Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain
the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in
Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles
and JavaScript.
Nature Reviews Neurology
volume 20, pages 114–126 (2024)Cite this article
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.
Prices may be subject to local taxes which are calculated during checkout
Rexach, J., Lee, H., Martinez-Agosto, J. A., Nemeth, A. H. & Fogel, B. L. Clinical application of next-generation sequencing to the practice of neurology. Lancet Neurol. 18, 492–503 (2019).
Article
CAS
PubMed
PubMed Central
Google Scholar
Foo, J. N., Liu, J. J. & Tan, E. K. Whole-genome and whole-exome sequencing in neurological diseases. Nat. Rev. Neurol. 8, 508–517 (2012).
Olgiati, S., Quadri, M. & Bonifati, V. Genetics of movement disorders in the next-generation sequencing era. Mov. Disord. 31, 458–470 (2016).
Abdo, W. F., van de Warrenburg, B. P., Burn, D. J., Quinn, N. P. & Bloem, B. R. The clinical approach to movement disorders. Nat. Rev. Neurol. 6, 29–37 (2010).
Cordeiro, D. et al. Genetic landscape of pediatric movement disorders and management implications. Neurol. Genet. 4, e265 (2018).
Article
PubMed
PubMed Central
Google Scholar
Kim, M. J., Yum, M. S., Seo, G. H., Ko, T. S. & Lee, B. H. Phenotypic and genetic complexity in pediatric movement disorders. Front. Genet. 13, 829558 (2022).
Article
CAS
PubMed
PubMed Central
Google Scholar
Perez-Duenas, B. et al. The genetic landscape of complex childhood-onset hyperkinetic movement disorders. Mov. Disord. 37, 2197–2209 (2022).
Article
CAS
PubMed
PubMed Central
Google Scholar
Marras, C. et al. Nomenclature of genetic movement disorders: recommendations of the International Parkinson and Movement Disorder Society Task Force. Mov. Disord. 31, 436–457 (2016).
Lange, L. M. et al. Nomenclature of genetic movement disorders: recommendations of the International Parkinson and Movement Disorder Society Task Force — an update. Mov. Disord. 37, 905–935 (2022).
Hamosh, A., Scott, A. F., Amberger, J. S., Bocchini, C. A. & McKusick, V. A. Online Mendelian Inheritance in Man (OMIM), a knowledgebase of human genes and genetic disorders. Nucleic Acids Res. 33, D514–D517 (2005).
Gorcenco, S. et al. New generation genetic testing entering the clinic. Parkinsonism Relat. Disord. 73, 72–84 (2020).
Kwong, A. K. et al. Exome sequencing in paediatric patients with movement disorders. Orphanet J. Rare Dis. 16, 32 (2021).
Article
PubMed
PubMed Central
Google Scholar
Trinh, J. et al. Utility and implications of exome sequencing in early-onset Parkinson’s disease. Mov. Disord. 34, 133–137 (2019).
Zech, M. et al. Monogenic variants in dystonia: an exome-wide sequencing study. Lancet Neurol. 19, 908–918 (2020).
Article
CAS
PubMed
PubMed Central
Google Scholar
Sun, M. et al. Targeted exome analysis identifies the genetic basis of disease in over 50% of patients with a wide range of ataxia-related phenotypes. Genet. Med. 21, 195–206 (2019).
Martinez-Rubio, D. et al. Mutations, genes, and phenotypes related to movement disorders and ataxias. Int. J. Mol. Sci. 23, 11847 (2022).
Article
CAS
PubMed
PubMed Central
Google Scholar
Landrum, M. J. et al. ClinVar: public archive of interpretations of clinically relevant variants. Nucleic Acids Res. 44, D862–D868 (2016).
Boone, P. M., Wiszniewski, W. & Lupski, J. R. Genomic medicine and neurological disease. Hum. Genet. 130, 103–121 (2011).
Article
CAS
PubMed
PubMed Central
Google Scholar
Cooper, G. M. & Shendure, J. Needles in stacks of needles: finding disease-causal variants in a wealth of genomic data. Nat. Rev. Genet. 12, 628–640 (2011).
Pereira, R., Oliveira, J. & Sousa, M. Bioinformatics and computational tools for next-generation sequencing analysis in clinical genetics. J. Clin. Med. 9, 132 (2020).
Article
CAS
PubMed
PubMed Central
Google Scholar
Karczewski, K. J. et al. The mutational constraint spectrum quantified from variation in 141,456 humans. Nature 581, 434–443 (2020).
Article
CAS
PubMed
PubMed Central
ADS
Google Scholar
Crowther, L. M., Poms, M. & Plecko, B. Multiomics tools for the diagnosis and treatment of rare neurological disease. J. Inherit. Metab. Dis. 41, 425–434 (2018).
Article
CAS
PubMed
PubMed Central
Google Scholar
van Karnebeek, C. D. M. et al. The role of the clinician in the multi-omics era: are you ready? J. Inherit. Metab. Dis. 41, 571–582 (2018).
Article
PubMed
PubMed Central
Google Scholar
Keogh, M. J. & Chinnery, P. F. Next generation sequencing for neurological diseases: new hope or new hype? Clin. Neurol. Neurosurg. 115, 948–953 (2013).
Article
CAS
PubMed
PubMed Central
Google Scholar
Coutelier, M. et al. Efficacy of exome-targeted capture sequencing to detect mutations in known cerebellar ataxia genes. JAMA Neurol. 75, 591–599 (2018).
Article
PubMed
PubMed Central
Google Scholar
Keller Sarmiento, I. J. & Mencacci, N. E. Genetic dystonias: update on classification and new genetic discoveries. Curr. Neurol. Neurosci. Rep. 21, 8 (2021).
Lange, L. M. et al. Genotype-phenotype relations for isolated dystonia genes: MDSGene systematic review. Mov. Disord. 36, 1086–1103 (2021).
Posey, J. E. et al. Molecular diagnostic experience of whole-exome sequencing in adult patients. Genet. Med. 18, 678–685 (2016).
Feng, H. et al. Movement disorder in GNAO1 encephalopathy associated with gain-of-function mutations. Neurology 89, 762–770 (2017).
Article
CAS
PubMed
PubMed Central
Google Scholar
Wirth, T. et al. Highlighting the dystonic phenotype related to GNAO1. Mov. Disord. 37, 1547–1554 (2022).
Article
CAS
PubMed
PubMed Central
Google Scholar
Turro, E. et al. Whole-genome sequencing of patients with rare diseases in a national health system. Nature 583, 96–102 (2020).
Article
CAS
PubMed
PubMed Central
ADS
Google Scholar
100,000 Genomes Project Pilot Investigators et al. 100,000 Genomes pilot on rare-disease diagnosis in health care — preliminary report. N. Engl. J. Med. 385, 1868–1880 (2021).
Bertoli-Avella, A. M. et al. Successful application of genome sequencing in a diagnostic setting: 1007 index cases from a clinically heterogeneous cohort. Eur. J. Hum. Genet. 29, 141–153 (2021).
Di Resta, C., Pipitone, G. B., Carrera, P. & Ferrari, M. Current scenario of the genetic testing for rare neurological disorders exploiting next generation sequencing. Neural Regen. Res. 16, 475–481 (2021).
Pfundt, R. et al. Detection of clinically relevant copy-number variants by exome sequencing in a large cohort of genetic disorders. Genet. Med. 19, 667–675 (2017).
Royer-Bertrand, B. et al. CNV detection from exome sequencing data in routine diagnostics of rare genetic disorders: opportunities and limitations. Genes 12, 1427 (2021).
Article
CAS
PubMed
PubMed Central
Google Scholar
Zech, M. et al. Clinically relevant copy-number variants in exome sequencing data of patients with dystonia. Parkinsonism Relat. Disord. 84, 129–134 (2021).
Coutelier, M. et al. Combining callers improves the detection of copy number variants from whole-genome sequencing. Eur. J. Hum. Genet. 30, 178–186 (2022).
Mok, K. Y. et al. Deletions at 22q11.2 in idiopathic Parkinson’s disease: a combined analysis of genome-wide association data. Lancet Neurol. 15, 585–596 (2016).
Article
CAS
PubMed
PubMed Central
Google Scholar
Cunningham, A. C. et al. Movement disorder phenotypes in children with 22q11.2 deletion syndrome. Mov. Disord. 35, 1272–1274 (2020).
Article
CAS
PubMed
PubMed Central
Google Scholar
Pirooznia, M., Goes, F. S. & Zandi, P. P. Whole-genome CNV analysis: advances in computational approaches. Front. Genet. 6, 138 (2015).
Article
PubMed
PubMed Central
Google Scholar
Lillevali, H. et al. Genome sequencing identifies a homozygous inversion disrupting QDPR as a cause for dihydropteridine reductase deficiency. Mol. Genet. Genom. Med. 8, e1154 (2020).
Chiang, T. et al. Atlas-CNV: a validated approach to call single-exon CNVs in the eMERGESeq gene panel. Genet. Med. 21, 2135–2144 (2019).
Article
PubMed
PubMed Central
Google Scholar
Wagner, M. et al. Mitochondrial DNA mutation analysis from exome sequencing — a more holistic approach in diagnostics of suspected mitochondrial disease. J. Inherit. Metab. Dis. 42, 909–917 (2019).
van der Sanden, B. et al. Systematic analysis of short tandem repeats in 38,095 exomes provides an additional diagnostic yield. Genet. Med. 23, 1569–1573 (2021).
Ibanez, K. et al. Whole genome sequencing for the diagnosis of neurological repeat expansion disorders in the UK: a retrospective diagnostic accuracy and prospective clinical validation study. Lancet Neurol. 21, 234–245 (2022).
Article
CAS
PubMed
PubMed Central
Google Scholar
Griffin, H. R. et al. Accurate mitochondrial DNA sequencing using off-target reads provides a single test to identify pathogenic point mutations. Genet. Med. 16, 962–971 (2014).
Article
CAS
PubMed
PubMed Central
Google Scholar
Poole, O. V. et al. Mitochondrial DNA analysis from exome sequencing data improves diagnostic yield in neurological diseases. Ann. Neurol. 89, 1240–1247 (2021).
Article
CAS
PubMed
PubMed Central
Google Scholar
Yaldiz, B. et al. Twist exome capture allows for lower average sequence coverage in clinical exome sequencing. Hum. Genomics 17, 39 (2023).
Article
CAS
PubMed
PubMed Central
Google Scholar
Dolzhenko, E. et al. ExpansionHunter Denovo: a computational method for locating known and novel repeat expansions in short-read sequencing data. Genome Biol. 21, 102 (2020).
Article
PubMed
PubMed Central
Google Scholar
Rafehi, H. et al. An intronic GAA repeat expansion in FGF14 causes the autosomal-dominant adult-onset ataxia SCA50/ATX-FGF14. Am. J. Hum. Genet. 110, 105–119 (2023).
Magrinelli, F. et al. Detection and characterization of a de novo Alu retrotransposition event causing NKX2-1-related disorder. Mov. Disord. 38, 347–353 (2023).
Gilissen, C., Hoischen, A., Brunner, H. G. & Veltman, J. A. Disease gene identification strategies for exome sequencing. Eur. J. Hum. Genet. 20, 490–497 (2012).
Article
CAS
PubMed
PubMed Central
Google Scholar
Boycott, K. M. et al. International cooperation to enable the diagnosis of all rare genetic diseases. Am. J. Hum. Genet. 100, 695–705 (2017).
Article
CAS
PubMed
PubMed Central
Google Scholar
Skorvanek, M. et al. WARS2 mutations cause dopa-responsive early-onset parkinsonism and progressive myoclonus ataxia. Parkinsonism Relat. Disord. 94, 54–61 (2022).
Sleiman, S. et al. Compound heterozygous variants in SHQ1 are associated with a spectrum of neurological features, including early-onset dystonia. Hum. Mol. Genet. 31, 614–624 (2022).
MacDonald, J. R., Ziman, R., Yuen, R. K., Feuk, L. & Scherer, S. W. The Database of Genomic Variants: a curated collection of structural variation in the human genome. Nucleic Acids Res. 42, D986–D992 (2014).
Lappalainen, I. et al. DbVar and DGVa: public archives for genomic structural variation. Nucleic Acids Res. 41, D936–D941 (2013).
Brunet, T. et al. De novo variants in neurodevelopmental disorders-experiences from a tertiary care center. Clin. Genet. 100, 14–28 (2021).
Chang, F. C. et al. Phenotypic insights into ADCY5-associated disease. Mov. Disord. 31, 1033–1040 (2016).
Article
CAS
PubMed
PubMed Central
Google Scholar
Westenberger, A. et al. Spectrum of FAR1 (fatty acyl-CoA reductase 1) variants and related neurological conditions. Mov. Disord. 38, 502–504 (2023).
Meyer, E. et al. Mutations in the histone methyltransferase gene KMT2B cause complex early-onset dystonia. Nat. Genet. 49, 223–237 (2017).
Beetz, C. et al. LRRK2 loss-of-function variants in patients with rare diseases: no evidence for a phenotypic impact. Mov. Disord. 36, 1029–1031 (2021).
Article
CAS
PubMed
PubMed Central
Google Scholar
Blauwendraat, C. et al. Frequency of loss of function variants in LRRK2 in Parkinson disease. JAMA Neurol. 75, 1416–1422 (2018).
Article
PubMed
PubMed Central
Google Scholar
Salles, P. A., Mata, I. F., Brunger, T., Lal, D. & Fernandez, H. H. ATP1A3-related disorders: an ever-expanding clinical spectrum. Front. Neurol. 12, 637890 (2021).
Article
PubMed
PubMed Central
Google Scholar
Havrilla, J. M., Pedersen, B. S., Layer, R. M. & Quinlan, A. R. A map of constrained coding regions in the human genome. Nat. Genet. 51, 88–95 (2019).
Wiel, L. et al. MetaDome: pathogenicity analysis of genetic variants through aggregation of homologous human protein domains. Hum. Mutat. 40, 1030–1038 (2019).
CAS
PubMed
PubMed Central
Google Scholar
Wiel, L. et al. De novo mutation hotspots in homologous protein domains identify function-altering mutations in neurodevelopmental disorders. Am. J. Hum. Genet. 110, 92–104 (2023).
Singh, S. et al. De novo variants of NR4A2 are associated with neurodevelopmental disorder and epilepsy. Genet. Med. 22, 1413–1417 (2020).
Article
CAS
PubMed
PubMed Central
Google Scholar
Winter, B. et al. NR4A2 and dystonia with dopa responsiveness. Mov. Disord. 36, 2203–2204 (2021).
Jesus, S. et al. NR4A2 mutations can cause intellectual disability and language impairment with persistent dystonia-parkinsonism. Neurol. Genet. 7, e543 (2021).
Article
PubMed
PubMed Central
Google Scholar
Geisheker, M. R. et al. Hotspots of missense mutation identify neurodevelopmental disorder genes and functional domains. Nat. Neurosci. 20, 1043–1051 (2017).
Article
CAS
PubMed
PubMed Central
Google Scholar
Kircher, M. et al. A general framework for estimating the relative pathogenicity of human genetic variants. Nat. Genet. 46, 310–315 (2014).
Article
CAS
PubMed
PubMed Central
Google Scholar
Wilcox, E. H. et al. Evaluating the impact of in silico predictors on clinical variant classification. Genet. Med. 24, 924–930 (2022).
Martin, A. R. et al. PanelApp crowdsources expert knowledge to establish consensus diagnostic gene panels. Nat. Genet. 51, 1560–1565 (2019).
Richards, S. et al. Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. Genet. Med. 17, 405–424 (2015).
Article
PubMed
PubMed Central
Google Scholar
Li, Q. & Wang, K. InterVar: clinical interpretation of genetic variants by the 2015 ACMG-AMP guidelines. Am. J. Hum. Genet. 100, 267–280 (2017).
Article
CAS
PubMed
PubMed Central
Google Scholar
Vears, D. F., Senecal, K. & Borry, P. Reporting practices for variants of uncertain significance from next generation sequencing technologies. Eur. J. Med. Genet. 60, 553–558 (2017).
Clift, K. et al. Patients’ views on variants of uncertain significance across indications. J. Community Genet. 11, 139–145 (2020).
Liu, P. et al. Reanalysis of clinical exome sequencing data. N. Engl. J. Med. 380, 2478–2480 (2019).
Article
PubMed
PubMed Central
Google Scholar
Mensah, N. E. et al. Automated reanalysis application to assist in detecting novel gene-disease associations after genome sequencing. Genet. Med. 24, 811–820 (2022).
Fattahi, Z. et al. Iranome: a catalog of genomic variations in the Iranian population. Hum. Mutat. 40, 1968–1984 (2019).
Cordts, I. et al. Adult-onset neurodegeneration in nucleotide excision repair disorders (NERD(ND)): time to move beyond the skin. Mov. Disord. 37, 1707–1718 (2022).
Skorvanek, M. et al. Adult-onset neurodegeneration in nucleotide excision repair disorders: more common than expected. Mov. Disord. 37, 2323–2324 (2022).
Rehm, H. L. Evolving health care through personal genomics. Nat. Rev. Genet. 18, 259–267 (2017).
Article
CAS
PubMed
PubMed Central
Google Scholar
Gilissen, C., Hoischen, A., Brunner, H. G. & Veltman, J. A. Unlocking Mendelian disease using exome sequencing. Genome Biol. 12, 228 (2011).
Article
CAS
PubMed
PubMed Central
Google Scholar
Bamshad, M. J., Nickerson, D. A. & Chong, J. X. Mendelian gene discovery: fast and furious with no end in sight. Am. J. Hum. Genet. 105, 448–455 (2019).
Article
CAS
PubMed
PubMed Central
Google Scholar
McInnes, G. et al. Opportunities and challenges for the computational interpretation of rare variation in clinically important genes. Am. J. Hum. Genet. 108, 535–548 (2021).
Article
CAS
PubMed
PubMed Central
Google Scholar
Stenson, P. D. et al. The Human Gene Mutation Database: towards a comprehensive repository of inherited mutation data for medical research, genetic diagnosis and next-generation sequencing studies. Hum. Genet. 136, 665–677 (2017).
Article
CAS
PubMed
PubMed Central
Google Scholar
Firth, H. V. et al. DECIPHER: database of chromosomal imbalance and phenotype in humans using Ensembl resources. Am. J. Hum. Genet. 84, 524–533 (2009).
Article
CAS
PubMed
PubMed Central
Google Scholar
Brandon, M. C. et al. MITOMAP: a human mitochondrial genome database — 2004 update. Nucleic Acids Res. 33, D611–D613 (2005).
Lill, C. M. et al. Launching the movement disorders society genetic mutation database (MDSGene). Mov. Disord. 31, 607–609 (2016).
Hindorff, L. A. et al. Prioritizing diversity in human genomics research. Nat. Rev. Genet. 19, 175–185 (2018).
Philippakis, A. A. et al. The matchmaker exchange: a platform for rare disease gene discovery. Hum. Mutat. 36, 915–921 (2015).
Article
PubMed
PubMed Central
Google Scholar
Sobreira, N., Schiettecatte, F., Valle, D. & Hamosh, A. GeneMatcher: a matching tool for connecting investigators with an interest in the same gene. Hum. Mutat. 36, 928–930 (2015).
Article
PubMed
PubMed Central
Google Scholar
Gannamani, R., van der Veen, S., van Egmond, M., de Koning, T. J. & Tijssen, M. A. J. Challenges in clinicogenetic correlations: one phenotype — many genes. Mov. Disord. Clin. Pract. 8, 311–321 (2021).
Article
PubMed
PubMed Central
Google Scholar
Neilson, D. E. et al. A novel variant of ATP5MC3 associated with both dystonia and spastic paraplegia. Mov. Disord. 37, 375–383 (2022).
Turner, T. N. et al. denovo-db: a compendium of human de novo variants. Nucleic Acids Res. 45, D804–D811 (2017).
Lappalainen, I. et al. The European genome-phenome archive of human data consented for biomedical research. Nat. Genet. 47, 692–695 (2015).
Article
CAS
PubMed
PubMed Central
Google Scholar
Zurek, B. et al. Solve-RD: systematic pan-European data sharing and collaborative analysis to solve rare diseases. Eur. J. Hum. Genet. 29, 1325–1331 (2021).
Article
PubMed
PubMed Central
Google Scholar
Zech, M. et al. Variants in mitochondrial ATP synthase cause variable neurologic phenotypes. Ann. Neurol. 91, 225–237 (2022).
Article
CAS
PubMed
PubMed Central
Google Scholar
Aref-Eshghi, E. et al. Evaluation of DNA methylation episignatures for diagnosis and phenotype correlations in 42 Mendelian neurodevelopmental disorders. Am. J. Hum. Genet. 106, 356–370 (2020).
Article
CAS
PubMed
PubMed Central
Google Scholar
Mirza-Schreiber, N. et al. Blood DNA methylation provides an accurate biomarker of KMT2B-related dystonia and predicts onset. Brain 145, 644–654 (2022).
Ciolfi, A. et al. Childhood-onset dystonia-causing KMT2B variants result in a distinctive genomic hypermethylation profile. Clin. Epigenetics 13, 157 (2021).
Article
CAS
PubMed
PubMed Central
Google Scholar
Kremer, L. S. et al. Genetic diagnosis of Mendelian disorders via RNA sequencing. Nat. Commun. 8, 15824 (2017).
Article
CAS
PubMed
PubMed Central
ADS
Google Scholar
Lee, H. et al. Diagnostic utility of transcriptome sequencing for rare Mendelian diseases. Genet. Med. 22, 490–499 (2020).
Yepez, V. A. et al. Clinical implementation of RNA sequencing for Mendelian disease diagnostics. Genome Med. 14, 38 (2022).
Article
CAS
PubMed
PubMed Central
Google Scholar
Fresard, L. et al. Identification of rare-disease genes using blood transcriptome sequencing and large control cohorts. Nat. Med. 25, 911–919 (2019).
Article
CAS
PubMed
PubMed Central
Google Scholar
Amarasinghe, S. L. et al. Opportunities and challenges in long-read sequencing data analysis. Genome Biol. 21, 30 (2020).
Article
PubMed
PubMed Central
Google Scholar
Miyatake, S. et al. Rapid and comprehensive diagnostic method for repeat expansion diseases using nanopore sequencing. NPJ Genom. Med. 7, 62 (2022).
Article
CAS
PubMed
PubMed Central
Google Scholar
Wagner, N. et al. Aberrant splicing prediction across human tissues. Nat. Genet. 55, 861–870 (2023).
Magri, S. et al. Digenic inheritance of STUB1 variants and TBP polyglutamine expansions explains the incomplete penetrance of SCA17 and SCA48. Genet. Med. 24, 29–40 (2022).
Parlar, S. C., Grenn, F. P., Kim, J. J., Baluwendraat, C. & Gan-Or, Z. Classification of GBA1 variants in Parkinson’s disease: the GBA1-PD browser. Mov. Disord. 38, 489–495 (2023).
Kalogeropulou, A. F. et al. Impact of 100 LRRK2 variants linked to Parkinson’s disease on kinase activity and microtubule binding. Biochem. J. 479, 1759–1783 (2022).
Splinter, K. et al. Effect of genetic diagnosis on patients with previously undiagnosed disease. N. Engl. J. Med. 379, 2131–2139 (2018).
Article
CAS
PubMed
PubMed Central
Google Scholar
Buphamalai, P., Kokotovic, T., Nagy, V. & Menche, J. Network analysis reveals rare disease signatures across multiple levels of biological organization. Nat. Commun. 12, 6306 (2021).
Article
CAS
PubMed
PubMed Central
ADS
Google Scholar
Bakhit, Y. et al. Intrafamilial and interfamilial heterogeneity of PINK1-associated Parkinson’s disease in Sudan. Parkinsonism Relat. Disord. 111, 105401 (2023).
Beijer, D. et al. Standards of NGS data sharing and analysis in ataxias: recommendations by the NGS working group of the Ataxia Global Initiative. Cerebellum https://doi.org/10.1007/s12311-023-01537-1 (2023).
Meneret, A. et al. Efficacy of caffeine in ADCY5-related dyskinesia: a retrospective study. Mov. Disord. 37, 1294–1298 (2022).
Gilbert, D. L., Leslie, E. J., Keddache, M. & Leslie, N. D. A novel hereditary spastic paraplegia with dystonia linked to chromosome 2q24-2q31. Mov. Disord. 24, 364–370 (2009).
M.Z. and J.W. receive research support from the German Research Foundation (DFG 458949627; ZE 1213/2-1; WI 1820/14-1). M.Z. acknowledges grant support from the European Joint Programme on Rare Diseases (European Joint Programme on Rare Diseases Joint Transnational Call 2022) and the German Federal Ministry of Education and Research (BMBF, Bonn, Germany), awarded to the project PreDYT (PREdictive biomarkers in DYsTonia, 01GM2302), and from the Federal Ministry of Education and Research (BMBF) and the Free State of Bavaria under the Excellence Strategy of the Federal Government and the Länder as well as by the Technical University of Munich — Institute for Advanced Study. M.Z. is a member of the Medical and Scientific Advisory Council of the Dystonia Medical Research Foundation and a member of the Governance Council of the International Cerebral Palsy Genomics Consortium. MZ’s research is supported by a “Schlüsselprojekt” grant from the Else Kröner-Fresenius-Stiftung (2022_EKSE.185).
Institute of Human Genetics, School of Medicine, Technical University of Munich, Munich, Germany
Institute for Advanced Study, Technical University of Munich, Garching, Germany
You can also search for this author in
PubMed Google Scholar
You can also search for this author in
PubMed Google Scholar
Nature Reviews Neurology thanks H. Houlden and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
European Joint Programme on Rare Diseases: https://www.ejprarediseases.org/
ExpansionHunter Denovo: https://github.com/Illumina/ExpansionHunterDenovo
Genome Aggregation Database (gnomAD): https://gnomad.broadinstitute.org/
Movement Disorder Society Genetic mutation database: https://www.mdsgene.org/
Copy number variant detection tools that determine the presence of a deletion or duplication by comparing the read coverage in the affected genomic interval with the rest of the sequenced exome or genome. Higher sequencing depth is necessary for reliable analysis.
A mechanism whereby the expression of a disease phenotype is determined by the presence of genetic pathologies in two different loci, often associated with epistatic interactions between these loci (encoded proteins might act in the same pathway).
Algorithms that can be used to produce new content, including synthetic data.
Paired-end mapping approaches can define copy number variants on the basis of alterations in the insert size of paired-end reads, whereas split-read approaches are helpful for predicting copy number changes by assessing unaligned discordant reads that were split and mapped separately from the reference genome.
A measure of the accuracy of alignment of sequencing reads to the correct location in the genome. Can be confounded by DNA characteristics such as repetitive regions.
A high-throughput approach used in next-generation sequencing studies, which allows analysis of millions of short reads (usually containing 100–150 bp) in an automated miniaturized fashion. This approach differs from traditional capillary Sanger analysis in terms of time-effective mass production of sequencing outputs.
Clinical diseases that are caused by high-effect rare variants in single genes, in contrast to polygenic or multifactorial diseases, which are associated with many common variants with low effect sizes at various genomic loci and are influenced by other non-genetic factors.
A measure of genetic intolerance to amino acid substitutions, which can aid prioritization of gene candidates involved in missense mutation-associated diseases.
Genomic sequences that can move between chromosomes, for example, through cut-and-paste mechanisms in DNA transposons. These elements have a role in genome evolution, and their integration into disease-associated genes can disrupt the open reading frame and cause clinical phenotypes.
A measure of the proportion of carriers of a specific monogenic disease predisposition who present with clinical features of the associated condition.
A phenomenon whereby variants in a disease-related gene are associated with multiple (similar or divergent) phenotypic abnormalities.
Individuals with a disease phenotype who have no relatives affected by the same condition.
A protocol that dynamically incorporates specific DNA segments into the sequencing analysis; for example, complementary interrogation of all base pairs of the mitochondrial genome in addition to the nuclear coding sequences in the form of a mitochondrial spike-in panel in diagnostic exome studies.
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.
Zech, M., Winkelmann, J. Next-generation sequencing and bioinformatics in rare movement disorders.
Nat Rev Neurol 20, 114–126 (2024). https://doi.org/10.1038/s41582-023-00909-9
Anyone you share the following link with will be able to read this content:
Nature Reviews Neurology (Nat Rev Neurol)
ISSN 1759-4766 (online)
ISSN 1759-4758 (print)
Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.