Molecular determinants of obstructive sleep apnea

Orientin Promotes Antioxidant Capacity, Mitochondrial Biogenesis, and Fiber Transformation in Skeletal Muscles through the AMPK Pathway

The sleep-breathing condition obstructive sleep apnea (OSA) is characterized by repetitive upper airway collapse, which can exacerbate oxidative stress and free radical generation, thereby detrimentally impacting both motor and sensory nerve function and inducing muscular damage. OSA development is promoted by increasing proportions of fast-twitch muscle fibers in the genioglossus. Orientin, a water-soluble dietary C-glycosyl flavonoid with antioxidant properties, increased the expression of slow myosin heavy chain (MyHC) and signaling factors associated with AMP-activated protein kinase (AMPK) activation both in vivo and in vitro. Inhibiting AMPK signaling diminished the effects of orientin on slow MyHC, fast MyHC, and Sirt1 expression. Overall, orientin enhanced type I muscle fibers in the genioglossus, enhanced antioxidant capacity, increased mitochondrial biogenesis through AMPK signaling, and ultimately improved fatigue resistance in C2C12 myotubes and mouse genioglossus. These findings suggest that orientin may contribute to upper airway stability in patients with OSA, potentially preventing airway collapse.

Identification of novel biomarkers in obstructive sleep apnea via integrated bioinformatics analysis and experimental validation

Background

Obstructive sleep apnea (OSA) is a complex and multi-gene inherited disease caused by both genetic and environmental factors. However, due to the high cost of diagnosis and complex operation, its clinical application is limited. This study aims to explore potential target genes associated with OSA and establish a corresponding diagnostic model.

Methods

This study used microarray datasets from the Gene Expression Omnibus (GEO) database to identify differentially expressed genes (DEGs) related to OSA and perform functional annotation and pathway analysis. The study employed multi-scale embedded gene co-expression network analysis (MEGENA) combined with least absolute shrinkage and selection operator (LASSO) regression analysis to select hub genes and construct a diagnostic model for OSA. In addition, the study conducted correlation analysis between hub genes and OSA-related genes, immunoinfiltration, gene set enrichment analysis (GSEA), miRNA network analysis, and identified potential transcription factors (TFs) and targeted drugs for hub genes. Finally, the study used chronic intermittent hypoxia (CIH) mouse model to simulate OSA hypoxic conditions and verify the expression of hub genes in CIH mice.

Results

In this study, a total of 401 upregulated genes and 275 downregulated genes were identified, and enrichment analysis revealed that these differentially expressed genes may be associated with pathways such as vasculature development, cellular response to cytokine stimulus, and negative regulation of cell population proliferation. Through MEGENA combined with LASSO regression, seven OSA hub genes were identified, including C12orf54, FOS, GPR1, OR9A4, MYO5B, RAB39B, and KLHL4. The diagnostic model constructed based on these genes showed strong stability. The expression levels of hub genes were significantly correlated with the expression levels of OSA-related genes and mainly acted on pathways such as the JAK/STAT signaling pathway and the cytosolic DNA-sensing pathway. Drug-target predictions for hub genes were made using the Connectivity Map (CMap) database and the Drug-Gene Interaction database (Dgidb), which identified targeted therapeutic drugs for the hub genes. In vivo experiments showed that the hub genes were all decreasing in the OSA mouse model.

Conclusions

This study identified novel biomarkers for OSA and established a reliable diagnostic model. The transcriptional changes identified may help to reveal the pathogenesis, mechanisms, and sequelae of OSA.

Evaluation of clinical and genetic factors in obstructive sleep apnoea

Purpose

To evaluate the correlation between several presumed candidate genes for obstructive sleep apnoea (OSA) and clinical OSA phenotypes and propose a predictive comprehensive model for diagnosis of OSA.

Methods

This case-control study compared polysomnographic patterns, clinical data, morbidities, dental factors and genetic data for polymorphisms in PER3, BDNF, NRXN3, APOE, HCRTR2, MC4R between confirmed OSA cases and ethnically matched clinically unaffected controls. A logistic regression model was developed to predict OSA using the combined data.

Results

The cohort consisted of 161 OSA cases and 81 controls. Mean age of cases was 53.5 ± 14.0 years, mostly males (57%) and mean body mass index (BMI) of 27.5 ± 4.3 kg/m2. None of the genotyped markers showed a statistically significant association with OSA after adjusting for age and BMI. A predictive algorithm included the variables gender, age, snoring, hypertension, mouth breathing and number of T alleles of PER3 (rs228729) presenting 76.5% specificity and 71.6% sensitivity.

Conclusions

No genetic variant tested showed a statistically significant association with OSA phenotype. Logistic regression analysis resulted in a predictive model for diagnosing OSA that, if validated by larger prospective studies, could be applied clinically to allow risk stratification for OSA.

Emerging role of metabolomics for biomarker discovery in obstructive sleep apnea

Obstructive sleep apnea (OSA) is characterized by the complete or partial blockage of the upper airway passage during sleep which causes repetitive breaks in sleep and may result in excessive daytime sleepiness. OSA has been linked to various metabolic disorders and chronic health conditions, such as obesity, diabetes, hypertension, and depression. Profiling of alterations in metabolites and their regulation in OSA has been hypothesized to be an effective approach for early diagnosis and prognosis of OSA. Several studies have characterized metabolic fingerprints associated with sleep disorders. There is a lack of understanding of metabolite contents and their alterations in OSA that may help to identify specific biomarkers. The information provided in this review will help update new methodologies and interventions of high throughput advanced molecular/metabolomics tools which may clarify the metabolic aspects and mechanisms for improved management and treatment of OSA.

Whole-exome identifies germline variants in families with obstructive sleep apnea syndrome

Background: Obstructive sleep apnea syndrome (OSAS) (OMIM #107650) is characterized by complete or partial obstruction of the upper airways, resulting in periods of sleep associated apnea. OSAS increases morbidity and mortality risk from cardiovascular and cerebrovascular diseases. While heritability of OSAS is estimated at ∼40%, the precise underlying genes remain elusive. Brazilian families with OSAS that follows as seemingly autosomal dominant inheritance pattern were recruited. Methods: The study included nine individuals from two Brazilian families displaying a seemingly autosomal dominant inheritance pattern of OSAS. Whole exome sequencing of germline DNA were analyzed using Mendel, MD software. Variants selected were analyzed using Varstation^® with subsequent analyses that included validation by Sanger sequencing, pathogenic score assessment by ACMG criteria, co-segregation analyses (when possible) allele frequency, tissue expression patterns, pathway analyses, effect on protein folding modeling using Swiss-Model and RaptorX. Results: Two families (six affected patients and three unaffected controls) were analyzed. A comprehensive multistep analysis yielded variants in COX20 (rs946982087) (family A), PTPDC1 (rs61743388) and TMOD4 (rs141507115) (family B) that seemed to be strong candidate genes for being OSAS associated genes in these families. Conclusion: Sequence variants in COX20, PTPDC1 and TMOD4 seemingly are associated with OSAS phenotype in these families. Further studies in more, ethnically diverse families and non-familial OSAS cases are needed to better define the role of these variants as contributors to OSAS phenotype.

Integrative Analysis and Experimental Validation of Competing Endogenous RNAs in Obstructive Sleep Apnea

Background: Obstructive sleep apnea (OSA) is highly prevalent yet underdiagnosed. This study aimed to develop a predictive signature, as well as investigate competing endogenous RNAs (ceRNAs) and their potential functions in OSA. Methods: The GSE135917, GSE38792, and GSE75097 datasets were collected from the National Center for Biotechnology Information (NCBI) Gene Expression Omnibus (GEO) database. Weighted gene correlation network analysis (WGCNA) and differential expression analysis were used to identify OSA-specific mRNAs. Machine learning methods were applied to establish a prediction signature for OSA. Furthermore, several online tools were used to establish the lncRNA-mediated ceRNAs in OSA. The hub ceRNAs were screened using the cytoHubba and validated by real-time quantitative reverse transcription-polymerase chain reaction (qRT-PCR). Correlations between ceRNAs and the immune microenvironment of OSA were also investigated. Results: Two gene co-expression modules closely related to OSA and 30 OSA-specific mRNAs were obtained. They were significantly enriched in the antigen presentation and lipoprotein metabolic process categories. A signature that consisted of five mRNAs was established, which showed a good diagnostic performance in both independent datasets. A total of twelve lncRNA-mediated ceRNA regulatory pathways in OSA were proposed and validated, including three mRNAs, five miRNAs, and three lncRNAs. Of note, we found that upregulation of lncRNAs in ceRNAs could lead to activation of the nuclear factor kappa B (NF-κB) pathway. In addition, mRNAs in the ceRNAs were closely correlated to the increased infiltration level of effector memory of CD4 T cells and CD56bright natural killer cells in OSA. Conclusions: In conclusion, our research opens new possibilities for diagnosis of OSA. The newly discovered lncRNA-mediated ceRNA networks and their links to inflammation and immunity may provide potential research spots for future studies.

Biomarkers for the severity of periodontal disease in patients with obstructive sleep apnea:IL-1 β, IL-6, IL-17A, and IL-33

Objective

This study aims to compare the salivary and gingival crevicular fluid (GCF) concentrations of five cytokines: IL-1β, IL-6, IL-17A, IL-33, and Tumor Necrosis Factor-alpha (TNF-α) in patients with OSA and their association with periodontitis.

Methods

Samples of saliva and GCF were obtained from 84 patients classified into four groups according to periodontal and OSA diagnosis: G1(H) healthy patients, G2(P) periodontitis and non-OSA patients, G3(OSA) OSA and non-periodontitis patients, and G4(P-OSA) periodontitis and OSA patients. The cytokines in the samples were quantified using multiplexed bead immunoassays. Data were analyzed with the Kruskal-Wallis test, Dunn's multiple comparisons test, and the Spearman correlation test.

Results

Stage III periodontitis was the highest in patients with severe OSA (69%; p=0.0142). Similar levels of IL-1β and IL-6 in saliva were noted in G2(P) and G4(P-OSA). The IL-6, IL-17A and IL-33 levels were higher in the GCF of G4(P-OSA). There was a significant positive correlation between IL-33 in saliva and stage IV periodontitis in G4(P-OSA) (r _s  = 0.531). The cytokine profile of the patients in G4(P-OSA) with Candida spp. had an increase of the cytokine's levels compared to patients who did not have the yeast.

Conclusions

OSA may increase the risk of developing periodontitis due to increase of IL-1β and IL-6 in saliva and IL-6, IL-17A and IL-33 in GCF that share the activation of the osteoclastogenesis. Those cytokines may be considered as biomarkers of OSA and periodontitis.

Chronic intermittent hypoxia impaired collagen synthesis in mouse genioglossus via ROS accumulation: A transcriptomic analysis

Obstructive sleep apnea (OSA) is a sleep-related breathing disorder characterized by intermittent and recurrent upper airway collapse during sleep that leads to chronic intermittent hypoxia (CIH). The genioglossus (GG) is the largest dilator muscle, which controls the upper airway and plays an important role in OSA pathology. Elucidating its genetic alterations may help identify potential targets for OSA. However, the genetic aspects of the GG in CIH mice remain unclear. Here, we have conducted an RNA sequencing (RNA-Seq) analysis to assess the differentially expressed genes (DEGs) in the GG between CIH mice and normoxia (NOR) mice. A total of 637 DEGs were identified to be dysregulated in CIH mice compared with control mice. Bioinformatics analysis showed that the DEGs were related to various physiological processes, such as the endogenous stimulus responses, cellular component organization and metabolic processes. Extracellular matrix (ECM)-receptor interaction was the top KEGG pathway in the environmental information processing category with high significance and large fold changes. From the gene weight distributions of collagen (Col)-related biological processes (BPs), we found several significant DEGs, such as Col1a1, Col1a2, Mmp2, Col3a1, Col5a1, Fmod, and Col5a2. A PPI network showed that Col1a1 was linked to ECM-receptor interactions, responses to reactive oxygen species (ROS) and Col-related BPs. It was verified in vivo and in vitro that hypoxia can induce excess ROS and reduce Col expression levels. Moreover, we found NAC can effectively scavenge ROS and restore collagen synthesis. These findings contribute to a better understanding of the mechanisms linking OSA and upper airway muscle injury and may help identify potential therapeutic targets.

Identification of metabolic fingerprints in severe obstructive sleep apnea using gas chromatography-Mass spectrometry

Objective: Obstructive sleep apnea (OSA) is considered a major sleep-related breathing problem with an increasing prevalence rate. Retrospective studies have revealed the risk of various comorbidities associated with increased severity of OSA. This study aims to identify novel metabolic biomarkers associated with severe OSA. Methods: In total, 50 cases of OSA patients (49.74 ± 11.87 years) and 30 controls (39.20 ± 3.29 years) were included in the study. According to the polysomnography reports and questionnaire-based assessment, only patients with an apnea-hypopnea index (AHI >30 events/hour) exceeding the threshold representing severe OSA patients were considered for metabolite analysis. Plasma metabolites were analyzed using gas chromatography-mass spectrometry (GC-MS). Results: A total of 92 metabolites were identified in the OSA group compared with the control group after metabolic profiling. Metabolites and their correlated metabolic pathways were significantly altered in OSA patients with respect to controls. The fold-change analysis revealed markers of chronic kidney disease, cardiovascular risk, and oxidative stress-like indoxyl sulfate, 5-hydroxytryptamine, and 5-aminolevulenic acid, respectively, which were significantly upregulated in OSA patients. Conclusion: Identifying these metabolic signatures paves the way to monitor comorbid disease progression due to OSA. Results of this study suggest that blood plasma-based biomarkers may have the potential for disease management.

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

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