Microstructure of the cerebellum and its afferent pathways underpins dystonia in myoclonus dystonia.
cerebellum
diffusion tensor imaging
dystonia
myoclonus
neuroimaging
Journal
European journal of neurology
ISSN: 1468-1331
Titre abrégé: Eur J Neurol
Pays: England
ID NLM: 9506311
Informations de publication
Date de publication:
10 Sep 2024
10 Sep 2024
Historique:
revised:
14
08
2024
received:
21
05
2024
accepted:
20
08
2024
medline:
10
9
2024
pubmed:
10
9
2024
entrez:
10
9
2024
Statut:
aheadofprint
Résumé
Myoclonus dystonia due to a pathogenic variant in SGCE (MYC/DYT-SGCE) is a rare condition involving a motor phenotype associating myoclonus and dystonia. Dysfunction within the networks relying on the cortex, cerebellum, and basal ganglia was presumed to underpin the clinical manifestations. However, the microarchitectural abnormalities within these structures and related pathways are unknown. Here, we investigated the microarchitectural brain abnormalities related to the motor phenotype in MYC/DYT-SGCE. We used neurite orientation dispersion and density imaging, a multicompartment tissue model of diffusion neuroimaging, to compare microarchitectural neurite organization in MYC/DYT-SGCE patients and healthy volunteers (HVs). Neurite density index (NDI), orientation dispersion index (ODI), and isotropic volume fraction (ISOVF) were derived and correlated with the severity of motor symptoms. Fractional anisotropy (FA) and mean diffusivity (MD) derived from the diffusion tensor approach were also analyzed. In addition, we studied the pathways that correlated with motor symptom severity using tractography analysis. Eighteen MYC/DYT-SGCE patients and 24 HVs were analyzed. MYC/DYT-SGCE patients showed an increase of ODI and a decrease of FA within their motor cerebellum. More severe dystonia was associated with lower ODI and NDI and higher FA within motor cerebellar cortex, as well as with lower NDI and higher ISOVF and MD within the corticopontocerebellar and spinocerebellar pathways. No association was found between myoclonus severity and diffusion parameters. In MYC/DYT-SGCE, we found microstructural reorganization of the motor cerebellum. Structural change in the cerebellar afferent pathways that relay inputs from the spinal cord and the cerebral cortex were specifically associated with the severity of dystonia.
Sections du résumé
BACKGROUND AND PURPOSE
OBJECTIVE
Myoclonus dystonia due to a pathogenic variant in SGCE (MYC/DYT-SGCE) is a rare condition involving a motor phenotype associating myoclonus and dystonia. Dysfunction within the networks relying on the cortex, cerebellum, and basal ganglia was presumed to underpin the clinical manifestations. However, the microarchitectural abnormalities within these structures and related pathways are unknown. Here, we investigated the microarchitectural brain abnormalities related to the motor phenotype in MYC/DYT-SGCE.
METHODS
METHODS
We used neurite orientation dispersion and density imaging, a multicompartment tissue model of diffusion neuroimaging, to compare microarchitectural neurite organization in MYC/DYT-SGCE patients and healthy volunteers (HVs). Neurite density index (NDI), orientation dispersion index (ODI), and isotropic volume fraction (ISOVF) were derived and correlated with the severity of motor symptoms. Fractional anisotropy (FA) and mean diffusivity (MD) derived from the diffusion tensor approach were also analyzed. In addition, we studied the pathways that correlated with motor symptom severity using tractography analysis.
RESULTS
RESULTS
Eighteen MYC/DYT-SGCE patients and 24 HVs were analyzed. MYC/DYT-SGCE patients showed an increase of ODI and a decrease of FA within their motor cerebellum. More severe dystonia was associated with lower ODI and NDI and higher FA within motor cerebellar cortex, as well as with lower NDI and higher ISOVF and MD within the corticopontocerebellar and spinocerebellar pathways. No association was found between myoclonus severity and diffusion parameters.
CONCLUSIONS
CONCLUSIONS
In MYC/DYT-SGCE, we found microstructural reorganization of the motor cerebellum. Structural change in the cerebellar afferent pathways that relay inputs from the spinal cord and the cerebral cortex were specifically associated with the severity of dystonia.
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
e16460Subventions
Organisme : Amadys
Organisme : Dystonia Medical Research Foundation
Organisme : European Union's Horizon 2020 research and innovation programme under the European Joint Programme on Rare Diseases (EJP RD) COFUND-EJP No. 825575-EurDyscover
Organisme : Fondation pour la Recherche Médicale
Informations de copyright
© 2024 The Author(s). European Journal of Neurology published by John Wiley & Sons Ltd on behalf of European Academy of Neurology.
Références
Roze E, Lang AE, Vidailhet M. Myoclonus‐dystonia: classification, phenomenology, pathogenesis, and treatment. Curr Opin Neurol. 2018;31(4):484‐490.
Washburn S, Fremont R, Moreno‐Escobar MC, Angueyra C, Khodakhah K. Acute cerebellar knockdown of Sgce reproduces salient features of myoclonus‐dystonia (DYT11) in mice. Elife. 2019;8:e52101.
Carbon M, Raymond D, Ozelius L, et al. Metabolic changes in DYT11 myoclonus‐dystonia. Neurology. 2013;80(4):385‐391.
Weissbach A, Werner E, Bally JF, et al. Alcohol improves cerebellar learning deficit in myoclonus–dystonia: a clinical and electrophysiological investigation. Ann Neurol. 2017;82(4):543‐553.
Beukers RJ, van der Meer JN, van der Salm SM, Foncke EM, Veltman DJ, Tijssen MAJ. Severity of dystonia is correlated with putaminal gray matter changes in myoclonus‐dystonia. Eur J Neurol. 2011;18(6):906‐912.
Welter ML, Grabli D, Karachi C, et al. Pallidal activity in myoclonus dystonia correlates with motor signs. Mov Disord. 2015;30(7):992‐996.
Beukers RJ, Foncke EMJ, van der Meer JN, et al. Disorganized sensorimotor integration in mutation‐positive myoclonus‐dystonia: a functional magnetic resonance imaging study. Arch Neurol. 2010;67(4):469‐474.
Popa T, Milani P, Richard A, et al. The neurophysiological features of myoclonus‐dystonia and differentiation from other dystonias. JAMA Neurol. 2014;71(5):612‐619.
Sperandeo A, Tamburini C, Noakes Z, et al. Cortical neuronal hyperexcitability and synaptic changes in SGCE mutation‐positive myoclonus dystonia. Brain. 2022;146:1523‐1541.
Broad RJ, Gabel MC, Dowell NG, et al. Neurite orientation and dispersion density imaging (NODDI) detects cortical and corticospinal tract degeneration in ALS. J Neurol Neurosurg Psychiatry. 2019;90(4):404‐411.
van der Meer JN, Beukers RJ, van der Salm SMA, Caan MWA, Tijssen MAJ, Nederveen AJ. White matter abnormalities in gene‐positive myoclonus‐dystonia. Mov Disord. 2012;27(13):1666‐1672.
Coll G, De Schlichting E, Sakka L, Garcier JM, Peyre H, Lemaire JJ. Assessment of maturational changes in White matter anisotropy and volume in children: a DTI study. Am J Neuroradiol. 2020;41:1726‐1732.
Ciccarelli O, Werring DJ, Wheeler–Kingshott CAM, et al. Investigation of MS normal‐appearing brain using diffusion tensor MRI with clinical correlations. Neurology. 2001;56(7):926‐933.
Zhang H, Schneider T, Wheeler‐Kingshott CA, Alexander DC. NODDI: practical in vivo neurite orientation dispersion and density imaging of the human brain. Neuroimage. 2012;61(4):1000‐1016.
Grussu F, Schneider T, Tur C, et al. Neurite dispersion: a new marker of multiple sclerosis spinal cord pathology? Ann Clin Transl Neurol. 2017;4(9):663‐679.
Kamiya K, Hori M, Aoki S. NODDI in clinical research. J Neurosci Methods. 2020;346:108908.
Burke RE, Fahn S, Marsden CD, Bressman SB, Moskowitz C, Friedman J. Validity and reliability of a rating scale for the primary torsion dystonias. Neurology. 1985;35(1):73‐77.
Frucht SJ, Leurgans SE, Hallett M, Fahn S. The unified myoclonus rating scale. Adv Neurol. 2002;89:361‐376.
Bastiani M, Cottaar M, Fitzgibbon SP, et al. Automated quality control for within and between studies diffusion MRI data using a non‐parametric framework for movement and distortion correction. Neuroimage. 2019;184:801‐812.
Jbabdi S, Sotiropoulos SN, Savio AM, Graña M, Behrens TEJ. Model‐based analysis of multishell diffusion MR data for tractography: how to get over fitting problems. Magn Reson Med. 2012;68(6):1846‐1855.
Behrens TEJ, Berg HJ, Jbabdi S, Rushworth MFS, Woolrich MW. Probabilistic diffusion tractography with multiple fibre orientations: what can we gain? Neuroimage. 2007;34(1):144‐155.
Martínez‐Molina N, Mas‐Herrero E, Rodríguez‐Fornells A, Zatorre RJ, Marco‐Pallarés J. White matter microstructure reflects individual differences in music reward sensitivity. J Neurosci. 2019;39(25):5018‐5027.
Schilling KG, Tax CMW, Rheault F, et al. Prevalence of white matter pathways coming into a single white matter voxel orientation: the bottleneck issue in tractography. Hum Brain Mapp. 2022;43(4):1196‐1213.
Guell X, Schmahmann J. Cerebellar functional anatomy: a didactic summary based on human fMRI evidence. Cerebellum. 2020;19(1):1‐5.
Spanò B, Giulietti G, Pisani V, et al. Disruption of neurite morphology parallels MS progression. Neurol Neuroimmunol Neuroinflamm. 2018;5(6):e502.
Haykal S, Invernizzi A, Carvalho J, Jansonius NM, Cornelissen FW. Microstructural visual pathway White matter alterations in primary open‐angle glaucoma: a neurite orientation dispersion and density imaging study. Am J Neuroradiol. 2022;43:756‐763.
Huisman TAGM. Diffusion‐weighted and diffusion tensor imaging of the brain, made easy. Cancer Imaging. 2010;10(1A):S163‐S171.
Venkatesh A, Stark SM, Stark CEL, Bennett IJ. Age‐ and memory‐ related differences in hippocampal gray matter integrity are better captured by NODDI compared to single‐tensor diffusion imaging. Neurobiol Aging. 2020;96:12‐21.
Ball G, Srinivasan L, Aljabar P, et al. Development of cortical microstructure in the preterm human brain. Proc Natl Acad Sci USA. 2013;110(23):9541‐9546.
Batalle D, O'Muircheartaigh J, Makropoulos A, et al. Different patterns of cortical maturation before and after 38 weeks gestational age demonstrated by diffusion MRI in vivo. Neuroimage. 2019;185:764‐775.
Penzes P, Cahill ME, Jones KA, VanLeeuwen JE, Woolfrey KM. Dendritic spine pathology in neuropsychiatric disorders. Nat Neurosci. 2011;14(3):285‐293.
Ritz K, van Schaik BD, Jakobs ME, et al. SGCE isoform characterization and expression in human brain: implications for myoclonus‐dystonia pathogenesis? Eur J Hum Genet. 2011;19(4):438‐444.
Sadnicka A, Hoffland BS, Bhatia KP, van de Warrenburg BP, Edwards MJ. The cerebellum in dystonia – help or hindrance? Clin Neurophysiol. 2012;123(1):65‐70.
Nishiyama A, Endo T, Takeda S, Imamura M. Identification and characterization of ε‐sarcoglycans in the central nervous system. Mol Brain Res. 2004;125(1–2):1‐12.
Waite A, Tinsley CL, Locke M, Blake DJ. The neurobiology of the dystrophin‐associated glycoprotein complex. Ann Med. 2009;41(5):344‐359.
Mitoma H, Buffo A, Gelfo F, et al. Consensus paper. Cerebellar reserve: from cerebellar physiology to cerebellar disorders. Cerebellum. 2020;19(1):131‐153.
Wojcinski A, Lawton AK, Bayin NS, Lao Z, Stephen DN, Joyner AL. Cerebellar granule cell replenishment postinjury by adaptive reprogramming of nestin+ progenitors. Nat Neurosci. 2017;20(10):1361‐1370.
Frucht SJ, Riboldi GM. Alcohol‐responsive hyperkinetic movement disorders—a mechanistic hypothesis. Tremor Hyperkinetic Mov. 2020;10(1):47.
Prell T, Peschel T, Köhler B, et al. Structural brain abnormalities in cervical dystonia. BMC Neurosci. 2013;14(1):123.
Tomić A, Agosta F, Sarasso E, et al. Brain structural changes in focal dystonia—what about task specificity? A multimodal MRI study. Mov Disord. 2021;36(1):196‐205.
Papapetropoulos S, Argyriou AA, Polychronopoulos P, Spyridonidis T, Gourzis P, Chroni E. Frontotemporal and striatal SPECT abnormalities in myoclonus‐dystonia: phenotypic and pathogenetic considerations. Neurodegener Dis. 2008;5(6):355‐358.
Tarrano C, Wattiez N, Delorme C, et al. Visual sensory processing is altered in myoclonus dystonia. Mov Disord. 2020;35(1):151‐160.
Xiao J, Vemula SR, Xue Y, et al. Role of major and brain‐specific Sgce isoforms in the pathogenesis of myoclonus‐dystonia syndrome. Neurobiol Dis. 2017;98:52‐65.
Balint B, Mencacci NE, Valente EM, et al. Dystonia. Nat Rev Dis Primer. 2018;4(1):25.
Pocratsky AM, Nascimento F, Özyurt MG, et al. Pathophysiology of Dyt1‐ Tor1a dystonia in mice is mediated by spinal neural circuit dysfunction. Sci Transl Med. 2023;15(694):eadg3904.
Ciccarelli O, Werring DJ, Barker GJ, et al. A study of the mechanisms of normal‐appearing white matter damage in multiple sclerosis using diffusion tensor imaging. J Neurol. 2003;250(3):287‐292.
Seyedmirzaei H, Nabizadeh F, Aarabi MH, Pini L. Neurite orientation dispersion and density imaging in multiple sclerosis: a systematic review. J Magn Reson Imaging. 2023;58(4):1011‐1029.
Nemanich ST, Mueller BA, Gillick BT. Neurite orientation dispersion and density imaging quantifies corticospinal tract microstructural organization in children with unilateral cerebral palsy. Hum Brain Mapp. 2019;40(17):4888‐4900.
Draganski B, Gaser C, Busch V, Schuierer G, Bogdahn U, May A. Changes in grey matter induced by training. Nature. 2004;427(6972):311‐312.
Kaji R, Bhatia K, Graybiel AM. Pathogenesis of dystonia: is it of cerebellar or basal ganglia origin? J Neurol Neurosurg Psychiatry. 2018;89(5):488‐492.