Mazeika, Gandis

Abstract Introduction n this cross-validation study, the distributions of sleep biomarker-based neurodegenerative disorder (NDD) risk were evaluated across a spectrum of NDD patients and presumed controls which were independent of the model development dataset. Methods Variables that included age, time-REM, non-REM hypertonia, autonomic-activation index, spindle-duration, atypical-N3, time-supine, sleep-efficiency, relative-theta, and theta/alpha obtained with Sleep Profiler were used to train a 4-class machine learning algorithm that generated probabilities of NDD risk for the groups: Alzheimer’s dementia (AD), Lewy body disorder (LBD), prodromal synucleinopathy (pSYN based on REM sleep behavior disorder patients), and controls (CG). Records with CG output probabilities >70% were labeled Probably-normal, and from 45-70% Likely-normal with indications of a NDD added when the LBD, AD or pSYN risks exceeded approximately 25%. Similar thresholds were used to assign Likely- or Probable- LBD, AD, pSYN or Mixed based on the group probabilities. This cross-validation study was designed to use datasets that were independent of those used to train the classification algorithm. Thus, NDD risk distributions were evaluated in patients with mild cognitive impairment (MCI=71), Parkinson’s disease (PD=16), progressive supranuclear palsy (PSP=21) and control subjects (NC=41) with Mini-Mental State Exam scores>28 and/or normal for MCI by Petersen criteria. Results In the MCI group, NDD risk assignments were Probable-AD=26%, -Mixed=10%, -LBD=1%, Likely-AD= 7%, -Mixed=6%, -LBD=3%, -pSYN=1%, Likely-Normal indications-AD=9%, -pSYN=7%, -Mixed=4%, and Probably-Normal=26% In the PSP group, Probable-LBD=43%, -Mixed=29% and -pSYN=4%, Likely-Mixed=10%, Likely-Normal indications AD=10%, and Probably-Normal=4%. In the PD group, Probable-LBD=13%, -pSYN=13%, -AD=6%, Likely-Mixed=19%, -pSYN=6%, Likely-Normal Indications-pSYN=19%, -AD=12%, Likely-Normal=6% and Probably-Normal=6% In the NC group, 83% were assigned minimal NDD risk with Probably-Normal=70%, Likely-Normal plus indications=13%, but with Likely NDD=13% and Probable NDD=4%. Conclusion NDD risks were disbursed in a manner consistent with the range of severities expected In MCI and PD groups, with 25% exhibiting relatively normal sleep patterns. Over 70% of the PSP patients exhibited probable NDD risk, with patterns similar to those with LBD. The NC NDD risk distributions were consistent with those assigned to the CG used for model development. Support (if any) NIH grants R44AG050326, R44AG054256, RO1AG060477, R33AG064271, ULRR024150, R34AG056639.

Abstract Introduction In this pilot study, the diagnostic agreement for sleep biomarker-based neurodegenerative disorder (NDD) risk probabilities was evaluated in patients with Alzheimer’s disease dementia (AD), Lewy Body disease (LBD), and isolated REM sleep behavior disorder (iRBD) and controls with a Mini-Mental State Exam scores>28. Methods Sleep biomarkers recorded with the Sleep Profiler (Advanced Brain Monitoring, Inc) were used as inputs to a 4-class machine learning algorithm trained to assign NDD risk probabilities to AD=27, LBD=19, iRBD=15 and controls (CG=58). Input variables included age, time-REM, non-REM hypertonia, autonomic-activation index, spindle-duration, atypical-N3, time-supine, sleep-efficiency, relative-theta, and theta/alpha. Records with CG output probabilities >70% were labeled Probably-normal, and from 45-70% Likely-normal with indications of a NDD added when the LBD, AD or prodromal synucleinopathy (pSYN) risks exceeded approximately 25%. Similar thresholds were used to assign Likely- or Probable- LBD, AD, or pSYN based each of the group probabilities. Classification accuracies were evaluated in AD=37, LBD=19, iRBD=19 and CG=61 records. Longitudinal test-retest reliabilities were assessed for CG (n=45, range 8-56 months), and after six-months for LBD (n=10) and AD (n=9). Results In the AD group, NDD risk assignments were consistent with diagnoses=85%, with Probable-NDD=59%, Likely-NDD=11%, Normal plus AD/Mixed indications=15%, but with 5%=Probably-normal. In the LBD group, assigned risks were consistent with the diagnosis=79%, with Probable-NDD=74%, Normal with pSYN indications=5%, but with 11%=Probably-normal. In the iRBD group, Probable-NDD=42%, Normal plus pSYN indications=26% and Probably-normal=32%. In the CG group, 89% were assigned minimal NDD risks with Probably-normal=67%, Normal plus indications=22%, but with Likely NDD=8% and Probable NDD=3%. The AD test-retest reliability showed the same NDD classifications=78%, with slightly increasing=11% and decreased=11%. In the LBD group, the same NDD classifications were achieved=80%, with trending equivalence=10%, and decreasing severity=20%. The CG test-retest reliability showed the same NDD classifications=76%, with trending equivalence=22%, and increased severity=2%. Conclusion Consistencies between the diagnoses and assigned NDD risks and test-retest classification agreements were approximately 80% in the AD, LBD, and CG groups. In the iRBD group, the NDD risks were disbursed consistent with the range of expected severities. These results needed to be cross-validated in independent NDD datasets. Support (if any) NIH grants R44AG050326, R44AG054256, RO1AG060477, R33AG064271, ULRR024150, R34AG056639.

Abstract Introduction In this pilot study, sleep biomarker-based neurodegenerative disorder (NDD) risk was assessed in a clinical cohort of patients diagnosed with varying severity of obstructive sleep apnea (OSA). Methods Consecutive in-home multi-night Sleep Profiler records from a community sleep clinic were screened for age >54 years old. Cases with comorbid restless leg syndrome, hypersomnia, missing apnea-hypopnea indexes (AHI), AHI< 5 or single-night recordings were excluded. The 67 remaining records were 40% female, ages 63 + 7.4 years and up to 84 years old. NDD risk was assigned using a machine-learning algorithm combining age and nine sleep biomarkers to assign group probabilities: for Alzheimer’s disease, Lewy Body disease, prodromal synucleinopathy and controls (CG). Sleep biomarkers included: time-REM, non-REM hypertonia, autonomic-activation index, spindle-duration, atypical-N3, time-supine, sleep-efficiency, relative-theta, and theta/alpha. Those with CG probability score >70% were classified as “Probably-normal”. Those with CG probability between 45 - 70% were classified as “Likely-normal”. Insomnia severity >14 and a PHQ 9 > 5 were used as cutoffs for clinical insomnia and depression. Mann-Whitney U-tests were used to evaluate group differences. Results This cohort had 37% mild, 34% moderate, and 29% severe OSA. Self-reported comorbid insomnia and depression were present in 43%. Seventy-three percent of patients were classified as “Probably-normal”, 16% “Likely-normal”, 11% “Likely-NDD” or “Probable-NDD”. The “Probably-normal” group was younger than the rest of the cohort (62 + 6.2 years vs. 68 + 8.6 years, p< 0.01). Of those classified as “Probably-normal” (n=49), OSA was mild in 16, moderate in 17 and severe in 16. Mean AHI trended higher in the “Probably-normal” group than in those with elevated NDD risk (29 + 23.9 vs. 19 + 13.6 events/h, p=0.085). Conclusion Approximately 89% of the clinical cohort was classified as “Probably-normal” or “Likely-normal”. NDD risk was age-dependent. Interactions between OSA severity and NDD risk were not apparent in these findings, possibly related to group-wide effects. NDD risk, as measured by this model, did not appear to be adversely biased by untreated OSA. These results suggest a need for longitudinal studies to compare NDD risk in untreated OSA versus controls without sleep disordered breathing. Support (if any) NIH grants R44AG050326, R44AG054256, RO1AG060477, R33AG064271, ULRR024150, and R34AG056639.

Abstract Introduction Non-REM hypertonia (NRH) was recently reported to be independently associated with the synucleinopathy-mediated neurodegenerative disorders: dementia with Lewy Bodies/Parkinson Disease Dementia (DLB/PDD), Parkinson Disease (PD), and isolated REM sleep behavior disorder (iRBD). In this NRH investigation, we included progressive supranuclear palsy (PSP), a Parkinsonian-spectrum disorder caused by tau pathology. Methods In this multicenter study, patients broadly characterized as presumed Parkinsonian-spectrum disorders (PSD) included DLB/PDD (n=16), PD (n=16), iRBD (n=19), and PSP (n=13). Presumed non-PSD subjects included Alzheimer’s Disease dementia (AD=22), mild cognitive impairment (MCI=35), and normal cognition (NC=61). Sleep Profiler studies were acquired in all participants. NRH, auto-detected based on persistently elevated electromyographic (EMG) power relative to delta, theta, and sigma bands in the differential Af7-Af8 signal, was measured as a percentage of sleep time and then weight-averaged in the 75% of in-home studies with two-nights of data. A >5% threshold characterized abnormal-NRH. Twenty-nine NC were longitudinally retested after 364- to 563-days. Statistical analyses included inter-class correlations (ICC), Bland-Altman plots, multiple logistic regression, and receiver-operating-characteristic curves (ROC). Results In the PSD=41 and non-PSD=95 records with two-nights of data, NRH-severity demonstrated moderate consistency (ICC=0.78, bias=0.6+/-6.2%, P<0.0001). Across the two-nights, NRH was classified consistently as normal or abnormal in 59.6% and 27.2% of the records, vs. normal/abnormal=4.4% or abnormal/normal=8.8%. The test-retest reliability of NRH-severity was good (ICC=0.84, bias=0.06+/-3.8%, P<0.0001), with all retest comparisons repeating as normal (73%) or abnormal (27%). The frequency of abnormal-NRH in PSP=92% was significantly greater than MCI=26%, AD=14%, and NC=16% (all P<0.0001) and PD=56% (P<0.05), but not DLB/PDD=81% and iRBD=74%. Abnormal-NRH was significantly associated with the PSD group (P<0.0001) and it differentiated PSD versus non-PSD group with an area under the curve of 0.78 (95%CI: 0.72-0.85) based on a sensitivity of 0.75 (95%CI: 0.63-0.84) and a specificity of 0.81 (85%CI: 0.73-0.87). Conclusion NRH independently discriminated PSD patients from age-sex similar non-PSD subjects, suggesting that NRH is a common sleep motor signature across clinical PSD phenotypes. We speculate that NRH could be related to pathological changes within the key non-REM sleep motor modulating center in synucleinopathies and PSP. Support (If Any) NIA grants: R44AG050326, R44AG054256, P30AG62677 and R34AG56639.

Abstract Introduction Decreased sleep spindle oscillations were previously associated with cognitive decline in older adults, increased tau levels, and phenoconversion to dementia in patients with Parkinson disease (PD). We analyzed quantitative sleep spindle measures to determine if this biomarker was associated with particular neurodegenerative disorder syndromes. Methods Sleep spindle oscillations ascertained in patients broadly characterized as presumed Parkinsonian-spectrum disorders (PSD), which included the subtypes dementia with Lewy Bodies/Parkinson Disease Dementia (DLB/PDD, n=16), PD (n=16), isolated REM sleep behavior disorder (iRBD, n=19), and progressive supranuclear palsy (PSP, n=13), were compared with non-PSD subtypes Alzheimer Disease dementia (AD, n=22), mild cognitive impairment (MCI, n=35), and normal cognition (NC, n=61). Sleep Profiler studies were conducted in all participants. The automated spindle detection algorithms recognized temporal excursions in the alpha (8-12 Hz) and sigma (12-16 Hz) power of 250 milliseconds or greater, with spindle duration being the sum of all spindle elapsed times. Night-to-night variability was assessed in PSP=13, PD=16, DLB/PDD=12, AD=17, MCI=25, and NC=53. Statistical analyses included intraclass correlations (ICC) and Bland-Altman plots for two-night data, and Mann-Whitney U-tests and multiple logistic regression applied to sleep-time weight-averaged spindle-durations. Results The night-to-night spindle-duration ICC was 0.95 (P<0.0001), with a Bland-Altman bias of 0.05+/-2.83 minutes. Spindle-duration was independently associated with PSD versus non-PSD groups (P=0.017, OR 1.08, 95%-CI 1.01-1.15), but not significantly associated with age (P=0.12, OR 1.03, 95%-CI 0.99-1.07) or sex (P=0.54). When stratified by subtype, age was associated with spindle-duration when NC were compared to AD and MCI (P=0.0003, OR 1.10, 95%-CI 1.04-1.16) and when iRBD were compared to DLB/PDD, PD and PSP (P<0.05, OR 1.00, 95%-CI 0.89-1.13)Spindle-durations were reduced in PSP (0.9+/-2.1) and DLB/PDD (2.0+/-5.1) when individually compared to AD (3.2+/-7.1), iRBD (3.3+/-3.4), PD (5.3+/-6.6), MCI (5.3+/-9.7), and NC (8.0+/-11.1) subtypes (all P<0.05). AD patients also exhibited lower spindle-durations than NC (P=0.03). Conclusion Auto-detected sleep spindle-durations exhibited excellent night-to-night reliability in both NC and patients with neurologic disorders. Decreased sleep spindle-duration was independently associated with PSP and DLB/PDD, and in AD. Reduced sleep spindle duration may be a distinct sleep biomarker for those disorders likely indicating thalamocortical dysfunction. Support (If Any) NIA grants: R44AG050326, R44AG054256, P30AG62677 and R34AG56639.

Abstract Introduction The severity of REM sleep without atonia, a prodromal biomarker for synucleinopathy-related neurodegenerative disorders, is influenced by selective serotonin reuptake inhibitor (SSRI) or serotonin-norepinephrine retake inhibitor (SNRI) use. This study investigates whether SSRI/SNRIs similarly impacts the severity of Non-REM hypertonia (NRH), a biomarker independently associated with patients broadly characterized with presumed Parkinsonian-spectrum disorders (PSD). Methods In this multi-center study, the relationship between NRH and SSRI/SNRIs was evaluated in PSD patients [Lewy Body/Parkinson Disease Dementia (DLB/PDD=16), Parkinson Disease (PD=16), isolated REM sleep behavior disorder (iRBD=19), and progressive supranuclear palsy (PSP=12)], and non-PSD subjects [Alzheimer Disease (AD=22), mild cognitive impairment (MCI=35), and normal cognition (NC=61)]. Studies were conducted with the Sleep Profiler in all participants. NRH was auto-detected based on persistently elevated electromyographic (EMG) power relative to delta, theta, and sigma bands. Abnormal-NRH was based on a threshold of >5% of sleep time, and weight-averaged by sleep time, in the 75% of studies with two-nights of data. Statistical analyses included multiple logistic regression, Fisher Exact, and Mann-Whitney U tests. Results Across all 181 records, 38% had abnormal-NRH and 24% used SSRI/SNRIs (P<0.005). No differences were observed in the distributions of NRH for those with NRH-only vs. those with combined NRH and SSRI/SNRI use (n=45, 14.5+/-7.7% versus n=24, 18.6+/-11.6%, respectively; P=0.19). Abnormal-NRH was associated with the PSD versus non-PSD groups (P<0.0001, odds-ratio=14.0) and SSRI/SNRI use (P<0.05, odds-ratio=2.4), but not age and sex. Within the PSD and non-PSD groups, the frequency of abnormal-NRH was 75% vs. 19% (P<0.0001), and SSRI/SNRI use was 32% vs. 19% (P=0.07), respectively. The distributions of abnormal-NRH in the PSD and non-PSD subgroups ranged from PSP=92%, DLB/PDD=81%, PD=56% ,and RBD=74% versus MCI=26%, and NC=16%, AD=14%, respectively. By comparison, distributions of SSRI/SNRI use were DLB/PDD=50%, RBD=42%, PSP=33%, and PD=0% in the PSD subgroups, compared to MCI=34%, AD=23%, and NC=10% in the non-PSD subgroups. Conclusion Abnormal non-REM hypertonia exhibited a very strong association with Parkinsonian-spectrum disorder diagnoses (odds-ratio=14.0) and a relatively weaker association with selective serotonin reuptake inhibitor or serotonin-norepinephrine retake inhibitor use (odds-ratio=2.4), suggesting a finding that reflects an interactive, rather than causal inference. Support (If Any) NIA grants R44AG050326, R44AG054256, P30AG62677 and R34AG56639.