REM slaap gedragsstoornis REM-sleep-behavior disorder (RBD)
Conditions
Interventions
None listed
Sponsors
Universitair Medisch Centrum Groningen
Eligibility
Age
18 Years to 99 Years
Inclusion criteria
Inclusion criteria: - Age between 40 and 70 years old at the time of the first FDG PET scan - Women, only if they are postmenopausal (> 1 year no menses). - Written informed consent - Capacity to understand the study - Diagnosis of RBD according to the criteria of International Classification of Sleep Disorders (ASDA Criteria 2005
Exclusion criteria
Exclusion criteria: * Claustrophobia * Abuse of drugs or alcohol at present or in the past (as determined by disclosed medical history) * Kidney diseases with elevated levels of blood creatinine, liver diseases with elevated levels of blood transaminases (at least 3 times as high as normal), or an elevated blood level of gamma-GT (at least 5 times higher than normal) * Insulin-dependent diabetes mellitus * Hyperglycemia before the [18F]FDG-PET scan (> 7 mmol/l) * Use of benzodiazepines during the day before the FDG-PET scan * Structural cerebral lesion or any other neurological disease which can interfere with the analysis of the image data (for example, a stroke in the past) * If subjects do not want to be informed about an unforeseen clinical finding * Phenoconversion to manifest alpha-synucleinopathy (PD, MSA, DLB) during REMPET2
Design outcomes
Primary
| Measure | Time frame |
|---|---|
| PDRP expression scores will be extracted from the [18F]FDG-PET data images of participants with RBD at two (and in some cases three) time points. The key measure will be the expression of the PDRP pattern at the time of the clinical diagnosis (PSG-confirmed) of iRBD - the baseline - and after a follow-up period approximately of 4 years. In addition, we aim to measure functional dopaminergic deterioration over time as well. Thus, the changes between the baseline DAT-SPECT exam and DAT-SPECT scan at the follow-up visit (approximately 4 years) will be investigated in parallel. An MRI scan of the brain at baseline has been already acquired to exclude other diagnoses. During REMPET2, 20% of our iRBD subjects phenoconverted to PD (4/20). Considering the more extensive dataset now available from the 5 participating centres, we strive to end up with a group of 20-25 phenoconverted iRBD subjects with multiple [18F]FDG-PET brain scans throughout this study. | — |
Secondary
| Measure | Time frame |
|---|---|
| Secondary aims: In addition, we aim to investigate PDRP expression in a sub-group of iRBD patients (19 out of 159; combined Dutch (n=2) and German (n=17)) at three time points. These are the iRBD patients that already participated in both REMPET2 and REMPET1 studies, and did not yet phenoconvert during those studies. Dutch patients will be invited for a third follow-up visit, including clinical work-up and imaging with [18F]FDG-PET and DAT-SPECT. German patients are followed up clinically and with DAT-SPECT in Marburg, Germany, but will be invited to come to the UMCG for their third [18F]FDG-PET scan because they performed the previous [18F]FDG-PET scans in UMCG in the context of REMPET1 and/or REMPET2 studies. REMPET2 covered three years of follow-up and given promising results [2], the continuation of the project in REMPET3 is warranted. Neurodegeneration in iRBD is an ongoing process, and accordingly, brain metabolic patterns might change over time. The latency from symptom onset to disease phenoconversion (i.e. conversion from iRBD to defined DLB, PD, or MSA) averages over 10 years. Thus, having [18F]FDG-PET scans at multiple time points will maximise the possibility to find meaningful changes over time. No longitudinal studies have yet assessed the temporal evolution of the PDRP in iRBD patients considering multiple time points. Thus, having three time points [18F]FDG-PET acquisitions combined with a long clinical follow-up allows us to have a unique imaging and clinical database with the great potential to track neurobiological mechanisms underlying a-synuclein related neurodegenerative spreading. Another secondary objective is to apply other uni- and multivariate methods to the data, as well as advanced machine-learning algorithms to explore whether other methods may give additional information about the brain metabolic changes over time in association with disease progression. Finally, changes in functional dopaminergic deteriorati | — |
Countries
Netherlands
Outcome results
None listed