Next-generation sequencing and bioinformatics in rare movement disorders

被引:14
作者
Zech, Michael [1 ,2 ,3 ]
Winkelmann, Juliane [1 ,2 ,4 ,5 ]
机构
[1] Tech Univ Munich, Inst Human Genet, Sch Med, Munich, Germany
[2] Helmholtz Zentrum Munchen, Inst Neurogenom, Munich, Germany
[3] Tech Univ Munich, Inst Adv Study, Garching, Germany
[4] SyNergy, Munich Cluster Syst Neurol, Munich, Germany
[5] Deutsch Zentrum Psych Gesundheit, DZPG, Munich, Germany
关键词
MUTATION DATABASE; VARIANTS; DISEASE; GENOME; PHENOTYPE; DIAGNOSIS; ASSOCIATION; GENETICS; HOTSPOTS; ARCHIVE;
D O I
10.1038/s41582-023-00909-9
中图分类号
R74 [神经病学与精神病学];
学科分类号
摘要
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.
引用
收藏
页码:114 / 126
页数:13
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