COVID-19 exposure and obstructive sleep apnea: a therapeutic approach.
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ABSTRACT:
SUBMITTER: Mohit
PROVIDER: S-EPMC7884227 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description: Not available
| S-EPMC8223009 | biostudies-literature
Project description:Rationale: Obstructive sleep apnea (OSA) has been associated with metabolic dysregulation and systemic inflammation. This may be due to pathophysiologic effects of OSA on visceral adipose tissue. We sought to assess the transcriptional consequences of OSA on adipocytes by utilizing pathway-focused analyses. Methods: Patients scheduled to undergo ventral hernia repair surgery were recruited to wear a portable home sleep monitor for two nights prior to surgery. Visceral fat biopsies were obtained intra-operatively. RNA was extracted and whole-genome expression profiling was performed. Gene Set Enrichment Analysis (GSEA) was used to identify curated gene sets that were differentially enriched in OSA subjects. Network analysis was applied to a select set of highly enriched pathways. Results: 10 patients with OSA and 8 control subjects were recruited. There were no differences in age, gender, body mass index between the two groups, but the OSA subjects had a significantly higher respiratory disturbance index (19.2 vs. 0.6, P-value 0.05) and worse hypoxemia (minimum oxygen saturation 79.7% vs. 87.8%, P-value < 0.001). GSEA identified a number of gene sets up-regulated in adipose tissue of OSA patients including the pro-inflammatory NF-M-NM-:B pathway and the proteolytic ubiquitin/proteasome module. A critical metabolic pathway, the peroxisome proliferator-activated receptor (PPAR), was down-regulated in subjects with OSA. Network analysis linked members of these modules together and identified regulatory hubs. Conclusions: OSA is associated with alterations in visceral fat gene expression. Pathway-based network analysis highlighted perturbations in several key pathways whose coordinated interactions may contribute to the metabolic dysregulation observed in this complex disorder. Total RNA from visceral fat of 18 subjects (10 OSA, 8 Control) was hybridized to 18 Affymetrix Genechip Human Gene 1.0 ST microarrays.
2012-09-01 | E-GEOD-38792 | biostudies-arrayexpress
Project description:Rationale: Obstructive sleep apnea (OSA) has been associated with metabolic dysregulation and systemic inflammation. This may be due to pathophysiologic effects of OSA on visceral adipose tissue. We sought to assess the transcriptional consequences of OSA on adipocytes by utilizing pathway-focused analyses. Methods: Patients scheduled to undergo ventral hernia repair surgery were recruited to wear a portable home sleep monitor for two nights prior to surgery. Visceral fat biopsies were obtained intra-operatively. RNA was extracted and whole-genome expression profiling was performed. Gene Set Enrichment Analysis (GSEA) was used to identify curated gene sets that were differentially enriched in OSA subjects. Network analysis was applied to a select set of highly enriched pathways. Results: 10 patients with OSA and 8 control subjects were recruited. There were no differences in age, gender, body mass index between the two groups, but the OSA subjects had a significantly higher respiratory disturbance index (19.2 vs. 0.6, P-value 0.05) and worse hypoxemia (minimum oxygen saturation 79.7% vs. 87.8%, P-value < 0.001). GSEA identified a number of gene sets up-regulated in adipose tissue of OSA patients including the pro-inflammatory NF-κB pathway and the proteolytic ubiquitin/proteasome module. A critical metabolic pathway, the peroxisome proliferator-activated receptor (PPAR), was down-regulated in subjects with OSA. Network analysis linked members of these modules together and identified regulatory hubs. Conclusions: OSA is associated with alterations in visceral fat gene expression. Pathway-based network analysis highlighted perturbations in several key pathways whose coordinated interactions may contribute to the metabolic dysregulation observed in this complex disorder.
2012-09-01 | GSE38792 | GEO
Project description: Not available
| S-EPMC8183001 | biostudies-literature
Project description:Study objectivesObstructive sleep apnea (OSA) has been proposed as a risk factor for severe COVID-19. Confounding is an important consideration as OSA is associated with several known risk factors for severe COVID-19. Our aim was to assess the association of OSA with hospitalization due to COVID-19 using a population-based cohort with detailed information on OSA and comorbidities.MethodsIncluded were all community-dwelling Icelandic citizens 18 years of age and older diagnosed with SARS-CoV-2 infection in 2020. Data on demographics, comorbidities, and outcomes of COVID-19 was obtained from centralized national registries. Diagnosis of OSA was retrieved from the centralized Sleep Department Registry at Landspitali-The National University Hospital. Severe COVID-19 was defined as the composite outcome of hospitalization and death. The associations between OSA and the outcome were expressed as odds ratios (OR) with 95% confidence intervals (95% CI), calculated using logistic regression models and inverse probability weighting.ResultsA total of 4,756 individuals diagnosed with SARS-CoV-2 infection in Iceland were included in the study (1.3% of the Icelandic population), of whom 185 had a diagnosis of OSA. In total, 238 were hospitalized or died, 38 of whom had OSA. Adjusted for age, sex, and BMI, OSA was associated with poor outcome (OR 2.2, 95% CI 1.4 -3.5). This association was slightly attenuated (OR 2.0, 95% CI 2.0, 1.2-3.2) when adjusted for demographic characteristics and various comorbidities.ConclusionsOSA was associated with twofold increase in risk of severe COVID-19, and the association was not explained by obesity or other comorbidities.
| S-EPMC8690036 | biostudies-literature
Project description:Illumina MiSeq next generation sequencing chip was used to identify differentially expressed miRs by comparing peripheral blood mononuclear cell samples between OSA patients and healthy non-snorers.
2021-12-01 | GSE174245 | GEO
Project description:ObjectiveTo characterize the relationship between severity of sleep apnea and coronavirus disease 2019 (COVID-19) hospitalization and severe illness.Study designRetrospective cohort study.SettingMontefiore Health System in the Bronx, New York.MethodsThe data set consisted of adult patients with an active diagnosis of obstructive sleep apnea in the past 2 years and a positive severe acute respiratory syndrome coronavirus 2 quantitative polymerase chain reaction test at our institution between March 16, 2020, and May 26, 2020. Sleep apnea severity and continuous positive airway pressure compliance data were abstracted from the electronic medical record. The International Classification of Diseases, 10th Revision was used to classify comorbidities.ResultsA total of 461 patients with sleep apnea tested positive for COVID-19, of whom 149 were excluded for missing data in the electronic medical record. Patients with moderate and severe sleep apnea had higher rates of COVID-19 hospitalization compared to those with mild sleep apnea (P = .003). This association was reduced when accounting for confounders, most notably the Charlson Comorbidity Index, a measure of comorbid illness burden. Moderate and severe sleep apnea were associated with increased Charlson Comorbidity Indices, compared to mild sleep apnea (P = .01). Sleep apnea severity was not associated with a composite outcome of mechanical ventilation, intensive care unit admission, and death.ConclusionSleep apnea severity was associated with the Charlson Comorbidity Index and may be a risk factor for COVID-19 hospitalization. We found no evidence that sleep apnea severity among hospitalized patients was associated with a composite outcome of mechanical ventilation, intensive care unit admission, and death.
| S-EPMC8132102 | biostudies-literature
Project description: Not available
| S-EPMC7667903 | biostudies-literature
Project description:Obstructive sleep apnea (OSA) has been linked to dysregulated metabolic states and treatment of sleep apnea may improve these conditions. Subcutaneous adipose tissue is a readily samplable fat depot that plays an important role in regulating metabolism. However, neither the pathophysiologic consequences of OSA nor the effects of continuous positive airway pressure (CPAP) in altering this compartment’s molecular pathways are understood. This study aimed to systematically identify subcutaneous adipose tissue transcriptional programs modulated in OSA and in response to its effective treatment with CPAP. Two subject groups were investigated: Study Group 1 was comprised of 10 OSA and 8 controls; Study Group 2 included 24 individuals with OSA studied at baseline and following CPAP. For each subject, genome-wide gene expression measurement of subcutaneous fat was performed. Differentially activated pathways elicited by OSA (Group 1) and in response to its treatment (Group 2) were determined using network and Gene Set Enrichment Analysis (GSEA). In Group 2, treatment of OSA with CPAP improved apnea hypopnea index, daytime sleepiness, and blood pressure, but not anthropometric measures. In Group 1, GSEA revealed many up-regulated gene sets in OSA subjects, most of which were involved in immuno-inflammatory (e.g., interferon-γ signaling), transcription, and metabolic processes such as adipogenesis. Unexpectedly, CPAP therapy in Group 2 subjects was also associated with up-regulation of several immune pathways as well as cholesterol biosynthesis. Collectively, our findings demonstrate that OSA alters distinct inflammatory and metabolic programs in subcutaneous fat, but these transcriptional signatures are not reversed with short-term effective therapy.
2019-12-21 | GSE135917 | GEO
Project description:IntroductionEnhanced characterization of sleep architecture, compared with routine polysomnographic metrics such as stage percentages and sleep efficiency, may improve the predictive phenotyping of fragmented sleep. One approach involves using stage transition analysis to characterize sleep continuity.Methods and principal findingsWe analyzed hypnograms from Sleep Heart Health Study (SHHS) participants using the following stage designations: wake after sleep onset (WASO), non-rapid eye movement (NREM) sleep, and REM sleep. We show that individual patient hypnograms contain insufficient number of bouts to adequately describe the transition kinetics, necessitating pooling of data. We compared a control group of individuals free of medications, obstructive sleep apnea (OSA), medical co-morbidities, or sleepiness (n = 374) with mild (n = 496) or severe OSA (n = 338). WASO, REM sleep, and NREM sleep bout durations exhibited multi-exponential temporal dynamics. The presence of OSA accelerated the "decay" rate of NREM and REM sleep bouts, resulting in instability manifesting as shorter bouts and increased number of stage transitions. For WASO bouts, previously attributed to a power law process, a multi-exponential decay described the data well. Simulations demonstrated that a multi-exponential process can mimic a power law distribution.Conclusion and significanceOSA alters sleep architecture dynamics by decreasing the temporal stability of NREM and REM sleep bouts. Multi-exponential fitting is superior to routine mono-exponential fitting, and may thus provide improved predictive metrics of sleep continuity. However, because a single night of sleep contains insufficient transitions to characterize these dynamics, extended monitoring of sleep, probably at home, would be necessary for individualized clinical application.
| S-EPMC2893208 | biostudies-literature