Hamilton, Joanne M.

Abstract Background Healthy aging and cognitive decline in Alzheimer's Disease (AD) and its precursor, Mild Cognitive Impairment (MCI), are linked to changes in resting‐state EEG power spectral density (PSD). Theta band (3‐7 Hz) power decreases with normal aging but increases with cognitive decline. However, frequency content does not always indicate true oscillatory activity. Oscillations reflect power concentration at a specific frequency, appearing as peaks in the frequency domain and visible rhythms in the time domain. Rhythmicity analysis quantifies oscillation persistence (percentage of time observed) independently of power. This study examined Theta power and Theta rhythms in healthy controls (HC) versus individuals with MCI/AD. Method Participants included 32 AD, 88 MCI, and 115 and age‐ matched HC, who completed 5‐minutes of resting‐state eyes‐closed EEG at their baseline visit. PSD was computed for one‐second epochs. Relative Theta power was defined as the proportion of total power in the Theta band, averaging across epochs. Theta rhythm duration was defined as the percentage of epochs with Theta oscillations. Baseline differences and longitudinal changes were analyzed for a subset of participants: 28 MCI and 5 AD with at least one follow‐up visit, and 25 HC with at least two follow‐ups. Result At baseline, the MCI/AD group exhibited significantly higher relative Theta power ( p <0.01, df=233, ES=0.35 at T6) and a greater Theta rhythm duration ( p <0.01, df=231, ES=0.41 at T6) compared to HC. Longitudinally, HC exhibited a significant reduction in Theta power by the second follow‐up ( p <0.05, df=24, ES=0.51 at Cz), with no significant changes in Theta rhythms duration. In contrast, MCI/AD showed a significant increase in Theta rhythm duration (and not power) at first follow‐up visit ( p < 0.05, df =32, ES=0.30 at T3). Conclusion Theta power and Theta rhythm duration are both linked to cognitive decline in MCI and AD but differ from healthy aging patterns. While Theta power reflects age‐related changes, Theta rhythms duration may serve as a specific biomarker for disease progression in MCI and AD. These findings support the value of Rhythmicity analysis in EEG‐based biomarkers of cognitive decline.

AbstractBackgroundEEG slowing, a biomarker of cognitive decline in Alzheimer’s disease (AD), has been reported in wake or sleep EEG [1,2,3]. However, the relation between wake and sleep EEG and their comparative sensitivity to early stage of cognitive decline is less understood. In this study we compared sleep and wake EEG biomarkers using a common set of endpoints.MethodsParticipants included individuals with mild cognitive impairment (MCI, n = 30, ages 53‐88), Alzheimer’s disease dementia (ADem, n = 15, ages 60‐84), and controls with normal cognition (HC, n = 55, ages 50‐84). Twenty‐channel resting‐state EEG with eyes‐closed was collected during 5‐minutes of wakefulness (STAT X24). Sleep EEG recordings from AF7‐AF8 were collected in‐home and staged using Sleep ProfilerTM. Power spectral densities (PSD) and the derived Theta‐Alpha ratios were computed for wake EEG sites (counterpart bipolar montage), with the wake FP1‐FP2 compared by stage to the sleep EEG at AF7‐AF8. Significant differences in Theta‐Alpha ratios between MCI or ADem vs. HC groups were identified using independent t‐test (p<0.05) with the normalized effect size measured using Hedges‐g (E.S.).ResultsCorrelation coefficients between wake Alpha, Theta power and non‐REM sleep were: r = 0.83, 0.75 for stage N1, r = 0.71, 0.66 for stage N2, and r = 0.55, 0.50 for stage N3. Based on the frontal Theta‐Alpha ratios, the ADem group showed significant EEG slowing during both wake (E.S. = 0.73) and sleep (E.S. = 1.65, 1.31, 0.61, 1.71 for N1, N2, N3, and REM) as compared to the HC, while MCI group only exhibited EEG slowing during sleep (E.S. = 0.56, 0.77, 0.51 for N1, N2 and REM). Temporal (T5‐T6) wake EEG manifested significant slowing in both ADem (E.S. = 1.21) and MCI (E.S. = 0.56) groups. Compared to the HC, ADem patients exhibited significantly less sleep time (E.S. = 0.91, p = 0.002) and less stage REM (E.S. = 1.0, p = 0.001).ConclusionsCognitive decline in the AD spectrum is associated with common signatures in both sleep and wake EEG. However, the magnitude of these effects and their spatial distribution may be different in sleep versus wakefulness. These findings support a multi modal approach to neurophysiological assessment using both sleep and wakefulness data.

AbstractBackgroundEvent‐related‐potentials (ERPs) during cognitive tasks are sensitive measures of cognitive decline [1]‐[2] and could quantitatively measure the trajectory of disease progression or response to clinical interventions. In this longitudinal study, we aimed to compare ERPs between individuals with mild cognitive impairment (MCI) and controls, and to demonstrate the test‐retest reliability of ERP measures to assess their potential utility for future observational studies and treatment trials.MethodsParticipants included individuals with mild cognitive impairment (MCI, n=31) and healthy controls stratified by age: HC2 (n=46, 40‐60 yrs.), HC3 (n=56, 60‐90 yrs.). ERPs during attention, image recognition, and verbal memory tasks were recorded using a wireless EEG to determine amplitudes and latencies of the P200 and late positive potential (LPP) ERP components in response to target (memorized) and non‐target (novel) stimuli. Differences between MCI and HC3 groups were characterized at the initial visit, and longitudinal changes in ERP components were determined at 1‐year follow‐up for both groups. Reliability of ERP measures was demonstrated by computing intraclass correlation coefficient (ICC) measures of test‐retest variability in all healthy controls (HC2 and HC3) from initial visit to 1‐year follow‐up.ResultsAt the initial visit, the MCI group demonstrated reduced LPP amplitude (Hedges‐g=0.8, p=10‐3) and delayed P200‐latency (Hedges‐g=0.89, p=10‐4) when compared to HC3. Reliability in healthy controls was high for LPP (0.85 and 0.75 for target and non‐target stimuli, respectively) and moderate for P200‐latency (0.67 and 0.53 for target and non‐target stimuli, respectively), without longitudinal changes after 1‐year follow‐up. Individuals with MCI demonstrated increased P200‐latency (Hedges‐g= 1.05, p=0.02, df=8).ConclusionsIndividuals with MCI demonstrated quantifiable memory ERP deficits at baseline with detectable change in the P200 component at 1‐year follow‐up, demonstrating that ERPs are sensitive measures for quantifying mild cognitive impairment. Test‐retest reliability of these measures was good or moderate after 1‐year, supporting their feasibility for longitudinal monitoring of patients during disease progression or quantifying the cognitive impact of potential interventions.

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 &gt;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&lt;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&lt;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&lt;0.0001) and PD=56% (P&lt;0.05), but not DLB/PDD=81% and iRBD=74%. Abnormal-NRH was significantly associated with the PSD group (P&lt;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 Increased non-REM hypertonia (NRH) and decreased sleep spindle-durations were found to be independently associated with patients broadly characterized as presumed Parkinsonian-spectrum disorder [i.e., dementia with Lewy Bodies/Parkinson Disease Dementia (DLB/PDD), Parkinson Disease (PD), progressive supranuclear palsy (PSP), or isolated REM sleep behavior disorder (iRBD)] when compared to subjects with Alzheimer Disease dementia (AD), mild cognitive impairment (MCI) and normal cognition (NC). In this investigation, the NRH and spindle-duration features were combined to determine whether these biomarkers could distinguish neurodegenerative disorder subtypes. Methods This multicenter investigation included analysis of several neurodegenerative disorder patient subtypes including: DLB/PDD (n=16), PD (n=16), iRBD (n=19), PSP (n=13), AD (n=22), MCI (n=35), and NC (n=61). Sleep Profiler (SP) studies were conducted in all participants. NRH was auto-detected based on persistently elevated electromyographic (EMG) power relative to delta, theta, and sigma bands, while spindles were recognized by temporal excursions in alpha and sigma power &gt; 250-milliseconds. With NRH &gt;5% of sleep-time and spindle-duration &lt;1-minute considered abnormal, tallies were compared across neurodegenerative disorder subtypes with Fisher Exact tests. Results Combined SP features of Normal-NRH/normal-SpD were greater in the NC (56%), AD (46%), and MCI (43%) subtypes versus PSP (8%) and DLB/PDD (6%), and when iRBD (21%) was compared to NC (all P&lt;0.05). Abnormal-NRH/abnormal-SpD were more frequent in PSP (85%) and DLB/PDD (75%) subtypes versus iRBD (26%), PD (25%), MCI (11%), AD (9%), and NC (8%)(all P&lt;0.02). Abnormal-NRH/normal-SpD were greater in iRBD (47%) compared to MCI (14%), NC (8%), PSP (8%), DLB/PDD (6%), and AD (5%) subtypes, and in PD (31%) versus NC (all P&lt;0.05). Normal-NRH/abnormal-SpD occurred more often in AD (41%) than iRBD (5%) and PSP (0%)(both P&lt;0.05). Conclusion The combination of NRH and spindle-duration abnormality occurred more frequently in DLB/PDD and PSP subtypes. Abnormal NRH with normal sleep-duration was more frequent in iRBD and PD subtypes. Normal NRH and spindle-duration occurred most often in NC and MCI types. AD exhibited normal NRH with isolated cases of either normal or abnormal spindle-duration. Our preliminary findings suggest that auto-detected sleep biomarkers may aid in the characterization of neurodegenerative disorder subtypes. Larger prospective cohort studies are needed. 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&lt;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&lt;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&lt;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 &gt;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&lt;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&lt;0.0001, odds-ratio=14.0) and SSRI/SNRI use (P&lt;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&lt;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.

AbstractBackgroundNeurodegenerative disease (NDD) is associated with sleep disturbances, including decreased stage N3 and REM sleep and reduced spindle activity. Further, supine sleep position may impact NDD risk by altering glymphatic clearance. This study evaluated conventional and exploratory sleep metrics in the differentiation of subjects with normal cognition (NC) and patients with Alzheimer’s disease dementia (AD) and alpha‐synucleinopathies (α‐Syn).MethodHome sleep data were acquired across multiple study sites using the self‐applied Sleep ProfilerTM, including 44 NC subjects (age=69+5.0), 22 patients diagnosed with AD (age=75+7.1) and 25 with α‐Syn (Parkinson’s disease=14, Parkinson’s disease with Dementia or Dementia with Lewy Bodies=11; age=69+6.9). Recordings were auto‐staged and technically reviewed, with 86% of the records having two‐night averages. Logistic regression and Mann‐Whitney U tests were used to characterize group differences based on age, conventional sleep metrics (i.e., sleep efficiency, sleep onset (SO), awakenings, percent of sleep time (%) in REM,N1, N2 and N3, and sleep spindles) and exploratory sleep measures [i.e., % supine, % Light N2 (L2=N2 epochs absent of spindles with K‐complexes and/or alpha or EMG (>40 Hz) intrusion), % NREM sleep with hypertonia (NRSH=>4 consecutive epochs with persistently elevated EMG power relative to delta and theta power) and % atypical N3 (AN3=epochs staged N3 with low theta and sigma power relative to delta, alpha, beta and EMG)].ResultAD were older than both NC and α‐Syn patients (p<0.005). Both AD and α‐Syn had lower %REM and greater %supine than NC (p<0.005), and %NRSH was greater in α‐Syn than NC or AD (p<0.005). Based on logistic regression, AD was differentiated from NC based on age, %REM, %L2 (p<0.05) and %supine (p=0.06). α‐Syn was distinguished from NC using both conventional (%N3 and SO, p<0.05) and exploratory sleep metric (%AN3 and %NRSH, p<0.05; %supine, p=0.06). Age (p=0.05) and %NRSH (p<0.01) were the only metrics that differentiated α‐Syn from AD.ConclusionObjective home sleep profiles hold promise for differentiating NDD patients from NC. The sleep metrics that provided the greatest distinction between NDD and NC were %REM, %supine and NRSH, while only NRSH distinguished AD from α‐Syn patients. Further confirmatory studies are underway.