2025 Volume 72 Issue 1 Pages 79-91
Circular RNAs (circRNAs) play an important role in regulating inflammation and oxidative stress during the pathogenesis of metabolic dysfunction-associated steatotic liver disease (MASLD); however, the underlying mechanism is unclear. This study aimed to determine the role of mmu_circ_0009303 in MASLD. We used a bioinformatics approach to identify potential targets and established an in vitro model of MASLD. Oil red O staining, cell transfection and dual-luciferase reporter assay were used to determine the role of mmu_circ_0009303. The results indicated that the mmu_circ_0009303 expression was significantly increased in the MASLD model both in vitro and in vivo and was associated with oxidative stress levels and inflammation. Moreover, bioinformatics analyses revealed that miRNA-182-5p and Foxo3 are targets of mmu_circ_0009303 and miRNA-182-5p, respectively. In the in vitro MASLD model, mmu_circ_0009303 promoted fat deposition in NCTC1469 cells, which was induced by free fatty acid (FFA) through the regulation of miRNA-182-5p/Foxo3. The expression of miRNA-182-5p and Forkhead box O3 (Foxo3) was associated with mmu_circ_0009303 expression in the liver of mice with MASLD, which was induced by a high-fat diet. Furthermore, mmu_circ_0009303 may be involved in regulating the expression of lipid metabolism-related regulatory proteins, such as CPT1A, SLC27A4, ACBD3, SREBP1, FAS, PPARα, and PPARγ. Taken together, mmu_circ_0009303 promotes oxidative stress, inflammation, and excessive fat accumulation in NCTC1469 cells induced by FFA through the regulation of miRNA-182-5p/Foxo3 and lipid metabolism-related regulatory proteins. These findings provide a potential target for the treatment of MASLD.
In recent years, the incidence of metabolic dysfunction-associated steatotic liver disease (MASLD) has markedly increased worldwide, which poses a serious threat to public health. The occurrence and development of MASLD are associated with a liver fat metabolism disorder that results in excessive fat deposition in the liver, leading to the accumulation of inflammatory substances and steatosis. If these are not well controlled, they may develop into liver fibrosis, cirrhosis, or even hepatocellular cancer [1-3]. All histological stages of MASLD are associated with significantly increased overall mortality, most of which results from extrahepatic cancer and cirrhosis [4-6]. Lifestyle intervention and drug therapy are the primary treatments for MASLD; however, the benefits of lifestyle intervention are limited and drug therapy involves side effects such as weight gain and increased mortality [7]. Therefore, it is necessary to determine the molecular mechanism underlying this disease and identify new biomarkers and treatment targets.
Noncoding RNAs (ncRNAs) are a class of RNAs that do not encode proteins. They are classified as long and small RNAs based on their length [8]. Small RNAs can be further categorized into small housekeeping ncRNAs, which include transfer, small nucleolar, and small nuclear RNAs as well as small regulatory ncRNAs, such as PIWI-interacting RNAs, circular (circRNAs), and microRNAs. Long RNAs may be similarly classified [8]. CircRNAs are endogenous RNAs formed by reverse splicing linear precursor mRNA. They are resistant to degradation by RNase R exonuclease and are more stable than linear mRNAs [9, 10]. With the advancement of RNA sequencing technology, several studies have determined that circRNAs regulate gene expression at the transcriptional and post-transcriptional levels by acting as miRNA sponges and through interactions with lncRNA, mRNA, and proteins [11]. Because of their stability in the circulation, they are potential biomarkers and therapeutic targets; thus, circRNAs have recently attracted significant attention [11, 12]. Currently, research on circRNAs in liver diseases has primarily focused on liver cancer and hepatitis [13]. Only a few studies have shown that they play a role in regulating inflammation and oxidative stress during MASLD pathogenesis [14-16]. Nonetheless, a specific role for circRNAs in MASLD requires further exploration.
We previously analyzed the GEO database (GSE94841) and found that the expression of mmu_circ_0009303 was significantly increased in a MASLD mouse model. In the present study, we established an in vitro MASLD model to determine the effect of modulating mmu_circ_0009303 expression on adipocyte lesions and explore its underlying mechanism of action.
NCTC 1469 cells were purchased from iCell Bioscience Inc. (Shanghai, China) and cultured in Dulbecco’s modified Eagle’s medium (Gibco, Invitrogen, USA) supplemented with 10% horse serum and 1% penicillin/streptomycin at 37°C in a humidified atmosphere containing 5% CO2. The cells were treated with 600 or 800 μM free fatty acids (FFA) (oleic acid: palmitic acid = 2:1) for 24 h to establish the NAFLD cell model [17].
Cell transfectionsiRNA-NC and siRNAs, specific to different sites on mmu_circ_0009303, were designed by General BioL (An’Hui, China). NCTC-1469 cells were seeded onto a 96-well plate at a density of 2.5 × 104 cells/well. Transfection was done using Lipofectamine TM 2000 reagent (Invitrogen, USA), and the cells were cultured at 37°C in a 5% CO2 atmosphere.
AnimalsFor the in vivo experiments, 20 6-week-old specific pathogen-free male C57BL/6 mice, weighing 20 ± 2 g, were obtained from the Shanghai Shrek Experimental Animal Co., Ltd. All mice were reared under a 12-h light/dark cycle (temperature 25°C ± 2°C, humidity 60% ± 5%). After acclimating for 1 week, the mice were divided into a control group and a high-fat diet group. The high-fat diet group was used to establish the MASLD model. After 16 weeks, serum and liver tissues were collected. All animal experiments were performed in accordance with ethical practices adhering to international regulations (NIH Guide for the Care and Use of Laboratory Animals, NIH Publication No. 85-23, 1985, revised 1996). The Kunming Medical University Ethical Committee approved all animal protocols.
qRT-PCR analysisCells and liver tissues were collected, and total RNA was extracted using the UNlQ-10 Column Trizol Total RNA Isolation Kit (Sangon Biotech, Shanghai, China). Reverse transcription was performed using the EasyScript® One-Step gDNA Removal and cDNA Synthesis SuperMix kits (TransGen Biotech, Beijing, China). cDNA was amplified using TransStart® Top Green qPCR SuperMix (TransGen Biotech) on an LC96 real-time PCR Detection System (Roche, Switzerland). The reactions were performed in triplicate using specific primer sequences for mmu_circ_0009303, Trmp7, miR-182-5p, Forkhead box O3 (Foxo3), and GAPDH (Table 1). The relative expression was normalized and calculated using the 2–ΔΔ Ct method [18].
| Primer names | Primer sequences |
|---|---|
| mmu_circ_0009303 F | 5'-GTTTATGGACAACAGTGGCTGGTTGG-3' |
| mmu_circ_0009303 R | 5'-CCAACCAGCCACTGTTGTCCATAAAC-3' |
| Trmp7 F [16] | 5'-ATGGCACTGTTG GAAAGTATGG-3' |
| Trmp7 R | 5'-CGCCTTCAAATATCAAAGCCAC-3' |
| miR-182-5p F [17] | 5'-ATCACTTTTGGCAATGGTAGAACT-3' |
| miR-182-5p R | 5'-TATGGTTTTGACGACTGTGTGAT-3' |
| Foxo3 F [18] | 5'-CGGACAAACGGCTCACTCT-3' |
| Foxo3 R | 5'-GGACCCGCATGAATCGACTAT-3' |
| GAPDH F [14] | 5'-GTTGTCTCCTGCGACTTCA-3' |
| GAPDH R | 5'-GCCCCTCCTGTTATTATGG-3' |
The viability and proliferation of transfected NCTC 1469 cells were determined using the cell counting kit-8 (CCK-8; Beyotime, Shanghai, China) assay. Briefly, NCTC 1469 cells were seeded onto 96-well plates at a density of 2.5 × 104 cells/well. The cells were transfected and treated for 24 h. Subsequently, 10 μL of CCK8 solution was added to each well and incubated at 37°C for 2 h. The absorbance was measured at 450 nm.
Flow cytometryApoptosis was detected using the Annexin V-FITC/PI double-staining apoptosis detection kit (Nanjing Jiancheng, Nanjing, China). Briefly, 2 × 105 cells were centrifuged at 1,000 × g for 5 min, and 500 μL of conjugation solution was added to gently resuspend the cells after the supernatant was discarded. Annexin V-FITC (5 μL) and propidium iodide (5 μL) were added. Flow cytometry displayed annexin V-FITC as green fluorescence and PI as red fluorescence. Intracellular ROS levels were measured using the ROS Assay Kit (Beyotime). Following transfection and treatment of the cells for 24 h, 2',7'-dichlorofluorescein-diacetate was added and the reactions were incubated at 37°C for 20 min based on the manufacturer’s instructions. The DCF fluorescence distribution of the cells was observed under a fluorescence microscope and measured at 488 nm excitation and 525 nm emission.
Oil red O and hematoxylin and eosin (H&E) stainingThe cells were fixed with formaldehyde and calcium for 10 min, washed with 60% isopropanol, stained with oil red O (Solarbio, Beijing, China) for 10 min, differentiated into clear stroma with 60% isopropanol, and re-stained with Mayer’s hematoxylin. The cells were observed and photographed under a microscope. The liver tissue was stained with oil red O and H&E. The fixed liver tissue was cut into 5-μm slices and stained with H&E. The hepatocytes were observed under a microscope.
Dual-luciferase reporter assayThe binding sites of mmu_circ_0009303 and Foxo3 to miR-182-5p were predicted using miRtarbase, TarBase v.8, or the regRNA and miRDB databases. To validate the association between mmu_circ_0009303 and miR-182-5p, miR-296-5p, and Foxo3, the sequences of the wild-type and mutant mmu_circ_0009303, wild-type and mutant Foxo3 3'-UTR, miRNA mimics, and miRNA NC were cloned into the pGL3 vector (Promega, USA) to form recombinant plasmids. NCTC 1469 cells were seeded onto 96-well plates and cotransfected with the indicated plasmids. After transfection for 48 h, fluorescence intensity was detected using a dual-luciferase reporter assay system (Promega) based on the manufacturer’s instructions.
Western blot analysisTotal proteins from samples collected from each group were extracted with RIPA lysis buffer (Applygen Technologies Inc., Beijing, China). Protein concentration was determined using the BCA kit (Solarbio). The proteins were separated by 12% sodium dodecyl sulfate-polyacrylamide gel electrophoresis (MultiSciences, Hangzhou, China), transferred onto PVDF membranes, and blocked with 5% skim milk at 25°C for 90 min. The membranes were incubated overnight at 4°C with the following primary antibodies diluted 1:1,000: anti-CPT1A (CST12252, 1:1,000, Cell Signaling Technology, USA), anti-SLC27A4 (ab200353), anti-ACBD3 (ab134952), anti-FAS (ab133619), anti-Foxo3 (ab109629), anti-PPARα (ab215270), and anti-PPARγ (ab178860, Abcam, UK). The membranes were then incubated with HRP-conjugated secondary antibodies (SE134 or GB23301, 1:1,000, Solarbio) at 25°C for 90 min, and the bands were visualized using an ECL chromogenic reagent (PE0010, Solarbio).
Enzyme-linked immunosorbent assayThe cells were collected, lysates were prepared, and centrifuged at 12,000 r/min for 10 min. The concentrations of interleukin-6 (IL-6) and tumor necrosis factor α (TNF-α) were measured using enzyme-linked immunosorbent assay (ELISA) kits.
Biochemical testThe cells were pretreated as described for the ELISA. The concentration or activity of triglyceride (TG), malondialdehyde (MDA), and superoxide dismutase (SOD) was determined according to the manufacturer’s instructions. The plasma concentration of nonesterified fatty acid (NEFA) was also detected using a kit, whereas concentrations of total cholesterol (TC), TG, low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein (HDL-C), alanine aminotransferase (ALT), and aspartate aminotransferase (AST) were determined using an automatic biochemical analyzer (Beckman, California, USA).
Statistical analysisAll data are presented as the mean ± standard deviation (SD). The differences in the relative expression of mmu_circ_0009303 or Trpm7 between the control and 600-μM treatment groups were analyzed using an unpaired two-sided t-test. Differences were analyzed using a one-way analysis of variance with Tukey’s test, and p < 0.05 was considered statistically significant.
To confirm our previous findings that the expression of mmu_circ_0009303 was significantly increased in a mouse model of MASLD, we established a MASLD model in vitro and found that the concentrations of TG, IL-6, and TNF-α and MDA activity in the model groups were significantly higher than those in the control group (p < 0.001). In contrast, the activity of SOD in the model groups was lower than that in the control group (p < 0.001) (Fig. 1A–E). Flow cytometry revealed that ROS levels in the model cells increased significantly in a dose-dependent manner (p < 0.001) (Fig. 1F and G). Oil red O staining revealed a blue nucleus and a large number of red fat droplets in the model group cells, whereas there were almost no red fat droplets in the control cells (p < 0.001) (Fig. 1H and I). The expression of mmu_circ_0009303 in the MASLD model cells was significantly upregulated in a dose-dependent manner (p < 0.001) (Fig. 1J), and it was primarily expressed in the cytoplasm (Fig. 1K). Similar to mmu_circ_0009303, Trpm7 expression was primarily expressed in the cytoplasm (Fig. 1L). mmu_circ_0009303 expression did not change significantly in the control or model NCTC 1469 cells treated with RNase R (p > 0.05) (Fig. 1M), whereas Trpm7 expression decreased significantly (p < 0.001) (Fig. 1N).
To determine the role of mmu_circ_0009303 in MASLD model cells, we observed cell growth after silencing mmu_circ_0009303. The results of the CCK-8 assay and flow cytometry indicated that the cell viability of the FFA + si-CircRNA group was significantly higher than that of the FFA and FFA + si-Circ-NC groups (p < 0.001) (Fig. 2A and B). ROS levels in the FFA + si-CircRNA group were markedly lower than those in the FFA and FFA + si-Circ-NC groups (Fig. 2C). The number of red fat droplets and apoptotic cells in the FFA + si-CircRNA group was significantly lower than that in the FFA and si-Circ-NC groups (p < 0.001) (Fig. 2D and E). MDA and TG concentrations in the FFA + si-CircRNA group were lower than those in the FFA and FFA + si-Circ-NC groups, whereas changes in SOD in these groups were opposite to those observed for MDA and TG (p < 0.001) (Fig. 2F–H). The results of western blot analysis revealed that the expression levels of CPTIA, SLC27A4, and ACBD3 proteins in the FFA + si-CircRNA group were significantly higher than those in the FFA and si-Circ-NC groups, whereas those of SREBP1 and FAS in the FFA + si-CircRNA group were significantly lower than those in the FFA and si-Circ-NC groups (p < 0.001) (Fig. 2I–N).
To determine the mechanism of inhibition of mmu_circ_0009303 in ameliorating MASLD in the model cells, we found that mmu-mir-182-5p was a target of mmu_circ_0009303 based on an analysis of the GSE94799 and miRDB databases. To confirm this finding, a dual-luciferase reporter assay was performed to determine whether mmu_circ_0009303 interacts directly with mmu-mir-182-5p (Fig. 3A). The results indicated that the luciferase activity of the circRNA (wt) + miRNA mimics was markedly lower than that of the circRNA (wt) + miRNA NC group (p < 0.01). The results for the circRNA (mut) + miRNA mimics group were similar to those of the circRNA (mut) + miRNA NC group (p > 0.05) (Fig. 3B). Quantitative RT-PCR analysis revealed that the expression of mmu-miR-182-5p in the MASLD model cells was significantly decreased (p < 0.001) (Fig. 3C). Moreover, oil red O staining revealed that the number of red fat droplets in the FFA + si-circRNA-0009303 + mmu-miR group was significantly lower than that in the FFA, FFA + mmu-miR-182-5p mimics, and FFA + si-circRNA-0009303 groups (p < 0.001) (Fig. 3D and E). Meanwhile, the CCK8 assay revealed that the absorbance in the FFA + si-circRNA-0009303 + mmu-miR group was significantly higher than that of the FFA, FFA + mmu-miR-182-5p mimics, and FFA + si-circRNA-0009303 groups (p < 0.001). The absorbance of the latter two groups was significantly higher than that of the FFA group (p < 0.001) (Fig. 3F). Changes in SOD IL-6, and TNF-α concentrations in the various groups were similar to the changes in cell proliferation in each group, whereas changes in TG, MDA, and ROS concentrations were opposite to the changes in cell proliferation in each group (Fig. 3G–K).
Our analysis of the miRDB and miRTarBase databases revealed that Foxo3 was a target of mmu-miR-182-5p. The expression of Foxo3 protein increased significantly in a dose-dependent manner in the MASLD model cells (p < 0.001) (Fig. 4A and B). Western blot analysis revealed that FoxO3 expression was closely associated with that of mmu-miR-182-5p and mmu_circ_0009303 (p < 0.001) (Fig. 4C and D). A dual-luciferase reporter assay was conducted to determine whether mmu-mir-182-5p directly interacts with Foxo3. The luciferase activity of the Foxo3 3'-UTR (wt) + miRNA mimics group (0.68 ± 0.03) was significantly lower than that of the Foxo3 3'-UTR (wt) + miRNA NC group (0.96 ± 0.02), whereas that of the Foxo3 3'-UTR + miRNA mutant group (0.97 ± 0.03) was unchanged compared with that of the Foxo3 3'-UTR + miRNA NC group (0.97 ± 0.04) (Fig. 4E). Oil red O staining revealed that the number of red fat droplets in the FFA + mmu-miR-mimics + si-Foxo3 group was lower than that in the FFA + si-Foxo3 group (p < 0.001) (Fig. 4F and G). Similarly, cell proliferation in the FFA group was significantly lower than that in the FFA + si-Foxo3 groups (p < 0.001), whereas cell proliferation in the FFA + mmu-miR-mimics + si-Foxo3 group was higher than that in the FFA + si-Foxo3 group (p < 0.001) (Fig. 4H). Furthermore, changes in SOD content and the ratio of IL-6 and TNF-α in these groups were similar to the changes in cell proliferation, whereas changes in TG and MDA concentrations in these groups were opposite to the changes in cell proliferation (Fig. 4I–L).
The arrangement of hepatocytes in the model group was disordered (Fig. 5A). There were a large number of fat droplets of varying sizes in the cells (blue arrows) as well as a large number of denatured or necrotic hepatocytes (red arrow), accompanied by severe inflammatory cell invasion (yellow arrow). Similarly, the area and depth of oil red O staining in the liver cells of the model mice were significantly increased (p < 0.001) (Fig. 5B and C). Moreover, biochemical analysis revealed that TC, TG, NEFA, LDL-C, ALT, and AST concentrations in the model group were significantly higher than those in the control group (p < 0.001), and the HDL-C concentration in the model group was significantly lower than that in the control group (p < 0.001) (Fig. 5D–G). To further verify our findings, we measured the expression levels of mmu_circ_0009303, mmu-miR-182-5p, and Foxo3 by qRT-PCR. The results indicated a downregulated expression of mmu-miR-182-5p (p < 0.001) and a significantly upregulated expression of mmu_circ_0009303 and Foxo3 in the liver of the model mice (p < 0.001) (Fig. 5H–J). This was consistent with the results of the cell model.
To further confirm our findings, oil red O staining revealed that the number of red fat droplets in the FFA + si-circRNA group was lower than that in the FFA group. Moreover, the number of fat droplets in the FFA + si-circRNA group was higher than that in the FFA + si-circRNA + mmu-miRNA mimics or FFA + si-circRNA + si-Foxo3 groups (p < 0.001) (Fig. 6A and B). The CCK8 assay revealed that the absorbance of the FFA + si-circRNA group was significantly higher than that of the FFA group. The absorbance of the FFA + si-circRNA group was lower than that of the FFA + si-circRNA + mmu-miRNA mimics or FFA + si-circRNA + si-Foxo3 group (p < 0.001) (Fig. 6C). Changes in TGA and MDA concentrations in these groups were similar to those observed in the CCK-8 assay. Changes in SOD activity and the concentration ratio of IL-6 and TNF-α in these groups were opposite to those of the CCK-8 assay (Fig. 6D–G). Changes in the expression of the CPT1A, SLC27A4, ACBD3, PPARα, and PPARγ proteins in these groups were similar to those of SOD activity, whereas changes in SREBP1 and FAS in these groups were similar to the changes in TG and MDA concentrations (Fig. 6H–O).
MASLD is considered a common chronic liver disease that is characterized by the accumulation of excessive fat in the liver [19]. In addition to the prevalence of diabetes and obesity, numerous studies indicate that many extrahepatic manifestations, such as chronic kidney disease, cardiovascular disease, and sleep apnea, are associated with MASLD [20]. Recent studies have found that circRNAs may be important targets for the treatment of MASLD [21-23]; however, because of the large number of circRNAs, their role in MASLD is unknown. In the present study, we found that the expression of mmu_circ_0009303 was abnormally increased in a mouse model of MASLD using a bioinformatics analysis, and this finding was confirmed in an in vitro model. We observed that its abnormal expression is associated with the level of oxidative stress and the inflammatory response. We found that it also promotes fat deposition in NCTC 1469 cells induced by FFA through the regulation of miRNA-182-5p/Foxo3. In the liver of MASLD mice fed a high-fat diet, the expression of miRNA-182-5p and Foxo3 was associated with that of mmu_circ_0009303. In addition, mmu_circ_0009303 was found to be involved in regulating the expression of lipid metabolism-related regulatory proteins, including CPT1A, SLC27A4, ACBD3, SREBP1, FAS, PPARα, and PPARγ. Our results provide evidence of the involvement of circRNAs in MASLD development and a potential target for treating MASLD.
MASLD is characterized by macrovascular steatosis in ≥5% of hepatocytes. It includes several liver diseases, such as fibrosis and cirrhosis [24]. The pathogenesis of MASLD remains unclear; however, insulin resistance and genetic variation in patatin-like phospholipase domain containing 3, and transmembrane 6 superfamily member 2 [25], may contribute to the progression of MASLD, indicating that rather than a “two-hit” hypothesis, it is characterized by a “multi-hit” model consisting of lipotoxicity, innate immune activation, and the microbiome [24]. Different molecular mechanisms are involved at each stage of MASLD, such as steatosis, which is the result of genetic factors, diet, gut microbiota, and de novo lipogenesis [25]. Meanwhile, steatosis activates NF-κB signaling and induces the production of proinflammatory factors, such as IL-6, TNF-α, and IL-1β, which contribute to inflammatory signaling and insulin resistance [26, 27]. Moreover, excessive fat accumulation leads to lipotoxicity mitochondrial dysfunction, and endoplasmic reticulum stress [28], which can further induce oxidative stress and apoptosis. In the present study, we observed that the level of oxidative stress in NCTC 1469 cells induced by FFA as well as the level of proinflammatory factors increased significantly. Concomitantly, there were a large number of red fat particles and apoptotic cells in this model. Furthermore, we observed the abnormal expression of some regulatory factors associated with lipid metabolism, including CPT1A [29], SLC27A4 [30, 31], ACBD3 [32], SREBP1 [33], and FAS [34], in the MASLD model cells.
A large number of studies have identified a role for circRNAs in tumor formation [35-37]. Some studies have indicated that they are involved in the pathogenesis of MASLD, whereas has_circ_0048179 and circRNA_0046367 have different roles in hepatic steatosis [15, 38]. In the present study, we performed bioinformatics analysis and validation to identify mmu_circ_0009303 and show that it is significantly overexpressed in MASLD model cells. The change in expression was associated with oxidative stress, proinflammatory factors, and cellular fat accumulation. It is recognized that circRNAs act as competitive endogenous RNAs to adsorb microRNAs to regulate gene expression by binding and isolating proteins [39, 40]. We found that miRNA-182-5p is a potential target of mmu_circ_0009303 through a bioinformatics analysis, which was confirmed in the MASLD model.
A previous study found that miR-182-5p stimulates Cyp7a1-mediated cholic acid production in hepatocytes and promotes hedgehog (Hh) ligand production in stellate cells. This leads to the activation of Hh signaling in hepatocytes and consequent hepatocyte proliferation [41]. Moreover, miR-182-5p mimics reduced TNF-α and IL-6 levels in the oleic acid treatment of HepG2 cells [42]. Moreover, miR-182-5p inhibits TC, TG, ROS, and MDA levels and apoptosis as well as enhances SOD activity [43]. Thus, miR-182-5p may play anti-inflammatory and anti-oxidative roles, thereby inhibiting cell apoptosis and promoting cell proliferation. Liu et al. demonstrated that miR-182-5p was sponged by circ_002664, which induced cell apoptosis and decreased cell proliferation and mitochondrial potential during oxygen-glucose deprivation and reoxygenation of HT22 cells [44]. Furthermore, many circRNAs, such as circ_0025202 [45], circ_0003570 [46], and circ_0105558 [47], act as a miRNA sponge for miR-182-5p and regulate cell apoptosis, oxidative stress, and inflammation. Our results suggest that circ_0009303 sponges miR-182-5p; however, more studies are needed to verify whether circ_0009303 regulates oxidative stress and inflammation by regulating miR-182-5p expression in MASLD. Similarly, we confirmed that FoxO3 is a target of miRNA-182-5p and that miRNA-182-5p/Foxo3 is involved in oxidative stress, proinflammatory factor production, and fat droplet deposition in NCTC 1469 cells induced by FFA. Finally, the expression of miRNA-182-5p and Foxo3 was found to be associated with that of mmu_circ_0009303 in the liver of MASLD mice induced by a high-fat diet.
In conclusion, we determined that mmu_circ_0009303 is involved in oxidative stress, inflammation, and excessive fat accumulation during the pathogenesis of MASLD by regulating miRNA-182-5p/Foxo3 expression. Our results provide insight into the involvement of circRNAs in the development of MASLD and identify a potential therapeutic target.
The authors declare that there are no conflicts of interest.
Author contributionsConceptualization: Zhiwen Duan, Ju Zhou, and Wu Li; Funding acquisition: Zhiwen Duan; Data curation: Ju Zhou and Wu Li; Methodology and Validation: Ju Zhou, Xiaowei Chi, Dingchun Li, and Chunxia Yang; Project administration and Supervision: Zhiwen Duan and Wu Li; Visualization: Ju Zhou and Wu Li; Roles/Writing-original draft: Ju Zhou; Writing-review & editing: Zhiwen Duan, Ju Zhou, Wu Li, Xiaowei Chi, Dingchun Li, and Chunxia Yang.
FundingThis work was supported by Basic Applied Research in Yunnan Province Yunnan [2017FE468(-173)].
Availability of data and materialsThe raw data are available from the corresponding author on reasonable request.
Ethics approval and consent to participateThis study has been approved by the Ethics Committee of the First Affiliated Hospital of Kunming Medical University.
