Sex Differences in the Role of Sleep on Cognition in Older Adults

Study Objectives

The study aimed to investigate sex differences in the relationship between sleep quality (self-report and objective) and cognitive function across three domains (executive function, verbal memory, and attention) in older adults.

Methods

We analyzed cross-sectional data from 207 participants with normal cognition or mild cognitive impairment (89 males and 118 females) aged over 60. The relationship between sleep quality and cognitive performance was estimated using generalized additive models. Objective sleep was measured with the GT9X Link Actigraph, and self-reported sleep was measured with the Pittsburgh Sleep Quality Index.

Results

We found that females exhibited stable performance of executive function with up to about 400 minutes of total sleep time, with significant declines in performance (p = 0.02) when total sleep time was longer. Additionally, a longer total sleep time contributed to lower verbal memory in a slightly non-linear manner (p = 0.03). Higher self-reported sleep complaints were associated with poorer executive function in females with normal cognition (p = 0.02). In males, a positive linear relationship emerged between sleep efficiency and executive function (p = 0.04), while self-reported sleep was not associated with cognitive performance in males with normal cognition.

Conclusions

Our findings suggest that the relationships between sleep quality and cognition differ between older males and females, with executive function being the most influenced by objective and self-reported sleep. Interventions targeting sleep quality to mitigate cognitive decline in older adults may need to be tailored according to sex, with distinct approaches for males and females.

Design of a pragmatic randomized implementation effectiveness trial testing a health system wide hypertension program for older adults

Hypertension control remains poor. Multiple barriers at the level of patients, providers, and health systems interfere with implementation of hypertension guidelines and effective lowering of BP. Some strategies such as self-measured blood pressure (SMBP) and remote management by pharmacists are safe and effectively lower BP but have not been effectively implemented. In this study, we combine such evidence-based strategies to build a remote hypertension program and test its effectiveness and implementation in large health systems. This randomized, controlled, pragmatic type I hybrid implementation effectiveness trial will examine the virtual collaborative care clinic (vCCC), a hypertension program that integrates automated patient identification, SMBP, remote BP monitoring by trained health system pharmacists, and frequent patient-provider communication. We will randomize 1000 patients with uncontrolled hypertension from two large health systems in a 1:1 ratio to either vCCC or control (usual care with education) groups for a 2-year intervention. Outcome measures including BP measurements, cognitive function, and a symptom checklist will be completed during study visits. Other outcome measures of cardiovascular events, mortality, and health care utilization will be assessed using Medicare data. For the primary outcome of proportion achieving BP control (defined as systolic BP < 130 mmHg) in the two groups, we will use a generalized linear mixed model analysis. Implementation outcomes include acceptability and feasibility of the program. This study will guide implementation of a hypertension program within large health systems to effectively lower BP.

Positive Airway Pressure Therapy Predicts Lower Mortality and Major Adverse Cardiovascular Events Incidence in Medicare Beneficiaries with Obstructive Sleep Apnea

Background

Obesity is associated with obstructive sleep apnea (OSA) and cardiovascular risk. Positive airway pressure (PAP) is the first line treatment for OSA, but evidence on its beneficial effect on major adverse cardiovascular events (MACE) prevention is limited. Using claims data, the effects of PAP on mortality and incidence of MACE among Medicare beneficiaries with OSA were examined.

Methods

A cohort of Medicare beneficiaries with ≥2 distinct OSA claims was defined from multi-state, state-wide, multi-year (2011-2020) Medicare fee-for-service claims data. Evidence of PAP initiation and utilization was based on PAP claims after OSA diagnosis. MACE was defined as a composite of myocardial infarction, heart failure, stroke, or coronary revascularization. Doubly robust Cox proportional hazards models with inverse probability of treatment weights estimated treatment effects controlling for sociodemographic and clinical factors.

Results

Among 888,835 beneficiaries with OSA (median age 73 years; 43.9% women; median follow-up 1,141 days), those with evidence of PAP initiation (32.6%) had significantly lower all-cause mortality (HR [95%CI]: 0.53 [0.52-0.54]) and MACE incidence risk (0.90 [0.89-0.91]). Higher quartiles of annual PAP claims were progressively associated with lower mortality (Q2: 0.84 [0.81-0.87], Q3: 0.76 [0.74-0.79], Q4: 0.74 [0.72-0.77]) and MACE incidence risk (Q2: 0.92 [0.89-0.95], Q3: 0.89 [0.86-0.91], Q4: 0.87 [0.85-0.90]).

Conclusion

PAP utilization was associated with lower all-cause mortality and MACE incidence among Medicare beneficiaries with OSA. Results might inform trials assessing the importance of OSA therapy towards minimizing cardiovascular risk and mortality in older adults.

Loop Gain as a Predictor of Blood Pressure Response in Patients Treated for Obstructive Sleep Apnea: Secondary Analysis of a Clinical Trial

Rationale: Randomized trials have shown inconsistent cardiovascular benefits from obstructive sleep apnea (OSA) therapy. Intermittent hypoxemia can increase both sympathetic nerve activity and loop gain ("ventilatory instability"), which may thus herald cardiovascular treatment benefit. Objectives: To test the hypothesis that loop gain predicts changes in 24-hour mean blood pressure (MBP) in response to OSA therapy and compare its predictive value against that of other novel biomarkers. Methods: The HeartBEAT (Heart Biomarker Evaluation in Apnea Treatment) trial assessed the effect of 12 weeks of continuous positive airway pressure (CPAP) versus oxygen versus control on 24-hour MBP. We measured loop gain and hypoxic burden from sleep tests and identified subjects with a sleepy phenotype using cluster analysis. Associations between biomarkers and 24-h MBP were assessed in the CPAP/oxygen arms using linear regression models adjusting for various covariates. Secondary outcomes and predictors were analyzed similarly. Results: We included 93 and 94 participants in the CPAP and oxygen arms, respectively. Overall, changes in 24-hour MBP were small, but interindividual variability was substantial (mean [standard deviation], -2 [8] and 1 [8] mm Hg in the CPAP and oxygen arms, respectively). Higher loop gain was significantly associated with greater reductions in 24-hour MBP independent of covariates in the CPAP arm (-1.5 to -1.9 mm Hg per 1-standard-deviation increase in loop gain; P ⩽ 0.03) but not in the oxygen arm. Other biomarkers were not associated with improved cardiovascular outcomes. Conclusions: To our knowledge, this is the first study suggesting that loop gain predicts blood pressure response to CPAP therapy. Eventually, loop gain estimates may facilitate patient selection for research and clinical practice. Clinical trial registered with www.clinicaltrials.gov (NCT01086800).

Obstructive sleep apnea heterogeneity and autonomic function: a role for heart rate variability in therapy selection and efficacy monitoring

Obstructive sleep apnea is a highly prevalent sleep-related breathing disorder, resulting in a disturbed breathing pattern, changes in blood gases, abnormal autonomic regulation, metabolic fluctuation, poor neurocognitive performance, and increased cardiovascular risk. With broad inter-individual differences recognised in risk factors, clinical symptoms, gene expression, physiological characteristics, and health outcomes, various obstructive sleep apnea subtypes have been identified. Therapeutic efficacy and its impact on outcomes, particularly for cardiovascular consequences, may also vary depending on these features in obstructive sleep apnea. A number of interventions such as positive airway pressure therapies, oral appliance, surgical treatment, and pharmaceutical options are available in clinical practice. Selecting an effective obstructive sleep apnea treatment and therapy is a challenging medical decision due to obstructive sleep apnea heterogeneity and numerous treatment modalities. Thus, an objective marker for clinical evaluation is warranted to estimate the treatment response in patients with obstructive sleep apnea. Currently, while the Apnea-Hypopnea Index is used for severity assessment of obstructive sleep apnea and still considered a major guide to diagnosis and managements of obstructive sleep apnea, the Apnea-Hypopnea Index is not a robust marker of symptoms, function, or outcome improvement. Abnormal cardiac autonomic modulation can provide additional insight to better understand obstructive sleep apnea phenotyping. Heart rate variability is a reliable neurocardiac tool to assess altered autonomic function and can also provide cardiovascular information in obstructive sleep apnea. Beyond the Apnea-Hypopnea Index, this review aims to discuss the role of heart rate variability as an indicator and predictor of therapeutic efficacy to different modalities in order to optimise tailored treatment for obstructive sleep apnea.

Incident Coronary Calcium Score in Patients With OSA With and Without Excessive Sleepiness: Brazilian Longitudinal Study of Adult Health

BACKGROUND

Uncertainty exists about the impact of OSA and its phenotypes on cardiovascular disease.

RESEARCH QUESTION

Are OSA and clinical features such as daytime sleepiness associated with incident subclinical coronary atherosclerosis?

STUDY DESIGN AND METHODS

In this prospective community-based cohort study, we administered a sleepiness questionnaire, actigraphy, and home sleep studies at baseline. Coronary artery calcium (CAC; 64-slice multidetector CT scan imaging) was measured at two different time points throughout the study (baseline, between 2010 and 2014, and follow-up, between 2016 and 2018). Incidence of subclinical atherosclerosis was defined as baseline CAC of 0 followed by CAC of > 0 at a 5-year follow-up visit. The association of incident CAC outcome was assessed using logistic regression. Stratified analyses based on excessive daytime sleepiness (EDS) were performed.

RESULTS

We analyzed 1,956 participants with available CAC scores at baseline (mean age, 49 ± 8 years; 57.9% female; 32.4% with OSA). In covariate-adjusted analyses (n = 1,247; mean follow-up, 5.1 ± 0.9 years), we found a significant association between OSA and incidence of subclinical atherosclerosis (OR, 1.26; 95% CI, 1.06-1.48), with stronger effects among those reporting EDS (OR, 1.66; 95% CI, 1.30-2.12; P = .028 for interaction). Interestingly, EDS per se was not associated with any CAC outcome. An exploratory analysis of the square root of CAC progression (baseline CAC > 0 followed by a numerical increase in scores at follow-up; n = 319) showed a positive association for both OSA (β = 1.084; 95% CI, 0.032-2.136; P = .043) and OSA with EDS (β = 1.651; 95% CI, 0.208-3.094; P = .025).

INTERPRETATION

OSA, particularly with EDS, predicts the incidence and progression of CAC. These results support biological plausibility for the increased cardiovascular risk observed among patients with OSA with excessive sleepiness.

The relationship between alcohol- and sleep-related traits: Results from polygenic risk score and Mendelian randomization analyses

STUDY OBJECTIVES

We investigated whether genetic risk for insomnia and sleep duration abnormalities are associated with AUD and alcohol consumption. We also evaluated the causal relationships between sleep- and alcohol-related traits.

METHODS

Individual-level phenotype and genotype data from the Million Veteran Program were used. Polygenic risk scores (PRS) were computed using summary statistics from two recent discovery GWAS of insomnia (N= 453,379 European-ancestry (EA) individuals) and sleep duration (N= 446,118 EAs) and tested for association with lifetime AUD diagnosis (N= 34,658 EA cases) and past-year Alcohol Use Disorders Identification Test-Consumption scale scores (AUDIT-C, N= 200,680 EAs). Bi-directional two-sample Mendelian Randomization (MR) analyses assessed causal associations between the two sleep traits and the two alcohol-related traits.

RESULTS

The insomnia PRS was positively associated with AUD at 2/9 PRS thresholds, with p<0.01 being the most significant (OR = 1.02, p = 3.48 × 10-5). Conversely, insomnia PRS was negatively associated with AUDIT-C at 6/9 PRS thresholds (most significant threshold being p = 0.001 (β = -0.02, p = 5.6 × 10-8). Sleep duration PRS was positively associated with AUDIT-C at 2/9 PRS thresholds, with the most significant threshold being p = 1 × 10-6 (β = 0.01, p = 0.0009). MR analyses supported a significant positive causal effect of insomnia on AUD (14 SNPs; β = 104.14; SE = 16.19; p = 2.22 × 10-5), although with significant heterogeneity. MR analyses also showed that shorter sleep duration had a causal effect on the risk of AUD (27 SNPs; β = -63.05; SE = 3.54; p = 4.55 × 10-16), which was robust to sensitivity analyses.

CONCLUSION

The genetic risk for insomnia shows pleiotropy with AUD, and sleep continuity abnormalities have a causal influence on the development of AUD.

Risk of post-acute sequelae of SARS-CoV-2 infection associated with pre-coronavirus disease obstructive sleep apnea diagnoses: an electronic health record-based analysis from the RECOVER initiative

STUDY OBJECTIVES

Obstructive sleep apnea (OSA) has been associated with more severe acute coronavirus disease-2019 (COVID-19) outcomes. We assessed OSA as a potential risk factor for Post-Acute Sequelae of SARS-CoV-2 (PASC).

METHODS

We assessed the impact of preexisting OSA on the risk for probable PASC in adults and children using electronic health record data from multiple research networks. Three research networks within the REsearching COVID to Enhance Recovery initiative (PCORnet Adult, PCORnet Pediatric, and the National COVID Cohort Collaborative [N3C]) employed a harmonized analytic approach to examine the risk of probable PASC in COVID-19-positive patients with and without a diagnosis of OSA prior to pandemic onset. Unadjusted odds ratios (ORs) were calculated as well as ORs adjusted for age group, sex, race/ethnicity, hospitalization status, obesity, and preexisting comorbidities.

RESULTS

Across networks, the unadjusted OR for probable PASC associated with a preexisting OSA diagnosis in adults and children ranged from 1.41 to 3.93. Adjusted analyses found an attenuated association that remained significant among adults only. Multiple sensitivity analyses with expanded inclusion criteria and covariates yielded results consistent with the primary analysis.

CONCLUSIONS

Adults with preexisting OSA were found to have significantly elevated odds of probable PASC. This finding was consistent across data sources, approaches for identifying COVID-19-positive patients, and definitions of PASC. Patients with OSA may be at elevated risk for PASC after SARS-CoV-2 infection and should be monitored for post-acute sequelae.

Estimating sleep duration: performance of open-source processing of actigraphy compared to in-laboratory polysomnography in the community

Comparisons of actigraphy findings between studies are challenging given differences between brand-specific algorithms. This issue may be minimized by using open-source algorithms. However, the accuracy of actigraphy-derived sleep parameters processed in open-source software needs to be assessed against polysomnography (PSG). Middle-aged adults from the Raine Study (n = 835; F 58%; Age 56.7 ± 5.6 years) completed one night of in-laboratory PSG and concurrent actigraphy (GT3X+ ActiGraph). Actigraphic measures of total sleep time (TST) were analyzed and processed using the open-source R-package GENEActiv and GENEA data in R (GGIR) with and without a sleep diary and additionally processed using proprietary software, ActiLife, for comparison. Bias and agreement (intraclass correlation coefficient) between actigraphy and PSG were examined. Common PSG and sleep health variables associated with the discrepancy between actigraphy, and PSG TST were examined using linear regression. Actigraphy, assessed in GGIR, with and without a sleep diary overestimated PSG TST by (mean ± SD) 31.0 ± 50.0 and 26.4 ± 69.0 minutes, respectively. This overestimation was greater (46.8 ± 50.4 minutes) when actigraphy was analyzed in ActiLife. Agreement between actigraphy and PSG TST was poor (ICC = 0.27-0.44) across all three methods of actigraphy analysis. Longer sleep onset latency and longer wakefulness after sleep onset were associated with overestimation of PSG TST. Open-source processing of actigraphy in a middle-aged community population, agreed poorly with PSG and, on average, overestimated TST. TST overestimation increased with increasing wakefulness overnight. Processing of actigraphy without a diary in GGIR was comparable to when a sleep diary was used and comparable to actigraphy processed with proprietary algorithms in ActiLife.

Association Between Positive Airway Pressure Adherence and Health Care Costs Among Individuals With OSA

BACKGROUND

The impact of positive airway pressure (PAP) therapy for OSA on health care costs is uncertain.

RESEARCH QUESTION

Are 3-year health care costs associated with PAP adherence in participants from the Tele-OSA clinical trial?

STUDY DESIGN AND METHODS

Participants with OSA and prescribed PAP in the Tele-OSA study were stratified into three PAP adherence groups based on usage patterns over 3 years: (1) high (consistently ≥ 4 h/night), (2) moderate (2-3.9 h/night or inconsistently ≥ 4 h/night), and (3) low (< 2 h/night). Using data from 3 months of the Tele-OSA trial and 33 months of posttrial follow up, average health care costs (2020 US dollars) in 6-month intervals were derived from electronic health records and analyzed using multivariable generalized linear models.

RESULTS

Of 543 participants, 25% were categorized as having high adherence, 22% were categorized as having moderate adherence, and 52% were categorized as having low adherence to PAP therapy. Average PAP use mean ± SD was 6.5 ± 1.0 h, 3.7 ± 1.2 h, and 0.5 ± 0.5 h for the high, moderate, and low adherence groups, respectively. The high adherence group had the lowest average covariate-adjusted 6-month health care costs ± SE ($3,207 ± $251) compared with the moderate ($3,638 ± $363) and low ($4,040 ± $304) adherence groups. Significant cost differences were observed between the high and low adherence groups ($832; 95% CI, $127 to $1,538); differences between moderate and low adherence were nonsignificant ($401; 95% CI, -$441 to $1,243).

INTERPRETATION

In participants with OSA, better PAP adherence was associated with significantly lower health care costs over 3 years. Findings support the importance of strategies to enhance long-term PAP adherence.

Five-year Transitions of Symptom Subtypes in Untreated Obstructive Sleep Apnea

Objectives

It is unknown if symptom subtypes of obstructive sleep apnea (OSA) transition over time and what clinical factors may predict transitions.

Methods

Data from 2,643 participants of the Sleep Heart Health Study with complete baseline and 5-year follow-up visits were analyzed. Latent Class Analysis on 14 symptoms at baseline and follow up determined symptom subtypes. Individuals without OSA (AHI<5) were incorporated as a known class at each time point. Multinomial logistic regression assessed the effect of age, sex, body mass index (BMI) and AHI on specific class transitions.

Results

The sample consisted of 1,408 women (53.8%) and mean (SD) age 62.4 (10.5) years. We identified four OSA symptom subtypes at both baseline and follow-up visits: minimally symptomatic, disturbed sleep, moderately sleepy and excessively sleepy . Nearly half (44.2%) of the sample transitioned to a different subtype from baseline to follow-up visits; transitions to moderately sleepy were the most common (77% of all transitions). A five-year older age was associated with a 6% increase in odds to transit from excessively sleepy to moderately sleepy [OR (95% CI) = 1.06 (1.02, 1.12)]. Women had 2.35 times higher odds (95% CI: 1.27, 3.27) to transition from moderately sleepy to minimal symptoms . A 5-unit increase in BMI was associated with 2.29 greater odds (95% CI: 1.19, 4.38) to transition from minimal symptoms to excessively sleepy .

Interpretation

While over half of the sample did not transition their subtype over 5 years, among those who did, the likelihood of transitioning between subtypes was significantly associated with a higher baseline age, higher baseline BMI and with women, but was not predicted by AHI.

Clinical Trials

Sleep Heart Health Study (SHHS) Data Coordinating Center, (SHHS) https://clinicaltrials.gov/ct2/show/NCT00005275 , NCT00005275.

Statement of significance

There is very little research assessing symptom progression and its contributions to clinical heterogeneity in OSA. In a large sample with untreated OSA, we grouped common OSA symptoms into subtypes and assessed if age, sex, or BMI predicted transitions between the subtypes over 5 years. Approximately half the sample transitioned to a different symptom subtype and improvements in symptom subtype presentation were common. Women and older individuals were more likely to transition to less severe subtypes, while increased BMI predicted transition to more severe subtype. Determining whether common symptoms like disturbed sleep or excessive daytime sleepiness occur early in the course of the disease or as a result of untreated OSA over an extended period can improve clinical decisions concerning diagnosis and treatment.

Cost-effectiveness of a 3-year tele-messaging intervention for positive airway pressure use

OBJECTIVES

To evaluate the cost-effectiveness of a 3-year tele-messaging intervention for positive airway pressure (PAP) use in obstructive sleep apnea (OSA).

STUDY DESIGN

A post hoc cost-effectiveness analysis (from US payers' perspective) of data from a 3-month tele-OSA trial, augmented with 33 months of epidemiologic follow-up.

METHODS

Cost-effectiveness was compared among 3 groups of participants with an apnea-hypopnea index of at least 15 events/hour: (1) no messaging (n = 172), (2) messaging for 3 months (n = 124), and (3) messaging for 3 years (n = 46). We report the incremental cost (2020 US$) per incremental hour of PAP use and the fraction probability of acceptability based on a willingness-to-pay threshold of $1825 per year ($5/day).

RESULTS

The use of 3 years of messaging had similar mean annual costs ($5825) compared with no messaging ($5889; P = .89) but lower mean cost compared with 3 months of messaging ($7376; P = .02). Those who received messaging for 3 years had the highest mean PAP use (4.11 hours/night), followed by no messaging (3.03 hours/night) and 3 months of messaging (2.84 hours/night) (all P < .05). The incremental cost-effectiveness ratios indicated that 3 years of messaging showed lower costs and greater hours of PAP use compared with both no messaging and 3 months of messaging. Based on a willingness-to-pay threshold of $1825, there is a greater than 97.5% chance (ie, 95% confidence) that 3 years of messaging is acceptable compared with the other 2 interventions.

CONCLUSIONS

Long-term tele-messaging is highly likely to be cost-effective compared with both no and short-term messaging, with an acceptable willingness-to-pay threshold. Future long-term cost-effectiveness studies in a randomized controlled trial setting are warranted.

Implementing a home-based virtual hypertension programme-a pilot feasibility study

INTRODUCTION

Implementing a health system-based hypertension programme may lower blood pressure (BP).

METHODS

We performed a randomized, controlled pilot study to assess feasibility, acceptability, and safety of a home-based virtual hypertension programme integrating evidence-based strategies to overcome current barriers to BP control. Trained clinical pharmacists staffed the virtual collaborative care clinic (vCCC) to remotely manage hypertension using a BP dashboard and phone "visits" to monitor BP, adherence, side effects of medications, and prescribe anti-hypertensives. Patients with uncontrolled hypertension were identified via electronic health records. Enrolled patients were randomized to either vCCC or usual care for 3 months. We assessed patients' home BP monitoring behaviour, and patients', physicians', and pharmacists' perspectives on feasibility and acceptability of individual programme components.

RESULTS

Thirty-one patients (vCCC = 17, usual care = 14) from six physician clinics completed the pilot study. After 3 months, average BP decreased in the vCCC arm (P = 0.01), but not in the control arm (P = 0.45). The vCCC participants measured BP more (9.9 vs. 1.2 per week, P < 0.001). There were no intervention-related adverse events. Participating physicians (n = 6), pharmacists (n = 5), and patients (n = 31) rated all programme components with average scores of >4.0, a pre-specified benchmark. Nine adaptations in vCCC design and delivery were made based on potential barriers to implementing the programme and suggestions.

CONCLUSION

A home-based virtual hypertension programme using team-based care, technology, and a logical integration of evidence-based strategies is safe, acceptable, and feasible to intended users. These pilot data support studies to assess the effectiveness of this programme at a larger scale.

Variant-to-gene mapping followed by cross-species genetic screening identifies GPI-anchor biosynthesis as a regulator of sleep

Genome-wide association studies (GWAS) in humans have identified loci robustly associated with several heritable diseases or traits, yet little is known about the functional roles of the underlying causal variants in regulating sleep duration or quality. We applied an ATAC-seq/promoter focused Capture C strategy in human iPSC-derived neural progenitors to carry out a "variant-to-gene" mapping campaign that identified 88 candidate sleep effector genes connected to relevant GWAS signals. To functionally validate the role of the implicated effector genes in sleep regulation, we performed a neuron-specific RNA interference screen in the fruit fly, Drosophila melanogaster, followed by validation in zebrafish. This approach identified a number of genes that regulate sleep including a critical role for glycosylphosphatidylinositol (GPI)-anchor biosynthesis. These results provide the first physical variant-to-gene mapping of human sleep genes followed by a model organism-based prioritization, revealing a conserved role for GPI-anchor biosynthesis in sleep regulation.

Symptom subtypes and risk of incident cardiovascular and cerebrovascular disease in a clinic-based obstructive sleep apnea cohort

STUDY OBJECTIVES

Patients with obstructive sleep apnea (OSA) are at increased risk of cardiovascular and cerebrovascular disease, but predicting those at greatest risk is challenging. Using latent class analysis, patients with OSA can be placed into discrete symptom subtypes. The aim of this study was to determine whether symptom subtypes are associated with future cerebrovascular disease in patients with OSA in a clinic-based cohort.

METHODS

Patients with suspected OSA referred for a polysomnogram at an academic sleep center completed a comprehensive symptom survey. Patients with OSA (apnea-hypopnea index ≥ 5 events/h) were then placed into symptom subtypes based on responses to survey questions using latent class analysis. Cardiovascular events (stroke, myocardial infarction, unstable angina, bypass grafting, percutaneous coronary intervention, cardiac resynchronization therapy, defibrillation) occurring within 8 years of polysomnogram were identified by linkage to provincial health databases.

RESULTS

1,607 patients were studied, of whom 1,292 had OSA. One hundred forty first events occurred within 8 years of polysomnogram. Patients in the excessively sleepy with disturbed sleep subtype had a significantly increased rate of events compared to the minimally symptomatic subtype (hazard ratio = 2.25, 95% confidence interval: 1.02-4.94; P = .04). Two symptoms (restless legs and dozing off or sleeping while talking to someone) were significantly associated with future risk of cerebrovascular disease (hazard ratio = 1.68, 1.12-2.49 and 4.23, 1.61-11.16, respectively).

CONCLUSIONS

Patients with OSA in the clinic who are in the excessively sleepy with disturbed sleep subtype are significantly more likely to have a future cardiovascular event. This underscores the importance of understanding clinical heterogeneity and incorporating symptom subtype definitions into routine clinical care.

CITATION

Allen AJH, Jen R, Mazzotti DR, et al. Symptom subtypes and risk of incident cardiovascular and cerebrovascular disease in a clinic-based obstructive sleep apnea cohort. J Clin Sleep Med. 2022;18(9):2093-2102.

Calculating genetic risk for dysfunction in pleiotropic biological processes using whole exome sequencing data

BACKGROUND

Numerous genes are implicated in autism spectrum disorder (ASD). ASD encompasses a wide-range and severity of symptoms and co-occurring conditions; however, the details of how genetic variation contributes to phenotypic differences are unclear. This creates a challenge for translating genetic evidence into clinically useful knowledge. Sleep disturbances are particularly prevalent co-occurring conditions in ASD, and genetics may inform treatment. Identifying convergent mechanisms with evidence for dysfunction that connect ASD and sleep biology could help identify better treatments for sleep disturbances in these individuals.

METHODS

To identify mechanisms that influence risk for ASD and co-occurring sleep disturbances, we analyzed whole exome sequence data from individuals in the Simons Simplex Collection (n = 2380). We predicted protein damaging variants (PDVs) in genes currently implicated in either ASD or sleep duration in typically developing children. We predicted a network of ASD-related proteins with direct evidence for interaction with sleep duration-related proteins encoded by genes with PDVs. Overrepresentation analyses of Gene Ontology-defined biological processes were conducted on the resulting gene set. We calculated the likelihood of dysfunction in the top overrepresented biological process. We then tested if scores reflecting genetic dysfunction in the process were associated with parent-reported sleep duration.

RESULTS

There were 29 genes with PDVs in the ASD dataset where variation was reported in the literature to be associated with both ASD and sleep duration. A network of 108 proteins encoded by ASD and sleep duration candidate genes with PDVs was identified. The mechanism overrepresented in PDV-containing genes that encode proteins in the interaction network with the most evidence for dysfunction was cerebral cortex development (GO:0,021,987). Scores reflecting dysfunction in this process were associated with sleep durations; the largest effects were observed in adolescents (p = 4.65 × 10^-3).

CONCLUSIONS

Our bioinformatic-driven approach detected a biological process enriched for genes encoding a protein-protein interaction network linking ASD gene products with sleep duration gene products where accumulation of potentially damaging variants in individuals with ASD was associated with sleep duration as reported by the parents. Specifically, genetic dysfunction impacting development of the cerebral cortex may affect sleep by disrupting sleep homeostasis which is evidenced to be regulated by this brain region. Future functional assessments and objective measurements of sleep in adolescents with ASD could provide the basis for more informed treatment of sleep problems in these individuals.

Sleep and circadian informatics data harmonization: a workshop report from the Sleep Research Society and Sleep Research Network

The increasing availability and complexity of sleep and circadian data are equally exciting and challenging. The field is in constant technological development, generating better high-resolution physiological and molecular data than ever before. Yet, the promise of large-scale studies leveraging millions of patients is limited by suboptimal approaches for data sharing and interoperability. As a result, integration of valuable clinical and basic resources is problematic, preventing knowledge discovery and rapid translation of findings into clinical care. To understand the current data landscape in the sleep and circadian domains, the Sleep Research Society (SRS) and the Sleep Research Network (now a task force of the SRS) organized a workshop on informatics and data harmonization, presented at the World Sleep Congress 2019, in Vancouver, Canada. Experts in translational informatics gathered with sleep research experts to discuss opportunities and challenges in defining strategies for data harmonization. The goal of this workshop was to fuel discussion and foster innovative approaches for data integration and development of informatics infrastructure supporting multi-site collaboration. Key recommendations included collecting and storing findable, accessible, interoperable, and reusable data; identifying existing international cohorts and resources supporting research in sleep and circadian biology; and defining the most relevant sleep data elements and associated metadata that could be supported by early integration initiatives. This report introduces foundational concepts with the goal of facilitating engagement between the sleep/circadian and informatics communities and is a call to action for the implementation and adoption of data harmonization strategies in this domain.

Diabetes and cardiovascular diseases are associated with the worsening of intermittent hypoxaemia

Intermittent hypoxaemia is a risk factor for numerous diseases. However, the reverse pathway remains unclear. Therefore, we investigated whether pre-existing hypertension, diabetes or cardiovascular diseases are associated with the worsening of intermittent hypoxaemia. Among the included 2,535 Sleep Heart Health Study participants, hypertension (n = 1,164), diabetes (n = 170) and cardiovascular diseases (n = 265) were frequently present at baseline. All participants had undergone two polysomnographic recordings approximately 5.2 years apart. Covariate-adjusted linear regression analyses were utilized to investigate the difference in the severity of intermittent hypoxaemia at baseline between each comorbidity group and the group of participants free from all comorbidities (n = 1,264). Similarly, we investigated whether the pre-existing comorbidities are associated with the progression of intermittent hypoxaemia. Significantly higher oxygen desaturation index (β = 1.77 [95% confidence interval: 0.41-3.13], p = 0.011), desaturation severity (β = 0.07 [95% confidence interval: 0.00-0.14], p = 0.048) and desaturation duration (β = 1.50 [95% confidence interval: 0.31-2.69], p = 0.013) were observed in participants with pre-existing cardiovascular diseases at baseline. Furthermore, the increase in oxygen desaturation index (β = 3.59 [95% confidence interval: 1.78-5.39], p < 0.001), desaturation severity (β = 0.08 [95% confidence interval: 0.02-0.14], p = 0.015) and desaturation duration (β = 2.60 [95% confidence interval: 1.22-3.98], p < 0.001) during the follow-up were higher among participants with diabetes. Similarly, the increase in oxygen desaturation index (β = 2.73 [95% confidence interval: 1.15-4.32], p = 0.001) and desaturation duration (β = 1.85 [95% confidence interval: 0.62-3.08], p = 0.003) were higher among participants with cardiovascular diseases. These results suggest that patients with pre-existing diabetes or cardiovascular diseases are at increased risk for an expedited worsening of intermittent hypoxaemia. As intermittent hypoxaemia is an essential feature of sleep apnea, these patients could benefit from the screening and follow-up monitoring of sleep apnea.

Characterizing Long COVID: Deep Phenotype of a Complex Condition

BACKGROUND

Numerous publications describe the clinical manifestations of post-acute sequelae of SARS-CoV-2 (PASC or "long COVID"), but they are difficult to integrate because of heterogeneous methods and the lack of a standard for denoting the many phenotypic manifestations. Patient-led studies are of particular importance for understanding the natural history of COVID-19, but integration is hampered because they often use different terms to describe the same symptom or condition. This significant disparity in patient versus clinical characterization motivated the proposed ontological approach to specifying manifestations, which will improve capture and integration of future long COVID studies.

METHODS

The Human Phenotype Ontology (HPO) is a widely used standard for exchange and analysis of phenotypic abnormalities in human disease but has not yet been applied to the analysis of COVID-19.

FUNDING

We identified 303 articles published before April 29, 2021, curated 59 relevant manuscripts that described clinical manifestations in 81 cohorts three weeks or more following acute COVID-19, and mapped 287 unique clinical findings to HPO terms. We present layperson synonyms and definitions that can be used to link patient self-report questionnaires to standard medical terminology. Long COVID clinical manifestations are not assessed consistently across studies, and most manifestations have been reported with a wide range of synonyms by different authors. Across at least 10 cohorts, authors reported 31 unique clinical features corresponding to HPO terms; the most commonly reported feature was Fatigue (median 45.1%) and the least commonly reported was Nausea (median 3.9%), but the reported percentages varied widely between studies.

INTERPRETATION

Translating long COVID manifestations into computable HPO terms will improve analysis, data capture, and classification of long COVID patients. If researchers, clinicians, and patients share a common language, then studies can be compared/pooled more effectively. Furthermore, mapping lay terminology to HPO will help patients assist clinicians and researchers in creating phenotypic characterizations that are computationally accessible, thereby improving the stratification, diagnosis, and treatment of long COVID.

FUNDING

U24TR002306; UL1TR001439; P30AG024832; GBMF4552; R01HG010067; UL1TR002535; K23HL128909; UL1TR002389; K99GM145411.

Continuous positive airway pressure and adverse cardiovascular events in obstructive sleep apnea: are participants of randomized trials representative of sleep clinic patients?

STUDY OBJECTIVES

Randomized controlled trials (RCTs) have shown no reduction in adverse cardiovascular (CV) events in patients randomized to continuous positive airway pressure (CPAP) therapy for obstructive sleep apnea (OSA). This study examined whether randomized study populations were representative of OSA patients attending a sleep clinic.

METHODS

Sleep clinic patients were 3,965 consecutive adults diagnosed with OSA by in-laboratory polysomnography from 2006 to 2010 at a tertiary hospital sleep clinic. Characteristics of these patients were compared with participants of five recent RCTs examining the effect of CPAP on adverse CV events in OSA. The percentage of patients with severe (apnea-hypopnea index, [AHI] ≥ 30 events/h) or any OSA (AHI ≥ 5 events/h) who met the eligibility criteria of each RCT was determined, and those criteria that excluded the most patients identified.

RESULTS

Compared to RCT participants, sleep clinic OSA patients were younger, sleepier, more likely to be female and less likely to have established CV disease. The percentage of patients with severe or any OSA who met the RCT eligibility criteria ranged from 1.2% to 20.9% and 0.8% to 21.9%, respectively. The eligibility criteria that excluded most patients were preexisting CV disease, symptoms of excessive sleepiness, nocturnal hypoxemia and co-morbidities.

CONCLUSIONS

A minority of sleep clinic patients diagnosed with OSA meet the eligibility criteria of RCTs of CPAP on adverse CV events in OSA. OSA populations in these RCTs differ considerably from typical sleep clinic OSA patients. This suggests that the findings of such OSA treatment-related RCTs are not generalizable to sleep clinic OSA patients.Randomized Intervention with Continuous Positive Airway Pressure in CAD and OSA (RICCADSA) trial, https://clinicaltrials.gov/ct2/show/NCT00519597, ClinicalTrials.gov number, NCT00519597.Usefulness of Nasal Continuous Positive Airway Pressure (CPAP) Treatment in Patients with a First Ever Stroke and Sleep Apnea Syndrome, https://clinicaltrials.gov/ct2/show/NCT00202501, ClinicalTrials.gov number, NCT00202501.Effect of Continuous Positive Airway Pressure (CPAP) on Hypertension and Cardiovascular Morbidity-Mortality in Patients with Sleep Apnea and no Daytime Sleepiness, https://clinicaltrials.gov/ct2/show/NCT00127348, ClinicalTrials.gov number, NCT00127348.Continuous Positive Airway Pressure (CPAP) in Patients with Acute Coronary Syndrome and Obstructive Sleep Apnea (OSA) (ISAACC), https://clinicaltrials.gov/ct2/show/NCT01335087, ClinicalTrials.gov number, NCT01335087.

Landscape of biomedical informatics standards and terminologies for clinical sleep medicine research: A systematic review

A systematic literature review was conducted to understand the current landscape of standards and terminologies used in clinical sleep medicine. Literature search on PubMed, EMBASE, Medline and Web of Science was performed in March 2021 using terms related to sleep, terminologies, standards, harmonization, semantics, ontology, and electronic health records (EHR). Systematic review was carried out according to PRISMA. Among 128 included studies, 35 were eligible for review. Articles were broadly classified into six topics: standard terminology efforts, reporting standards, databases and resources, data integration efforts, EHR abstraction and standards for automated sleep scoring. This review highlights the progress and challenges related to establishing computable terminologies in sleep medicine, and identifies gaps, limitations and research opportunities related to data integration that could improve adoption of clinical research informatics in this field. There is a need for the systematic adoption of standardized terminologies in all areas of sleep medicine. Existing data aggregation resources could be leveraged to support the development of an integrated infrastructure and subsequent deployment in EHR systems within sleep centers. Ultimately, the adoption of standardized practices for documenting sleep disorders and related traits facilitates data sharing, thus accelerating discovery and clinical translation of informatics approaches applied to sleep medicine.

Characteristics and Reproducibility of Novel Sleep EEG Biomarkers and their Variation with Sleep Apnea and Insomnia in a Large Community-Based Cohort

STUDY OBJECTIVES

New EEG features became available for use in polysomnography and have shown promise in early studies. They include a continuous index of sleep depth (Odds-Ratio-Product; ORP), agreement between right and left sleep depth (R/L coefficient), dynamics of sleep recovery following arousals (ORP-9), general EEG amplification (EEG Power), alpha intrusion and arousal intensity. This study was undertaken to establish ranges and reproducibility of these features in subjects with different demographics and clinical status.

METHODS

We utilized data from the two phases of the Sleep-Heart-Health-Study (SHHS1 and SHHS2). Polysomnograms of 5804 subjects from SHHS1 were scored to determine the above features. Feature values were segregated according to clinical status of Obstructive Sleep Apnea (OSA), insomnia, insomnia plus OSA, no clinical sleep disorder, and demographics (age, gender and race). Results from SHHS visit2 were compared with SHHS1 results.

RESULTS

All features varied widely among clinical groups and demographics. Relative to participants with no sleep disorder, wake ORP was higher in participants reporting insomnia symptoms and lower in those with OSA (p<0.0001 for both), reflecting opposite changes in sleep pressure, while NREM ORP was higher in both insomnia and OSA (p<0.0001), reflecting lighter sleep in both groups. There were significant associations with age, gender, and race. EEG Power, and REM ORP were highly reproducible across the two studies (ICC>0.75).

CONCLUSIONS

The reported results serve as bases for interpreting studies that utilize novel sleep EEG biomarkers and identify characteristic EEG changes that vary with age, gender and may help distinguish insomnia from OSA.

Heart rate variability during wakefulness as a marker of obstructive sleep apnea severity

STUDY OBJECTIVES

Patients with obstructive sleep apnea (OSA) exhibit heterogeneous heart rate variability (HRV) during wakefulness and sleep. We investigated the influence of OSA severity on HRV parameters during wakefulness in a large international clinical sample.

METHODS

1247 subjects (426 without OSA and 821 patients with OSA) were enrolled from the Sleep Apnea Global Interdisciplinary Consortium. HRV parameters were calculated during a 5-minute wakefulness period with spontaneous breathing prior to the sleep study, using time-domain, frequency-domain and nonlinear methods. Differences in HRV were evaluated among groups using analysis of covariance, controlling for relevant covariates.

RESULTS

Patients with OSA showed significantly lower time-domain variations and less complexity of heartbeats compared to individuals without OSA. Those with severe OSA had remarkably reduced HRV compared to all other groups. Compared to non-OSA patients, those with severe OSA had lower HRV based on SDNN (adjusted mean: 37.4 vs. 46.2 ms; p < 0.0001), RMSSD (21.5 vs. 27.9 ms; p < 0.0001), ShanEn (1.83 vs. 2.01; p < 0.0001), and Forbword (36.7 vs. 33.0; p = 0.0001). While no differences were found in frequency-domain measures overall, among obese patients there was a shift to sympathetic dominance in severe OSA, with a higher LF/HF ratio compared to obese non-OSA patients (4.2 vs. 2.7; p = 0.009).

CONCLUSIONS

Time-domain and nonlinear HRV measures during wakefulness are associated with OSA severity, with severe patients having remarkably reduced and less complex HRV. Frequency-domain measures show a shift to sympathetic dominance only in obese OSA patients. Thus, HRV during wakefulness could provide additional information about cardiovascular physiology in OSA patients.

CLINICAL TRIAL INFORMATION

A Prospective Observational Cohort to Study the Genetics of Obstructive Sleep Apnea and Associated Co-Morbidities (German Clinical Trials Register - DKRS, DRKS00003966) https://www.drks.de/drks_web/navigate.do?navigationId=trial.HTML&TRIAL_ID=DRKS00003966.

Longer and Deeper Desaturations Are Associated With the Worsening of Mild Sleep Apnea: The Sleep Heart Health Study

Study Objectives

Obesity, older age, and male sex are recognized risk factors for sleep apnea. However, it is unclear whether the severity of hypoxic burden, an essential feature of sleep apnea, is associated with the risk of sleep apnea worsening. Thus, we investigated our hypothesis that the worsening of sleep apnea is expedited in individuals with more severe desaturations.

Methods

The blood oxygen saturation (SpO₂) signals of 805 Sleep Heart Health Study participants with mild sleep apnea [5 ≤ oxygen desaturation index (ODI) < 15] were analyzed at baseline and after a mean follow-up time of 5.2 years. Linear regression analysis, adjusted for relevant covariates, was utilized to study the association between baseline SpO₂-derived parameters and change in sleep apnea severity, determined by a change in ODI. SpO₂-derived parameters, consisting of ODI, desaturation severity (DesSev), desaturation duration (DesDur), average desaturation area (avg. DesArea), and average desaturation duration (avg. DesDur), were standardized to enable comparisons between the parameters.

Results

In the group consisting of both men and women, avg. DesDur (β = 1.594, p = 0.001), avg. DesArea (β = 1.316, p = 0.004), DesDur (β = 0.998, p = 0.028), and DesSev (β = 0.928, p = 0.040) were significantly associated with sleep apnea worsening, whereas ODI was not (β = -0.029, p = 0.950). In sex-stratified analysis, avg. DesDur (β = 1.987, p = 0.003), avg. DesArea (β = 1.502, p = 0.024), and DesDur (β = 1.374, p = 0.033) were significantly associated with sleep apnea worsening in men.

Conclusion

Longer and deeper desaturations are more likely to expose a patient to the worsening of sleep apnea. This information could be useful in the planning of follow-up monitoring or lifestyle counseling in the early stage of the disease.

Sleep classification from wrist-worn accelerometer data using random forests

Accurate and low-cost sleep measurement tools are needed in both clinical and epidemiological research. To this end, wearable accelerometers are widely used as they are both low in price and provide reasonably accurate estimates of movement. Techniques to classify sleep from the high-resolution accelerometer data primarily rely on heuristic algorithms. In this paper, we explore the potential of detecting sleep using Random forests. Models were trained using data from three different studies where 134 adult participants (70 with sleep disorder and 64 good healthy sleepers) wore an accelerometer on their wrist during a one-night polysomnography recording in the clinic. The Random forests were able to distinguish sleep-wake states with an F1 score of 73.93% on a previously unseen test set of 24 participants. Detecting when the accelerometer is not worn was also successful using machine learning ([Formula: see text]), and when combined with our sleep detection models on day-time data provide a sleep estimate that is correlated with self-reported habitual nap behaviour ([Formula: see text]). These Random forest models have been made open-source to aid further research. In line with literature, sleep stage classification turned out to be difficult using only accelerometer data.

Simple and Unbiased OSA Prescreening: Introduction of a New Morphologic OSA Prediction Score

PURPOSE

An early prescreening in suspected obstructive sleep apnea (OSA) patients is desirable to expedite diagnosis and treatment. However, the accuracy and applicability of current prescreening tools is insufficient. We developed and tested an unbiased scoring system based solely on objective variables, which focuses on the diagnosis of severe OSA and exclusion of OSA.

PATIENTS AND METHODS

The OSA prediction score was developed (n = 150) and validated (n = 50) within German sleep center patients that were recruited as part of the Sleep Apnea Global Interdisciplinary Consortium (SAGIC). Six objective variables that were easy to assess and highly correlated with the apnea-hypopnea index were chosen for the score, including some known OSA risk factors: body-mass index, neck circumference, waist circumference, tongue position, male gender, and age (for women only). To test the predictive ability of the score and identify score thresholds, the receiver-operating characteristics (ROC) and curve were calculated.

RESULTS

A score ≥8 for predicting severe OSA resulted in an area under the ROC curve (ROC-AUC) of 90% (95% confidence interval: 84%, 95%), test accuracy of 82% (75%, 88%), sensitivity of 82% (65%, 93%), specificity of 82% (74%, 88%), and positive likelihood ratio of 4.55 (3.00, 6.90). A score ≤5 for predicting the absence of OSA resulted in a ROC-AUC of 89% (83%, 94%), test accuracy of 80% (73%, 86%), sensitivity of 72% (55%, 85%), specificity of 83% (75%, 89%), and positive likelihood ratio of 4.20 (2.66, 6.61). Performance characteristics were comparable in the small validation sample.

CONCLUSION

We introduced a novel prescreening tool combining easily obtainable objective measures with predictive power and high general applicability. The proposed tool successfully predicted severe OSA (important due to its high risk of cardiovascular disease) and the exclusion of OSA (rarely a feature of previous screening instruments, but important for better differential diagnosis and treatment).

Reinventing polysomnography in the age of precision medicine

For almost 50 years, sleep laboratories around the world have been collecting massive amounts of polysomnographic (PSG) physiological data to diagnose sleep disorders, the majority of which are not utilized in the clinical setting. Only a small fraction of the information available within these signals is utilized to generate indices. For example, the apnea-hypopnea index (AHI) remains the primary tool for diagnostic and therapeutic decision-making for obstructive sleep apnea (OSA) despite repeated studies showing it to be inadequate in predicting clinical consequences. Today, there are many novel approaches to PSG signals, making it possible to extract more complex metrics and analyses that are potentially more clinically relevant for individual patients. However, the pathway to implement novel PSG metrics/analyses into routine clinical practice is unclear. Our goal with this review is to highlight some of the novel PSG metrics/analyses that are becoming available. We suggest that stronger academic-industry relationships would facilitate the development of state-of-the-art clinical research to establish the value of novel PSG metrics/analyses in clinical sleep medicine. Collectively, as a sleep community, it is time to reinvent how we utilize the polysomnography to move us towards Precision Sleep Medicine.

Characterization of genetic and phenotypic heterogeneity of obstructive sleep apnea using electronic health records

Background

Obstructive sleep apnea (OSA) is defined by frequent episodes of reduced or complete cessation of airflow during sleep and is linked to negative health outcomes. Understanding the genetic factors influencing expression of OSA may lead to new treatment strategies. Electronic health records (EHRs) can be leveraged to both validate previously reported OSA-associated genomic variation and detect novel relationships between these variants and comorbidities.

Methods

We identified candidate single nucleotide polymorphisms (SNPs) via systematic literature review of existing research. Using datasets available at Geisinger (n = 39,407) and Vanderbilt University Medical Center (n = 24,084), we evaluated associations between 40 previously implicated SNPs and OSA diagnosis, defined using clinical codes. We also evaluated associations between these SNPs and OSA severity measures obtained from sleep reports at Geisinger (n = 6571). Finally, we used a phenome-wide association study approach to help reveal pleiotropic genetic effects between OSA candidate SNPs and other clinical codes and laboratory values available in the EHR.

Results

Most previously reported OSA candidate SNPs showed minimal to no evidence for associations with OSA diagnosis or severity in the EHR-derived datasets. Three SNPs in LEPR, MMP-9, and GABBR1 validated for an association with OSA diagnosis in European Americans; the SNP in GABBR1 was associated following meta-analysis of results from both clinical populations. The GABBR1 and LEPR SNPs, and one additional SNP, were associated with OSA severity measures in European Americans from Geisinger. Three additional candidate OSA SNPs were not associated with OSA-related traits but instead with hyperlipidemia and autoimmune diseases of the thyroid.

Conclusions

To our knowledge, this is one of the largest candidate gene studies and one of the first phenome-wide association studies of OSA genomic variation. Results validate genetic associates with OSA in the LEPR, MMP-9 and GABBR1 genes, but suggest that the majority of previously identified genetic associations with OSA may be false positives. Phenome-wide analyses provide evidence of mediated pleiotropy. Future well-powered genome-wide association analyses of OSA risk and severity across populations with diverse ancestral backgrounds are needed. The comprehensive nature of the analyses represents a platform for informing future work focused on understanding how genetic data can be useful to informing treatment of OSA and related comorbidities.

0049 Odds Ratio Product as a Measure of Sleep Depth During REM Sleep: Effects on REM Duration and REM Sleep Fragmentation

Introduction

The odds ratio product (ORP) is a new highly-validated electroencephalogram biomarker of sleep depth. ORP has been validated as such by several studies investigating the effect of sleep disorders, responses to sleep deprivation and traffic noise. ORP during REM sleep varies considerably among individuals. Whether ORP reflects sleep depth also in REM sleep is unknown. We hypothesized that subjects with high REM ORP are more prone to REM sleep fragmentation.

Methods

Using data from the baseline (SHHS1; N=5,537) and follow-up (SHHS2; N=2,595) visits of the Sleep Heart Health Study, we calculated and summarized ORP in 30-second intervals corresponding to manually scored sleep stage epochs. We developed a heuristic to identify REM periods, defined as sequences of REM sleep epochs separated by no more than 10 minutes of other sleep stages or wake epochs. Using general linear models adjusted by age, sex, body mass index, race and ethnicity, we evaluated the relationship between REM ORP and total REM duration, number of awakening episodes per REM period and arousal index during REM sleep.

Results

Higher REM ORP was correlated with shorter total REM duration (ρ SHHS1=-0.12; p &lt 0.001, ρ SHHS2=-0.07; p &lt 0.001), more awakening episodes (ρ SHHS1=0.26; p&lt;0.001, ρ SHHS2=0.30; p &lt 0.001) and higher arousal index (ρ SHHS1=0.18; p &lt 0.001, ρ SHHS2=0.16; p &lt &lt; 0.001) during identified REM periods. In adjusted analyses, one-unit increase in REM ORP was associated, on average, with a 7 minute decrease in total REM duration (β=-7.10; p &lt 0.001), 1 more awakening episode per REM period (β=1.29; p &lt 0.001) and an increase of 6 arousals/hour (β=6.16; p &lt 0.001) during REM sleep periods.

Conclusion

We found that higher REM ORP was associated with shorter REM periods, higher proportion of awake during REM periods and higher REM arousal index. Although small, these differences suggest that ORP is consistent with the concept of sleep depth also during REM sleep.

Support

None

0593 Hypoxemia During Sleep Disordered Breathing and Cardiovascular Disease: A Comparison of Different Oxygen Desaturation Measures

Introduction

The apnea-hypopnea index has been used to characterize obstructive sleep apnea (OSA) severity. However, this metric is limited in providing information about cardiovascular disease (CVD) risk. Recent studies proposed alternative metrics that capture frequency, duration, depth, and combinations of duration and depth of hypoxemia. This study provides a systematic evaluation of the association between conventional or novel nocturnal hypoxemia metrics and the incidence of CVD and CV mortality in the Sleep Heart Health Study (SHHS).

Methods

We used data from 5,042 participants of the SHHS. Over 10.7 years, there were 1,312 (26.0%) incident CVD events and 359 (7.1%) CV deaths. We calculated standardized (z-scored) values of eight nocturnal hypoxemia indices, including conventional (e.g., oxygen desaturation index) and novel metrics (e.g., hypoxic burden, respiratory event-related area under desaturation curve and desaturation severity, corresponding to alternative quantitative measurements looking at the shape of each desaturation event). The association between each metric and incidence of CVD or CV mortality was evaluated using Cox proportional hazards models. Age, sex, body mass index, race, ethnicity, smoking, total sleep time, number of respiratory events, and prevalent CVD at baseline were used as covariates. Hazard ratios (HR) are presented as the effect of one standard deviation increase in each correponding metric.

Results

In unadjusted models, all nocturnal hypoxemia indices were associated with increased incidence of CVD and CV mortality. In adjusted models, longer average desaturation duration was associated with lower CVD incidence (HR[95%CI]=0.93[0.86-0.99];p=0.034), higher hypoxic burden with increased CV mortality (HR[95%CI]=1.22[1.04-1.43];p=0.017), and higher % sleep time with oxygen saturation less than 90% (Tlt90%) with increased CV mortality (HR[95%CI]=1.12[1.00-1.26];p=0.040).

Conclusion

Different metrics of nocturnal hypoxemia derived from polysomnography were associated with CV risk in the SHHS. However, after covariate adjustment, only shorter average desaturation duration, and higher hypoxic burden and Tlt90% were independent CV risk factors.

Support

AASM Foundation (194-SR-18,188-SR-17); American Heart Association (19CDA34660137); NIH (U01HL53940,U01HL53941,U01HL63463,U01HL53937, U01HL53938,U01HL53916,U01HL53934,U01HL63429,U01HL53931,HL114473, P01HL094307,HL134015,R35HL135818,1R21HL145492-01,R01HL102321,R01HL128658); The State Research Funding (KUH: 5041767, 5041768; TUH: VTR3242, VTR3228, EVO2089), Academy of Finland (313697, 323536), Business Finland (5133/31/2018), Respiratory Foundation of Kuopio Region, Tampere Tuberculosis Foundation, Research Foundation of Pulmonary Diseases, Foundation of Finnish Anti-Tuberculosis Association.

0386 Identification of Sleep Complaints Using Social Media: Effect of the Daylight Savings Time to Standard Time Transition

Introduction

Transitions to and from daylight savings time (DST) are natural experiments of circadian disruption and are associated with negative health consequences. Yet, the majority of the United States and several other countries still adopt these changes. Large observational studies focused on understanding the impact of DST transitions on sleep are difficult to conduct. Social media platforms, like Twitter, are powerful sources of human behavior data. We used machine learning to identify tweets reporting sleep complaints (TRSC) during the week of the standard time (ST)-DST transition. Next, we evaluated the circadian patterns of TRSC and compared their prevalence before and after the transition.

Methods

Using data publicly available via the Twitter API, we collected 500 tweets with evidence of sleep complaints, and manually annotated each tweet to validate true sleep complaints. Next, we calculated term frequency-inverse document frequency of each word in each tweet and trained a random forest to classify TRSC using a 3-fold cross-validation design. The trained model was then used to annotate a collection of tweets captured between Oct. 30, 2019-Nov. 6, 2019, overlapping with the DST-ST transition, which occurred on Nov. 3, 2019.

Results

Random forest demonstrated good performance in classifying TRSC (AUC[95%CI]=0.85[0.82-0.89]). This model was applied to 3,738,383 tweets collected around the DST-ST transition, and identified 11,044 TRSC. Posting of these tweets had a circadian pattern, with peak during nighttime. We found a higher frequency of TRSC after the DST-ST transition (0.33% vs. 0.27%, p&lt;0.00001), corresponding to a ~20% increase in the odds of reporting sleep complaints (OR[95%CI]=1.21[1.16-1.25]).

Conclusion

Using machine learning and Twitter data, we identified tweets reporting sleep complaints, described their circadian patterns and demonstrated that the prevalence of these types of tweets is significantly increased after the transition from DST to ST. These results demonstrate the applicability of social media data mining for public health in sleep medicine.

Support

NIH (K01LM012870); AASM Foundation (194-SR-18)

Symptom subtypes and cognitive function in a clinic-based OSA cohort: a multi-centre Canadian study

BACKGROUND

Distinct symptom subtypes are found in patients with OSA. The association between these subtypes and neurocognitive function is unclear.

OBJECTIVE

The purposes of this study were to assess whether OSA symptom subtypes are present in a cohort of Canadian patients with suspected OSA and evaluate the relationship between subtypes and neurocognitive function.

METHODS

Patients with suspected OSA who completed a symptom questionnaire and underwent testing for OSA were included. Symptom subtypes were identified using latent class analysis. Associations between subtypes and neurocognitive outcomes (Montreal Cognitive Assessment [MoCA], Rey Auditory Verbal Learning Test [RAVLT], Wechsler Adult Intelligence Scale [WAIS-IV], Digit-Symbol Coding subtest [DSC]) were assessed using analysis of covariance (ANCOVA), controlling for relevant covariates.

RESULTS

Four symptom subtypes were identified in patients with OSA (oxygen desaturation index ≥5 events/hour). Three were similar to prior studies, including the Excessively Sleepy (N=405), Disturbed Sleep (N=382) and Minimally Symptomatic (N=280), and one was a novel subtype in our sample defined as Excessively Sleepy with Disturbed Sleep (N=247). After covariate adjustment, statistically significant differences among subtypes (p=0.037) and among subtypes and patients without OSA (p=0.044) were observed in DSC scores; the Minimally Symptomatic subtype had evidence of higher DSC scores than all other groups, including non-OSA patients. No differences were seen in MoCA or RAVLT.

CONCLUSIONS

Results support the existence of previously identified OSA symptom subtypes of excessively sleepy, disturbed sleep and minimally symptomatic in a clinical sample from Canada. Subtypes were not consistently associated with neurocognitive function across multiple instruments.

Defining Extreme Phenotypes of OSA Across International Sleep Centers

BACKGROUND

Extreme phenotypes of OSA have not been systematically defined.

RESEARCH QUESTION

This study developed objective definitions of extreme phenotypes of OSA by using a multivariate approach. The utility of these definitions for identifying characteristics that confer predisposition toward or protection against OSA is shown in a new prospective sample.

STUDY DESIGN AND METHODS

In a large international sample, race-specific liability scores were calculated from a weighted logistic regression that included age, sex, and BMI. Extreme cases were defined as individuals with an apnea-hypopnea index (AHI) ≥ 30 events/hour but low likelihood of OSA based on age, sex, and BMI (liability scores > 90th percentile). Similarly, extreme controls were individuals with an AHI < 5 events/hour but high likelihood of OSA (liability scores < 10th percentile). Definitions were applied to a prospective sample from the Sleep Apnea Global Interdisciplinary Consortium, and differences in photography-based craniofacial and intraoral phenotypes were evaluated.

RESULTS

This study included retrospective data from 81,338 individuals. A total of 4,168 extreme cases and 1,432 extreme controls were identified by using liability scores. Extreme cases were younger (43.1 ± 14.7 years), overweight (28.6 ± 6.8 kg/m²), and predominantly female (71.1%). Extreme controls were older (53.8 ± 14.1 years), obese (34.0 ± 8.1 kg/m²), and predominantly male (65.8%). These objective definitions identified 29 extreme cases and 87 extreme controls among 1,424 Sleep Apnea Global Interdisciplinary Consortium participants with photography-based phenotyping. Comparisons suggest that a greater cervicomental angle increases risk for OSA in the absence of clinical risk factors, and smaller facial widths are protective in the presence of clinical risk factors.

INTERPRETATION

This objective definition can be applied in sleep centers throughout the world to consistently define OSA extreme phenotypes for future studies on genetic, anatomic, and physiologic pathways to OSA.

Detecting multiple differentially methylated CpG sites and regions related to dimensional psychopathology in youths

Background

Psychiatric symptomatology during late childhood and early adolescence tends to persist later in life. In the present longitudinal study, we aimed to identify changes in genome-wide DNA methylation patterns that were associated with the emergence of psychopathology in youths from the Brazilian High-Risk Cohort (HRC) for psychiatric disorders. Moreover, for the differentially methylated genes, we verified whether differences in DNA methylation corresponded to differences in mRNA transcript levels by analyzing the gene expression levels in the blood and by correlating the variation of DNA methylation values with the variation of mRNA levels of the same individuals. Finally, we examined whether the variations in DNA methylation and mRNA levels were correlated with psychopathology measurements over time.

Methods

We selected 24 youths from the HRC who presented with an increase in dimensional psychopathology at a 3-year follow-up as measured by the Child Behavior Checklist (CBCL). The DNA methylation and gene expression data were compared in peripheral blood samples (n = 48) obtained from the 24 youths before and after developing psychopathology. We implemented a methodological framework to reduce the effect of chronological age on DNA methylation using an independent population of 140 youths and the effect of puberty using data from the literature.

Results

We identified 663 differentially methylated positions (DMPs) and 90 differentially methylated regions (DMRs) associated with the emergence of psychopathology. We observed that 15 DMPs were mapped to genes that were differentially expressed in the blood; among these, we found a correlation between the DNA methylation and mRNA levels of RB1CC1 and a correlation between the CBCL and mRNA levels of KMT2E. Of the DMRs, three genes were differentially expressed: ASCL2, which is involved in neurogenesis; HLA-E, which is mapped to the MHC loci; and RPS6KB1, the gene expression of which was correlated with an increase in the CBCL between the time points.

Conclusions

We observed that changes in DNA methylation and, consequently, in gene expression in the peripheral blood occurred concurrently with the emergence of dimensional psychopathology in youths. Therefore, epigenomic modulations might be involved in the regulation of an individual’s development of psychopathology.

Symptom Subtypes of Obstructive Sleep Apnea Predict Incidence of Cardiovascular Outcomes

Rationale: Symptom subtypes have been described in clinical and population samples of patients with obstructive sleep apnea (OSA). It is unclear whether these subtypes have different cardiovascular consequences.Objectives: To characterize OSA symptom subtypes and assess their association with prevalent and incident cardiovascular disease in the Sleep Heart Health Study.Methods: Data from 1,207 patients with OSA (apnea-hypopnea index ≥ 15 events/h) were used to evaluate the existence of symptom subtypes using latent class analysis. Associations between subtypes and prevalence of overall cardiovascular disease and its components (coronary heart disease, heart failure, and stroke) were assessed using logistic regression. Kaplan-Meier survival analysis and Cox proportional hazards models were used to evaluate whether subtypes were associated with incident events, including cardiovascular mortality.Measurements and Main Results: Four symptom subtypes were identified (disturbed sleep [12.2%], minimally symptomatic [32.6%], excessively sleepy [16.7%], and moderately sleepy [38.5%]), similar to prior studies. In adjusted models, although no significant associations with prevalent cardiovascular disease were found, the excessively sleepy subtype was associated with more than threefold increased risk of prevalent heart failure compared with each of the other subtypes. Symptom subtype was also associated with incident cardiovascular disease (P < 0.001), coronary heart disease (P = 0.015), and heart failure (P = 0.018), with the excessively sleepy again demonstrating increased risk (hazard ratios, 1.7-2.4) compared with other subtypes. When compared with individuals without OSA (apnea-hypopnea index < 5), significantly increased risk for prevalent and incident cardiovascular events was observed mostly for patients in the excessively sleepy subtype.Conclusions: OSA symptom subtypes are reproducible and associated with cardiovascular risk, providing important evidence of their clinical relevance.

A Global Comparison of Anatomic Risk Factors and Their Relationship to Obstructive Sleep Apnea Severity in Clinical Samples

STUDY OBJECTIVES

Obstructive sleep apnea (OSA) is a global health issue and is associated with obesity and oropharyngeal crowding. Global data are limited on the effect of ethnicity and sex on these relationships. We compare associations between the apnea-hypopnea index (AHI) and these risk factors across ethnicities and sexes within sleep clinics.

METHODS

This is a cross-sectional, multicenter study of patients with OSA from eight sleep centers representing the Sleep Apnea Global Interdisciplinary Consortium (SAGIC). Four distinct ethnic groups were analyzed, using a structured questionnaire: Caucasians (Australia, Iceland, Germany, United States), African Americans (United States), Asians (Taiwan), and South Americans (Brazil). Regression analyses and interaction tests were used to assess ethnic and sex differences in relationships between AHI and anthropometric measures (body mass index [BMI], neck circumference, waist circumference) or Mallampati score.

RESULTS

Analyses included 1,585 individuals from four ethnic groups: Caucasian (60.6%), African American (17.5%), Asian (13.1%), and South American (8.9%). BMI was most strongly associated with AHI in South Americans (7.8% increase in AHI per 1 kg/m² increase in BMI; P < .0001) and most weakly in African Americans (1.9% increase in AHI per 1 kg/m² increase in BMI; P = .002). In Caucasians and South Americans, associations were stronger in males than females. Mallampati score differed between ethnicities but did not influence AHI differently across groups.

CONCLUSIONS

We demonstrate ethnic and sex variations in associations between obesity and OSA. For similar BMI increases, South American patients show greatest AHI increases compared to African Americans. Findings highlight the importance of considering ethnicity and sex in clinical assessments of OSA risk.

Genetic studies of accelerometer-based sleep measures yield new insights into human sleep behaviour

Sleep is an essential human function but its regulation is poorly understood. Using accelerometer data from 85,670 UK Biobank participants, we perform a genome-wide association study of 8 derived sleep traits representing sleep quality, quantity and timing, and validate our findings in 5,819 individuals. We identify 47 genetic associations at P < 5 × 10-8, of which 20 reach a stricter threshold of P < 8 × 10-10. These include 26 novel associations with measures of sleep quality and 10 with nocturnal sleep duration. The majority of identified variants associate with a single sleep trait, except for variants previously associated with restless legs syndrome. For sleep duration we identify a missense variant (p.Tyr727Cys) in PDE11A as the likely causal variant. As a group, sleep quality loci are enriched for serotonin processing genes. Although accelerometer-derived measures of sleep are imperfect and may be affected by restless legs syndrome, these findings provide new biological insights into sleep compared to previous efforts based on self-report sleep measures.