Poster Presentations
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MicroRNA expression profiling and bioinformatics analysis of dysregulated microRNAs in OSA patients
Kun Li, Student, Beijing An Zhen Hospital, Capital Medical University, Beijing, China
OBJECTIVE: Obstructive sleep apnea (OSA) is a common chronic obstructive sleep disease in clinic.[1,2] The purpose of our study is to identify different microRNAs (miRNAs) between OSA patients and healthy controls.
MATERIALS AND METHODS: 3 OSA patients’ and 3 healthy controls’ serum samples were collected. Serum RNA was extracted and library was constructed for RNA sequencing on Illumina HiSeq2000 platform. Differentially expressed microRNAs were calculated by the criteria of fold-change >=1.5 and Fisher exact test p-value < 0.01. Thereafter, TargetScan and mircoT-CDS databases were used to predict the potential target genes and pathways were enriched with Funrich. Regulatory miRNA-target gene network was constructed with Cytoscape.
RESULTS: A total of 118 differentially expressed microRNAs were identified between OSA patients and healthy control. Supervised hierarchical clustering was conducted based on the expression of 118 microRNAs in OSA patients and healthy controls. 6621 potential target genes were predicted and 119 target genes were screened based on co-expression coefficient in String database. Regulatory co-expression network was constructed, including 23 differentially expressed microRNAs and 18 most related potential target genes. The metabolic signaling pathways was mostly enriched and microRNAs like hsa-miR-485-5p, hsa-miR-107, hsa-miR-574-5p ,hsa-miR-199-3p,hsa-miR-127-3p and hsa-miR-139-3p had high degree.
CONCLUSIONS: Differentially expressed microRNAs like hsa-miR-485-5p, hsa-miR-107, hsa-miR-574-5p and hsa-miR-199-3p might participate in OSA. These results would pave ways for further study of OSA mechanism, and for the prevention and diagnosis of OSA. However, more experimental verifications are required to prove these predictions.
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