lncRNA SND1-IT1/miR-494-3p regulation in ox-LDL-induced endothelial cell injury: novel insights into coronary heart disease pathogenesis and diagnostic biomarkers

Abstract

Objectives

Coronary heart disease (CHD) is a major challenge in cardiovascular disease. This study investigated the role of lncRNA SND1-IT1 in oxidized low-density lipoprotein (ox-LDL)-induced injury of human umbilical vein endothelial cells (HUVECs).

Materials and methods

Serum was collected from healthy individuals and CHD patients. SND1-IT1 and miR-494-3p expression was analyzed by RT-qPCR, with ROC curves evaluating diagnostic potential. HUVECs were exposed to ox-LDL to induce injury and transfected to modulate target molecule expression. Cell viability and apoptosis were assessed using CCK8 and flow cytometry. Inflammatory cytokines and antioxidant enzymes were assessed by ELISA. Molecular interactions were verified through dual-luciferase reporters and RIP.

Results

In CHD patients, SND1-IT1 expression was significantly elevated (1.29 ± 0.18) compared to healthy controls (1.00 ± 0.14, P < 0.001), while miR-494-3p expression was notably downregulated (0.72 ± 0.16 vs. 1.01 ± 0.15, P < 0.001). Their combined assessment provide effective diagnostic value for CHD occurrence. Ox-LDL damaged HUVECs by inhibiting viability, enhancing apoptosis, inflammation, oxidative stress, and cell adhesion. SND1-IT1 knockdown alleviated these ox-LDL-induced injuries. SND1-IT1 acts as a sponge for miR-494-3p, whose downregulation reversed the protective effects of SND1-IT1 silencing. ZBTB20 was identified as a direct target of miR-494-3p and was upregulated in ox-LDL-treated HUVECs, counteracting the beneficial effects of miR-494-3p upregulation.

Conclusion

Altered SND1-IT1 and miR-494-3p expressions in CHD patients show potential as biomarkers for CHD risk assessment. SND1-IT1 may regulate ox-LDL-induced damage in HUVECs by modulating the interaction between miR-494-3p and ZBTB20.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40001-026-03918-8.

Introduction

Coronary heart disease (CHD) poses a significant global threat to human life, with its incidence and mortality rates steadily rising amidst societal development. Also referred to as coronary atherosclerotic heart disease, CHD occurs when the coronary arteries become narrowed or blocked, leading to myocardial ischemia, hypoxia, or necrosis [1]. Endothelial dysfunction is the initiating stage in the development of these cardiovascular diseases [2]. Endothelial cells serve as the first line of defense for the blood vessel wall; once damaged, they not only facilitate the formation of atheromatous plaques but also significantly intensify the inflammatory response within the blood vessels, thereby accelerating the pathological process of atherosclerosis and promoting the progression of CHD [3]. Oxidized low-density lipoprotein (ox-LDL) is thought to be a significant initiator that causes endothelial injury, which is an early step in the process of atherosclerosis [4]. Research indicates that ox-LDL can induce a series of pathophysiological alterations in human umbilical vein endothelial cells (HUVECs), including enhanced intracellular oxidative stress, increased secretion of inflammatory cytokines, and elevated cellular apoptosis [5, 6]. These changes not only disrupt the integrity and stability of the vascular wall but also facilitate monocyte adhesion, migration, and foam cell formation. This process accelerates atherosclerosis, ultimately culminating in the onset of CHD [7, 8]. Therefore, conducting in-depth research into the underlying pathophysiological mechanisms of endothelial cell injury and identifying effective therapeutic targets based on this research is of crucial importance for improving the treatment outcomes of CHD.

Long non-coding RNAs (lncRNAs), a class of functional non-coding RNAs, have garnered increasing attention in recent years for their roles in endothelial cell injury. For instance, lncRNA APPAT has been shown to exert a protective effect against endothelial cell injury induced by ox-LDL by modulating the miR-647/FGF5 axis [9]. Furthermore, lncRNA FGF7-5 and lncRNA GLRX3 have also been found to participate in the pathological processes of CHD by regulating endothelial cell function and inflammatory responses [10]. These findings suggest that lncRNAs play pivotal regulatory roles in the formation and progression of CHD.

In our initial screening of several candidate lncRNAs potentially involved in ox-LDL-induced endothelial injury, SND1-IT1 emerged as a molecule of particular interest due to its significant dysregulation. As an emerging lncRNA, SND1-IT1 has been reported to be aberrantly expressed in various tumors, including osteosarcoma [12] and gastric cancer [13], and is closely associated with malignant biological behaviors. More importantly, a key clue for its potential role in cardiovascular diseases came from a study by Xu et al., which demonstrated that SND1-IT1 plays a regulatory role in myocardial ischemia–reperfusion injury by targeting miR-183-5p [11], suggesting its inherent potential in cardiovascular pathophysiology. Our preliminary experiments provided direct evidence supporting its relevance to our model: treating HUVECs with 50 μg/mL ox-LDL for 24 h resulted in a significant upregulation of SND1-IT1 expression compared to the control group, as detected by qRT-PCR. This finding directly suggests its potential involvement in ox-LDL-induced endothelial cell injury. In addition, bioinformatic prediction using the StarBase and LncRNASNPv3 databases revealed highly complementary conserved binding sites (conservation score > 0.85) between SND1-IT1 and miR-494-3p, indicating a potential ceRNA mechanism. However, the specific function and mechanism of SND1-IT1 in endothelial cell injury, particularly its relationship with miR-494-3p, remain completely unexplored.

miR-494-3p, as a crucial miRNA, exhibits significant regulatory effects in the pathophysiological processes of the cardiovascular system. Specifically, miR-494-3p affects endothelial barrier function by regulating the expression of tight junction protein TJP1 [14]. In addition, in cardiomyocytes, Peli1 regulates the expression of miR-494-3p and promotes its expression through the NF-κB/AP-1 signaling pathway, which is then transmitted to cardiac fibroblasts via exosomes, activating them and playing a pivotal role in the process of myocardial fibrosis [15]. Furthermore, several studies have shown that miR-494-3p can mediate various lncRNA to play an important role in cellular processes. For instance, lncRNA SNHG8 plays a protective role in cerebral ischemia–reperfusion injury by sponging miR-494-3p, which subsequently inhibits microglial inflammation and apoptosis [16]. In addition, lncRNA TUG1 competitively binds to miR-494-3p, mediating the occurrence of ischemia–reperfusion-induced acute kidney injury [17]. These findings underscore the importance of miR-494-3p and its interaction with lncRNAs in cellular injury processes, yet its potential relationship with SND1-IT1 has not been investigated. Therefore, based on the preliminary experimental evidence of SND1-IT1 upregulation under ox-LDL stress, the reported role of SND1-IT1 in myocardial injury, the bioinformatically predicted strong interaction with miR-494-3p, and the established significance of miR-494-3p in cardiovascular pathophysiology, we hypothesized that the SND1-IT1/miR-494-3p axis might be a critical regulatory pathway in ox-LDL-induced endothelial injury.

The study aims to investigate the expression and diagnostic value of SND1-IT1 and miR-494-3p in CHD, and to elucidate their interaction and how they regulate the expression of related genes, impacting the pathological changes in ox-LDL-induced HUVECs. This research seeks to offer new insights and approaches for CHD prevention, diagnosis, and treatment.

Materials and methods

Clinical blood samples

This study recruited 59 healthy volunteers with no history of cardiovascular disease (HC) and 59 patients with CHD from the Affiliated Hospital of Qingdao University as subjects (those who visited the hospital during 2020–2022). All participants were confirmed to have no other comorbidities. CHD diagnosis was verified by coronary angiography, with ≥ 50% stenosis in at least one major coronary artery (left anterior descending, circumflex, or right coronary artery); clinical phenotypes included stable angina pectoris (n = 32) and acute coronary syndrome (ACS, n = 27, comprising 16 cases of ST-segment elevation myocardial infarction [STEMI] and 11 cases of non-ST-segment elevation myocardial infarction [NSTEMI]). Baseline characteristics of the two groups were carefully matched: demographic indicators (gender, age, body mass index [BMI]) and key non-lipid risk factors (hypertension, diabetes mellitus, and smoking status) showed no significant differences (all P > 0.05). As expected, the atherosclerotic lipid profile was significantly more severe in the CHD group than in the HC group: total cholesterol (TC), low-density lipoprotein-cholesterol (LDL-C), oxidized LDL (ox-LDL), and triglycerides (TGs) were elevated, while high-density lipoprotein-cholesterol (HDL-C) was reduced (all P < 0.05). Detailed baseline characteristics are presented in Table S1. The research plan was cleared by the Ethics Committee of the Affiliated Hospital of Qingdao University, with all participants giving their written consent. The use of cardiovascular medications (e.g., statins, antiplatelet agents, beta-blockers, and ACE inhibitors/ARBs) was documented for all participants. To minimize potential acute effects of medication on circulating RNA levels, blood samples were collected in the morning after an overnight fast, prior to the intake of any morning doses. Blood samples were collected from all participants, from which serum was extracted and preserved at −80 °C for the purpose of isolating total RNA.

Cell culture and treatment

After thawing and resuscitating the HUVECs (ATCC, USA), the cells were cultured in DMEM medium (supplied by Solarbio, Beijing, China) supplemented with 10% fetal bovine serum and 1% antibiotics at 37 °C in an atmosphere containing 5% CO₂. Regular observations were conducted to monitor cell growth. When the cells had proliferated to occupy 80% of the culture flask, the medium was replaced for subculturing. The fourth-generation HUVECs, which were in a logarithmic growth phase, were selected and seeded into fresh medium. Simultaneously, ox-LDL (sourced from Nanjing Jiancheng Bioengineering Institute, China) was diluted with PBS buffer to concentrations of 0, 25, 50, and 100 μg/mL. These different concentrations of ox-LDL were then added to the culture medium to co-incubate with the HUVECs for 24 h. Following the observation of cellular status, HUVECs stimulated with 50 μg/mL of ox-LDL were selected for subsequent experiments.

Cell transfection

HUVECs were processed through digestion, washing, resuspension, and plated in 12-well plates. Following 24 h of incubation, transfection was conducted with Lipofectamine™ 3000 (Thermo-Fisher, Waltham, MA). The transfection mixtures included silenced-SND1-IT1 (si-SND1) and its negative control (si-NC), miR-494-3p inhibitor, miR-494-3p mimic, and its negative control (miR-NC), ZBTB20 overexpression vector (pcDNA-ZBTB20), and a blank pcDNA vector. These were incubated with HUVECs pretreated with 50 μg/mL ox-LDL for 48 h. Prior to formal incubation, the transfection efficiency of each aforementioned plasmid (si-SND1, miR-494-3p mimic/inhibitor, and pcDNA-ZBTB20) was verified by qRT-PCR, and then co-transfection was carried out according to the experimental grouping. Compared with their respective controls, si-SND1 transfection significantly knocked down SND1-IT1 expression by > 60% (Figure S2a), miR-494-3p mimic and inhibitor increased and decreased miR-494-3p levels by > 55% and > 50%, respectively (Figure S2b), and pcDNA-ZBTB20 transfection elevated ZBTB20 mRNA expression by > 60% (Figure S2c). The experiment comprised a blank control group and a group of ox-LDL-treated HUVECs (not transfected). At the end, cells with verified high transfection efficiency were selected for subsequent experiments.

Flow cytometry

Cells from various groups of HUVECs were collected for the assessment of apoptosis using a dual staining method. Initially, the HUVECs were digested with trypsin to obtain a single-cell suspension. The cells were then stained with 5 mL of Annexin V labeled with fluorescein isothiocyanate (FITC) and 5 mL of propidium iodide (PI) under dark conditions for 20 min. After staining, the cells were rinsed with buffer and subjected to analysis using a flow cytometer (BD Biosciences, UK). Finally, the apoptotic rate was calculated based on the fluorescence signals emitted by the cells.

CCK-8 assay

Cells from the aforementioned treated groups were plated into 96-well plates at a density of 1 × 10³ cells per well. Cell viability was evaluated at different time intervals (0, 24, 48, and 72 h) using the CCK-8 kit (Biyuntian Biotechnology, Shanghai, China). At each specified time point, 10 μL of CCK-8 solution was introduced to each well, and the optical density (OD) read at 450 nm was used as an indicator of cell viability.

IL-6 and TNF-α level assay

HUVECs from each group, exhibiting robust growth and a density of approximately 80%, were selected. The existing medium was gently aspirated using a pipette, and then washed. Following this, the cells were transferred to serum-free medium and incubated for 48 h. Subsequently, the supernatant was collected by centrifugation. The concentrations of interleukin-6 (IL-6) and tumor necrosis factor-alpha (TNF-α) in the supernatant were assayed according to the protocols provided by the ELISA kits (Saipai Biotechnology Co., Ltd., Wuhan, China).

CAT and SOD activity assay

Cells were selected and subsequently washed following the aforementioned procedures. They were then transferred into a medium containing RIPA lysate to allow for sufficient reaction. After lysis, the cell suspension was centrifuged, and the resultant supernatant, which constituted the cell lysate, was carefully collected. To determine the activities of peroxidase (CAT) and superoxide dismutase (SOD), assays were conducted using the CAT and SOD kits (JianCheng Bioengineering Research Institute Co., Ltd., Nanjing, China). This involved the addition of substrate, enzyme working solution, and color developer, followed by the measurement and recording of the absorbance changes within a 15-min timeframe. Finally, the activities of SOD and CAT in the lysate were calculated based on the formula outlined in the instruction manual.

qRT-PCR

According to the instructions provided by the RNAliquid Blood RNA Kit (RN23, Aidlab Biotechnologies Co., Ltd., Beijing, China), 0.75 μl of lysis buffer was added to the samples and mixed thoroughly. Total RNA was extracted from serum samples or cells from different treatment groups. The absorbance values of the RNA samples were then measured using a Q9000 spectrophotometer. Subsequently, 1 μg of RNA from each sample was used for reverse transcription, following the guidelines of the Fast King RT Kit (KR116, Tiangen Biotech Co., Ltd., Beijing, China). Prior to reversing transcription, genomic DNA (gDNA) was removed. The RNA was then incubated at 42 °C for 15 min and at 95 °C for 3 min in a 20 μl reaction system, followed by immediate placement on ice to reverse transcribe into cDNA. Quantitative real-time polymerase chain reaction (qRT-PCR) was conducted using the FastFire qPCR PreMix (FP207, Tiangen Biotech Co., Ltd., Beijing, China) on an ABI 7500 Fast Real-Time PCR System (Applied Biosystems, USA). The PCR conditions were established as follows: an initial denaturation step at 95 °C for 1 min; this was followed by 40 cycles consisting of denaturation at 95 °C for 5 s and annealing at 60 °C for 15 s. Expression data for SND1-IT1 and ZBTB20 mRNA were normalized against GAPDH levels, while miR-494-3p expression levels were normalized against U6. Relative expression levels were calculated utilizing the 2^−ΔΔCt method. The primer sequences used for qPCR are listed in Supplementary Table S2. All primers were synthesized by Sangon Biotech (Shanghai, China).

Dual-luciferase reporter gene assay

The LncRNASNP2 (https://guolab.wchscu.cn/lncRNASNP/#!/) and StarBase (http://starbase.sysu.edu.cn/) databases predicted the binding sites of SND1-IT1, miR-494-3p, and ZBTB20 respectively. Targeted mutagenesis generated the miR-494-3p mutation site in the mutant SND1-IT1 and ZBTB20 luciferase reporter vectors. Wild-type and mutant PCR amplification products were cloned into PMIR-GLO luciferase vectors named WT-SND1-IT1, MUT-SND1-IT1, WT-ZBTB20, and MUT-ZBTB20. The dual-luciferase assay was conducted by co-transfecting each of the above luciferase vector plasmids with miR-mimic, miR-inhibitor, or miR-NC into HUVECs cells using Lipofectamine™ 3000. After 48 h of transfection, cell lysates were obtained, and luciferase activity was determined using a dual-luciferase reporter gene assay kit (Promega, USA).

RIP assay

The binding of molecules to their targets was verified with the EZ-agna RNA Immunoprecipitation (RIP) Kit (Promega, USA), in conjunction with qRT-PCR analysis. Initially, 100 μL of cell lysate was obtained by lysing the targeted HUVECs using RIP lysis buffer. This lysate was incubated for 6 h at 4 °C with RIP buffer containing magnetic beads coated with either a human Argonaute 2 antibody (anti-Ago2, clone: EPR20250, catalog number: ab186733, Abcam) or a negative control antibody (normal mouse anti-IgG, catalog number: 12-371, Millipore). Following incubation, the beads were treated with Proteinase K buffer to digest the proteins bound to them. Subsequently, the immunoprecipitated RNA was extracted and analyzed using qRT-PCR to determine the enrichment levels of SND1-IT1, miR-494-3p, and ZBTB20.

Subcellular localization

The subcellular distribution of SND1‑IT1 was determined in HUVECs using a commercial nuclear‑cytoplasmic fractionation kit (PARIS™, Thermo Fisher Scientific). Following the manufacturer’s protocol, RNA was separately isolated from the nuclear and cytoplasmic fractions. The abundance of SND1‑IT1 transcript in each compartment was then quantified by qRT‑PCR. To validate the specificity of the fractionation procedure, the small nuclear RNA U6 (nuclear‑enriched) and GAPDH mRNA (cytoplasmic‑enriched) were analyzed in parallel as internal controls.

Western blot analysis

For detection of ZBTB20 protein expression, total cellular protein was extracted using RIPA lysis buffer. Equal amounts of protein samples were separated by 10% SDS‑PAGE and transferred onto PVDF membranes. The membranes were blocked with 5% non‑fat milk for 1 h at room temperature, followed by overnight incubation at 4 °C with primary antibodies against ZBTB20 (1:1000) and β‑Actin (1:5000). After incubation with HRP‑conjugated secondary antibodies for 1 h at room temperature, protein bands were visualized using an ECL chemiluminescence reagent and captured with a gel imaging system. β‑Actin was used as a loading control, and relative protein expression was calculated as the ratio of the band intensity of ZBTB20 to that of β‑Actin.

Statistical analysis

SPSS 21.0 was utilized for statistical analysis. Continuous variables were presented as mean ± standard deviation (x ± s). Independent sample t tests were used for comparing two groups, while comparisons among multiple groups employed univariate ANOVA followed by Tukey’s post-hoc test. Pearson’s correlation coefficient was applied for correlation analysis. ROC curves evaluated the diagnostic accuracy for HC and CHD. The level of statistical significance was determined to be p < 0.05.

Results

Expression and diagnostic value of SND1-IT1 and miR-494-3p in CHD patients

Serum samples from HC and CHD patients were analyzed using RT-qPCR. Notably, SND1-IT1 expression was markedly raised in CHD patients compared to HC (Fig. 1a). The diagnostic value of SND1-IT1, assessed by ROC curve analysis, yielded an AUC of 0.896 (95% CI 0.837–0.954), with a sensitivity of 77.97% and a specificity of 91.53% at the optimal cutoff (Fig. 1b). In contrast, miR-494-3p expression was significantly downregulated in CHD patients (Fig. 1c), with a diagnostic AUC of 0.880 (95% CI 0.816–0.942), a sensitivity of 79.66%, and a specificity of 88.14% as determined by ROC curve analysis (Fig. 1d). Furthermore, SND1-IT1 and miR-494-3p expression levels were negatively correlated in CHD patients (r =  −0.776, p < 0.001, Fig. 1e). When the two molecules were combined to diagnose CHD, the AUC value increased significantly to 0.958 (95% CI 0.924–0.992), achieving a sensitivity of 82.35% and a specificity of 89.72% (Fig. 1f). Further subgroup analysis revealed a gradient increase in SND1-IT1 levels across the clinical spectrum: expression was significantly higher in patients with SA than in HC, and further elevated in those with ACS compared to the SA group (Figure S1a). Within the ACS cohort, no significant difference was observed between STEMI and NSTEMI patients (Figure S1b). To explore the functional basis of SND1-IT1, we determined its subcellular localization in HUVECs. Nuclear-cytoplasmic fractionation assay demonstrated that SND1-IT1 is predominantly localized in the cytoplasm (Figure S1c).

Fig. 1.

Diagnostic roles of SND1-IT1 and miR-494-3p in CHD. a Relative expression of SND1-IT1 in serum from healthy controls (HC) and CHD patients detected by RT-qPCR. b ROC curve analysis of SND1-IT1 for CHD diagnosis. c Relative expression of miR-494-3p in serum detected by RT-qPCR. d ROC curve analysis of miR-494-3p. e Correlation analysis between SND1-IT1 and miR-494-3p expression levels. f Combined ROC analysis of SND1-IT1 and miR-494-3p

Induction of HUVECs damage by ox-LDL

To mimic the pathological environment of atherosclerosis, HUVECs were stimulated with varying concentrations of ox-LDL. SND1-IT1 expression increased with rising ox-LDL concentrations (Fig. 2a), while miR-494-3p expression in HUVECs gradually decreased as ox-LDL concentrations increased (Fig. 2b). In addition, the study revealed that the higher the ox-LDL concentration, the more severe the damage to HUVECs. Specifically, ox-LDL inhibited HUVEC viability in a concentration-dependent manner at the 72-h time (Fig. 2c). Concurrently, it induced cellular apoptosis (Fig. 2d, see Supplementary File 1 for original flow cytometry plots) and dysregulated apoptosis-related gene expression, evidenced by promoted Bax mRNA levels and inhibited Bcl-2 mRNA levels (Fig. 2e). Furthermore, ox-LDL treatment enhanced the expressions of cell adhesion molecules VCAM-1 and ICAM-1 (Fig. 2f), promoted the release of inflammatory cytokines IL-6 and TNF-α (Fig. 2g), and inhibited the activities of antioxidant enzymes CAT and SOD (Fig. 2h).

Fig. 2.

ox-LDL effects on HUVECs. a–b Expression levels of SND1-IT1 (a) and miR-494-3p (b) measured by RT-qPCR after treatment with increasing concentrations of ox-LDL. c Cell viability assessed by CCK-8 assay (72 h). d Apoptosis rate determined by flow cytometry. e mRNA expression of apoptosis-related genes (Bax, Bcl-2) analyzed by RT-qPCR. f mRNA expression of cell adhesion molecules (VCAM-1, ICAM-1) measured by RT-qPCR. g Inflammatory cytokine levels (IL-6, TNF-α) detected by ELISA. h Antioxidant enzyme activities (CAT, SOD) measured using specific kits

SND1-IT1 downregulation protects HUVECs from ox-LDL-induced damage

To investigate the impact of SND1-IT1 on HUVECs exposed to ox-LDL, it successfully knocked down SND1-IT1 expression using si-SND1-IT1 transfection (Fig. 3a). This knockdown enhanced the viability of HUVECs suppressed by ox-LDL (Fig. 3b) and inhibited ox-LDL-induced apoptosis (Fig. 3c, the original flow cytometry dot plots corresponding to this quantification are detailed in Supplementary File 1), evidenced by the downregulation of Bax and upregulation of Bcl-2 expression (Fig. 3d). In addition, SND1-IT1 downregulation significantly reversed the ox-LDL-induced expression of cell adhesion molecules (Fig. 3e). Furthermore, it suppressed the release of inflammatory cytokines (Fig. 3f) and enhanced the activity of antioxidant enzymes (Fig. 3g).

Fig. 3.

The role of SND1-IT1 downregulation on ox-LDL-treated HUVECs. a SND1-IT1 expression after transfection with si-SND1-IT1 measured by RT-qPCR. b Cell viability by CCK-8 assay. c Apoptosis rate determined by flow cytometry. d mRNA expression of apoptosis-related genes (Bax, Bcl-2) analyzed by RT-qPCR. e mRNA expression of cell adhesion molecules (VCAM-1, ICAM-1) measured by RT-qPCR. f Inflammatory cytokine levels (IL-6, TNF-α) detected by ELISA. g Antioxidant enzyme activities (CAT, SOD) measured using specific kits

miR-494-3p knockdown reverses si-SND1-IT1-mediated protection in ox-LDL-stimulated HUVECs

Bioinformatics analysis revealed potential binding sites between SND1-IT1 and miR-494-3p. To validate this, dual-luciferase reporter assays and RIP experiments were conducted. The results showed that miR-494-3p significantly negatively regulated the luciferase activity of the WT-SND1-IT1 but had no effect on the MUT-SND1-IT1 (Fig. 4a). Both miR-494-3p and SND1-IT1 were significantly enriched in the anti-Ago2 complex (Fig. 4b). For SND1-IT1 expression (Fig. 4c), transfection with si-SND1-IT1 significantly reduced SND1-IT1 levels compared to the ox-LDL-only group, confirming effective knockdown of SND1-IT1. Notably, co-transfection with the miR-494-3p inhibitor did not alter SND1-IT1 expression relative to the ox-LDL + si-SND1-IT1 group, indicating that miR-494-3p does not regulate SND1-IT1 expression. For miR-494-3p expression (Fig. 4d), SND1-IT1 knockdown (ox-LDL + si-SND1-IT1) significantly increased miR-494-3p levels compared to the ox-LDL-only group, suggesting that SND1-IT1 negatively regulates miR-494-3p. This effect was reversed by co-transfection with the miR-494-3p inhibitor, as miR-494-3p levels in the ox-LDL + si-SND1-IT1 + miR-inhibitor group were significantly lower than those in the ox-LDL + si-SND1-IT1 group, confirming the inhibitor’s efficacy.

Fig. 4.

SND1-IT1-miR-494-3p interaction. a Dual-luciferase reporter assay confirming direct binding. b RNA immunoprecipitation (RIP) showing enrichment of both molecules. c SND1-IT1 expression after miR-494-3p inhibition measured by RT-qPCR. d miR-494-3p expression after SND1-IT1 knockdown measured by RT-qPCR. e–j Effects of miR-494-3p downregulation on cell viability (e, CCK-8), apoptosis (f, flow cytometry), apoptosis-related gene mRNA (g, RT-qPCR), cell adhesion molecule mRNA expression (h, RT-qPCR), inflammatory cytokines (i, ELISA), and antioxidant enzymes (j, specific kits). ox-LDL + si-SND1: HUVECs stimulated with ox-LDL and transfected with siRNA targeting SND1-IT1; ox-LDL + si + miR-NC: ox-LDL-stimulated HUVECs co-transfected with si-SND1-IT1 and a negative control for miRNA; ox-LDL + si + miR-inhibitor: ox-LDL-stimulated HUVECs co-transfected with si-SND1-IT1 and an inhibitor of miR-494-3p

In HUVECs stimulated with ox-LDL, the downregulation of miR-494-3p significantly inhibited the enhancement of cell viability (Fig. 4e) mediated by SND1-IT1 downregulation. Inhibition of miR-494-3p expression significantly facilitated the apoptosis rate of ox-LDL-induced HUVECs (Fig. 4f, see Supplementary File 1 for original flow cytometry plots), enhanced the expression of Bax mRNA, and depressed the expression of Bcl-2 mRNA (Fig. 4g). Furthermore, the downregulation of miR-494-3p promoted the release and expression of VCAM-1 and ICAM-1 (Fig. 4h) and IL-6 and TNF-α (Fig. 4i) in HUVECs exposed to ox-LDL, while reducing the activity of antioxidant enzymes CAT and SOD (Fig. 4j), reversing the effects of SND1-IT1 knockdown.

miR-494-3p directly targeted ZBTB20

The downstream target genes of miR-494-3p were mined through miRDB (https://mirdb.org/), TargetScan (https://www.targetscan.org/vert_72/), and miRWalk (http://mirwalk.umm.uni-heidelberg.de/) databases. As shown in Fig. 5a, two target genes were finally screened. CYSTM1 mRNA in CHD patients did not significantly differ from that in healthy individuals (Fig. 5b). We further investigated its regulation in HUVECs. In ox-LDL-treated HUVECs, CYSTM1 expression remained unaltered compared to controls. Moreover, neither miR-494-3p mimic nor inhibitor transfection affected CYSTM1 mRNA levels in HUVECs (Figure S3). In contrast, ZBTB20 mRNA expression was upregulated (Fig. 5c) and exhibited a negative correlation with miR-494-3p expression (r =  −0.515, p < 0.001; Fig. 5d). Based on the binding sites between ZBTB20 and miR-494-3p, primer sequences were designed for relevant experiments. It was revealed that miR-494-3p significantly negatively regulated the luciferase activity of WT-ZBTB20 but had no significant effect on the activity of MUT-ZBTB20 (Fig. 5e). Furthermore, both ZBTB20 and miR-494-3p were enriched in anti-Ago2 (Fig. 5f).

Fig. 5.

Identification of miR-494-3p target genes. a Venn diagram of predicted target genes from three databases. b–c Expression levels of CYSTM1 (b) and ZBTB20 (c) in CHD patients and healthy controls measured by RT-qPCR. d Correlation between ZBTB20 and miR-494-3p expression. e Dual-luciferase reporter assay confirming ZBTB20 as a direct target. f RNA immunoprecipitation assay showing enrichment of ZBTB20 and miR-494-3p

By targeting ZBTB20, miR-494-3p provides protection to HUVECs from the effects of ox-LDL

As illustrated in Fig. 6a, transfection of miR-494-3p mimics in HUVECs stimulated with ox-LDL significantly suppressed the expression of ZBTB20 mRNA. Correspondingly, western blot analysis confirmed that miR-494-3p mimic transfection also markedly reduced ZBTB20 protein levels, whereas co-transfection with the ZBTB20 overexpression plasmid (pcDNA-ZBTB20) restored its expression (Fig. 6b). Further analysis revealed that upregulation of miR-494-3p (via mimic transfection) markedly enhanced the viability of HUVECs induced by ox-LDL (Fig. 6c) and inhibited their apoptosis (Fig. 6d-e, original flow cytometry plots are provided in Supplementary File 1), while co-transfection with ZBTB20-overexpressing plasmids significantly attenuated these protective effects. In addition, upregulation of ZBTB20 counteracted the miR-494-3p-mediated inhibition of ox-LDL-induced cell adhesion molecule expression (Fig. 6f) and inflammatory cytokine release (Fig. 6g), and reversed the miR-494-3p-induced enhancement of antioxidant enzyme activity (Fig. 6h).

Fig. 6.

The role of ZBTB20 overexpression in ox-LDL-treated HUVECs. a ZBTB20 expression after transfection measured by RT-qPCR. b ZBTB20 protein expression detected by Western blot. c Cell viability assessed by CCK-8 assay. d Apoptosis rate determined by flow cytometry. e mRNA expression of apoptosis-related genes (Bax, Bcl-2) analyzed by RT-qPCR. f mRNA expression of cell adhesion molecules (VCAM-1, ICAM-1) measured by RT-qPCR. g Inflammatory cytokine levels (IL-6, TNF-α) detected by ELISA. h Antioxidant enzyme activities (CAT, SOD) measured using specific kits. ox-LDL + miR-NC: HUVECs stimulated with ox-LDL and transfected with a miRNA negative control; ox-LDL + miR-mimic: ox-LDL-stimulated HUVECs transfected with a miR-494-3p mimic; ox-LDL + miR + pcDNA: ox-LDL-stimulated HUVECs co-transfected with miR-494-3p mimic and an empty pcDNA vector; ox-LDL + miR + pcDNA-ZBTB20: ox-LDL-stimulated HUVECs co-transfected with miR-494-3p mimic and a ZBTB20-overexpressing plasmid (pcDNA-ZBTB20)

Discussion

As dietary and lifestyle habits evolve, CHD has increasingly become a significant global health burden, necessitating an in-depth understanding of its underlying mechanisms and the development of novel diagnostic and therapeutic strategies [18]. With advancements in molecular biology, several lncRNAs and miRNAs have been identified as potential key players in the pathological processes associated with CHD [19, 20]. However, among the numerous RNA molecules, the mechanism underlying the interaction between SND1-IT1 and miR-494-3p in ox-LDL-induced endothelial cell dysfunction remains to be elucidated, and this study aims to fill this knowledge gap.

We first found that SND1-IT1 is upregulated in CHD patients and exhibits diagnostic potential. To further investigate the role of SND1-IT1 in CHD, an ox-LDL-stimulated HUVEC model was employed to simulate the CHD pathological environment. This well-established model demonstrates that ox-LDL induces endothelial cell injury through multiple mechanisms including suppressed proliferation, enhanced apoptosis, aggravated inflammatory responses, upregulated adhesion molecule expression, and intensified oxidative stress, all of which are closely associated with CHD pathogenesis [21, 22]. In the present study, these characteristic injury phenotypes were observed in ox-LDL-treated HUVECs. Importantly, ox-LDL treatment significantly promoted SND1-IT1 expression, suggesting its potential involvement in ox-LDL-induced endothelial cell injury. The lncRNA MIAT was also identified to be upregulated in response to ox-LDL stimulation, and knockdown of its expression ameliorated ox-LDL-induced cell apoptosis, inflammation, and oxidative stress [23]. Similarly, Zhang et al. reported that lncRNA OIP5-AS1 was overexpressed following ox-LDL stimulation, and they also observed that knocking down its expression alleviated the cellular injury caused by ox-LDL [24]. Building on these findings, the current study further investigated and found that knocking down the expression of SND1-IT1 had a similar effect. These results suggest that SND1-IT1 may contribute to the development of CHD by modulating the mechanisms involved in endothelial cell injury.

Xu et al. [11] reported that SND1-IT1 mediated myocardial ischemia/reperfusion injury via targeting miR-183-5p. In addition, SND1-IT1 promotes gastric cancer cell activity by adsorbing miR-124 [25]. Based on these findings, it is conceivable that SND1-IT1 may influence HUVECs injury by targeting specific miRNAs. In our study, miR-494-3p was downregulated in CHD patients and holds significant diagnostic value for CHD. Previous research has highlighted the crucial role of miR-494-3p in cardiovascular diseases. Tang et al. [15] discovered that miR-494-3p regulates cardiomyocyte fibrosis by targeting PTEN. Notably, studies have also indicated that miR-494-3p acts as a regulatory molecule in vascular smooth muscle cells (VSMCs), influencing proliferation and inflammatory responses, and thereby affecting plaque development in CHD [26]. Our study confirms that SND1-IT1 targets miR-494-3p and further reveals that knockdown of miR-494-3p inverts the protection provided by SND1-IT1 downregulation in ox-LDL-exposed HUVECs.

Through bioinformatics analysis and related experiments, the target gene of miR-494-3p, ZBTB20, was identified. As a member of the zinc finger protein subfamily, ZBTB20 has been implicated in various studies concerning cardiovascular diseases. Research has demonstrated that ZBTB20 regulates cardiac contraction and relaxation by modulating sarcoplasmic reticulum Ca²⁺ levels [27]. Increased expression of ZBTB20 has been observed in tissues from patients with CHD lesions and in macrophages stimulated with ox-LDL, with ZBTB20 knockout found to inhibit ox-LDL-induced oxidative stress in macrophages [28]. Previous studies by Wang et al. support the pathogenic role of ZBTB20 in endothelial injury, demonstrating that its upregulation in ox-LDL stimulated HUVECs contributes to cellular damage, while its inhibition attenuates such injury [29]. These phenomena were also demonstrated in this study, further suggesting that miR-494-3p protects HUVECs from the damaging effects of ox-LDL, possibly by targeting ZBTB20. Notably, previous studies have demonstrated that ZBTB20 directly interacts with the NF-κB p65 subunit and enhances its transcriptional activity [30, 31], and the NF-κB pathway represents one of the key signaling cascades regulating endothelial inflammation and injury [32, 33]. In our model, overexpression of ZBTB20 upregulated the levels of TNF-α, IL-6, VCAM-1, and ICAM-1, which are classic NF-κB target proteins [34, 35]. Although we did not directly detect the activation of NF-κB here, the consistency between our functional data and the documented ZBTB20-NF-κB interactions supports the hypothesis that this axis partially contributes to endothelial injury through inflammatory signaling. Future studies specifically investigating the activation mechanism of the NF-κB pathway will help fully elucidate the downstream mechanisms of the miR-494-3p/ZBTB20 axis.

This study has several limitations that should be acknowledged. First, while SND1-IT1 and miR-494-3p demonstrate promising diagnostic value, these findings are preliminary due to the single-center cohort with limited sample size; therefore, validation through larger multicenter studies incorporating diverse CHD phenotypes and non-CHD cardiovascular controls is essential to establish clinical utility. Second, the exclusive use of HUVECs limits physiological relevance; future work should employ primary coronary artery endothelial cells and animal models of atherosclerosis to confirm the pathophysiological significance of the identified regulatory axis. Third, it should be emphasized that the observed alterations in serum SND1-IT1 and miR-494-3p levels in CHD patients demonstrate a correlative relationship rather than establishing causality. The current clinical data cannot determine whether these molecular changes actively contribute to CHD pathogenesis or merely represent secondary consequences of the disease process. However, our subsequent in vitro functional experiments provide mechanistic evidence supporting the potential causal role of this regulatory axis in endothelial injury, a key pathological process in CHD. Future studies employing animal models with genetic manipulation and prospective cohort designs will be essential to definitively establish causal relationships between this molecular axis and CHD development. Fourth, while we focused on miR-494-3p, SND1-IT1 may regulate additional miRNAs; comprehensive identification of its full interactome will provide a more complete understanding of its regulatory network. Fifth, our study did not measure ZBTB20 protein levels in patient serum samples due to constraints in sample volume and preservation. While our cellular data confirm the functional relevance of ZBTB20 in the proposed axis, future studies with dedicated cohorts are needed to validate its potential as a circulating protein biomarker. Fifth, although we identified ZBTB20 as the functional target downstream of the SND1-IT1/miR-494-3p interaction, a definitive genetic rescue experiment (e.g., SND1-IT1 knockdown combined with ZBTB20 overexpression) to prove that ZBTB20 upregulation is obligatory for SND1-IT1-mediated injury was not performed. This remains a key experiment to solidify the causal chain within this axis. Finally, although our data align with NF-κB-mediated inflammatory responses, direct investigation of this and other relevant signaling pathways downstream of ZBTB20 will be crucial to fully elucidate the mechanistic basis of endothelial injury in CHD. Addressing these aspects will significantly advance our understanding of this regulatory axis and its therapeutic potential.

In summary, this study has unveiled the significant potential of the SND1-IT1/miR-494-3p axis as a biomarker for the diagnosis of CHD. It has also demonstrated that disrupting the expression of SND1-IT1 can effectively mitigate ox-LDL-induced HUVECs damage, and this protective effect is associated with the regulation of miR-494-3p. In addition, our findings confirm that the miR-494-3p/ZBTB20 axis plays a crucial role in mediating ox-LDL-induced endothelial injury. Based on this established downstream relationship and the confirmed interaction between SND1-IT1 and miR-494-3p, we speculate that SND1-IT1 may indirectly influence ZBTB20 expression by sequestering miR-494-3p. However, due to the current lack of direct experimental evidence (e.g., a rescue experiment) definitively linking ZBTB20 to SND1-IT1-mediated phenotypes, this potential cascade relationship requires further validation. This discovery not only provides new insights into the pathogenesis of CHD but also opens up promising avenues for the future development of novel diagnostic tools and therapeutic approaches targeting CHD.

Abbreviations

CHD

Coronary heart disease

anti-Ago2

Argonaute 2 antibody

CAT

Activities of peroxidase

FITC

Fluorescein isothiocyanate

gDNA

Genomic DNA

HUVECs

Human umbilical vein endothelial cells

IL-6

Interleukin-6

lncRNAs

Long non-coding RNAs

miR-NC

MiR-494-3p negative control

OD

Optical density

Ox-LDL

Oxidized low-density lipoprotein

PI

Propidium iodide

qRT-PCR

Quantitative real-time polymerase chain reaction

RIP

RNA Immunoprecipitation

si-SND1

Silenced SND1-IT1si-NC, silenced SND1-IT1 negative control

SOD

Superoxide dismutase

TNF-α

Tumor necrosis factor-alpha

VSMCs

Vascular smooth muscle cells

Author contributions

All authors designed this study. ZX L conducted the experiment and analyzed the data. YX S wrote the manuscript. ZX L revised the manuscript. All authors reviewed and approved for publication.

Funding

No funding was received for conducting this study.

Data availability

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

Declarations

Ethics approval and consent to participate

The authors state that they have obtained the Affiliated Hospital of Qingdao University review board approval and have followed the principles outlined in the Declaration of Helsinki for all human or animal experimental investigations. In addition, for investigations involving human subjects, informed consent has been obtained from the participants involved.

Consent for publication

All patients provided written informed consent.

Competing interests

The authors declare no competing interests.