Qingxian Wang, Yunhe Chang, Xuqing Yang, Ziwang Han
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引用次数: 0
Abstract
Deep venous thrombosis is one of the most common peripheral vascular diseases that lead to major morbidity and mortality. The authors aimed to identify potential differentially expressed miRNAs and target mRNAs, which were helpful in understanding the potential molecule mechanism of deep venous thrombosis. The plasma samples of patients with deep venous thrombosis were obtained for the RNA sequencing. Differentially expressed miRNAs were identified, followed by miRNA-mRNA target analysis. Enrichment analysis was used to analyze the potential biological function of target mRNAs. GSE19151 and GSE173461 datasets were used for expression validation of mRNAs and miRNAs. 131 target mRNAs of 21 differentially expressed miRNAs were identified. Among which, 8 differentially expressed miRNAs including hsa-miR-150-5p, hsa-miR-326, hsa-miR-144-3p, hsa-miR-199a-5p, hsa-miR-199b-5p, hsa-miR-125a-5p, hsa-let-7e-5p and hsa-miR-381-3p and their target mRNAs (PRKCA, SP1, TP53, SLC27A4, PDE1B, EPHB3, IRS1, HIF1A, MTUS1 and ZNF652) were found associated with deep venous thrombosis for the first time. Interestingly, PDE1B and IRS1 had a potential diagnostic value for patients. Additionally, 3 important signaling pathways including p53, PI3K-Akt and MAPK were identified in the enrichment analysis of target mRNAs (TP53, PRKCA and IRS1). Identified circulating miRNAs and target mRNAs and related signaling pathways may be involved in the process of deep venous thrombosis.
期刊介绍:
IET Systems Biology covers intra- and inter-cellular dynamics, using systems- and signal-oriented approaches. Papers that analyse genomic data in order to identify variables and basic relationships between them are considered if the results provide a basis for mathematical modelling and simulation of cellular dynamics. Manuscripts on molecular and cell biological studies are encouraged if the aim is a systems approach to dynamic interactions within and between cells.
The scope includes the following topics:
Genomics, transcriptomics, proteomics, metabolomics, cells, tissue and the physiome; molecular and cellular interaction, gene, cell and protein function; networks and pathways; metabolism and cell signalling; dynamics, regulation and control; systems, signals, and information; experimental data analysis; mathematical modelling, simulation and theoretical analysis; biological modelling, simulation, prediction and control; methodologies, databases, tools and algorithms for modelling and simulation; modelling, analysis and control of biological networks; synthetic biology and bioengineering based on systems biology.