Automated Analysis of REM Sleep without Atonia in the Lewy Body Disease Spectrum
Emma P. Strainis, Jack T. Jagielski, Laurene LeClair‐Visonneau, Scott A. Przybelski, John C Feemster, Stuart J McCarter, Diego Z. Carvalho, Michael H Silber, Prashanthi Vemuri, Clifford R. Jack, Toji Miyagawa, Leah K. Forsberg, Julie A. Fields, Rodolfo Savica, Jonathan Graff‐Radford, David T. Jones, Hugo Botha, Vijay K Ramanan, David S. Knopman, Neill R Graff‐Radford, Tanis J Ferman, Ronald C. Petersen, Val J. Lowe, Brad F. Boeve, Kejal Kantarci, Brynn Dredla, Erik K St Louis- Psychiatry and Mental health
- Cellular and Molecular Neuroscience
- Geriatrics and Gerontology
- Neurology (clinical)
- Developmental Neuroscience
- Health Policy
- Epidemiology
Abstract
Background
Quantitative rapid eye movement (REM) sleep without atonia (RSWA) recorded during polysomnography (PSG) represents loss of normal REM sleep atonia. RSWA is the neurophysiologic signature of REM sleep behavior disorder (RBD). Visually scored RSWA is a candidate biomarker for synucleinopathies. However, visual RSWA scoring requires expert scoring, limiting widespread application. We comparatively analyzed RSWA in DLB and iRBD using the automated Ferri REM Atonia Index (RAI).
Method
We quantitatively analyzed the RAI in 12 DLB and 20 iRBD patients, compared to 20 controls using Hypnolab Software for Sleep Analysis (SWS Soft, Inc, Colognola ai Colli, Italy). PSG data were converted to European Data Format (.EDF), and the submentalis surface electromyogram (EMG) signal was notch‐filtered at 60 Hertz and rectified. Automatically calculated RAI scores were comparatively analyzed across groups (DLB, iRBD, controls) using Kruskal Wallis H tests for group comparisons, and regression analyses determined relationships between diagnosis, age, and sex. Logistic regression ROC determined optimal RAI for distinguishing iRBD from DLB. When interpreting RAI, lower values represent greater amounts of RSWA, and higher values represent more normal REM atonia.
Result
Mean age was older in DLB than in iRBD or controls (72.6 vs. 68.7 vs. 66.5 years). All 12 DLB participants were men, the iRBD group had 18 men and 2 women, and controls were comprised of 16 men and 4 women. Mean RAI was lowest in DLB (0.46), intermediate in iRBD (0.71) and highest in controls (0.96), indicating a gradient in RSWA amounts from DLB patients (highest) to controls (lowest) (Figure). Regression demonstrated diagnosis independently predicted RAI, controlling for age and sex (adjusted R2 = 0.49, p = 0.0001). The RAI that optimally distinguished iRBD from DLB was 0.46 (specificity 85%, sensitivity 58%, AUC = 0.75).
Conclusion
The RAI demonstrated a clear gradient throughout the Lewy body spectrum; highest (indicating lowest RSWA amounts) in controls, intermediate in iRBD, and lowest (indicating greatest RSWA) in DLB. The RAI is a promising, time efficient and broadly applicable candidate biomarker for DLB and iRBD. Automated quantitative RSWA could be a valuable tool for deep phenotyping throughout the Lewy body disease spectrum.