See Morris and Weil (doi: ) for a scientific commentary on this article. In a prospective multicentre study involving 1280 patients with idiopathic RBD, Postuma et al. show that approximately 6% of patients each year (>73.5% over 12 years) convert to full neurodegenerative disease. They test the predictive power of 21 prodromal markers of neurodegeneration, providing a template for planning neuroprotective trials.

So-called idiopathic rapid eye movement (REM) sleep behaviour disorder (RBD), formerly seen as a rare parasomnia, is now recognized as the prodromal stage of an α-synucleinopathy. Given the very high risk that patients with idiopathic RBD have of developing α-synucleinopathies, such as Parkinson disease (PD), PD dementia, dementia with Lewy bodies or multiple system atrophy, and the outstandingly high specificity and very long interval between the onset of idiopathic RBD and the clinical manifestations of α-synucleinopathies, the prodromal phase of this disorder represents a unique opportunity for potentially disease-modifying intervention. This Review provides an update on classic and novel biomarkers of α-synuclein-related neurodegeneration in patients with idiopathic RBD, focusing on advances in imaging and neurophysiological, cognitive, autonomic, tissue-specific and other biomarkers. We discuss the strengths, potential weaknesses and suitability of these biomarkers for identifying RBD and neurodegeneration, with an emphasis on predicting progression to overt α-synucleinopathy. The role of video polysomnography in providing quantifiable and potentially treatment-responsive biomarkers of neurodegeneration is highlighted. In light of all these advances, and the now understood role of idiopathic RBD as an early manifestation of α-synuclein disease, we call for idiopathic RBD to be reconceptualized as isolated RBD.

Analysis of sleep for the diagnosis of sleep disorders such as Type-1 Narcolepsy (T1N) currently requires visual inspection of polysomnography records by trained scoring technicians. Here, we used neural networks in approximately 3,000 normal and abnormal sleep recordings to automate sleep stage scoring, producing a hypnodensity graph—a probability distribution conveying more information than classical hypnograms. Accuracy of sleep stage scoring was validated in 70 subjects assessed by six scorers. The best model performed better than any individual scorer (87% versus consensus). It also reliably scores sleep down to 5 s instead of 30 s scoring epochs. A T1N marker based on unusual sleep stage overlaps achieved a specificity of 96% and a sensitivity of 91%, validated in independent datasets. Addition of HLA-DQB1*06:02 typing increased specificity to 99%. Our method can reduce time spent in sleep clinics and automates T1N diagnosis. It also opens the possibility of diagnosing T1N using home sleep studies.

SummaryBackgroundRestless legs syndrome is a prevalent chronic neurological disorder with potentially severe mental and physical health consequences. Clearer understanding of the underlying pathophysiology is needed to improve treatment options. We did a meta-analysis of genome-wide association studies (GWASs) to identify potential molecular targets.MethodsIn the discovery stage, we combined three GWAS datasets (EU-RLS GENE, INTERVAL, and 23andMe) with diagnosis data collected from 2003 to 2017, in face-to-face interviews or via questionnaires, and involving 15 126 cases and 95 725 controls of European ancestry. We identified common variants by fixed-effect inverse-variance meta-analysis. Significant genome-wide signals (p≤5 × 10−8) were tested for replication in an independent GWAS of 30 770 cases and 286 913 controls, followed by a joint analysis of the discovery and replication stages. We did gene annotation, pathway, and gene-set-enrichment analyses and studied the genetic correlations between restless legs syndrome and traits of interest.FindingsWe identified and replicated 13 new risk loci for restless legs syndrome and confirmed the previously identified six risk loci. MEIS1 was confirmed as the strongest genetic risk factor for restless legs syndrome (odds ratio 1·92, 95% CI 1·85–1·99). Gene prioritisation, enrichment, and genetic correlation analyses showed that identified pathways were related to neurodevelopment and highlighted genes linked to axon guidance (associated with SEMA6D), synapse formation (NTNG1), and neuronal specification (HOXB cluster family and MYT1).InterpretationIdentification of new candidate genes and associated pathways will inform future functional research. Advances in understanding of the molecular mechanisms that underlie restless legs syndrome could lead to new treatment options. We focused on common variants; thus, additional studies are needed to dissect the roles of rare and structural variations.FundingDeutsche Forschungsgemeinschaft, Helmholtz Zentrum München–Deutsches Forschungszentrum für Gesundheit und Umwelt, National Research Institutions, NHS Blood and Transplant, National Institute for Health Research, British Heart Foundation, European Commission, European Research Council, National Institutes of Health, National Institute of Neurological Disorders and Stroke, NIH Research Cambridge Biomedical Research Centre, and UK Medical Research Council.

DAT-SPECT identifies IRBD patients at short-term risk for synucleinopathy. Decreased FP-CIT putamen uptake greater than 25% predicts synucleinopathy after 3 years' follow-up. These observations may be useful to select candidates for disease modification trials in IRBD. Ann Neurol 2017;82:419-428.

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Video-polysomnography (v-PSG) is essential for diagnosing rapid eye movement (REM) sleep behavior disorder (RBD). Although there are current American Academy of Sleep Medicine standards to diagnose RBD, several aspects need to be addressed to achieve harmonization across sleep centers. Prodromal RBD is a stage in which symptoms and signs of evolving RBD are present, but do not yet meet established diagnostic criteria for RBD. However, the boundary between prodromal and definite RBD is still unclear. As a common effort of the Neurophysiology Working Group of the International RBD Study Group, this manuscript addresses the need for comprehensive and unambiguous v-PSG recommendations to diagnose RBD and identify prodromal RBD. These include: (1) standardized v-PSG technical settings; (2) specific considerations for REM sleep scoring; (3) harmonized methods for scoring REM sleep without atonia; (4) consistent methods to analyze video and audio recorded during v-PSGs and to classify movements and vocalizations; (5) clear v-PSG guidelines to diagnose RBD and identify prodromal RBD. Each section follows a common template: The current recommendations and methods are presented, their limitations are outlined, and new recommendations are described. Finally, future directions are presented. These v-PSG recommendations are intended for both practicing clinicians and researchers. Classification and quantification of motor events, RBD episodes and vocalizations are however intended for research purposes only. These v-PSG guidelines will allow collection of homogeneous data, providing objective v-PSG measures and making future harmonized multicentric studies and clinical trials possible.

Sleep disturbances are common in Parkinson's disease and comprise the entire spectrum of sleep disorders. On the one hand regulation of sleep and wakefulness is affected in Parkinson's disease, leading to the development of disorders, such as insomnia and daytime sleepiness. While on the other hand control of motor activity during sleep is impaired, with subsequent manifestation of parasomnias (mainly REM sleep behavior disorders, but also, albeit more rarely, sleepwalking, and overlap parasomnia). Restless legs syndrome has been reported to be frequent in patients with Parkinson's disease, although there is no consensus on whether it is more frequent in Parkinson's disease than in the general population. The same is true for sleep-related breathing disorders. Regarding the diagnosis of sleep disorders in patients with Parkinson's disease, one of the main challenges is correctly identifying excessive daytime sleepiness as there are many potential confounding factors, for example it is necessary to distinguish sleeprelated breathing disorders from medication effects, and to distinguish restless legs syndrome from the concomitant presence of potential mimics specific to Parkinson's disease, such as akathisia, nocturnal leg cramps, nocturnal hypokinesia, early morning dystonia, etc. The correct diagnosis of REM sleep behavior disorder is also not always easy, and video-polysomnography should be performed in order to exclude mimic-like movements at the end of sleep apneas or violent periodic leg movements of sleep. These aspects and specific considerations about diagnosis and treatment of sleep disorders in patients with Parkinson's disease will be reviewed.