0416 Poor Sleep Quality Predicts Serum Markers of Neurodegeneration and Cognitive Deficits in Warriors with Mild Traumatic Brain Injury

Abstract Introduction Increasing evidence links neurodegeneration to traumatic brain injury (TBI), and a separate body of literature links neurodegeneration to sleep dysfunction, implicating increased toxin production and decreased glymphatic clearance. Sleep disorders affect 50% of TBI patients, yet the sleep-neurodegeneration connection in these patients remains unexplored. We hypothesized that warfighters with TBI and sleep dysfunction would have increased neuronal injury, revealing potential mechanistic underpinnings for TBI outcomes. We measured plasma biomarkers, cognitive function and sleep surveys for correlation analysis. Methods In a retrospective cross-sectional study of warfighters (n=113 chronic mild TBI patients), the Pittsburgh sleep quality index (PSQI) was compared with amyloid β42 (Aβ42), neurofilament light (NFL), tau, and phospho-tau (threonine 181) isolated from plasma and exosomes. Executive function was tested with the categorical fluency test. Exosomes were precipitated from plasma. Proteins were measured with the Single Molecule Array (Quanterix). Linear models were adjusted for age, ApoE, and number of TBIs. Results Poor sleepers with TBI (PSQI>8) had elevated NFL compared to good sleepers in plasma (p=0.007) and exosomes (p=0.00017), and PSQI directly correlated with NFL (plasma: Beta=0.23, p=0.0079; exosomes: Beta=2.19, p=0.0013) stronger than any other marker of neurodegeneration. Poor sleepers also showed higher obstructive sleep apnea (OSA) risk compared to good sleepers by STOP-BANG scores (3.6, SD=1.6 vs 2.8, SD=1.74; p=0.0014) as well as decreased categorical fluency (20.7, SD=4.1) (18.3, SD=4.6, p=.0067). Plasma tau and Aβ42 also correlated with PSQI (Beta=0.64, p=0.028, and Beta=0.40, p=0.049 respectively). Conclusion This is the first reported data correlating markers of neuronal injury and cognitive deficits with sleep complaints and OSA risk in patients with TBI - possibly identifying treatable pathophysiological mediators of TBI neurodegeneration. Limitations include a small sample size, lack of objective sleep measures, and inability to establish directionality due to cross-sectional design. Prospective trials will be required to further explore our proposed hypothesis. If confirmed, these findings would call for targeting sleep disorders in the TBI population to mitigate risk of neurodegeneration. Support This work was supported by grant funding from: Department of Defense, Chronic Effects of Neurotrauma Consortium (CENC) Award W81XWH-13-2-0095 and Department of Veterans Affairs CENC Award I01 CX001135.

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798 Diffusion tensor imaging as a potential biomarker of sleep dysfunction in warfighters with chronic, severe, traumatic brain injury

SLEEP ◽

10.1093/sleep/zsab072.795 ◽

2021 ◽

Vol 44 (Supplement_2) ◽

pp. A310-A311

Author(s):

J Kent Werner ◽

Brian Gerstenslager ◽

Ping-Hong Yeh ◽

Rujirutana Srikanchana ◽

Kimbra Kenney ◽

...

Keyword(s):

Traumatic Brain Injury ◽

Brain Injury ◽

Sleep Disorders ◽

Control Group ◽

Linear Modeling ◽

Sleep Dysfunction ◽

Generalized Linear Modeling ◽

Potential Biomarker ◽

Obstructive Sleep ◽

Severe Tbi

Abstract Introduction Traumatic brain injury (TBI) plagues service members in times of war and training. Diagnosis and management of TBI remain challenging, with many suffering from sleep disorders. We hypothesized that TBI-related damage to the hypothalamus, a master regulator of breathing and sleep, could be related to post-TBI obstructive sleep apnea (OSA) and serve as a pathophysiological biomarker for a subpopulation of OSA patients. Methods This was a retrospective study of warfighters with TBI from the National Intrepid Center of Excellence (NICoE). Subjects were identified by severe TBI on neuroimaging and compared against a control group without TBI. All subjects underwent screening polysomnography (PSG). MRI was acquired via 3T scanner. The hypothalamus was automatically segmented using a diffeomorphic algorithm. DTI scalar values were analyzed with scalar t-tests between subjects and controls. Generalized linear modeling with DTI scalar values was used to predict AHI in subjects. Results 6 subjects and 61 controls were identified. There was significant sleep dysfunction amongst TBI subjects (mean apnea-hypopnea index (AHI) 5.1+/-6.6 events/hour; mild OSA incidence 33.3%; Pittsburgh Sleep Quality Index (PSQI) mean 13.3+/-2.6). Radial diffusivity (RD), axial diffusivity (AD) and mean diffusivity (MD) were significantly higher among subjects (control RD 9.64x10^-10+/-7.54x10^-11 m^2/s, subject RD 1.13x10^-9+/-1.20x10^-10m^2/s, p = 0.023; control AD 1.32x10^-9+/-7.64x10^-11m^2/s, subject AD 1.50x10^-9+/-1.43x10^-10m^2/s, p = 0.029; control MD 1.08x10^-9+/-7.43x10^-11m^2/s, subject MD 1.25x10^-9+/-1.34x10^-10m^2/s, p = 0.025). There were no differences in age or body-mass index. Generalized linear modeling with diffusivity measures as predictors of AHI in subjects was not significant. Conclusion Using a diffeomorphic algorithm to define the hypothalamus reveals significantly elevated scalar DTI measures in chronic, severe TBI compared to controls. DTI differences in the hypothalamus are a novel finding and possibly underlie part of the pathophysiology of TBI. Although this may have potential to serve as a biomarker in severe TBI patients with sleep disorders, these initial data do not support a relationship between DTI and AHI, despite high incidence of OSA and subjective sleep dysfunction. Future studies with more subjects may better elucidate the changes in hypothalamic DTI after TBI for clinical outcomes analysis. Support (if any) This work was supported by grant 130132 from USAMRMC.

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0046 Diffusion Tensor Imaging Evidence of Hypothalamic Injury in Traumatic Brain Injury Warfighters with Sleep Dysfunction

SLEEP ◽

10.1093/sleep/zsaa056.045 ◽

2020 ◽

Vol 43 (Supplement_1) ◽

pp. A19-A19

Author(s):

K Werner ◽

B Gerstenslager ◽

P Yeh ◽

R Srikanchana ◽

K Kenney ◽

...

Keyword(s):

Traumatic Brain Injury ◽

Brain Injury ◽

Sleep Quality ◽

Linear Models ◽

Diffusion Tensor ◽

Small Sample Size ◽

Small Sample ◽

Poor Sleep ◽

Sleep Dysfunction ◽

California Institute Of Technology

Abstract Introduction While sleep disorders occur in 40–70% of chronic traumatic brain injury (TBI) patients, the pathophysiology remains unknown. Increasingly, DTI has been used to evaluate gray matter structures, but no prior studies have evaluated hypothalamic regions in TBI. We hypothesized that TBI patients with poor sleep quality by questionnaire and/or polysomnography (PSG) may have structural injury to hypothalamic sleep circuitry and that this may be detectable by diffusion magnetic resonance imaging (dMRI). We examined diffusion tensor parameters in warfighters using dMRI within the hypothalamus of poor sleepers and compared them to good sleepers. Methods A retrospective review of 92 warfighters with blast TBI and loss of consciousness included demographics, structural MRI, dMRI, PSG and Pittsburgh Sleep Quality Index (PSQI) questionnaire. Acquisition of diffusion-weighted and structural data was performed with three Tesla MRI. Using the California Institute of Technology probabilistic high-resolution in vivo atlas as a prior, the hypothalamic nuclei were segmented by applying diffeomorphic registration of T1- and T2-weighted structural images and mapped to dMRI space. Results TBI patients within the lowest quartile of hypothalamic fractional anisotropy (FA) measures demonstrated decreased total sleep time (320 +/- 52 minutes vs. 382 +/- 19, p=0.006) on PSG and had more sleep complaints on PSQI (p=0.029) compared to those with the highest quartile of FA measures. There was no difference in BMI, age or AHI among the quartiles. Radial, mean and axial diffusivity quartiles did not carry significant differences in TST or PSQI. Linear models did not show significant correlation between any imaging parameter and sleep quality measures. Conclusion Our results reveal microstructural differences in the hypothalami of military TBI patients that may be related to clinical sleep dysfunction. Biomarkers of sleep circuitry damage may further our understanding of sleep dysfunction after TBI. Lack of correlations in linear models may be a reflection of the small sample size or a complex interaction, and removal of outliers did not change our results. Larger longitudinal studies may help clarify the association between hypothalamic and brainstem circuitry structure after TBI and sleep dysfunction. Support This work was supported by a grant 130132 from USAMRMC.

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021 Poor sleep quality in traumatic brain injury patients is associated with elevated inflammatory biomarkers

SLEEP ◽

10.1093/sleep/zsab072.020 ◽

2021 ◽

Vol 44 (Supplement_2) ◽

pp. A10-A10

Author(s):

Josephine Pucci ◽

Sara Mithani ◽

Jacqueline Leete ◽

Chen Lai ◽

Kimbra Kenney ◽

...

Keyword(s):

Traumatic Brain Injury ◽

Brain Injury ◽

Sleep Quality ◽

Protein Quantification ◽

Model Systems ◽

Inflammatory Biomarkers ◽

Poor Sleep ◽

Type I ◽

Necrosis Factor Alpha ◽

Cross Sectional

Abstract Introduction Mild traumatic brain injury (mTBI) and sleep disorders are independently associated with inflammation. Following mTBI, elevated levels of cytokines, such as interleukin-6 (IL-6), 10 (IL-10) and tumor necrosis factor alpha (TNFα), have been observed. These signals are also known to modulate sleep homeostasis. IL-6, IL-10 and TNFα concentrations are typically measured in plasma, but recent work has shown that their measurement in extracellular vesicles (EVs) may hold additional value, as they are shielded from degradation and may be more biologically relevant. We hypothesized that inflammatory biomarkers in chronic mTBI patients would be elevated in poor sleepers. Methods In a cross-sectional cohort of warfighters (n=137 mTBI, 44 controls), the Pittsburgh Sleep Quality Index (PSQI) was compared with EV and plasma IL-6, IL-10, TNFα. Protein quantification was performed with Simoa. Two-tailed tests were used with a type I error of p<0.05. Linear models controlled for age, sex, and body mass index. Results In the mTBI cohort, poor sleepers (PSQI>=10, a published military cutoff) had elevated IL-6 vs. good sleepers (mean [SD] pg/mL, EV: 0.47 [0.63] vs 1.01 [1.54], p=0.04, d=0.44; plasma: 5.00 [13.31] vs 6.88 [13.51], p=0.03, d=0.14). Poor sleepers with mTBI had less EV IL-10 (1.71 [8.18] vs 0.30 [0.54], p=0.017). Comparisons of plasma IL-10 were not significant. No differences in TNFα were observed in mTBI groups. In our model, PSQI was the strongest predictor of EV IL-6 (βstd=0.27, p=0.03) in mTBI patients, whereas only BMI predicted IL-6 in controls. EV IL-6, IL-10, and TNFα correlated with PSQI (R=0.21, p=0.019; R=0.21, p=0.014; R=0.22, p=0.013, respectively), but these relationships were not found with plasma. In controls, no correlations or differences in any biomarker were observed between groups. Conclusion Warfighters who report poor sleep had significantly elevated inflammatory biomarkers after chronic mTBI. Cytokine levels in EVs had greater effect sizes between groups compared to plasma levels suggesting EV measurements may have improved signal. Poor sleep and its association with inflammatory cytokines after mTBI may have therapeutic implications. Support (if any) DoD: Contract W91YTZ-13-C-0015/ HT0014-19-C-0004 with VHA Central Office VA TBI Model Systems Program of Research/DHA Contracting Office (CO-NCR) HT0014

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Comprehensive insomnia assessment following mild traumatic brain injury

10.32920/ryerson.14646009.v1 ◽

2021 ◽

Author(s):

Dora M. Zalai

Keyword(s):

Traumatic Brain Injury ◽

Brain Injury ◽

Sleep Quality ◽

Sleep Disorders ◽

Mild Traumatic Brain Injury ◽

Primary Insomnia ◽

Chronic Insomnia ◽

Poor Sleep ◽

Wake Time ◽

Insomnia Symptoms

Background and Rationale: Insomnia symptoms following mild traumatic brain injury (mTBI) predict poor TBI outcomes. Insomnia symptoms may be caused by sleep disorders that can be effectively treated, which in turn, may improve mTBI outcomes. Previous studies have focused on insomnia symptom assessment in mTBI or evaluated samples with all TBI severities. To effectively manage insomnia following mTBI, it is important to understand which sleep disorders contribute to insomnia symptoms in this clinical group. Furthermore, it is important to extend research on primary insomnia to determine which variables are related to the perception of poor sleep among individuals who report new onset/worsening insomnia symptoms following mTBI. Objectives: (1) determine the prevalence of sleep disorders that contribute to chronic insomnia symptoms in patients with mTBI and (2) determine which objectively measured electroencephalographic and subjective variables are associated with subjective wake time and the perception of poor sleep among patients with chronic insomnia symptoms following mTBI. Methods: Individuals with chronic insomnia symptoms following mTBI (N = 50; age 17-65; 64% females; 3 - 24 months post mTBI) participated in a multi-method sleep and circadian assessment. Sleep disorders were diagnosed according to ICSD-3 criteria. Results: Insomnia disorder was the most common diagnosis (62%), followed by obstructive sleep apnea (OSA) -44%; circadian rhythm sleep-wake disorders (CRSWD) - 26% and periodic limb movement disorder (PLMD) - 8%. The overestimation of wake time was similar to what has been described in primary insomnia. In contrast to the REM instability hypothesis of primary insomnia, REM sleep duration was not related to subjective wake time. Both low sleep quality and feeling unrested in the morning had the strongest relationship to subjective wake time. Feeling unrested was also associated with anxiety. Conclusions: OSA and CRSWD frequently occur among patients whose main presenting sleep symptom is chronic insomnia following a mTBI. Accordingly, objective sleep and circadian assessment should be part of chronic insomnia evaluation following a mTBI. The results imply that interventions reducing subjective wake time and anxiety could improve subjective sleep quality; however, these interventions should be mplemented in conjunction with the treatment for OSA, CRSWD and PLMD.

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Comprehensive insomnia assessment following mild traumatic brain injury

10.32920/ryerson.14646009 ◽

2021 ◽

Author(s):

Dora M. Zalai

Keyword(s):

Traumatic Brain Injury ◽

Brain Injury ◽

Sleep Quality ◽

Sleep Disorders ◽

Mild Traumatic Brain Injury ◽

Primary Insomnia ◽

Chronic Insomnia ◽

Poor Sleep ◽

Wake Time ◽

Insomnia Symptoms

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Decreasing Incidence and Mortality in Traumatic Brain Injury in Korea, 2008–2017: A Population-Based Longitudinal Study

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph17176197 ◽

2020 ◽

Vol 17 (17) ◽

pp. 6197

Author(s):

Han-Kyoul Kim ◽

Ja-Ho Leigh ◽

Ye Seol Lee ◽

Yoonjeong Choi ◽

Yoon Kim ◽

...

Keyword(s):

Traumatic Brain Injury ◽

Brain Injury ◽

South Korea ◽

Age Groups ◽

Population Based ◽

Small Sample ◽

Health Concern ◽

Global Public Health ◽

Cross Sectional ◽

Incidence And Mortality

Traumatic brain injury (TBI), a global public health concern, may lead to death and major disability. While various short-term, small-sample, and cross-sectional studies on TBI have been conducted in South Korea, there is a lack of clarity on the nationwide longitudinal TBI trends in the country. This retrospective study investigated the epidemiological TBI trends in South Korea, using a population-based dataset of the National Health Insurance (2008–2017). The crude and age adjusted TBI incidence and mortality values were calculated and stratified by age, sex, and TBI diagnosis. The age-adjusted incidence per 100,000 people increased until 2010 and showed a decreasing trend (475.8 cases in 2017) thereafter; however, a continuously decreasing age-adjusted mortality trend was observed (42.9 cases in 2008, 11.3 in 2017). The crude incidence rate increased continually in those aged >70 years across all the TBI diagnostic categories. The mortality per 100,000 people was significantly higher among participants aged ≥70 years than in the other age groups. We observed changing trends in the TBI incidence, with a continuously decreasing overall incidence and a rapidly increasing incidence and high mortality values in older adults. Our findings highlight the importance of active TBI prevention in elderly people.

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Sleep Dysfunction is an Independent Predictor of Productivity Losses in Patients with Chronic Rhinosinusitis

Annals of Otology Rhinology & Laryngology ◽

10.1177/00034894211005986 ◽

2021 ◽

pp. 000348942110059

Author(s):

Gretchen M. Oakley ◽

Kristine A. Smith ◽

Shaelene Ashby ◽

Richard R. Orlandi ◽

Jeremiah A. Alt

Keyword(s):

Sleep Quality ◽

Chronic Rhinosinusitis ◽

Disease Severity ◽

Independent Predictor ◽

Cross Sectional ◽

Economic Productivity ◽

Sleep Dysfunction ◽

Productivity Losses ◽

Obstructive Sleep ◽

Lost Productivity

Background: Chronic rhinosinusitis (CRS) is known to have a significant impact on economic productivity. Sleep dysfunction is associated with staggering productivity losses and is highly prevalent in patients with CRS. The effect of sleep dysfunction on productivity in CRS has not been elucidated. The objective of this study was to determine the relationship between sleep dysfunction and lost productivity in patients with CRS. Methods: Eighty-two adult patients with CRS were prospectively enrolled into a cross-sectional cohort study. Patients with obstructive sleep apnea were excluded. Sleep quality was measured using the Pittsburgh Sleep Quality Index (PSQI). Presenteeism (reduced work efficiency), absenteeism (missed work days), and lost work, household, and overall productivity were analyzed. The primary aim was assessing the correlation between PSQI and productivity. Regression analyses were performed to account for disease severity, pain, and depression. Results: Sleep dysfunction is significantly correlated with overall lost productivity (R2 = 0.397, P < .05). Presenteeism is the most strongly affected by sleep dysfunction (R2 = –0.441, P < .001). Higher PSQI scores were significantly associated with productivity losses, whereas lower scores were not. Sleep remained an independent predictor of productivity when regression analysis accounted for disease severity, depression, and pain. Conclusion: Sleep dysfunction has a significant association with lost productivity in patients with CRS, particularly with worsening PSQI scores. More clearly defining those components of CRS that most impact a patient’s daily function will allow clinicians to more optimally manage and counsel patients with CRS.

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Poor sleep correlates with biomarkers of neurodegeneration in mild traumatic brain injury patients: a CENC Study

SLEEP ◽

10.1093/sleep/zsaa272 ◽

2020 ◽

Author(s):

J Kent Werner ◽

Pashtun Shahim ◽

Josephine U Pucci ◽

Lai Chen ◽

Sorana Raiciulescu ◽

...

Keyword(s):

Traumatic Brain Injury ◽

Executive Function ◽

Brain Injury ◽

Cognitive Function ◽

Sleep Quality ◽

Mild Traumatic Brain Injury ◽

Poor Sleep ◽

Neurofilament Light ◽

Therapeutic Implications ◽

Obstructive Sleep

Abstract Study Objectives Sleep disorders affect over half of mild traumatic brain injury (mTBI) patients. Despite evidence linking sleep and neurodegeneration, longitudinal TBI-related dementia studies have not considered sleep. We hypothesized that poor sleepers with mTBI would have elevated markers of neurodegeneration and lower cognitive function compared to mTBI good sleepers and controls. Our objective was to compare biomarkers of neurodegeneration and cognitive function with sleep quality in warfighters with chronic mTBI. Methods In an observational warfighters cohort (n=138 mTBI, 44 controls), the Pittsburgh Sleep Quality Index (PSQI) was compared with plasma biomarkers of neurodegeneration and cognitive scores collected an average of 8 years after injury. Results In the mTBI cohort, poor sleepers (PSQI≥10, n = 86) had elevated plasma neurofilament light (NfL, x̅ = 11.86 vs. 7.91 pg/mL, p=0.0007, d=0.63) and lower executive function scores by the categorical fluency (x̅ = 18.0 vs 21.0, p=0.0005, d= -0.65) and stop-go tests (x̅ = 30.1 vs 31.1, p=0.024, d = -0.37). These findings were not observed in controls (n = 44). PSQI predicted NfL (Beta=0.22, p=0.00002) and tau (Beta=0.14, p=0.007), but not amyloid β42. Poor sleepers showed higher obstructive sleep apnea (OSA) risk by STOP-BANG scores (x̅ = 3.8 vs 2.7, p=0.0005), raising the possibility that the PSQI might be partly secondary to OSA. Conclusions Poor sleep is linked to neurodegeneration and select measures of executive function in mTBI patients. This supports implementation of validated sleep measures in longitudinal studies investigating pathobiological mechanisms of TBI related neurodegeneration, which could have therapeutic implications.

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