LncRNA NBR2 affects pancreatic β-cell function in type 2 diabetes mellitus by targeting miR-646

Abstract

Background

Type 2 diabetes mellitus (T2DM) is one of the major diseases threatening human health. This study aims to investigate the role of the NBR2/miR-646 axis in T2DM and pancreatic β-cell function.

Methods

95 T2DM patients and 83 healthy individuals were enrolled in the study. Serum NBR2 and miR-646 expression were detected by quantitative reverse transcription polymerase chain reaction. The diagnostic value of NBR2 in T2DM was evaluated using receiver operating characteristic curve. To assess cell viability and apoptosis, the cell counting kit-8 assay and flow cytometry were utilized. Enzyme-linked immunosorbent assay was employed to determine insulin secretion, levels of inflammatory factors, and oxidative stress. The interaction between NBR2 and its target was confirmed using luciferase reporter assay, and their association was evaluated through Pearson correlation analysis.

Results

Serum NBR2 expression was upregulated in T2DM patients, while miR-646 expression was decreased. NBR2 could serve as a biomarker for T2DM diagnosis, with an area under the curve of 0.908 (95% confidence interval : 0.866–0.950), sensitivity of 89.5%, and specificity of 79.5%, and was negatively correlated with miR-646. Inhibiting NBR2 could increase the viability of INS-1 cells, insulin secretion, and superoxide dismutase activity, while reducing apoptosis, as well as the levels of interleukin-6, tumor necrosis factor-α, and malondialdehyde. miR-646 was identified as a target of NBR2. Inhibiting miR-646 could partially reverse the protective effect of NBR2 inhibition on cell function damage.

Conclusion

NBR2 is highly expressed in T2DM patients and has potential value in T2DM diagnosis. NBR2 can participate in the regulation of pancreatic β-cell function by modulating miR-646.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13098-025-02017-8.

Background

Diabetes mellitus (DM) is a prevalent chronic metabolic disorder in clinical practice, with hyperglycemia as its core feature [1]. Among all DM patients, type 2 diabetes mellitus (T2DM) makes up more than 80% [2]. With the accelerating pace of population aging, the incidence rate of T2DM among the elderly population continues to rise, placing a heavy burden on society [3]. Insulin resistance and pancreatic β-cell dysfunction are core pathological features of T2DM [4]. Previous studies have confirmed that hyperglycemia plays a key role in inducing pancreatic β-cell apoptosis and affecting insulin secretion [5]. However, the specific mechanisms underlying pancreatic β-cell dysfunction remain unclear. Current research indicates that oxidative damage, endoplasmic reticulum stress, mitochondrial dysfunction, and glycolipid toxicity may all contribute to β-cell failure [6]. Given that impaired pancreatic β-cell function constitutes a key factor in the onset and progression of T2DM [7], further scientific research is urgently needed to explore its mechanisms in depth.

Long non-coding RNAs (LncRNAs), a category of non-coding RNA molecules that cannot be translated into proteins, have become promising disease diagnostic markers [8, 9]. Currently, extensive research has confirmed that lncRNAs play a crucial role in regulating pancreatic β-cell function and the pathogenesis of T2DM [10, 11]. For example, serum LINC-P21 was highly expressed in T2DM patients and caused damage to pancreatic β-cell function [6]. Recent studies found that NBR2 was upregulated in the peripheral blood of T2DM patients [12]. Liu et al. further revealed that NBR2 was a lncRNA induced by glucose deprivation, which interacted with AMPK and regulates its activity during glucose deprivation [13]. In addition, research demonstrated that NBR2 exhibited abnormal expression in the plasma of patients with heart failure and myocardial hypertrophy, and this abnormal expression affected myocardial hypertrophy and endoplasmic reticulum stress [14]. The above research findings suggest that NBR2 is associated with DM and vascular disease. Nevertheless, the specific role of NBR2 in the advancement of T2DM and the process of pancreatic β-cell dysfunction remains to be further clarified.

Targeting downstream microRNAs (miRNAs) has been recognized as the primary mechanism by which lncRNAs exert their regulatory effects [15]. Among them, miR-646 can be negatively regulated by NBR2. Currently, the role of miR-646 in DM and related complications has been extensively studied and reported. Research indicated that miR-646 was downregulated in human retinal microvascular endothelial cells (RMECs) and served a critical role in regulating the function of these cells [16]. However, the function of miR-646 in pancreatic β-cells is yet to be clarified.

Based on the aforementioned findings, we hypothesized that the NBR2 is upregulated in T2DM and contributes to pancreatic β-cell dysfunction by acting as a molecular sponge for miR-646. This study aims to analyze the expression and diagnostic value of NBR2 in T2DM patients, investigate its impact on pancreatic β-cell function, and elucidate the specific mechanisms by which NBR2 exerts these effects. This study aims to provide new biomarkers for the diagnosis of T2DM and further reveal the role of pancreatic β-cell dysfunction in the pathogenesis of T2DM.

Methods

Clinical case sample collection

The study included 95 T2DM patients and 83 healthy subjects who were treated at Yantai Yantaishan Hospital. According to the 1999 World Health Organization criteria, the diagnosis of diabetes mellitus was confirmed by an oral glucose tolerance test (OGTT) [6, 17, 18]. Inclusion criteria for the T2DM group: (1) Fasting plasma glucose (FPG) ≥ 7.0 mmol/L and/or a 2-hour plasma glucose (2 h PG) value ≥ 11.1 mmol/L; (2) No previous treatment with antidiabetic drugs or insulin. Exclusion criteria: (1) Patients with other types of diabetes, severe liver or kidney disease, severe cardiovascular disease, or malignant tumors; (2) Patients with chronic inflammation or infectious diseases; (3) Patients currently participating in other research projects. The blood glucose criteria for the healthy control group were: FPG < 6.1 mmol/L and 2 h PG < 7.8 mmol/L. All study procedures were approved by the Ethics Committee of Yantai Yantaishan Hospital, and all subjects signed informed consent forms. The sample collection and processing were as follows: Fasting venous blood (5 mL) was collected from all subjects and aliquoted into RNase-free Eppendorf tubes. Subsequently, the blood was centrifuged at 1500 r/min for 5 min to extract the serum, which was then stored at −80 °C for testing.

Cell culture

INS-1 cells were obtained from the Chinese Academy of Sciences Cell Bank (Shanghai, China). Roswell Park Memorial Institute (RPMI)−1640 complete medium containing 10% fetal bovine serum (FBS), 50 µM β-mercaptoethanol, and 1% penicillin-streptomycin. To construct a high-glucose (HG)-induced cell damage model, cells were cultured in medium containing 25 mM glucose (Sigma-Aldrich, Saint Louis, MO, USA) [20–22]. All reagents used for cell culture were purchased from Invitrogen Corporation (Carlsbad, CA, USA).

Oligonucleotides and cell transfection

Si-NBR2, miR-646 mimic, miR-646 inhibitor, and their negative controls were obtained from RiboBio (Guangzhou, Guangdong, China). For transfection and subsequent functional assays, INS-1 cells were seeded at a density of 2 × 10⁵ cells per well in a 6-well plate. Transfection was performed using Lipofectamine 2000 reagent (Invitrogen) according to the manufacturer’s instructions when the cell confluence reached approximately 70–80%. After transfection, cells were cultured for 48 h before collection for subsequent experiments. The control group in this study consisted of cells that underwent no treatment.

RNA expression detection

Total RNA was extracted using TRIzol reagent (Invitrogen) from serum samples and treated INS-1 cells. The extracted RNA was reverse transcribed using PrimeScript RT Reagent Kit (Takara, Dalian, China). The quantitative reverse transcription polymerase chain reaction (qRT-PCR) analysis was performed as follows: SYBR green I Master Mix kit (Invitrogen) was used on the ABI 7900 system (Applied Biosystems, Foster City, CA, USA). GAPDH and U6 served as reference genes. The relative expression levels of genes were calculated using the 2^−ΔΔCt formula. All primer sequences were listed in Table S1.

Cell Counting Kit-8 (CCK-8) assay

Cells were seeded in 96-well plates (Corning, NY, USA) at 2 × 10³ cells/well. At the indicated time points (0, 24, 48, and 72 h), 10 µL of CCK-8 solution (R&D Systems, Minneapolis, MN, USA) was added to each well. After 1 h incubation at 37 °C, absorbance at 450 nm was measured using a microplate reader (Thermo Fisher Scientific, Waltham, MA, USA).

Apoptosis assay

Apoptosis was analyzed by Annexin V-FITC and propidium iodide (PI) (BD Biosciences, San Jose, CA, USA). The specific procedure was as follows: collected cells were washed with cold PBS (Solarbio, Beijing, China). Next, cells were stained with 5 µL Annexin V-FITC and 5 µL PI in binding buffer at room temperature for 15 min. Apoptotic cells were quantified using a FACSalibur flow cytometer (BD Biosciences).

Glucose‑stimulated insulin secretion (GSIS) assay and cellular insulin content

Transfected cells were seeded into 96-well plates and starved overnight at 37 °C. Subsequently, the medium was replaced with a solution containing 25 mM glucose, and the cells were incubated for an additional hour. The processed INS-1 cell culture medium was collected for insulin secretion measurement. To determine total cellular insulin content, INS-1 cells were resuspended in acidic methanol (Sigma-Aldrich), subjected them to ultrasonic disruption, and the supernatant was collected for insulin quantification. Insulin levels were measured using an insulin enzyme-linked immunosorbent assay (ELISA) kit (Abcam, Cambridge, UK), with all procedures strictly adhering to the manufacturer’s protocol. Ultimately, insulin secretion capacity was assessed by normalizing the measured insulin secretion levels in the culture medium against the total insulin content within the cells.

ELISA assay

The supernatant was collected from the treated INS-1 cells for detection of the levels of relevant substances. Interleukin-6 (IL-6), and tumor necrosis factor-α (TNF-α) levels were measured using the corresponding ELISA kits (Abcam) and strictly following the kit instructions. The levels of malondialdehyde (MDA) and superoxide dismutase (SOD) in the supernatant of cells were analyzed using an ELISA kit from Nanjing Jiancheng Biotechnology Co. (Nanjing, Jiangsu, China) to assess the level of oxidative stress in the cells.

Dual-luciferase reporter assay

miRNAs that might be adsorbed by NBR2 sponges were predicted using the lncRNASNP2 tool. Potential target genes of miR-646 were predicted using the TargetScan, miRDB, EVmiRNA, and miRWalk databases. The 3’-untranslated region fragments of wild-type (WT) and mutant (MUT) genes for both NBR2 and CNOT6L were amplified and cloned into the pmirGLO reporter vector (Promega, Madison, WI, USA) to construct NBR2-WT, NBR2-MUT, CNOT6L-WT and CNOT6L-MUT plasmids. These plasmids were co-transfected into cells along with miR-646 mimics or inhibitors using Lipofectamine 2000. At 48 h post-transfection, luciferase activities were measured using the Dual-Luciferase Reporter Assay System (Promega).

RNA Immunoprecipitation (RIP) assay

The RIP assay was performed using the EZ-Magna RIP Kit (Millipore, Billerica, MA, USA) according to the manufacturer’s instructions. Briefly, INS-1 cells were lysed in RIP lysis buffer. A volume of 100 µL cell lysate was incubated with magnetic beads conjugated with anti-argonaute 2 (Ago2) antibody or control normal immunoglobulin G (IgG) (Millipore) overnight at 4 °C. The beads were then extensively washed to remove non-specifically bound RNAs. Subsequently, the combined RNA-protein complex was placed in a proteinase K buffer for agitated digestion. Finally, the immunoprecipitated RNAs were purified and analyzed by qRT-PCR.

Statistical analysis

Data analysis was performed using SPSS 23.0 (IBM, Armonk, NY, USA) and GraphPad Prism 7.0 (GraphPad Software, San Diego, CA, USA). All data results were expressed as mean ± standard deviation. Continuous variables between two groups were compared using t-test, categorical variables were compared using chi-square test, and comparisons between multiple groups were performed using analysis of variance (ANOVA). The association between NBR2 levels and clinical characteristics was assessed using the chi-square test. The diagnostic value of NBR2 in T2DM patients was evaluated by receiver operating characteristic (ROC) curve analysis. Pearson correlation coefficient was employed to examine the relationship between NBR2 and miR-646 in T2DM patients. All statistical tests were two-tailed. P < 0.05 was considered statistically significant.

Results

Baseline clinicopathological features

In T2DM patients, the levels of FBG and glycated hemoglobin (HbA1c) were significantly higher than in healthy subjects (P < 0.001), while other indicators showed no significant differences (Table 1).

Table 1.

Baseline characteristics of the study population

Characteristics	Healthy controls (n = 83)	T2DM patients (n = 95)	P value
Age (years)	59.58 ± 9.09	60.23 ± 8.13	0.613
Gender (male/female)	47/36	52/43	0.800
BMI (kg/m2)	25.18 ± 1.49	25.30 ± 1.47	0.599
Hypertension (yes/no)	38/45	46/49	0.725
HbA1c (%)	4.71 ± 0.89	7.64 ± 1.22	< 0.001
FBG (mmol/L)	4.61 ± 0.70	8.81 ± 1.33	< 0.001
TC (mmol/L)	4.64 ± 1.02	4.85 ± 0.85	0.149
TG (mmol/L)	1.80 ± 0.44	1.87 ± 0.44	0.290
HDL (mmol/L)	1.36 ± 0.12	1.32 ± 0.16	0.069
LDL (mmol/L)	2.42 ± 0.24	2.46 ± 0.33	0.370

T2DM, type 2 diabetes mellitus; BMI, body mass index; HbA1c, glycosylated hemoglobin; FBG, fasting blood glucose; TC, total cholesterol; TG, triglyceride; HDL, high density lipoproteins; LDL, low density lipoproteins. Data are expressed as n or mean ± standard deviation

NBR2 in patients with type 2 diabetes mellitus

Serum NBR2 expression was upregulated in T2DM patients compared with healthy subjects (P < 0.0001, Fig. 1A). Given the abnormal expression of NBR2 in T2DM patients, its diagnostic value was further evaluated using the ROC curve. The area under the curve (AUC) was 0.908 (95% confidence interval (CI): 0.866–0.950), with sensitivity and specificity of 89.5% and 79.5%, respectively (Fig. 1B), indicating that serum NBR2 can effectively distinguish between T2DM patients and healthy subjects and has good diagnostic value. In addition, based on the mean expression level of NBR2, T2DM patients were stratified into a high-expression group (n = 50) and a low-expression group (n = 45). The chi-square test results showed that NBR2 expression was closely related to FBG and HbA1c (P < 0.05, Table 2). In summary, the experimental data suggest that NBR2 may be an effective indicator for the diagnosis of T2DM.

Fig. 1.

Serum NBR2 expression and diagnostic value in T2DM patients. (A) Serum NBR2 was highly expressed in T2DM patients. (B) The diagnostic value of NBR2 for T2DM was evaluated using ROC curve. ^****P < 0.0001. The raw data (Ct values) of qRT-PCR was in Table S2

Table 2.

Correlation analysis of the expression of LncRNA NBR2 with the clinicopathological features of T2DM

Characteristics	cases (n = 95)	LncRNA NBR2		P value
		Low (n = 45)	High (n = 50)
Age				0.501
≤ 60	52	23	29
> 60	43	22	21
Gender				0.794
Male	52	24	28
Female	43	21	22
BMI				0.879
Low	52	25	27
High	43	20	23
Hypertension				0.619
Yes	46	23	23
No	49	22	27
HbA1c				0.031
Low	48	28	20
High	47	17	30
FBG				0.019
Low	45	27	18
High	50	18	32
TC				0.475
Low	47	24	23
High	48	21	27
TG				0.604
Low	48	24	24
High	47	21	26
HDL				0.501
Low	52	23	29
High	43	22	21
LDL				0.199
Low	53	22	31
High	42	23	19

T2DM, type 2 diabetes mellitus; BMI, body mass index; HbA1c, glycosylated hemoglobin; FBG, fasting blood glucose; TC, total cholesterol; TG, triglyceride; HDL, high density lipoproteins; LDL, low density lipoproteins. Data are expressed as n or mean ± standard deviation

The effect of NBR2 on INS-1 cell function

This study used HG treatment of pancreatic β cells to simulate the development of T2DM. As shown in Fig. S1, transfection of si-NBR2 in INS-1 cells significantly reduced NBR2 expression, indicating good transfection efficiency (P < 0.0001). HG induction upregulated NBR2 expression, while further transfection with si-NBR2 downregulated its expression (P < 0.0001, Fig. 2A). In terms of cell viability and apoptosis, HG induction inhibited cell viability and increased apoptosis rates, while inhibition of NBR2 promoted cell viability under HG induction and inhibited apoptosis (P < 0.01, Fig. 2B-C). ELISA analysis of insulin secretion revealed that HG induction inhibited insulin secretion in cells, whereas transfection with si-NBR2 increased HG-induced insulin secretion in cells (P < 0.01, Fig. 2D). In addition, after testing the inflammatory response and oxidative stress indicators of the cells, it was found that HG induction enhanced the inflammatory and oxidative stress responses of the cells, specifically manifested as increased levels of IL-6, TNF-α, and MDA, and decreased SOD activity (P < 0.05, Fig. 2E-F), while si-NBR2 transfection significantly weakened this effect.

Fig. 2.

Inhibition of NBR2 on HG-induced INS-1 cell function. (A) The relative expression of NBR2 in each group of cells were detected. (B) Cell viability was determined using the CCK-8 method. (C) Cell apoptosis was detected by flow cytometry. (D-F) The levels of insulin secretion, inflammatory factors, and oxidative stress were measured using the ELISA. ^*P < 0.05, ^**P < 0.01, ^***P < 0.001, ^****P < 0.0001

miR-646 could be used as a target for NBR2

To further investigate the molecular mechanism of NBR2, this study used the lncRNASNP2 online database to predict its potential targets and found that miR-646 and NBR2 had complementary binding sequences (Fig. 3A). The binding relationship between the two was verified using a dual luciferase reporter gene assay, with results shown in Fig. 3B: co-transfection of NBR2-WT and miR-646 mimic resulted in reduced luciferase activity; co-transfection of miR-646 inhibitor increased luciferase activity (P < 0.0001); co-transfection with NBR2-MUT had no significant effect on luciferase activity. RIP results showed that both NBR2 and miR-646 were significantly enriched in Ago2 immunoprecipitation complexes compared to the IgG control group (P < 0.0001, Fig. 3C). Further investigation into the clinical value of miR-646 in T2DM patients revealed that serum miR-646 was downregulated in T2DM patients (P < 0.0001, Fig. 3D). Pearson correlation analysis revealed that NBR2 levels in T2DM patients were negatively correlated with miR-646 levels (r = −0.772, P < 0.0001, Fig. 3E). In addition, cell experiments revealed that transfection with miR-646 inhibitors significantly reduced the expression of miR-646 in INS-1 cells (P < 0.001, Fig. S2). miR-646 was downregulated in HG-induced cells, and further inhibition of NBR2 increased miR-646 expression (P < 0.001). Co-transfection of si-NBR2 and miR-646 inhibitor into HG-induced INS-1 cells significantly reduced miR-646 expression (P < 0.05, Fig. 3F).

Fig. 3.

miR-646 was a target of NBR2. (A) Potential binding sites between NBR2 and miR-646. (B-C) The interaction between NBR2 and miR-646 was validated using luciferase reporter assay and RIP assay. (D) Serum miR-646 was downregulated in T2DM patients. (E) Pearson correlation analysis results. (F) The relative expression of miR-646 in each group of cells was detected. ^*P < 0.05, ^***P < 0.001, ^****P < 0.0001

miR-646 acted as a mediator of NBR2

We further investigated the regulatory role of miR-646 on INS-1 cell function. At the level of cell viability and apoptosis, as shown in Fig. 4A-B, under HG conditions, co-transfection with miR-646 inhibitor reversed the improvement in cell function mediated by si-NBR2, resulting in decreased cell viability and increased apoptosis (P < 0.05). For HG-induced insulin secretion, si-NBR2 upregulated secretion, but miR-646 inhibitor transfection reversed this upregulation (P < 0.001, Fig. 4C). In terms of inflammatory factors and oxidative stress, inhibition of miR-646 partially offset the inhibitory effect of si-NBR2 transfection on cells, resulting in increased levels of inflammatory factors and exacerbated oxidative stress (Fig. 4D-E), indicating that miR-646 participates in regulating the effect of NBR2 on INS-1 cell function.

Fig. 4.

miR-646 participated in NBR2-mediated functional regulation of INS-1 cells. (A) Cell viability was determined using the CCK-8 method. (B) Cell apoptosis was detected by flow cytometry. (C-E) The levels of insulin secretion, inflammatory factors, and oxidative stress were measured using the ELISA. ^*P < 0.05, ^**P < 0.01, ^***P < 0.001, ^****P < 0.0001

CNOT6L was a target gene of miR-646

The potential target genes of miR-646 were predicted using multiple online databases, including TargetScan, miRDB, EVmiRNA, and miRWalk. Venn diagram analysis identified 245 overlapping target genes (Fig. 5A). The TargetScan database further predicted a binding site between miR-646 and CNOT6L (Fig. 5B). To validate this interaction, we performed a dual-luciferase reporter assay. The results showed that co-transfection with CNOT6L-WT and miR-646 mimic significantly decreased luciferase activity, while co-transfection with CNOT6L-WT and miR-646 inhibitor increased luciferase activity (P < 0.0001). However, these effects were not observed when CNOT6L-MUT was transfected (Fig. 5C). Furthermore, qRT-PCR results confirmed this regulatory relationship: inhibition of miR-646 upregulated CNOT6L expression, whereas overexpression of miR-646 downregulated its expression (P < 0.001, Fig. 5D). These results indicate that CNOT6L is a direct target of miR-646.

Fig. 5.

CNOT6L was a target gene of miR-646. (A) Venn diagram. (B) Potential binding sites between miR-646 and CNOT6L. (C) The interaction between miR-646 and CNOT6L was validated using luciferase reporter assay. (F) The relative expression of CNOT6L in each group of cells was detected. ^***P < 0.001, ^****P < 0.0001

Discussion

Studies on pancreatic development and function have shown that lncRNA is associated with different stages of DM and can regulate multiple key genes involved in apoptosis and glucose-stimulated insulin secretion. Previous research has indicated that NBR2 is highly expressed in T2DM patients, but its specific role in T2DM remains unclear. This study focused on NBR2, first exploring its biological characteristics and functions in T2DM patients and pancreatic β cells, and then further investigating the mechanisms of action of NBR2 and its target miRNA in INS-1 cells. The findings demonstrated that NBR2 was upregulated in T2DM patients and could influence HG-induced INS-1 cell function by targeting miR-646, providing a theoretical foundation for the utilization of NBR2 in T2DM diagnosis and therapy.

Numerous studies have shown that lncRNA participates in the progression of T2DM and has the potential to become a biological marker for T2DM patients. However, there are still unknowns regarding the mechanisms related to T2DM [23]. In this study, we observed that NBR2 was highly expressed in T2DM patients. Clinical analysis showed that NBR2 had high sensitivity and specificity in diagnosing T2DM and could effectively distinguish between patients and healthy individuals. Previous T2DM studies found similar results, such as high expression of plasma LINC01018, with an AUC of 0.896, indicating good diagnostic value [20]. Further research found that NBR2 was significantly correlated with FBG and HbA1c levels, which was consistent with previous studies. Chen et al. found that serum PTGS2 expression was elevated in T2DM patients and was correlated with FBG [18]. In summary, NBR2 has the potential to become a biomarker for T2DM.

In the progression of T2DM, impaired pancreatic β-cell function and abnormal insulin secretion, as well as a decline in β-cell number and function, are considered to be core components of disease onset and progression [24, 25]. INS-1 cells possess many important characteristics of normal pancreatic β cells, and HG can simulate β cell dysfunction in T2DM. Therefore, INS-1 cells were selected for cell function experiments in this study [26]. Functional deficiency experiments showed that in HG-induced INS-1 cells, transfection with si-NBR2 reduced NBR2 expression, increased cell viability and insulin secretion levels, and reduced cell apoptosis, inflammatory factors, and oxidative stress levels. Similarly, Xu et al. found that SNHG1 inhibited cell proliferation and insulin secretion [27]. Inhibition of LEGLTBC increased glucose-induced apoptosis and reactive oxygen species production in INS-1 cells [21]. These studies indirectly confirm that NBR2 regulates the function of INS-1 cells induced by HG, suggesting that its abnormal expression may be involved in the occurrence of pancreatic β-cell dysfunction in the progression of T2DM.

LncRNAs often act as competitive endogenous RNAs, regulating function by competing with miRNA [28]. This study used the lncRNASNP2 online database for prediction and confirmed through luciferase assays that NBR2 and miR-646 interact with each other and exhibit a negative correlation. Further studies found that miR-646 was downregulated in both T2DM patients and HG-induced INS-1 cells. After inhibiting NBR2 and miR-646, cell viability and insulin secretion levels decreased, while cell apoptosis rates and inflammatory factor and oxidative stress levels increased, suggesting that miR-646 is likely involved in the regulation of DM progression. Previous research has shown that cell function is regulated by miRNAs, which mediate the occurrence and development of DM [29]. For example, miR-646 was downregulated in HRPE and ARPE-19 cells, and suppressing miR-646 reversed the protective effect of circ_0000615 and circ_0041795 siRNA against HG-induced cellular dysfunction [30, 31]. Based on this study and previous findings, miR-646 may participate in DM-related pathological processes by affecting cellular functions. Its regulatory role in HG-induced damage in different cellular models also provides clues for further understanding the pathogenesis of DM.

This study has several limitations. (1) The limited clinical sample size necessitates cohort expansion and multicenter validation to enhance the universal applicability of NBR2’s diagnostic value. (2) As a stress-responsive lncRNA, NBR2 is widely expressed in multiple metabolic tissues; however, its circulating origin and systemic regulatory functions remain unclear. (3) Beyond miR-646, other miRNAs may participate in regulatory processes, and their mechanisms require further investigation. (4) The specific downstream target genes and signaling pathways of the NBR2/miR-646 axis have not been fully elucidated. (5) Current functional experiments are based on the INS-1 cell line, and thus the conclusions require further validation in primary cells and in vivo models. Future research will: (1) expand the clinical cohort and conduct prospective studies; (2) analyze the tissue expression profile of NBR2 in rat models to clarify its cellular origin and secretion mechanisms; (3) validate the functions of other candidate miRNAs; (4) identify downstream target genes of miR-646 to construct a comprehensive regulatory network; (5) validate the findings using primary islet cells and animal models; and (6) combine bioinformatics and experimental approaches to elucidate whether miR-646 influences β-cell function through signaling pathways such as PI3K/Akt and AMPK.

In summary, NBR2 is highly expressed in T2DM patients and is closely related to FPG and HbA1c levels, enabling the differentiation between T2DM patients and healthy individuals. Cell experiments further confirmed that inhibition of NBR2 alleviates HG-induced INS-1 cell dysfunction, and this protective effect can be effectively reversed by miR-646. The above results indicate that NBR2 affects INS-1 cell function by regulating miR-646, providing new potential targets and research directions for the treatment of T2DM.

Author contributions

MM P, LL K and YJ C designed this study. JL L and LJ S conducted the experiment and analyzed the data. JL L wrote the manuscript. MM P, LL K, YJ C, LJ S revised the manuscript. All authors reviewed and approved for publication.

Funding

No funding was received to assist with the preparation of this work.

Data availability

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

Declarations

Ethics approval and consent to participate

The study protocol was approved by The Ethics Committee of Yantai Yantaishan Hospital. All procedures performed in studies involving human participants were in accordance with the 1964 Helsinki Declaration and later versions.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Clinical trial number

Not applicable.