Parkinsonism & Related Disorders · Mar 2, 2026

Biological characteristics of individuals with REM sleep behavior disorder: A multicenter prospective longitudinal cohort

By Feuerstein J, Brown E, Chahine L et al.

BACKGROUND: Treating neuronal alpha-synuclein disease (NSD) requires early disease identification. Isolated REM Sleep Behavior (iRBD), a key clinical biomarker, can present before clinically diagnostic symptoms. Characterizing RBD longitudinally, using biological and clinical markers, will optimize future clinical trial enrollment, evaluation, and outcome measures. We aim to characterize baseline and longitudinal progression of polysomnography-confirmed iRBD participants and compare those who do and do not progress to a clinically defined synucleinopathy. METHODS: Characteristics of 28 iRBD participants were evaluated at baseline and annually through year four. Those with clinical synucleinopathy at baseline were excluded. Dopamine Transporter (DAT) SPECT at baseline and year 4 were compared. Clinical phenoconversion was defined by a new clinical synucleinopathy diagnosis. NSD + individuals were characterized using the NSD Integrated Staging System (NSD-ISS) [1]. RESULTS: At year 4, 25% of participants had clinically defined synucleinopathy. At baseline, participants who phenoconverted were S+ (type 1), had age/sex-expected lowest putamen specific binding ratio (%DAT) of 40.1% (±11.2%), lowest putamen specific binding ratio (SBR) of 0.8 (±0.2), and were NSD stage 2b or above. Baseline %DAT of non-phenoconverters was 61.1% (±13.7%) and SBR was 1.1 (±0.3). Between-group comparison of %DAT and SBR were significantly different at baseline (p = 0.001 and 0.013, respectively). CONCLUSION: The NSD-ISS, informed by biological and clinical data, identifies individuals at risk for clinical phenoconversion before clinical diagnoses occur, and its utilization may identify optimal participants for enrollment in disease modifying clinical trials. DAT imaging may serve as an appropriate marker of disease progression in NSD.

doi.org/10.1016/j.parkreldis.2026.108266 PubMed 41780487 Biomarkers