Associations of actigraphy measures of sleep duration and continuity with executive function, vigilance, and fine motor control in children with snoring and mild sleep-disordered breathing

STUDY OBJECTIVES

Children with snoring and mild sleep-disordered breathing may be at increased risk for neurocognitive deficits despite few obstructive events. We hypothesized that actigraphy-based sleep duration and continuity associate with neurobehavioral functioning and explored whether these associations vary by demographic and socioeconomic factors.

METHODS

298 children enrolled in the Pediatric Adenotonsillectomy Trial, ages 3 to 12.9 years, 47.3% from racial or ethnic minority groups, with habitual snoring and an apnea-hypopnea index < 3 were studied with actigraphy (mean 7.5 ± 1.4 days) and completed a computerized vigilance task (Go-No-Go) and a test of fine motor control (9-Hole Pegboard). Caregivers completed the Behavior Rating Inventory of Executive Function. Regression analyses evaluated associations between sleep exposures (24-hour and nocturnal sleep duration, sleep fragmentation index, sleep efficiency) with the Behavior Rating Inventory of Executive Function Global Executive Composite index, pegboard completion time (fine motor control), and vigilance (d prime on the Go-No-Go), adjusting for demographic factors and study design measures.

RESULTS

Longer sleep duration, higher sleep efficiency, and lower sleep fragmentation were associated with better executive function; each additional hour of sleep over 24 hours associated with more than a 3-point improvement in executive function (P = .002). Longer nocturnal sleep (P = .02) and less sleep fragmentation (P = .001) were associated with better fine motor control. Stronger associations were observed for boys and children less than 6 years old.

CONCLUSIONS

Sleep quantity and continuity are associated with neurocognitive functioning in children with mild sleep-disordered breathing, supporting efforts to target these sleep health parameters as part of interventions for reducing neurobehavioral morbidity.

CLINICAL TRIAL REGISTRATION

Registry: ClinicalTrials.gov; Name: Pediatric Adenotonsillectomy for Snoring (PATS); URL: https://clinicaltrials.gov/ct2/show/NCT02562040; Identifier: NCT02562040.

CITATION

Robinson KA, Wei Z, Radcliffe J, et al. Associations of actigraphy measures of sleep duration and continuity with executive function, vigilance, and fine motor control in children with snoring and mild sleep-disordered breathing. J Clin Sleep Med. 2023;19(9):1595-1603.

Disparities in Sleep-Disordered Breathing: Upstream Risk Factors, Mechanisms, and Implications

Sleep-disordered breathing (SDB) refers to a spectrum of disorders ranging from habitual snoring without frank episodes of obstructed breathing or desaturation during sleep to obstructive sleep apnea, where apneas and hypopneas repetitively occur with resultant intermittent hypoxia, arousal, and sleep disruption. Disparities in SDB reflect its overall high prevalence in children and adults from racially and ethnically minoritized or low socioeconomic status backgrounds coupled with high rates of underdiagnosis and suboptimal treatment.

Obstructive sleep apnoea heterogeneity and cardiovascular disease

Obstructive sleep apnoea (OSA), characterized by recurrent periods of upper airway obstruction and intermittent hypoxaemia, is prevalent in patients with cardiovascular disease (CVD), and is therefore important to consider in the prevention and management of CVD. Observational studies indicate that OSA is a risk factor for incident hypertension, poorly controlled blood pressure, stroke, myocardial infarction, heart failure, cardiac arrhythmias, sudden cardiac death and all-cause death. However, clinical trials have not provided consistent evidence that treatment with continuous positive airway pressure (CPAP) improves cardiovascular outcomes. These overall null findings might be explained by limitations in trial design and low levels of adherence to CPAP. Studies have also been limited by the failure to consider OSA as a heterogeneous disorder that consists of multiple subtypes resulting from variable contributions from anatomical, physiological, inflammatory and obesity-related risk factors, and resulting in different physiological disturbances. Novel markers of sleep apnoea-associated hypoxic burden and cardiac autonomic response have emerged as predictors of OSA-related susceptibility to adverse health outcomes and treatment response. In this Review, we summarize our understanding of the shared risk factors and causal links between OSA and CVD and emerging knowledge on the heterogeneity of OSA. We discuss the varied mechanistic pathways that result in CVD that also vary across subgroups of OSA, as well as the potential role of new biomarkers for CVD risk stratification.

Relevance of cortical arousals for risk stratification in sleep apnea: a 3 cohort analysis

STUDY OBJECTIVES

There is uncertainty on best approaches for defining apnea-hypopnea events. To clarify the contributions of desaturation vs arousal to defining hypopneas, we examined the associations of events with desaturation (≥ 3%) but not arousal (apnea-hypopnea index [AHI]≥3%Only) vs events with arousals but no desaturation (AHIArOnly) with obstructive sleep apnea-related comorbidities and incident cardiovascular disease across multiple cohorts.

METHODS

In the Sleep Heart Health Study (n = 5,473), the Multi-Ethnic Study of Atherosclerosis (n = 1,904), and the Osteoporotic Fractures in Men Study (n = 2,685), we examined the independent associations of AHI≥3%Only and AHIArOnly with hypertension, diabetes, and daytime sleepiness, and incident cardiovascular disease.

RESULTS

After adjusting for covariates and AHI based on events with electroencephalogram arousal (regardless of desaturation), AHI≥3%Only was associated with hypertension in Sleep Heart Health Study (odds ratio: 1.12; 95% confidence interval: 1.04,1.21), per 1 standard deviation increase). Similar associations were observed in the Multi-Ethnic Study of Atherosclerosis and Osteoporotic Fractures in Men Study, as well as for associations with diabetes (odds ratio: 1.30; 1.09,1.54, and 1.25; 1.07,1.47, respectively), sleepiness (odds ratio: 1.19; 1.00,1.41; and 1.17; 1.01-1.35), and incident cardiovascular disease (hazard ratio: 1.37; 1.05,1.77 and 1.14; 1.00,1.29). In contrast, after adjusting for events with desaturation (regardless of arousal), AHIArOnly was unassociated with these outcomes. In Sleep Heart Health Study, greater baseline obstructive sleep apnea severity was associated with a reduction in arousal frequency over 5 years (P < .0001).

CONCLUSIONS

In middle-aged and older individuals, addition of events with arousals does not improve the strength of associations with comorbidities or incident cardiovascular disease. Research is needed to understand generalizability to younger individuals and the mechanistic role of arousals in obstructive sleep apnea.

CITATION

Azarbarzin A, Sands SA, Han S, et al. Relevance of cortical arousals for risk stratification in sleep apnea: a 3 cohort analysis. J Clin Sleep Med. 2023;19(8):1475-1484.

Is exposure to chemical pollutants associated with sleep outcomes? A systematic review

Environmental exposures may influence sleep; however, the contributions of environmental chemical pollutants to sleep health have not been systematically investigated. We conducted a systematic review to identify, evaluate, summarize, and synthesize the existing evidence between chemical pollutants (air pollution, exposures related to the Gulf War and other conflicts, endocrine disruptors, metals, pesticides, solvents) and dimensions of sleep health (architecture, duration, quality, timing) and disorders (sleeping pill use, insomnia, sleep-disordered breathing)). Of the 204 included studies, results were mixed; however, the synthesized evidence suggested associations between particulate matter, exposures related to the Gulf War, dioxin and dioxin-like compounds, and pesticide exposure with worse sleep quality; exposures related to the Gulf War, aluminum, and mercury with insomnia and impaired sleep maintenance; and associations between tobacco smoke exposure with insomnia and sleep-disordered breathing, particularly in pediatric populations. Possible mechanisms relate to cholinergic signaling, neurotransmission, and inflammation. Chemical pollutants are likely key determinants of sleep health and disorders. Future studies should aim to evaluate environmental exposures on sleep across the lifespan, with a particular focus on developmental windows and biological mechanisms, as well as in historically marginalized or excluded populations.

Metabolomic Profiles of Sleep-Disordered Breathing are Associated with Hypertension and Diabetes Mellitus Development: the HCHS/SOL

Sleep-disordered breathing (SDB) is a prevalent disorder characterized by recurrent episodic upper airway obstruction. In a dataset from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL), we applied principal component analysis (PCA) on seven measures characterizing SDB-associated respiratory events. We estimated the association of the top two SDB PCs with serum levels of 617 metabolites, in both single-metabolite analysis, and a joint, penalized regression analysis using the least absolute shrinkage and selection operator (LASSO). Discovery analysis included n = 3,299 HCHS/SOL individuals; associations were validated in a separate dataset of n = 1,522 HCHS/SOL individuals. Seven metabolite associations with SDB PCs were discovered and replicated. Metabolite risk scores (MRSs) developed based on LASSO association results and representing metabolite signatures associated with the two SDB PCs were associated with 6-year incident hypertension and incident diabetes. MRSs have the potential to serve as biomarkers for SDB, guiding risk stratification and treatment decisions.

Associations between sleep health and grey matter volume in the UK Biobank cohort (n = 33 356)

As suggested by previous research, sleep health is assumed to be a key determinant of future morbidity and mortality. In line with this, recent studies have found that poor sleep is associated with impaired cognitive function. However, to date, little is known about brain structural abnormalities underlying this association. Although recent findings link sleep health deficits to specific alterations in grey matter volume, evidence remains inconsistent and reliant on small sample sizes. Addressing this problem, the current preregistered study investigated associations between sleep health and grey matter volume (139 imaging-derived phenotypes) in the UK Biobank cohort (33 356 participants). Drawing on a large sample size and consistent data acquisition, sleep duration, insomnia symptoms, daytime sleepiness, chronotype, sleep medication and sleep apnoea were examined. Our main analyses revealed that long sleep duration was systematically associated with larger grey matter volume of basal ganglia substructures. Insomnia symptoms, sleep medication and sleep apnoea were not associated with any of the 139 imaging-derived phenotypes. Short sleep duration, daytime sleepiness as well as late and early chronotype were associated with solitary imaging-derived phenotypes (no recognizable pattern, small effect sizes). To our knowledge, this is the largest study to test associations between sleep health and grey matter volume. Clinical implications of the association between long sleep duration and larger grey matter volume of basal ganglia are discussed. Insomnia symptoms as operationalized in the UK Biobank do not translate into grey matter volume findings.

Sleep Architecture, Obstructive Sleep Apnea, and Cognitive Function in Adults

Importance

Good sleep is essential for health, yet associations between sleep and dementia risk remain incompletely understood. The Sleep and Dementia Consortium was established to study associations between polysomnography (PSG)-derived sleep and the risk of dementia and related cognitive and brain magnetic resonance imaging endophenotypes.

Objective

To investigate association of sleep architecture and obstructive sleep apnea (OSA) with cognitive function in the Sleep and Dementia Consortium.

Design, Setting, and Participants

The Sleep and Dementia Consortium curated data from 5 population-based cohorts across the US with methodologically consistent, overnight, home-based type II PSG and neuropsychological assessments over 5 years of follow-up: the Atherosclerosis Risk in Communities study, Cardiovascular Health Study, Framingham Heart Study (FHS), Osteoporotic Fractures in Men Study, and Study of Osteoporotic Fractures. Sleep metrics were harmonized centrally and then distributed to participating cohorts for cohort-specific analysis using linear regression; study-level estimates were pooled in random effects meta-analyses. Results were adjusted for demographic variables, the time between PSG and neuropsychological assessment (0-5 years), body mass index, antidepressant use, and sedative use. There were 5946 participants included in the pooled analyses without stroke or dementia. Data were analyzed from March 2020 to June 2023.

Exposures

Measures of sleep architecture and OSA derived from in-home PSG.

Main Outcomes and Measures

The main outcomes were global cognitive composite z scores derived from principal component analysis, with cognitive domains investigated as secondary outcomes. Higher scores indicated better performance.

Results

Across cohorts, 5946 adults (1875 females [31.5%]; mean age range, 58-89 years) were included. The median (IQR) wake after sleep onset time ranged from 44 (27-73) to 101 (66-147) minutes, and the prevalence of moderate to severe OSA ranged from 16.9% to 28.9%. Across cohorts, higher sleep maintenance efficiency (pooled β per 1% increase, 0.08; 95% CI, 0.03 to 0.14; P < .01) and lower wake after sleep onset (pooled β per 1-min increase, -0.07; 95% CI, -0.13 to -0.01 per 1-min increase; P = .02) were associated with better global cognition. Mild to severe OSA (apnea-hypopnea index [AHI] ≥5) was associated with poorer global cognition (pooled β, -0.06; 95% CI, -0.11 to -0.01; P = .01) vs AHI less than 5; comparable results were found for moderate to severe OSA (pooled β, -0.06; 95% CI, -0.11 to -0.01; P = .02) vs AHI less than 5. Differences in sleep stages were not associated with cognition.

Conclusions and Relevance

This study found that better sleep consolidation and the absence of OSA were associated with better global cognition over 5 years of follow-up. These findings suggest that the role of interventions to improve sleep for maintaining cognitive function requires investigation.

International Consensus Statement on Obstructive Sleep Apnea

BACKGROUND

Evaluation and interpretation of the literature on obstructive sleep apnea (OSA) allows for consolidation and determination of the key factors important for clinical management of the adult OSA patient. Toward this goal, an international collaborative of multidisciplinary experts in sleep apnea evaluation and treatment have produced the International Consensus statement on Obstructive Sleep Apnea (ICS:OSA).

METHODS

Using previously defined methodology, focal topics in OSA were assigned as literature review (LR), evidence-based review (EBR), or evidence-based review with recommendations (EBR-R) formats. Each topic incorporated the available and relevant evidence which was summarized and graded on study quality. Each topic and section underwent iterative review and the ICS:OSA was created and reviewed by all authors for consensus.

RESULTS

The ICS:OSA addresses OSA syndrome definitions, pathophysiology, epidemiology, risk factors for disease, screening methods, diagnostic testing types, multiple treatment modalities, and effects of OSA treatment on multiple OSA-associated comorbidities. Specific focus on outcomes with positive airway pressure (PAP) and surgical treatments were evaluated.

CONCLUSION

This review of the literature consolidates the available knowledge and identifies the limitations of the current evidence on OSA. This effort aims to create a resource for OSA evidence-based practice and identify future research needs. Knowledge gaps and research opportunities include improving the metrics of OSA disease, determining the optimal OSA screening paradigms, developing strategies for PAP adherence and longitudinal care, enhancing selection of PAP alternatives and surgery, understanding health risk outcomes, and translating evidence into individualized approaches to therapy.

Strategies to Assess the Effect of Continuous Positive Airway Pressure on Long-Term Clinically Important Outcomes among Patients with Symptomatic Obstructive Sleep Apnea: An Official American Thoracic Society Workshop Report

Continuous positive airway pressure (CPAP) is the first-line treatment for obstructive sleep apnea (OSA). Although CPAP improves symptoms (e.g., daytime sleepiness), there is a lack of high-quality evidence that CPAP prevents many long-term outcomes, including cognitive impairment, myocardial infarction, and stroke. Observational studies suggest that patients with symptoms may be particularly likely to experience these preventive benefits with CPAP, but ethical and practical concerns limited the participation of such patients in prior long-term randomized trials. As a result, there is uncertainty about the full benefits of CPAP, and resolving this uncertainty is a key priority for the field. This workshop assembled clinicians, researchers, ethicists, and patients to identify strategies to understand the causal effects of CPAP on long-term clinically important outcomes among patients with symptomatic OSA. Quasi-experimental designs can provide valuable information and are less time and resource intensive than trials. Under specific conditions and assumptions, quasi-experimental studies may be able to provide causal estimates of CPAP's effectiveness from generalizable observational cohorts. However, randomized trials represent the most reliable approach to understanding the causal effects of CPAP among patients with symptoms. Randomized trials of CPAP can ethically include patients with symptomatic OSA, as long as there is outcome-specific equipoise, adequate informed consent, and a plan to maximize safety while minimizing harm (e.g., monitoring for pathologic sleepiness). Furthermore, multiple strategies exist to ensure the generalizability and practicality of future randomized trials of CPAP. These strategies include reducing the burden of trial procedures, improving patient-centeredness, and engaging historically excluded and underserved populations.

The public health impact of poor sleep on severe COVID-19, influenza and upper respiratory infections

BACKGROUND

Poor sleep is associated with an increased risk of infections and all-cause mortality but the causal direction between poor sleep and respiratory infections has remained unclear. We examined if poor sleep contributes as a causal risk factor to respiratory infections.

METHODS

We used data on insomnia, influenza and upper respiratory infections (URIs) from primary care and hospital records in the UK Biobank (N ≈ 231,000) and FinnGen (N ≈ 392,000). We computed logistic regression to assess association between poor sleep and infections, disease free survival hazard ratios, and performed Mendelian randomization analyses to assess causality.

FINDINGS

Utilizing 23 years of registry data and follow-up, we discovered that insomnia diagnosis associated with increased risk for infections (FinnGen influenza Cox's proportional hazard (CPH) HR = 4.34 [3.90, 4.83], P = 4.16 × 10-159, UK Biobank influenza CPH HR = 1.54 [1.37, 1.73], P = 2.49 × 10-13). Mendelian randomization indicated that insomnia causally predisposed to influenza (inverse-variance weighted (IVW) OR = 1.65, P = 5.86 × 10-7), URI (IVW OR = 1.94, P = 8.14 × 10-31), COVID-19 infection (IVW OR = 1.08, P = 0.037) and risk of hospitalization from COVID-19 (IVW OR = 1.47, P = 4.96 × 10-5).

INTERPRETATION

Our findings indicate that chronic poor sleep is a causal risk factor for contracting respiratory infections, and in addition contributes to the severity of respiratory infections. These findings highlight the role of sleep in maintaining sufficient immune response against pathogens.

FUNDING

Instrumentarium Science Foundation, Academy of Finland, Signe and Ane Gyllenberg Foundation, National Institutes of Health.

Cardiovascular Outcomes in Adults with Coronary Artery Disease and Obstructive Sleep Apnea with versus without Excessive Daytime Sleepiness in the RICCADSA Cinical Trial

Rationale: Recent randomized controlled trials did not show cardiovascular benefits of continuous positive airway pressure (CPAP) in adults with coronary artery disease (CAD) and obstructive sleep apnea (OSA) in intention-to-treat analyses. It has been argued that exclusion of patients with OSA with excessive daytime sleepiness (EDS), who may be most likely to benefit from CPAP treatment, may be a reason for the null results. Objectives: We addressed 1) the effect of concomitant EDS on adverse outcomes in patients with CAD and OSA; and 2) whether the cardiovascular benefit of CPAP adherence differs between individuals with versus without EDS. Methods: This was a secondary analysis of the RICCADSA (Randomized Intervention with CPAP in CAD and Obstructive Sleep Apnea) trial, conducted in Sweden between 2005 and 2013. Data were analyzed from 155 patients with CAD with OSA (apnea-hypopnea index ⩾ 15/h) and EDS (Epworth Sleepiness Scale score ⩾ 10), who were allocated to CPAP and 244 patients without EDS (ESS < 10), who were randomized to CPAP or no CPAP. Patients who were allocated to no CPAP or were nonadherent (CPAP usage < 4 h/night) were compared with adherent patients (CPAP usage ⩾ 4 h/night) at 1-year follow-up. Inverse probability of treatment weighting was applied to mimic randomization of EDS. The primary endpoint was the first event of repeat revascularization, myocardial infarction, stroke, or cardiovascular mortality. Results: The median follow-up was 52.2 months. The incidence of the primary endpoint did not differ significantly between the EDS versus no-EDS groups in the entire cohort. Within the adherent group, patients without EDS had a significantly decreased risk compared with patients with EDS (adjusted hazard ratio, 0.41; 95% confidence interval, 0.20-0.85; P = 0.02). Conclusions: Adverse cardiovascular outcomes did not differ by degrees of EDS for patients with CAD with OSA who were untreated or nonadherent to treatment. CPAP use, at least 4 h/night, was associated with reduced adverse outcomes in participants without EDS. Clinical trial registered with www.clinicaltrials.gov (NCT00519597).

Rare variants in long non-coding RNAs are associated with blood lipid levels in the TOPMed Whole Genome Sequencing Study

Long non-coding RNAs (lncRNAs) are known to perform important regulatory functions. Large-scale whole genome sequencing (WGS) studies and new statistical methods for variant set tests now provide an opportunity to assess the associations between rare variants in lncRNA genes and complex traits across the genome. In this study, we used high-coverage WGS from 66,329 participants of diverse ancestries with blood lipid levels (LDL-C, HDL-C, TC, and TG) in the National Heart, Lung, and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) program to investigate the role of lncRNAs in lipid variability. We aggregated rare variants for 165,375 lncRNA genes based on their genomic locations and conducted rare variant aggregate association tests using the STAAR (variant-Set Test for Association using Annotation infoRmation) framework. We performed STAAR conditional analysis adjusting for common variants in known lipid GWAS loci and rare coding variants in nearby protein coding genes. Our analyses revealed 83 rare lncRNA variant sets significantly associated with blood lipid levels, all of which were located in known lipid GWAS loci (in a ±500 kb window of a Global Lipids Genetics Consortium index variant). Notably, 61 out of 83 signals (73%) were conditionally independent of common regulatory variations and rare protein coding variations at the same loci. We replicated 34 out of 61 (56%) conditionally independent associations using the independent UK Biobank WGS data. Our results expand the genetic architecture of blood lipids to rare variants in lncRNA, implicating new therapeutic opportunities.

Use and misuse of random forest variable importance metrics in medicine: demonstrations through incident stroke prediction

BACKGROUND

Machine learning tools such as random forests provide important opportunities for modeling large, complex modern data generated in medicine. Unfortunately, when it comes to understanding why machine learning models are predictive, applied research continues to rely on 'out of bag' (OOB) variable importance metrics (VIMPs) that are known to have considerable shortcomings within the statistics community. After explaining the limitations of OOB VIMPs - including bias towards correlated features and limited interpretability - we describe a modern approach called 'knockoff VIMPs' and explain its advantages.

METHODS

We first evaluate current VIMP practices through an in-depth literature review of 50 recent random forest manuscripts. Next, we recommend organized and interpretable strategies for analysis with knockoff VIMPs, including computing them for groups of features and considering multiple model performance metrics. To demonstrate methods, we develop a random forest to predict 5-year incident stroke in the Sleep Heart Health Study and compare results based on OOB and knockoff VIMPs.

RESULTS

Nearly all papers in the literature review contained substantial limitations in their use of VIMPs. In our demonstration, using OOB VIMPs for individual variables suggested two highly correlated lung function variables (forced expiratory volume, forced vital capacity) as the best predictors of incident stroke, followed by age and height. Using an organized analytic approach that considered knockoff VIMPs of both groups of features and individual features, the largest contributions to model sensitivity were medications (especially cardiovascular) and measured medical risk factors, while the largest contributions to model specificity were age, diastolic blood pressure, self-reported medical risk factors, polysomnography features, and pack-years of smoking. Thus, we reach very different conclusions about stroke risk factors using OOB VIMPs versus knockoff VIMPs.

CONCLUSIONS

The near-ubiquitous reliance on OOB VIMPs may provide misleading results for researchers who use such methods to guide their research. Given the rapid pace of scientific inquiry using machine learning, it is essential to bring modern knockoff VIMPs that are interpretable and unbiased into widespread applied practice to steer researchers using random forest machine learning toward more meaningful results.

Method comparison and estimation of causal effects of insomnia on health outcomes in a survey sampled population

Applying causal inference methods, such as weighting and matching methods, to a survey sampled population requires properly incorporating the survey weights and design to obtain effect estimates that are representative of the target population and correct standard errors (SEs). With a simulation study, we compared various approaches for incorporating the survey weights and design into weighting and matching-based causal inference methods. When the models were correctly specified, most approaches performed well. However, when a variable was treated as an unmeasured confounder and the survey weights were constructed to depend on this variable, only the matching methods that used the survey weights in causal estimation and as a covariate in matching continued to perform well. If unmeasured confounders are potentially associated with the survey sample design, we recommend that investigators include the survey weights as a covariate in matching, in addition to incorporating them in causal effect estimation. Finally, we applied the various approaches to the Hispanic Community Health Study/Study of Latinos (HCHS/SOL) and found that insomnia has a causal association with both mild cognitive impairment (MCI) and incident hypertension 6-7 years later in the US Hispanic/Latino population.

Whole genome analysis of plasma fibrinogen reveals population-differentiated genetic regulators with putative liver roles

Genetic studies have identified numerous regions associated with plasma fibrinogen levels in Europeans, yet missing heritability and limited inclusion of non-Europeans necessitates further studies with improved power and sensitivity. Compared with array-based genotyping, whole genome sequencing (WGS) data provides better coverage of the genome and better representation of non-European variants. To better understand the genetic landscape regulating plasma fibrinogen levels, we meta-analyzed WGS data from the NHLBI's Trans-Omics for Precision Medicine (TOPMed) program (n=32,572), with array-based genotype data from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium (n=131,340) imputed to the TOPMed or Haplotype Reference Consortium panel. We identified 18 loci that have not been identified in prior genetic studies of fibrinogen. Of these, four are driven by common variants of small effect with reported MAF at least 10% higher in African populations. Three ( SERPINA1, ZFP36L2 , and TLR10) signals contain predicted deleterious missense variants. Two loci, SOCS3 and HPN , each harbor two conditionally distinct, non-coding variants. The gene region encoding the protein chain subunits ( FGG;FGB;FGA ), contains 7 distinct signals, including one novel signal driven by rs28577061, a variant common (MAF=0.180) in African reference panels but extremely rare (MAF=0.008) in Europeans. Through phenome-wide association studies in the VA Million Veteran Program, we found associations between fibrinogen polygenic risk scores and thrombotic and inflammatory disease phenotypes, including an association with gout. Our findings demonstrate the utility of WGS to augment genetic discovery in diverse populations and offer new insights for putative mechanisms of fibrinogen regulation.

Key Points

Largest and most diverse genetic study of plasma fibrinogen identifies 54 regions (18 novel), housing 69 conditionally distinct variants (20 novel).Sufficient power achieved to identify signal driven by African population variant.Links to (1) liver enzyme, blood cell and lipid genetic signals, (2) liver regulatory elements, and (3) thrombotic and inflammatory disease.

Evaluating the use of blood pressure polygenic risk scores across race/ethnic background groups

We assess performance and limitations of polygenic risk scores (PRSs) for multiple blood pressure (BP) phenotypes in diverse population groups. We compare "clumping-and-thresholding" (PRSice2) and LD-based (LDPred2) methods to construct PRSs from each of multiple GWAS, as well as multi-PRS approaches that sum PRSs with and without weights, including PRS-CSx. We use datasets from the MGB Biobank, TOPMed study, UK biobank, and from All of Us to train, assess, and validate PRSs in groups defined by self-reported race/ethnic background (Asian, Black, Hispanic/Latino, and White). For both SBP and DBP, the PRS-CSx based PRS, constructed as a weighted sum of PRSs developed from multiple independent GWAS, perform best across all race/ethnic backgrounds. Stratified analysis in All of Us shows that PRSs are better predictive of BP in females compared to males, individuals without obesity, and middle-aged (40-60 years) compared to older and younger individuals.

AI-Driven sleep staging from actigraphy and heart rate

Sleep is an important indicator of a person's health, and its accurate and cost-effective quantification is of great value in healthcare. The gold standard for sleep assessment and the clinical diagnosis of sleep disorders is polysomnography (PSG). However, PSG requires an overnight clinic visit and trained technicians to score the obtained multimodality data. Wrist-worn consumer devices, such as smartwatches, are a promising alternative to PSG because of their small form factor, continuous monitoring capability, and popularity. Unlike PSG, however, wearables-derived data are noisier and far less information-rich because of the fewer number of modalities and less accurate measurements due to their small form factor. Given these challenges, most consumer devices perform two-stage (i.e., sleep-wake) classification, which is inadequate for deep insights into a person's sleep health. The challenging multi-class (three, four, or five-class) staging of sleep using data from wrist-worn wearables remains unresolved. The difference in the data quality between consumer-grade wearables and lab-grade clinical equipment is the motivation behind this study. In this paper, we present an artificial intelligence (AI) technique termed sequence-to-sequence LSTM for automated mobile sleep staging (SLAMSS), which can perform three-class (wake, NREM, REM) and four-class (wake, light, deep, REM) sleep classification from activity (i.e., wrist-accelerometry-derived locomotion) and two coarse heart rate measures-both of which can be reliably obtained from a consumer-grade wrist-wearable device. Our method relies on raw time-series datasets and obviates the need for manual feature selection. We validated our model using actigraphy and coarse heart rate data from two independent study populations: the Multi-Ethnic Study of Atherosclerosis (MESA; N = 808) cohort and the Osteoporotic Fractures in Men (MrOS; N = 817) cohort. SLAMSS achieves an overall accuracy of 79%, weighted F1 score of 0.80, 77% sensitivity, and 89% specificity for three-class sleep staging and an overall accuracy of 70-72%, weighted F1 score of 0.72-0.73, 64-66% sensitivity, and 89-90% specificity for four-class sleep staging in the MESA cohort. It yielded an overall accuracy of 77%, weighted F1 score of 0.77, 74% sensitivity, and 88% specificity for three-class sleep staging and an overall accuracy of 68-69%, weighted F1 score of 0.68-0.69, 60-63% sensitivity, and 88-89% specificity for four-class sleep staging in the MrOS cohort. These results were achieved with feature-poor inputs with a low temporal resolution. In addition, we extended our three-class staging model to an unrelated Apple Watch dataset. Importantly, SLAMSS predicts the duration of each sleep stage with high accuracy. This is especially significant for four-class sleep staging, where deep sleep is severely underrepresented. We show that, by appropriately choosing the loss function to address the inherent class imbalance, our method can accurately estimate deep sleep time (SLAMSS/MESA: 0.61±0.69 hours, PSG/MESA ground truth: 0.60±0.60 hours; SLAMSS/MrOS: 0.53±0.66 hours, PSG/MrOS ground truth: 0.55±0.57 hours;). Deep sleep quality and quantity are vital metrics and early indicators for a number of diseases. Our method, which enables accurate deep sleep estimation from wearables-derived data, is therefore promising for a variety of clinical applications requiring long-term deep sleep monitoring.

Obstructive Sleep Apnea and Longitudinal Changes in Interstitial Lung Imaging and Lung Function: The MESA Study

Rationale: Obstructive sleep apnea (OSA) has been hypothesized to be a risk factor in interstitial lung disease (ILD) and is associated with radiological markers that may represent the earlier stages of ILD. Prior studies have been limited by their cross-sectional design and potential confounding by body habitus. Objectives: To test the hypothesis that OSA severity is associated with more high-attenuation areas (HAAs) on computed tomography and worse lung function over time among older community-dwelling adults. Methods: We used data from participants in the MESA (Multi-Ethnic Study of Atherosclerosis) who had apnea-hypopnea index (AHI) measured from polysomnography (2010-2013), high attenuation areas (HAAs, -600 to -250 Hounsfield units, n = 784), assessments from exams 5 (2010-2012) and 6 (2016-2018) full-lung computed tomography scans, and spirometry assessments (n = 677). Linear mixed-effects models with random intercept were used to examine associations of OSA severity (i.e., AHI and hypoxic burden) with changes in HAAs, total lung volumes, and forced vital capacity (FVC) between exams 5 and 6. Potential confounders were adjusted for in the model, including age, sex, smoking history, height, and weight. Results: Among those with a higher AHI there were more men and a higher body mass index. Participants with AHI ⩾ 15 events/h and in the highest hypoxic burden quartile each had increases in HAAs of 11.30% (95% confidence interval [CI], 3.74-19.35%) and 9.85% (95% CI, 1.40-19.01%) per 10 years, respectively. There was a more rapid decline in total lung volumes imaged and FVC among those with AHI ⩾ 15 events/h of 220.2 ml (95% CI, 47.8-392.5 ml) and 3.63% (95% CI, 0.43-6.83%) per 10 years, respectively. Conclusions: A greater burden of hypoxia related to obstructive events during sleep was associated with increased lung densities over time and a more rapid decline in lung volumes regardless of body habitus. Our findings suggest OSA may be a contributing factor in the early stages of ILD.

The genetic determinants of recurrent somatic mutations in 43,693 blood genomes

Nononcogenic somatic mutations are thought to be uncommon and inconsequential. To test this, we analyzed 43,693 National Heart, Lung and Blood Institute Trans-Omics for Precision Medicine blood whole genomes from 37 cohorts and identified 7131 non-missense somatic mutations that are recurrently mutated in at least 50 individuals. These recurrent non-missense somatic mutations (RNMSMs) are not clearly explained by other clonal phenomena such as clonal hematopoiesis. RNMSM prevalence increased with age, with an average 50-year-old having 27 RNMSMs. Inherited germline variation associated with RNMSM acquisition. These variants were found in genes involved in adaptive immune function, proinflammatory cytokine production, and lymphoid lineage commitment. In addition, the presence of eight specific RNMSMs associated with blood cell traits at effect sizes comparable to Mendelian genetic mutations. Overall, we found that somatic mutations in blood are an unexpectedly common phenomenon with ancestry-specific determinants and human health consequences.

The genetic etiology of periodic limb movement in sleep

STUDY OBJECTIVES

Periodic limb movement in sleep is a common sleep phenotype characterized by repetitive leg movements that occur during or before sleep. We conducted a genome-wide association study (GWAS) of periodic limb movements in sleep (PLMS) using a joint analysis (i.e., discovery, replication, and joint meta-analysis) of four cohorts (MrOS, the Wisconsin Sleep Cohort Study, HypnoLaus, and MESA), comprised of 6843 total subjects.

METHODS

The MrOS study and Wisconsin Sleep Cohort Study (N = 1745 cases) were used for discovery. Replication in the HypnoLaus and MESA cohorts (1002 cases) preceded joint meta-analysis. We also performed LD score regression, estimated heritability, and computed genetic correlations between potentially associated traits such as restless leg syndrome (RLS) and insomnia. The causality and direction of the relationships between PLMS and RLS was evaluated using Mendelian randomization.

RESULTS

We found 2 independent loci were significantly associated with PLMS: rs113851554 (p = 3.51 × 10-12, β = 0.486), an SNP located in a putative regulatory element of intron eight of MEIS1 (2p14); and rs9369062 (p = 3.06 × 10-22, β = 0.2093), a SNP located in the intron region of BTBD9 (6p12); both of which were also lead signals in RLS GWAS. PLMS is genetically correlated with insomnia, risk of stroke, and RLS, but not with iron deficiency. Pleiotropy adjusted Mendelian randomization analysis identified a causal effect of RLS on PLMS.

CONCLUSIONS

Because PLMS is more common than RLS, PLMS may have multiple causes and additional studies are needed to further validate these findings.

Associations between Aircraft Noise Exposure and Self-Reported Sleep Duration and Quality in the United States-Based Prospective Nurses' Health Study Cohort

BACKGROUND

Sleep disruption is linked with chronic disease, and aircraft noise can disrupt sleep. However, there are few investigations of aircraft noise and sleep in large cohorts.

OBJECTIVES

We examined associations between aircraft noise and self-reported sleep duration and quality in the Nurses' Health Study, a large prospective cohort.

METHODS

Aircraft nighttime equivalent sound levels (Lnight) and day-night average sound levels (DNL) were modeled around 90 U.S. airports from 1995 to 2015 in 5-y intervals using the Aviation Environmental Design Tool and linked to geocoded participant residential addresses. Lnight exposure was dichotomized at the lowest modeled level of 45 A-weighted decibels [dB(A)] and at multiple cut points for DNL. Multiple categories of both metrics were compared with < 45 dB(A). Self-reported short sleep duration (< 7 h/24-h day) was ascertained in 2000, 2002, 2008, 2012, and 2014, and poor sleep quality (frequent trouble falling/staying asleep) was ascertained in 2000. We analyzed repeated sleep duration measures using generalized estimating equations and sleep quality by conditional logistic regression. We adjusted for participant-level demographics, behaviors, comorbidities, and environmental exposures (greenness and light at night) and examined effect modification.

RESULTS

In 35,226 female nurses averaging 66.1 years of age at baseline, prevalence of short sleep duration and poor sleep quality were 29.6% and 13.1%, respectively. In multivariable models, exposure to Lnight ≥ 45 dB(A) was associated with 23% [95% confidence interval (CI): 7%, 40%] greater odds of short sleep duration but was not associated with poor sleep quality (9% lower odds; 95% CI: - 30 % , 19%). Increasing categories of Lnight and DNL ≥ 45 dB(A) suggested an exposure-response relationship for short sleep duration. We observed higher magnitude associations among participants living in the West, near major cargo airports, and near water-adjacent airports and among those reporting no hearing loss.

DISCUSSION

Aircraft noise was associated with short sleep duration in female nurses, modified by individual and airport characteristics. https://doi.org/10.1289/EHP10959.