Single-cell RNA-seq uncovers cellular heterogeneity and provides a signature for paediatric sleep apnoea.

BACKGROUND: Obstructive sleep apnoea (OSA) is a highly prevalent disease and a major cause of systemic inflammation leading to neurocognitive, behavioural, metabolic and cardiovascular dysfunction in children and adults. However, the impact of OSA on the heterogeneity of circulating immune cells remains to be determined. METHODS: We applied single-cell transcriptomics analysis (scRNA-seq) to identify OSA-induced changes in transcriptional landscape in peripheral blood mononuclear cell (PBMC) composition, which uncovered severity-dependent differences in several cell lineages. Furthermore, a machine-learning approach was used to combine scRNAs-seq cell-specific markers with those differentially expressed in OSA. RESULTS: scRNA-seq demonstrated OSA-induced heterogeneity in cellular composition and enabled the identification of previously undescribed cell types in PBMCs. We identified a molecular signature consisting of 32 genes, which distinguished OSA patients from various controls with high precision (area under the curve 0.96) and accuracy (93% positive predictive value and 95% negative predictive value) in an independent PBMC bulk RNA expression dataset. CONCLUSION: OSA deregulates systemic immune function and displays a molecular signature that can be assessed in standard cellular RNA without the need for pre-analytical cell separation, thereby making the assay amenable to application in a molecular diagnostic setting.

Nocturnal oximetry parameters as predictors of sleep apnea severity in resource-limited settings.

Nocturnal oximetry is an alternative modality for evaluating obstructive sleep apnea syndrome (OSAS) severity when polysomnography is not available. The Oxygen Desaturation (≥3%) Index (ODI3) and McGill Oximetry Score (MOS) are used as predictors of moderate-to-severe OSAS (apnea-hypopnea index-AHI >5 episodes/h), an indication for adenotonsillectomy. We hypothesised that ODI3 is a better predictive parameter for AHI >5 episodes/h than the MOS. All polysomnograms performed in otherwise healthy, snoring children with tonsillar hypertrophy in a tertiary hospital (November 2014 to May 2019) were analysed. The ODI3 and MOS were derived from the oximetry channel of each polysomnogram. Logistic regression was applied to assess associations of ODI3 or MOS (predictors) with an AHI >5 episodes/h (primary outcome). Receiver operating characteristic (ROC) curves and areas under ROC curves were used to compare the ODI3 and MOS as predictors of moderate-to-severe OSAS. The optimal cut-off value for each oximetry parameter was determined using Youden's index. Polysomnograms of 112 children (median [interquartile range] age 6.1 [3.9-9.1] years; 35.7% overweight) were analysed. Moderate-to-severe OSAS prevalence was 49.1%. The ODI3 and MOS were significant predictors of moderate-to-severe OSAS after adjustment for overweight, sex, and age (odds ratio [OR] 1.34, 95% confidence interval [CI] 1.19-1.51); and OR 4.10, 95% CI 2.06-8.15, respectively; p < 0.001 for both). Area under the ROC curve was higher for the ODI3 than for MOS (0.903 [95% CI 0.842-0.964] versus 0.745 [95% CI 0.668-0.821]; p < 0.001). Optimal cut-off values for the ODI3 and MOS were ≥4.3 episodes/h and ≥2, respectively. The ODI3 emerges as preferable or at least a complementary oximetry parameter to MOS for detecting moderate-to-severe OSAS in snoring children when polysomnography is not available.

Heart rate variability spectrum characteristics in children with sleep apnea.

BACKGROUND: Classic spectral analysis of heart rate variability (HRV) in pediatric sleep apnea-hypopnea syndrome (SAHS) traditionally evaluates the very low frequency (VLF: 0-0.04 Hz), low frequency (LF: 0.04-0.15 Hz), and high frequency (HF: 0.15-0.40 Hz) bands. However, specific SAHS-related frequency bands have not been explored. METHODS: One thousand seven hundred and thirty-eight HRV overnight recordings from two pediatric databases (0-13 years) were evaluated. The first one (981 children) served as training set to define new HRV pediatric SAHS-related frequency bands. The associated relative power (RP) were computed in the test set, the Childhood Adenotonsillectomy Trial database (CHAT, 757 children). Their relationships with polysomnographic variables and diagnostic ability were assessed. RESULTS: Two new specific spectral bands of pediatric SAHS within 0-0.15 Hz were related to duration of apneic events, number of awakenings, and wakefulness after sleep onset (WASO), while an adaptive individual-specific new band from HF was related to oxyhemoglobin desaturations, arousals, and WASO. Furthermore, these new spectral bands showed improved diagnostic ability than classic HRV. CONCLUSIONS: Novel spectral bands provide improved characterization of pediatric SAHS. These findings may pioneer a better understanding of the effects of SAHS on cardiac function and potentially serve as detection biomarkers. IMPACT: New specific heart rate variability (HRV) spectral bands are identified and characterized as potential biomarkers in pediatric sleep apnea. Spectral band BW1 (0.001-0.005 Hz) is related to macro sleep disruptions. Spectral band BW2 (0.028-0.074 Hz) is related to the duration of apneic events. An adaptive spectral band within the respiratory range, termed ABW3, is related to oxygen desaturations. The individual and collective diagnostic ability of these novel spectral bands outperforms classic HRV bands.

Wavelet Analysis of Overnight Airflow to Detect Obstructive Sleep Apnea in Children.

This study focused on the automatic analysis of the airflow signal (AF) to aid in the diagnosis of pediatric obstructive sleep apnea (OSA). Thus, our aims were: (i) to characterize the overnight AF characteristics using discrete wavelet transform (DWT) approach, (ii) to evaluate its diagnostic utility, and (iii) to assess its complementarity with the 3% oxygen desaturation index (ODI3). In order to reach these goals, we analyzed 946 overnight pediatric AF recordings in three stages: (i) DWT-derived feature extraction, (ii) feature selection, and (iii) pattern recognition. AF recordings from OSA patients showed both lower detail coefficients and decreased activity associated with the normal breathing band. Wavelet analysis also revealed that OSA disturbed the frequency and energy distribution of the AF signal, increasing its irregularity. Moreover, the information obtained from the wavelet analysis was complementary to ODI3. In this regard, the combination of both wavelet information and ODI3 achieved high diagnostic accuracy using the common OSA-positive cutoffs: 77.97%, 81.91%, and 90.99% (AdaBoost.M2), and 81.96%, 82.14%, and 90.69% (Bayesian multi-layer perceptron) for 1, 5, and 10 apneic events/hour, respectively. Hence, these findings suggest that DWT properly characterizes OSA-related severity as embedded in nocturnal AF, and could simplify the diagnosis of pediatric OSA.

Cell-Selective Altered Cargo Properties of Extracellular Vesicles Following In Vitro Exposures to Intermittent Hypoxia.

Intermittent hypoxia (IH), a hallmark of obstructive sleep apnea (OSA), is associated with cardiovascular and metabolic dysfunction. However, the mechanisms underlying these morbidities remain poorly delineated. Extracellular vesicles (EVs) mediate intercellular communications, play pivotal roles in a multitude of physiological and pathological processes, and could mediate IH-induced cellular effects. Here, the effects of IH on human primary cells and the release of EVs were examined. Microvascular endothelial cells (HMVEC-d), THP1 monocytes, THP1 macrophages M0, THP1 macrophages M1, THP1 macrophages M2, pre-adipocytes, and differentiated adipocytes (HAd) were exposed to either room air (RA) or IH for 24 h. Secreted EVs were isolated and characterized using transmission electron microscopy, nanoparticle tracking analysis, and Western blotting. The effects of each of the cell-derived EVs on endothelial cell (EC) monolayer barrier integrity, on naïve THP1 macrophage polarity, and on adipocyte insulin sensitivity were also evaluated. IH did not alter EVs cell quantal release, but IH-EVs derived from HMVEC-d (p < 0.01), THP1 M0 (p < 0.01) and HAd (p < 0.05) significantly disrupted HMVEC-d monolayer integrity, particularly after H2O2 pre-conditioning. IH-EVs from HMVEC-d and THP1 M0 elicited M2-polarity changes did not alter insulin sensitivity responses. IH induces cell-selective changes in EVs cargo, which primarily seem to target the emergence of endothelial dysfunction. Thus, changes in EVs cargo from selected cell sources in vivo may play causal roles in some of the adverse outcomes associated with OSA.

Erratum: Martín-Montero et al. Bispectral Analysis of Heart Rate Variability to Characterize and Help Diagnose Pediatric Sleep Apnea. Entropy 2021, 23, 1016.

The author wishes to make the following correction to this paper [...].

Bispectral Analysis of Heart Rate Variability to Characterize and Help Diagnose Pediatric Sleep Apnea.

Pediatric obstructive sleep apnea (OSA) is a breathing disorder that alters heart rate variability (HRV) dynamics during sleep. HRV in children is commonly assessed through conventional spectral analysis. However, bispectral analysis provides both linearity and stationarity information and has not been applied to the assessment of HRV in pediatric OSA. Here, this work aimed to assess HRV using bispectral analysis in children with OSA for signal characterization and diagnostic purposes in two large pediatric databases (0-13 years). The first database (training set) was composed of 981 overnight ECG recordings obtained during polysomnography. The second database (test set) was a subset of the Childhood Adenotonsillectomy Trial database (757 children). We characterized three bispectral regions based on the classic HRV frequency ranges (very low frequency: 0-0.04 Hz; low frequency: 0.04-0.15 Hz; and high frequency: 0.15-0.40 Hz), as well as three OSA-specific frequency ranges obtained in recent studies (BW1: 0.001-0.005 Hz; BW2: 0.028-0.074 Hz; BWRes: a subject-adaptive respiratory region). In each region, up to 14 bispectral features were computed. The fast correlation-based filter was applied to the features obtained from the classic and OSA-specific regions, showing complementary information regarding OSA alterations in HRV. This information was then used to train multi-layer perceptron (MLP) neural networks aimed at automatically detecting pediatric OSA using three clinically defined severity classifiers. Both classic and OSA-specific MLP models showed high and similar accuracy (Acc) and areas under the receiver operating characteristic curve (AUCs) for moderate (classic regions: Acc = 81.0%, AUC = 0.774; OSA-specific regions: Acc = 81.0%, AUC = 0.791) and severe (classic regions: Acc = 91.7%, AUC = 0.847; OSA-specific regions: Acc = 89.3%, AUC = 0.841) OSA levels. Thus, the current findings highlight the usefulness of bispectral analysis on HRV to characterize and diagnose pediatric OSA.

Transcriptomic Changes of Murine Visceral Fat Exposed to Intermittent Hypoxia at Single Cell Resolution.

Intermittent hypoxia (IH) is a hallmark of obstructive sleep apnea (OSA) and induces metabolic dysfunction manifesting as inflammation, increased lipolysis and insulin resistance in visceral white adipose tissues (vWAT). However, the cell types and their corresponding transcriptional pathways underlying these functional perturbations are unknown. Here, we applied single nucleus RNA sequencing (snRNA-seq) coupled with aggregate RNA-seq methods to evaluate the cellular heterogeneity in vWAT following IH exposures mimicking OSA. C57BL/6 male mice were exposed to IH and room air (RA) for 6 weeks, and nuclei from vWAT were isolated and processed for snRNA-seq followed by differential expressed gene (DEGs) analyses by cell type, along with gene ontology and canonical pathways enrichment tests of significance. IH induced significant transcriptional changes compared to RA across 14 different cell types identified in vWAT. We identified cell-specific signature markers, transcriptional networks, metabolic signaling pathways, and cellular subpopulation enrichment in vWAT. Globally, we also identify 298 common regulated genes across multiple cellular types that are associated with metabolic pathways. Deconvolution of cell types in vWAT using global RNA-seq revealed that distinct adipocytes appear to be differentially implicated in key aspects of metabolic dysfunction. Thus, the heterogeneity of vWAT and its response to IH at the cellular level provides important insights into the metabolic morbidity of OSA and may possibly translate into therapeutic targets.

Circulating Exosomal miRNAs Signal Circadian Misalignment to Peripheral Metabolic Tissues.

Night shift work increases risk of metabolic disorders, particularly obesity and insulin resistance. While the underlying mechanisms are unknown, evidence points to misalignment of peripheral oscillators causing metabolic disturbances. A pathway conveying such misalignment may involve exosome-based intercellular communication. Fourteen volunteers were assigned to a simulated day shift (DS) or night shift (NS) condition. After 3 days on the simulated shift schedule, blood samples were collected during a 24-h constant routine protocol. Exosomes were isolated from the plasma samples from each of the blood draws. Exosomes were added to naïve differentiated adipocytes, and insulin-induced pAkt/Akt expression changes were assessed. ChIP-Seq analyses for BMAL1 protein, mRNA microarrays and exosomal miRNA arrays combined with bioinformatics and functional effects of agomirs and antagomirs targeting miRNAs in NS and DS exosomal cargo were examined. Human adipocytes treated with exosomes from the NS condition showed altered Akt phosphorylation responses to insulin in comparison to those treated with exosomes from the DS condition. BMAL1 ChIP-Seq of exosome-treated adipocytes showed 42,037 binding sites in the DS condition and 5538 sites in the NS condition, with a large proportion of BMAL1 targets including genes encoding for metabolic regulators. A significant and restricted miRNA exosomal signature emerged after exposure to the NS condition. Among the exosomal miRNAs regulated differentially after 3 days of simulated NS versus DS, proof-of-concept validation of circadian misalignment signaling was demonstrated with hsa-mir-3614-5p. Exosomes from the NS condition markedly altered expression of key genes related to circadian rhythm in several cultured cell types, including adipocytes, myocytes, and hepatocytes, along with significant changes in 29 genes and downstream gene network interactions. Our results indicate that a simulated NS schedule leads to changes in exosomal cargo in the circulation. These changes promote reduction of insulin sensitivity of adipocytes in vitro and alter the expression of core clock genes in peripheral tissues. Circulating exosomal miRNAs may play an important role in metabolic dysfunction in NS workers by serving as messengers of circadian misalignment to peripheral tissues.

Assessment of Airflow and Oximetry Signals to Detect Pediatric Sleep Apnea-Hypopnea Syndrome Using AdaBoost.

The reference standard to diagnose pediatric Obstructive Sleep Apnea (OSA) syndrome is an overnight polysomnographic evaluation. When polysomnography is either unavailable or has limited availability, OSA screening may comprise the automatic analysis of a minimum number of signals. The primary objective of this study was to evaluate the complementarity of airflow (AF) and oximetry (SpO2) signals to automatically detect pediatric OSA. Additionally, a secondary goal was to assess the utility of a multiclass AdaBoost classifier to predict OSA severity in children. We extracted the same features from AF and SpO2 signals from 974 pediatric subjects. We also obtained the 3% Oxygen Desaturation Index (ODI) as a common clinically used variable. Then, feature selection was conducted using the Fast Correlation-Based Filter method and AdaBoost classifiers were evaluated. Models combining ODI 3% and AF features outperformed the diagnostic performance of each signal alone, reaching 0.39 Cohens's kappa in the four-class classification task. OSA vs. No OSA accuracies reached 81.28%, 82.05% and 90.26% in the apnea-hypopnea index cutoffs 1, 5 and 10 events/h, respectively. The most relevant information from SpO2 was redundant with ODI 3%, and AF was complementary to them. Thus, the joint analysis of AF and SpO2 enhanced the diagnostic performance of each signal alone using AdaBoost, thereby enabling a potential screening alternative for OSA in children.

Cloud algorithm-driven oximetry-based diagnosis of obstructive sleep apnoea in symptomatic habitually snoring children.

The ability of a cloud-driven Bluetooth oximetry-based algorithm to diagnose obstructive sleep apnoea syndrome (OSAS) was examined in habitually snoring children concurrently undergoing overnight polysomnography.Children clinically referred for overnight in-laboratory polysomnographic evaluation for suspected OSAS were simultaneously hooked to a Bluetooth oximeter linked to a smartphone. Polysomnography findings were scored and the apnoea/hypopnoea index (AHIPSG) was tabulated, while oximetry data yielded an estimated AHIOXI using a validated algorithm.The accuracy of the oximeter in identifying correctly patients with OSAS in general, or with mild (AHI 1-5 events·h-1), moderate (5-10 events·h-1) or severe (>10 events·h-1) OSAS was examined in 432 subjects (6.5±3.2 years), with 343 having AHIPSG >1 event·h-1 The accuracies of AHIOXI were consistently >79% for all levels of OSAS severity, and specificity was particularly favourable for AHI >10 events·h-1 (92.7%). Using the criterion of AHIPSG >1 event·h-1, only 4.7% of false-negative cases emerged, from which only 0.6% of cases showed moderate or severe OSAS.Overnight oximetry processed via Bluetooth technology by a cloud-based machine learning-derived algorithm can reliably diagnose OSAS in children with clinical symptoms suggestive of the disease. This approach provides virtually limitless scalability and should alleviate the substantial difficulties in accessing paediatric sleep laboratories while markedly reducing the costs of OSAS diagnosis.

Obstructive Sleep Apnea and Inflammation: Proof of Concept Based on Two Illustrative Cytokines.

Obstructive sleep apnea syndrome (OSAS) is a markedly prevalent condition across the lifespan, particularly in overweight and obese individuals, which has been associated with an independent risk for neurocognitive, behavioral, and mood problems as well as cardiovascular and metabolic morbidities, ultimately fostering increases in overall mortality rates. In adult patients, excessive daytime sleepiness (EDS) is the most frequent symptom leading to clinical referral for evaluation and treatment, but classic EDS features are less likely to be reported in children, particularly among those with normal body-mass index. The cumulative evidence collected over the last two decades supports a conceptual framework, whereby sleep-disordered breathing in general and more particularly OSAS should be viewed as low-grade chronic inflammatory diseases. Accordingly, it is assumed that a proportion of the morbid phenotypic signature in OSAS is causally explained by underlying inflammatory processes inducing end-organ dysfunction. Here, the published links between OSAS and systemic inflammation will be critically reviewed, with special focus on the pro-inflammatory cytokines tumor necrosis factor α (TNF-α) and interleukin 6 (IL-6), since these constitute classical prototypes of the large spectrum of inflammatory molecules that have been explored in OSAS patients.

Plasma Extracellular Vesicles in Children with OSA Disrupt Blood-Brain Barrier Integrity and Endothelial Cell Wound Healing in Vitro.

Pediatric obstructive sleep apnea (P-OSA) is associated with neurocognitive deficits and endothelial dysfunction, suggesting the possibility that disruption of the blood-brain barrier (BBB) may underlie these morbidities. Extracellular vesicles (EVs), which include exosomes, are small particles involved in cell-cell communications via different mechanisms and could play a role in OSA-associated end-organ injury. To examine the roles of EVs in BBB dysfunction, we recruited three groups of children: (a) absence of OSA or cognitive deficits (CL, n = 6), (b) OSA but no evidence of cognitive deficits (OSA-NC(-), n = 12), and (c) OSA with evidence of neurocognitive deficits (OSA-NC(+), n = 12). All children were age-, gender-, ethnicity-, and BMI-z-score-matched, and those with OSA were also apnea-hypopnea index (AHI)-matched. Plasma EVs were characterized, quantified, and applied on multiple endothelial cell types (HCAEC, HIAEC, human HMVEC-D, HMVEC-C, HMVEC-L, and hCMEC/D3) while measuring monolayer barrier integrity and wound-healing responses. EVs from OSA children induced significant declines in hCMEC/D3 transendothelial impedance compared to CL (p < 0.001), and such changes were greater in NC(+) compared to NC(-) (p < 0.01). The effects of EVs from each group on wound healing for HCAEC, HIAEC, HMVED-d, and hCMEC/D3 cells were similar, but exhibited significant differences across the three groups, with evidence of disrupted wound healing in P-OSA. However, wound healing in HMVEC-C was only affected by NC(+) (p < 0.01 vs. NC(-) or controls (CO). Furthermore, no significant differences emerged in HMVEC-L cell wound healing across all three groups. We conclude that circulating plasma EVs in P-OSA disrupt the integrity of the BBB and exert adverse effects on endothelial wound healing, particularly among OSA-NC(+) children, while also exhibiting endothelial cell type selectivity. Thus, circulating EVs cargo may play important roles in the emergence of end-organ morbidity in pediatric OSA.

Sleep-disordered breathing, circulating exosomes, and insulin sensitivity in adipocytes.

BACKGROUND: Sleep-disordered-breathing (SDB), which is characterized by chronic intermittent hypoxia (IH) and sleep fragmentation (SF), is a prevalent condition that promotes metabolic dysfunction, particularly among patients suffering from obstructive hypoventilation syndrome (OHS). Exosomes are generated ubiquitously, are readily present in the circulation, and their cargo may exert substantial functional cellular alterations in both physiological and pathological conditions. However, the effects of plasma exosomes on adipocyte metabolism in patients with OHS or in mice subjected to IH or SF mimicking SDB are unclear. METHODS: Exosomes from fasting morning plasma samples from obese adults with polysomnographically-confirmed OSA before and after 3 months of adherent CPAP therapy were assayed. In addition, C57BL/6 mice were randomly assigned to (1) sleep control (SC), (2) sleep fragmentation (SF), and (3) intermittent hypoxia (HI) for 6 weeks, and plasma exosomes were isolated. Equivalent exosome amounts were added to differentiated adipocytes in culture, after which insulin sensitivity was assessed using 0 nM and 5 nM insulin-induced pAKT/AKT expression changes by western blotting. RESULTS: When plasma exosomes were co-cultured and internalized by human naive adipocytes, significant reductions emerged in Akt phosphorylation responses to insulin when compared to exosomes obtained after 24 months of adherent CPAP treatment (n = 24; p < 0.001), while no such changes occur in untreated patients (n = 8). In addition, OHS exosomes induced significant increases in adipocyte lipolysis that were attenuated after CPAP, but did not alter pre-adipocyte differentiation. Similarly, exosomes from SF- and IH-exposed mice induced attenuated p-AKT/total AKT responses to exogenous insulin and increased glycerol content in naive murine adipocytes, without altering pre-adipocyte differentiation. CONCLUSIONS: Using in vitro adipocyte-based functional reporter assays, alterations in plasma exosomal cargo occur in SDB, and appear to contribute to adipocyte metabolic dysfunction. Further exploration of exosomal miRNA signatures in either human subjects or animal models and their putative organ and cell targets appears warranted.

Nocturnal Oximetry-based Evaluation of Habitually Snoring Children.

RATIONALE: The vast majority of children around the world undergoing adenotonsillectomy for obstructive sleep apnea-hypopnea syndrome (OSA) are not objectively diagnosed by nocturnal polysomnography because of access availability and cost issues. Automated analysis of nocturnal oximetry (nSpO2), which is readily and globally available, could potentially provide a reliable and convenient diagnostic approach for pediatric OSA. METHODS: Deidentified nSpO2 recordings from a total of 4,191 children originating from 13 pediatric sleep laboratories around the world were prospectively evaluated after developing and validating an automated neural network algorithm using an initial set of single-channel nSpO2 recordings from 589 patients referred for suspected OSA. MEASUREMENTS AND MAIN RESULTS: The automatically estimated apnea-hypopnea index (AHI) showed high agreement with AHI from conventional polysomnography (intraclass correlation coefficient, 0.785) when tested in 3,602 additional subjects. Further assessment on the widely used AHI cutoff points of 1, 5, and 10 events/h revealed an incremental diagnostic ability (75.2, 81.7, and 90.2% accuracy; 0.788, 0.854, and 0.913 area under the receiver operating characteristic curve, respectively). CONCLUSIONS: Neural network-based automated analyses of nSpO2 recordings provide accurate identification of OSA severity among habitually snoring children with a high pretest probability of OSA. Thus, nocturnal oximetry may enable a simple and effective diagnostic alternative to nocturnal polysomnography, leading to more timely interventions and potentially improved outcomes.

Assessment of oximetry-based statistical classifiers as simplified screening tools in the management of childhood obstructive sleep apnea.

PURPOSE: A variety of statistical models based on overnight oximetry has been proposed to simplify the detection of children with suspected obstructive sleep apnea syndrome (OSAS). Despite the usefulness reported, additional thorough comparative analyses are required. This study was aimed at assessing common binary classification models from oximetry for the detection of childhood OSAS. METHODS: Overnight oximetry recordings from 176 children referred for clinical suspicion of OSAS were acquired during in-lab polysomnography. Several training and test datasets were randomly composed by means of bootstrapping for model optimization and independent validation. For every child, blood oxygen saturation (SpO2) was parameterized by means of 17 features. Fast correlation-based filter (FCBF) was applied to search for the optimum features. The discriminatory power of three statistical pattern recognition algorithms was assessed: linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), and logistic regression (LR). The performance of each automated model was evaluated for the three common diagnostic polysomnographic cutoffs in pediatric OSAS: 1, 3, and 5 events/h. RESULTS: Best screening performances emerged using the 1 event/h cutoff for mild-to-severe childhood OSAS. LR achieved 84.3% accuracy (95% CI 76.8-91.5%) and 0.89 AUC (95% CI 0.83-0.94), while QDA reached 96.5% PPV (95% CI 90.3-100%) and 0.91 AUC (95% CI 0.85-0.96%). Moreover, LR and QDA reached diagnostic accuracies of 82.7% (95% CI 75.0-89.6%) and 82.1% (95% CI 73.8-89.5%) for a cutoff of 5 events/h, respectively. CONCLUSIONS: Automated analysis of overnight oximetry may be used to develop reliable as well as accurate screening tools for childhood OSAS.

Exosome and Macrophage Crosstalk in Sleep-Disordered Breathing-Induced Metabolic Dysfunction.

Obstructive sleep apnea (OSA) is a highly prevalent worldwide public health problem that is characterized by repetitive upper airway collapse leading to intermittent hypoxia, pronounced negative intrathoracic pressures, and recurrent arousals resulting in sleep fragmentation. Obesity is a major risk factor of OSA and both of these two closely intertwined conditions result in increased sympathetic activity, oxidative stress, and chronic low-grade inflammation, which ultimately contribute, among other morbidities, to metabolic dysfunction, as reflected by visceral white adipose tissue (VWAT) insulin resistance (IR). Circulating extracellular vesicles (EVs), including exosomes, are released by most cell types and their cargos vary greatly and reflect underlying changes in cellular homeostasis. Thus, exosomes can provide insights into how cells and systems cope with physiological perturbations by virtue of the identity and abundance of miRNAs, mRNAs, proteins, and lipids that are packaged in the EVs cargo, and are secreted from the cells into bodily fluids under normal as well as diseased states. Accordingly, exosomes represent a novel pathway via which a cohort of biomolecules can travel long distances and result in the modulation of gene expression in selected and targeted recipient cells. For example, exosomes secreted from macrophages play a critical role in innate immunity and also initiate the adaptive immune response within specific metabolic tissues such as VWAT. Under normal conditions, phagocyte-derived exosomes represent a large portion of circulating EVs in blood, and carry a protective signature against IR that is altered when secreting cells are exposed to altered physiological conditions such as those elicited by OSA, leading to emergence of IR within VWAT compartment. Consequently, increased understanding of exosome biogenesis and biology should lead to development of new diagnostic biomarker assays and personalized therapeutic approaches. Here, the evidence on the major biological functions of macrophages and exosomes as pathophysiological effectors of OSA-induced metabolic dysfunction is discussed.

Effect of Sleep-disordered Breathing Severity on Cognitive Performance Measures in a Large Community Cohort of Young School-aged Children.

RATIONALE: Sleep-disordered breathing (SDB) in children is associated with cognitive challenges. However, potential associations between SDB severity and neurocognitive function, as well as the presence of an SDB cutoff, have not been fully explored. OBJECTIVES: To determine whether SDB-associated adverse changes in neurocognitive functioning are severity dependent. METHODS: A total of 1,010 snoring and nonsnoring children ages 5-7 years were prospectively recruited from public schools and underwent polysomnography and neurocognitive assessments of intellectual, attention, memory, language, and executive function development. The children were subdivided into four severity groups on the basis of apnea-hypopnea index (AHI), followed by comparisons of cognitive function, with a particular focus on standardized subtests of intellectual, language, attention, memory, and executive function. MEASUREMENT AND MAIN RESULTS: Differential Ability Scales Verbal (P < 0.001) and Nonverbal (P = 0.002) performance, as well as global conceptual ability (IQ) (P < 0.001) scores, differed significantly across the groups, with individuals with higher AHI showing worse performance. Additionally, specific NEPSY (a Developmental Neuropsychological Assessment) subscores focused on attention and executive skills differed across the groups, indicating differences in levels of engagement and problem solving. Children with higher AHI (>5 per hour of total sleep time) were significantly more impaired than all three lower AHI groups, indicating a dose-response impact of SDB. CONCLUSIONS: This large community-based sample of children highlights the significant deleterious impact of SDB, particularly in children with moderate to severe obstructive sleep apnea, and also that even snoring alone affects neurocognitive function. By affecting developing capabilities, as illustrated by cognitive measures in a severity-graded manner, SDB could adversely impact children's capacity to attain academic and adaptive goals, ultimately hampering their ability to reach independence. Our findings support the need for increased awareness of SDB, with particular emphasis on children with more severe obstructive sleep apnea.