Skip to main content
Download PDF

Diagnostic and prognostic potential of long non-coding RNA NORAD in patients with acute deep vein thrombosis and its role in endothelial cell function

Thrombosis Journal volume 22, Article number: 3 (2024) Cite this article

Abstract

Background

Deep venous thrombosis (DVT) is the common clinical cardiovascular disease, and easily develops into post-thrombotic syndrome (PTS). The study aimed to examine the clinical value of long non-coding RNA NORAD gene in the development of DVT and PTS. In vitro, the underlying mechanism was explored.

Methods

Serum levels of lncRNA NORAD gene in 85 DVT cases and 85 healthy individuals were tested. The role of lncRNA NORAD gene in human umbilical vein endothelial cells (HUVECs) proliferation, migration and inflammation was examined. The candidate downstream target gene was predicted via bioinformatic analysis. Gene ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were done for the function annotation and pathway enrichment.

Results

LncRNA NORAD gene was at high expression in the serum of DVT patients, it can distinguish DVT patients from healthy controls with the area under the curve of 0.919. Elevated expression of lncRNA NORAD gene in PTS patients was detected, DVT cases with high expression of lncRNA NORAD gene were more susceptible to PTS. LncRNA NORAD gene knockdown promoted HUVECs’ proliferation, migration while suppressing cell apoptosis and inflammation. MiR-93-5p served as a target of lncRNA NORAD gene, and its overexpression reversed the role of lncRNA NORAD gene in the biological function of HUVECs. The target genes of miR-93-5p were enriched in HIF-1 signaling, TGF-beta signaling and PI3K-Akt signaling, protein-protein interaction (PPI) network indicated STAT3, MAPK1 to be the key targets.

Conclusions

Upregulation of expression of lncRNA NORAD gene was a potential diagnostic biomarker for DVT and related to the development of PTS. LncRNA NORAD/miR-93-5p axis was involved in the progress of DVT through regulating endothelial cell function.

Background

Deep venous thrombosis (DVT) is the common clinical cardiovascular disease characterized by a thrombus in the lumen of a deep vein of legs [1]. Clinically, the stage of DVT can be divided into acute phase (within 14 days of onset), the subacute phase (15–30 days of onset) and the chronic phase (after 30 days of onset) [2]. Historically, DVT is diagnosed based on the primarily imaging modalities, including duplex ultrasound, helical CT scans, and venography [3]. Currently, D-dimer has been adopted in the diagnosis of DVT, but it can only be used as rule in marker for ultrasound investigations for DVT [3]. At present, the common treatment means include anti-coagulation, thrombolysis and surgical thrombectomy [4]. Post-thrombotic syndrome (PTS) is the most common sequela of DVT, occurring in up to 40% of DVT cases [5]. PTS is featured by swelling, pain, edema, venous ectasia, and skin induration of the affected limb [6]. Thereby, timely diagnosis and effective treatment are very important for the prognosis of DVT patients.

In recent years, non-coding RNAs have gradually become a hot topic in medical research, especially microRNA (miRNA), long non-coding RNA (lncRNA) and circulating RNA (circRNA). LncRNAs are widely present in various human tissues and have a wide range of gene regulatory functions. In recent years, a large number of studies have shown that lncRNA has regulatory effects on cardiovascular diseases, malignant tumors, nervous system diseases, endocrine diseases, etc. [7]. With the improvement of detection methods, the discovery of serum lncRNA provides a new class of biomarkers for the diagnosis of a variety of diseases [7]. Dysregulation of the expression of lncRNAs has been detected in DVT patients, such as nuclear enriched abundant transcript 1 (NEAT1) and X inactive specific transcript (XIST) [8, 9]. In fact, a number of lncRNAs have been identified to be closely related to endothelial injury, which is the major risk factor for the progress of DVT [10, 11]. For example, elevated expression of lncRNA XIST gene was detected in the plasma of DVT patients, the activity restriction and apoptosis of human umbilical vein endothelial cells (HUVECs) caused by lncRNA XIST gene are the mechanisms involved in DVT progression [9]. The results indicate that these dysregulated expression of lncRNAs have the potential as a marker of DVT, and are involved in the pathogenesis of disease.

The non-coding RNA activated by DNA damage (NORAD) is a novel lncRNA, its role in vascular endothelial cell injury, atherosclerosis, and coronary artery disease has been recently presented [12]. In a study about atherosclerosis (AS), lncRNA NORAD gene was determined to be at high expression in both oxidized low-density lipoprotein (ox-LDL) induced HUVECs and high fat diet (HFD)-treated mice, lncRNA NORAD gene knockdown was suggested to relieve vascular endothelial cell injury [12]. In another in vivo study, increased NORAD was identified in atherosclerotic mouse aortas, which was related to inflammation, oxidative stress and endothelial dysfunction in atherosclerotic mouse aortas [13]. In consideration of the important role of in the pathogenesis of DVT, the role of lncRNA NORAD gene in the development of DVT attracted our attention. Therefore, the present study was designed to determine the expression changes and contribution of lncRNA NORAD gene in the diagnosis for acute DVT patients. Moreover, the prognostic value of lncRNA NORAD gene in the occurrence of PTS was examined based on the follow-up results. In addition, the possible mechanism of lncRNA NORAD gene in the development of DVT was further explored in vitro.

Methods

Study population

85 cases with acute lower extremity DVT were enrolled in the present study who admitted to Taihe Hospital, Affiliated Hospital of Hubei University of Medicine from January 2021 to December 2022. Another 85 cases who were suspected DVT but actually DVT-negative according to the Duplex ultrasound examination were selected as the control group. This study was conducted under the supervision and approval of the Ethics Committee of Taihe Hospital, Affiliated Hospital of Hubei University of Medicine.

Inclusion criteria of DVT cases: (1) aged from 18 to 65 years old; (2) patients were informed and voluntarily agreed to participate in the study; (3) patients had clinical symptoms such as swelling and pain in the affected limb; (4) central or whole-limb DVT was diagnosed based on the lower extremity venous Duplex ultrasound examination; (5) time of onset was less than 14 days; (6) all patients were unilateral first disease. Exclusion criteria: (1) poor body tolerance; (2) patients who cannot undergo catheterization thrombolytic therapy; (3) there is coagulation dysfunction; (4) patient was complicated with mental illness and could not cooperate to complete this study. All patients were followed up for 18 months to record the development of PTS. PTS was scored according to the International Society on Thrombosis Haemostasis (ISTH) guidance, patients were diagnosed with PTS if the Villalta score was at least 5 [14].

Demographics and laboratory data

Demographic data including age, gender, body mass index (BMI), medical history (such as hypertension, diabetes mellitus, hyperlipidemia), and smoking habits were recorded in hospitalization. The blood test was done using an automatic CBC analysis device (Beckman Coulter Inc., CA, USA) for the collection of laboratory data within 24 h of admission. Blood samples were initially centrifuged at 1000× g for 15 min and the resulted supernatant was centrifuged again at 2500× g for 15 min for serum sample collection. The serum samples were transferred into frozen tubes and stored at − 80 °C.

Cell culture and transfection

HUVECs were gained from the American Typical Culture Conservatory (ATCC), which were cultured in DMEM maintained in a 37 °C, 5% CO2 incubator. 10% fetal bovine serum and 10% endothelial cell growth supplement were added to the medium. Small interfering (si) RNA (si-NORAD) sequence of lncRNA NORAD gene and its negative control (si-NC), and overexpression plasmid of pcDNA3.1-NORAD were provided by GenePharma Co, while miR-93-5p mimic, mimic-NC, miR-93-5p inhibitor and inhibitor-NC were obtained from the RIBOBIO Co. When cells grew to 80% confluence, the cell transfection was performed using Lipofectamine 3000 (Invitrogen, USA). After 5 h of culture, a new medium was replaced.

RNA extraction and real-time quantitative reverse transcription PCR (RT-qPCR)

Clinical serum samples and HUVECs were used for the total RNA extraction using Trizol LS reagent (Invitrogen, USA). After purity identification, RNA reverse transcription was performed by Fastking gDNA Dispelling RT SuperMix Kit or miRcute Plus miRNA First Stand cDNA Kit (TIANGEN, Beijing, China). SuperReal PreMix Plus (SYBR Green) or miRcute Plus miRNA qPCR Kit (SYBR Green, TIANGEN, Beijing, China) were applied for qPCR on ABI PRISM 7300 (ABI)., while the primer sequences were designed and synthesized by RIBOBIO Co. The relative expression of NORAD and miR-93-5p was calculated by 2−ΔΔCt method. GAPDH was used as the internal reference of lncRNA NORAD gene while U6 was for the internal reference of miR-93-5p, because they were stably expressed and proven to be suitable internal controls. Relative quantities of gene expression levels were normalized to the reference genes (GAPDH or U6) and then normalized to the control group.

Cell proliferation

100 µl HUVECs resuspension was plated into a 96-well plate. Daily cell viability detection was performed for three days consecutively. 10 µl cell counting kit-8 (CCK-8, Dojindo, Japan) was added to the well and incubated for 2 h. The optical density (OD) at 450 nm was tested.

Cell apoptosis

After cell transfection, cells in each group were collected to detect the apoptotic rate using Annexin V-FITC Apoptosis Detection Kit. Specifically, HUVECs were resuspended and incubated with 5 µl Annexin V-FITC mixed with 5 µl propidium iodide (PI) for 5 min in the dark. Finally, the cell apoptotic rate was detected on a flow cytometer.

Cell migration

Cell migration was measured using Trabswell (Corning, USA). The resuspended HUVECs were seeded into the upper chamber of the Transwell, while the lower chamber was filled with 500 µl of DMEM. After incubation for 24 h, the cells migrated into the lower chamber were stained with methanol and crystal violet. After a water rinse, the migrated cells were counted under a light microscope.

Enzyme-linked immunosorbent assay (ELISA)

The concentration of inflammatory cytokines including (TNF)-α, IL (interleukin)-6 (IL-6), and IL-1β were quantified by a commercially available ELISA Kit from Abcam (USA). In brief, the diluted samples and protein standards were added to the plate, and incubated with HRP-coupled detection antibodies. Then the termination solution was added followed by detection of absorbance at 450 nm.

Nuclear/cytoplasmic fractionation assay

The nuclear/cytoplasmic fractionation assay was done using the commercial PARIS kit (Invitrogen, USA). The collected HUVECs were incubated with 450 µl cell grading buffer on ice. After centrifugation at 1200 rpm for 5 min, the upper cytoplasmic RNA was collected. The precipitate fraction was collected and added to the NER regent. After centrifugation, the nuclear RNA was collected. Then RT-qPCR was performed for the detection of OIP5-AS1 expression in the nucleus and cytoplasm via using U6 and GAPDH as the internal control.

Prediction and verification of target binding

The target miRNAs with potential binding sites for NORAD were predicted through LncBook 2.0 and Starbase 3.0 (ENCORI) software. GSE173461 dataset was applied for the extraction of miRNAs related to DVT [15], and key miRNAs were identified by the overlapping in both LncBook 2.0 (https://ngdc.cncb.ac.cn/lncbook) and Starbase 3.0 ((http://starbase.sysu.edu.cn/) datasets. Prediction of miR-93-5p was performed based on TargetScan (http://www.targetscan.org/vert_72/), miRDB (http://www.mirdb.org/) and GeneCard database (http://www.genecards.org/). Then Venn diagram was performed in the online analysis toll Bioinformatics (www.bioinformatics.com) to show the number of differentially expressed genes in the database.

Luciferase reporter assay

The target fragments containing wild type (WT) or mutant (MT) binding sites in the 3’UTR of NORAD were amplified by PCR and subcloned into the psiCHECK2 luciferase reporter vector. Then luciferase reporter assay was performed in HUVECs, and the above plasmid was co-transfected with miR-93-5p mimic or miR-93-5p inhibitor using Lipofectamine 2000, respectively. After culturation for 48 h, the cells were lysed and luciferase activity was detected through the luciferase reporting system kit (Promega, USA).

Bioinformatics analysis

The overlapping target genes were mapped into the protein-protein interaction (PPI) networks via STRING, and the highest-confidence interaction score of more than 0.9 was used as the cutoff. Then Gene ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were done for the gene function annotation and pathway enrichment.

Statistical analysis

Three independently repeated experiments were done for each assay. Data were checked for normality via the Kolmogorov–Smirnov (K-S) normality test. The continuous variables with normal distribution were presented as mean and standard deviation (SD), which were compared between groups via applying student’s t-test or one-way ANOVA. All data analyses were completed on SPSS 23.0 or Graphpad prism 7.0 software. The receiver operator characteristic (ROC) curve was drawn for the diagnostic value analysis of lncRNA NORAD gene in DVT, and the area under the curve (AUC) was calculated for the evaluation of the diagnostic potential. Moreover, cox regression analysis and Kaplan-Meier were deployed for the prognostic value assessment. P < 0.05 was set as the cutoff value of significance.

Results

Demographic and laboratory data of the subjects

The clinical basic information of the study groups was presented in Table 1. No significant difference appeared in terms of age, gender, BMI, hypertension, diabetes mellitus, hyperlipidemia and smoking (P > 0.05). Almost all coagulation indicators including prothrombin time (PT), antithrombin (AT), international normalized ratio (INR), fibrinogen (FIB) and D-dimer significantly differed from the case and control groups (P < 0.05), except for thrombin time (TT). For DVT patients, their duration symptoms before diagnosis, varicose veins at diagnosis and DVT location were also recorded in Table 1.

Table 1 Baseline information of the study objects
Full size table

Expression change and diagnostic value assessment of serum NORAD in DVT patients

As shown by qRT-PCR analysis results, lncRNA NORAD gene was at high expression in the serum of DVT patients (Fig. 1A, P < 0.001). In addition, the correlation of lncRNA NORAD gene with D-dimer concentration was also evaluated. Based on the Pearson’s correlation analysis results, the expression of lncRNA NORAD gene showed a prominent correlation with D-dimer concentration in all participants (r = 0.809, P < 0.001, Fig. 1B). Moreover, its diagnostic potential was evaluated through drawing ROC curve (Fig. 1C). It was observed that the expression of lncRNA NORAD gene can distinguish DVT patients from healthy controls, with the AUC of 0.919. The maximum value of the Yoden index was 0.718 with the cutoff value at 1.44. The sensitivity and specificity were 72.90% and 98.8%, respectively.

Fig. 1
figure 1

Expression changes and clinical value of lncRNA NORAD gene in DVT. (A) High serum NORAD levels in the serum of DVT patients. Data were expressed as mean and SD. **** P < 0.0001. (B) Expression of lncRNA NORAD gene showed prominent correlation with D-dimer concentration in all participants. (C) ROC curve of lncRNA NORAD gene for distinguishing DVT

Full size image

Clinical value of NORAD in predicting PTS onset of DVT patients

According to the follow-up information, a total of 28 cases developed into PTS during 18 months follow-up time. Based on the univariate cox regression analysis results, a total of seven clinical indicators presented significant levels, namely varicose veins, duration symptoms, D-dimer, hyperlipidemia, BMI, gender and age (Fig. 2A, P < 0.05). These seven indicators that showed significant level were further introduced into the multiple Cox regression analysis model. Interestingly, qRT-PCR results indicated the elevated expression of lncRNA NORAD gene in PTS patients (Fig. 2B), which was also introduced in the multiple Cox regression analysis. As displayed in Fig. 2C, D-dimer (HR = 3.427, 95% CI = 1.471–7.980), age (HR = 2.577, 95% CI = 1.019–6.516) and lncRNA NORAD gene (HR = 3.363, 95% CI = 1.172–9.650) were independently influence factors related to the development of PTS for DVT patients. Moreover, Kaplan-Meier plot was drawn to more intuitively present the predictive value of lncRNA NORAD gene in PTS (Fig. 2D). It was seen that DVT cases with high levels of lncRNA NORAD gene were more susceptible to PTS (P = 0.027).

Fig. 2
figure 2

Clinical value of NORAD in predicting PTS. (A) Univariate cox regression analysis to assess the association of clinical indicators with PTS. (B) Expression of lncRNA NORAD gene in the serum of PTS cases. **** P < 0.0001. (C) Cox regression analysis indicates independent influence factors related to the onset of PTS. (D) Kaplan-Meier plot of lncRNA NORAD gene in the onset PTS

Full size image

Role verification of NORAD in cell functions of HUVECs

To excavate the potential mechanisms of NORAD in DVT, its subcellular localization was accomplished and lncRNA NORAD gene was found to be mainly located in the cytoplasm of HUVECs (Fig. 3A). Levels of lncRNA NORAD gene were mediated via cell transfection to investigate its role in DVT. As displayed in Fig. 3B, si-NORAD transfection contributed to the downregulation of lncRNA NORAD gene while pcDNA3.1-NORAD led to the levels’ upregulation (P < 0.001). Besides, the function experiments determined that lncRNA NORAD gene knockdown promoted HUVECs’ proliferation, migration while suppressing cell apoptosis, but lncRNA NORAD gene upregulation brought an adverse effect (Fig. 3C–E). Similarly, inflammatory cytokines namely TNF-α, IL-1β and IL-6 were also remarkably diminished by lncRNA NORAD gene knockdown, which was aggravated by lncRNA NORAD gene upregulation (Fig. 3F).

Fig. 3
figure 3

Role of lncRNA NORAD gene in cell functions of HUVECs. (A) Subcellular localization of lncRNA NORAD gene in HUVECs. (B) Expression changes of lncRNA NORAD gene in HUVECs after cell transfection. (C) CCK-8 results of HUVECs after cell transfection. (D) Number of migrated cells after cell transfection. (E) Apoptotic cell percentage after cell transfection. (F) Concentration of inflammatory cytokines in HUVECs after cell transfection. Data were expressed as mean and SD. *** means P < 0.001

Full size image

Target miRNAs of lncRNA NORAD gene

The predicted target miRNAs with potential binding sites for lncRNA NORAD gene were obtained through LncBook 2.0 and Starbase 3.0 (ENCORI) software. As shown in Fig. 4A, 172 miRNAs were predicted. Moreover, GSE173461 dataset was used for the extraction of miRNAs related to DVT that overlapped in both LncBook 2.0 and Starbase 3.0 datasets. Finally, a total of 8 miRNAs were identified, including miR-324-3p, miR-150-5p, miR-30c-5p, miR-30e-5p, miR-378a-3p, miR-642a-3p, miR-92a-3p, miR-93-5p. Furthermore, the expression changes of these night miRNAs were verified in the clinical serum samples. Among the eight miRNAs, only two were significantly upregulated in the serum of DVT patients, namely miR-324-3p and miR-150-5p (Fig. 4B, C, P < 0.001). The expression changes of miR-30c-5p, miR-30e-5p and miR-378a-3p were not significant between the case and control groups (Fig. 4D–F, P > 0.05). As displayed in Fig. 4H–J, miR-642a-3p, miR-92a-3p, miR-93-5p were all significantly downregulated in DVT patients, in which miR-93-5p expression changes were the most significant (P < 0.001). Thus miR-93-5p was selected for further mechanism exploration.

Fig. 4
figure 4

Target miRNAs of lncRNA NORAD gene. (A) Overlapping target miRNAs of lncRNA NORAD gene in LncBook 2.0 and Starbase 3.0 (ENCORI) datasets. SE173461 dataset was used for the extraction of miRNAs related to DVT that overlapped in both LncBook 2.0 and Starbase 3.0 datasets. (B–J) Levels of eight overlapping miRNAs in the serum of DVT patients calculated by qRT-PCR. Data were expressed as mean and SD. * P < 0.05; **** P < 0.0001

Full size image

NORAD serves as competing endogenous RNA (ceRNA) of miR-93-5p

Target miRNAs of lncRNA NORAD gene was subsequently explored. Figure 5A shows the target binding sites of lncRNA NORAD gene with miR-93-5p. The miR-93-5p mimic typically decreased the luciferase activity of NORAD-WT, while the miR-93-5p inhibitor significantly increased the luciferase activity of lncRNA NORAD gene (P < 0.05, Fig. 5B), but neither of them had a significant effect on the luciferase activity of NORAD-MUT (P > 0.05, Fig. 5B). In HUVECs, si-NORAD transfection was accompanied with the upregulation of miR-93-5p, while lncRNA NORAD gene upregulation led to the downregulation of miR-93-5p (Fig. 5C).

Fig. 5
figure 5

LncRNA NORAD gene serves as ceRNA competitively binds miR-93-5p. (A) The target binding sites of lncRNA NORAD gene with miR-93-5p. (B) Luciferase activity of cells transfected with different sequence. (C) MiR-93-5p levels in HUVECs after mediating expression of lncRNA NORAD gene. Data were expressed as mean and SD. *** P < 0.001 compared with the control/untreated group

Full size image

MiR-93-5p reversed the role of NORAD in biological function of HUVECs

The co-regulatory function of lncRNA NORAD gene and miR-93-5p was distinguished in HUVECs. As seen in Fig. 6A, pcDNA3.1-NORAD transfection decreased the levels of miR-93-5p, which was greatly restored by miR-93-5p mimic transfection (Fig. 6A). In addition, lncRNA NORAD gene upregulation-induced inhibition of cell viability and migration was also reversed by miR-93-5p overexpression (Fig. 6B, C). Similarly, the promotion of cell apoptosis induced by lncRNA NORAD gene was also restored by miR-93-5p (Fig. 6D). What’s more, lncRNA NORAD gene stimulated the release of inflammatory cytokines, including TNF-α, IL-1β and IL-6. But the influence was back-spined by miR-93-5p (Fig. 6E).

Fig. 6
figure 6

miR-93-5p reversed the role of lncRNA NORAD gene in biological function of HUVECs. (A) miR-93-5p levels in HUVECs after cell transfection. (B) Cell viability of HUVECs after cell transfection. (C) Cell migration of HUVECs after cell transfection. (D) Cell apoptosis of HUVECs after cell transfection. (E) Concentrations of inflammatory cytokines in HUVECs after cell transfection. Data were expressed as mean and SD. *** P < 0.001 compared with the untreated group; ### P < 0.001 compared with pcDNA3.1-NORAD group

Full size image

Functional and pathway enrichment analysis of predicted target genes of miR-93-5p by GO and KEGG

Prediction of miR-93-5p was performed based on TargetScan, miRDB and GeneCard database. As the Venn diagram shown, a total of 124 genes were overlapped (Fig. 7A). GO terms enabled the function enrichment analysis, including three items of biological process (BP), cellular component (CC), and molecular function (MF). As seen in Fig. 7B, the target genes are mainly enriched in regulation of angiogenesis, cardiac muscle tissue development, external side of plasma membrane, RNA polymerase II transcription regulator complex, SMAD binding, cytokine receptor binding and so on. Furthermore, based on the KEGG analysis, HIF-1 signaling, TGF-beta signaling and PI3K-Akt signaling were mainly enriched (Fig. 7C).

Fig. 7
figure 7

Functional and pathway enrichment analysis of predicted target genes of miR-93-5p. (A) Venn diagram of miR-93-5p target genes based on TargetScan, miRDB and GeneCard database. (B) Go results of biological process (BP), cellular component (CC), and molecular function (MF). (C) Pathway enrichment results by KEGG. (D) PPI networks among target genes mapped in STRING

Full size image

Moreover, the PPI networks among target genes were mapped in STRING. As seen in Fig. 7D, a PPI network of 124 nodes and 68 edges was constructed, with the P value less than e− 16. The top 10 hub genes were presented in Supplementary Table based on the degree of connectivity, namely STAT3, MAPK1, PIK3R1, ESR1, CREB1, HIF1A, JAK1, SMAD5, BMPR2 and CCND1.

Discussion

Deep vein thrombosis (DVT) is a common peripheral vascular disease in clinical practice, with an annual incidence of 0.1–0.27% [16]. The physiological basis of DVT includes vascular endothelium damage, slow blood flow velocity and blood hypercoagulability [17]. Recent studies have supported that lncRNA has regulatory effects on cell proliferation, migration, apoptosis and other functions [16]. Moreover, the regulatory role of lncRNAs in vascular endothelial injury is almost certain [16]. LncRNA NORAD gene is a vascular endothelial cell injury-related lncRNA. In AS studies, lncRNA NORAD gene was indicated to stimulate vascular endothelial cell injury through mediating cell inflammation and oxidative stress [12, 13]. Based on the present qRT-PCR results, lncRNA NORAD gene was determined to be at high expression in the serum of DVT patients. Clinically, serum levels of lncRNA NORAD gene can distinguish DVT patients from healthy controls. The findings indicated the diagnostic potential of lncRNA NORAD gene in DVT. It is known that PTS is a long-term complication of DVT, and the incidence of PTS within 2 years is 20–50%, even if DVT patients receive standardized anticoagulant therapy [18]. In the present study, all DVT patients were followed up for 18 months to record the occurrence of PTS. It can be seen that approximately 33% of patients developed into PTS, which was consistent with the previous reported incidence [19]. Moreover, qRT-PCR results indicated the elevated expression of lncRNA NORAD gene levels in serum of PTS patients. Based on the multiple Cox regression analysis results, lncRNA NORAD gene was independently related to the development of PTS during the follow-up time. Collectively, serum expression of lncRNA NORAD gene had considerable diagnostic and prognostic significance in discriminating DVT patients and healthy people. In addition, our present results also indicated the close relationship of age and D-dimer with the development of PTS, which was consistent with the previous evidence [20, 21].

Vascular endothelial injury is one of the important mechanisms of DVT [22]. Thus, HUVECs were applied for the cell function experiments. It was found that lncRNA NORAD gene knockdown promoted HUVECs’ proliferation, migration while suppressing cell apoptosis. Consistently, under hypoxic conditions, lncRNA NORAD gene knockdown was determined to promote HUVECs’ migration and tube formation [23]. In ox-LDL- induced HUVECs models, lncRNA NORAD gene knockdown contributed to the recovery of cell apoptosis induced by ox-LDL [12]. It is known that vascular endothelial cell inflammation contributes to the development of DVT [24]. Based on our present cell experiment results, inflammatory cytokines including TNF-α, IL-1β and IL-6 were also remarkably diminished by lncRNA NORAD gene knockdown in HUVECs. Collectively, it was concluded that lncRNA NORAD gene knockdown may protect against DVT through improving vascular endothelial injury and inflammation.

MiRNAs serve as targets of lncRNAs that degrade or inhibit the translation of target genes [25]. In DVT, the dysregulation and involvement of miRNAs have been widely reported [26, 27]. In the current study, miR-93-5p was identified to the the candidate target of NORAD in DVT based on bioinformatic analysis and luciferase reporter assay. Moreover, in clinical serum samples, downregulated miR-93-5p was detected in DVT patients. Thus, its involvement in the role of lncRNA NORAD gene was explored in HUVECs via cell transfection. The findings indicated that miR-93-5p reversed the role of lncRNA NORAD gene in biological function of HUVECs, lncRNA NORAD gene serves as ceRNA of miR-93-5p in DVT. Consistently, in mice models with myocarditis, the development of cardiac microvascular endothelial injury was accompanied by the downregulation of miR-93-5p [28]. The further rescue experiment results indicated that the upregulation of miR-93-5p can alleviate cardiac microvascular endothelial injury via suppressing inflammatory response [28]. In the sepsis-induced acute kidney injury mouse model, the involvement of miR-93-5p was determined to be associated with the endothelial protection of the endothelial progenitor cell (EPC)-derived extracellular vesicles [29]. All evidence supported the crucial role of miR-93-5p in DVT.

Accumulating evidence demonstrates that miRNAs and lncRNAs interact to regulate target genes and further mediate the downstream signaling pathways and thus modulate disease progression [27]. Therefore, the target genes of miR-93-5p were predicted and subsequently enriched by the GO and KEGG. According to the GO analysis results, the functions were mainly enriched in angiogenesis, cardiac muscle tissue development, external side of plasma membrane, RNA polymerase II transcription regulator complex, SMAD binding, cytokine receptor binding and so on. As reported, angiogenesis is the key component of DVT resolution and restitution of vascular patency after thrombosis [30, 31]. It was concluded that lncRNA NORAD gene played an important role in angiogenesis in function, which might be its protective mechanism in DVT and followed PTS. In addition, HIF-1 signaling, TGF-beta signaling and PI3K-Akt signaling were enriched by KEGG analysis. HIF-1 pathway was known to stimulate coagulopathy and recruitment of inflammatory cytokines, which was related to the onset and development of DVT [32, 33]. In the development of DVT, overexpression of TGF-β was detected, indicating its important role in disease progression [34]. The role of TGF-β signaling pathway in venous calcification was reported, and venous calcification was a further adverse progression after PTS [35]. In addition, TGF-β signaling was determined to be involved in the occurrence of thrombophlebitis [36]. The phosphoinositide 3-kinase (PI3K)/AKT signaling pathway was an important contributor in inflammatory response [37]. In DVT mice, the activation of PI3K/AKT signaling was determined, which was related to endothelial cell injury and inflammation [38]. These findings explained the possible involvement mechanism of NORAD/miR-93-5p in the progress of DVT. Moreover, PPI network indicated STAT3, MAPK1 to be the key targets, which were all involved in the development of DVT [39].

Although the current findings provide the direction for our later research on the mechanism of lncRNA NORAD gene in DVT, the key genes and downstream signaling pathways did not verified. In addition, an external validation of expression of lncRNA NORAD gene in a DVT cohort was necessary, which was a limitation of our study. The present findings should be verified in another study population with larger sample size. Besides, we used ISTH guidance for PTS diagnosis, but there was no clear guidelines and diagnostic criteria for PTS currently. So the role of lncRNA NORAD gene in PTS required further verification. Moreover, in vivo studies need to be considered to validate the role of lncRNA NORAD gene in DVT today.

Conclusions

In summary, upregulation of lncRNA NORAD gene was identified to be a potential diagnostic biomarker for DVT, moreover, it is related to the development of PTS. In vitro, lncRNA NORAD gene may aggravate the vascular endothelial injury via sponging miR-93-5p. The present findings expand new perspectives on the diagnosis and mechanism exploration of DVT.

Data availability

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Abbreviations

ATCC:

American Typical Culture Conservatory

AUC:

Area under the curve

BP:

Biological process

CC:

Cellular component

circRNA:

Circulating RNA

DVT:

Deep venous thrombosis

ELISA:

Enzyme-Linked immunosorbent assay

EPC:

Endothelial progenitor cell

GO:

Gene ontology

KEGG:

Kyoto Encyclopedia of Genes and Genomes

lncRNA:

Long non-coding RNA

MF:

Molecular function

miRNA:

MicroRNA

MT:

Mutant

PI:

Propidium iodide

PI3K:

Phosphoinositide 3-kinase

PTS:

Post-thrombotic syndrome

ROC:

Receiver operator characteristic

RT-qPCR:

Real-time quantitative reverse transcription PCR

SD:

Standard deviation

si-NC:

Negative control siRNA

si-NORAD:

NORAD small interfering (si) RNA

WT:

Wild type

HUVECs:

Human umbilical vein endothelial cells

References

  1. Duffett L. Deep venous Thrombosis. Ann Intern Med. 2022;175:ITC129–44.

    Article  PubMed  Google Scholar 

  2. Tang J, Wen Z. Color Doppler diagnosis of Abdominal and Peripheral Vascularity. People’s Medical Publishing House; 2007.

  3. Hou H, Ge Z, Ying P, Dai J, Shi D, Xu Z, Chen D, Jiang Q. Biomarkers of deep venous Thrombosis. J Thromb Thrombolysis. 2012;34:335–46.

    Article  CAS  PubMed  Google Scholar 

  4. Jin J, Wang C, Ouyang Y, Zhang D. Elevated mir-195-5p expression in deep vein Thrombosis and mechanism of action in the regulation of vascular endothelial cell physiology. Exp Ther Med. 2019;18:4617–24.

    CAS  PubMed  PubMed Central  Google Scholar 

  5. Visona A, Quere I, Mazzolai L, Amitrano M, Lugli M, Madaric J, Prandoni P. European Society of Vascular M: post-thrombotic syndrome. Vasa. 2021;50:331–40.

    Article  PubMed  Google Scholar 

  6. Kahn SR. The post-thrombotic syndrome. Hematol Am Soc Hematol Educ Program. 2016;2016:413–8.

    Article  Google Scholar 

  7. Lou Z, Zhu J, Li X, Li X, Du K, Wang B, Zhang F, Zhang X. LncRNA Sirt1-AS upregulates Sirt1 to attenuate aging related deep venous Thrombosis. Aging. 2021;13:6918–35.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Wang S, Wang F, Ren J, Yang H. LncRNA NEAT1 promotes vascular endothelial cell dysfunction via miR-218-5p/GAB2 and serves as a diagnostic biomarker for deep vein Thrombosis. Clin Appl Thromb Hemost. 2023;29:10760296231179447.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Cao G, Zhou H, Wang D, Xu L. Knockdown of lncRNA XIST ameliorates IL-1beta-Induced apoptosis of HUVECs and Change of Tissue Factor Level via miR-103a-3p/HMGB1 Axis in deep venous Thrombosis by regulating the ROS/NF-kappaB signaling pathway. Cardiovasc Ther. 2022;2022:6256384.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Guo Y, Yang JH, He Y, Zhou HF, Wang Y, Ding ZS, Jin B, Wan HT. Protocatechuic aldehyde prevents ischemic injury by attenuating brain microvascular endothelial cell pyroptosis via lncRNA. Xist Phytomedicine. 2022;94:153849.

    Article  CAS  PubMed  Google Scholar 

  11. Qian W, Zheng ZQ, Nie JG, Liu LJ, Meng XZ, Sun H, Xiao FM, Kang T. LncRNA SNHG12 alleviates hypertensive vascular endothelial injury through miR-25-3p/SIRT6 pathway. J Leukoc Biol. 2021;110:651–61.

    Article  CAS  PubMed  Google Scholar 

  12. Kai H, Wu Q, Yin R, Tang X, Shi H, Wang T, Zhang M, Pan C. LncRNA NORAD promotes vascular endothelial cell Injury and Atherosclerosis through suppressing VEGF gene transcription via enhancing H3K9 deacetylation by recruiting HDAC6. Front Cell Dev Biol. 2021;9:701628.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Fu DN, Wang Y, Yu LJ, Liu MJ, Zhen D. Silenced long non-coding RNA activated by DNA damage elevates microRNA-495-3p to suppress atherosclerotic plaque formation via reducing Kruppel-like factor 5. Exp Cell Res. 2021;401:112519.

    Article  CAS  PubMed  Google Scholar 

  14. Kahn SR, Partsch H, Vedantham S, Prandoni P, Kearon C. Subcommittee on Control of Anticoagulation of the S, Standardization Committee of the International Society on T, Haemostasis: definition of post-thrombotic syndrome of the leg for use in clinical investigations: a recommendation for standardization. J Thromb Haemost. 2009;7:879–83.

    Article  CAS  PubMed  Google Scholar 

  15. Chu C, Wang B, Zhang Z, Liu W, Sun S, Liang G, Zhang X, An H, Wei R, Zhu X, et al. miR-513c-5p suppression aggravates pyroptosis of endothelial cell in deep venous Thrombosis by promoting Caspase-1. Front Cell Dev Biol. 2022;10:838785.

    Article  PubMed  PubMed Central  Google Scholar 

  16. Yilmaz MB, Durdag E, Egemen E, Coskun B, Emmez H, Kurt G, Ilgit E. Role of vena cava inferior filter on neurosurgical deep venous Thrombosis. Turk Neurosurg. 2012;22:269–73.

    PubMed  Google Scholar 

  17. Zhi L, Feng W, Liang J, Zhong Q, Ren L, Ma J, Yao S, Liqiang Zhi WF. Jingqi Liang contributed equally to this w: the Effect of Common variants in SLC44A2 on the contribution to the risk of deep Cein Thrombosis after orthopedic Surgery. J Atheroscler Thromb. 2021;28:293–303.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Erol ME, Ozyalcin S, Tekin KA, Diken AI, Yalcinkaya A, Unal EU. Factors affecting recanalization in Femoropopliteal Deep vein Thrombosis. Clin Appl Thromb Hemost. 2023;29:10760296231173409.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Hu G, Wang J. Percutaneous endovenous intervention versus anticoagulation in the treatment of lower extremity deep vein Thrombosis: a systematic review and meta-analysis. Ann Transl Med. 2022;10:1018.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Ariyanti F, Sukrisman L, Antono D, Harimurti K. The risk for post-thrombotic syndrome of subjects with deep vein Thrombosis in an Indonesian referral hospital: a retrospective cohort study. Thromb J. 2023;21:38.

    Article  PubMed  PubMed Central  Google Scholar 

  21. Stain M, Schonauer V, Minar E, Bialonczyk C, Hirschl M, Weltermann A, Kyrle PA, Eichinger S. The post-thrombotic syndrome: risk factors and impact on the course of thrombotic Disease. J Thromb Haemost. 2005;3:2671–6.

    Article  CAS  PubMed  Google Scholar 

  22. McLendon K, Goyal A, Attia M. Deep venous Thrombosis risk factors. StatPearls. Treasure Island (FL) ineligible companies. Disclosure: Amandeep Goyal declares no relevant financial relationships with ineligible companies. Disclosure: Maximos Attia declares no relevant financial relationships with ineligible companies.; 2023.

    Google Scholar 

  23. Zhao X, Wei X, Wang X, Qi G. Long non–coding RNA NORAD regulates angiogenesis of human umbilical vein endothelial cells via miR–590–3p under hypoxic conditions. Mol Med Rep. 2020;21:2560–70.

    CAS  PubMed  PubMed Central  Google Scholar 

  24. Ma J, Li X, Wang Y, Yang Z, Luo J. Rivaroxaban attenuates Thrombosis by targeting the NF-kappaB signaling pathway in a rat model of deep venous thrombus. Int J Mol Med. 2017;40:1869–80.

    CAS  PubMed  PubMed Central  Google Scholar 

  25. Paraskevopoulou MD, Hatzigeorgiou AG. Analyzing MiRNA-LncRNA interactions. Methods Mol Biol. 2016;1402:271–86.

    Article  CAS  PubMed  Google Scholar 

  26. Pan Z, Zhang Y, Li C, Yin Y, Liu R, Zheng G, Fan W, Zhang Q, Song Z, Guo Z, et al. MiR-296-5p ameliorates deep venous Thrombosis by inactivating S100A4. Exp Biol Med (Maywood). 2021;246:2259–68.

    Article  CAS  PubMed  Google Scholar 

  27. Han J, Hao W, Ma Y, Hou Y. MiR-128-3p promotes the progression of deep venous Thrombosis through binding SIRT1. Phlebology 2023:2683555231190268.

  28. Ma SX, Bai ZF, Wang W, Wu HY. Effects of microrna-93 on mouse cardiac microvascular endothelial cells injury and inflammatory response by mediating SPP1 through the NF-KappaB pathway. J Cell Biochem. 2019;120:2847–58.

    Article  CAS  PubMed  Google Scholar 

  29. He Z, Wang H, Yue L. Endothelial progenitor cells-secreted extracellular vesicles containing microRNA-93-5p confer protection against sepsis-induced acute kidney injury via the KDM6B/H3K27me3/TNF-alpha axis. Exp Cell Res. 2020;395:112173.

    Article  CAS  PubMed  Google Scholar 

  30. Kellermair J, Redwan B, Alias S, Jabkowski J, Panzenboeck A, Kellermair L, Winter MP, Weltermann A, Lang IM. Platelet endothelial cell adhesion molecule 1 deficiency misguides venous thrombus resolution. Blood. 2013;122:3376–84.

    Article  CAS  PubMed  Google Scholar 

  31. Altmann J, Sharma S, Lang IM. Advances in our understanding of mechanisms of venous thrombus resolution. Expert Rev Hematol. 2016;9:69–78.

    Article  CAS  PubMed  Google Scholar 

  32. Wang X, Sundquist K, Svensson PJ, Rastkhani H, Palmer K, Memon AA, Sundquist J, Zoller B. Association of recurrent venous thromboembolism and circulating microRNAs. Clin Epigenetics. 2019;11:28.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Sadia K, Ashraf MZ, Mishra A. Therapeutic role of Sirtuins Targeting unfolded protein response, Coagulation, and inflammation in Hypoxia-Induced Thrombosis. Front Physiol. 2021;12:733453.

    Article  PubMed  PubMed Central  Google Scholar 

  34. Mo JW, Zhang DF, Ji GL, Liu XZ, Fan B. TGF-beta1 and Serpine 1 expression changes in traumatic deep vein Thrombosis. Genet Mol Res. 2015;14:13835–42.

    Article  CAS  PubMed  Google Scholar 

  35. Wang P, Pan Y, Yang C, Zhang L, Zhao Z, Ye K, Li L, Xia S, Lu X, Shi H, et al. TNFalpha activation and TGFbeta blockage act synergistically for smooth muscle cell calcification in patients with venous Thrombosis via TGFbeta/ERK pathway. J Cell Mol Med. 2022;26:4479–91.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Kowalewski R, Malkowski A, Gacko M, Sobolewski K. Influence of thrombophlebitis on TGF-beta1 and its signaling pathway in the vein wall. Folia Histochem Cytobiol. 2010;48:542–8.

    PubMed  Google Scholar 

  37. Li D, Guo YY, Cen XF, Qiu HL, Chen S, Zeng XF, Zeng Q, Xu M, Tang QZ. Lupeol protects against cardiac hypertrophy via TLR4-PI3K-Akt-NF-kappaB pathways. Acta Pharmacol Sin. 2022;43:1989–2002.

    Article  CAS  PubMed  Google Scholar 

  38. Meng Y, Yin Q, Ma Q, Qin H, Zhang J, Zhang B, Pang H, Tian H. FXII regulates the formation of deep vein Thrombosis via the PI3K/AKT signaling pathway in mice. Int J Mol Med 2021, 47.

  39. Wei X, Zhang B, Wei F, Ding M, Luo Z, Han X, Tan X. Gegen Qinlian pills alleviate carrageenan-induced Thrombosis in mice model by regulating the HMGB1/NF-kappaB/NLRP3 signaling. Phytomedicine. 2022;100:154083.

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

Not applicable.

Funding

No funding was received for conducting this study.

Author information

Authors and Affiliations

  1. Department of Breast Thyroid Vascular Surgery, Taihe Hospital, Affiliated Hospital of Hubei University of Medicine, 442000, Shiyan, China

    Kun Zhou & Yan Yang

  2. Department of Hematology, Taihe Hospital, Affiliated Hospital of Hubei University of Medicine, 442000, Shiyan, China

    Na Li

  3. Department of Ophthalmology, Taihe Hospital, Affiliated Hospital of Hubei University of Medicine, 442000, Shiyan, China

    Jia Qi & Pingping Tu

  4. Department of Emergency, Taihe Hospital, Affiliated Hospital of Hubei University of Medicine, No.32, Renmin South Road, 442000, Shiyan, Huibei Province, China

    Hui Duan

Authors
  1. Kun Zhou
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Na Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jia Qi
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Pingping Tu
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Yan Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Hui Duan
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

KZ, NL, JQ, PPT, YY made substantial contributions to conception and design, acquisition of data, analysis and interpretation of data, and draft of the manuscript. HD revised the manuscript critically for important intellectual content. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Hui Duan.

Ethics declarations

Ethics approval and consent to participate

This study was conducted under the supervision and approval of the Ethics Committee of Taihe Hospital, Affiliated Hospital of Hubei University of Medicine. Informed consent was obtained from all subjects involved in the study.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary Material 1: Supplementary Table

. The top 10 nodes of PPI network.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhou, K., Li, N., Qi, J. et al. Diagnostic and prognostic potential of long non-coding RNA NORAD in patients with acute deep vein thrombosis and its role in endothelial cell function. Thrombosis J 22, 3 (2024). https://doi.org/10.1186/s12959-023-00575-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12959-023-00575-3

Keywords

Thrombosis Journal

ISSN: 1477-9560

Contact us