Objective To study the role of GBA variants in the risk for isolated REM sleep behavior disorder (iRBD) and conversion to overt neurodegeneration. Methods A total of 4,147 individuals were included: 1,061 patients with iRBD and 3,086 controls. GBA was fully sequenced using molecular inversion probes and Sanger sequencing. We analyzed the effects of GBA variants on the risk of iRBD, age at onset (AAO), and conversion rates. Results GBA variants were found in 9.5% of patients with iRBD compared to 4.1% of controls (odds ratio, 2.45; 95% confidence interval [CI], 1.87–3.22; p = 1 × 10⁻¹⁰). The estimated OR for mild p.N370S variant carriers was 3.69 (95% CI, 1.90–7.14; p = 3.5 × 10⁻⁵), while for severe variant carriers it was 17.55 (95% CI, 2.11–145.9; p = 0.0015). Carriers of severe GBA variants had an average AAO of 52.8 years, 7–8 years earlier than those with mild variants or noncarriers (p = 0.029). Of the GBA variant carriers with available data, 52.5% had converted, compared to 35.6% of noncarriers (p = 0.011), with a trend for faster conversion among severe GBA variant carriers. However, the results on AAO and conversion were based on small numbers and should be interpreted with caution. Conclusions GBA variants robustly and differentially increase the risk of iRBD. The rate of conversion to neurodegeneration is also increased and may be faster among severe GBA variant carriers, although confirmation will be required in larger samples. Screening for RBD in healthy carriers of GBA variants should be studied as a potential way to identify GBA variant carriers who will develop a synucleinopathy in the future.

REM sleep without atonia (RSWA) is the polysomnographic (PSG) hallmark of rapid eye movement (REM) sleep behavior disorder (RBD), a feature essential for the diagnosis of this condition. Several additional neurophysiological aspects of this complex disorder have also recently been investigated in depth, which constitute the focus of this narrative review, together with RSWA. First, we describe the complex neural network underlying REM sleep and its muscle atonia, focusing on the disordered mechanisms leading to RSWA. RSWA is then described in terms of its polysomnographic features, and the methods (visual and automatic) currently available for its scoring and quantification are exposed and discussed. Subsequently, more recent and advanced neurophysiological features of RBD are described, such as electroencephalography during wakefulness and sleep, transcranial magnetic stimulation, and vestibular evoked myogenic potentials. The role of the assessment of neurophysiological features in the study of RBD is then carefully discussed, highlighting their usefulness and sensitivity in detecting neurodegeneration in the early or prodromal stages of RBD, as well as their relationship with other proposed biomarkers for the diagnosis, prognosis, and monitoring of this condition. Finally, a future research agenda is proposed to help clarify the many still unclear aspects of RBD.

To compare three different methods, two visual and one automatic, for the quantification of rapid eye movement (REM) sleep without atonia (RSWA) in the diagnosis of REM sleep behavior disorder (RBD) in Parkinson’s disease (PD) patients. Sixty-two consecutive patients with idiopathic PD underwent video-polysomnographic recording and showed more than 5 minutes of REM sleep. The electromyogram during REM sleep was analyzed by means of two visual methods (Montréal and SINBAR) and one automatic analysis (REM Atonia Index or RAI). RBD was diagnosed according to standard criteria and a series of diagnostic accuracy measures were calculated for each method, as well as the agreement between them. RBD was diagnosed in 59.7% of patients. The accuracy (85.5%), receiver operating characteristic (ROC) area (0.833) and Cohen’s K coefficient (0.688) obtained with RAI were similar to those of the visual parameters. Visual tonic parameters, alone or in combination with phasic activity, showed high values of accuracy (93.5–95.2%), ROC area (0.92–0.94), and Cohen’s K (0.862–0.933). Similarly, the agreement between the two visual methods was very high, and the agreement between each visual methods and RAI was substantial. Visual phasic measures alone performed worse than all the other measures. The diagnostic accuracy of RSWA obtained with both visual and automatic methods was high and there was a general agreement between methods. RAI may be used as the first line method to detect RSWA in the diagnosis of RBD in PD, together with the visual inspection of video-recorded behaviors, while the visual analysis of RSWA might be used in doubtful cases.