TY - JOUR
T1 - Next-generation sequencing and bioinformatics in rare movement disorders
AU - Zech, Michael
AU - Winkelmann, Juliane
N1 - Publisher Copyright:
© Springer Nature Limited 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
PY - 2024/2
Y1 - 2024/2
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85181238591&partnerID=8YFLogxK
U2 - 10.1038/s41582-023-00909-9
DO - 10.1038/s41582-023-00909-9
M3 - Article
AN - SCOPUS:85181238591
SN - 1759-4758
VL - 20
SP - 114
EP - 126
JO - Nature Reviews Neurology
JF - Nature Reviews Neurology
IS - 2
ER -