Dataset Information

Identification and validation of circulating miRNAs as endogenous controls in obstructive sleep apnea.

ABSTRACT: microRNAs (miRNAs) are non-coding RNAs highly relevant as biomarkers for disease. A seminal study that explored the role of miRNAs in obstructive sleep apnea syndrome (OSA) demonstrated their usefulness in clinical management. Nevertheless, the miRNAs that may act as endogenous controls (ECs) have not yet been established. The identification of ECs would contribute to the standardization of these biomarkers in OSA. The objective of the study is to identify miRNAs that can be used as ECs in OSA. We evaluated 100 patients divided into two different cohorts: a learning cohort of 10 non-OSA and 30 OSA patients, and a validation cohort (20 non-OSA and 40 OSA patients). In the learning cohort, a profile of 188 miRNAs was determined in plasma by TaqMan Low Density Array. The best EC candidates were identified by mean center+SD normalization and concordance correlation restricted normalization. The results were validated using NormFinder and geNorm to assess the stability of those ECs. Eight miRNAs were identified as EC candidates. The combination miRNA-106a/miRNA-186 was identified as the most stable among all candidates. We identified a set of ECs to be used in the determination of circulating miRNA in OSA that may contribute to the homogeneity of results.

SUBMITTER: Santamaria-Martos F

PROVIDER: S-EPMC6415855 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Identification and validation of circulating miRNAs as endogenous controls in obstructive sleep apnea.

Santamaria-Martos Fernando F Benítez Ivan I Zapater Andrea A Girón Cristina C Pinilla Lucía L Fernandez-Real Jose Manuel JM Barbé Ferran F Ortega Francisco Jose FJ Sánchez-de-la-Torre Manuel M

PloS one 20190313 3

microRNAs (miRNAs) are non-coding RNAs highly relevant as biomarkers for disease. A seminal study that explored the role of miRNAs in obstructive sleep apnea syndrome (OSA) demonstrated their usefulness in clinical management. Nevertheless, the miRNAs that may act as endogenous controls (ECs) have not yet been established. The identification of ECs would contribute to the standardization of these biomarkers in OSA. The objective of the study is to identify miRNAs that can be used as ECs in OSA. ...[more]

PMID: 30865706

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Project description:BackgroundBy 2020, the prevalence of Obstructive Sleep Apnea Syndrome (OSAS) in the US has reached 26. 6-43.2% in men and 8.7-27.8% in women. OSAS promotes hypertension, diabetes, and tumor growth through unknown means. Chronic intermittent hypoxia (CIH), sleep fragmentation, and increased pleural pressure are central mechanisms of OSAS complications. CIH exacerbates ferroptosis, which is closely related to malignancies. The mechanism of ferroptosis in OSAS disease progression remains unknown.MethodsOSAS-related datasets (GSE135917 and GSE38792) were obtained from the GEO. Differentially expressed genes (DEGs) were screened using the R software and intersected with the ferroptosis database (FerrDb V2) to get ferroptosis-related DEGs (f-DEGs). GO, DO, KEGG, and GSEA enrichment were performed, a PPI network was constructed and hub genes were screened. The TCGA database was used to obtain the thyroid cancer (THCA) gene expression profile, and hub genes were analyzed for differential and survival analysis. The mechanism was investigated using GSEA and immune infiltration. The hub genes were validated with RT-qPCR, IHC, and other datasets. Sprague-Dawley rats were randomly separated into normoxia and CIH groups. ROS, MDA, and GSH methods were used to detect CIH-induced ferroptosis and oxidative stress.ResultsGSEA revealed a statistically significant difference in ferroptosis in OSAS (FDR < 0.05). HIF1A, ATM, HSPA5, MAPK8, MAPK14, TLR4, and CREB1 were identified as hub genes among 3,144 DEGs and 74 f-DEGs. HIF1A and ATM were the only two validated genes. F-DEGs were mainly enriched in THCA. HIF1A overexpression in THCA promotes its development. HIF1A is associated with CD8 T cells and macrophages, which may affect the immunological milieu. The result found CIH increased ROS and MDA while lowering GSH indicating that it could cause ferroptosis. In OSAS patients, non-invasive ventilation did not affect HIF1A and ATM expression. Carvedilol, hydralazine, and caffeine may be important in the treatment of OSAS since they suppress HIF1A and ATM.ConclusionsOur findings revealed that the genes HIF1A and ATM are highly expressed in OSAS, and can serve as biomarkers and targets for OSAS.

Project description:BackgroundObstructive 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.MethodsThis 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.ResultsIn 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.ConclusionsThis 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.

Dataset Information

Identification and validation of circulating miRNAs as endogenous controls in obstructive sleep apnea.

Publications

Identification and validation of circulating miRNAs as endogenous controls in obstructive sleep apnea.

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