Comprehensive analysis of m6A-modified circRNAs in mice model of myocardial injury induced by obstructive sleep apnea
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ORGANISM(S): Mus musculus
PROVIDER: GSE224632 | GEO | 2025/04/09
REPOSITORIES: GEO
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Project description:Comprehensive analysis of m6A-modified circRNAs in mice model of myocardial injury induced by obstructive sleep apnea
| PRJNA931983 | ENA
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:Impaired brachial flow-mediated dilation (FMD) is associated with risk for subsequent cardiovascular events in patients after myocardial infarction (MI). These patients often have obstructive sleep apnea (OSA). We tested the hypothesis that patients with OSA post MI will exhibit more severe impairment in FMD.We studied 64 patients with MI admitted to our hospital. OSA was determined using polysomnography. FMD was measured using high-resolution ultrasonography, with researchers blind to the OSA diagnosis.The mean age was 60 ± 11 years, and the mean BMI was 29 (26, 32 kg/m(2)), 84% of patients were men, 39% had moderate to severe OSA (apnea-hypopnea index [AHI] > 15), and 31% of the patients had mild OSA (5 ≤ AHI < 15). FMD was severely impaired in patients with moderate to severe OSA (0.8% ± 0.7%) as compared with patients without OSA (4.7% ± 0.8%, P = .001) and with mild OSA (3.9% ± 0.8%, P = .015). Linear regression showed that FMD was associated with log nocturnal nadir oxygen saturation (minSaO(2)) (β = 31.17, P = .0001), age (β = -0.11, P = .006). MinSaO(2) was an independent predictor of FMD after adjustment for possible confounders (β = 26.15, P = .001).FMD is severely impaired in patients with moderate to severe OSA post MI, which may be partially related to nocturnal hypoxemia. Patients with OSA may, therefore, be at higher risk for subsequent cardiovascular events after an MI. Identifying and treating OSA may have important implications in the long-term prognosis of patients post MI. Further studies are necessary to determine if the presence of OSA would affect the long-term occurrence of cardiovascular events after an MI.
| S-EPMC3130528 | biostudies-other
Project description:PurposeObstructive sleep apnea (OSA) is prevalent in children and diagnostic polysomnography is costly and not readily available in all areas. We developed a pediatric modification of a commonly used adult clinical prediction tool for stratifying the risk of OSA and the need for polysomnography.MethodsA total of 312 children (age 9-17 years) from phase 2 of the Tucson Children's Assessment of Sleep Apnea cohort study, with complete anthropomorphic data, parent questionnaires, and home polysomnograms were included. An adolescent modification of STOP-Bang (teen STOP-Bang) was developed and included snoring, tired, observed apnea, blood pressure ≥ 95th percentile, BMI > 95th percentile, academic problems, neck circumference >95th percentile for age, and male gender. An apnea-hypopnea index ≥ 1.5 events/hour was considered diagnostic of OSA.ResultsReceiver Operator Characteristic (ROC) curves for parent-reported STOP-Bang scores were generated for teenage and pre-teen children. A STOP-Bang score of < 3 in teenagers was associated with a negative predictive value of 0.96. ROC curves were also generated based upon child-reported sexual maturity rating (SMR; n = 291). The ability of teen STOP-Bang to discriminate the presence or absence of OSA as measured by the AUC for children with SMR ≥ 4 (0.83; 95%CI 0.71-0.95) was better than children with SMR < 4 (0.63; 95%CI 0.46-0.81; p = 0.048).ConclusionsIn community dwelling adolescents, teen STOP-Bang may be useful in stratifying the risk of OSA.
| S-EPMC4651349 | 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:Obstructive Sleep Apnea (OSA) is a respiratory disorder characterized by frequent breathing pauses during sleep. The apnea-hypopnea index is a measure used to assess the severity of sleep apnea and the hourly rate of respiratory events. Despite numerous commercial devices available for apnea diagnosis and early detection, accessibility remains challenging for the general population, leading to lengthy wait times in sleep clinics. Consequently, research on monitoring and predicting OSA has surged. This comprehensive paper reviews devices, emphasizing distinctions among representative apnea devices and technologies for home detection of OSA. The collected articles are analyzed to present a clear discussion. Each article is evaluated according to diagnostic elements, the implemented automation level, and the derived level of evidence and quality rating. The findings indicate that the critical variables for monitoring sleep behavior include oxygen saturation (oximetry), body position, respiratory effort, and respiratory flow. Also, the prevalent trend is the development of level IV devices, measuring one or two signals and supported by prediction software. Noteworthy methods showcasing optimal results involve neural networks, deep learning, and regression modeling, achieving an accuracy of approximately 99%.
| S-EPMC10708697 | biostudies-literature
Project description:Some ceRNA associated with lncRNA have been considered as possible diagnostic and therapeutic biomarkers for obstructive sleep apnea (OSA). We intend to identify the potential hub genes for the development of OSA, which will provide a foundation for the study of the molecular mechanism underlying OSA and for the diagnosis and treatment of OSA.We collected plasma samples from OSA patients and healthy controls for the detection of ceRNA using a chip. Based on the differential expression of lncRNA, we identified the target genes of miRNA that bind to lncRNAs. We then constructed lncRNA-related ceRNA networks, performed functional enrichment analysis and protein-protein interaction analysis, and performed internal and external validation of the expression levels of stable hub genes. Then, we conducted LASSO regression analysis on the stable hub genes, selected relatively significant genes to construct a simple and easy-to-use nomogram, validated the nomogram, and constructed the core ceRNA sub-network of key genes.We successfully identified 282 DElncRNAs and 380 DEmRNAs through differential analysis, and we constructed an OSA-related ceRNA network consisting of 292 miRNA-lncRNAs and 41 miRNA-mRNAs. Through PPI and hub gene selection, we obtained 7 additional robust hub genes, CCND2, WT1, E2F2, IRF1, BAZ2A, LAMC1, and DAB2. Using LASSO regression analysis, we created a nomogram with four predictors (CCND2, WT1, E2F2, and IRF1), and its area under the curve (AUC) is 1. Finally, we constructed a core ceRNA sub-network composed of 74 miRNA-lncRNA and 7 miRNA-mRNA nodes.Our study provides a new foundation for elucidating the molecular mechanism of lncRNA in OSA and for diagnosing and treating OSA.
2023-04-25 | GSE226379 | GEO
Project description:Study objectivesThe aim of the study was to investigate the effect of ambient temperature on sleep, sleep apnea, and morning alertness in patients with obstructive sleep apnea.DesignRandomized controlled trial.SettingIn-hospital investigations.ParticipantsForty patients with obstructive sleep apnea naïve to treatment, with an apnea-hypopnea index of 10-30.InterventionsThree different nights in room temperatures of 16°C, 20°C, and 24°C.MeasurementsOvernight polysomnography and Karolinska Sleepiness Scale.ResultsThe obstructive apnea-hypopnea index was 30 ± 17 at 16°C room temperature, 28 ± 17 at 20°C, and 24 ± 18 at 24°C. The obstructive apnea-hypopnea index was higher at 16°C room temperature versus 24°C (P = 0.001) and at 20°C room temperature versus 24°C (P = 0.033). Total sleep time was a mean of 30 min longer (P = 0.009), mean sleep efficiency was higher (77 ± 11% versus 71 ± 13% respectively, P = 0.012), and the patients were significantly more alert according to the Karolinska Sleepiness Scale (P < 0.028) in the morning at 16°C room temperature versus 24°C. The amount of sleep in different sleep stages was not affected by room temperature.ConclusionsUntreated patients with obstructive sleep apnea sleep longer, have better sleep efficiency, and are more alert in the morning after a night's sleep at 16°C room temperature compared with 24°C, but obstructive sleep apnea is more severe at 16°C and 20°C compared with 24°C.Clinical trial informationThis study is registered in ClinicalTrials.gov number NCT00544752.
| S-EPMC3296793 | biostudies-literature
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