2025 Volume 72 Issue 7 Pages 831-838
The prevalence of metabolic syndrome (MS) is rising due to lifestyle changes. To investigate the pathogenesis of MS and identify potential biomarkers, bioinformatics tools were used to screen for MS-related genes, such as Fras-1-related extracellular matrix protein 2 (FREM2), and miRNAs, including miR-28-5p and miR-424-5p. An insulin resistance (IR) cell model was established by treating human liver cells with insulin. The roles of FREM2, miR-28-5p, and miR-424-5p in IR were examined through overexpression and silencing experiments. Transfection of miR-28-5p/miR-424-5p mimics and a dual-luciferase assay were performed to explore their regulation of FREM2. The diagnostic value of miR-28-5p/miR-424-5p in MS was assessed using the receiver operating characteristic (ROC) curve. Increased expression of FREM2 and suppression of miR-28-5p/miR-424-5p enhanced glucose uptake in IR cells. Transfection with miR-28-5p or miR-424-5p mimics reduced luciferase activity in cells transfected with the wild-type FREM2 reporter vector and suppressed FREM2 expression. The ROC curve analysis indicated that miR-28-5p and miR-424-5p serve as effective classifiers for MS, with their combined use offering higher reliability. In conclusion, miR-28-5p and miR-424-5p exacerbated IR progression in human liver cells (HHL-5) through the negative regulation of FREM2, and they are potential biomarkers for MS.
MS is a multifaceted pathological condition characterized by abnormalities in the metabolism of key components such as proteins, carbohydrates, and lipids. It encompasses central obesity, hypertension, dyslipidemia, hyperglycemia, and insulin resistance, all of which increase the risk of cardiovascular diseases, diabetes, cancer, and other health problems [1-3]. The rising incidence of MS is largely due to poor dietary habits and sedentary lifestyles. While the exact causes of MS remain unclear, it is believed to result from the interplay of multiple genetic and environmental factors, with immune and genetic influences playing significant roles [4].
Insulin resistance, a central feature of MS, occurs when insulin loses its physiological effectiveness. This condition arises from the malfunction of insulin receptors in cells and tissues, leading to reduced glucose uptake and an inability to lower blood glucose levels effectively [5, 6]. MicroRNAs have become a key focus in molecular and cellular biology, playing essential roles in regulating various physiological and pathological processes within the human body. Nguyen et al. showed that miR-183-5p can suppress the expression of insulin receptor substrate-1 by targeting its 3' UTR, thus impacting insulin signaling [7]. Gonzalez-Lopez et al. suggested that miR-155-5p and miR-143-3p are involved in vascular insulin resistance in atherosclerotic plaques by modulating the expression of protein kinase B and the insulin-like growth factor type II receptor, respectively [8].
However, despite some evidence suggesting the potential involvement of miRNAs in insulin resistance (IR), the mechanisms by which they contribute to IR and metabolic disorders remain poorly understood. This study aimed to develop an IR liver cell model using 10 μg/mL insulin to investigate the role of the miR-28-5p/miR-424-5p-FREM2 pathway in IR and evaluate the diagnostic potential of miR-28-5p and miR-424-5p for MS.
The datasets GSE260666, GSE235696, and GSE227788 were accessed from the Gene Expression Omnibus (GEO) database. The GeneCards and starBase databases were employed to identify MS-related genes and predict upstream miRNAs that target FREM2, respectively.
2.2 VolunteersThe study included healthy volunteers and MS patients from The Affiliated Chuzhou Hospital of Anhui Medical University. Their basic information and peripheral blood samples were collected and stored (Supplementary Table 1). Informed consent was obtained from all participants, and the study was approved by the Ethics Committee of The Affiliated Chuzhou Hospital of Anhui Medical University.
2.3 Cells and TreatmentThe HHL-5 cell line was provided by Qingqi Biotechnology Development Co., Ltd. The cells were cultured in DMEM high-glucose medium with 10% fetal bovine serum (FBS) and 1% penicillin/streptomycin, at 37°C in a 5% CO2 incubator.
The IR model was established by incubating HHL-5 cells with 10 μg/mL insulin for 36 h [9]. Glucose metabolism in the cells was evaluated by measuring the glucose concentration in the culture supernatant using the Glucose Assay Kit.
For transfection, exogenous RNA or DNA was mixed with Optimal-MEM medium and Lipo6000TM Transfection Reagent and incubated for 15 min at room temperature. The mixture was added to cells cultured in 6-well plates. After 8 h of incubation at 37°C, the old medium was replaced with fresh medium, and the cells were cultured for an additional 24–48 h before proceeding with further experiments.
2.4 Real-time Quantitative PCR (RT-qPCR)Total RNA was isolated using TRIzol reagent (Invitrogen) and used as the template for RT-qPCR in a real-time PCR system, with a SuperScript IV one-step RT-PCR kit. GAPDH acted as the internal reference gene for FREM2 expression, while U6 was used as the internal control for miR-28-5p and miR-424-5p. The relative expression levels of genes or miRNAs were calculated using the 2–ΔΔCt method. The sequences of the primers are provided below:
FREM2 (F/R): 5'-TGAGCCAACTGTGTTTATTC-3'/5'-GTATAACAGACCACCATCAAC-3';
miR-28-5p (F/R): 5'-GCGCATTGCACTTGTCTCG-3'/5'-AGTGCAGGGTCCGAGGTATT-3';
miR-424-5p (F/R): 5'-AGCAGCAATTCATGTTTTG-3'/5'-GAACATGTCTGCGTATCTC-3';
GAPDH (F/R): 5'-GTAACCCGTTGAACCCCATT-3'/5-CCATCCAATCGGTAGTAGCG-3;
U6 (F/R): 5'-CTCGCTTCGGCAGCACA-3'/5'-AACGCTTCACGAATTTGCGT-3'.
2.5 Western BlottingTotal protein was extracted from the supernatant using RIPA lysis buffer. Proteins were separated by SDS-PAGE and transferred to a PVDF membrane, which was incubated in skim milk powder for 2 h. Afterward, the membrane was incubated with anti-FREM2/GAPDH antibodies at 4°C overnight. The following day, the membrane was incubated with a mouse secondary antibody for 1.5 h, and protein signals were detected using an ECL chemiluminescence detection kit.
2.6 Dual-Luciferase Reporter AssayThe mimics of miR-28-5p/miR-424-5p (mim-28-5p/mim-424-5p) (RiboBio, China) or their corresponding negative controls (mim-NC) were co-transfected into HHL-5 cells along with luciferase vectors containing either wild-type or mutant FREM2, using liposome-mediated transfection (see method 2.3). After 48 h, luciferase activity was measured using the Firefly Luciferase Reporter Gene Detection Kit II (Beyotime, China). Briefly, the cells were lysed, and the lysate was centrifuged at 10,000–15,000×g for 3–5 min. The supernatant was collected for analysis. Luciferase activity was quantified in a 96-well plate by mixing 100 μL of the cell lysate with 100 μL of the firefly luciferase detection reagent.
2.7 Detection of PI3KThe Human Phosphoinositide 3-Kinase (PI3K) ELISA kit (mlbio, China) was used to evaluate the production of PI3K. Cell cultures were taken and centrifuged at 1,000×g for 10 min to remove particles and polymers. The samples were incubated simultaneously with biotin-labeled antibodies. After washing, avidin-labeled HRP was added, incubated at 37°C for 30 min, and then washed to remove the unbound enzyme conjugate. Then substrate A/B was added to incubate for 10 min at 37°C away from light. Finally, OD values of each hole were measured at 450 nm wavelength immediately after the termination solution was added.
2.8 Evaluation of the Diagnostic Value of miR-28-5p/miR-424-5pSPSS software was used to construct ROC curves to evaluate the diagnostic value of miR-28-5p/miR-424-5p in MS. The predictive value of various clinical factors for MS risk was assessed through multi-factor binary logistic regression analysis in the same software.
2.9 Statistical AnalysisAll statistical analyses were performed using GraphPad Prism 5.0 software, with Student’s t-test or one-way ANOVA. A p-value of ≤ 0.05 was considered statistically significant.
Non-alcoholic fatty liver disease (NAFLD) is a major feature of MS [10]. FREM2 was found to be downregulated (p < 0.05, log2FC < –1) in liver tissue from NAFLD patients (GSE260666) and in visceral adipose tissue from overweight individuals (GSE235696) using GEO2R analysis within the GEO database. It was also identified as a gene likely associated with MS in the GeneCards database (Supplementary Fig. 1). Our results show that FREM2 expression was lower in the peripheral blood of overweight individuals compared to normal-weight controls (Fig. 1A), and it was further downregulated in the peripheral blood of MS patients (Fig. 1B). Insulin treatment (10 μg/mL) for 48 h notably weakened glucose metabolism in HHL-5 cells (Fig. 1C). FREM2 expression was found to be lower in insulin-resistant cells (Fig. 1D, E). Transfection of FREM2 plasmid (p-FREM2) led to a significant increase in its expression (Fig. 1F, G), which enhanced glucose uptake in HHL-5 cells (Fig. 1H). Additionally, overexpression of FREM2 resulted in increased PI3K production (Fig. 1I). These findings suggest that FREM2 negatively regulates insulin resistance in HHL-5 cells.
To understand the mechanisms behind insulin resistance, miRNAs that regulate FREM2 were predicted using the starBase database. MiR-28-5p and miR-424-5p were found to be significantly altered (p < 0.05, log2FC > 1) in the plasma of obese children in the GSE227788 dataset (Fig. 2A). Transfection with miR-28-5p and miR-424-5p mimics significantly increased their levels inside the cells (Fig. 2B, C), leading to reduced luciferase activity in cells co-transfected with the luciferase vector of wild-type (wt) FREM2 (Fig. 2D). The upregulation of miR-28-5p and miR-424-5p led to a decrease in FREM2 expression (Fig. 2E, F). In contrast, the use of miR-28-5p/miR-424-5p inhibitors suppressed their levels (Fig. 2G, H), resulting in an increase in FREM2 expression (Fig. 2I, J). These results confirm that miR-28-5p and miR-424-5p downregulate FREM2 expression.
The levels of miR-28-5p and miR-424-5p were elevated in HHL-5 cells with IR (Fig. 3A, B). Inhibition of miR-28-5p or miR-424-5p promoted glucose consumption in IR HHL-5 cells, and this effect was reversed by co-transfection with FREM2 small interfering RNA (siFREM2) (Fig. 3C, D). Additionally, the knockdown of FREM2 reversed the increase in PI3K production caused by the miR-28-5p/miR-424-5p inhibitors (Fig. 3E, F), suggesting that miR-28-5p and miR-424-5p contribute to the progression of IR via the regulation of FREM2.
Due to their stable expression in human body fluids, circulating miRNAs are considered potential biomarkers for disease diagnosis [11]. Consequently, the diagnostic value of miR-28-5p and miR-424-5p in MS was evaluated. Both miR-28-5p and miR-424-5p were found to be abnormally expressed in MS patients (Fig. 4A, B), and the ROC curve analysis demonstrated that they are reliable classifiers for MS, with AUC of 0.815 and 0.863, respectively. Their combined use provided a higher accuracy for predicting MS (AUC = 0.934) (Fig. 4C). Furthermore, multivariate logistic regression analysis confirmed that miR-28-5p and miR-424-5p are significant risk factors for MS (p < 0.001) (Table 1).
| Factors | OR | 95% CI | p value | |
|---|---|---|---|---|
| Lower | Upper | |||
| Age | 1.191 | 0.542 | 2.615 | 0.664 |
| Gender | 1.053 | 0.466 | 2.382 | 0.901 |
| BMI | 2.732 | 1.234 | 6.046 | 0.013 |
| Drinking | 1.496 | 0.669 | 3.347 | 0.327 |
| Smoking | 1.145 | 0.516 | 2.539 | 0.739 |
| HTG | 2.530 | 1.069 | 5.985 | 0.035 |
| HT | 2.425 | 1.061 | 5.540 | 0.036 |
| miR-28-5p | 1.948 | 1.567 | 2.422 | <0.001 |
| miR-424-5p | 3.059 | 2.197 | 4.258 | <0.001 |
Notes: BMI, body mass index; HTG, hypertriglyceridemia; HT, hypertension; OR, odds ratio; CI, confidence interval.
MS encompasses a range of metabolic disturbances often linked to obesity, defined by the World Health Organization as impaired fasting blood glucose or IR, hypertension, dyslipidemia, central obesity, or microalbuminuria [12]. While current diagnostic methods for MS are effective, identifying new biomarkers could offer valuable insights into the pathogenesis and treatment of MS.
As crucial regulators of gene expression, miRNAs present a promising avenue for biomarker development. For instance, the serum level of miR-200b can distinguish lung cancer (LC) patients from those without LC with high accuracy. Sensitivity and specificity for diagnosing LC using hsa-miR-210 or miR-126 in plasma were found to be 86% and 97%, respectively [13, 14]. Moreover, elevated levels of hsa-miR-200, hsa-miR-21, miR-183, hsa-miR-182, and hsa-miR-210 are linked to greater malignancy in LC tumors [15]. Increased expression of miR-155 and miR-146b is associated with poorer survival outcomes in LC patients. Additionally, plasma levels of hsa-miR-21 and hsa-miR-34 are related to LC relapse [16]. In atherosclerosis, circulating levels of miR-155 are significantly lower compared to healthy individuals, while miR-212 is upregulated in the serum of affected patients. Combining miR-212 with other markers such as hemoglobin A1c, HDL cholesterol, and lipoprotein (a) improves the diagnostic accuracy for atherosclerosis [17, 18]. Research by Heneghan et al. highlighted that reduced miR-17-5p expression correlates with increased body mass index [19]. Ramzan et al. found a deficiency of miR-17-5p in MS patients and also noted that miR-15a-5p negatively correlated with elevated visceral fat and triglyceride levels, suggesting that both miR-17-5p and miR-15a-5p could serve as predictors for MS [20]. A study of 100 MS patients and 50 healthy controls showed elevated levels of miRNA-33a and miR-122 in MS patients, with sensitivity and specificity values of 87%/83% and 95%/92%, respectively, for differentiating MS from healthy individuals [21]. In this study, we examined the diagnostic potential of circulating miR-424-5p and miR-28-5p in MS. Both miRNAs were found to be highly expressed in MS patient blood, with their elevated levels acting as risk factors for MS. Their combined predictive power yielded a high accuracy (AUC = 0.934), demonstrating their potential as effective biomarkers for MS.
In HepG2 cells treated with palmitoleic acid and livers of mice with high-fat diet-induced obesity, miR-424-5p is upregulated and inhibits INSR expression by binding to its 3' UTR, which results in impaired glycogen synthesis and insulin signaling [22]. While the role of miR-28-5p has been studied in diseases like cancer, carotid artery stenosis, and Down’s syndrome [23-25], the involvement of miR-424-5p in MS has not been previously reported. In our experiments, both miR-28-5p and miR-424-5p were found to be upregulated in the IR cell model, where they inhibited glucose uptake by liver cells. FREM2, a shared target gene of miR-28-5p and miR-424-5p, is linked to abnormal eye and kidney development when mutated or dysfunctional [26, 27]. However, its role in MS was not known. Our findings show that FREM2 was upregulated in MS patients and in IR-HHL-5 cells. MiR-28-5p and miR-424-5p reduced FREM2 expression by binding to its 3' UTR, thus promoting the progression of IR.
In conclusion, our study demonstrated that miR-28-5p and miR-424-5p are reliable biomarkers for predicting MS and are involved in the IR process of liver cells through the regulation of FREM2 (Graphical Abstract).
None of the authors have any potential conflicts of interest associated with this research.
FundingThis article did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.
