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Intermittent hypoxia (IH) is an important pathophysiological feature of obstructive sleep apnea (OSA), but its molecular mechanism is still unclear. We aim to investigate the role of endogenous competing endogenous RNA (ceRNA) regulatory network in the development of IH in OSA rats. An intermittent hypoxic rat model of OSA was constructed by hypoxic and reoxygenation cycles. CircRNAs and mRNAs were detected in rat bronchial tissues, and 230 up-regulated and 181 down-regulated circRNAs and 1238 up-regulated and 608 down-regulated mRNAs were analyzed and screened. The results of Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis of the differential circRNAs and mRNAs suggested that they were mainly associated with metabolic pathways and PI3K-Akt signaling pathways. The key circRNAs (the top six circRNAs with the largest differences) were further validated by quantitative real-time polymerase chain reaction (qRT-PCR), chr9:52042693| 52047844 and chr4: 64889575|64899587 were expressed in bronchial tissues consistent with the sequencing results, which were used to further construct the ceRNA regulatory network. Four potential ceRNA regulatory networks were identified by TargetScan and miRanda database, combined with the results of differential circRNA and mRNA. The expression of molecules in the four potential ceRNA regulatory networks was detected by qRT-PCR in bronchial and lung tissues, and the results suggested that the expression of this regulatory network, chr9:52042693|52047844-miR-351-5p-Pten, was consistent with the sequencing results. The findings indicate that chr9:52042693 | 52047844-miR-351-5p-Pten may be involved in the development and progression of obstructive sleep apnea syndrome through a ceRNA mechanism.
RESUMEN
【Objective】 To construct a prediction model of severe obstructive sleep apnea (OSA) risk in the general population by using nomogram in order to explore the independent risk factors of severe OSA and guide the early diagnosis and treatment. 【Methods】 We retrospectively enrolled patients who had been diagnosed by polysomnography and divided them into training and validation sets at the ratio of 7∶3. Patients were divided into severe OSA group and non-severe OSA group according to apnea hypopnea index (AHI)>30. Variables entering the model were identified by least absolute shrinkage and selection operator regression model (Lasso), and logistic regression (LR) method. Then, multivariable logistic regression analysis was used to establish the nomogram, and the area under the receiver operating characteristic curve (AUC) was used to evaluate the discriminative properties of the nomogram model. Finally, we conducted decision curve analysis (DCA) of nomogram model, STOP-Bang questionnaire and Berlin questionnaire to assess clinical utility. 【Results】 Through single factor and multiple factor logistic regression analyses, the independent risk factors for severe OSA were screened out, including moderate and severe sleepiness, family history of hypertension, history of smoking, drinking, snoring, history of suffocation, sedentary lifestyle, male, age, body mass index (BMI), waist and neck circumference. Lasso logistic regression identified smoke, suffocation time, snoring time, waistline, Epworth sleepiness scale (ESS) and BMI as predictive factors for inclusion in the nomogram. The AUC of the model was 0.795 [95% confidence interval (CI): 0.769-0.820] . Hosmer-Lemeshow test indicated that the model was well calibrated (χ2=3.942, P=0.862). The DCA results on the visual basis confirmed that the nomogram had superior overall net benefits within a wide, practical threshold probability range which displayed the nomogram was higher than that of STOP-Bang questionnaire and Berlin questionnaire, which is clinically useful. The Clinical Impact Curve (CIC) analysis showed the clinical effectiveness of the prediction model when the threshold probability was greater than 82% of the predicted score probability value. The prediction model determined that the high-risk population with severe OSA was highly matched with the actual population with severe OSA, which confirmed the high clinical effectiveness of the prediction model. 【Conclusion】 The model performed better than STOP-Bang questionnaire and Berlin questionnaire in predicting severe OSA and can be applied to screening. And it can be helpful to the early diagnosis and treatment of OSA in order to reduce social burden.
RESUMEN
Resumen: El inicio de la respiración nasal marca un impulso genéticamente determinado para airear las cavidades de la cara o senos paranasales, que a su vez inician su crecimiento y forman el espacio útil transitable desde el punto de vista respiratorio durante el desarrollo del tercio medio facial. Considerando la evidencia de que la obstrucción de la vía aérea superior tiene un rol primordial en la patogénesis de los trastornos respiratorios del sueño, cualquier patología que cause dificultad permanente al flujo aéreo nasal durante la respiración llevará a un hipodesarrollo de la amplitud requerida en esta vía, disminuyendo la estimulación del crecimiento de las cavidades sinusales y alterando el desarrollo del tercio medio facial en su conjunto.
Abstract: The onset of nasal breathing sets a genetically determined impulse to aerate the face cavities or paranasal sinuses, which in turn initiate its growth creating the useful trafficable space for air during the development of the midface. Considering the evidence that the upper airway obstruction has a primary role in the pathogenesis of respiratory sleep disorders, any condition that causes a permanent difficulty to the nasal airflow during breathing will cause hypo-development of the required amplitude in this airway, reducing the growth stimulation of the sinus cavities and altering the development of the midface as a whole.
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Background: Sleep-disordered breathing or obstructive sleep apnea (OSA) has an important effect on the quality of life. Very few data of OSA are available for Thai persons. Objective: Investigate the prevalence of high risk to OSA and the relationship between OSA and risk factors in Thai medical students. Materials and methods: Three hundred seven subjects were recruited from all of the medical students (fourth year to sixth year) the Faculty of Medicine, Srinakharinwirot University, Thailand for this cross-sectional study. Data was collected between June and September 2010. The Berlin questionnaire was used to determine risk for OSA. Logistic regression analysis was performed with p-value less than 0.05 for statistical significance. Results: The prevalence of high risk to OSA was 6.8%. Total mean of sleep duration, bedtime, and wake-time was 6.59 hours. Bedtime of male students was significantly later than female students. The medical students with body mass index (BMI) >23 kilogram/meter2 and with underlying diseases were at high-risk for OSA. Conclusion: Prevalence of high-risk to OSA of Thai medical students was 6.8%. The medical students with BMI >23 kilogram/meter2 and with underlying diseases were at high risk for OSA but gender, age, academic year, and academic achievement did not relate to OSA.