Objective: To develop an imaging biomarker predicting subtype-specific phenoconversion in isolated REM sleep behavior disorder (iRBD), we aim at identifying MRI-driven cortical thickness signature in a prospective cohort of iRBD.

Background: The biomarkers that can easily and reliably predict subtype-specific phenoconversion in iRBD have not yet been established.

Method: The DLB-related cortical thickness covariance pattern (DLB-pattern) was derived from 22 established DLB patients using principal component analysis with 3T MR images that best differentiated DLB from age-matched controls. Then, we calculated the DLB-pattern expressions and mean cortical thickness in 48 polysomnography-proven iRBD patients. We investigated the longitudinal trajectory of the DLB-pattern expressions and mean cortical thickness in individuals with iRBD. We analyzed the predictability of baseline cortical thickness signature in overall and subtype-specific phenoconversions in iRBD patients.

Results: The DLB-pattern comprised temporal, orbitofrontal, and insular cortices as a negative contribution and precentral and inferior parietal cortices as a positive contribution. The DLB-pattern scores showed correlation with attention and frontal executive functions (trail making test-A: R=-0.55, p=0.024 and trail making test-B: R=-0.56, p=0.036) and visuospatial performance (Rey-figure copy test: R=-0.54, p=0.0047) in DLB patients and controls. The DLB-pattern was not elevated in the iRBD group at baseline, but the expression scores correlated with 4-year cognitive declines in the visuospatial (Rey-figure copy test: R=-0.22, p=0.035) and memory domains (verbal learning test: R=-0.46, p=0.018) in iRBD patients. Fifteen patients developed phenoconversion during average ± standard deviation of 4.23 ± 2.49 follow-up years (annual conversion rate=7.2%). The baseline DLB-pattern score differentiated dementia-first converters and parkinsonism-first converters with 80% sensitivity and 100% specificity. The low mean cortical thickness (z-score < 0) significantly predicted overall pheonconversion in iRBD patients (HR [95% confidence interval] = 9.28 [1.14 75.77]).

Conclusion: We identified MRI-driven cortical thickness signature that predicts subtype-specific conversion in iRBD which can be a candidate biomarker for optimized monitoring and stratifying future converters in iRBD.

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MDS Abstracts - https://www.mdsabstracts.org/abstract/the-cortical-thickness-signature-and-future-phenoconversion-in-isolated-rem-sleep-behavior-disorder-a-longitudinal-analysis/