Dopaminergic imaging and clinical predictors for phenoconversion of REM sleep behaviour disorder

Author:

Arnaldi Dario12,Chincarini Andrea3,Hu Michele T4,Sonka Karel5ORCID,Boeve Bradley6,Miyamoto Tomoyuki7,Puligheddu Monica8,De Cock Valérie Cochen9,Terzaghi Michele1011,Plazzi Giuseppe1213,Tachibana Naoko14,Morbelli Silvia215,Rolinski Michal416,Dusek Petr5,Lowe Val17,Miyamoto Masayuki18,Figorilli Michela8,Verbizier Delphine de19,Bossert Irene20,Antelmi Elena1221,Meli Riccardo12,Barber Thomas R4ORCID,Trnka Jiří22,Miyagawa Toji6,Serra Alessandra23,Pizza Fabio1213,Bauckneht Matteo215ORCID,Bradley Kevin M24,Zogala David22ORCID,McGowan Daniel R25,Jordan Lennon17,Manni Raffaele10,Nobili Flavio12

Affiliation:

1. Clinical Neurology, Department of Neuroscience (DINOGMI), University of Genoa, Italy

2. IRCCS Ospedale Policlinico San Martino, Genoa, Italy

3. National Institute of Nuclear Physics (INFN), Genoa section, Genoa, Italy

4. Oxford Parkinson’s Disease Centre, Nuffield Department of Clinical Neurosciences, University of Oxford, John Radcliffe Hospital, Oxford, UK

5. Department of Neurology and Centre of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic

6. Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA

7. Department of Neurology, Dokkyo Medical University Saitama Medical Centre, Saitama, Japan

8. Sleep Disorder Centre, Department of Medical Sciences and Public Health, University of Cagliari, Italy

9. Department of Sleep and Neurology, Beau Soleil Clinic, and EuroMov Digital Health in Motion, University of Montpellier, Montpellier, France

10. Unit of Sleep Medicine and Epilepsy, IRCCS Mondino Foundation, Pavia, Italy

11. Department of Brain and Behavioural Sciences, University of Pavia, Pavia, Italy

12. Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, Italy

13. IRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy

14. Division of Sleep Medicine, Kansai Electric Power Medical Research Institute, Osaka, Japan

15. Nuclear Medicine, Department of Health Sciences (DISSAL), University of Genoa, Italy

16. Institute of Clinical Neurosciences, University of Bristol, Bristol, UK

17. Department of Nuclear Medicine, Mayo Clinic, Rochester, Minnesota, USA

18. Centre of Sleep Medicine, Dokkyo Medical University Hospital, Tochigi, Japan

19. Nuclear Medicine Unit, University hospital of Montpellier, France

20. Nuclear Medicine Unit, ICS Maugeri SpA SB IRCCS, Pavia, Italy

21. Neurology Unit, Movement Disorders Division, Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy

22. Institute of Nuclear Medicine, First Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic

23. Nuclear Medicine Unit, Department of Medical Science and Public Health, University of Cagliari, Cagliari, Italy

24. PETIC, University Hospital of Wales, Cardiff, UK

25. Radiation Physics and Protection Department, Churchill Hospital, Oxford, UK

Abstract

Abstract This is an international multicentre study aimed at evaluating the combined value of dopaminergic neuroimaging and clinical features in predicting future phenoconversion of idiopathic REM sleep behaviour (iRBD) subjects to overt synucleinopathy. Nine centres sent 123I-FP-CIT-SPECT data of 344 iRBD patients and 256 controls for centralized analysis. 123I-FP-CIT-SPECT images were semiquantified using DaTQUANTTM, obtaining putamen and caudate specific to non-displaceable binding ratios (SBRs). The following clinical variables were also analysed: (i) Movement Disorder Society-sponsored revision of the Unified Parkinson’s Disease Rating Scale, motor section score; (ii) Mini-Mental State Examination score; (iii) constipation; and (iv) hyposmia. Kaplan-Meier survival analysis was performed to estimate conversion risk. Hazard ratios for each variable were calculated with Cox regression. A generalized logistic regression model was applied to identify the best combination of risk factors. Bayesian classifier was used to identify the baseline features predicting phenoconversion to parkinsonism or dementia. After quality check of the data, 263 iRBD patients (67.6 ± 7.3 years, 229 males) and 243 control subjects (67.2 ± 10.1 years, 110 males) were analysed. Fifty-two (20%) patients developed a synucleinopathy after average follow-up of 2 years. The best combination of risk factors was putamen dopaminergic dysfunction of the most affected hemisphere on imaging, defined as the lower value between either putamina (P < 0.000001), constipation, (P < 0.000001) and age over 70 years (P = 0.0002). Combined features obtained from the generalized logistic regression achieved a hazard ratio of 5.71 (95% confidence interval 2.85–11.43). Bayesian classifier suggested that patients with higher Mini-Mental State Examination score and lower caudate SBR asymmetry were more likely to develop parkinsonism, while patients with the opposite pattern were more likely to develop dementia. This study shows that iRBD patients older than 70 with constipation and reduced nigro-putaminal dopaminergic function are at high risk of short-term phenoconversion to an overt synucleinopathy, providing an effective stratification approach for future neuroprotective trials. Moreover, we provide cut-off values for the significant predictors of phenoconversion to be used in single subjects.

Funder

Monument Trust Discovery Award

National Institute for Health Research (NIHR) Oxford Biomedical Research Centre

Oxford University Hospitals NHS Trust

University of Oxford, the NIHR Clinical Research Network

Dementias and Neurodegenerative Diseases Research Network

GE Healthcare

NIH

Publisher

Oxford University Press (OUP)

Subject

Clinical Neurology

Reference31 articles.

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4. Smell diskettes as screening test of olfaction;Briner;Rhinology,1999

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