Biological clocks shape metabolism, but how circadian programs govern nutrient processing is unclear. Here, using human metabolomics and 13C6-glucose tracing in Drosophila, we delineate previously under characterized daily oscillations in glucose-derived metabolic networks, providing a mechanistic framework for a purpose-built isotope-tracing approach. In flies, we reveal a pronounced "rush hour" of glucose utilization early in the light phase, with carbons directed to biosynthetic and energetic pathways. By contrast, a dopamine reuptake-deficient hyperactive mutant (fumin) with elevated metabolic rate shows phase-shifted and amplified metabolic peaks, indicating that altered neural signaling reshapes temporal glucose flux. Neither altered feeding schedules nor short-term fasting disrupt these intrinsic metabolic rhythms, strongly suggesting that circadian timing, rather than nutrient availability, orchestrates temporal homeostasis. By integrating human metabolite profiling with isotope-tracing in flies, we define a conserved temporal architecture of glucose utilization and demonstrate that metabolic flux is dynamically gated across the day. Our findings establish a framework for understanding how circadian misalignment contributes to metabolic dysfunction and disease.

Abstract Introduction Sleep-disordered breathing (SDB) is a major global health concern with substantial cardiometabolic consequences, yet its determinants and physiological expression may differ across populations. This study used harmonised data from the Study of Health in Pomerania (SHIP) in Germany and the Korean Genome and Epidemiology Study (KoGES) in South Korea to examine ethnic differences in SDB prevalence, correlates, and metabolic profiles in European and East Asian adults. Methods Participants aged 45 years and older with at least four hours of valid sleep data were included. Demographic, anthropometric, behavioural, and cardiometabolic variables were harmonised to ensure comparability. Age and sex distributions were balanced using inverse probability weighting. SDB severity was defined using apnea–hypopnea index thresholds. Regression models with cohort-by-severity interaction terms evaluated population-specific associations, adjusting for age, sex, and waist-to-height ratio (WHtR), selected for its cross-ethnic comparability. Results Before adjustment, SHIP participants exhibited higher BMI and WHtR, while KoGES participants showed higher diabetes prevalence and elevated HbA1c. In both cohorts, SDB prevalence increased with age and was higher in men. Anthropometric indices rose with increasing severity in both populations, but gradients were steeper in SHIP, indicating a stronger adiposity-linked pathway. Cardiometabolic profiles diverged: in SHIP, greater severity was associated with elevated LDL cholesterol, triglycerides, and hypertension, whereas in KoGES it was linked to increased HbA1c and diabetes prevalence. Adjustment for WHtR reduced inter-cohort differences in lipid and blood pressure markers but did not eliminate disparities in glycaemic outcomes, suggesting distinct metabolic susceptibility. Conclusion Although central adiposity is a shared determinant of SDB, the physiological consequences of higher severity differ across populations. In the European cohort, SDB was more strongly linked to vascular and lipid-related burden, whereas in the East Asian cohort it was more closely associated with impaired glucose regulation, reflecting heightened glycaemic vulnerability. These population-specific patterns likely stem from differences in fat distribution, metabolic risk, and lifestyle transitions. Overall, SDB manifests through distinct pathways across populations, underscoring the need for tailored screening and management strategies rather than universal clinical models. Support (if any)

OBJECTIVES:Multiple studies have shown that symptom-based subtypes of obstructive sleep apnea (OSA) exist and are generalizable to clinical and population-based samples of different race/ethnic and regional backgrounds. However, there have not been studies evaluating the generalizability within a clinical sample of Chinese ancestry. Thus, the aim of the current study was to investigate the generalizability of symptom-based subtypes within clinical patients from China. METHODS:This is a cross-sectional, multi-center study of patients with OSA from international sleep centers participating in the Sleep Apnea Global Interdisciplinary Consortium (SAGIC). Two Chinese cohorts were collected: 666 patients from Peking University People's Hospital (PKUPH) and 503 patients from other China sites (Peking University International Hospital, Taiwan, and Shanghai). In addition, 694 White patients were included from 7 sites across 5 countries (Iceland, Germany [Berlin], Australia [Sydney, Perth], Brazil, and the United States [Ohio State University and University of Pennsylvania]). Symptom-based subtypes were determined using a latent class analysis (LCA) of 18 self-reported symptom variables and 3 comorbidities. RESULTS:A total of 1,863 patients were included in the LCA. The previously described 5 symptom subtype (disturbed sleep, minimal symptoms, excessively sleepy, moderately sleepy, and upper airway symptoms dominant) were optimal in the PKUPH site, other China sites, and White patients from SAGIC. Chinese patients had higher prevalence of the minimal symptoms subtype (P < .001) compared to White patients. Among the five subtypes, the excessively sleepy subtype exhibited the highest AHI, and ODI. CONCLUSIONS:: Based on the included symptoms and comorbidities, five subtypes provided the optimal groupings across both Chinese and White patients in SAGIC. Chinese patients were more likely to present with fewer symptoms. These data further enhance understanding of the generalizability of OSA symptom subtypes across ethnically diverse backgrounds, and pave the way for precision management of OSA in the future.

Abstract Introduction Large-scale Genome Wide Association Studies (GWAS) have been performed for a variety of sleep traits including insomnia, excessive daytime sleepiness, sleep duration, and chronotype. These studies have provided a wealth of data identifying common genetic variants associated with sleep function and informing biological mechanisms underlying each trait. A primary impediment to interpreting the biological relevance of GWAS loci is that the majority of these variants reside in non-protein-coding regions of the genome often distal to any protein-coding gene. Our work outlines an integrative approach to pinpoint causal genes associated with each GWAS locus using human spatial and functional genomics data paired with cross-species sleep phenotyping. Methods We collected lead and correlated (r2>0.6) proxy variants from published GWAS summary statistics for insomnia and excessive daytime sleepiness. Cis-regulatory regions were defined using ATACseq and Promoter Capture C/Hi-C data collected from 9 different human-derived brain cell types including neural progenitors, neurons, and glia. GWAS variants were intersected with cell-specific cis-regulatory regions to identify putative causal effector genes contacted by each variant. These implicated effector genes were then screened for their effects on sleep using cell-specific GAL4-RNAi (glial or neuronal subtypes) knockdown in Drosophila. Genes showing significant effects on sleep were then validated in a vertebrate model, zebrafish, using CRISPR-mediated knockout paired with sleep phenotyping. Results We identified multiple highly conserved regulators of sleep that mapped to both the nearest gene of the GWAS association (e.g. MEIS1 and CADM2) as well as distal genes that were not previously implicated by these GWAS (e.g. PIGQ and AP3B2). Each of these significantly influenced sleep in both Drosophila and zebrafish in the same direction and showed cell-specific effects when knocked down in Drosophila. Loss of orthologs to MEIS1, which was identified from the insomnia GWAS, showed short and fragmented sleep. Additionally, loss of orthologs to CADM2 and AP3B2, which were identified from the excessive daytime sleepiness GWAS, displayed increased sleep. Conclusion Together our integrative cross-species approach defined highly conserved regulators of sleep from human GWAS associations revealing novel biological targets for intervention. Support (if any) T32 HL07953, T32 HL170968, R01 HL143790, P01 HL094307, and P01 HL160471

How phenotypes are measured, especially when relying on subjective reports, is an impediment to the utility of genome-wide association studies (GWAS). This is a common problem in GWAS for sleep traits, as many sleep disturbances appear subjectively similar despite having distinct underlying pathophysiology. Phenotype refinement is, therefore, necessary to improve our understanding of complex trait biology. Here, we utilise expanded questionnaire data collected from ~180,000 participants in the UK Biobank to help further distinguish insomnia from restless legs syndrome (RLS) from subjective reports. We demonstrate prior GWAS efforts for insomnia likely mischaracterised participants using a single-question approach. Through statistical models, we examine two of the most significant GWAS signals for insomnia, namely at the MEIS1 and BTBD9 loci, finding their effects are largely or completely, driven by their effects on RLS. Collectively, our results underscore the necessity of improving phenotype classification and highlight the utility of newly released UK Biobank data for sleep research.

Abstract Introduction The pathogenesis of obstructive sleep apnea (OSA) is multifactorial and likely involves reduced activation of upper airway (UA) dilator muscles during sleep. The genioglossus, the primary tongue protrusor, contracts with each inspiration to prevent posterior tongue collapse and maintain airway patency. Several OSA therapies target tongue musculature; however, the impact of tongue protrusion strength on OSA severity remains poorly defined. Prior studies examining this relationship lacked comprehensive characterization of UA anatomy, overlooking key structural confounders. Our study aimed to define the relationship between tongue protrusion strength and OSA severity while accounting for tongue volume and fat, as quantified by magnetic resonance imaging (MRI). Methods The sample included 219 participants from the EXPO study, a multicenter, international, case-control study of adults with moderate-to-severe OSA (apnea-hypopnea index [AHI] > 15 events/hr) and controls (AHI < 15). Tongue protrusion strength was derived from the mean of four maximal isometric pressure trials with a pressure transducer. UA anatomy was quantified by MRI, including genioglossus volume, total tongue volume, and fat percentage of tongue. Tongue force measurements were compared between apneics and controls using Pearson correlations (unadjusted) and linear regression adjusted for age, gender, BMI, race, and site. Results Participants were predominantly male (59.4%) with mean age 51.4 years, BMI 30.5 kg/m2, and AHI 22.9 events/hour (135 apneics, 84 controls). Maximal tongue force was not associated with OSA status or severity, in either adjusted or unadjusted analyses. Similarly, in both unadjusted and adjusted analyses, maximal tongue force was not correlated with genioglossus volume, total tongue volume, or tongue fat percentage. Comparisons between apneics and controls showed no significant correlations between maximal tongue force and any of the three anatomic tongue metrics, regardless of adjustment. Conclusion This study is the first to use quantitative MRI of the UA to examine the relationship between tongue strength and OSA severity. Overall, our results indicate that maximal tongue force alone does not explain OSA severity. These findings underscore the importance of considering that tongue strength also includes fatiguability, which may contribute to OSA pathogenesis and inform the development of targeted therapies. Support (if any) NIH Grants P01 HL094307, P01 HL160471, F32HL182221; ATS ASPIRE Fellowship.

Background and objective: The study aims to determine whether respiratory inductance plethysmography (RIP) signals can be used to quantify changes in ventilation and provide advanced obstructive sleep apnea (OSA) severity metrics. This approach seeks to address limitations in current airflow-based OSA measures, particularly those relying on nasal pressure, which may be compromised by oral breathing. Methods: Adult patients with OSA (N = 89, 68Male:21Female) completed in-laboratory polysomnography (PSG) allowing for RIP-based ventilation estimates to be compared against a gold standard oronasal-pneumotach (normalized ventilation %(eupnea)). Concordance was assessed on three levels: 1) individual breath ventilation, 2) individual respiratory event depth (percentage reduction in ventilation from local average), and 3) patient-specific OSA severity in terms of average event depth and ventilatory burden (average event depth x average event duration x event rate). To address overestimation of RIP ventilation during obstruction, we developed and applied a calibration and linearization method ("RIP correction"). Concordance analysis evaluated median bias for both small (<70%(eupnea)) and large breaths (>130%(eupnea)), along with bias and intraclass correlation coefficient (ICC) calculation for events and patient-specific measures. Results: For individual breaths (N = 495,631), RIP correction reduced overestimation bias for small breaths from 12 to 2%(eupnea). For individual events (N = 34,497), RIP correction reduced mean bias for event depth estimates from 9 to 1%(eupnea). For patient-specific analysis underestimation of average event depth was attenuated from 9 to 4%(eupnea) and for ventilatory burden, from 275 to 117%(eupnea) min/hr. Additionally, RIP correction improved ICC for event depth and patient-level traits. Conclusion: RIP signals, with appropriate processing, enable quantification of advanced ventilation-based OSA metrics, addressing concerns that airflow-based measures may be affected by breathing route.

Idiopathic hypersomnia (IH) is a poorly-understood sleep disorder characterized by excessive daytime sleepiness despite normal nighttime sleep. Combining human genomics with behavioral and mechanistic studies in fish and flies, we uncover a role for beat-Ia/CADM2 , synaptic adhesion molecules of the immunoglobulin superfamily, in excessive sleepiness. Neuronal knockdown of Drosophila beat-Ia results in sleepy flies and loss of the vertebrate ortholog of beat-Ia , CADM2 , results in sleepy fish. We delineate a developmental function for beat-Ia in synaptic elaboration of neuropeptide F (NPF) neurites projecting to the suboesophageal zone (SEZ) of the fly brain. Brain connectome and experimental evidence demonstrate these NPF outputs synapse onto a subpopulation of SEZ GABAergic neurons to stabilize arousal. NPF is the Drosophila homolog of vertebrate neuropeptide Y (NPY), and an NPY receptor agonist restores sleep to normal levels in zebrafish lacking CADM2 . These findings point towards NPY modulation as a treatment target for human hypersomnia.

center dot There are multiple different dimensions to the heterogeneity of Obstructive Sleep Apnea (OSA). We need to seek to integrate information from different domains to provide the optimal tool for center dot Much of the focus on personalized medicine approaches to OSA has been on different endotypes. It is proposed that these can be estimated from routine sleep study data using a simple model of ventilatory control. However, whether this provides reliable estimates is currently unknown and there is lack of validation. center dot There are different clinical subtypes of OSA based on symptoms that have been demonstrated in multiple studies worldwide in both population-based and clinical cohorts. Before they are used clinically, they have to be shown to not change over a brief period of time. center dot There are multiple new metrics of severity of OSA. These are proposed to provide better clinical prediction of outcomes than the apnea-hypopnea index (AHI). We need to know if these new metrics are each providing new information or if they are very correlated.

Study objectives Studies on obstructive sleep apnoea (OSA) have identified clinically relevant symptom-based subtypes and novel OSA-specific nocturnal hypoxic measures. Both traits are individually associated with cardiovascular outcomes, but evidence about their independent or shared effects is unknown. This study investigated the simultaneous contributions of OSA symptom subtypes and hypoxic burden (HB) on incident cardiovascular outcomes. Methods Sleep Heart Health Study participants with high-quality oxygen saturation, apnoea–hypopnea index (AHI) and symptom data were included. Participants with OSA (AHI ≥5 events·h−1) were grouped into symptom subtypes. HB was calculated from respiratory event-related hypoxia. Cox proportional hazards models assessed whether symptom subtypes and/or HB were independently associated with cardiovascular mortality and major adverse cardiovascular events (MACE). Results 4396 participants free of cardiovascular disease were analysed, with median follow-up >11 years. Higher HB was associated with worse cardiovascular mortality (HR (95% CI): 1.63 (1.13–2.35); p=0.009) independently of symptom subtypes. Compared to those without OSA, the excessively sleepy OSA subtype had higher risk of incident MACE (1.62 (1.23–2.15); p<0.001), independently of HB. Among participants with moderate–severe OSA (AHI ≥15 events·h−1), excessively sleepy participants had higher risk of cardiovascular end-points compared to other subtypes, but HB was not associated with cardiovascular mortality or MACE risk. Conclusion OSA symptom subtypes and HB are independently associated with MACE and cardiovascular mortality, respectively. Thus, both are important for understanding OSA-related cardiovascular risk. Future studies using clinical samples including OSA therapy information that incorporate symptom subtypes and novel biomarkers, such as HB, could improve predictive models for cardiovascular disease risk.

IntroductionHealthy sleep and wake are integral to good health and occur when an organism is able to maintain long bouts of both sleep and wakefulness. Homer proteins have been shown to be important for sleep in both Drosophila and mice. For example, genetic deletion of Homer1a in mice results in failure to sustain long bouts of wakefulness. Homer1a has also been shown to amplify mGluR activity by facilitating binding of the prolyl isomerase Pin1 to mGluR. This study uses mouse models to evaluate whether the Homer1a null sleep phenotype may be dependent on the mGluR-Pin1 interaction and examines sleep/wake behavior.MethodsEEG recordings were used to determine and compare sleep and wake in three different mouse models and their littermate control mice. Mouse models included: mGluR(TS-AA) knock-in mice in which Pin1 binding is prevented and activity-dependent prolyl isomerization of mGluR is inhibited; mGluR(F-R) knock-in mice in which Homer binding is eliminated but Pin1 binding is allowed; and a Homer1a null, mGluR(F-R) double mutant mouse to evaluate whether Pin1 binding can rescue the Homer1a knock-out phenotype. Sleep-wake behavior was analyzed using traditional summary measures and a spike-and-slab mixture distribution to better characterize microarchitecture.ResultsKnock-in mGluR(TS-AA) mice display a reduced ability to sustain long bouts of wakefulness during the active lights off period, recapitulating part of the previously observed wake phenotype of the Homer1a knock-out mouse. Alteration of the Homer binding site to mGluR in mGluR(F-R) knock-in mice has no effect on the sleep phenotype, whereas crossing the mGluR(F-R) knock-in into the Homer null background resulted in increased duration of long wake bouts, suggesting a restored ability to maintain wakefulness, with other sleep/wake characteristics similar to littermate mice.ConclusionThese studies highlight the role of Pin1 binding to mGluR as a potential mechanism in the control of sleep/wake behavior. Future studies should explore whether other binding partners of Homer and mGluR also affect sleep and wake.

Sleep dysfunctions are highly comorbid with Alzheimer’s disease (AD), though often associated with later stages of AD, sleep disruptions have been noted to appear decades before the onset of cognitive symptoms. Here, we provide the first evidence that genetic factors interact with AD mutations to influence sleep behavior even before the onset of cognitive symptoms. To identify novel genetic factors underlying disordered sleep that precede cognitive decline in our AD-BXD mouse genetic reference panel (n = 179 mice across 25 strains, 7-months-old), we first used sleep phenotypes measured in the PiezoSleep chambers and performed quantitative trait loci (QTL) mapping and discovered Kirrel3 as the novel gene candidate associated with disordered sleep. To further evaluate the causal role of Kirrel3 in susceptibility to sleep decline in the presence of Alzheimer’s disease pathology, we generated mice heterozygous for the Kirrel3 gene with and without the 5XFAD transgene, and then did sleep phenotyping in these mice (n = 153, 7-months-old). We found that in AD-BXD mouse population sleep was highly heritable ( h 2 RIx̄ = 22% – 71%) and varied by light/dark cycle, sex, and the presence of the 5XFAD transgene. This implies high heritability of sleep that lays within the heritability observed in humans. Using QTL mapping we then identified Kirrel3 as a novel genetic factor underlying disordered sleep that precedes AD-related cognitive decline in mice. Further evaluation of sleep changes in Kirrel3 heterozygous mice revealed a significant reduction in total sleep and sleep during dark cycle, for both sexes but only in the presence of 5XFAD transgene. Recent GWAS studies in humans nominated Kirrel3 (aka Neph2) as a potential AD risk gene and as a regulator of sleep behavior (independent of disease). In this study we identified Kirrel3 as a novel genetic factor contributing to disordered sleep that precedes cognitive decline in our AD-BXD mouse genetic reference panel. Further, using Kirrel3 heterozygous mice, we provide, first evidence for the causal role of Kirrel3 in sleep regulation only in the presence of 5XFAD transgene.

AIMS:Studies support the short-term benefit of continuous positive airway pressure (CPAP) therapy on cardiometabolic risk in adults with obstructive sleep apnoea (OSA). Evidence is limited on the benefits of CPAP for preventing acute major adverse cardiovascular events (MACE). This study aimed to assess the association between CPAP use and incidence of MACE in a longitudinal clinical cohort of adults with OSA at a large U.S. healthcare system. METHODS:Adults with OSA (apnoea-hypopnoea index [AHI]≥5) were identified from Kaiser Permanente Southern California between 2018 and 2020 (N = 34,782). MACE was defined as first occurrence of myocardial infarction, stroke, unstable angina, heart failure or cardiovascular death, using validated electronic health record algorithms. CPAP use (h/night) was based on daily telemonitoring data. Inverse probability of treatment weighted Cox proportional hazards models stratified by OSA severity (mild [5≤AHI<15]), moderate-severe [AHI ≥15]), were used to assess associations between CPAP use and MACE. RESULTS:Among individuals with moderate-severe OSA, those using CPAP <4 h/night (HR [95 % CI] = 0.53 [0.35-0.82]; p = 0.004) or ≥4 h/night (HR [95 % CI] = 0.46 [0.27-0.77]; p = 0.004) had lower MACE incidence compared to those not using CPAP. Increased CPAP use (in hours) was associated with lower MACE incidence in moderate-severe OSA (HR [95 % CI] = 0.90 [0.82-0.98]; p = 0.021). In individuals with mild OSA, CPAP use was not associated with lower MACE incidence. CONCLUSION:CPAP use was associated with lower MACE incidence in adults with moderate-severe OSA. Treatment of moderate-severe OSA may have a positive impact on prevention of MACE.

Rationale: Obesity is the most important risk factor for obstructive sleep apnea (OSA). However, the complex relationship between obesity and upper airway anatomy (craniofacial structure, soft tissues, and airway caliber) has not been robustly examined in patients with OSA. Objectives: To evaluate the relationship between obesity, on the basis of body mass index (BMI), and upper airway anatomic structures in adult patients with moderate or severe OSA. Methods: In this cross-sectional study, 583 patients with apnea-hypopnea index ≥15 events/h (mean age, 53.7 ± 10.4 yr; 81.0% men) were included from the Iceland Sleep Apnea Cohort. Airway sizes, soft tissue volumes, and craniofacial dimensions were quantified using three-dimensional magnetic resonance imaging. We examined how upper airway anatomy was associated with BMI using linear regression (continuous BMI) and analysis of covariance (BMI categories), adjusting for age, sex, and apnea-hypopnea index. Results: Most upper airway anatomy was significantly associated with BMI among patients with OSA. Higher BMI was associated with a different airway shape, including larger minimum anteroposterior distance at both the retropalatal and retroglossal regions and smaller minimum lateral distance in the retropalatal region. All pharyngeal soft tissues were larger with greater BMI, including the volumes of the tongue (and tongue fat), soft palate (and soft palate fat), lateral walls, fat pads, epiglottis, and pterygoids. Patients with lower BMIs had smaller craniofacial measures (e.g., distances between hyoid, retropogonion, and third cervical vertebrae, intramandibular volume, and nasooropharyngeal areas) and more retrognathia. BMI was only weakly associated with the proportion of mandibular space occupied by soft tissues (with no difference among BMI groups), suggesting comparable intraoral "crowdedness" among patients with OSA at different degrees of obesity, albeit for different reasons. Conclusions: The present results support associations between obesity and airway shape, soft tissue volumes, and craniofacial measures among patients with moderate to severe OSA. These relationships provide insights into anatomic traits leading to OSA in lean and obese patients and can inform more personalized treatment options.

Insomnia significantly impairs daily functioning, but the underlying dimensional structure of daily dysfunction and its physiological predictors remain underexplored. This study aims to better characterize the daily dysfunction in individuals with and without insomnia and examines the physiological predictors of this dysfunction. Data from the Sleep Apnea Global Interdisciplinary Consortium (SAGIC) were analyzed, including 1058 participants (50% female; age 45.3±14.7 years) without obstructive sleep apnea (OSA) or shift work. Insomnia was defined by self-reported difficulty falling or staying asleep ≥3 nights/week for >3 months (n=387, 57% female; age 49.0±14.5 years). The dimensionality of self-reported daily dysfunction items (e.g., bother, affecting work, affecting social life, affecting sex life, affecting others, irritability, trouble concentrating, fatigue, and sleepy) was assessed using exploratory factor analysis (EFA). The role of EEG metrics (macro and micro-architecture and Odds-Ratio-Product [ORP]) in determining daytime dysfunction was examined using linear regression analyses to evaluate the predictive value of sleep metrics, group differences, and interaction effects. EFA identified a single-factor structure, explaining 60.4% of the variability in measures of daily dysfunction (KMO = 0.93; > 0.80, Bartlett’s test: χ²(36) = 2452.844, p < 0.001). The single factor represents overall daily dysfunction, with higher values indicating greater severity. All variables load in the same direction, meaning that as values increase, dysfunction worsens. Linear regression analyses revealed that longer sleep onset latency (SOL) and higher ORP-9, reflecting fragmented and unstable sleep, significantly predicted greater daily dysfunction in individuals with insomnia. In the ORP model, the higher ORP-9 × group (insomnia yes/no) interaction predicted worse daily dysfunction, while higher ORP wake was unexpectedly associated with better functioning. This suggests that preserved arousal stability may buffer some negative effects of insomnia. The interaction examines whether the effect of ORP-9 on daytime dysfunction differs between the insomnia groups. The linear regression models accounted for 19–23% of the variance in daily dysfunction. These findings highlight the role of fragmented sleep and altered arousal stability in daily dysfunction among individuals with insomnia, emphasizing the value of combined sleep metrics in understanding sleep-related functional impairments.

Despite decades of research, defining insomnia remains challenging due to its complex and variable nature. Various diagnostic systems emphasize the chronic nature of insomnia and its impact on daily functioning, relying heavily on patient self-reporting due to limitations in objective measures such as polysomnography (PSG). Discrepancies between subjective experiences and objective PSG results highlight the need for more nuanced approaches, such as electroencephalogram (EEG) spectral analysis, which reveals distinct patterns of high-frequency activity in individuals with insomnia. This study explores EEG markers of insomnia by integrating subjective reports with objective physiological markers, specifically ORP (Odds-Ratio-Product) and spectral features, to address inconsistencies found in previous research and clinical settings. Qualitative and quantitative definitions of insomnia are contrasted to highlight differences in sleep architecture and EEG characteristics. The research aims to determine whether groups defined by weekly frequency and daily duration of symptoms have different distribution patterns and which physiological characteristics best distinguish insomnia patients from controls. Our findings suggest that ORP, as a dependent variable, captures the most significant differences in the independent variables across the model. Elevated beta power in insomnia patients indicates increased cortical arousal, supporting the perspective of insomnia as a hyperarousal disorder. Future research should focus on using ORP to enhance the understanding of sleep disturbances in insomnia. Comprehensive evaluation of insomnia requires integrating qualitative, quantitative, and neurophysiological data to fully understand its impact on sleep architecture and quality.

Over 10 years ago, a seminal study using cluster analysis in the Icelandic Sleep Apnea Cohort (ISAC) identified subtypes of patients with obstructive sleep apnea (OSA) defined as excessively sleepy (presenting with multiple sleepiness complaints), disturbed sleep (characterized by insomnia-related complains), and minimally symptomatic. These subtypes have since been shown to generalize in clinical and population samples worldwide. An important step towards clinical translation is understanding the short-term (e.g., weeks) reliability of these subtypes. We describe results from an ongoing study to answer this question across sites in the Sleep Apnea Global Interdisciplinary Consortium (SAGIC). We used a prospective test-retest study of subjects with newly diagnosed or suspected OSA prior to initiating therapy. Participants completed a questionnaire on OSA symptoms twice (at least two weeks apart). A patient’s symptom subtype at each timepoint was determined based on questionnaire responses using a prediction model derived in existing SAGIC patients. To understand short-term reliability of subtypes, we calculated the percent agreement and simple kappa coefficients. Kappa values indicate slight (0.00-0.20), fair (0.21-0.40), moderate (0.41-0.60), substantial (0.61-0.80), and almost perfect (0.81-1.00) reliability. Our sample included 116 participants from 4 SAGIC sites: Ohio State (n=43), Kansas (n=7), Sydney (n=37) and Perth (n=29). The sample was 50% male, 55.2±13.9 years-old, had a BMI of 31.8±6.8 kg/m2, and an AHI of 22.3±18.5 events/hour. Questionnaires were completed an average (±SD) of 18.8±7.8 days apart. At the first visit, 51 (44.0%) patients had the disturbed sleep subtype, 42 (36.2%) were minimally symptomatic, and 23 (19.8%) were excessively sleepy. At the second visit, 47 (40.5%) had the disturbed sleep subtype, 43 (37.1%) the minimally symptomatic and 26 (22.4%) the excessively sleepy. Overall, 84.5% (95% CI: 77.9%, 91.1%) of patients fell within the same subtype at both timepoints. The Kappa (95% CI) was 0.759 (0.657, 0.853), indicating substantial short-term reliability. While recruitment is ongoing across all SAGIC sites, this early analysis suggests substantial reliability of symptom subtypes over a short timeframe (without treatment). This further supports the potential clinical utility of the symptom subtype framework in advancing more personalized patient care.

The SURMOUNT-OSA trial evaluated the impact of the weight loss drug tirzepatide in obese patients with obstructive sleep apnea (OSA). The primary endpoint assessed was a change in the apnea-hypopnea index (AHI) after 52 weeks in individuals on the drug compared to placebo. There were robust decrements in AHI with resolution of OSA in approximately 50% of subjects. These impressive results raise the question: what role will this medication play in routine management of OSA? This Forum article asked four opinion leaders to give their views. All agreed that tirzepatide will play a major role, but there were different opinions as to what that role will be. There was a fairly broad view that the role in primary treatment would be limited, given how long it takes to get an effect, whereas CPAP gives immediate benefit. Thus, initially the drug will likely be used in concert with CPAP. After weight loss is achieved, there will be consideration as to whether CPAP can be stopped. Opinion leaders argued that there are opportunities for treatment of obesity hypoventilation syndrome that require study. Other primary outcomes need to be investigated as well. Moreover, studies comparing drug treatment with CPAP need to be considered. The high cost of the drug could increase already existing disparities in care. There are concerns about long-term adherence, but current data are largely about the initial drugs of this type. In conclusion, the precise guidelines for optimal tirzepatide use in OSA remain to be determined.

Background: OSA is a heterogeneous disease, with obesity a significant risk factor in many but not all cases of OSA, via increased airway collapsibility, reduced lung volumes, and possibly body fat distribution. Research question: We sought to develop PRSs that summarize the genetic liability to OSA that include and exclude obesity related pathways, and to study the associations of these PRSs with OSA comorbid cardiometabolic and CVD outcomes. Approach: Using 1.2 million race/ethnic diverse samples from the Million Veteran Program, FinnGen, TOPMed, All of Us (AoU), Geisinger’s MyCode, MGB Biobank, and the Human Phenotype Project (HPP), we developed, selected, and assessed PRSs for OSA, relying on genome wide association studies both adjusted and unadjusted for BMI: BMIadjOSA and BMIunadjOSA PRS. We tested their associations with cardiometabolic and CVD outcomes in AoU. Results: In association with OSA, adjusted odds ratios (ORs) per 1 standard deviation of the PRSs ranged from 1.38 to 2.75, all statistically significant (Figure). The associations of BMIadjOSA and BMIunadjOSA PRSs with CVD outcomes in AoU shared both common and distinct patterns. For example, BMIunadjOSA PRS was associated with type 2 diabetes, heart failure, and coronary artery disease, but the associations of BMIadjOSA PRS with these outcomes were statistically insignificant with estimated OR close to 1. In contrast, both BMIadjOSA and BMIunadjOSA PRSs were associated with hypertension and stroke. Sex stratified analyses revealed that BMIadjOSA PRS association with hypertension was driven by data from females: females had OR=1.1, p-value=0.002, but males OR=1.01 and statistically insignificant. OSA PRSs were also associated with dual-energy X-ray absorptiometry (DXA) body fat measures. In BMI adjusted analysis, BMIadjOSA PRS was associated with higher visceral adipose tissue (VAT) proportion of total body fat mass (TFM), with lower proportion of gynoid fat mass out of TFM, higher proportion of android fat mass out of TFM, and lower gynoid to android fat mass. In females only, the PRS was associated with higher VAT to SAT ratio (Figure). Conclusions: Distinct components of OSA genetic risk are related to obesity and body fat distribution, and may influence clinical outcomes. These may explain differing OSA risk and associations with cardiometabolic and CVD morbidities between sex groups.