Leveraging pleiotropy to discover and interpret GWAS results for sleep-associated traits.

Genetic association studies of many heritable traits resulting from physiological testing often have modest sample sizes due to the cost and burden of the required phenotyping. This reduces statistical power and limits discovery of multiple genetic associations. We present a strategy to leverage pleiotropy between traits to both discover new loci and to provide mechanistic hypotheses of the underlying pathophysiology. Specifically, we combine a colocalization test with a locus-level test of pleiotropy. In simulations, we show that this approach is highly selective for identifying true pleiotropy driven by the same causative variant, thereby improves the chance to replicate the associations in underpowered validation cohorts and leads to higher interpretability. Here, as an exemplar, we use Obstructive Sleep Apnea (OSA), a common disorder diagnosed using overnight multi-channel physiological testing. We leverage pleiotropy with relevant cellular and cardio-metabolic phenotypes and gene expression traits to map new risk loci in an underpowered OSA GWAS. We identify several pleiotropic loci harboring suggestive associations to OSA and genome-wide significant associations to other traits, and show that their OSA association replicates in independent cohorts of diverse ancestries. By investigating pleiotropic loci, our strategy allows proposing new hypotheses about OSA pathobiology across many physiological layers. For example, we identify and replicate the pleiotropy across the plateletcrit, OSA and an eQTL of DNA primase subunit 1 (PRIM1) in immune cells. We find suggestive links between OSA, a measure of lung function (FEV1/FVC), and an eQTL of matrix metallopeptidase 15 (MMP15) in lung tissue. We also link a previously known genome-wide significant peak for OSA in the hexokinase 1 (HK1) locus to hematocrit and other red blood cell related traits. Thus, the analysis of pleiotropic associations has the potential to assemble diverse phenotypes into a chain of mechanistic hypotheses that provide insight into the pathogenesis of complex human diseases.

Association of back pain with all-cause and cause-specific mortality among older men: a cohort study.

OBJECTIVE: We evaluated whether more severe back pain phenotypes-persistent, frequent, or disabling back pain-are associated with higher mortality rate among older men. METHODS: In this secondary analysis of a prospective cohort, the Osteoporotic Fractures in Men (MrOS) study, we evaluated mortality rates by back pain phenotype among 5215 older community-dwelling men (mean age, 73 years, SD = 5.6) from 6 sites in the United States. The primary back pain measure used baseline and Year 5 back pain questionnaire data to characterize participants as having no back pain, nonpersistent back pain, infrequent persistent back pain, or frequent persistent back pain. Secondary measures of back pain from the Year 5 questionnaire included disabling back pain phenotypes. The main outcomes measured were all-cause and cause-specific death. RESULTS: After the Year 5 exam, during up to 18 years of follow-up (mean follow-up = 10.3 years), there were 3513 deaths (1218 cardiovascular, 764 cancer, 1531 other). A higher proportion of men with frequent persistent back pain versus no back pain died (78% versus 69%; sociodemographic-adjusted HR = 1.27, 95% CI = 1.11-1.45). No association was evident after further adjustment for health-related factors, such as self-reported general health and comorbid chronic health conditions (fully adjusted HR = 1.00; 95% CI = 0.86-1.15). Results were similar for cardiovascular deaths and other deaths, but we observed no association of back pain with cancer deaths. Secondary back pain measures, including back-related disability, were associated with increased mortality risk that remained statistically significant in fully adjusted models. CONCLUSION: Although frequent persistent back pain was not independently associated with risk of death in older men, additional secondary disabling back pain phenotypes were independently associated with increased mortality rate. Future investigations should evaluate whether improvements in disabling back pain affect general health and well-being or risk of death.

Sleep Apnea Physiological Burdens and Cardiovascular Morbidity and Mortality.

Rationale: Obstructive sleep apnea is characterized by frequent reductions in ventilation, leading to oxygen desaturations and/or arousals. Objectives: In this study, association of hypoxic burden with incident cardiovascular disease (CVD) was examined and compared with that of "ventilatory burden" and "arousal burden." Finally, we assessed the extent to which the ventilatory burden, visceral obesity, and lung function explain variations in hypoxic burden. Methods: Hypoxic, ventilatory, and arousal burdens were measured from baseline polysomnograms in the Multi-Ethnic Study of Atherosclerosis (MESA) and the Osteoporotic Fractures in Men (MrOS) studies. Ventilatory burden was defined as event-specific area under ventilation signal (mean normalized, area under the mean), and arousal burden was defined as the normalized cumulative duration of all arousals. The adjusted hazard ratios for incident CVD and mortality were calculated. Exploratory analyses quantified contributions to hypoxic burden of ventilatory burden, baseline oxygen saturation as measured by pulse oximetry, visceral obesity, and spirometry parameters. Measurements and Main Results: Hypoxic and ventilatory burdens were significantly associated with incident CVD (adjusted hazard ratio [95% confidence interval] per 1 SD increase in hypoxic burden: MESA, 1.45 [1.14, 1.84]; MrOS, 1.13 [1.02, 1.26]; ventilatory burden: MESA, 1.38 [1.11, 1.72]; MrOS, 1.12 [1.01, 1.25]), whereas arousal burden was not. Similar associations with mortality were also observed. Finally, 78% of variation in hypoxic burden was explained by ventilatory burden, whereas other factors explained only <2% of variation. Conclusions: Hypoxic and ventilatory burden predicted CVD morbidity and mortality in two population-based studies. Hypoxic burden is minimally affected by measures of adiposity and captures the risk attributable to ventilatory burden of obstructive sleep apnea rather than a tendency to desaturate.

From sleep patterns to heart rhythm: Predicting atrial fibrillation from overnight polysomnograms.

BACKGROUND: Atrial fibrillation (AF) is often asymptomatic and thus under-observed. Given the high risks of stroke and heart failure among patients with AF, early prediction and effective management are crucial. Given the prevalence of obstructive sleep apnea among AF patients, electrocardiogram (ECG) analysis from polysomnography (PSG) offers a unique opportunity for early AF prediction. Our aim is to identify individuals at high risk of AF development from single­lead ECGs during standard PSG. METHODS: We analyzed 18,782 single­lead ECG recordings from 13,609 subjects undergoing PSG at the Massachusetts General Hospital sleep laboratory. AF presence was identified using ICD-9/10 codes. The dataset included 15,913 recordings without AF history and 2054 recordings from patients diagnosed with AF between one month to fifteen years post-PSG. Data were partitioned into training, validation, and test cohorts ensuring that individual patients remained exclusive to each cohort. The test set was held out during the training process. We employed two different methods for feature extraction to build a final model for AF prediction: Extraction of hand-crafted ECG features and a deep learning method. For extraction of ECG-hand-crafted features, recordings were split into 30-s windows, and those with a signal quality index (SQI) below 0.95 were discarded. From each remaining window, 150 features were extracted from the time, frequency, time-frequency domains, and phase-space reconstructions of the ECG. A compilation of 12 statistical features summarized these window-specific features per recording, resulting in 1800 features (12 × 150). A pre-trained deep neural network from the PhysioNet Challenge 2021 was updated using transfer learning to discriminate recordings with and without AF. The model processed PSG ECGs in 16-s windows to generate AF probabilities, from which 13 statistical features were extracted. Combining 1800 features from feature extraction with 13 from the deep learning model, we performed a feature selection and subsequently trained a shallow neural network to predict future AF and evaluated its performance on the test cohort. RESULTS: On the test set, our model exhibited sensitivity, specificity, and precision of 0.67, 0.81, and 0.3, respectively, for AF prediction. Survival analysis revealed a hazard ratio of 8.36 (p-value: 1.93 × 10-52) for AF outcomes using the log-rank test. CONCLUSIONS: Our proposed ECG analysis method, utilizing overnight PSG data, shows promise in AF prediction despite modest precision, suggesting false positives. This approach could enable low-cost screening and proactive treatment for high-risk patients. Refinements, including additional physiological parameters, may reduce false positives, enhancing clinical utility and accuracy.

Sleep Duration Polygenic Risk and Phenotype: Associations with Biomarkers of Accelerated Aging in the Baltimore Longitudinal Study of Aging.

We sought to explore whether genetic risk for, and self-reported, short sleep are associated with biological aging and whether age and sex moderate these associations. Participants were a subset of individuals from the Baltimore Longitudinal Study of Aging who had complete data on self-reported sleep (n = 567) or genotype (n = 367). Outcomes included: Intrinsic Horvath age, Hannum age, PhenoAge, GrimAge, and DNAm-based estimates of plasminogen activator inhibitor-1 (PAI-1) and granulocyte count. Results demonstrated that polygenic risk for short sleep was positively associated with granulocyte count; compared to those reporting <6 hr sleep, those reporting >7 hr demonstrated faster PhenoAge and GrimAge acceleration and higher estimated PAI-1. Polygenic risk for short sleep and self-reported sleep duration interacted with age and sex in their associations with some of the outcomes. Findings highlight that polygenic risk for short sleep and self-reported long sleep is associated with variation in the epigenetic landscape and subsequently aging.

Multivariate prediction of cognitive performance from the sleep electroencephalogram.

Human cognitive performance is a key function whose biological foundations have been partially revealed by genetic and brain imaging studies. The sleep electroencephalogram (EEG) is tightly linked to structural and functional features of the central nervous system and serves as another promising biomarker. We used data from MrOS, a large cohort of older men and cross-validated regularized regression to link sleep EEG features to cognitive performance in cross-sectional analyses. In independent validation samples 2.5-10% of variance in cognitive performance can be accounted for by sleep EEG features, depending on the covariates used. Demographic characteristics account for more covariance between sleep EEG and cognition than health variables, and consequently reduce this association by a greater degree, but even with the strictest covariate sets a statistically significant association is present. Sigma power in NREM and beta power in REM sleep were associated with better cognitive performance, while theta power in REM sleep was associated with worse performance, with no substantial effect of coherence and other sleep EEG metrics. Our findings show that cognitive performance is associated with the sleep EEG (r = 0.283), with the strongest effect ascribed to spindle-frequency activity. This association becomes weaker after adjusting for demographic (r = 0.186) and health variables (r = 0.155), but its resilience to covariate inclusion suggest that it also partially reflects trait-like differences in cognitive ability.

Effect on Patient Safety of a Resident Physician Schedule without 24-Hour Shifts.

BACKGROUND: The effects on patient safety of eliminating extended-duration work shifts for resident physicians remain controversial. METHODS: We conducted a multicenter, cluster-randomized, crossover trial comparing two schedules for pediatric resident physicians during their intensive care unit (ICU) rotations: extended-duration work schedules that included shifts of 24 hours or more (control schedules) and schedules that eliminated extended shifts and cycled resident physicians through day and night shifts of 16 hours or less (intervention schedules). The primary outcome was serious medical errors made by resident physicians, assessed by intensive surveillance, including direct observation and chart review. RESULTS: The characteristics of ICU patients during the two work schedules were similar, but resident physician workload, described as the mean (±SD) number of ICU patients per resident physician, was higher during the intervention schedules than during the control schedules (8.8±2.8 vs. 6.7±2.2). Resident physicians made more serious errors during the intervention schedules than during the control schedules (97.1 vs. 79.0 per 1000 patient-days; relative risk, 1.53; 95% confidence interval [CI], 1.37 to 1.72; P<0.001). The number of serious errors unitwide were likewise higher during the intervention schedules (181.3 vs. 131.5 per 1000 patient-days; relative risk, 1.56; 95% CI, 1.43 to 1.71). There was wide variability among sites, however; errors were lower during intervention schedules than during control schedules at one site, rates were similar during the two schedules at two sites, and rates were higher during intervention schedules than during control schedules at three sites. In a secondary analysis that was adjusted for the number of patients per resident physician as a potential confounder, intervention schedules were no longer associated with an increase in errors. CONCLUSIONS: Contrary to our hypothesis, resident physicians who were randomly assigned to schedules that eliminated extended shifts made more serious errors than resident physicians assigned to schedules with extended shifts, although the effect varied by site. The number of ICU patients cared for by each resident physician was higher during schedules that eliminated extended shifts. (Funded by the National Heart, Lung, and Blood Institute; ROSTERS ClinicalTrials.gov number, NCT02134847.).

Targeted Genome Sequencing Identifies Multiple Rare Variants in Caveolin-1 Associated with Obstructive Sleep Apnea.

Rationale: Obstructive sleep apnea (OSA) is a common disorder associated with increased risk for cardiovascular disease, diabetes, and premature mortality. There is strong clinical and epidemiologic evidence supporting the importance of genetic factors influencing OSA but limited data implicating specific genes. Objectives: To search for rare variants contributing to OSA severity. Methods: Leveraging high-depth genomic sequencing data from the NHLBI Trans-Omics for Precision Medicine (TOPMed) program and imputed genotype data from multiple population-based studies, we performed linkage analysis in the CFS (Cleveland Family Study), followed by multistage gene-based association analyses in independent cohorts for apnea-hypopnea index (AHI) in a total of 7,708 individuals of European ancestry. Measurements and Main Results: Linkage analysis in the CFS identified a suggestive linkage peak on chromosome 7q31 (LOD = 2.31). Gene-based analysis identified 21 noncoding rare variants in CAV1 (Caveolin-1) associated with lower AHI after accounting for multiple comparisons (P = 7.4 × 10-8). These noncoding variants together significantly contributed to the linkage evidence (P < 10-3). Follow-up analysis revealed significant associations between these variants and increased CAV1 expression, and increased CAV1 expression in peripheral monocytes was associated with lower AHI (P = 0.024) and higher minimum overnight oxygen saturation (P = 0.007). Conclusions: Rare variants in CAV1, a membrane-scaffolding protein essential in multiple cellular and metabolic functions, are associated with higher CAV1 gene expression and lower OSA severity, suggesting a novel target for modulating OSA severity.

Automated Sleep Stages Classification Using Convolutional Neural Network From Raw and Time-Frequency Electroencephalogram Signals: Systematic Evaluation Study.

BACKGROUND: Most existing automated sleep staging methods rely on multimodal data, and scoring a specific epoch requires not only the current epoch but also a sequence of consecutive epochs that precede and follow the epoch. OBJECTIVE: We proposed and tested a convolutional neural network called SleepInceptionNet, which allows sleep classification of a single epoch using a single-channel electroencephalogram (EEG). METHODS: SleepInceptionNet is based on our systematic evaluation of the effects of different EEG preprocessing methods, EEG channels, and convolutional neural networks on automatic sleep staging performance. The evaluation was performed using polysomnography data of 883 participants (937,975 thirty-second epochs). Raw data of individual EEG channels (ie, frontal, central, and occipital) and 3 specific transformations of the data, including power spectral density, continuous wavelet transform, and short-time Fourier transform, were used separately as the inputs of the convolutional neural network models. To classify sleep stages, 7 sequential deep neural networks were tested for the 1D data (ie, raw EEG and power spectral density), and 16 image classifier convolutional neural networks were tested for the 2D data (ie, continuous wavelet transform and short-time Fourier transform time-frequency images). RESULTS: The best model, SleepInceptionNet, which uses time-frequency images developed by the continuous wavelet transform method from central single-channel EEG data as input to the InceptionV3 image classifier algorithm, achieved a Cohen κ agreement of 0.705 (SD 0.077) in reference to the gold standard polysomnography. CONCLUSIONS: SleepInceptionNet may allow real-time automated sleep staging in free-living conditions using a single-channel EEG, which may be useful for on-demand intervention or treatment during specific sleep stages.

Sequencing Analysis at 8p23 Identifies Multiple Rare Variants in DLC1 Associated with Sleep-Related Oxyhemoglobin Saturation Level.

Average arterial oxyhemoglobin saturation during sleep (AvSpO2S) is a clinically relevant measure of physiological stress associated with sleep-disordered breathing, and this measure predicts incident cardiovascular disease and mortality. Using high-depth whole-genome sequencing data from the National Heart, Lung, and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) project and focusing on genes with linkage evidence on chromosome 8p23,1,2 we observed that six coding and 51 noncoding variants in a gene that encodes the GTPase-activating protein (DLC1) are significantly associated with AvSpO2S and replicated in independent subjects. The combined DLC1 association evidence of discovery and replication cohorts reaches genome-wide significance in European Americans (p = 7.9 × 10-7). A risk score for these variants, built on an independent dataset, explains 0.97% of the AvSpO2S variation and contributes to the linkage evidence. The 51 noncoding variants are enriched in regulatory features in a human lung fibroblast cell line and contribute to DLC1 expression variation. Mendelian randomization analysis using these variants indicates a significant causal effect of DLC1 expression in fibroblasts on AvSpO2S. Multiple sources of information, including genetic variants, gene expression, and methylation, consistently suggest that DLC1 is a gene associated with AvSpO2S.

Association of sleep duration and insomnia with metabolic syndrome and its components in the Women's Health Initiative.

BACKGROUND: Epidemiological evidence suggests that inadequate sleep duration and insomnia may be associated with increased risk of metabolic syndrome (MetS). However, longitudinal data with repeated measures of sleep duration and insomnia and of MetS are limited. We examined the association of sleep duration and insomnia with MetS and its components using longitudinal data from the Women's Health Initiative (WHI). METHODS: The study included postmenopausal women (ages 50-79 years) diabetes-free at enrollment in the WHI, with baseline data on sleep duration (n = 5,159), insomnia (n = 5,063), MetS, and its components. Repeated measures of self-reported sleep duration and insomnia were available from years 1 or 3 of follow-up and of the MetS components from years 3, 6 and 9. Associations were assessed using logistic regression and generalized estimating equations models, and odds ratios and 95% confidence intervals (CI) adjusted for major risk factors were calculated. RESULTS: In cross-sectional analysis, baseline sleep duration ≥ 9 h was positively associated with MetS (OR = 1.51; 95%CI 1.12-2.04), while sleep duration of 8- < 9 h was associated with waist circumference > 88 cm and triglycerides ≥ 150 mg/dL (OR = 1.18; 95%CI 1.01-1.40 and OR = 1.23; 95%CI 1.05-1.46, respectively). Insomnia had a borderline positive association with MetS (OR = 1.14; 95%CI 0.99-1.31), and significant positive associations with waist circumference > 88 cm and glucose ≥ 100 mg/dL (OR = 1.18; 95%CI 1.03-1.34 and OR = 1.17; 95%CI 1.02-1.35, respectively). In the longitudinal analysis, change from restful sleep to insomnia over time was associated with increased odds of developing MetS (OR = 1.40; 95%CI 1.01-1.94), and of a triglyceride level ≥ 150 mg/dL (OR = 1.48; 95%CI 1.08-2.03). CONCLUSIONS: Among postmenopausal women in the WHI, sleep duration and insomnia were associated with current and future risk of MetS and some of its components.

Associations of variants In the hexokinase 1 and interleukin 18 receptor regions with oxyhemoglobin saturation during sleep.

Sleep disordered breathing (SDB)-related overnight hypoxemia is associated with cardiometabolic disease and other comorbidities. Understanding the genetic bases for variations in nocturnal hypoxemia may help understand mechanisms influencing oxygenation and SDB-related mortality. We conducted genome-wide association tests across 10 cohorts and 4 populations to identify genetic variants associated with three correlated measures of overnight oxyhemoglobin saturation: average and minimum oxyhemoglobin saturation during sleep and the percent of sleep with oxyhemoglobin saturation under 90%. The discovery sample consisted of 8,326 individuals. Variants with p < 1 × 10(-6) were analyzed in a replication group of 14,410 individuals. We identified 3 significantly associated regions, including 2 regions in multi-ethnic analyses (2q12, 10q22). SNPs in the 2q12 region associated with minimum SpO2 (rs78136548 p = 2.70 × 10(-10)). SNPs at 10q22 were associated with all three traits including average SpO2 (rs72805692 p = 4.58 × 10(-8)). SNPs in both regions were associated in over 20,000 individuals and are supported by prior associations or functional evidence. Four additional significant regions were detected in secondary sex-stratified and combined discovery and replication analyses, including a region overlapping Reelin, a known marker of respiratory complex neurons.These are the first genome-wide significant findings reported for oxyhemoglobin saturation during sleep, a phenotype of high clinical interest. Our replicated associations with HK1 and IL18R1 suggest that variants in inflammatory pathways, such as the biologically-plausible NLRP3 inflammasome, may contribute to nocturnal hypoxemia.

Subjective social status moderates back pain and mental health in older men.

OBJECTIVES: Back pain and poor mental health are interrelated issues in older men. Evidence suggests that socioeconomic status moderates this relationship, but less is known about the role of subjective social status (SSS). This study examined if the association between back pain and mental health is moderated by SSS. METHOD: We used a sample of community-dwelling older men (≥65 years) from the Osteoporotic Fractures in Men Study (N = 5994). Participants self-reported their back pain severity and frequency over the past 12 months. SSS was assessed with the MacArthur Scale of SSS. Mental health was assessed with the SF-12 Mental Component Summary (MCS). RESULTS: Severe back pain was associated with lower SF-12 MCS scores (p = .03). Back pain frequency was not associated with SF-12 MCS scores. SSS moderated the back pain and mental health relationship. Among men with higher national or community SSS, the association between back pain severity and SF-12 MCS scores was not significant. However, among men with lower national or community SSS, more severe back pain was associated with lower SF-12 MCS scores (p's < .001). Among those with lower national or community SSS, greater back pain frequency was also associated with lower SF-12 MCS scores (p's < .05). CONCLUSION: Where one ranks oneself within their nation or community matters for the back pain and mental health relationship. Higher SSS may be a psychosocial resource that buffers the negative associations of severe and frequent back pain on mental health in older men.

The Role of Social Support in Coping with Psychological Trauma: An Integrated Biopsychosocial Model for Posttraumatic Stress Recovery.

This theoretical review proposes an integrated biopsychosocial model for stress recovery, highlighting the interconnectedness of intra- and interpersonal coping processes. The proposed model is conceptually derived from prior research examining interpersonal dynamics in the context of stressor-related disorders, and it highlights interconnections between relational partner dynamics, perceived self-efficacy, self-discovery, and biological stress responsivity during posttraumatic recovery. Intra- and interpersonal processes are discussed in the context of pre-, peri-, and post-trauma stress vulnerability as ongoing transactions occurring within the individual and between the individual and their environment. The importance of adopting an integrated model for future traumatic stress research is discussed. Potential applications of the model to behavioral interventions are also reviewed, noting the need for more detailed assessments of relational dynamics and therapeutic change mechanisms to determine how relational partners can most effectively contribute to stress recovery.

Admixture mapping identifies novel loci for obstructive sleep apnea in Hispanic/Latino Americans.

Obstructive sleep apnea (OSA) is a common disorder associated with increased risk of cardiovascular disease and mortality. Its prevalence and severity vary across ancestral background. Although OSA traits are heritable, few genetic associations have been identified. To identify genetic regions associated with OSA and improve statistical power, we applied admixture mapping on three primary OSA traits [the apnea hypopnea index (AHI), overnight average oxyhemoglobin saturation (SaO2) and percentage time SaO2 < 90%] and a secondary trait (respiratory event duration) in a Hispanic/Latino American population study of 11 575 individuals with significant variation in ancestral background. Linear mixed models were performed using previously inferred African, European and Amerindian local genetic ancestry markers. Global African ancestry was associated with a lower AHI, higher SaO2 and shorter event duration. Admixture mapping analysis of the primary OSA traits identified local African ancestry at the chromosomal region 2q37 as genome-wide significantly associated with AHI (P < 5.7 × 10-5), and European and Amerindian ancestries at 18q21 suggestively associated with both AHI and percentage time SaO2 < 90% (P < 10-3). Follow-up joint ancestry-SNP association analyses identified novel variants in ferrochelatase (FECH), significantly associated with AHI and percentage time SaO2 < 90% after adjusting for multiple tests (P < 8 × 10-6). These signals contributed to the admixture mapping associations and were replicated in independent cohorts. In this first admixture mapping study of OSA, novel associations with variants in the iron/heme metabolism pathway suggest a role for iron in influencing respiratory traits underlying OSA.

Spectral sleep electroencephalographic correlates of sleep efficiency, and discrepancies between actigraphy and self-reported measures, in older men.

Discrepancies between actigraphic and self-reported sleep measures are common. Studies of people with insomnia, in whom both sleep disturbances and discrepancy are common, suggest disturbances and discrepancy reflect differences in the sleeping brain's activity measurable using spectral electroencephalogram (EEG). Disentangling effects of discrepancy and disturbance on sleep EEG could help target research on the consequences and treatments of different sleep phenotypes. We therefore categorized participants in a cohort study including 2,850 men (average age = 76 years, standard deviation = 5.5) into four groups using median splits on actigraphic and self-reported sleep efficiency (SE). We compared spectral power between these groups in 1-Hz bins up to 24 Hz. Compared with the concordant-high SE group: (a) the group with high actigraphic and low self-reported SE had higher spectral power from 11-15 Hz across the night; (b) both groups with low actigraphic SE had higher power across the 15-24 Hz range, predominantly in early cycles, and greater slow frequency power in later cycles. These findings suggest that perceived wakefulness undetected by actigraphy may result from or drive activity corresponding to spindles. We also found, consistent with hyperarousal models, that low SE detectable via actigraphy was related to higher frequency power in the beta range; actigraph-measured inefficiency was also associated with later slow oscillations, potentially representing attempts to dissipate homeostatic drive elevated from earlier hyperarousal. These distinct spectral EEG markers (of low SE measured with actigraphy vs. low perceived SE that is not captured by actigraphy) may have different causes or consequences.

Physiological sleep measures predict time to 15-year mortality in community adults: Application of a novel machine learning framework.

Clarifying whether physiological sleep measures predict mortality could inform risk screening; however, such investigations should account for complex and potentially non-linear relationships among health risk factors. We aimed to establish the predictive utility of polysomnography (PSG)-assessed sleep measures for mortality using a novel permutation random forest (PRF) machine learning framework. Data collected from the years 1995 to present are from the Sleep Heart Health Study (SHHS; n = 5,734) and the Wisconsin Sleep Cohort Study (WSCS; n = 1,015), and include initial assessments of sleep and health, and up to 15 years of follow-up for all-cause mortality. We applied PRF models to quantify the predictive abilities of 24 measures grouped into five domains: PSG-assessed sleep (four measures), self-reported sleep (three), health (eight), health behaviours (four), and sociodemographic factors (five). A 10-fold repeated internal validation (WSCS and SHHS combined) and external validation (training in SHHS; testing in WSCS) were used to compute unbiased variable importance metrics and associated p values. We observed that health, sociodemographic factors, and PSG-assessed sleep domains predicted mortality using both external validation and repeated internal validation. The PSG-assessed sleep efficiency and the percentage of sleep time with oxygen saturation <90% were among the most predictive individual measures. Multivariable Cox regression also revealed the PSG-assessed sleep domain to be predictive, with very low sleep efficiency and high hypoxaemia conferring the highest risk. These findings, coupled with the emergence of new low-burden technologies for objectively assessing sleep and overnight oxygen saturation, suggest that consideration of physiological sleep measures may improve risk screening.

Later high school start time is associated with lower migraine frequency in adolescents.

OBJECTIVE: To determine whether high school start time is associated with headache frequency in adolescents with migraine. BACKGROUND: Adolescence is marked by a physiologic delayed circadian phase, characterized by later bedtimes and wake times. The American Academy of Pediatrics (AAP) recommends that high schools start no earlier than 8:30 a.m., but most high schools in the United States start earlier. The study hypothesis was that adolescents with migraine whose high schools start at 8:30 a.m. or later (late group) would have lower headache frequency than those whose schools start earlier than 8:30 a.m. (early group). METHODS: This was a cross-sectional Internet survey study of US high schoolers with migraine recruited online through social media. Comparisons were made between the late group and the early group. The primary outcome measure was self-reported headache days/month. RESULTS: In total, 1012 respondents constituted the analytic set: n = 503 in the late group versus n = 509 in the early group. Mean (SD) self-reported headache days/month was 4.8 (4.6) versus 7.7 (6.1) in the late and early groups, respectively (p < 0.001); mean difference -2.9 (95% CI -2.2 to -3.6). Mean (SD) self-reported hours of sleep on a school night was 7.9 (0.9) versus 6.9 (1.3), p < 0.001. Adjusting for total hours of sleep, sex, taking a migraine preventive, days of acute medication use, hours of homework, grade level, and missing breakfast, mean (SD) self-reported headache days/month remained lower in the late group than in the early group: 5.8 (95% CI 5.3-6.2) versus 7.1 (95% CI 6.7-7.4), (p < 0.001); mean difference -1.3 (95% CI -1.9 to -0.7). CONCLUSION: Adolescents with migraine who attend high schools that follow AAP recommendations for start times have lower self-reported headache frequency than those whose high schools start before 8:30 a.m. If prospective studies confirm this finding, shifting to a later high school start time may be an effective strategy for migraine prevention in adolescents.

Composition of nocturnal hypoxaemic burden and its prognostic value for cardiovascular mortality in older community-dwelling men.

AIMS: To investigate the composition of nocturnal hypoxaemic burden and its prognostic value for cardiovascular (CV) mortality in community-dwelling older men. METHODS AND RESULTS: We analysed overnight oximetry data from polysomnograms obtained in 2840 men from the Outcomes of Sleep Disorders in Older Men (MrOS Sleep) study (ClinicalTrials.gov Identifier: NCT00070681) to determine the number of acute episodic desaturations per hour (oxygen desaturation index, ODI) and time spent below 90% oxygen saturation (T90) attributed to acute desaturations (T90desaturation) and to non-specific drifts in oxygen saturation (T90non-specific), respectively, and their relationship with CV mortality. After 8.8 ± 2.7 years follow-up, 185 men (6.5%) died from CV disease. T90 [hazard ratio (HR) 1.21, P < 0.001], but not ODI (HR 1.13, P = 0.06), was significantly associated with CV death in univariate analysis. T90 remained significant when adjusting for potential confounders (HR 1.16, P = 0.004). Men with T90 > 12 min were at an elevated risk of CV mortality (HR 1.59; P = 0.006). Approximately 20.7 (5.7-48.5) percent of the variation in T90 could be attributed to non-specific drifts in oxygen saturation. T90desaturation and T90non-specific were individually associated with CV death but combining both variables did not improve the prediction. CONCLUSION: In community-dwelling older men, T90 is an independent predictor of CV mortality. T90 is not only a consequence of frank desaturations, but also reflects non-specific drifts in oxygen saturation, both contributing towards the association with CV death. Whether T90 can be used as a risk marker in the clinical setting and whether its reduction may constitute a treatment target warrants further study.

International, evidence-based consensus treatment guidelines for idiopathic multicentric Castleman disease.

Castleman disease (CD) describes a group of heterogeneous hematologic disorders with characteristic histopathological features. CD can present with unicentric or multicentric (MCD) regions of lymph node enlargement. Some cases of MCD are caused by human herpesvirus-8 (HHV-8), whereas others are HHV-8-negative/idiopathic (iMCD). Treatment of iMCD is challenging, and outcomes can be poor because no uniform treatment guidelines exist, few systematic studies have been conducted, and no agreed upon response criteria have been described. The purpose of this paper is to establish consensus, evidence-based treatment guidelines based on the severity of iMCD to improve outcomes. An international Working Group of 42 experts from 10 countries was convened by the Castleman Disease Collaborative Network to establish consensus guidelines for the management of iMCD based on published literature, review of treatment effectiveness for 344 cases, and expert opinion. The anti-interleukin-6 monoclonal antibody siltuximab (or tocilizumab, if siltuximab is not available) with or without corticosteroids is the preferred first-line therapy for iMCD. In the most severe cases, adjuvant combination chemotherapy is recommended. Additional agents are recommended, tailored by disease severity, as second- and third-line therapies for treatment failures. Response criteria were formulated to facilitate the evaluation of treatment failure or success. These guidelines should help treating physicians to stratify patients based on disease severity in order to select the best available therapeutic option. An international registry for patients with CD (ACCELERATE, #NCT02817997) was established in October 2016 to collect patient outcomes to increase the evidence base for selection of therapies in the future.