The research appears in an online supplement of the journal, Sleep. These abstracts are available for immediate media coverage.
PRESENTATIONS
Tuesday, June 10
11:45 a.m. - 12:45 p.m. Pacific (2:45 - 3:45 p.m. Eastern)
3AB
Lunch Debate-02: Does the Failure of Brain Cleaning During Sleep Really Cause Alzheimer’s Disease?
Presenter: Andrew W. Varga, MD, PhD, Associate Professor of Medicine (Pulmonary, Critical Care and Sleep Medicine) at the Icahn School of Medicine at Mount Sinai
Wednesday, June 11
3:30 – 5:30 p.m. Pacific (6:30 – 9:30 p.m. Eastern)
Ballroom 6B
Symposia-32: Updates on Biomarkers in RBD: Neurophysiology, Actigraphy, and Biofluid Markers
Presenter: Emmanuel During, MD, Associate Professor of Neurology (Movement Disorders) and Medicine (Pulmonary Medicine, Critical Care and Sleep Medicine) at the Icahn School of Medicine at Mount Sinai
3:30 – 5:30 p.m. Pacific (6:30 – 8:30 p.m. Eastern)
Ballroom 6E
Symposia-33: Impact of Obstructive Sleep Apnea on Neurodegenerative & Alzheimer’s Disease Pathogenesis: Examining Physiologic, Race, and Sex Specific Mechanisms
Presenters: Korey Kam, PhD, Assistant Professor of Medicine (Pulmonary, Critical Care and Sleep Medicine) at the Icahn School of Medicine at Mount Sinai; Anna Mullins, PhD, Assistant Professor of Medicine (Pulmonary, Critical Care and Sleep Medicine) at the Icahn School of Medicine at Mount Sinai
POSTERS
0112: Impact of REM OSA and Hypoxic Burden on Sleep-Dependent Spatial Navigational memory and White Matter Integrity in Cognitively Normal Elderly with OSA
Anjona Datta, MA, Graduate Student at the Icahn School of Medicine at Mount Sinai; Daphne Valencia, MA, Research Manager at the Mount Sinai Integrative Sleep Center
Overnight sleep enhances spatial navigational performance, but such benefits may be minimized by obstructive sleep apnea (OSA). In this study, the researchers aimed to explore whether REM-specific OSA (REM AHI4%) and Hypoxic Burden (HB) influence overnight task performance differentially compared to standardly-defined presence/absence of OSA, and investigate associations between these sleep apnea variables and diffusion tensor imaging (DTI) metrics of white matter integrity in brain regions critical for memory consolidation. 0114: Role of Encoding Opportunity and Change in Slow Wave Activity Across K-complexes on Sleep-Dependent Spatial Navigational Memory in Older Adults
Anna Mullins, PhD, Assistant Professor of Medicine (Pulmonary, Critical Care and Sleep Medicine) at the Icahn School of Medicine at Mount Sinai
While younger adults show significant overnight spatial navigational memory (SNM) performance gains, older adults exhibit attenuated improvements, possibly due to reduced slow wave activity (SWA) during non-REM sleep. Older adults may show equivalent offline gains to younger adults if provided an enhanced encoding opportunity. This study examined whether increased encoding opportunities enhance SNM consolidation in cognitively normal older adults. The researchers additionally probed whether particular features of sleep microstructure correlated with overnight change in performance. 0135: Effects of Early-Adulthood Sleep Disruption on Longitudinal Spatial Learning, Neuroinflammation, and Late-Life Tau Pathology in the PS19 Mouse Model
Kerly Lozano, BA, Graduate Student at the Icahn School of Medicine at Mount Sinai
Sleep disruption is thought to exacerbate tau hyperphosphorylation and neurodegeneration. This study aims to investigate how early-adulthood sleep disruption (SD) affects late life spatial memory, tau pathology, neurodegeneration, neuroinflammation, and sleep architecture in PS19 tauopathy mice. 0460: A Foundational Transformer Leveraging Full-Night, Multichannel Sleep Study Representations Estimate Cardiovascular Mortality Risk
Benjamin Fox, MS, Graduate Student at the Icahn School of Medicine at Mount Sinai; Sajila Wickramaratne, PhD, Associate Scientist at the Icahn School of Medicine at Mount Sinai,
Sleep disorders and deprivation disrupt daily activities, mental health, and longevity and are closely linked to cardiovascular disease, which accounts for 33% of global deaths. Early detection and management of cardiovascular disease are critical for mitigating risk. Polysomnography (PSG) offers valuable data for assessing cardiovascular risk due to the relationship between sleep disorders, such as obstructive sleep apnea, and cardiovascular disease. PSG involves collecting electrophysiological data during sleep, which is manually annotated for staging, cardiac, and respiratory events. Cohort datasets, such as the Sleep Heart Health Study (SHHS), also provide long-term health outcome labels. Advanced machine-learning models, such as the transformer (the model behind ChatGPT), are well-suited for modeling time series data and can learn multichannel signal representations via self-supervision. These representations can be leveraged to predict risk for various outcomes, including cardiovascular disease, by training of an additional classifier model. 0604: Arousal threshold estimated by phenotyping using polysomnography is lower using automated arousal scoring compared to manual arousal scoring
Thomas M. Tolbert, MD, Assistant Professor of Medicine (Pulmonary, Critical Care and Sleep Medicine) at the Icahn School of Medicine at Mount Sinai
Phenotyping using polysomnography (PUP) is a computer-based method for “endotyping” obstructive sleep apnea (OSA) using clinical sleep study data. PUP provides estimates of mechanisms causing upper airway collapse in sleep: arousal threshold (ArTH), loop gain, and upper airway collapsibility and muscle response. PUP analyses have typically depended on manual scoring of sleep stages, respiratory events, and arousals. However, PUP has an automated arousal scoring capability based on electroencephalography (EEG) power analysis. The researchers hypothesized that automated arousal scoring may produce systematic differences in ArTH estimates compared to manual arousal scoring. 0606: Demographic Differences in the Physiological Burdens of Sleep Apnea
Sarah Chu, MS, Clinical Research Coordinator at the Icahn School of Medicine at Mount Sinai
Diagnosis of obstructive sleep apnea (OSA) depends on the Apnea-Hypopnea Index (AHI), a metric with acknowledged limitations, but known variation across demographic groups. Novel methodologies may better quantify OSA pathophysiology, but differences in these metrics across age, sex, and race/ethnicity remain yet to be explored. Leveraging data from the Sleep Heart Health Study and the Multi-Ethnic Study of Atherosclerosis, the researchers investigated potential variations in the emerging physiological metrics of OSA across participant demographics. 0612: OSA influences locus coeruleus structural integrity on 7T MRI in cognitively normal older adults
Korey Kam, PhD, Assistant Professor of Medicine (Pulmonary, Critical Care and Sleep Medicine) at the Icahn School of Medicine at Mount Sinai
The locus coeruleus (LC), an important sleep/wake regulating structure and site of early change in neurodegenerative disease, is best measured in humans with ultra-high field 7-Tesla MRI, due to its small size. The researchers hypothesize that obstructive sleep apnea (OSA) would negatively influence LC structural integrity and volume in cognitively normal elderly individuals. 0619: Shallower sleep by odds ratio product is associated with low arousal threshold when adjusted for confounding obstructive sleep apnea severity
Thomas M. Tolbert, MD, Assistant Professor of Medicine (Pulmonary, Critical Care and Sleep Medicine) at the Icahn School of Medicine at Mount Sinai
Odds ratio product (ORP) is an electroencephalography-based method for capturing sleep depth. Higher OR indicates greater probability of sleep interruption by wakefulness (“shallower sleep”). A potential source of sleep interruption is arousal in response to respiratory events due to obstructive sleep apnea (OSA). Phenotyping using polysomnography (PUP) is a computer-based method to estimate the mechanisms contributing to OSA from routine sleep study data. The researchers hypothesized that shallower sleep (higher ORP) would be associated with easier arousal by respiratory events (low PUP-estimated ArTH). 0690: Examining the diagnostic validity of PAT device against concurrent nocturnal polysomnography recording in a community dwelling cohort of older adults
Daphne Valencia, MA, Research Manager at the Mount Sinai Integrative Sleep Center
In a cohort of community dwelling participants, the researchers previously showed a modest correlation for obstructive sleep apnea (OSA) severity between WatchPAT™(WP) and polysomnography used on separate night recordings. Given the known night-to-night variability in OSA, the researchers reassess the diagnostic validity of simultaneous peripheral arterial tonometry and polysomnography. 1127: Actigraphy-Based Sleep Irregularity Measures and Cardiometabolic Imaging Biomarkers Using PET/MRI: A Descriptive Analysis
Bolong Xu, MD, Resident Physician at Mount Sinai Hospital
There is mounting evidence that irregular sleep patterns are associated with impaired cardiometabolic health. However, few studies have explored this link independent of obstructive sleep apnea (OSA), an important confounder in this relationship. Here, the researchers report a descriptive analysis of their study, investigating the link between irregular sleep, vascular inflammation, and abdominal adiposity in a cohort of patients without significant OSA. 1157: The Impact of Chronic Rhinosinusitis on Insomnia Symptoms and Sleep Duration in World Trade Center Rescue and Recovery Workers
Horacio Romero Castillo, BA, Graduate Student at the Icahn School of Medicine at Mount Sinai
Chronic rhinosinusitis (CRS) is highly prevalent in World Trade Center rescue and recovery workers and was found to be a significant risk factor for shorter subjective sleep duration, sleepiness, sleep quality, and insomnia. Symptoms of CRS such as facial pain, congestion, and rhinorrhea may impair patients’ ability to fall asleep and stay asleep. The purpose of this study is to compare objective sleep duration and variability, sleepiness, and insomnia symptoms in patients with and without CRS. 1271: Cognitive impairment and sleep disturbances in World Trade Center (WTC) rescue and recovery workers and volunteers
Katarina Martillo, BA, Clinical Research Coordinator at Icahn School of Medicine at Mount Sinai
World Trade Center rescue and recovery workers and volunteers have elevated levels of poor sleep quality, insomnia symptoms and obstructive sleep apnea (OSA). Increasing evidence of early onset of cognitive deficits in some of these workers highlights the importance of early identification of cognitive impairment. The researchers aim to describe cognitive impairment in this heterogeneous population with a broad range of education levels using multiple assessment methods and investigate potential relationships between cognition and sleep disturbance. 1253: Prevalence of Psychiatric Conditions in a Large Sleep Clinic Population
Ankit Parekh, PhD, Director of the Sleep And Circadian Analysis (SCAN) Group and Assistant Professor of Medicine (Pulmonary, Critical Care and Sleep Medicine) at the Icahn School of Medicine at Mount Sinai
Psychiatric conditions often affect sleep, and sleep disorders can also affect mental health. The prevalence of psychiatric conditions in patients evaluated for sleep disorders is not well-established. This study reviews electronic medical records (EMRs) from a major metropolitan health system to assess the burden of psychiatric conditions in patients with suspected sleep disorders who underwent nocturnal polysomnography. 1265: Relationship Between Self-Reported Sleep Disturbances and Cognition in Older Chinese Americans: A Pilot Mediation Analysis
Li Zhou; MD, PhD, Postdoctoral Fellow at Icahn School of Medicine at Mount Sinai; Ankit Parekh, PhD, Director of the Sleep And Circadian Analysis (SCAN) Group and Assistant Professor of Medicine (Pulmonary, Critical Care and Sleep Medicine) at the Icahn School of Medicine at Mount Sinai
Sleep disturbance/disorders are common among immigrants in the United States, yet few studies focus on older Chinese Americans and their link to Alzheimer’s Disease and Alzheimer’s Disease Related Dementias (AD/ADRD). While physical and mental health are known to affect cognition, it is unclear whether they mediate the relationship between sleep disturbances and cognition. This study aimed to: 1) investigate the association between self-reported sleep disturbances and both objective and subjective cognitive functions in older Chinese Americans; and 2) explore whether this relationship is mediated by immigration experiences or physical and mental health. 1272: Longitudinal effect of slow wave sleep on plasma Alzheimer's disease biomarkers in cognitively normal older adults
Daphne Valencia, MA, Research Manager at the Mount Sinai Integrative Sleep Center
There has been emerging evidence on the bidirectional relationship between sleep and Alzheimer’s disease (AD) pathology. However, there has been sparse data using plasma AD biomarkers despite its advantages of high accessibility and safety when sampling. This study aims to examine the longitudinal effect of slow wave sleep on plasma beta-amyloid (Aβ) 42/40 ratio and phosphorylated-tau 217 (p-tau 217) in cognitively normal older adults. 1307: External Validation of Actigraphy-based iRBD Classifier Using a Different Actigraph
Emmanuel During, MD, Associate Professor of Neurology (Movement Disorders) and Medicine (Pulmonary Medicine, Critical Care and Sleep Medicine) at the Icahn School of Medicine at Mount Sinai
Wrist-worn actigraphs have shown significant promise in detecting isolated REM sleep behavior disorder (iRBD). The researchers previously developed a fully automated classifier for iRBD in a cohort using the AX-6 device (1-s epochs), which achieved a sensitivity of 95.2% and specificity of 85.7% by analyzing motion data during the sleep period. However, its generalizability across populations and other actigraphy devices remains unclear. This study aimed to externally validate the previous iRBD classifier in the larger cohort using the Philips Actiwatch device (60-s epochs) (Actiwatch Spectrum Plus). LATE-BREAKING POSTERS
1597: Beyond CPAP Downloads: The Role of Effective AHI in Evaluating Treatment Burden
Joy Ayyoub, MBBCH, Sleep Medicine Fellow at the Mount Sinai Hospital; Korey Kam, PhD, Assistant Professor of Medicine (Pulmonary, Critical Care and Sleep Medicine) at the Icahn School of Medicine at Mount Sinai
The Apnea-Hypopnea index (AHI) obtained from continuous positive airway pressure (CPAP) downloads is the standard measure of OSA treatment efficacy, but does not include respiratory events occurring during sleep periods where CPAP is not used. This study aims to assess the validity and utility of calculating the effective AHI (eAHI) using data from actigraphy and CPAP downloads compared to a home sleep test. 1604: Automated Severity Rating of REM Sleep Behavior Disorder with Computer Vision
Emmanuel During, MD, Associate Professor of Neurology (Movement Disorders) and Medicine (Pulmonary Medicine, Critical Care and Sleep Medicine) at the Icahn School of Medicine at Mount Sinai
The severity of rapid eye movement (REM) sleep behavior disorder (RBD) symptoms is a key endpoint in clinical trials. To standardize assessment, the International RBD Study Group introduced a rating scale that classifies each movement as mild, moderate, or severe, assigning weights of 1, 5, and 10, respectively, to calculate a wholenight severity score. However, manual scoring is labor-intensive, time-consuming, and subject to inter-rater variability. This study aimed to develop an automated system for rating RBD severity using video recordings of REM sleep and computer vision, offering a more efficient and objective alternative to manual scoring. 1639: Screening for Idiopathic REM Sleep Behavior Disorder Using a Synucleinopathy Prodrome Questionnaire and Machine Learning
Emmanuel During, MD, Associate Professor of Neurology (Movement Disorders) and Medicine (Pulmonary Medicine, Critical Care and Sleep Medicine) at the Icahn School of Medicine at Mount Sinaii
Synucleinopathies, including Parkinson’s disease, dementia with Lewy Bodies, and Multiple System Atrophy are common yet challenging to detect in their prodromal stages. REM behavior disorder (RBD) is an early prodromal marker and strong predictor of synucleinopathy with >80% of patients phenoconverting within 10 years of diagnosis. A staged approach for screening RBD and prodromal synucleinopathy could combine a questionnaire on RBD symptoms plus (RBD+) other prodromes, followed in screen-positive individuals by further screening using wearables or biological markers. The goal in this study was to develop a machine learning (ML) classifier for detecting RBD+ as a first stage in such a screening paradigm.
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