Publications by authors named "Leila Kheirandish-Gozal"

179 Publications

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

Sensors (Basel) 2021 Feb 21;21(4). Epub 2021 Feb 21.

Biomedical Engineering Group, University of Valladolid, 47011 Valladolid, Spain.

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: () to characterize the overnight AF characteristics using discrete wavelet transform (DWT) approach, () to evaluate its diagnostic utility, and () to assess its complementarity with the 3% oxygen desaturation index (3). In order to reach these goals, we analyzed 946 overnight pediatric AF recordings in three stages: () DWT-derived feature extraction, () feature selection, and () 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 3. In this regard, the combination of both wavelet information and 3 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.
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http://dx.doi.org/10.3390/s21041491DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7926995PMC
February 2021

Validity and Cost-Effectiveness of Pediatric Home Respiratory Polygraphy for the Diagnosis of Obstructive Sleep Apnea in Children: Rationale, Study Design, and Methodology.

Methods Protoc 2021 Jan 19;4(1). Epub 2021 Jan 19.

Research Service and Bioaraba Research Institute, OSI Araba University Hospital, UPV/EHU, 01004 Vitoria, Spain.

Obstructive sleep apnea (OSA) in children is a prevalent, albeit largely undiagnosed disease associated with a large spectrum of morbidities. Overnight in-lab polysomnography remains the gold standard diagnostic approach, but is time-consuming, inconvenient, and expensive, and not readily available in many places. Simplified Home Respiratory Polygraphy (HRP) approaches have been proposed to reduce costs and facilitate the diagnostic process. However, evidence supporting the validity of HRP is still scarce, hampering its implementation in routine clinical use. The objectives were: Primary; to establish the diagnostic and therapeutic decision validity of a simplified HRP approach compared to PSG among children at risk of OSA. Secondary: (a) Analyze the cost-effectiveness of the HRP versus in-lab PSG in evaluation and treatment of pediatric OSA; (b) Evaluate the impact of therapeutic interventions based on HRP versus PSG findings six months after treatment using sleep and health parameters and quality of life instruments; (c) Discovery and validity of the urine biomarkers to establish the diagnosis of OSA and changes after treatment.
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http://dx.doi.org/10.3390/mps4010009DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7838960PMC
January 2021

A convolutional neural network architecture to enhance oximetry ability to diagnose pediatric obstructive sleep apnea.

IEEE J Biomed Health Inform 2021 Jan 6;PP. Epub 2021 Jan 6.

This study aims at assessing the usefulness of deep learning to enhance the diagnostic ability of oximetry in the context of automated detection of pediatric obstructive sleep apnea (OSA). A total of 3196 blood oxygen saturation (SpO2) signals from children were used for this purpose. A convolutional neural network (CNN) architecture was trained using 20-min SpO2 segments from the training set (859 subjects) to estimate the number of apneic events. CNN hyperparameters were tuned using Bayesian optimization in the validation set (1402 subjects). This model was applied to three test sets composed of 312, 392, and 231 subjects from three independent databases, in which the apnea-hypopnea index (AHI) estimated for each subject (AHICNN) was obtained by aggregating the output of the CNN for each 20-min SpO2 segment. AHICNN outperformed the 3% oxygen desaturation index (ODI3), a clinical approach, as well as the AHI estimated by a conventional feature-engineering approach based on multi-layer perceptron (AHIMLP). Specifically, AHICNN reached higher four-class Cohen's kappa in the three test databases than ODI3 (0.515 vs 0.417, 0.422 vs 0.372, and 0.423 vs 0.369) and AHIMLP (0.515 vs 0.377, 0.422 vs 0.381, and 0.423 vs 0.306). In addition, our proposal outperformed state-of-the-art studies, particularly for the AHI severity cutoffs of 5 e/h and 10 e/h. This suggests that the information automatically learned from the SpO2 signal by deep-learning techniques helps to enhance the diagnostic ability of oximetry in the context of pediatric OSA.
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http://dx.doi.org/10.1109/JBHI.2020.3048901DOI Listing
January 2021

Bispectral analysis of overnight airflow to improve the pediatric sleep apnea diagnosis.

Comput Biol Med 2021 Feb 7;129:104167. Epub 2020 Dec 7.

Biomedical Engineering Group, University of Valladolid, Valladolid, Spain; CIBER-BBN, Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina, Valladolid, Spain.

Pediatric Obstructive Sleep Apnea (OSA) is a respiratory disease whose diagnosis is performed through overnight polysomnography (PSG). Since it is a complex, time-consuming, expensive, and labor-intensive test, simpler alternatives are being intensively sought. In this study, bispectral analysis of overnight airflow (AF) signal is proposed as a potential approach to replace PSG when indicated. Thus, our objective was to characterize AF through bispectrum, and assess its performance to diagnose pediatric OSA. This characterization was conducted using 13 bispectral features from 946 AF signals. The oxygen desaturation index ≥3% (ODI3), a common clinical measure of OSA severity, was also obtained to evaluate its complementarity to the AF bispectral analysis. The fast correlation-based filter (FCBF) and a multi-layer perceptron (MLP) were used for subsequent automatic feature selection and pattern recognition stages. FCBF selected 3 bispectral features and ODI3, which were used to train a MLP model with ability to estimate apnea-hypopnea index (AHI). The model reached 82.16%, 82.49%, and 90.15% accuracies for the common AHI cut-offs 1, 5, and 10 events/h, respectively. The different bispectral approaches used to characterize AF in children provided complementary information. Accordingly, bispectral analysis showed that the occurrence of apneic events decreases the non-gaussianity and non-linear interaction of the AF harmonic components, as well as the regularity of the respiratory patterns. Moreover, the bispectral information from AF also showed complementarity with ODI3. Our findings suggest that AF bispectral analysis may serve as a useful tool to simplify the diagnosis of pediatric OSA, particularly for children with moderate-to-severe OSA.
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http://dx.doi.org/10.1016/j.compbiomed.2020.104167DOI Listing
February 2021

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

Int J Mol Sci 2020 Dec 29;22(1). Epub 2020 Dec 29.

Department of Child Health, School of Medicine, University of Missouri, Columbia, MO 65211, USA.

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.
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http://dx.doi.org/10.3390/ijms22010261DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7795619PMC
December 2020

Predicting Behavioral Problems from Sleep-disordered Breathing Trajectories. Not an Easy Game.

Am J Respir Crit Care Med 2021 03;203(6):669-670

Children's Hospital of Eastern Ontario University of Ottawa Ottawa, Ontario, Canada.

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http://dx.doi.org/10.1164/rccm.202011-4291EDDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7958504PMC
March 2021

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

Entropy (Basel) 2020 Jun 17;22(6). Epub 2020 Jun 17.

Biomedical Engineering Group, University of Valladolid, 47011 Valladolid, Spain.

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 (SpO) 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 SpO 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 SpO was redundant with ODI 3%, and AF was complementary to them. Thus, the joint analysis of AF and SpO enhanced the diagnostic performance of each signal alone using AdaBoost, thereby enabling a potential screening alternative for OSA in children.
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http://dx.doi.org/10.3390/e22060670DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7517204PMC
June 2020

Automatic Assessment of Pediatric Sleep Apnea Severity Using Overnight Oximetry and Convolutional Neural Networks.

Annu Int Conf IEEE Eng Med Biol Soc 2020 07;2020:633-636

In this study, we use the overnight blood oxygen saturation (SpO) signal along with convolutional neural networks (CNN) for the automatic estimation of pediatric sleep apnea-hypopnea syndrome (SAHS) severity. The few preceding studies have focused on the application of conventional feature extraction methods to obtain information from the SpO signal, which may omit relevant data related to the illness. In contrast, deep learning techniques are able to automatically learn features from raw input signal. Thus, we propose to assess whether CNN, a deep learning algorithm, could automatically estimate the apnea-hypopnea index (AHÍ) from nocturnal oximetry to help establish pediatric SAHS presence and severity. A database of 746 SpO recordings is involved in the study. CNN was trained using 20-min segments from the SpO signal in the training set (400 subjects). Hyperparameters of the CNN architecture were tuned using a validation set (100 subjects). This model was applied to a test set (246 subjects), in which the final AHI of each patient was obtained as the average of the output of the CNN for all the segments of the corresponding SpO signal. The AHI estimated by the CNN showed a promising diagnostic performance, with 74.8%, 90.7%, and 95.1% accuracies for the common AHI severity thresholds of 1, 5, and 10 events per hour (e/h), respectively. Furthermore, this model reached 28.6, 32.9, and 120.0 positive likelihood ratios for the above-mentioned AHI thresholds. This suggests that the information extracted from the oximetry signal by deep learning techniques may be useful to both establish pediatric SAHS and its severity.
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http://dx.doi.org/10.1109/EMBC44109.2020.9176342DOI Listing
July 2020

Heart rate variability spectrum characteristics in children with sleep apnea.

Pediatr Res 2020 Sep 14. Epub 2020 Sep 14.

Biomedical Engineering Group, University of Valladolid, Valladolid, Spain.

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.
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http://dx.doi.org/10.1038/s41390-020-01138-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7956022PMC
September 2020

Escalation of sleep disturbances amid the COVID-19 pandemic: a cross-sectional international study.

J Clin Sleep Med 2021 01;17(1):45-53

Pediatric Pulmonary & Sleep Unit, Hadassah Medical Center and The Hebrew University of Jerusalem's School of Medicine, Jerusalem, Israel.

Study Objectives: The stress imposed by the COVID-19 pandemic and ensuing social isolation could adversely affect sleep. As sleep problems may persist and hurt health, it is important to identify which populations have experienced changes in sleeping patterns during the pandemic and their extent.

Methods: In Study 1, 3,062 responders from 49 countries accessed the survey website voluntarily between March 26 and April 26, 2020, and 2,562 (84%; age: 45.2 ± 14.5, 68% women) completed the study. In Study 2, 1,022 adult US responders were recruited for pay through Mechanical Turk, and 971 (95%; age 40.4 ± 13.6, 52% women) completed the study. The survey tool included demographics and items adapted from validated sleep questionnaires on sleep duration, quality and timing, and sleeping pills consumption.

Results: In Study 1, 58% of the responders were unsatisfied with their sleep. Forty percent of the responders reported a decreased sleep quality vs before COVID-19 crisis. Self-reported sleeping pill consumption increased by 20% (P < .001). Multivariable analysis indicated that female sex, being in quarantine, and 31- to 45-years age group, reduced physical activity and adverse impact on livelihood were independently associated with more severe worsening of sleep quality during the pandemic. The majority of findings were reproduced in the independent cohort of Study 2.

Conclusions: Changes imposed due to the pandemic have led to a surge in individuals reporting sleep problems across the globe. The findings raise the need to screen for worsening sleep patterns and use of sleeping aids, especially in more susceptible populations, namely, women and people with insecure livelihoods subjected to social isolation.
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http://dx.doi.org/10.5664/jcsm.8800DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7849644PMC
January 2021

Circulating Exosomal miRNAs Signal Circadian Misalignment to Peripheral Metabolic Tissues.

Int J Mol Sci 2020 Sep 3;21(17). Epub 2020 Sep 3.

Department of Child Health, Child Health Research Institute, University of Missouri School of Medicine, Columbia, MO 65201, USA.

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.
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http://dx.doi.org/10.3390/ijms21176396DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7503323PMC
September 2020

Treatment of Obstructive Sleep Apnea in Children: Handling the Unknown with Precision.

J Clin Med 2020 Mar 24;9(3). Epub 2020 Mar 24.

Department of Child Health and the Child Health Research Institute, University of Missouri School of Medicine, Columbia, MO 65201, USA.

Treatment approaches to pediatric obstructive sleep apnea (OSA) have remarkably evolved over the last two decades. From an a priori assumption that surgical removal of enlarged upper airway lymphadenoid tissues (T&A) was curative in the vast majority of patients as the recommended first-line treatment for pediatric OSA, residual respiratory abnormalities are frequent. Children likely to manifest persistent OSA after T&A include those with severe OSA, obese or older children, those with concurrent asthma or allergic rhinitis, children with predisposing oropharyngeal or maxillomandibular factors, and patients with underlying medical conditions. Furthermore, selection anti-inflammatory therapy or orthodontic interventions may be preferable in milder cases. The treatment options for residual OSA after T&A encompass a large spectrum of approaches, which may be complementary, and clearly require multidisciplinary cooperation. Among these, continuous positive airway pressure (CPAP), combined anti-inflammatory agents, rapid maxillary expansion, and myofunctional therapy are all part of the armamentarium, albeit with currently low-grade evidence supporting their efficacy. In this context, there is urgent need for prospective evidence that will readily identify the correct candidate for a specific intervention, and thus enable some degree of scientifically based precision in the current one approach fits all model of pediatric OSA medical care.
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http://dx.doi.org/10.3390/jcm9030888DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7141493PMC
March 2020

Usefulness of Spectral Analysis of Respiratory Rate Variability to Help in Pediatric Sleep Apnea-Hypopnea Syndrome Diagnosis.

Annu Int Conf IEEE Eng Med Biol Soc 2019 Jul;2019:4580-4583

The sleep apnea-hypopnea syndrome (SAHS) is a chronic respiratory disorder of high prevalence among children (up to 4%). Nocturnal polysomnography (PSG) is the gold standard method to diagnose SAHS, which is a complex, expensive, and time-consuming test. Consequently, alternative simplified methods are demanded. We propose the analysis of the respiratory rate variability (RRV) signal, directly obtained from the airflow (AF) signals. The aim of our study is to evaluate the usefulness of the spectral information obtained from RRV in the diagnosis of pediatric SAHS. A database composed of 946 AF and blood oxygen saturation (SpO2) recordings from children between 0 and 13 years old was used. Our database was divided into four severity groups according to the apnea-hipopnea index (AHI): no-SAHS (AHI <; 1 events/h), mild (1 events/h ≤ AHI <; 5 events/h), moderate (5 events/h ≤ AHI <; 10 events/h), and severe SAHS (AHI ≥ 10 events/h). RRV and 3% oxygen desaturation index (ODI3) were obtained from AF and SpO2 recordings, respectively. A spectral band of interest was determined (0.09-0.20 Hz.) and a total of 12 spectral features were extracted. Nine of these features showed statistically significant differences (p-value <; 0.05) among the four severity groups. The spectral features from RRV along with ODI3 were used as inputs to binary logistic regression (LR) classifiers. The diagnostic performance of LR models were evaluated for the AHI cut-off points of 1, 5, and 10 e/h, achieving 66.5%, 84.0%, and 88.5% accuracy, respectively. These results outperformed those obtained by single ODI3. The joint use of the spectral information from RRV and ODI3 achieved a high diagnostic capability in the most severely-affected children, thus showing their complementarity. These results suggest that the information contained in RRV spectrum together with ODI3 is useful to help identify moderate-to-severe SAHS.
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http://dx.doi.org/10.1109/EMBC.2019.8857719DOI Listing
July 2019

Convolutional Neural Networks to Detect Pediatric Apnea-Hypopnea Events from Oximetry.

Annu Int Conf IEEE Eng Med Biol Soc 2019 Jul;2019:3555-3558

Pediatric sleep apnea-hypopnea syndrome (SAHS) is a highly prevalent breathing disorder that is related to many negative consequences for the children's health and quality of life when it remains untreated. The gold standard for pediatric SAHS diagnosis (overnight polysomnography) has several limitations, which has led to the search for alternative tests. In this sense, automated analysis of overnight oximetry has emerged as a simplified technique. Previous studies have focused on the extraction of ad-hoc features from the blood oxygen saturation (SpO) signal, which may miss useful information related to apnea and hypopnea (AH) events. In order to overcome this limitation of traditional approaches, we propose the use of convolutional neural networks (CNN), a deep learning technique, to automatically detect AH events from the SpO raw data. CHAT-baseline dataset, composed of 453 SpO recordings, was used for this purpose. A CNN model was trained using 60-s segments from the SpO signal using a training set (50% of subjects). Optimum hyperparameters of the CNN architecture were obtained using a validation set (25% of subjects). This model was applied to a third test set (25% of subjects), reaching 93.6% accuracy to detect AH events. These results suggest that the application of CNN may be useful to detect changes produced in the oximetry signal by AH events in pediatric SAHS patients.
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http://dx.doi.org/10.1109/EMBC.2019.8857934DOI Listing
July 2019

Reduced sleep spindle activity in children with primary snoring.

Sleep Med 2020 01 11;65:142-146. Epub 2019 Oct 11.

Department of Child Health and Child Health Research Institute, University of Missouri School of Medicine, Columbia, MO, 65201, USA.

Background: Habitually snoring children are at risk of manifesting disease-related problems even if their sleep studies are overall within normal limits.

Study Objectives: To compare sleep spindle activity in children with primary snoring and healthy controls.

Methods: Sleep spindle activity including analysis of fast and slow spindles (ie, >13 Hz and <13 Hz, respectively) was evaluated in polysomnographic (PSG) recordings of 20 randomly selected children with primary snoring (PS; normal PSG recordings except for objective presence of snoring; 12 boys, mean age 6.5 ± 2.1 years), and 20 age- and gender-matched PSG-confirmed non-snoring controls.

Results: PS children showed significantly lower spindle indices in all non-rapid eye movement (NREM) sleep stages (p < 0.05). In contrast, fast spindles were found in 40% (n = 8) children with PS and in 25% (n = 5) controls. Sleep spindle activity was particularly higher in NREM sleep stage 2 in controls compared PS (76% versus 43% of all marked sleep spindles events in NREM sleep stage 2, p < 0.001).

Conclusions: Children with PS exhibit significantly reduced spindle activity when compared to matched controls. Reduced sleep spindle activity may be an indicator of sleep disruption and, therefore, could be involved in the development of disease-related consequences in snoring children.
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http://dx.doi.org/10.1016/j.sleep.2019.10.001DOI Listing
January 2020

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

Int J Mol Sci 2019 Dec 10;20(24). Epub 2019 Dec 10.

Child Health Research Institute, Department of Child Health, University of Missouri School of Medicine, Columbia, MO 65201, USA.

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, = 6), (b) OSA but no evidence of cognitive deficits (OSA-NC(-), = 12), and (c) OSA with evidence of neurocognitive deficits (OSA-NC(+), = 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 ( < 0.001), and such changes were greater in NC(+) compared to NC(-) ( < 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(+) ( < 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.
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http://dx.doi.org/10.3390/ijms20246233DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6941040PMC
December 2019

Usefulness of recurrence plots from airflow recordings to aid in paediatric sleep apnoea diagnosis.

Comput Methods Programs Biomed 2020 Jan 18;183:105083. Epub 2019 Sep 18.

Biomedical Engineering Group, Universidad de Valladolid, Valladolid, Spain; IMUVA, Instituto de Investigación en Matemáticas, Universidad de Valladolid, Valladolid, Spain. Electronic address: http://www.gib.tel.uva.es.

Background And Objective: In-laboratory overnight polysomnography (PSG) is the gold standard method to diagnose the Sleep Apnoea-Hypopnoea Syndrome (SAHS). PSG is a complex, expensive, labour-intensive and time-consuming test. Consequently, simplified diagnostic methods are desirable. We propose the analysis of the airflow (AF) signal by means of recurrence plots (RP) features. The main goal of our study was to evaluate the utility of the information from RPs of the AF signals to detect paediatric SAHS at different levels of severity. In addition, we also evaluated the complementarity with the 3% oxygen desaturation index (ODI).

Methods: 946 AF and blood oxygen saturation (SpO) recordings from children ages 0-13 years were used. The population under study was randomly split into training (60%) and test (40%) sets. RP was computed and 9 RP features were extracted from each AF recording. ODI was also calculated from each SpO recording. A feature selection stage was conducted in the training group by means of the fast correlation-based filter (FCBF) methodology to obtain a relevant and non-redundant optimum feature subset. A multi-layer perceptron neural network with Bayesian approach (BY-MLP), trained with these optimum features, was used to estimate the apnoea-hypopnoea index (AHI).

Results: 8 of the RP features showed statistically significant differences (p-value <0.01) among the SAHS severity groups. FCBF selected the maximum length of the diagonal lines from RP, as well as the ODI. Using these optimum features, the BY-MLP model achieved 83.2%, 78.5%, and 91.0% accuracy in the test group for the AHI thresholds 1, 5, and 10 events/h, respectively. Moreover, this model reached a negative likelihood ratio of 0.1 for 1 event/h and a positive likelihood ratio of 13.7 for 10 events/h.

Conclusions: RP analysis enables extraction of useful SAHS-related information from overnight AF paediatric recordings. Moreover, it provides complementary information to the widely-used clinical variable ODI. Thus, RP applied to AF signals can be used along with ODI to help in paediatric SAHS diagnosis, particularly to either confirm the absence of SAHS or the presence of severe SAHS.
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http://dx.doi.org/10.1016/j.cmpb.2019.105083DOI Listing
January 2020

Plasma exosomes in OSA patients promote endothelial senescence: effect of long-term adherent continuous positive airway pressure.

Sleep 2020 02;43(2)

Department of Child Health and the Child Health Research Institute, University of Missouri School of Medicine, Columbia, MO.

Obstructive sleep apnea (OSA) is associated with increased risk for end-organ morbidities, which can collectively be viewed as accelerated aging. Vascular senescence is an important contributor to end-organ dysfunction. Exosomes are released ubiquitously into the circulation, and transfer their cargo to target cells facilitating physiological and pathological processes. Plasma exosomes from 15 patients with polysomnographically diagnosed OSA at baseline (OSA-T1) after 12 months of adherent continuous positive airway pressure (CPAP) treatment (OSA-T2), 13 untreated OSA patients at 12-month intervals (OSA-NT1, OSA-NT2), and 12 controls (CO1 and CO2) were applied on naïve human microvascular endothelialcells-dermal (HMVEC-d). Expression of several senescence gene markers including p16 (CDKN2A), SIRT1, and SIRT6 and immunostaining for β-galactosidase activity (x-gal) were performed. Endothelial cells were also exposed to intermittent hypoxia (IH) or normoxia (RA) or treated with hydrogen peroxide (H2O2), stained with x-gal and subjected to qRT-PCR. Exosomes from OSA-T1, OSA-NT1, and OSA-NT2 induced significant increases in x-gal staining compared to OSA-T2, CO1, and CO2 (p-value < 0.01). p16 expression was significantly increased (p < 0.01), while SIRT1 and SIRT6 expression levels were decreased (p < 0.02 and p < 0.009). Endothelial cells exposed to IH or to H2O2 showed significant increases in x-gal staining (p < 0.001) and in senescence gene expression. Circulating exosomes in untreated OSA induce marked and significant increases in senescence of naïve endothelial cells, which are only partially reversible upon long-term adherent CPAP treatment. Furthermore, endothelial cells exposed to IH or H2O2 also elicit similar responses. Thus, OSA either directly or indirectly via exosomes may initiate and exacerbate cellular aging, possibly via oxidative stress-related pathways.
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http://dx.doi.org/10.1093/sleep/zsz217DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7901815PMC
February 2020

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

Int J Mol Sci 2019 Jan 22;20(3). Epub 2019 Jan 22.

Child Health Research Institute, Department of Child Health, University of Missouri School of Medicine, Columbia, MO 65201, USA.

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.
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http://dx.doi.org/10.3390/ijms20030459DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6387387PMC
January 2019

Wavelet analysis of oximetry recordings to assist in the automated detection of moderate-to-severe pediatric sleep apnea-hypopnea syndrome.

PLoS One 2018 7;13(12):e0208502. Epub 2018 Dec 7.

Biomedical Engineering Group, Universidad de Valladolid, Valladolid, Spain.

Background: The gold standard for pediatric sleep apnea hypopnea syndrome (SAHS) is overnight polysomnography, which has several limitations. Thus, simplified diagnosis techniques become necessary.

Objective: The aim of this study is twofold: (i) to analyze the blood oxygen saturation (SpO2) signal from nocturnal oximetry by means of features from the wavelet transform in order to characterize pediatric SAHS; (ii) to evaluate the usefulness of the extracted features to assist in the detection of pediatric SAHS.

Methods: 981 SpO2 signals from children ranging 2-13 years of age were used. Discrete wavelet transform (DWT) was employed due to its suitability to deal with non-stationary signals as well as the ability to analyze the SAHS-related low frequency components of the SpO2 signal with high resolution. In addition, 3% oxygen desaturation index (ODI3), statistical moments and power spectral density (PSD) features were computed. Fast correlation-based filter was applied to select a feature subset. This subset fed three classifiers (logistic regression, support vector machines (SVM), and multilayer perceptron) trained to determine the presence of moderate-to-severe pediatric SAHS (apnea-hypopnea index cutoff ≥ 5 events per hour).

Results: The wavelet entropy and features computed in the D9 detail level of the DWT reached significant differences associated with the presence of SAHS. All the proposed classifiers fed with a selected feature subset composed of ODI3, statistical moments, PSD, and DWT features outperformed every single feature. SVM reached the highest performance. It achieved 84.0% accuracy (71.9% sensitivity, 91.1% specificity), outperforming state-of-the-art studies in the detection of moderate-to-severe SAHS using the SpO2 signal alone.

Conclusion: Wavelet analysis could be a reliable tool to analyze the oximetry signal in order to assist in the automated detection of moderate-to-severe pediatric SAHS. Hence, pediatric subjects suffering from moderate-to-severe SAHS could benefit from an accurate simplified screening test only using the SpO2 signal.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0208502PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6286069PMC
May 2019

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

Eur Respir J 2019 02 21;53(2). Epub 2019 Feb 21.

Dept of Child Health, University of Missouri School of Medicine, Columbia, MO, USA.

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 (AHI) was tabulated, while oximetry data yielded an estimated AHI 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), moderate (5-10 events·h) or severe (>10 events·h) OSAS was examined in 432 subjects (6.5±3.2 years), with 343 having AHI >1 event·h The accuracies of AHI were consistently >79% for all levels of OSAS severity, and specificity was particularly favourable for AHI >10 events·h (92.7%). Using the criterion of AHI >1 event·h, only 4.7% of false-negative cases emerged, from which only 0.6% of cases showed moderate or severe OSAS.Overnight oximetry processed 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.
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http://dx.doi.org/10.1183/13993003.01788-2018DOI Listing
February 2019

Improving the Diagnostic Ability of Oximetry Recordings in Pediatric Sleep Apnea-Hypopnea Syndrome by Means of Multi-Class AdaBoost.

Annu Int Conf IEEE Eng Med Biol Soc 2018 Jul;2018:167-170

Pediatric sleep apnea-hypopnea syndrome (SAHS) is a highly prevalent respiratory disorder that may impose many negative effects on the health and development of children. Due to the drawbacks of overnight polysomnography (PSG), the gold standard diagnosis technique, automated analysis of nocturnal oximetry has emerged as a simplified alternative. In order to improve diagnosis ability of oximetry, we propose to evaluate the usefulness of AdaBoost, a classification boosting algorithm, in the context of pediatric SAHS. A database composed of 981 SpO recordings from pediatric subjects was used. For this purpose, a signal processing approach divided into two main stages was conducted: (i) feature extraction, where 3% oxygen desaturation index (ODI3), spectral, and nonlinear features were computed from the oximetry signal, and (ii) AdaBoost classification, where an AdaBoost.M2 model was trained with these features in order to determine the severity of pediatric SAHS according to the apnea-hypopnea index (AHI): AHI<1 events per hour (e/h), 1≤AHI<5 e/h, and AHI≥5 e/h. Our AdaBoost.M2 model achieved a Cohen's kappa of 0.474 in an independent test set in the 3-class classification task. In addition, high accuracies were obtained when using the AHI cutoffs for diagnosis of mild (AHI=1 e/h) and moderate-to-severe (AHI=5 e/h) SAHS: 80.9% and 82.9%, respectively. These results achieved slightly higher diagnostic accuracies than ODI3 as well as state-of-the-art studies. Therefore, AdaBoost could help to enhance the diagnostic ability of the oximetry signal to assess pediatric SAHS severity.
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http://dx.doi.org/10.1109/EMBC.2018.8512264DOI Listing
July 2018

Bispectral Analysis to Enhance Oximetry as a Simplified Alternative for Pediatric Sleep Apnea Diagnosis.

Annu Int Conf IEEE Eng Med Biol Soc 2018 Jul;2018:175-178

This study aims at assessing the bispectral analysis of blood oxygen saturation (SpO) from nocturnal oximetry to help in pediatric sleep apnea-hypopnea syndrome (SAHS) diagnosis. Recent studies have found excessive redundancy in the SAHS-related information usually extracted from SpO, while proposing only two features as a reduced set to be used. On the other hand, it has been suggested that SpO bispectral analysis is able to provide complementary information to common anthropometric, spectral, and clinical variables. We address these novel findings to assess whether bispectrum provides new non-redundant information to help in SAHS diagnosis. Thus, we use 981 pediatric SpO recordings to extract both the reduced set of features recently proposed as well as 9 bispectral features. Then, a feature selection method based on the fast correlationbased filter and bootstrapping is used to assess redundancy among all the features. Finally, the non-redundant ones are used to train a Bayesian multi-layer perceptron neural network (BYMLP) that estimate the apnea-hypopnea index (AHI), which is the diagnostic reference variable. Bispectral phase entropy was found complementary to the two previously recommended features and a BY-MLP model trained with the three of them reached high agreement with actual AHI (intra-class correlation coefficient = 0.889). Estimated AHI also showed high diagnostic ability, reaching 82.1%, 81.9%, and 90.3% accuracies and 0.814, 0.880, and 0.922 area under the receiver-operating characteristics curve for three common AHI thresholds: 1 e/h, 5 e/h, and 10 e/h, respectively. These results suggest that the information extracted from the bispectrum of SpO can improve the diagnostic performance of the oximetry test.
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http://dx.doi.org/10.1109/EMBC.2018.8512248DOI Listing
July 2018

Detrended fluctuation analysis of the oximetry signal to assist in paediatric sleep apnoea-hypopnoea syndrome diagnosis.

Physiol Meas 2018 11 14;39(11):114006. Epub 2018 Nov 14.

Biomedical Engineering Group, Universidad de Valladolid, Valladolid, Spain. Author to whom any correspondence should be addressed.

Objective: To evaluate whether detrended fluctuation analysis (DFA) provides information that improves the diagnostic ability of the oximetry signal in the diagnosis of paediatric sleep apnoea-hypopnoea syndrome (SAHS).

Approach: A database composed of 981 blood oxygen saturation (SpO) recordings in children was used to extract DFA-derived features in order to quantify the scaling behaviour and the fluctuations of the SpO signal. The 3% oxygen desaturation index (ODI3) was also computed for each subject. Fast correlation-based filter (FCBF) was then applied to select an optimum subset of relevant and non-redundant features. This subset fed a multi-layer perceptron (MLP) neural network to estimate the apnoea-hypopnoea index (AHI).

Main Results: ODI3 and four features from the DFA reached significant differences associated with the severity of SAHS. An optimum subset composed of the slope in the first scaling region of the DFA profile and the ODI3 was selected using FCBF applied to the training set (60% of samples). The MLP model trained with this feature subset showed good agreement with the actual AHI, reaching an intra-class correlation coefficient of 0.891 in the test set (40% of samples). Furthermore, the estimated AHI showed high diagnostic ability, reaching an accuracy of 82.7%, 81.9%, and 91.1% using three common AHI cut-offs of 1, 5, and 10 events per hour (e h), respectively. These results outperformed the overall performance of ODI3.

Significance: DFA may serve as a reliable tool to improve the diagnostic performance of oximetry recordings in the evaluation of paediatric patients with symptoms suggestive of SAHS.
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http://dx.doi.org/10.1088/1361-6579/aae66aDOI Listing
November 2018

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

Int J Mol Sci 2018 Oct 29;19(11). Epub 2018 Oct 29.

Department of Child Health and the Child Health Research Institute, University of Missouri School of Medicine, Columbia, MO 65201, USA.

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.
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http://dx.doi.org/10.3390/ijms19113383DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6274857PMC
October 2018

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

Int J Obes (Lond) 2018 06 11;42(6):1127-1139. Epub 2018 Jun 11.

Extremadura University, Caceres, Spain.

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.
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http://dx.doi.org/10.1038/s41366-018-0099-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6195831PMC
June 2018

Regional brain tissue integrity in pediatric obstructive sleep apnea.

Neurosci Lett 2018 08 5;682:118-123. Epub 2018 Jun 5.

Departments of Anesthesiology, University of California Los Angeles, Los Angeles, CA 90095, USA; Radiological Sciences, University of California Los Angeles, Los Angeles, CA 90095, USA; Bioengineering, University of California Los Angeles, Los Angeles, CA 90095, USA; Brain Research Institute, University of California Los Angeles, Los Angeles, CA 90095, USA. Electronic address:

Children with long-standing obstructive sleep apnea (OSA) show evidence of neural injury and functional deficits in behavioral and cognitive regulatory brain regions that are reflected in symptoms of altered cognitive performance and behaviors. While we earlier showed reduced gray matter volume and increased and reduced regional cortical thicknesses, such structural changes give little indication of the underlying pathology. Brain tissue integrity in pediatric OSA subjects can reflect the nature and extent of injury or structural adaptation, and can be assessed by entropy tissue texture, a measure of local changes in signal intensity patterns from high-resolution magnetic resonance images. We collected high-resolution T1-weighted magnetic resonance images from 10 pediatric OSA (age, 7.9 ± 1.1 years; apnea-hypopnea-index, 8.8 ± 3.0 events/hour; body-mass-index, 20 ± 6.7 kg/m; 7 male) and 8 healthy controls (age, 8.8 ± 1.6 years; body-mass-index, 19.6 ± 5.9 kg/m; 5 female). Images were bias-corrected and entropy maps calculated, individual maps were normalized to a common space, smoothed, and compared between groups (ANCOVA; covariates: age, gender; SPM12, uncorrected-threshold p < 0.005). No significant differences in age (p = .48), gender (p = .59), or body-mass-index (p = .63) emerged between groups. In OSA children, several brain sites including the pre-frontal cortex, middle and posterior corpus callosum, thalamus, hippocampus, and cerebellar areas showed reduced entropy values, indicating tissue changes suggestive of acute insults. No regions showed higher entropy values in OSA. Children suffering from OSA display predominantly acute tissue injury in neural regions principally localized within autonomic, respiratory, cognitive, and neuropsychologic control, functions that correspond to previously-reported comorbidities associated with OSA. A range of acute processes, including hypoxia/re-oxygenation, repeated arousals, and episodic hypercarbia, may have contributed to regional brain tissue integrity changes in pediatric OSA.
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http://dx.doi.org/10.1016/j.neulet.2018.06.002DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6102065PMC
August 2018

Exosomal Cargo Properties, Endothelial Function and Treatment of Obesity Hypoventilation Syndrome: A Proof of Concept Study.

J Clin Sleep Med 2018 05 15;14(5):797-807. Epub 2018 May 15.

Section of Sleep Medicine, Department of Pediatrics, Pritzker School of Medicine, Biological Sciences Division University of Chicago, Chicago, Illinois.

Study Objectives: Longitudinal studies support the usage of positive airway pressure (PAP) therapy in treating obstructive sleep apnea (OSA) to improve cardiovascular disease. However, the anticipated benefit is not ubiquitous. In this study, we elucidate whether PAP therapy leads to immediate improvements on endothelial function, a subclinical marker of cardiovascular status, by examining the effect of circulating exosomes, isolated from patients before and after PAP therapy, on naive endothelial cells.

Methods: We isolated plasma-derived circulating exosomes from 12 patients with severe OSA and obesity hypoventilation syndrome (OHS) before and after 6 weeks of PAP therapy, and examined their effect on cultured endothelial cells using several reporter assays.

Results: We found that circulating exosomes contributed to the induction and propagation of OSA/OHS-related endothelial dysfunction (ie, increased permeability and disruption of tight junctions along with increased adhesion molecule expression, and reduced endothelial nitric oxide synthase expression), and promoted increased monocyte adherence. Further, when comparing exosomes isolated before and after PAP therapy, the disturbances in endothelial cell function were attenuated with treatment, including an overall cumulative decrease in endothelial permeability in all 12 subjects by 10.8% ( = .035), as well as detection of a subset of 4 differentially expressed exosomal miRNAs, even in the absence of parallel changes in systemic blood pressure or metabolic function.

Conclusions: Circulating exosomes facilitate important intercellular signals that modify endothelial phenotype, and thus emerge as potential fundamental contributors in the context of OSA/OHS-related endothelial dysfunction. Exosomes may not only provide candidate biomarkers, but are also a likely and plausible mechanism toward OSA/OHS-induced cardiovascular disease.

Clinical Trial Registration: Registry: ClinicalTrials.gov, Title: AVAPS-AE Efficacy Study, URL: https://clinicaltrials.gov/ct2/show/NCT01368614, Identifier: NCT01368614.
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http://dx.doi.org/10.5664/jcsm.7110DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5940431PMC
May 2018

Response: Commentary: Parent-Reported Behavioral and Psychiatric Problems Mediate the Relationship between Sleep Disordered Breathing and Cognitive Deficits in School-Aged Children.

Front Neurol 2018 13;9:63. Epub 2018 Feb 13.

Department of Pediatrics, Pritzker School of Medicine, Biological Sciences Division, The University of Chicago, Chicago, IL, United States.

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http://dx.doi.org/10.3389/fneur.2018.00063DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5816957PMC
February 2018

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

Sleep Breath 2018 Dec 16;22(4):1063-1073. Epub 2018 Feb 16.

Servicio de Neumología, Hospital Universitario Río Hortega de Valladolid, c/ Dulzaina 2, 47012, Valladolid, Spain.

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 (SpO) 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.
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http://dx.doi.org/10.1007/s11325-018-1637-3DOI Listing
December 2018