transcriptomic and/or proteomic profiling to enable a more holistic evaluation of variant effects. Together, the approaches that we discuss offer pathways to the improved understanding of the genetic basis of rare movement disorders. In this Perspective, Zech and Winkelmann outline multidimensional strategies for genetic diagnosis in patients with rare movement disorders and highlight community-driven data-sharing and case-matchmaking platforms designed to foster the discovery of new genotype-phenotype relationships.
Dokumententyp: | Zeitschriftenartikel |
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Fakultät: | Medizin > Munich Cluster for Systems Neurology (SyNergy) |
Themengebiete: | 600 Technik, Medizin, angewandte Wissenschaften > 610 Medizin und Gesundheit |
URN: | urn:nbn:de:bvb:19-epub-117460-9 |
Sprache: | Englisch |
Dokumenten ID: | 117460 |
Datum der Veröffentlichung auf Open Access LMU: | 07. Jun. 2024, 15:47 |
Letzte Änderungen: | 02. Aug. 2024, 11:25 |
DFG: | Gefördert durch die Deutsche Forschungsgemeinschaft (DFG) - 390857198 |