Observational studyMedicine2017
MicroRNA expression profiling and bioinformatics analysis of dysregulated microRNAs in obstructive sleep apnea patients.
Observational study in Medicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
39 citing papers in PubMed, 57 citations in OpenAlex.
- Obstructive Sleep Apnea and Cardiovascular Disease: Mechanisms, Diagnostics, and Emerging Therapeutic Approaches.Biomedicines · 2026Review
- Article
- The Role of Hypoxia-SensitiveInternational journal of molecular sciences · 2025Article
- Circulating extracellular vesicles as potential biomarkers and mediators of acute respiratory distress syndrome in sepsis.Scientific reports · 2025Article
- Different expression of circulating microRNA profile in tibetan OSAHS with metabolic syndrome patients.Scientific reports · 2025Article
- Differential expression and correlation analysis of global transcriptome for obstructive sleep apnea hypopnea syndrome.Frontiers in molecular biosciences · 2025Article
- Integrative analysis of candidate MicroRNAs and gene targets for OSA management using in silico and in-vitro approach.Biotechnology notes (Amsterdam, Netherlands) · 2025Article
- Cross-Sectional Analysis of Hypoxia-RegulatedJournal of clinical medicine · 2024Article
- miR-574-5p in epigenetic regulation and Toll-like receptor signaling.Cell communication and signaling : CCS · 2024Review
- Advances in non-coding RNA as a biomarker for obstructive sleep apnoea hypoventilation syndrome.Sleep & breathing = Schlaf & Atmung · 2024Review
- [Effects of chronic intermittent hypoxia and reoxygenation on insulin resistance and skeletal muscle miR-27a-3p/PPARγ/IRS1/PI3K/AKT expressions in rats].Nan fang yi ke da xue xue bao = Journal of Southern Medical University · 2024Article
- Oxidative Stress in Obstructive Sleep Apnea Syndrome: Putative Pathways to Hearing System Impairment.Antioxidants (Basel, Switzerland) · 2023Review
- Pathophysiological mechanisms and therapeutic approaches in obstructive sleep apnea syndrome.Signal transduction and targeted therapy · 2023Review
- Molecular Pathology, Oxidative Stress, and Biomarkers in Obstructive Sleep Apnea.International journal of molecular sciences · 2023Review
- miR-485-5p alleviates obstructive sleep apnea syndrome with hypertension by inhibiting PI3K/AKT signaling pathway via downregulating HIF3A expression.Sleep & breathing = Schlaf & Atmung · 2023Article
- Article
- Article
- Development and validation of a genomic nomogram based on a ceRNA network for comprehensive analysis of obstructive sleep apnea.Frontiers in genetics · 2023Article
- Editorial: Computational methods to analyze RNA data for human diseases.Frontiers in genetics · 2023Article
- Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Obstructive sleep apnea (OSA) is a common chronic obstructive sleep disease in clinic. The purpose of our study was to use bioinformatics analysis to identify microRNAs (miRNAs) that are differentially expressed between OSA patients and healthy controls.Serum samples were collected from OSA patients and healthy controls. To better reveal the sample specificity of differentially expressed microRNAs, supervised hierarchical clustering was conducted. We used the microT-CDS and TargetScan databases to predict target genes of the differentially expressed microRNAs and selected the common genes. The Search Tool for the Retrieval of Interacting Genes (STRING) was used to evaluate many coexpression relationships. Moreover, we used these potential microRNA-target pairs and coexpression relationships to construct a regulatory coexpression network using Cytoscape software. Functional analysis of microRNA target genes was conducted with FunRich.A total of 104 microRNAs that were differentially expressed between OSA patients and healthy controls were identified. Supervised hierarchical clustering was conducted based on the expression of the 104 microRNAs in the OSA patients and healthy controls. Overall, 6621 potential target genes were predicted, and 119 target genes were screened based on coexpression coefficients in the STRING database. A regulatory coexpression network was constructed that included 23 differentially expressed microRNAs and 18 of the most related potential target genes. Metabolic signaling pathways were the most highly enriched category. Differentially expressed microRNAs, such as hsa-miR-485-5p, hsa-miR-107, hsa-miR-574-5p, and hsa-miR-199-3p, might participate in OSA. The target gene CAD might also be closely related to OSA.Our results may provide a basis for the pathogenesis of OSA and the study of disease diagnosis, prevention, and treatment. However, more experiments are needed to verify these predictions.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.