The potential role of chronic pain and the polytrauma clinical triad in predicting prodromal PD: A cross-sectional study of U.S. Veterans

Introduction

The research criteria for prodromal Parkinson disease (pPD) depends on prospectively validated clinical inputs with large effect sizes and/or high prevalence. Neither traumatic brain injury (TBI), post-traumatic stress disorder (PTSD), nor chronic pain are currently included in the calculator, despite recent evidence of association with pPD. These conditions are widely prevalent, co-occurring, and already known to confer risk of REM behavior disorder (RBD) and PD. Few studies have examined PD risk in the context of TBI and PTSD; none have examined chronic pain. This study aimed to measure the risk of pPD caused by TBI, PTSD, and chronic pain.

Methods

216 US Veterans were enrolled who had self-reported recurrent or persistent pain for at least three months. Of these, 44 met criteria for PTSD, 39 for TBI, and 41 for all three conditions. Several pain, sleep, affective, and trauma questionnaires were administered. Participants' history of RBD was determined via self-report, with a subset undergoing confirmatory video polysomnography.

Results

A greater proportion of Veterans with chronic pain met criteria for RBD (36 % vs. 10 %) and pPD (18.0 % vs. 8.3 %) compared to controls. Proportions were increased in RBD (70 %) and pPD (27 %) when chronic pain co-occurred with TBI and PTSD. Partial effects were seen with just TBI or PTSD alone. When analyzed as continuous variables, polytrauma symptom severity correlated with pPD probability (r = 0.28, P = 0.03).

Conclusion

These data demonstrate the potential utility of chronic pain, TBI, and PTSD in the prediction of pPD, and the importance of trauma-related factors in the pathogenesis of PD.

Head Injury Treatment With Healthy and Advanced Dietary Supplements: A Pilot Randomized Controlled Trial of the Tolerability, Safety, and Efficacy of Branched Chain Amino Acids in the Treatment of Concussion in Adolescents and Young Adults

Concussion is a common injury in the adolescent and young adult populations. Although branched chain amino acid (BCAA) supplementation has shown improvements in neurocognitive and sleep function in pre-clinical animal models of mild-to-moderate traumatic brain injury (TBI), to date, no studies have been performed evaluating the efficacy of BCAAs in concussed adolescents and young adults. The goal of this pilot trial was to determine the efficacy, tolerability, and safety of varied doses of oral BCAA supplementation in a group of concussed adolescents and young adults. The study was conducted as a pilot, double-blind, randomized controlled trial of participants ages 11-34 presenting with concussion to outpatient clinics (sports medicine and primary care), urgent care, and emergency departments of a tertiary care pediatric children's hospital and an urban tertiary care adult hospital, between June 24, 2014 and December 5, 2020. Participants were randomized to one of five study arms (placebo and 15 g, 30 g, 45 g, and 54 g BCAA treatment daily) and followed for 21 days after enrollment. Outcome measures included daily computerized neurocognitive tests (processing speed, the a priori primary outcome; and attention, visual learning, and working memory), symptom score, physical and cognitive activity, sleep/wake alterations, treatment compliance, and adverse events. In total, 42 participants were randomized, 38 of whom provided analyzable data. We found no difference in our primary outcome of processing speed between the arms; however, there was a significant reduction in total symptom score (decrease of 4.4 points on a 0-54 scale for every 500 g of study drug consumed, p value for trend = 0.0036, [uncorrected]) and return to physical activity (increase of 0.503 points on a 0-5 scale for every 500 g of study drug consumed, p value for trend = 0.005 [uncorrected]). There were no serious adverse events. Eight of 38 participants reported a mild (not interfering with daily activity) or moderate (limitation of daily activity) adverse event; there were no differences in adverse events by arm, with only two reported mild adverse events (both gastrointestinal) in the highest (45 g and 54 g) BCAA arms. Although limited by slow enrollment, small sample size, and missing data, this study provides the first demonstration of efficacy, as well as safety and tolerability, of BCAAs in concussed adolescents and young adults; specifically, a dose-response effect in reducing concussion symptoms and a return to baseline physical activity in those treated with higher total doses of BCAAs. These findings provide important preliminary data to inform a larger trial of BCAA therapy to expedite concussion recovery.

Validation of the RBD Symptom Severity Scale in the North American Prodromal Synucleinopathy Consortium

BACKGROUND AND OBJECTIVES

REM sleep behavior disorder (RBD) is a parasomnia characterized by dream enactment. The International RBD Study Group developed the RBD Symptom Severity Scale (RBDSSS) to assess symptom severity for clinical or research use. We assessed the psychometric and clinimetric properties of the RBDSSS in participants enrolled in the North American Prodromal Synucleinopathy (NAPS) Consortium for RBD.

METHODS

NAPS participants, who have polysomnogram-confirmed RBD, and their bedpartners completed the RBDSSS (participant and bedpartner versions). The RBDSSS contains 8 questions to assess the frequency and severity/impact of (1) dream content, (2) vocalizations, (3) movements, and (4) injuries associated with RBD. Total scores for participant (maximum score = 54) and bedpartner (maximum score = 38) questionnaires were derived by multiplying frequency and severity scores for each question. The Clinical Global Impression Scale of Severity (CGI-S) and RBD symptom frequency were assessed by a physician during a semistructured clinical interview with participants and, if available, bedpartners. Descriptive analyses, correlations between overall scores, and subitems were assessed, and item response analysis was performed to determine the scale's validity.

RESULTS

Among 261 study participants, the median (interquartile range) score for the RBDSSS-PT (participant) was 10 (4-18) and that for the RBDSSS-BP (bedpartner) was 8 (4-15). The median CGI-S was 3 (3-4), indicating moderate severity. RBDSSS-BP scores were significantly lower in women with RBD (6 vs 9, p = 0.02), while there were no sex differences in RBDSSS-PT scores (8 vs 10.5, p = 0.615). Positive correlations were found between RBDSSS-PT vs RBDSSS-BP (Spearman rs = 0.561), RBDSSS-PT vs CGI-S (rs = 0.556), and RBDSSS-BP vs CGI-S (rs = 0.491, all p < 0.0001). Item response analysis showed a high discriminatory value (range 1.40-2.12) for the RBDSSS-PT and RBDSSS-BP (1.29-3.47).

DISCUSSION

We describe the RBDSSS with adequate psychometric and clinimetric properties to quantify RBD symptom severity and good concordance between participant and bedpartner questionnaires and between RBDSSS scores and clinician-assessed global severity.

A case of prazosin in treatment of rapid eye movement sleep behavior disorder

Rapid eye movement (REM) sleep behavior disorder (RBD) is characterized by dream-enactment behaviors that emerge during a loss of REM sleep atonia. Untreated RBD carries risks for physical injury from falls or other traumatic events during dream enactment as well as risk of injury to the bed partner. Currently, melatonin and clonazepam are the mainstay pharmacological therapies for RBD. However, therapeutic response to these medications is variable. While older adults are most vulnerable to RBD, they are also particularly vulnerable to the adverse effects of benzodiazepines, including increased risk of falls, cognitive impairment, and increased risk of Alzheimer disease. Prazosin is a centrally active alpha-1 adrenergic receptor antagonist often prescribed for trauma nightmares characterized by REM sleep without atonia in patients with posttraumatic stress disorder. We report a case of successful RBD management with prazosin in a patient in whom high-dose melatonin was ineffective. Although there was no observable reduction in dream-enactment behaviors with high-dose melatonin, the possibility of a synergistic effect of prazosin combined with melatonin cannot be ruled out. This case report supports further evaluation of prazosin as a potential therapeutic for RBD.

CITATION

Cho Y, Iliff JJ, Lim MM, Raskind M, Peskind E. A case of prazosin in treatment of rapid eye movement sleep behavior disorder. J Clin Sleep Med. 2024;20(2):319-321.

Perivascular Space Burden and Cerebrospinal Fluid Biomarkers in US Veterans With Blast-Related Mild Traumatic Brain Injury

Blast-related mild traumatic brain injury (mTBI) is recognized as the "signature injury" of the Iraq and Afghanistan wars. Sleep disruption, mTBI, and neuroinflammation have been individually linked to cerebral perivascular space (PVS) dilatation. Dilated PVSs are putative markers of impaired cerebrospinal fluid (CSF) and interstitial fluid exchange, which plays an important role in removing cerebral waste. The aim of this cross-sectional, retrospective study was to define associations between biomarkers of inflammation and MRI-visible PVS (MV-PVS) burden in Veterans after blast-related mTBI (blast-mTBI) and controls. The CSF and plasma inflammatory biomarker concentrations were compared between blast-mTBI and control groups and correlated with MV-PVS volume and number per white matter cm3. Multiple regression analyses were performed with inflammatory biomarkers as predictors and MV-PVS burden as the outcome. Correction for multiple comparisons was performed using the Banjamini-Hochberg method with a false discovery rate of 0.05. There were no group-wise differences in MV-PVS burden between Veterans with blast-mTBI and controls. Greater MV-PVS burden was significantly associated with higher concentrations of several proinflammatory biomarkers from CSF (i.e., eotaxin, MCP-1, IL-6, IL-8) and plasma (i.e., MCP-4, IL-13) in the blast-mTBI group only. After controlling for sleep time and symptoms of post-traumatic stress disorder, temporal MV-PVS burden remained significantly associated with higher CSF markers of inflammation in the blast-mTBI group only. These data support an association between central, rather than peripheral, neuroinflammation and MV-PVS burden in Veterans with blast-mTBI independent of sleep. Future studies should continue to explore the role of blast-mTBI related central inflammation in MV-PVS development, as well as investigate the impact of subclinical exposures on MV-PVS burden.

Comorbid neurotrauma increases neurodegenerative-relevant cognitive, motor, and autonomic dysfunction in patients with REM sleep behavior disorder: A substudy of the North American Prodromal Synucleinopathy Consortium

STUDY OBJECTIVES

Rapid eye movement (REM) sleep behavior disorder (RBD) is strongly associated with phenoconversion to an overt synucleinopathy, e.g., Parkinson's disease (PD), Lewy Body Dementia (LBD), and related disorders. Comorbid traumatic brain injury (TBI) and posttraumatic stress disorder (PTSD) - henceforth "neurotrauma" (NT) - increase the odds of RBD by ~2.5-fold and is associated with an increased rate of service-connected PD in Veterans. Thus, RBD and NT are both independently associated with PD; however, it is unclear how NT influences neurological function in patients with RBD.

METHODS

Participants ≥18 years with overnight-polysomnogram-confirmed RBD were enrolled between 8/2018 to 4/2021 through the North American Prodromal Synucleinopathy (NAPS) Consortium. Standardized assessments for RBD, TBI, and PTSD history, as well as cognitive, motor, sensory and autonomic function were completed. This cross-sectional analysis compared cases (n=24; RBD+NT) to controls (n=96; RBD), matched for age (~60 years), sex (15% female), and years of education (~15 years).

RESULTS

RBD+NT reported earlier RBD symptom onset (37.5±11.9 vs. 52.2±15.1 years of age) and a more severe RBD phenotype. Similarly, RBD+NT reported more severe anxiety and depression, greater frequency of hypertension, and significantly worse cognitive, motor, and autonomic function compared to RBD. No differences in olfaction or color vision were observed.

CONCLUSION

This cross-sectional, matched case:control study shows individuals with RBD+NT have significantly worse neurological measures related to common features of an overt synucleinopathy. Confirmatory longitudinal studies are ongoing; however, these results suggest RBD+NT may be associated with more advanced neurological symptoms related to an evolving neurodegenerative process.

SEX-SPECIFIC IMPACTS OF EARLY LIFE SLEEP DISRUPTION: ETHANOL SEEKING, SOCIAL INTERACTION, AND ANXIETY ARE DIFFERENTIALLY ALTERED IN ADOLESCENT PRAIRIE VOLES

Early life sleep is important for neuronal development and maturation. Using the highly social prairie vole rodent model, we have previously reported that early-life sleep disruption (ELSD) during the pre-weaning period postnatal day (P)14 to 21 results in adult interference with social bonding and increases ethanol consumption following a stressor. Furthermore, we have reported increased parvalbumin expression and reduced glutamatergic neurotransmission in cortical regions in adult prairie voles that experienced this paradigm. To understand the impact of ELSD on the lifespan, examination of an earlier time in life is necessary. Thus, the aim of the present study was to examine the behavioral outcomes of ELSD on adolescent prairie voles. Here we hypothesized that anxiety and reward related behaviors, as measured by light/dark box, 2-bottle choice and social interactions, would be negatively impacted by ELSD in adolescent male and female prairie voles. Male ELSD voles were no different from control voles in measures of anxiety and ethanol preference or consumption, but affiliative social interactions were significantly reduced. ELSD differentially impacted female prairie voles, with increased anxiety-like behavior and reductions in ethanol consumption compared to Controls, but no impact on ethanol preference or social interactions. Together, these results suggest both male and female prairie voles experience differential changes to reward seeking behaviors, but only female prairie voles showed increases in anxiety-like behavior. These results further suggest that early-life sleep is critically important for neurotypical behaviors in adolescence, a time where reward-seeking and risky behaviors are adaptive for learning and promoting survival.

Frequency of Orthostatic Hypotension in Isolated REM Sleep Behavior Disorder

BACKGROUND AND OBJECTIVES

Although orthostatic hypotension (OH) can be an early feature of autonomic dysfunction in isolated REM sleep behavior disorder (iRBD), no large-scale studies have examined the frequency of OH in iRBD. In this study, we prospectively evaluated the frequency of OH in a large multicenter iRBD cohort.

METHODS

Participants 18 years or older with video polysomnogram-confirmed iRBD were enrolled through the North American Prodromal Synucleinopathy consortium. All participants underwent 3-minute orthostatic stand testing to assess the frequency of OH, and a Δ heart rate/Δ systolic blood pressure (ΔHR/ΔSBP) ratio <0.5 was used to define reduced HR augmentation, suggestive of neurogenic OH. All participants completed a battery of assessments, including the Scales for Outcomes in Parkinson Disease-Autonomic Dysfunction (SCOPA-AUT) and others assessing cognitive, motor, psychiatric, and sensory domains.

RESULTS

Of 340 iRBD participants (65 ± 10 years, 82% male), 93 (27%) met criteria for OH (ΔHR/ΔSBP 0.37 ± 0.28; range 0.0-1.57), and of these, 72 (77%) met criteria for OH with reduced HR augmentation (ΔHR/ΔSBP 0.28 ± 0.21; range 0.0-0.5). Supine hypertension (sHTN) was present in 72% of those with OH. Compared with iRBD participants without OH, those with OH were older, reported older age of RBD symptom onset, and had worse olfaction. There was no difference in autonomic symptom scores as measured by SCOPA-AUT.

DISCUSSION

OH and sHTN are common in iRBD. However, as patients may have reduced autonomic symptom awareness, orthostatic stand testing should be considered in clinical evaluations. Longitudinal studies are needed to clarify the relationship between OH and phenoconversion risk in iRBD.

TRIAL REGISTRATION INFORMATION

ClinicalTrials.gov: NCT03623672; North American Prodromal Synucleinopathy Consortium.

Longitudinal Sleep Patterns and Cognitive Impairment in Older Adults

Importance

Sleep disturbances and clinical sleep disorders are associated with all-cause dementia and neurodegenerative conditions, but it remains unclear how longitudinal changes in sleep impact the incidence of cognitive impairment.

Objective

To evaluate the association of longitudinal sleep patterns with age-related changes in cognitive function in healthy older adults.

Design, Setting, and Participants

This cross-sectional study is a retrospective longitudinal analyses of the Seattle Longitudinal Study (SLS), which evaluated self-reported sleep duration (1993-2012) and cognitive performance (1997-2020) in older adults. Participants within the SLS were enrolled as part of a community-based cohort from the Group Health Cooperative of Puget Sound and Health Maintenance Organization of Washington between 1956 and 2020. Data analysis was performed from September 2020 to May 2023.

Main Outcomes and Measures

The main outcome for this study was cognitive impairment, as defined by subthreshold performance on both the Mini-Mental State Examination and the Mattis Dementia Rating Scale. Sleep duration was defined by self-report of median nightly sleep duration over the last week and was assessed longitudinally over multiple time points. Median sleep duration, sleep phenotype (short sleep, median ≤7 hours; medium sleep, median = 7 hour; long sleep, median ≥7 hours), change in sleep duration (slope), and variability in sleep duration (SD of median sleep duration, or sleep variability) were evaluated.

Results

Of the participants enrolled in SLS, only 1104 participants who were administered both the Health Behavior Questionnaire and the neuropsychologic battery were included for analysis in this study. A total of 826 individuals (mean [SD] age, 76.3 [11.8] years; 468 women [56.7%]; 217 apolipoprotein E ε4 allele carriers [26.3%]) had complete demographic information and were included in the study. Analysis using a Cox proportional hazard regression model (concordance, 0.76) showed that status as a short sleeper (hazard ratio, 3.67; 95% CI, 1.59-8.50) and higher sleep variability (hazard ratio, 3.06; 95% CI, 1.14-5.49) were significantly associated with the incidence of cognitive impairment.

Conclusions and Relevance

In this community-based longitudinal study of the association between sleep patterns and cognitive performance, the short sleep phenotype was significantly associated with impaired cognitive performance. Furthermore, high sleep variability in longitudinal sleep duration was significantly associated with the incidence of cognitive impairment, highlighting the possibility that instability in sleep duration over long periods of time may impact cognitive decline in older adults.

Instability in longitudinal sleep duration predicts cognitive impairment in aged participants of the Seattle Longitudinal Study

Importance

Sleep disturbances and clinical sleep disorders are associated with all-cause dementia and neurodegenerative conditions. It remains unclear how longitudinal changes in sleep impact the incidence of cognitive impairment.

Objective

To evaluate how longitudinal sleep patterns contribute to age-related changes in cognitive function in healthy adults.

Design Setting Participants

This study utilizes retrospective longitudinal analyses of a community-based study within Seattle, evaluating self-reported sleep (1993-2012) and cognitive performance (1997-2020) in aged adults.

Main Outcomes and Measures

The main outcome is cognitive impairment as defined by sub-threshold performance on 2 of 4 neuropsychological batteries: Mini-Mental State Examination (MMSE), Mattis Dementia Rating Scale, Trail Making Test, and Wechsler Adult Intelligent Scale (Revised). Sleep duration was defined through self-report of 'average nightly sleep duration over the last week' and assessed longitudinally. Median sleep duration, change in sleep duration (slope), variability in sleep duration (standard deviation, Sleep Variability), and sleep phenotype ("Short Sleep" median ≤7hrs.; "Medium Sleep" median = 7hrs; "Long Sleep" median ≥7hrs.).

Results

A total of 822 individuals (mean age of 76.2 years [11.8]; 466 women [56.7%]; 216 APOE allele positive [26.3%]) were included in the study. Analysis using a Cox Proportional Hazard Regression model (concordance 0.70) showed that increased Sleep Variability (95% CI [1.27,3.86]) was significantly associated with the incidence of cognitive impairment. Further analysis using linear regression prediction analysis (R2=0.201, F (10, 168)=6.010, p=2.67E-07) showed that high Sleep Variability (β=0.3491; p=0.048) was a significant predictor of cognitive impairment over a 10-year period.

Conclusions and Relevance

High variability in longitudinal sleep duration was significantly associated with the incidence of cognitive impairment and predictive of decline in cognitive performance ten years later. These data highlight that instability in longitudinal sleep duration may contribute to age-related cognitive decline.

Lifelong Association of Disorders Related to Military Trauma with Subsequent Parkinson's Disease

BACKGROUND

Trauma-related disorders such as traumatic brain injury (TBI) and posttraumatic stress disorder (PTSD) are emerging as risk factors for Parkinson's disease (PD), but their association with development of PD and independence from comorbid disorders remains unknown.

OBJECTIVE

To examine TBI and PTSD related to early trauma in military veterans using a case-control study.

METHODS

PD was identified by International Classification of Diseases (ICD) code, recurrent PD-specific prescriptions, and availability of 5+ years of earlier records. Validation was performed by chart review by a movement disorder-trained neurologist. Control subjects were matched 4:1 by age, duration of preceding health care, race, ethnicity, birth year, and sex. TBI and PTSD were identified by ICD code and onset based on active duty. Association and interaction were measured for TBI and PTSD with PD going back 60 years. Interaction was measured for comorbid disorders.

RESULTS

A total of 71,933 cases and 287,732 controls were identified. TBI and PTSD increased odds of subsequent PD at all preceding 5-year intervals back to year -60 (odds ratio range: 1.5 [1.4, 1.7] to 2.1 [2.0, 2.1]). TBI and PTSD showed synergism (synergy index range: 1.14 [1.09, 1.29] to 1.28 [1.09, 1.51]) and additive association (odds ratio range: 2.2 [1.6, 2.8] to 2.7 [2.5, 2.8]). Chronic pain and migraine showed greatest synergy with PTSD and TBI. Effect sizes for trauma-related disorders were comparable with established prodromal disorders.

CONCLUSIONS

TBI and PTSD are associated with later PD and are synergistic with chronic pain and migraine. These findings provide evidence for TBI and PTSD as risk factors preceding PD by decades and could aid in prognostic calculation and earlier intervention. © 2023 International Parkinson and Movement Disorder Society. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.

Screening and Targeting Risk Factors for Prodromal Synucleinopathy: Taking Steps toward a Prescriptive Multi-modal Framework

As the prevalence of Parkinson's disease (PD) grows, so too does the population at-risk of developing PD, those in the so-called prodromal period. This period can span from those experiencing subtle motor deficits yet not meeting full diagnostic criteria or those with physiologic markers of disease alone. Several disease-modifying therapies have failed to show a neuroprotective effect. A common criticism is that neurodegeneration, even in the early motor stages, has advanced too far for neuro-restoration-based interventions to be effective. Therefore, identifying this early population is essential. Once identified, these patients could then potentially benefit from sweeping lifestyle modifications to alter their disease trajectory. Herein, we review the literature on risk factors for, and prodromal symptoms of, PD with an emphasis on ones which may be modifiable in the earliest possible stages. We propose a process for identifying this population and speculate on some strategies which may modulate disease trajectory. Ultimately, this proposal warrants prospective studies.

Early-life sleep disruption impairs subtle social behaviours in prairie voles: a pose-estimation study

Early-life sleep disruption (ELSD) has been shown to have long-lasting effects on social behaviour in adult prairie voles (Microtus ochrogaster), including impaired expression of pair bonding during partner preference testing. However, due to the limitations of manual behaviour tracking, the effects of ELSD across the time course of pair bonding have not yet been described, hindering our ability to trace mechanisms. Here, we used pose estimation to track prairie voles during opposite-sex cohabitation, the process leading to pair bonding. Male-female pairs were allowed to interact through a mesh divider in the home cage for 72 h, providing variables of body direction, distance-to-divider and locomotion speed. We found that control males displayed periodic patterns of body orientation towards females during cohabitation. In contrast, ELSD males showed reduced duration and ultradian periodicity of these body orientation behaviours towards females. Furthermore, in both sexes, ELSD altered spatial and temporal patterns of locomotion across the light/dark cycles of the 72 h recordings. This study allows a comprehensive behavioural assessment of the effects of ELSD on later life sociality and highlights subtle prairie vole behaviours. Our findings may shed light on neurodevelopmental disorders featuring sleep disruption and social deficits, such as autism spectrum disorders.

The temporal structure of REM sleep shows minute-scale fluctuations across brain and body in mice and humans

Rapid eye movement sleep (REM) is believed to have a binary temporal structure with "phasic" and "tonic" microstates, characterized by motoric activity versus quiescence, respectively. However, we observed in mice that the frequency of theta activity (a marker of rodent REM) fluctuates in a nonbinary fashion, with the extremes of that fluctuation correlating with phasic-type and tonic-type facial motricity. Thus, phasic and tonic REM may instead represent ends of a continuum. These cycles of brain physiology and facial movement occurred at 0.01 to 0.06 Hz, or infraslow frequencies, and affected cross-frequency coupling and neuronal activity in the neocortex, suggesting network functional impact. We then analyzed human data and observed that humans also demonstrate nonbinary phasic/tonic microstates, with continuous 0.01 to 0.04-Hz respiratory rate cycles matching the incidence of eye movements. These fundamental properties of REM can yield insights into our understanding of sleep health.

Early life sleep disruption has long lasting, sex specific effects on later development of sleep in prairie voles

In mammals, sleep duration is highest in the early postnatal period of life and is critical for shaping neural circuits that control the development of complex behaviors. The prairie vole is a wild, highly social rodent that serves as a unique model for the study of complex, species-typical social behaviors. Previous work in our laboratory has found that early life sleep disruption (ELSD) in prairie voles during a sensitive window of postnatal development leads to long lasting changes in social and cognitive behaviors as well as structural changes in excitatory and inhibitory neural circuits in the brain. However, it is currently unknown how later sleep is impacted by ELSD, both shortly after ELSD and over the long term. Therefore, the aim of this study was to describe the effects of ELSD on later life sleep, compared to sleep in normally developing prairie voles. First, we conducted tethered electroencephalogram/electromyogram (EEG/EMG) recordings in juvenile prairie voles undergoing ELSD, compared to Control conditions. Second, we conducted 24 h of home cage tethered EEG/EMG recordings in either adolescent or adult male and female prairie voles that had previously undergone ELSD or Control conditions as juveniles. We found that, as adults, male ELSD prairie voles showed persistently lower REM sleep duration and female ELSD prairie voles showed persistently higher NREM sleep duration compared to Controls, but no other sleep parameters differed. We concluded that 1) persistent effects of ELSD on sleep into adulthood may contribute to the social and cognitive deficits observed in adult voles, and 2) sleep disruption early in life can influence later sleep patterns in adulthood.

Loss of sleep when it is needed most - Consequences of persistent developmental sleep disruption: A scoping review of rodent models

Sleep is an essential component of development. Developmental sleep disruption (DSD) impacts brain maturation and has been associated with significant consequences on socio-emotional development. In humans, poor sleep during infancy and adolescence affects neurodevelopmental outcomes and may be a risk factor for the development of autism spectrum disorder (ASD) or other neuropsychiatric illness. Given the wide-reaching and enduring consequences of DSD, identifying underlying mechanisms is critical to best inform interventions with translational capacity. In rodents, studies have identified some mechanisms and neural circuits by which DSD causes later social, emotional, sensorimotor, and cognitive changes. However, these studies spanned methodological differences, including different developmental timepoints for both sleep disruption and testing, different DSD paradigms, and even different rodent species. In this scoping review on DSD in rodents, we synthesize these various studies into a cohesive framework to identify common neural mechanisms underlying DSD-induced dysfunction in brain and behavior. Ultimately, this review serves the goal to inform the generation of novel translational interventions for human developmental disorders featuring sleep disruption.

Remote Spectral Light Sensing in the Home Environment: Further Development of the TWLITE Study Concept

Aging is a significant contributor to changes in sleep patterns, which has compounding consequences on cognitive health. A modifiable factor contributing to poor sleep is inadequate and/or mistimed light exposure. However, methods to reliably and continuously collect light levels long-term in the home, a necessity for informing clinical guidance, are not well established. We explored the feasibility and acceptability of remote deployment and the fidelity of long-term data collection for both light levels and sleep within participants' homes. The original TWLITE study utilized a whole-home tunable lighting system, while the current project is an observational study of the light environment already existing in the home. This was a longitudinal, observational, prospective pilot study involving light sensors remotely deployed in the homes of healthy adults (n = 16, mean age: 71.7 years, standard deviation: 5.0 years) who were co-enrolled in the existing Collaborative Aging (in Place) Research Using Technology (CART) sub-study within the Oregon Center for Aging and Technology (ORCATECH). For 12 weeks, light levels were recorded via light sensors (ActiWatch Spectrum), nightly sleep metrics were recorded via mattress-based sensors, and daily activity was recorded via wrist-based actigraphy. Feasibility and acceptability outcomes indicated that participants found the equipment easy to use and unobtrusive. This proof-of-concept, feasibility/acceptability study provides evidence that light sensors can be remotely deployed to assess relationships between light exposure and sleep among older adults, paving the way for measurement of light levels in future studies examining lighting interventions to improve sleep.

Development of highly sensitive, flexible dual L-glutamate and GABA microsensors for in vivo brain sensing

Real-time tracking of neurotransmitter levels in vivo has been technically challenging due to the low spatiotemporal resolution of current methods. Since the imbalance of cortical excitation/inhibition (E:I) ratios are associated with a variety of neurological disorders, accurate monitoring of excitatory and inhibitory neurotransmitter levels is crucial for investigating the underlying neural mechanisms of these conditions. Specifically, levels of the excitatory neurotransmitter L-glutamate, and the inhibitory neurotransmitter GABA, are assumed to play critical roles in the E:I balance. Therefore, in this work, a flexible electrochemical microsensor is developed for real-time simultaneous detection of L-glutamate and GABA. The flexible polyimide substrate was used for easier handling during implantation and measurement, along with less brain damage. Further, by electrochemically depositing Pt-black nanostructures on the sensor's surface, the active surface area was enhanced for higher sensitivity. This dual neurotransmitter sensor probe was validated under various settings for its performance, including in vitro, ex vivo tests with glutamatergic neuronal cells and in vivo test with anesthetized rats. Additionally, the sensor's performance has been further investigated in terms of longevity and biocompatibility. Overall, our dual L-glutamate:GABA sensor microprobe has its unique features to enable accurate, real-time, and long-term monitoring of the E:I balance in vivo. Thus, this new tool should aid investigations of neural mechanisms of normal brain function and various neurological disorders.

Baseline characteristics of the North American prodromal Synucleinopathy cohort

OBJECTIVE

Rapid eye movement (REM) sleep behavior disorder (RBD) is widely considered a prodromal synucleinopathy, as most with RBD develop overt synucleinopathy within ~10 years. Accordingly, RBD offers an opportunity to test potential treatments at the earliest stages of synucleinopathy. The North American Prodromal Synucleinopathy (NAPS) Consortium has created a multisite RBD participant, primarily clinic-based cohort to better understand characteristics at diagnosis, and in future work, identify predictors of phenoconversion, develop synucleinopathy biomarkers, and enable early stage clinical trial enrollment.

METHODS

Participants ≥18 years of age with overnight polysomnogram-confirmed RBD without Parkinson's disease, dementia, multiple system atrophy, or narcolepsy were enrolled from nine sites across North America (8/2018 to 4/2021). Data collection included family/personal history of RBD and standardized assessments of cognitive, motor, sensory, and autonomic function.

RESULTS

Outcomes are primarily reported based on sex (361 total: n = 295 male, n = 66 female), and secondarily based on history of antidepressant use (n = 200 with, n = 154 without; with correction for sex differences) and based on extent of synucleinopathy burden (n = 56 defined as isolated RBD, n = 305 defined as RBD+ [i.e., exhibiting ≥1 abnormality]). Overall, these participants commonly demonstrated abnormalities in global cognition (MoCA; 38%), motor function (alternate tap test; 48%), sensory (BSIT; 57%), autonomic function (orthostatic hypotension, 38.8%), and anxiety/depression (BAI and PHQ-9; 39.3% and 31%, respectively).

INTERPRETATION

These RBD participants, assessed with extensive history, demographic, cognitive, motor, sensory, and autonomic function demonstrated a lack of sex differences and high frequency of concomitant neurological abnormalities. These participants will be valuable for future longitudinal study and neuroprotective clinical trials.

Unobtrusive Sensing Technology Detects Ecologically Valid Spatiotemporal Patterns of Daily Routines Distinctive to Persons With Mild Cognitive Impairment

BACKGROUND

The ability to capture people's movement throughout their home is a powerful approach to inform spatiotemporal patterns of routines associated with cognitive impairment. The study estimated indoor room activities over 24 hours and investigated relationships between diurnal activity patterns and mild cognitive impairment (MCI).

METHODS

One hundred and sixty-one older adults (26 with MCI) living alone (age = 78.9 ± 9.2) were included from 2 study cohorts-the Oregon Center for Aging & Technology and the Minority Aging Research Study. Indoor room activities were measured by the number of trips made to rooms (bathroom, bedroom, kitchen, living room). Trips made to rooms (transitions) were detected using passive infrared motion sensors fixed on the walls for a month. Latent trajectory models were used to identify distinct diurnal patterns of room activities and characteristics associated with each trajectory.

RESULTS

Latent trajectory models identified 2 diurnal patterns of bathroom usage (high and low usage). Participants with MCI were more likely to be in the high bathroom usage group that exhibited more trips to the bathroom than the low-usage group (odds ratio [OR] = 4.1, 95% CI [1.3-13.5], p = .02). For kitchen activity, 2 diurnal patterns were identified (high and low activity). Participants with MCI were more likely to be in the high kitchen activity group that exhibited more transitions to the kitchen throughout the day and night than the low kitchen activity group (OR = 3.2, 95% CI [1.1-9.1], p = .03).

CONCLUSIONS

The linkage between bathroom and kitchen activities with MCI may be the result of biological, health, and environmental factors in play. In-home, real-time unobtrusive-sensing offers a novel way of delineating cognitive health with chronologically-ordered movement across indoor locations.

Photosensitivity Is Associated with Chronic Pain following Traumatic Brain Injury

Individuals with a history of traumatic brain injury (TBI) report increased rates of chronic pain. Photosensitivity is also a common chronic symptom following TBI and is prevalent among other types of chronic pain. The aim of this study was to better understand the relationship between chronic pain, pain-related disability, and photosensitivity in a TBI population. We quantified participants' visual photosensitivity thresholds (VPT) using an Ocular Photosensitivity Analyzer and measured pressure-pain sensitivity using pressure algometry. Participants also completed a battery of self-report measures related to chronic pain, TBI history, and mental health. A total of 395 participants completed testing, with 233 reporting a history of TBI. The TBI group was divided into 120 symptomatic TBI participants (s-TBI), and 113 asymptomatic TBI participants (a-TBI) based on their Neurobehavioral Symptom Inventory (NSI) scores. Participants in the s-TBI group scored significantly higher on self-reported chronic pain measures compared with a-TBI and no-TBI participants, including the Symptom Impact Questionnaire Revised (SIQR; p < 0.001) and the Michigan Body Map (MBM; p < 0.001). Despite differences in chronic pain complaints, groups displayed similar pressure-pain thresholds (p = 0.270). Additionally, s-TBI participants were more sensitive to light (lower VPT, p < 0.001), and VPT was correlated with SIQR scores across all participants (R = -0.452, p < 0.001). These data demonstrate that photosensitivity is associated with self-reported chronic pain and disability in individuals with chronic TBI symptomatology. Photosensitivity could therefore serve as a simple, more highly quantitative marker of high-impact chronic pain after TBI.

Tunable White Light for Elders (TWLITE): A Protocol Demonstrating Feasibility and Acceptability for Deployment, Remote Data Collection, and Analysis of a Home-Based Lighting Intervention in Older Adults

Sleep disturbances are common in older adults and may contribute to disease progression in certain populations (e.g., Alzheimer's disease). Light therapy is a simple and cost-effective intervention to improve sleep. Primary barriers to light therapy are: (1) poor acceptability of the use of devices, and (2) inflexibility of current devices to deliver beyond a fixed light spectrum and throughout the entirety of the day. However, dynamic, tunable lighting integrated into the native home lighting system can potentially overcome these limitations. Herein, we describe our protocol to implement a whole-home tunable lighting system installed throughout the homes of healthy older adults already enrolled in an existing study with embedded home assessment platforms (Oregon Center for Aging & Technology-ORCATECH). Within ORCATECH, continuous data on room location, activity, sleep, and general health parameters are collected at a minute-to-minute resolution over years of participation. This single-arm longitudinal protocol collected participants' light usage in addition to ORCATECH outcome measures over a several month period before and after light installation. The protocol was implemented with four subjects living in three ORCATECH homes. Technical/usability challenges and feasibility/acceptability outcomes were explored. The successful implementation of our protocol supports the feasibility of implementing and integrating tunable whole-home lighting systems into an automated home-based assessment platform for continuous data collection of outcome variables, including long-term sleep measures. Challenges and iterative approaches are discussed. This protocol will inform the implementation of future clinical intervention trials using light therapy in patients at risk for developing Alzheimer's disease and related conditions.

Label Alignment Improves EEG-based Machine Learning-based Classification of Traumatic Brain Injury

Machine learning and deep learning algorithms have paved the way for improved analysis of biomedical data which has led to a better understanding of various biological conditions. However, one major hindrance to leveraging the potential of machine learning models is the requirement of huge datasets. In the biomedical domain, this becomes extremely difficult due to uncertainties in collecting high-quality data as well as, in the case of human subjects data, privacy. Further, when it comes to biomedical data, inter-subject variability has been a long-entrenched issue. The data obtained from different individuals will differ to a considerable extent that it becomes difficult to find population differences in small datasets. In this work, we investigate the use of label alignment techniques on an EEG-based Traumatic Brain Injury (TBI) classification task to overcome inter-subject variability, thereby increasing the classification accuracy. We show an increase in accuracy of around 6% in some cases as compared to our previous results. In the end, we also propose a methodology to incorporate TBI data from a different species (e.g., mice) after domain adaptation, which might further improve the performance by increasing the amount of training datasets available for the classification model.

Immediate impact of yogic breathing on pulsatile cerebrospinal fluid dynamics

Cerebrospinal fluid (CSF), a clear fluid bathing the central nervous system (CNS), undergoes pulsatile movements. Together with interstitial fluid, CSF plays a critical role for the removal of waste products from the brain, and maintenance of the CNS health. As such, understanding the mechanisms driving CSF movement is of high scientific and clinical impact. Since pulsatile CSF dynamics is sensitive and synchronous to respiratory movements, we are interested in identifying potential integrative therapies such as yogic breathing to regulate CSF dynamics, which has not been reported before. Here, we investigated the pre-intervention baseline data from our ongoing randomized controlled trial, and examined the impact of four yogic breathing patterns: (i) slow, (ii) deep abdominal, (iii) deep diaphragmatic, and (iv) deep chest breathing with the last three together forming a yogic breathing called three-part breath. We utilized our previously established non-invasive real-time phase contrast magnetic resonance imaging approach using a 3T MRI instrument, computed and tested differences in single voxel CSF velocities (instantaneous, respiratory, cardiac 1st and 2nd harmonics) at the level of foramen magnum during spontaneous versus yogic breathing. In examinations of 18 healthy participants (eight females, ten males; mean age 34.9 ± 14 (SD) years; age range: 18-61 years), we observed immediate increase in cranially-directed velocities of instantaneous-CSF 16-28% and respiratory-CSF 60-118% during four breathing patterns compared to spontaneous breathing, with the greatest changes during deep abdominal breathing (28%, p = 0.0008, and 118%, p = 0.0001, respectively). Cardiac pulsation was the primary source of pulsatile CSF motion except during deep abdominal breathing, when there was a comparable contribution of respiratory and cardiac 1st harmonic power [0.59 ± 0.78], suggesting respiration can be the primary regulator of CSF depending on the individual differences in breathing techniques. Further work is needed to investigate the impact of sustained training yogic breathing on pulsatile CSF dynamics for CNS health.

Dietary Supplementation With Branched Chain Amino Acids to Improve Sleep in Veterans With Traumatic Brain Injury: A Randomized Double-Blind Placebo-Controlled Pilot and Feasibility Trial

Study Objectives

Traumatic brain injury (TBI) is associated with chronic sleep disturbances and cognitive impairment. Our prior preclinical work demonstrated dietary supplementation with branched chain amino acids (BCAA: leucine, isoleucine, and valine), precursors to de novo glutamate production, restored impairments in glutamate, orexin/hypocretin neurons, sleep, and memory in rodent models of TBI. This pilot study assessed the feasibility and preliminary efficacy of dietary supplementation with BCAA on sleep and cognition in Veterans with TBI.

Methods

Thirty-two Veterans with TBI were prospectively enrolled in a randomized, double-blinded, placebo-controlled trial comparing BCAA (30 g, b.i.d. for 21-days) with one of two placebo arms (microcrystalline cellulose or rice protein, both 30 g, b.i.d. for 21-days). Pre- and post-intervention outcomes included sleep measures (questionnaires, daily sleep/study diaries, and wrist actigraphy), neuropsychological testing, and blood-based biomarkers related to BCAA consumption.

Results

Six subjects withdrew from the study (2/group), leaving 26 remaining subjects who were highly adherent to the protocol (BCAA, 93%; rice protein, 96%; microcrystalline, 95%; actigraphy 87%). BCAA were well-tolerated with few side effects and no adverse events. BCAA significantly improved subjective insomnia symptoms and objective sleep latency and wake after sleep onset on actigraphy.

Conclusion

Dietary supplementation with BCAA is a mechanism-based, promising intervention that shows feasibility, acceptability, and preliminary efficacy to treat insomnia and objective sleep disruption in Veterans with TBI. A larger scale randomized clinical trial is warranted to further evaluate the efficacy, dosing, and duration of BCAA effects on sleep and other related outcome measures in individuals with TBI.

Clinical Trial Registration

[http://clinicaltrials.gov/], identifier [NCT03990909].

Association Between Mild Cognitive Impairment and Seasonal Rest-Activity Patterns of Older Adults

Seasonal variation in rest-activity patterns has been observed in healthy adult populations. This study examined seasonal variation in total time spent overnight in the bedroom by cognitively intact older adults and older adults with mild cognitive impairment (MCI). We hypothesize that seasonal variation in rest-activity patterns is observed in the cognitively intact group and that this variation is disturbed in those with MCI. Study participants were 128 older adults; mean age 85.2 years. Ninety-eight were cognitively intact, and 30 had been diagnosed with MCI. All were enrolled in an ongoing longitudinal study using in-home passive monitoring technology. Infrared presence sensors were placed throughout each participant's home to monitor movement and presence in each room of the home. Activity data was collected from the sensors over a period of up to 527 days. Overnight time in bedroom was found to vary seasonally for the cognitively intact group, with longer times spent overnight in the bedroom during the winter months. This seasonal variation was not observed for those with non-amnestic MCI. MCI is associated with an attenuation of seasonal variation in total time spent in the bedroom at night. Detection of changes in infradian sleep patterns may be an early marker of cognitive decline. Which key determinants are driving these disturbed rhythms, such as features intrinsic to changes in the brain or to environmental factors or external cues, remains an important question for ongoing and future studies.

Validation of Visually Identified Muscle Potentials during Human Sleep Using High Frequency/Low Frequency Spectral Power Ratios

Surface electromyography (EMG), typically recorded from muscle groups such as the mentalis (chin/mentum) and anterior tibialis (lower leg/crus), is often performed in human subjects undergoing overnight polysomnography. Such signals have great importance, not only in aiding in the definitions of normal sleep stages, but also in defining certain disease states with abnormal EMG activity during rapid eye movement (REM) sleep, e.g., REM sleep behavior disorder and parkinsonism. Gold standard approaches to evaluation of such EMG signals in the clinical realm are typically qualitative, and therefore burdensome and subject to individual interpretation. We originally developed a digitized, signal processing method using the ratio of high frequency to low frequency spectral power and validated this method against expert human scorer interpretation of transient muscle activation of the EMG signal. Herein, we further refine and validate our initial approach, applying this to EMG activity across 1,618,842 s of polysomnography recorded REM sleep acquired from 461 human participants. These data demonstrate a significant association between visual interpretation and the spectrally processed signals, indicating a highly accurate approach to detecting and quantifying abnormally high levels of EMG activity during REM sleep. Accordingly, our automated approach to EMG quantification during human sleep recording is practical, feasible, and may provide a much-needed clinical tool for the screening of REM sleep behavior disorder and parkinsonism.

Investigation of Machine Learning and Deep Learning Approaches for Detection of Mild Traumatic Brain Injury from Human Sleep Electroencephalogram

Traumatic Brain Injury (TBI) is a highly prevalent and serious public health concern. Most cases of TBI are mild in nature, yet some individuals may develop following-up persistent disability. The pathophysiologic causes for those with persistent postconcussive symptoms are most likely multifactorial and the underlying mechanism is not well understood, although it is clear that sleep disturbances feature prominently in those with persistent disability. The sleep electroencephalogram (EEG) provides a direct window into neuronal activity during an otherwise highly stereotyped behavioral state, and represents a promising quantitative measure for TBI diagnosis and prognosis. With the ever-evolving domain of machine learning, deep convolutional neural networks, and the development of better architectures, these approaches hold promise to solve some of the long entrenched challenges of personalized medicine for uses in recommendation systems and/or in health monitoring systems. In particular, advanced EEG analysis to identify putative EEG biomarkers of neurological disease could be highly relevant in the prognostication of mild TBI, an otherwise heterogeneous disorder with a wide range of affected phenotypes and disability levels. In this work, we investigate the use of various machine learning techniques and deep neural network architectures on a cohort of human subjects with sleep EEG recordings from overnight, in-lab, diagnostic polysomnography (PSG). An optimal scheme is explored for the classification of TBI versus non-TBI control subjects. The results were promising with an accuracy of ∼95% in random sampling arrangement and ∼70% in independent validation arrangement when appropriate parameters were used using a small number of subjects (10 mTBI subjects and 9 age- and sex-matched controls). We are thus confident that, with additional data and further studies, we would be able to build a generalized model to detect TBI accurately, not only via attended, in-lab PSG recordings, but also in practical scenarios such as EEG data obtained from simple wearables in daily life.

Fabrication of Highly Sensitive Pt-black Electrochemical Sensors for GABA Detection

GABA (Gamma-aminobutyric acid) is the main inhibitory neurotransmitter in the central nervous system of mammals. It is known to be related with various neurological disorders. GABA plays a crucial role in normal neuronal activity, information processing and plasticity, and neuronal network synchronization. To date, microdialysis has been widely used to monitor the level of GABA but the temporal and spatial resolution is limited. Besides, electrochemical sensors for neurotransmitter measurement, having high temporal and spatial resolution, overcome this problem. Here, using a cost-effective method of electrodeposition of platinum black (Pt-black), a highly sensitive, GABA specific, amperometric electrochemical sensor is fabricated. Nanostructured Pt-black increases the active surface area of the electrode contributing to higher sensitivity. Along with that, a self-referencing site and an exclusion layer are integrated to increase the selectivity and the signal-to-noise ratio (SNR) of the biosensor. This provides a prototype for a highly sensitive GABA sensor that could later be used to study various neurological disorders related to GABA concentrations.Clinical Relevance- This electrochemical sensor allows real-time monitoring of major inhibitory neurotransmitter (GABA) with high sensitivity which can be used for studying various neurological disorders.

In-Home Mobility Frequency and Stability in Older Adults Living Alone With or Without MCI: Introduction of New Metrics

Background: Older adults spend a considerable amount of time inside their residences; however, most research investigates out-of-home mobility and its health correlates. We measured indoor mobility using room-to-room transitions, tested their psychometric properties, and correlated indoor mobility with cognitive and functional status. Materials and Methods: Community-dwelling older adults living alone (n = 139; age = 78.1 ± 8.6 years) from the Oregon Center for Aging & Technology (ORCATECH) and Minority Aging Research Study (MARS) were included in the study. Two indoor mobility features were developed using non-parametric parameters (frequency; stability): Indoor mobility frequency (room-to-room transitions/day) was detected using passive infrared (PIR) motion sensors fixed on the walls in four geographic locations (bathroom; bedroom; kitchen; living room) and using door contact sensors attached to the egress door in the entrance. Indoor mobility stability was estimated by variances of number of room-to-room transitions over a week. Test-retest reliability (Intra-class coefficient, ICC) and the minimal clinically important difference (MCID) defined as the standard error of measurement (SEM) were generated. Generalized estimating equations models related mobility features with mild cognitive impairment (MCI) and functional status (gait speed). Results: An average of 206 days (±127) of sensor data were analyzed per individual. Indoor mobility frequency and stability showed good to excellent test-retest reliability (ICCs = 0.91[0.88-0.94]; 0.59[0.48-0.70]). The MCIDs of mobility frequency and mobility stability were 18 and 0.09, respectively. On average, a higher indoor mobility frequency was associated with faster gait speed (β = 0.53, p = 0.04), suggesting an increase of 5.3 room-to-room transitions per day was associated with an increase of 10 cm/s gait speed. A decrease in mobility stability was associated with MCI (β = -0.04, p = 0.03). Discussion: Mobility frequency and stability in the home are clinically meaningful and reliable features. Pervasive-sensing systems deployed in homes can objectively reveal cognitive and functional status in older adults who live alone.

Onset of Skin, Gut, and Genitourinary Prodromal Parkinson's Disease: A Study of 1.5 Million Veterans

BACKGROUND

Prodromal Parkinson's disease of skin, genitourinary, and gastrointestinal systems offers a unique window for understanding early disease pathogenesis and developing disease modifying treatments. However, prior studies are limited by incomplete timing information, small sample size, and lack of adjustment for known confounders. Verifying prodromal timing and identifying new disorders in these accessible organs is critically important given their broad use.

OBJECTIVE

We aimed to measure onset timing for gastrointestinal, genitourinary, and skin disorders in a large, nationwide clinically characterized cohort of 1.5 million participants.

METHODS

Patients with Parkinson's disease (n = 303,693) were identified using diagnostic codes in the medical records database of the United States Veterans Affairs healthcare system and were compared 4:1 with matched controls. Disorder prevalence and estimated onset times were assessed for 20 years preceding diagnosis.

RESULTS

The earliest significantly increased prodromal disorders were gastroesophageal reflux, sexual dysfunction, and esophageal dyskinesia at 17, 16, and 15 years before diagnosis. Estimated onset times for each disorder occurred 5.5 ± 3.4 years before the first measured increase. The earliest estimated onset times were smell/taste, upper gastrointestinal tract, and sexual dysfunction at 20.9, 20.6, and 20.1 years before diagnosis. Onset times for constipation and urinary dysfunction were notably longer by 7 and 9 years compared to prior studies in sleep disorder patients. Dermatophytosis and prostatic hypertrophy were identified as new high prevalence prodromal disorders.

CONCLUSIONS

Gastrointestinal, genitourinary, and skin disorders manifest decades before diagnosis of Parkinson's disease, reiterating their potential as sites for developing early diagnostic testing and understanding pathogenesis.

Different methods for TBI diagnosis influence presence and symptoms of post-concussive syndrome in US Veterans

Common methods for evaluating history of traumatic brain injury (TBI) include self-report, electronic medical record review (EMR), and structured interviews such as the Head Trauma Events Characteristics (HTEC). Each has strengths and weaknesses, but little is known regarding how TBI diagnostic rates or the associated symptom profile differ among them. This study examined 200 Veterans recruited within the VA Portland Health Care System, each evaluated for TBI using self-report, EMR, and HTEC. Participants also completed validated questionnaires assessing chronic symptom severity in broad health-related domains (pain, sleep, quality of life, post-concussive symptoms). The HTEC was more sensitive (80% of participants in our cohort) than either self-report or EMR alone (40%). As expected from the high sensitivity, the HTEC+ group included many people with mild or no post-concussive symptoms. Participants were then grouped according to the degree of concordance across these three diagnostic methods: No-TBI, n=43; or TBI-positive in any one method (TBI-1dx, n=53), any two (TBI-2dx, n=45), or all three (TBI-3dx, n=59). The symptom profile of the TBI-1dx group was indistinguishable from the No TBI group. The TBI-3dx group carried the most severe symptom profile. These data show that understanding the method(s) used to ascertain TBI is essential when interpreting results from other studies, an issue that will be even more salient when interpreting data merged from multiple sources within centralized repositories (e.g., FITBIR). The development of a composite TBI assessment tool including self-report, medical record review, and neuropsychology outcomes is a crucial next step for the field.

Systematic Review and Methodological Considerations for the Use of Single Prolonged Stress and Fear Extinction Retention in Rodents

Posttraumatic stress disorder (PTSD) is a mental health condition triggered by experiencing or witnessing a terrifying event that can lead to lifelong burden that increases mortality and adverse health outcomes. Yet, no new treatments have reached the market in two decades. Thus, screening potential interventions for PTSD is of high priority. Animal models often serve as a critical translational tool to bring new therapeutics from bench to bedside. However, the lack of concordance of some human clinical trial outcomes with preclinical animal efficacy findings has led to a questioning of the methods of how animal studies are conducted and translational validity established. Thus, we conducted a systematic review to determine methodological variability in studies that applied a prominent animal model of trauma-like stress, single prolonged stress (SPS). The SPS model has been utilized to evaluate a myriad of PTSD-relevant outcomes including extinction retention. Rodents exposed to SPS express an extinction retention deficit, a phenotype identified in humans with PTSD, in which fear memory is aberrantly retained after fear memory extinction. The current systematic review examines methodological variation across all phases of the SPS paradigm, as well as strategies for behavioral coding, data processing, statistical approach, and the depiction of data. Solutions for key challenges and sources of variation within these domains are discussed. In response to methodological variation in SPS studies, an expert panel was convened to generate methodological considerations to guide researchers in the application of SPS and the evaluation of extinction retention as a test for a PTSD-like phenotype. Many of these guidelines are applicable to all rodent paradigms developed to model trauma effects or learned fear processes relevant to PTSD, and not limited to SPS. Efforts toward optimizing preclinical model application are essential for enhancing the reproducibility and translational validity of preclinical findings, and should be conducted for all preclinical psychiatric research models.

A Raspberry Pi-Based Traumatic Brain Injury Detection System for Single-Channel Electroencephalogram

Traumatic Brain Injury (TBI) is a common cause of death and disability. However, existing tools for TBI diagnosis are either subjective or require extensive clinical setup and expertise. The increasing affordability and reduction in the size of relatively high-performance computing systems combined with promising results from TBI related machine learning research make it possible to create compact and portable systems for early detection of TBI. This work describes a Raspberry Pi based portable, real-time data acquisition, and automated processing system that uses machine learning to efficiently identify TBI and automatically score sleep stages from a single-channel Electroencephalogram (EEG) signal. We discuss the design, implementation, and verification of the system that can digitize the EEG signal using an Analog to Digital Converter (ADC) and perform real-time signal classification to detect the presence of mild TBI (mTBI). We utilize Convolutional Neural Networks (CNN) and XGBoost based predictive models to evaluate the performance and demonstrate the versatility of the system to operate with multiple types of predictive models. We achieve a peak classification accuracy of more than 90% with a classification time of less than 1 s across 16–64 s epochs for TBI vs. control conditions. This work can enable the development of systems suitable for field use without requiring specialized medical equipment for early TBI detection applications and TBI research. Further, this work opens avenues to implement connected, real-time TBI related health and wellness monitoring systems.

Emfit Bed Sensor Activity Shows Strong Agreement with Wrist Actigraphy for the Assessment of Sleep in the Home Setting

PURPOSE

Wrist-worn actigraphy via research-grade devices, a well-established approach to the assessment of rest-activity, is limited by poor compliance, battery life, and lack of direct evidence for time spent physically in the bed. A non-invasive bed sensor (Emfit) may provide advantages over actigraphy for long-term sleep assessment in the home. This study compared sleep-wake measurements between this sensor and a validated actigraph.

PATIENTS AND METHODS

Thirty healthy subjects (6 to 54 years) underwent simultaneous monitoring with both devices for 14 days and filled out a daily sleep diary. Parameters included bed entry time, sleep start, sleep end, bed exit time, rest interval duration, and wake after sleep onset (WASO). The agreement between the two devices was measured using Bland-Altman plots and inter-class correlation coefficients (ICC). In addition, sensitivity, specificity, and accuracy were obtained from epoch-by-epoch comparisons of Emfit and actigraphy.

RESULTS

Fifteen percent of the subjects reported that wearing the actigraph was a burden. None reported that using the bed sensor was a burden. The minimal detectable change between Emfit and actigraphy was 11 minutes for bed entry time, 14 minutes for sleep start, 14 minutes for sleep end, 10 minutes for bed exit time, 20 minutes for rest interval duration, and 110 minutes for WASO. Inter-class correlation coefficients revealed an excellent agreement for all sleep parameters (ICC=0.99, 95% CI 98-99) except for WASO (ICC=0.46, 95% CI 0.33-0.56). Sensitivity, specificity, and accuracy were 0.62, 0.93, and 0.88, respectively. Kappa correlation analysis revealed a moderate correlation between the two devices (κ=0.55, p<0.0001).

CONCLUSION

Emfit is an acceptable alternative to actigraphy for the estimation of bed entry time, sleep start, sleep end, bed exit time, and rest interval duration. However, WASO estimates are poorly correlated between the two devices. Emfit may offer methodological advantages in situations where actigraphy is challenging to implement.

Classification of Electroencephalogram in a Mouse Model of Traumatic Brain Injury Using Machine Learning Approaches

Traumatic Brain Injury (TBI) is highly prevalent, affecting ~1% of the U.S. population, with lifetime economic costs estimated to be over $75 billion. In the U.S., there are about 50,000 deaths annually related to TBI, and many others are permanently disabled. However, it is currently unknown which individuals will develop persistent disability following TBI and what brain mechanisms underlie these distinct populations. The pathophysiologic causes for those are most likely multifactorial. Electroencephalogram (EEG) has been used as a promising quantitative measure for TBI diagnosis and prognosis. The recent rise of advanced data science approaches such as machine learning and deep learning holds promise to further analyze EEG data, looking for EEG biomarkers of neurological disease, including TBI. In this work, we investigated various machine learning approaches on our unique 24-hour recording dataset of a mouse TBI model, in order to look for an optimal scheme in classification of TBI and control subjects. The epoch lengths were 1 and 2 minutes. The results were promising with accuracy of ~80-90% when appropriate features and parameters were used using a small number of subjects (5 shams and 4 TBIs). We are thus confident that, with more data and studies, we would be able to detect TBI accurately, not only via long-term recordings but also in practical scenarios, with EEG data obtained from simple wearables in the daily life.

Excitability, Inhibition, and Neurotransmitter Levels in the Motor Cortex of Symptomatic and Asymptomatic Individuals Following Mild Traumatic Brain Injury

Purpose: The purpose of this study was to determine the level of excitability and inhibition, as well as the concentrations of excitatory and inhibitory neurotransmitters, in the motor cortex of individuals with acute and chronic symptoms from mTBI.

Methods: Fifty-three individuals were assigned to one of four groups: (i) without history of mTBI (Control), (ii) within 72-h of diagnosis of mTBI (Acute), (iii) with history of mTBI and no remaining symptoms (Chronic Asymptomatic), and (iv) with chronic symptoms from mTBI, lasting at least 3 months post-injury (Chronic Symptomatic). Measures of corticospinal excitability and inhibition were obtained using transcranial magnetic stimulation (TMS). On the same day, measures of glutamate and GABA concentrations were obtained from the primary motor cortex (M1) using proton magnetic resonance spectroscopy.

Results: MEP amplitude and area were both significantly lower in the Chronic Symptomatic group compared to the Control and Chronic Asymptomatic groups (p ≤ 0.05). Intracortical inhibition was not significantly different among groups (p = 0.14). The concentration of glutamate in M1 was similar between groups (p = 0.93) while there was a trend for a lower concentration of GABA in the Chronic Symptomatic group compared to the Acute group (p = 0.06).

Conclusions: Individuals with chronic mTBI symptoms appear to have lower corticospinal excitability compared with acutely-injured individuals and asymptomatic controls, but the absence of differences in intracortical inhibition, and concentrations of excitatory and inhibitory neurotransmitters in M1 suggests that neurotransmitter changes in the human brain post-mTBI do not follow the pattern typically seen in the animal literature.

The relationship between depressive symptoms, somatic complaints, and concussion history with poor sleep in collegiate athletes

OBJECTIVE

Ongoing exploration of factors related to poor sleep in collegiate athletes is important as understanding of the risks and consequences of poor sleep in this specific population increases.

DESIGN

Retrospective cohort study.

SETTING

University in the Pacific Northwest.

PARTICIPANTS

One-hundred thirty-seven male and female collegiate athletes across 5 collision, contact, and limited contact team sports.

MEASUREMENTS

Depressive symptoms (Patient Health Questionnaire 9; PHQ-9), anxiety symptoms (General Anxiety Disorder 7; GAD-7), and somatic complaints (Patient Health Questionnaire 15; PHQ-15). Sleep quality (Pittsburgh Sleep Quality Index; PSQI) used both a cutoff score ≥6 and a cutoff score of ≥8, indicating "poor sleep quality" to reduce threats to divergent validity.

RESULTS

Poor sleep quality as defined by PSQI ≥ 6 was present in 53% of athletes, and as defined by PSQI ≥ 8 was identified in 33.5% of the cohort. There were no differences in the incidence of poor sleepers between sport, race/ethnicity, or sex. Multiple regression analysis revealed that depressive symptoms, somatic complaints, Caucasian race, male sex, and number of concussions were significant predictors of poor sleep (P < .05). The model accounted for 43% of the variance in PSQI and primarily by depressive symptoms explaining 9% of reported sleep quality variability. Anxiety symptoms, sport category, and history of migraines were not significant predictors of poor sleep quality.

CONCLUSIONS

A high incidence of poor sleep among collegiate athletes was observed regardless of sport, and may be related to depressive symptoms, somatic complaints, Caucasian race, male sex, and historical number of concussions.

Early life sleep disruption is a risk factor for increased ethanol drinking after acute footshock stress in prairie voles

Early postnatal experiences are important for shaping the development of the stress response and may contribute to the later emergence of alcohol use disorders. We have previously found that early life sleep disruption impairs social development and alters GABA neurons in the brain of adult prairie voles, a socially monogamous rodent that displays natural ethanol preference in the laboratory. However, it is unclear whether these effects on social behavior are due, in part, to overall anhedonia and/or altered behavioral response to stress. To address this question, litters containing prairie vole pups were sleep disrupted by gentle cage agitation for 7 consecutive days from postnatal days (P) 14 to 21 (early life sleep disruption, or ELSD group) or allowed to sleep undisturbed (Control). Adult voles underwent a 2-bottle choice ethanol drinking procedure integrated with a single session of footshocks. Ethanol intake after footshock was measured as well as c-Fos immunoreactivity in the lateral and central amygdala. ELSD animals showed increased ethanol consumption and increased neural activity in these amygdala regions after footshock compared to control animals. There were no differences in baseline ethanol drinking prior to exposure to a stressor. These results suggest that early life sleep disruption in prairie voles does not produce anhedonia but can have long-lasting effects on stress reactivity. In addition to shaping species-typical social behavior, early life sleep may be important in the development of stress induced ethanol consumption and the activation of limbic pathways associated with stress. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Posttraumatic stress disorder increases the odds of REM sleep behavior disorder and other parasomnias in Veterans with and without comorbid traumatic brain injury

STUDY OBJECTIVES

To describe the crude prevalence of rapid eye movement (REM) sleep behavior disorder (RBD) following traumatic brain injury (TBI) and posttraumatic stress disorder (PTSD) in Veterans, given potential relationships between TBI, PTSD, RBD, and neurodegeneration.

METHODS

Veterans (n = 394; 94% male; 54.4 ± 15.5 years of age) were prospectively/cross-sectionally recruited from the VA Portland Health Care System and completed in-lab video-polysomnography and questionnaires. TBI and PTSD were assessed via diagnostic screening and medical record review. Subjects were categorized into four groups after assessment of REM sleep without atonia (RSWA) and self-reported dream enactment: (1) "Normal," neither RSWA nor dream enactment, (2) "Other Parasomnia," dream enactment without RSWA, (3) "RSWA," isolated-RSWA without dream enactment, and (4) "RBD," RSWA with dream enactment. Crude prevalence, prevalence odds ratio, and prevalence rate for parasomnias across subjects with TBI and/or PTSD were assessed.

RESULTS

Overall prevalence rates were 31%, 7%, and 9% for Other Parasomnia, RSWA, and RBD, respectively. The prevalence rate of RBD increased to 15% in PTSD subjects [age adjusted POR: 2.81 (1.17-4.66)] and to 21% in TBI + PTSD subjects [age adjusted POR: 3.43 (1.20-9.35)]. No subjects met all diagnostic criteria for trauma-associated sleep disorder (TASD), and no overt dream enactment was captured on video.

CONCLUSIONS

The prevalence of RBD and related parasomnias is significantly higher in Veterans compared with the general population and is associated with PTSD and TBI + PTSD. Considering the association between idiopathic-RBD and synucleinopathy, it remains unclear whether RBD (and potentially TASD) associated with PTSD or TBI + PTSD similarly increases risk for long-term neurologic sequelae.

Sleep-Wake Disturbances After Acquired Brain Injury in Children Surviving Critical Care

BACKGROUND

Sleep-wake disturbances are underevaluated among children with acquired brain injury surviving critical care. We aimed to quantify severity, phenotypes, and risk factors for sleep-wake disturbances.

METHODS

We performed a prospective cohort study of 78 children aged ≥3 years with acquired brain injury within three months of critical care hospitalization. Diagnoses included traumatic brain injury (n = 40), stroke (n = 11), infectious or inflammatory disease (n = 10), hypoxic-ischemic injury (n = 9), and other (n = 8). Sleep Disturbances Scale for Children standardized T scores measured sleep-wake disturbances. Overall sleep-wake disturbances were dichotomized as any total or subscale T score ≥60. Any T score ≥70 defined severe sleep-wake disturbances. Subscale T scores ≥60 identified sleep-wake disturbance phenotypes.

RESULTS

Sleep-wake disturbances were identified in 44 (56%) children and were classified as severe in 36 (46%). Sleep-wake disturbances affected ≥33% of patients within each diagnosis and were not associated with severity of illness measures. The most common phenotype was disturbance in initiation and maintenance of sleep (47%), although 68% had multiple concurrent sleep-wake disturbance phenotypes. One third of all patients had preadmission chronic conditions, and this increased risk for sleep-wake disturbances overall (43% vs 21%, P = 0.04) and in the traumatic brain injury subgroup (52% vs 5%, P = 0.001).

CONCLUSIONS

Over half of children surviving critical care with acquired brain injury have sleep-wake disturbances. Most of these children have severe sleep-wake disturbances independent of severity of illness measures. Many sleep-wake disturbances phenotypes were identified, but most children had disturbance in initiation and maintenance of sleep. Our study underscores the importance of evaluating sleep-wake disturbances after acquired brain injury.

Effects of sleep disruption on stress, nigrostriatal markers, and behavior in a chronic/progressive MPTP male mouse model of parkinsonism

Sleep complaints are an early clinical symptom of neurodegenerative disorders. Patients with Parkinson's disease (PD) experience sleep disruption (SD). The objective of this study was to determine if preexisting, chronic SD leads to a greater loss of tyrosine hydroxylase (TH) within the striatum and the substantia nigra following chronic/progressive exposure with the neurotoxin, 1-methyl-2-phenyl-1,2,3,6-tetrahydropyridine (MPTP). Male mice underwent chronic SD for 4 weeks, then injected with vehicle (VEH) or increasing doses of MPTP for 4 weeks. There was a significant decrease in the plasma corticosterone levels in the MPTP group, an increase in the SD group, and a return to the VEH levels in the SD+MPTP group. Protein expression levels for TH in the striatum (terminals) and substantia nigra pars compacta (dopamine [DA] cell counts) revealed up to a 78% and 38% decrease, respectively, in the MPTP and SD+MPTP groups compared to their relevant VEH and SD groups. DA transporter protein expression increased in the striatum in the MPTP versus VEH group and in the SN/midbrain between the SD+MPTP and the VEH group. There was a main effect of MPTP on various gait measures (e.g., braking) relative to the SD or VEH groups. In the SD+MPTP group, there were no differences compared to the VEH group. Thus, SD, prior to administration of MPTP, has effects on serum corticosterone and gait but more importantly does not potentiate greater loss of TH within the nigrostriatal pathway compared to the MPTP group, suggesting that in PD patients with SD, there is no exacerbation of the DA cell loss.

Effects of traumatic brain injury on sleep and enlarged perivascular spaces

Clearance of perivascular wastes in the brain may be critical to the pathogenesis of amyloidopathies. Enlarged perivascular spaces (ePVS) on MRI have also been associated with amyloidopathies, suggesting that there may be a mechanistic link between ePVS and impaired clearance. Sleep and traumatic brain injury (TBI) both modulate clearance of amyloid-beta through glymphatic function. Therefore, we sought to evaluate the relationship between sleep, TBI, and ePVS on brain MRI. A retrospective study was performed in individuals with overnight polysomnography and 3T brain MRI consented from a single site (n = 38). Thirteen of these individuals had a medically confirmed history of TBI. ePVS were visually assessed by blinded experimenters and analyzed in conjunction with sleep metrics and TBI status. Overall, individuals with shorter total sleep time had significantly higher ePVS burden. Furthermore, individuals with TBI showed a stronger relationship between sleep and ePVS compared to the non-TBI group. These results support the hypothesis that ePVS may be modulated by sleep and TBI, and may have implications for the role of the glymphatic system in ePVS.

Categorizing Sleep in Older Adults with Wireless Activity Monitors Using LSTM Neural Networks

Novel approaches are needed to accurately classify and monitor sleep patterns in older adults, particularly those with cognitive impairment and non-normative sleep. Traditional methods ignore underlying sleep architecture in these patient populations, and other modern approaches tend to focus on healthy, normative patient populations. In this paper, we developed a model using a long-short-term memory neural network (LSTM) and trained it on a sample of older, non-normative patients. The 22 nights of data collected were trained on gold-standard polysomnography (PSG) as ground truth and were compared against the clinical standard threshold-based method for sleep detection. The LSTM more than doubled the traditional method's ability to detect clinically-relevant wakefulness during sleep (37.7% vs. 15%) without significantly sacrificing accuracy (67.7% vs. 75%) or precision (90.7% vs. 94%) of sleep classification.