LncRNA A1BG-AS1 regulates the progress of diabetic foot ulcers via sponging miR-214-3p

Abstract

Nerve aberrations and vascular lesions in the distal lower limbs are the etiological factors for diabetic foot ulcers (DFUs). This study aimed to understand the regulatory mechanism of angiogenesis in patients with DFU by examining lncRNA, as well as to explore effective targets for diagnosing and treating DFU. The serum levels of A1BG-AS1 and miR-214-3p and the predictive power of A1BG-AS1 for DFU were determined by quantitative PCR and ROC analysis. The correlation of A1BG-AS1 with clinical characteristics was examined using chi-square tests. The risk factors for DFU in patients with type 2 diabetes mellitus (T2DM) were identified using the logistic regression model. Furthermore, the binding sites of A1BG-AS1 and miR-214-3p were determined. Next, A1BG-AS1 interference plasmid and miR-214-3p inhibitor were co-transfected into high glucose-induced cells to investigate their effects on the expression of angiogenesis-related genes and cell proliferation. The A1BG-AS1 levels were upregulated, whereas the miR-214-3p levels were downregulated in patients with DFU. The upregulation of A1BG-AS1 was significantly associated with both blood glucose levels and ulcer grades. A1BG-AS1 served as a crucial biomarker for diagnosing DFU and evaluating the risk of DFU occurrence in patients with T2DM. Co-transfection experiments revealed that the inhibition of miR-214-3p effectively recovered the suppressive effects of A1BG-AS1 on angiogenesis-related gene expression, endothelial cell differentiation, and proliferation. The sponging effect of A1BG-AS1 on miR-214-3p impaired angiogenesis in patients with DFU. Thus, A1BG-AS1 is a potential therapeutic target for DFU.

Introduction

Diabetic foot ulcers (DFUs), a serious chronic complication of diabetes, is associated with high treatment costs and is the main cause of non-traumatic amputation [1]. In addition to decreasing the quality of life of patients, DFUs are a major burden on patient families. The incidence of DFUs is increasing among patients with diabetes, affecting approximately 15%–25% of this population [2]. Previous studies have demonstrated that the mortality risk is high in patients with diabetes who have a history of amputations. The 5-year mortality rate in this population is more than 50%. Additionally, the prognosis of patients with DFUs is worse than that of patients with most other diseases or malignancies [3]. Vasculopathies, including macrovascular, small-vessel, and microvascular diseases, are the major causes of DFUs, as they are associated with aberrant blood supply [4]. Thus, the molecular mechanisms underlying angiogenesis in patients with DFUs must be elucidated to identify suitable early interventions and treatment modalities to expedite wound healing processes.

Long non-coding RNAs (lncRNAs), which are a class of RNA molecules with a length of >200 bp, do not encode proteins [5]. However, lncRNAs regulate protein expression by directly recruiting or sequestering gene or by indirectly modulating the expression of protein-coding genes through microRNAs (miRNAs). Thus, lncRNAs are involved in various biological processes, such as cell proliferation, migration, and differentiation [6]. Additionally, lncRNAs serve as key regulatory factors for the occurrence and development of various diseases. Recent studies have revealed that lncRNAs can enhance wound healing in DFU through various mechanisms, including the stimulation of fibroblast proliferation, the suppression of cell apoptosis, and the activation of specific signaling pathways [7]. However, the precise underlying mechanisms of lncRNAs must be further elucidated. A1BG antisense RNA 1 (A1BG-AS1), a novel lncRNA associated with tumor progression, is encoded on chromosome 19q13.43 [8]. Analysis of The Cancer Genome Atlas database revealed that A1BG-AS1 is downregulated in patients with hepatocellular carcinoma and is correlated with adverse prognostic indicators, such as microvascular infiltration, high tumor grade, and advanced tumor stage [9]. One study demonstrated that A1BG-AS1 expression is upregulated in type 2 diabetes (T2DM) using quantitative PCR (qPCR) and bioinformatics analyses. A1BG-AS1 is reported to regulate inflammation and occupy a central position in the lncRNA-mRNA co-expression network. This indicates that A1BG-AS1 is a potential therapeutic target for managing inflammation in T2DM [10].

miRNAs can specifically interact with the non-coding region of messenger RNA (mRNA), inhibiting protein translation and regulating cellular functions. lncRNAs can sequester miRNAs from their targeted mRNAs, which harbor the same miRNA response elements (MREs), modulating the expression of the targeted mRNAs and influencing the wound healing process in DFU [11]. For example, lncRNA H19 can modulate the expression of PTEN by targeting miR-152-3p, resulting in the suppression of fibroblast proliferation and migration [12]. Additionally, lncRNA ANRIL facilitates lymph angiogenesis by regulating the miR-181a/Prox1 axis, promoting wound healing in diabetes [13]. miR-214-3p is reported to regulate various signaling pathways and biological responses involved in cell growth, differentiation, apoptosis, neural development, oxidative stress, and vascular endothelial cell function protection [14]. LncRNAs exert regulatory effects on miR-214-3p in several diseases. For example, lncRNA MIAT can downregulate miR-214-3p expression in diabetic cardiomyopathy, regulating myocardial cell damage and atherosclerosis development [15]. The precise mechanisms of lncRNA A1BG-AS1 and miR-214-3p in DFU pathogenesis and angiogenesis during wound healing, as well as the diagnostic value of lncRNA A1BG-AS1 in DFUs, have not been elucidated.

This study examined the expression patterns and diagnostic utility of lncRNA A1BG-AS1 in patients with DFU. Additionally, the correlation of A1BG-AS1 with clinical and pathological characteristics was examined. The relationship between A1BG-AS1 and miR-214-3p target genes was analyzed to further examine their role and regulatory mechanism in angiogenesis. The findings of this study provided experimental evidence and a theoretical foundation for the future genetic-level diagnosis and treatment of DFU.

Patients and Methods

Study subjects

This study recruited 77 DFU patients with DFU treated at the Shijiazhuang Hospital of Traditional Chinese Medicine between 2020 and 2023 in the DFU group. Meanwhile, 85 patients with T2DM were recruited in the T2DM group in the same period. DFU patients met the following criteria to be included: (1) they complied with the “WHO developed diagnostic criteria for diabetes” and the “diabetes foot examination methods and diagnostic criteria”; (2) they had a history of diabetes; (3) the ulcer area of the diabetes foot must be less than 30 cm²; (4) they had limb lesions and weak dorsalis pedis artery pulsation; (5) they exhibited symptoms such as chills, pale skin, and stabbing pain on the limbs; (6) complete clinical data recorded linked to medical records; (7) the patient was in a healthy state of mind. The following were excluded: (1) ulcers for which a clear diagnosis of diabetes was not made; (2) patients with combined lower limb arteriovenous thrombosis; (3) tumor mergers or locally developed cancerous changes; (4) ulcers resulting from radiation therapy-induced local trauma; (5) patients with severe anemia or malnutrition; (6) patients who were unable to cooperate or refused treatment; (7) patients who had significant abnormalities in platelet and coagulation function before hospitalization; (8) patients who had severe heart, liver, kidney, and lung dysfunction before hospitalization. Patients in the T2DM group fulfilled the diagnostic requirements outlined in the Chinese Guidelines for the Prevention and Treatment of Type 2 Diabetes (2020 Edition) and had comprehensive clinical records with no concurrent autoimmune disorders, malignant tumors, local infections, or other diabetes types. In the control group, 75 age-matched and gender-matched healthy volunteers who completed medical examinations were recruited. Individuals in the control group had no history of infection, sickness, or medication use during the previous three months. The clinical characteristics of each patient from medical records, such as age, gender, body mass index (BMI), total cholesterol (TC), triglyceride (TG), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), glycated hemoglobin (HbA1c), fasting blood glucose (FBG), and Wagner grading were recorded. All participants provided their consent to participate in the study. This study was approved by the Shijiazhuang Hospital of Traditional Chinese Medicine and adhered to the principles of the Declaration of Helsinki.

Serum collection

On the morning of the second day after admission, 8–10 mL of peripheral venous blood sample was collected from all study patients in procoagulant tubes containing a separation gel. The samples were centrifuged at 4°C and 3,500 × g for 10 min to separate the serum. The serum was transferred to a 1.5 mL RNase-free EP tube and stored at –80°C until RNA extraction.

Cell culture and high glucose induction

A complete culture medium was prepared by combining penicillin-streptomycin solution, fetal bovine serum (FBS), and Dulbecco’s modified Eagle medium (DMEM) in a proportion of 1:10:89. The human dermal fibroblast (HDFa) cell line obtained from the Gibco (USA) was seeded into a cell culture vessel containing 4 mL of complete culture medium and cultured at 5% CO₂ and 37℃. Cell growth was observed daily, and the complete culture medium was replaced once every 48 h. When the confluency reached >90%, the cells were rinsed thrice with phosphate-buffered saline (PBS, pH = 7.2) and incubated with 4 mL of complete culture medium containing 5.5 mM D-glucose (HG). Cell differentiation was inhibited in a high-glucose environment. The cells were cultured in the incubator and used for cell transfection experiments after 10 stable passages.

Cell transfection

The small interfering RNA constructs targeting A1BG-AS1 (si-A1BG-AS1) and the corresponding negative control (si-NC) were synthesized by Sangon. The miR-214-3p mimic and its negative control (mimic-NC), as well as the miR-214-3p inhibitor and its negative control (inhibitor-NC), were sourced from RiboBio in Guangzhou, China. HDFa cells were seeded in a 12-well plate, cultured until the logarithmic growth phase, and transfected with the constructs. Transfection was performed using 10 nM of the vector and Lipofectamine 3000 transfection reagent (Thermo, USA), following the manufacturer’s instructions. At 6 h post-transfection, the culture medium was replaced, and the cells were further incubated to obtain cells for subsequent experimental procedures.

RNA extraction and cDNA synthesis

Total RNA was extracted from frozen serum samples and cell samples using the SteadyPure blood, serum, and plasma RNA extraction kit (Accurate, China) and the MolPure^® the cell RNA kit (Yeasen, China), respectively. The RNA solution that was collected was treated with 1 μL of DNase I (Beyotime, China) and incubated at 37°C for 30 min. Subsequently, the samples underwent a heating treatment at 65°C for 10 min to inactivate the DNase I, resulting in RNA samples with genomic DNA removed. The purity and concentration of the total RNA were assessed using NanoDrop 2000 (Thermo Fisher Scientific, USA) and 1.5% agarose gel electrophoresis. Total RNA (1 μg) was reverse-transcribed into cDNA using the SuperScript VILO cDNA synthesis kit (Thermo, USA), following the manufacturer’s instructions. The synthesized first strand cDNA was stored at –20°C for future use.

Real-time quantitative polymerase chain reaction (RT-qPCR)

The relative expression levels of A1BG-AS1, miR-214-3p, and angiogenesis-related genes, such as vascular endothelial growth factor (VEGF), stromal cell-derived factor-1α (SDF-1α), and Maf bZIP transcription factor G (mafG) were determined using the SYBR Premix Ex TaqTM II gene expression detection kit (Takara, Japan), with the reference genes U6 and GAPDH. RT-qPCR analysis was performed in a 20 μL reaction solution mixture with cDNA as a template, following the manufacturer’s instructions, using the Applied Biosystems 7500 Real-Time PCR system (Thermo, USA). The reaction parameters consisted of an initial pre-denaturation step at 95°C for 5 min, followed by a denaturation phase at 95°C for 10 s, an annealing phase at 60°C for 30 s, and an extension phase at 72°C for 34 s, culminating in a total of 40 cycles. The primers, which were synthesized by Beijing RuiBiotech Biotechnology Co., Ltd., are listed in Table 1. The relative gene expression levels were determined using the 2^–ΔΔCt method.

Table 1 Primers used in this study

Gene Name	Primer Sequence (5′-3′)
lncRNA A1BG-AS1	Forward	TTTAGTAGAGACGGGGTTTCGTC
	Reverse	CTGATGGTTGCAAAGGAGTTTG
miR-214-3p	Forward	CTCTCTGCTCCTCCTGTTCGAC
	Reverse	TGAGCGATGTGGCTCGGCT
mafG	Forward	CTGTTTTCCCGTGTTCGTTT
	Reverse	ACCCCAGTTTCACCTACCCC
SDF-1α	Forward	CGCACTTTCACTCTCCGTCA
	Reverse	AGCACGACCACGACCTTG
VEGF	Forward	CTACCTCCACCATGCCAAGT
	Reverse	GCAGTAGCTGCGCTGATAGA
U6	Forward	ATTGGAACGATACAGAGAAGATT
	Reverse	GGAACGCTTCACGAATTTG
GAPDH	Forward	ACCACAGTCCATGCCATCAC
	Reverse	TCCACCACCCTGTTGCTGTA

Cell proliferation activity assay

The transfected cells in the culture flack were digested with trypsin and seeded in a 96-well plate at a density of 5,000 cells per well (3 replicates per experimental group). After cell stabilization, cell proliferation was assessed using the cell counting kit-8 (CCK-8, Dojindo, Japan). Briefly, DMEM was mixed with CCK-8 reagent in a 10:1 ratio. The cells in the 96-well plate cultured for 0, 24, 48, and 72 h were incubated with this mixture in a dark incubator for 2 h. The optical density (OD) of the sample at 450 nm was determined using a microplate reader (3 repetitions per well).

Luciferase report assay

The starBase online database was used to identify downstream miRNAs. The binding sites of A1BG-AS1 in miR-214-3p were predicted using the lncRNA SNP2 database. The sequences of wild-type (WT) or mutant (MUT) A1BG-AS1 with miR-214-3p binding sites were integrated into the pmirGLO dual luciferase reporter vector to generate the recombinant plasmids A1BG-AS1-WT and A1BG-AS1-MUT, respectively. HDFa cells were cultured until the logarithmic growth phase and transfected with the prepared vectors using the Lipofectamine 3000 transfection reagent. At 48 h post-transfection, a Renilla luciferase assay (Beyotime, China) was performed, following the manufacturer’s guidelines.

Data analysis

All statistical analyses were performed using SPSS 23.0 and GraphPad Prism 9.0 software. The continuous data are presented as mean ± standard deviation (SD). Means between groups were compared using independent sample t-tests. Categorical data are expressed as percentages (%). Percentage values between groups were compared using the chi-square tests. Patients with DFU were categorized into high-expression and low-expression groups based on the average expression level of A1BG-AS1. The correlation between A1BG-AS1 and clinical pathological characteristics was assessed using chi-square tests. The serum expression levels of A1BG-AS1 and miR-214-3p, as well as the cellular expression levels of A1BG-AS1, miR-214-3p, VEGF, SDF-1 α, and mafG between the three groups were compared using analysis of variance. Pearson correlation analysis was performed to examine the correlation between A1BG-AS1 and miR-214-3p in patients with DFU. The diagnostic value of A1BG-AS1 in DFU was evaluated using receiver operating characteristic (ROC) curve analysis. Univariate and multivariate logistic regression analyses were performed to predict the onset of DFU in patients with T2DM. The odds ratio (OR) value and corresponding 95% confidence interval (CI) were calculated for each factor with a probability discrimination threshold of 0.5. Differences were considered significant at p < 0.05. All experiments were repeated at least three times.

Results

General characteristics of the study groups

The clinical data of the control, T2DM, and DFU groups were comparatively analyzed (Table 2). Clinical characteristics, such as age distribution, gender composition, BMI, as well as the TC, TG, and LDL-C levels, were not significantly different between the three groups (p > 0.05). Compared with those in the control group, the FBG (p < 0.001) and HbA1c (p < 0.01) levels were upregulated, and the HDL-C levels were significantly downregulated in the T2DM and DFU groups (p < 0.05). Furthermore, patients in the DFU group had Wagner grade II, III, and IV ulcers.

Table 2 The basic information of all subjects

Factors	Control (N = 75)	T2DM (N = 85)	DFU (N = 77)	p value
Age (years)	55.04 ± 10.19	53.96 ± 11.15	53.39 ± 10.08	0.7737
Gender				0.9698
Female	33 (44.00)	39 (45.88)	35 (45.45)
Male	42 (56.00)	46 (54.12)	42 (54.55)
BMI (kg/m2)	21.92 ± 3.12	22.72 ± 2.94	23.10 ± 3.01	0.7935
FBG (mmol/L)	4.71 ± 0.91	7.98 ± 1.68	8.66 ± 2.00	<0.0001
HbA1c (%)	5.13 ± 1.29	7.09 ± 1.66	8.82 ± 1.79	0.0071
Blood lipids
TC (mmol/L)	4.62 ± 0.98	4.76 ± 0.72	4.53 ± 1.12	0.2881
TG (mmol/L)	1.26 ± 0.37	1.19 ± 0.23	1.25 ± 0.27	0.2168
LDL-C (mmol/L)	2.54 ± 0.40	2.62 ± 0.30	2.60 ± 0.36	0.3421
HDL-C (mmol/L)	1.32 ± 0.31	1.15 ± 0.33	1.00 ± 0.24	0.0254
Wagner grade				—
I	—	—	7 (9.10)
II	—	—	18 (23.38)
III	—	—	28 (36.36)
IV	—	—	21 (27.27)
V	—	—	3 (3.89)

Notes: T2DM: diabetes mellitus type 2; DFUs: diabetic foot ulcers; BMI: body mass index; FBG: fasting blood glucose; HbA1c: glycated hemoglobin; TC: total cholesterol; TG: triglyceride; LDL-C: low-density lipoprotein cholesterol; HDL-C: high-density lipoprotein cholesterol; p < 0.05 means a significant difference.

Serum levels of lncRNA A1BG-AS1

RT-qPCR analysis revealed that the serum levels of lncRNA A1BG-AS1 in the T2DM and DFU groups were significantly upregulated when compared with those in the control group (p < 0.001, Fig. 1A). Additionally, the serum level of A1BG-AS1 in the DFU group was higher than that in the T2DM group (p < 0.001, Fig. 1A). ROC curve analysis (Fig. 1B) revealed that the area under the curve value (AUC) of A1BG-AS1 for diagnosing DFU was 0.7969 (95% CI: 0.7299–0.8640) with specificity and sensitivity values of 71.76% and 75.32%, respectively. These results indicated that A1BG-AS1 levels can predict DFU (p < 0.001, Fig. 1B). Additionally, these findings suggest a potential correlation between A1BG-AS1 dysregulation and DFU development.

Fig. 1  The expression level in the serum and the diagnostic significance of lncRNA A1BG-AS1 in DFU patients. A, the expression levels of A1BG-AS1. B, ROC curve analysis. ***, p < 0.001.

Correlation of lncRNA A1BG-AS1 expression with clinicopathological variables

Patients with DFU were categorized into high-expression and low-expression groups based on the mean serum A1BG-AS1 expression levels. The clinical and pathological characteristics of the high-expression and low-expression groups were compared. As shown in Table 3, age range, gender, BMI, and lipid profiles (including TC, TG, LDL-C, and HDL-C) were not significantly different between the high-expression and low expression groups (p > 0.05). The FBG, HbA1c, and Wagner grade indicators were significantly correlated with the expression level of A1BG-AS1 (p < 0.05). The high-expression group exhibited upregulated blood glucose levels and high ulcer grades.

Table 3 Relationship of serum lncRNA A1BG-AS1 expression with clinicopathological variables

Variables	DFU (N = 77)	lncRNA A1BG-AS1 expression		p value
		Low (n = 37)	High (n = 40)
Age (years)				0.4906
<53	33	14 (42.42)	19 (57.58)
≥53	44	23 (52.27)	21 (47.73)
Gender				0.9336
Female	35	17 (48.57)	18 (51.43)
Male	42	20 (47.62)	22 (52.38)
BMI (kg/m2)				0.4971
<23.1	38	20 (52.63)	18 (47.37)
≥23.1	39	17 (43.59)	22 (56.41)
FBG (mmol/L)				0.0227
<8.7	39	24 (61.54)	15 (38.46)
≥8.7	38	13 (34.21)	25 (65.79)
HbA1c (%)				0.0029
<8.8	40	26 (65.00)	14 (35.00)
≥8.8	37	11 (29.73)	26 (70.27)
TC (mmol/L)				0.8205
<4.5	37	17 (45.95)	20 (54.05)
≥4.5	40	20 (50.00)	20 (50.00)
TG (mmol/L)				0.6496
<1.2	33	17 (51.52)	16 (48.48)
≥1.2	44	20 (45.45)	24 (54.55)
LDL-C (mmol/L)				0.2560
<2.6	40	22 (55.00)	18 (45.00)
≥2.6	37	15 (40.54)	22 (59.46)
HDL-C (mmol/L)				0.1099
<1.0	32	19 (59.38)	13 (40.62)
≥1.0	45	18 (40.00)	27 (60.00)
Wagner grade				0.0274
I–II	25	17 (68.00)	8 (32.00)
III–V	52	20 (38.46)	32 (61.54)

Notes: DFUs: diabetic foot ulcers; BMI: body mass index; FBG: fasting blood glucose; HbA1c: glycated hemoglobin; TC: total cholesterol; TG: triglyceride; LDL-C: low-density lipoprotein cholesterol; HDL-C: high-density lipoprotein cholesterol; p < 0.05 means a significant difference.

Risk factors for DFU occurrence in patients with T2DM

Univariate analysis revealed that variables such as age, gender, BMI, TC, TG, and LDL-C were not significantly correlated with the development of DFU in patients with T2DM (p > 0.05, Table 4). Meanwhile, A1BG-AS1 (OR = 6.927, 95% CI: 3.520–14.150, p < 0.001), FBG (OR = 1.993, 95% CI: 1.069–3.754, p < 0.05), HbA1c (OR = 4.720, 95% CI: 2.460–9.305, p < 0.001), and HDL-C (OR = 0.333, 95% CI: 0.172–0.629, p < 0.001) were identified as risk factors for DFU occurrence in patients with T2DM. Multivariate analysis revealed that the A1BG-AS1, FBG, and HbA1c levels were significant risk factors for DFU occurrence in patients with T2DM (p < 0.05).

Table 4 Logistic regression analysis of clinical indexes related to DFU

Factors	Univariate		Multivariate
	OR (95% CI)	p value	OR (95% CI)	p value
Age (years)	0.908 (0.489–1.683)	0.7589	0.992 (0.465–2.125)	0.9830
Gender	1.017 (0.547–1.893)	0.9565	0.819 (0.365–1.816)	0.6228
BMI (kg/m2)	1.216 (0.656–2.261)	0.5344	0.811 (0.357–1.806)	0.6111
FBG (mmol/L)	1.993 (1.069–3.754)	0.0310	2.709 (1.271–6.017)	0.0115
HbA1c (%)	4.720 (2.460–9.305)	<0.0001	3.626 (1.728–7.799)	0.0008
TC (mmol/L)	0.713 (0.382–1.323)	0.2845	0.834 (0.374–1.857)	0.6551
TG (mmol/L)	1.028 (0.551–1.919)	0.9313	0.752 (0.348–1.599)	0.4607
LDL-C (mmol/L)	0.904 (0.487–1.675)	0.7471	1.141 (0.528–2.503)	0.7386
HDL-C (mmol/L)	0.333 (0.172–0.629)	0.0008	0.725 (0.317–1.688)	0.4487
lncRNA A1BG-AS1	6.927 (3.520–14.150)	<0.0001	6.381 (2.778–15.550)	<0.0001

Notes: DFUs: diabetic foot ulcers; BMI: body mass index; FBG: fasting blood glucose; HbA1c: glycated hemoglobin; TC: total cholesterol; TG: triglyceride; LDL-C: low-density lipoprotein cholesterol; HDL-C: high-density lipoprotein cholesterol; OR: odds ratio; 95% CI: confidence interval; p < 0.05 means a significant difference.

Correlation between lncRNA A1BG-AS1 and miR-214-3p

The potential binding sites of A1BG-AS1 and miR-214-3p were predicted using the online platform lncRNA SNP2 (Fig. 2A). The luciferase activity of the A1BG-AS1-WT vector was significantly suppressed in cells co-transfected with the miR-214-3p mimic and enhanced in cells co-transfected with the miR-214-3p inhibitor (p < 0.01, Fig. 2B). The miR-214-3p mimic and miR-214-3p inhibitor did not markedly affect the luciferase activity of A1BG-AS1-MUT (Fig. 2C). Compared with those in the control group, the serum levels of miR-214-3p were downregulated in the T2DM and DFU groups (p < 0.001). Additionally, the serum levels of miR-214-3p in the DFU group were lower than those in the T2DM group (p < 0.001, Fig. 2D). Correlation analysis revealed that the expression levels of A1BG-AS1 were significantly and negatively correlated with those of miR-214-3p in patients with DFU (r = –0.7881, p < 0.001, Fig. 2E).

Fig. 2  The relationship between lncRNA A1BG-AS1 and miR-214-3p. A, the binding sites. B, miR-214-3p targeted binding to A1BG-AS1-WT. C, miR-214-3p targeted binding to A1BG-AS1-MUT. D, the levels of miR-214-3p in controls and patients with T2DM and DFU. E, the correlation between A1BG-AS1 and miR-214-3p in the DFU group. **, p < 0.01; ***, p < 0.001.

To further explore the role of A1BG-AS1 in the angiogenesis process of patients with DFU, in vitro inhibition experiments were performed using HDFa cells and high glucose culture medium to induce differentiation. High glucose induction significantly upregulated the expression level of A1BG-AS1 (p < 0.001, Fig. 3A) and downregulated the expression levels of miR-214-3p and angiogenesis-related genes (mafG, SDF-1α, and VEGF) (p < 0.001, Fig. 3B, D–F). Transfection with si-A1BG-AS1, markedly downregulated the expression level of A1BG-AS1 (p < 0.001, Fig. 3A), and upregulated the expression levels of miR-214-3p and angiogenesis-related genes (mafG, SDF-1α, and VEGF) (p < 0.01, Fig. 3B, D–F). The mafG, SDF-1α, VEGF, and miR-214-3p expression levels in cells co-transfected with si-A1BG-AS1 and miR-214-3p inhibitor were significantly lower than those in cells transfected only with si-A1BG-AS1 (p < 0.05, Fig. 3B–F). Furthermore, transfection with si-A1BG-AS1 expression during high glucose induction enhanced the proliferation capacity of HDFa cells (p < 0.001, Fig. 3C). Co-transfection of si-A1BG-AS1 and miR-214-3p inhibitor restored the inhibitory effect on high glucose-induced HDFa cell differentiation (p < 0.001, Fig. 3C).

Fig. 3  The effects of co-transfection si-A1BG-AS1 and miR-214-3p inhibitor on the expression of related genes, as well as HDFa cell proliferation. A, the levels of A1BG-AS1. B, the levels of miR-214-3p. C, the changes in cell proliferation. D, the levels of mafG. E, the levels of SDF-1α. F, the levels of VEGF. ***, p < 0.001 versus control groups. ^&&, p < 0.01; ^&&&, p < 0.001 versus HG groups. ^$, p < 0.05; ^$$, p < 0.01; ^$$$, p < 0.001 versus HG + si-A1BG-AS1 groups.

Discussion

Diabetes, a major health burden, is associated with vascular and neuropathic complications, which can exacerbate the pathology [16]. The upregulated glucose levels in patients with diabetes impair the healing of infections or wounds, disrupt blood circulation, increase the risk of amputation, or may even cause fatality [17]. Conventional management of DFU typically involves insulin administration to regulate blood glucose levels, enhance circulation, and mitigate inflammatory responses. However, patients who undergo prolonged insulin therapy may develop drug resistance, resulting in suboptimal therapeutic outcomes [18]. Recently, immunomodulatory peptides have emerged as agents that facilitate wound healing by inhibiting the release of inflammatory mediators and promoting epithelial and vascular regeneration. Nonetheless, the efficacy of this approach is constrained in patients with concurrent renal impairment [19]. Cannabinol has demonstrated significant potential in the management of diabetes and its associated complications; however, the availability of related pharmacological agents in China remains limited [20]. Additionally, novel interventions such as stem cell transplantation and tissue engineering are characterized by high costs and present challenges for clinical implementation [21]. In recent years, lncRNAs have garnered attention as pivotal targets for disease treatment due to their ubiquitous presence, stability, and ease of detection. This molecular-targeted therapeutic strategy offers advantages including precision, high efficacy, minimal adverse effects, and favorable patient adherence. Recent studies have demonstrated the crucial regulatory role of lncRNAs in the onset and progression of DFUs. These findings suggest that lncRNAs are potential early diagnostic markers and therapeutic targets for DFU [22, 23].

LncRNAs are expressed in the endothelial cells of blood vessels, where they regulate various signaling pathways and angiogenesis. Thus, lncRNAs play a crucial role in the onset and progression of vascular diseases [24]. For instance, MEG3 and MALAT1 are upregulated in hypoxic human umbilical vein endothelial cells (HUVECs), suppressing cell proliferation and angiogenesis [25, 26]. Similarly, NRON upregulation in the plasma of patients with heart failure has been linked to impaired endothelial cell proliferation and migration, disrupting angiogenesis [27]. However, limited studies have examined the role of lncRNAs in angiogenesis in DFU. The upregulation of A1BG-AS1 in patients with T2DM suggests that it exerts regulatory effects on diabetes-related inflammation [10]. This study collected serum samples from patients in the T2DM, DFU, and control group. The serum A1BG-AS1 level was upregulated in the T2DM and DFU groups. Furthermore, A1BG-AS1 was identified as a potential predictive marker for DFU. FBG serves as an indirect measure of baseline insulin secretion in the absence of stressors and is a widely utilized diagnostic marker for diabetes [28]. The HbA1c level, which indicates the average blood glucose levels over a specific timeframe, is critical for evaluating the risk of diabetes-related complications [29]. The upregulation of FBG and HbA1c values suggests an increased risk of sustained high glucose-induced complications. The Wagner grade is a prevalent clinical classification system for DFU and is primarily employed to assess the severity and prognosis of patients with DFU [30]. Analysis of the correlation between A1BG-AS1 and various clinical indicators revealed that A1BG-AS1 upregulation was significantly correlated with the serum FBG and HbA1c levels and Wagner grading, as well as served as a risk factor for DFU in patients with T2DM. These findings indicate that A1BG-AS1 can serve as an effective screening tool for DFU and a potential biomarker for assessing the severity and poor prognosis of patients with DFU. Additionally, the A1BG-AS1 level can predict the occurrence of DFU in patients with T2DM. This study compared the characteristics of the T2DM and DFU groups. The occurrence of DFU must be tracked in patients in the T2DM group to validate the predictive value of A1BG-AS1. Additionally, the regulatory mechanism of A1BG-AS1 in the occurrence and development of DFU must be elucidated to understand the role of A1BG-AS1. Therefore, cellular experiments must be performed in the future.

In patients with diabetes, continuous high glucose levels lead to peripheral vascular lesions, and subsequently to DFU. Angiogenic factors enable the ischemic vessels to establish a vascular network in the side limb and ensure smooth blood circulation [31]. VEGF is a crucial angiogenic factor responsible for maintaining myocardial capillary density and promoting endothelial cell proliferation and migration [32]. SDF-1α, a chemokine, mobilizes bone marrow stem/progenitor cells to vascular injury sites for repair and stimulates endothelial cell proliferation and migration, facilitating rapid endothelial regeneration [33]. MafG, a transcription factor expressed in various types of endothelial cells, promotes oxidative stress, cell proliferation, migration, and angiogenesis in collaboration with other protein families [34]. In this study, high-glucose conditions downregulated the expression levels of VEGF, SDF-1α, and mafG and significantly upregulated the expression of A1BG-AS1. Transfection with si-A1BG-AS1 upregulated the expression of angiogenesis-related genes and enhanced cell proliferation. These findings suggest that A1BG-AS1 inhibits endothelial cell function, regulates angiogenesis processes, and suppresses wound healing in patients with DFUs.

Experimental evidence revealed that miR-214-3p exerts negative regulatory effects on angiogenesis by directly targeting QKI and downregulating the expression and release of pro-angiogenic growth factors. The upregulation of miR-214-3p impairs angiogenesis, cell migration, and wound healing capabilities and downregulates VEGF protein levels, impairing vascular growth [35]. miR-214-3p expression was significantly downregulated in the T2DM and DFU groups. The results of the luciferase reporter gene assay revealed that miR-214-3p is a target of A1BG-AS1 and that A1BG-AS1 knockdown upregulates the expression of miR-214-3p. This is consistent with the documented targeted sponge relationships observed in patients with tibial fracture healing [36] and myocardial dysfunction [37]. Co-transfection with si-A1BG-AS1 plasmids and miR-214-3p inhibitors effectively recovered the suppressive effects of A1BG-AS1 on angiogenesis-related gene expression, endothelial cell differentiation, and proliferation. Analysis of A1BG-AS1 as a competing RNA regulating miR-214-3p target gene can improve our understanding of the regulatory mechanism of A1BG-AS1 in DFU (Graphical Abstract). The development of animal models for in vivo experimentation could significantly contribute to the integrality and dependability of research findings, while also ensuring the sensitivity, specificity, and reproducibility of biomarkers employed in clinical applications. However, the establishment of these models demands rigorous experimental protocols and a considerable degree of expertise from researchers. This study encountered challenges in successfully creating the model, primarily due to limitations in technical proficiency and sample size, suggesting that further efforts are necessary in this area.

Graphical Abstract

Conclusions

A1BG-AS1 was significantly upregulated in patients with DFU. The upregulated expression of A1BG-AS1 was significantly associated with both blood glucose levels and ulcer grades. A1BG-AS1 served as a crucial biomarker for diagnosing DFU and evaluating the risk of DFU occurrence in patients with T2DM. Mechanistically, A1BG-AS1 targeted and sponged miR-214-3p, impeding its activity. Consequently, A1BG-AS1 downregulated the expression of angiogenic growth factors and endothelial cell proliferation, and impaired angiogenesis. This study offered insights for further exploration of the angiogenic mechanisms in patients with DFU and provided novel therapeutic targets for DFU.

Acknowledgments

Not Applicable.

Funding

This study was supported by The effect of diversified management on self-management of diabetes foot and its correlation analysis (Project No. 20241783).

Competing Interests

The authors declare that they have no competing interests.

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