All experiments were reviewed and approved by the ethics committee of the Institute of Laboratory Animal Science of Shanxi Medical University (Taiyuan, China).

Adult male Sprague Dawley (SD) rats (n=36; Shanxi Laboratory Animal Center, Taiyuan, China) 8–10 weeks of age and weighing 280–300 g were used in the present study. The rats were divided into three groups as follows: DVT, sham and control (n=12). The rats were anesthetized by 10% chloral hydrate. A midline laparotomy was performed. The inferior vena was explored by moving the small intestine out of the way, and all side branches were ligated. IVC was ligated just below the left renal vein. A microvascular clamp was attached to the confluence of iliac veins for 15 min. The skin was sutured by 3–0 Prolene suture and penicillin powder (Sigma, Washington, DC, USA) covering the incision evenly was used. The sham-surgery rats received anesthesia and all surgical procedures, but without IVC ligation or clamping. The control group received no treatment.

The rats were sacrificed at day 3 after ligation. The IVC with thrombus was carefully harvested. One part of the tissue was fixed in 10% formalin solution for histological analysis and the rest was stored in RNAsafety (Shanghai Biotechnology Corp., Shanghai, China) for microarray analyses.

For histological examinations, the IVC tissue was fixed with 4% paraformaldehyde for 48 h and embedded in paraffin wax. The tissues were then cut into 4-μm-thick sections and the sections were dewaxed in xylene twice at 37°C for 15 min each time, rehydrated through decreasing concentrations of ethanol, and washed in distilled water at room temperature for 5 min each time. They were finally stained with hematoxylin and eosin (H&E) or Masson's trichrome, both following the company's instructions (Nanjing Jiancheng Bioengineering Institute, Nanjing, China). For H&E staining, the slides were dipped into the jar containing hematoxylin for 5 min and with eosin for 30 sec with agitation at room temperature. For Masson staining, slides were stained at room temperature with nuclear staining solution for 1 min, with cytoplasmic stain solution for 45 sec, then washed with phosphomolybdic acid for 6 min and last counterstained for 5 min. After staining, specimens were observed under a light microscope (Panoramic SCAN II; 3DHISTECH Kft., Budapest, Hungary) to evaluate the histomorphology of the venous walls.

Total RNA was extracted and purified using an Ambion mirVana miRNA isolation kit (cat. no. AM1561; Thermo Fisher Scientific, Inc., Waltham, MA, USA) and RNA integrity was assessed using an Agilent Bioanalyzer 2100 (Agilent Technologies, Inc., Santa Clara, CA, USA). The RNA samples were used for microarrays. To avoid differences between individuals, 200 ng total RNA isolated from three rats per group was pooled into a single sample. Microarray experiments were repeated to produce three independent biological replicates.

miRNA expression analysis was performed using nine Agilent rat miRNA (8×60K) V21.0 microarrays (design ID: 70154; Agilent Technologies, Inc.) at the National Engineering Center for Biochip, Shanghai Biotechnology, Corp. (Shanghai, China) miRNA was labeled using the miRNA complete labeling and hybridization kit (cat. no. p/n 5190-0456; Agilent Technologies, Inc.). The kit was used to hybridize each slide with Cy3-labeled RNA in a hybridization oven. Subsequent to hybridization, slides were washed and scanned using a Microarray Scanner (cat. no. G2565CA; Agilent Technologies, Inc.) using Feature Extraction software (version 10.7; Agilent Technologies, Inc.).

Raw data were normalized using the quantile algorithm in the GeneSpring software (version 12.6; Agilent Technologies, Inc.). The results of signal values are presented as means ± standard deviation. Student's t-test was used to identify differences between groups using the R package. Furthermore, the fold change was the ratio of the mean values of two comparative groups. miRNAs with fold differences ≥2.0 and P≤0.05 were considered to indicate a statistically significant difference.

mRNA expression analysis was performed using nine Agilent Whole Rat Genome Microarrays 4×44K (design ID:014879; Agilent Technologies, Inc.) at the National Engineering Center for Biochip, Shanghai Biotechnology Corp. Total RNA was amplified and labeled using the Low Input Quick Amp Labeling kit, One-Color (cat. no. 5190-2305; Agilent Technologies, Inc.). Labeled cRNA was purified using an RNeasy mini kit (cat. no. 74106; Qiagen GmbH, Hilden, Germany). The left process was similar to miRNA microarray. mRNAs with fold differences ≥2.0 and P≤0.05 were considered to indicate a statistically significant difference.

Five prediction tools: TargetMiner (http://www.isical.ac.in/~bioinfo_miu/targetminer20.htm), miRDB (http://mirdb.org/miRDB/index.html), microRNA (http://www.microrna.org/microrna/home.do), TarBase (http://diana.imis.athena-innovation.gr/DianaTools/index.php?r=tarbase/index), and RNA22 (https://cm.jefferson.edu/rna22/) quoted by miRBase database, were used to obtain the target genes of differentially expressed miRNAs. All of the tools were assembled into an online tool (http://www.shbio.com/analysis.html).

The predicted mRNA targets were then compared with experimentally determined mRNAs by microarray. Subsequently, according to Pearson's correlation coefficients and the associations of mRNAs in STRING (http://string-db.org/), a regulatory network was determined, which was comprised of 19 miRNAs and 98 mRNAs.

These 98 mRNAs were uploaded to Database for Annotation, Visualization and Integrated Discovery (version 6.7; https://david.ncifcrf.gov/) for Gene Ontology (GO) functional annotation. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway database (http://www.genome.jp/kegg/kegg1.html) was used to identify the enriched pathways of targets. Additionally, 19 miRNAs were subjected to a two-way unsupervised hierarchical clustering analysis using MultiExperiment Viewer software 4.7.4, a part of the TM4 Microarray software suite (Dana-Farber Cancer Institute, Boston, MA, USA) and ranked according to fold change and degrees in the network.

Data are presented as the means ± SD. Statistical difference (P≤0.05) was calculated by Student's t-test and correlations were evaluated by Pearson's correlation coefficients using the R package. The P-value <0.05 was considered statistically significant.

Sections of the IVC were stained with H&E and Masson's trichrome and observed under a light microscope. Clear differences were observed among the three groups (Fig. 2). With discontinuous vascular endothelial cells (ECs), numerous inflammatory cells infiltrated and entered the blood vessels, demonstrating a stable mixed thrombus following treatment in the DVT group. The staining results indicated the success of the SD DVT models.

To evaluate the role of miRNAs in thrombosis, the miRNA profiling in the DVT animal models were investigated, along with the sham-surgery and control rats (n=9) by microarray. Among 758 detectable miRNAs, 65 miRNAs (29 upregulated and 36 downregulated) significantly difference between the DVT and control groups, 34 miRNAs (14 upregulated and 20 downregulated) between the DVT and sham groups, and 48 miRNAs (26 upregulated and 22 downregulated) between the sham and control groups using a cut-off with an adjusted P≤0.05 and a fold-change of ≥2.0 (Fig. 3A). To exclude any effects of the surgical procedure, only 22 differentially expressed miRNAs in the overlapping areas (Fig. 3C) were focused upon, indicating differences between the DVT and the two other groups, but no difference between the control and sham groups. These 22 miRNAs were subjected to further analyses.

More than 41,000 rat genes and transcripts were investigated in the present study. Of them, 3,695 genes (2,028 upregulated and 1,667 downregulated) differed significantly between the DVT and control groups, 2,627 genes (1,568 upregulated and 1,059 downregulated) between the sham and control groups, and 1,071 genes (242 upregulated and 829 downregulated) between the DVT and sham groups using a cut off with an adjusted P≤0.05 and a fold-change of ≥2.0 (Fig. 3B). Similarly, 487 differentially expressed genes (DEGs) in overlapping areas (Fig. 3D) were selected for further analyses.

The 22 miRNAs were integrated to the experimentally determined 487 DEGs to obtain the miRNA-mRNA network (Fig. 4), which was composed of 19 miRNAs (6 upregulated and 13 downregulated) and 98 differentially expressed mRNAs (13 upregulated and 85 downregulated).

GO assigns biological processes (BP), cellular components (CC) and molecular function (MF). The BP analysis involved 83 GO terms; five of the top 10 were associated with adenylate cyclase activity, and two were associated with cell growth (Fig. 5A). Seven were found in CC, indicating that the DEGs were predominantly extracellular genes (45.66%) and plasma membrane genes (34.78%) (Fig. 5B). In seven MF annotations, the majority of genes belonged to binding activity genes (18.4%), while active protein genes represented 8.7% (Fig. 5C).

To evaluate the roles of the target genes in DVT, six specific terms (angiogenesis, cell proliferation, adhesion, inflammatory response, apoptosis and hypoxia) mediating vascular function were extracted from multiple levels within the GO hierarchy (Table I). Notably, the majority of these genes were closely associated with endothelial function (marked in bold in Table I) and the majority demonstrated a decreased expression level in DVT. For example, the expression levels of EC proliferative and anti-apoptosis genes, growth arrest specific 6 (GAS6), vascular endothelial growth factor B (VEGFB), the most well-known inducer of angiogenesis, and endothelial inflammation factor, Kruppel like factor 4 (KLF4) were reported to be reduced in atherosclerosis (11). In addition, adhesion-associated genes, including junctional adhesion molecule 2 (JAM2), which affects EC junctions (12), C-X-C motif chemokine ligand 12 (CXCL12), which mediates recruitment of inflammatory and thrombotic cells (13), and apolipoprotein L domain containing 1 (APOLD1) (14), a novel EC early response protein associated with hypoxia, were equally reduced in DVT.

KEGG pathway analysis demonstrated that four of the top 15 signal pathways were associated with cardiovascular disease, and three to metabolism. Among them, the following three had enriched gene numbers >3: dilated cardiomyopathy, vascular smooth muscle contraction and focal adhesion pathways (Fig. 5D).

The clustering analysis of the nine samples and 19 differentially expressed miRNAs revealed a distinct miRNA signature during DVT (Fig. 6A). The six upregulated miRNAs grouped together and the 13 downregulated miRNAs were divided into two categories, in which miR-133b-3p, miR-218a-5p and miR-204-5p were grouped together, while the remaining 10 miRNAs all gather in a second cluster.

To demonstrate the value of the 19 miRNAs in DVT, they were positioned according to the degree of co-expression from network (Table II) and fold change form profiling (Tables III and IV). The co-expression was ranked according to the degree of co-expression, the highest degree scored 19 points, and the lowest 1 point. The fold change score was ranked in the same way. The most differentially expressed upregulated miRNA received 6 points (for a total of 6 upregulated miRNAs) and downregulated miRNAs received 13 points (for a total of 13 downregulated miRNAs), and the lowest 1 point (data not shown). Bar charts of the rankings are presented in Fig. 6B and C. The top upregulated miRNA was miR-92a-3p, while miR-218a-5p was ranked first among the downregulated miRNAs.