Predictors of Conversion to α-Synucleinopathy Diseases in Idiopathic Rapid Eye Movement Sleep Behavior Disorder

Idiopathic rapid eye movement sleep behavior disorder (iRBD) often precedes the development of α-synucleinopathy diseases.

We aimed to assess the predictive value of clinical variables and biomarkers for the early development of α-synucleinopathy diseases in subjects with iRBD.

56 patients with RBD Screening Questionnaire (RBDSQ) scores ≥5 at baseline and subsequent visit were enrolled as probable iRBD from the Parkinson's Progression Markers Initiative (PPMI) database. Baseline clinical data and biomarkers were analyzed. The endpoint was defined as disease progression to α-synucleinopathy diseases. Cox proportional hazard and Kaplan-Meier analyses were used to evaluate the predictive values of the indicators.

During a mean follow-up duration of 5.1 years, 15 of 56 patients (26.8%) developed α-synucleinopathy diseases. Baseline clinical variables, including University of Pennsylvania Smell Identification Test (UPSIT, HR = 26.18, p = 0.004), 15-item Geriatric Depression Scale (GDS, HR = 14.26, p = 0.001), Montreal Cognitive Assessment (MoCA, HR = 3.56, p = 0.025), and Hopkins Verbal Learning Test Total recall (HVLT-TR, HR = 3.70, p = 0.014); genotype status of TMEM175 (HR = 3.74, p = 0.017), SCN3A (HR = 5.81, p = 0.022) and NUCKS1 (HR = 0.342, p = 0.049); ratio of phosphorylated tau to total tau (p-tau/t-tau, HR = 8.36, p = 0.001) in cerebrospinal fluid; and gray matter atrophy in inferior frontal gyrus (IFG, HR = 15.49, p = 0.001) were associated with phenoconversion to α-synucleinopathy diseases. A model combined the three independent variables (UPSIT, TMEM175 and gray matter atrophy in IFG) exhibited significantly improved predictive performance.

For patients with iRBD, progression to α-synucleinopathy diseases can be predicted with good accuracy using a model combining clinical variables and biomarkers, which could form a basis for future disease prevention.