Skip to main content
Log in

Heterogeneity of cognitive impairments in myotonic dystrophy type 1 explained by three distinct cognitive profiles

  • Original Communication
  • Published:
Journal of Neurology Aims and scope Submit manuscript

Abstract

Background

Severity and nature of cognitive impairments in Myotonic dystrophy type 1 (DM1) are heterogeneous among studies. We hypothesized that this heterogeneity is explained by different cognitive profiles in DM1, with different clinical, biological and behavioral features.

Methods

Adult patients with genetically proven DM1 underwent a clinical, neuropsychological and behavioral assessment. We conducted a k-means clustering analysis on 9 cognitive tests representative of different domains (verbal/non-verbal episodic memory, visuo-constructive abilities, visual gnosis, executive functions, information processing speed).

Results

We included 124 DM1 patients. Mean age was 45.1 ± 13.5 years [19.8–73.2], mean age of onset was 30.4 ± 15.7 years [5–72], and mean CTG triplets’ expansion size was 489.7 ± 351.8 [50–1600]. We found 3 cognitive clusters, including, respectively, 84, 29 and 11 patients. The first cluster included patients with more preserved cognitive functions; the second included patients with worse cognitive performances which predominate on executive functions; and the third even more pronounced and diffuse cognitive deficits. Younger patients, with a more recent DM1 clinical onset, higher educational level were more frequently classified in the cluster with more preserved cognitive functions. There were no significant differences between clusters regarding CTG triplets’ expansion, neither age at DM1 onset, nor most of behavioral measures.

Conclusions

We found different cognitive profiles in our DM1 population, which seem influenced by age and DM1 duration. Our findings may explain the heterogeneity of studies about cognition in DM1, and suggest a potential neurodegenerative mechanism in DM1 adults.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2

Similar content being viewed by others

Data availability

Data of this study can be shared upon request to the corresponding author.

Abbreviations

ANOVA:

Analysis of variance

BECS-GRECO:

Groupe de réflexion sur les évaluations cognitives—neuropsychological semantic battery

CSCT:

Computerized Speed Cognitive Test

DM1:

Myotonic dystrophy type 1

HADS:

Hospital Anxiety and Depression Scale

HVLT:

Hopkins Verbal Learning Test

IQ:

Intellectual quotient

LARS:

Lille Apathy Rating Scale

MASC:

Movie for the Assessment of Social Cognition

MIRS:

Muscular Impairment Rating Scale

N-LST:

Number–letter sequence task

QFS:

Questionnaire de Fonctionnement Social

TMT:

Trail Making Test

ToM:

Theory of mind

VOSP:

Visual Object and Space Perception

WAIS:

Wechsler Adult Intelligence Scale

WHOQOL-BREF:

World Health Organization Quality of Life Brief Version

References

  1. Theadom A, Rodrigues M, Roxburgh R, Balalla S, Higgins C, Bhattacharjee R, Jones K, Krishnamurthi R, Feigin V (2014) Prevalence of muscular dystrophies: a systematic literature review. Neuroepidemiology 43:259–268. https://doi.org/10.1159/000369343

    Article  PubMed  Google Scholar 

  2. Harper P (2009) Myotonic dystrophy. OUP Oxford, Oxford

    Book  Google Scholar 

  3. Okkersen K, Buskes M, Groenewoud J, Kessels RPC, Knoop H, van Engelen B, Raaphorst J (2017) The cognitive profile of myotonic dystrophy type 1: a systematic review and meta-analysis. Cortex 95:143–155. https://doi.org/10.1016/j.cortex.2017.08.008

    Article  PubMed  Google Scholar 

  4. Van Spaendonck KP, Ter Bruggen JP, Weyn Banningh EW, Maassen BA, Van de Biezenbos JB, Gabreëls FJ (1995) Cognitive function in early adult and adult onset myotonic dystrophy. Acta Neurol Scand 91:456–461. https://doi.org/10.1111/j.1600-0404.1995.tb00446.x

    Article  PubMed  Google Scholar 

  5. Perini GI, Menegazzo E, Ermani M, Zara M, Gemma A, Ferruzza E, Gennarelli M, Angelini C (1999) Cognitive impairment and (CTG)n expansion in myotonic dystrophy patients. Biol Psychiatry 46:425–431. https://doi.org/10.1016/s0006-3223(99)00016-5

    Article  CAS  PubMed  Google Scholar 

  6. Gallais B, Gagnon C, Mathieu J, Richer L (2017) Cognitive decline over time in adults with myotonic dystrophy type 1: a 9-year longitudinal study. Neuromuscul Disord 27:61–72. https://doi.org/10.1016/j.nmd.2016.10.003

    Article  PubMed  Google Scholar 

  7. Peric S, Rakocevic Stojanovic V, Mandic Stojmenovic G, Ilic V, Kovacevic M, Parojcic A, Pesovic J, Mijajlovic M, Savic-Pavicevic D, Meola G (2017) Clusters of cognitive impairment among different phenotypes of myotonic dystrophy type 1 and type 2. Neurol Sci 38:415–423. https://doi.org/10.1007/s10072-016-2778-4

    Article  PubMed  Google Scholar 

  8. Fujino H, Suwazono S, Ueda Y, Kobayashi M, Nakayama T, Imura O, Matsumura T, Takahashi MP (2023) Longitudinal changes in neuropsychological functioning in Japanese patients with myotonic dystrophy type 1: a five year follow-up study. J Neuromuscul Dis 10:1083–1092. https://doi.org/10.3233/JND-230083

    Article  PubMed  PubMed Central  Google Scholar 

  9. Modoni A, Silvestri G, Vita MG, Quaranta D, Tonali PA, Marra C (2008) Cognitive impairment in myotonic dystrophy type 1 (DM1): a longitudinal follow-up study. J Neurol 255:1737–1742. https://doi.org/10.1007/s00415-008-0017-5

    Article  CAS  PubMed  Google Scholar 

  10. Rubinsztein JS, Rubinsztein DC, McKenna PJ, Goodburn S, Holland AJ (1997) Mild myotonic dystrophy is associated with memory impairment in the context of normal general intelligence. J Med Genet 34:229–233. https://doi.org/10.1136/jmg.34.3.229

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Mathieu J, Boivin H, Meunier D, Gaudreault M, Bégin P (2001) Assessment of a disease-specific muscular impairment rating scale in myotonic dystrophy. Neurology 56:336–340. https://doi.org/10.1212/wnl.56.3.336

    Article  CAS  PubMed  Google Scholar 

  12. Wechsler D (2000) WAIS-III: echelle d’intelligence de Wechsler pour adultes, vol 3rd. Editions du Centre de Psychologie Appliquée, Paris

    Google Scholar 

  13. Rieu D, Bachoud-Lévi A-C, Laurent A, Jurion E, Dalla Barba G (2006) French adaptation of the Hopkins verbal learning test. Rev Neurol 162:721–728. https://doi.org/10.1016/s0035-3787(06)75069-x

    Article  CAS  PubMed  Google Scholar 

  14. Dujardin K, Sockeel P, Cabaret M, De Sèze J, Vermersch P (2004) BCcogSEP: a French test battery evaluating cognitive functions in multiple sclerosis. Rev Neurol 160:51–62. https://doi.org/10.1016/s0035-3787(04)70847-4

    Article  CAS  PubMed  Google Scholar 

  15. Merck C, Charnallet A, Auriacombe S, Belliard S, Hahn-Barma V, Kremin H, Lemesle B, Mahieux F, Moreaud O, Palisson DP, Roussel M, Sellal F, Siegwart H (2011) The GRECO neuropsychological semantic battery (BECS GRECO): validation and normative data. Rev Neuropsychol 3:235–255. https://doi.org/10.1684/nrp.2011.0194

    Article  Google Scholar 

  16. Beery KE, Beery NA (2006) The beery-Buktenica developmental test of visual-motor integration, 5th, edition (BEERYTM VMI). Pearson, London

    Google Scholar 

  17. Warrington EK, James M (1991) A new test of object decision: 2D silhouettes featuring a minimal view. Cortex 27:370–383

    Article  CAS  PubMed  Google Scholar 

  18. GREFEX (2001) L’évaluation des fonctions exécutives en pratique clinique. Rev Neuropsychol 11(3):383–433

    Google Scholar 

  19. Reitan RM (1958) Validity of the trail making test as an indicator of organic brain damage. Percept Mot Skills 8:271–286

    Article  Google Scholar 

  20. Delis DC, Kaplan E, Kramer JH (2001) Delis-Kaplan Executive Function System (D-KEFS)

  21. Ruet A, Deloire MSA, Charré-Morin J, Hamel D, Brochet B (2013) A new computerised cognitive test for the detection of information processing speed impairment in multiple sclerosis. Mult Scler 19:1665–1672. https://doi.org/10.1177/1352458513480251

    Article  PubMed  Google Scholar 

  22. Dziobek I, Fleck S, Kalbe E, Rogers K, Hassenstab J, Brand M, Kessler J, Woike JK, Wolf OT, Convit A (2006) Introducing MASC: a movie for the assessment of social cognition. J Autism Dev Disord 36:623–636. https://doi.org/10.1007/s10803-006-0107-0

    Article  PubMed  Google Scholar 

  23. Allison C, Auyeung B, Baron-Cohen S (2012) Toward brief “Red Flags” for autism screening: the short autism spectrum quotient and the short quantitative checklist for autism in toddlers in 1000 cases and 3000 controls [corrected]. J Am Acad Child Adolesc Psychiatry 51:202-212.e7. https://doi.org/10.1016/j.jaac.2011.11.003

    Article  PubMed  Google Scholar 

  24. Dujardin K, Sockeel P, Carette A-S, Delliaux M, Defebvre L (2013) Assessing apathy in everyday clinical practice with the short-form Lille Apathy Rating Scale. Mov Disord 28:2014–2019. https://doi.org/10.1002/mds.25584

    Article  PubMed  Google Scholar 

  25. Zanello A, Weber Rouget B, Gex-Fabry M, Maercker A, Guimon J (2006) Validation of the QFS measuring the frequency and satisfaction in social behaviours in psychiatric adult population. Encephale 32:45–59. https://doi.org/10.1016/s0013-7006(06)76136-x

    Article  CAS  PubMed  Google Scholar 

  26. Zigmond AS, Snaith RP (1983) The hospital anxiety and depression scale. Acta Psychiatr Scand 67:361–370. https://doi.org/10.1111/j.1600-0447.1983.tb09716.x

    Article  CAS  PubMed  Google Scholar 

  27. Krupp LB, LaRocca NG, Muir-Nash J, Steinberg AD (1989) The fatigue severity scale: application to patients with multiple sclerosis and systemic lupus erythematosus. Arch Neurol 46:1121–1123. https://doi.org/10.1001/archneur.1989.00520460115022

    Article  CAS  PubMed  Google Scholar 

  28. Baumann C, Erpelding M-L, Régat S, Collin J-F, Briançon S (2010) The WHOQOL-BREF questionnaire: French adult population norms for the physical health, psychological health and social relationship dimensions. Rev Epidemiol Sante Publique 58:33–39. https://doi.org/10.1016/j.respe.2009.10.009

    Article  CAS  PubMed  Google Scholar 

  29. De Antonio M, Dogan C, Hamroun D, Mati M, Zerrouki S, Eymard B, Katsahian S, Bassez G, Network FMDC (2016) Unravelling the myotonic dystrophy type 1 clinical spectrum: a systematic registry-based study with implications for disease classification. Rev Neurol 172:572–580. https://doi.org/10.1016/j.neurol.2016.08.003

    Article  PubMed  Google Scholar 

  30. Weijs R, Okkersen K, van Engelen B, Küsters B, Lammens M, Aronica E, Raaphorst J, van Cappellen van Walsum A-M, (2021) Human brain pathology in myotonic dystrophy type 1: a systematic review. Neuropathology 41:3–20. https://doi.org/10.1111/neup.12721

    Article  PubMed  PubMed Central  Google Scholar 

  31. Caillet-Boudin M-L, Fernandez-Gomez F-J, Tran H, Dhaenens C-M, Buee L, Sergeant N (2014) Brain pathology in myotonic dystrophy: when tauopathy meets spliceopathy and RNAopathy. Front Mol Neurosci. https://doi.org/10.3389/fnmol.2013.00057

    Article  PubMed  PubMed Central  Google Scholar 

  32. Pinzan E, Weis L, Angelini C (2020) Abnormal gyrification in brain of early onset myotonic dystrophy patients (241). Neurology. https://doi.org/10.1212/WNL.94.15_supplement.2

    Article  Google Scholar 

  33. Bangen KJ, Thomas KR, Weigand AJ, Edmonds EC, Clark AL, Solders S, Delano-Wood L, Galasko DR, Bondi MW, Alzheimer’s Disease Neuroimaging Initiative, (2021) Elevated plasma neurofilament light predicts a faster rate of cognitive decline over 5 years in participants with objectively-defined subtle cognitive decline and MCI. Alzheimers Dement 17:1756–1762. https://doi.org/10.1002/alz.12324

    Article  CAS  PubMed  Google Scholar 

  34. Laberge L, Mathieu J, Auclair J, Gagnon É, Noreau L, Gagnon C (2013) Clinical, psychosocial, and central correlates of quality of life in myotonic dystrophy type 1 patients. Eur Neurol 70:308–315. https://doi.org/10.1159/000353991

    Article  CAS  PubMed  Google Scholar 

  35. Veldsman M, Werden E, Egorova N, Khlif MS, Brodtmann A (2020) Microstructural degeneration and cerebrovascular risk burden underlying executive dysfunction after stroke. Sci Rep 10:17911. https://doi.org/10.1038/s41598-020-75074-w

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Antonini G, Soscia F, Giubilei F, De Carolis A, Gragnani F, Morino S, Ruberto A, Tatarelli R (2006) Health-related quality of life in myotonic dystrophy type 1 and its relationship with cognitive and emotional functioning. J Rehabil Med 38:181–185. https://doi.org/10.1080/16501970500477967

    Article  PubMed  Google Scholar 

  37. Fujino H, Shingaki H, Suwazono S, Ueda Y, Wada C, Nakayama T, Takahashi MP, Imura O, Matsumura T (2018) Cognitive impairment and quality of life in patients with myotonic dystrophy type 1. Muscle Nerve 57:742–748. https://doi.org/10.1002/mus.26022

    Article  PubMed  Google Scholar 

  38. Peric S, Bjelica B, Bozovic I, Pesovic J, Paunic T, Banovic M, Brkusanin M, Aleksic K, Basta I, Pavicevic DS, Stojanovic VR (2019) Fatigue in myotonic dystrophy type 1: a seven-year prospective study. Acta Myol 38:239–244

    PubMed  PubMed Central  Google Scholar 

  39. Menzies V, Kelly DL, Yang GS, Starkweather A, Lyon DE (2021) A systematic review of the association between fatigue and cognition in chronic noncommunicable diseases. Chronic Illn 17:129–150. https://doi.org/10.1177/1742395319836472

    Article  PubMed  Google Scholar 

  40. Graff-Radford J, Aakre JA, Knopman DS, Schwarz CG, Flemming KD, Rabinstein AA, Gunter JL, Ward CP, Zuk SM, Spychalla AJ, Preboske GM, Petersen RC, Kantarci K, Huston J, Jack CR, Mielke MM, Vemuri P (2020) Prevalence and heterogeneity of cerebrovascular disease imaging lesions. Mayo Clin Proc 95:1195–1205. https://doi.org/10.1016/j.mayocp.2020.01.028

    Article  PubMed  Google Scholar 

  41. Gutschmidt K, Wenninger S, Montagnese F, Schoser B (2021) Dyslexia and cognitive impairment in adult patients with myotonic dystrophy type 1: a clinical prospective analysis. J Neurol 268:484–492. https://doi.org/10.1007/s00415-020-10161-6

    Article  CAS  PubMed  Google Scholar 

  42. Hermans MCE, Faber CG, De Baets MH, de Die-Smulders CEM, Merkies ISJ (2010) Rasch-built myotonic dystrophy type 1 activity and participation scale (DM1-Activ). Neuromuscul Disord 20:310–318. https://doi.org/10.1016/j.nmd.2010.03.010

    Article  PubMed  Google Scholar 

Download references

Acknowledgements

We thank the team of the neuromuscular center of the university hospital of Lille, which each day helps us to organize the patients’ follow-up. We also thank Sebastian Sorger Brock for the English proofreading.

Funding

This work was funded by the Centre Hospitalier Universitaire de Lille, F-59000, Lille, France; by the association Santélys, 59120, Loos, France; and by the Projet Fédératif Hospitalo-Universitaire-VasCog, F-59000, Lille, France.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Jean-Baptiste Davion.

Ethics declarations

Conflict of interest

The authors have no disclosures to report.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (DOCX 42 KB)

Rights and permissions

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.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Davion, JB., Tard, C., Fragoso, L. et al. Heterogeneity of cognitive impairments in myotonic dystrophy type 1 explained by three distinct cognitive profiles. J Neurol (2024). https://doi.org/10.1007/s00415-024-12404-2

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s00415-024-12404-2

Keywords

Navigation