Plasma-aqueous dual-fluid NEAT1/miR-93-5p axis may be involved in retinal ganglion cell degeneration in glaucoma: mechanistic dissection and diagnostic model construction

Abstract

The progressive degeneration of retinal ganglion cells (RGCs) is the primary pathological characteristic of glaucoma. The role of the NEAT1/miR-93-5p axis, a crucial part of the ceRNA network, in the plasma-aqueous dual-fluid of glaucoma and its regulatory mechanism for RGC degeneration remain unclear. Patients with glaucoma and those with simple cataracts had their plasma and aqueous humor (AH) samples taken. The expressions of NEAT1 and miR-93-5p were detected by qRT-PCR. The Pearson correlation analysis method was used to examine the expression correlation in the plasma-aqueous dual-fluid. Logistic regression analysis was used to identify independent factors associated with the disease state. To investigate the regulatory effects of the NEAT1/miR-93-5p axis on cell viability, inflammatory response, and oxidative stress, a NaIO₃-induced cell damage model was built. In comparison to the control group, glaucoma patients had significantly higher levels of NEAT1 in their plasma and AH, significantly lower levels of miR-93-5p, and a negative correlation between NEAT1 and miR-93-5p. NEAT1 and miR-93-5p are independent factors related to the pathological state of glaucoma. According to cell experiments, high NEAT1 expression would inhibit cell viability, promotes the release of inflammatory factors. Silencing NEAT1 can reverse this damage, and this regulatory effect may be mediated by miR-93-5p. The NEAT1/miR-93-5p axis in plasma may potentially serve as a biomarker for the diagnosis of glaucoma.

Introduction

Glaucoma is the leading irreversible blinding eye disease worldwide^1,2. Its pathological essence is the retrograde degeneration of axons of retinal ganglion cells (RGCs) and the progressive energy metabolism failure^3,4. Glaucoma is the second leading cause of blindness after cataract⁵. Oxidative stress plays a key regulatory role in the pathophysiological process of glaucoma^6,7. It is crucial to understand the molecular mechanism by which it damages retinal nerve cells in order to develop early glaucoma diagnostic markers, develop targeted intervention strategies, and slow the disease’s progression.

Long non-coding RNAs (lncRNAs) are a class of non-coding RNA molecules with a length exceeding 200 nucleotides⁸. They play a crucial regulatory role in the pathological processes of various diseases, and this characteristic has also made them a research hotspot in the field of ocular diseases⁹. For instance, previous studies have confirmed that lncRNA SNHG7 is significantly upregulated in the tear fluid samples of patients with dry eye disease and in human conjunctival epithelial cells cultured in vitro¹⁰. LncRNA-XR_002792574.1 further illustrates the functional diversity of lncRNA in ocular disorders by blocking the cGMP/PKG and apelin signaling pathways, which can cause myopia-related RGC damage¹¹. The lncRNA NEAT1 (Nuclear Enriched Abundant Transcript 1) is located in the region of human chromosome 11q13.1 and has been proven to be involved in the progression of various ocular diseases^12,13. Liu et al. confirmed that inhibiting the expression of NEAT1 can effectively prevent the formation of choroidal neovascularization and reduce the expression of factors related to angiogenesis¹⁴. Furthermore, the research on NEAT1 is expected to become a potential strategy for treating corneal endothelial dystrophy¹⁵. It is worth noting that some studies have found through sequencing analysis that NEAT1 is significantly upregulated in glaucoma patients¹⁶. However, the specific regulatory role and potential mechanism of NEAT1 in the occurrence and development of glaucoma still lack systematic analysis, and further in-depth research is urgently needed in this area. Moreover, NEAT1 can bind to miRNA via the ceRNA mechanism, competitively controlling the expression of the target genes of miRNA^17,18. Numerous studies have confirmed that miR-93-5p is a key regulatory molecule in the occurrence and development of ocular diseases, and its expression shows significant abnormalities in various ocular lesions. The expression level of miR-93-5p was found to be significantly lower in primary open-angle glaucoma samples when miRNAs in glaucoma eyes with varying degrees of optic nerve lesions were analyzed using next-generation sequencing technology¹⁹. Compared with the control group, the expression of miR-93-5p in acute high intraocular pressure retina was significantly decreased²⁰. Conducting miRNA microarray analysis, it was found that miR-93-5p was significantly downregulated in the central retinal vein occlusion group²¹. Based on this, this study used bioinformatics analysis to clarify the targeted interaction relationship between NEAT1 and miR-93-5p, suggesting that the two may jointly participate in the pathological regulatory processes related to glaucoma.

In summary, this study aims to elucidate the expression characteristics and interaction of NEAT1 and miR-93-5p in plasma–aqueous dual-fluid compartment of glaucoma patients. To explore the regulatory axis of NEAT1/miR-93-5p on the function and oxidative stress of RGCs, evaluate its diagnostic value, and identify independent factors related to the pathological state of glaucoma, in order to provide theoretical basis for clinical diagnosis and targeted treatment.

Materials and methods

Research subject selection

From December 2021 to December 2024, 198 glaucoma patients who received treatment at Eye and ENT Hospital were selected as the research group. Another 88 patients with cataract who were treated in the same hospital during the same period were selected as the control group. Inclusion criteria¹: The research group and the control group respectively met the clinical diagnostic criteria for glaucoma or cataract²; Age ≥ 18 years³; Complete clinical data, able to collaborate to finish all data gathering and tests⁴; No ocular trauma or intraocular surgery history in the past 3 months⁵; Proposed to undergo related surgical treatment, and the aqueous humor (AH) samples could be obtained during the operation⁶; The cataract group had no history of glaucoma and no family history of glaucoma. Exclusion criteria¹: Complicated with other severe ocular diseases (such as corneal ulcer, uveitis, retinal detachment, etc.)²; Complicated with severe systemic diseases (such as severe cardiovascular and cerebrovascular diseases, liver and kidney dysfunction, malignant tumors, autoimmune diseases, etc.)³; With a history of mental illness, cognitive dysfunction, unable to cooperate to complete information collection and examinations⁴; Pregnant or lactating women. All research subjects voluntarily participated in this study and signed the informed consent form. The research protocol was approved by the hospital’s ethics committee.

Collecting baseline data of all participants, including age, gender, smoking history, drinking history and ocular disease history. Visual acuity assessment was conducted using a standard logarithmic visual acuity chart to detect the preoperative best corrected visual acuity (BCVA). Intraocular pressure (IOP) measurement is carried out using a non-contact tonometer. All measurements were conducted in a quiet and well-lit indoor environment. The subjects were required to sit upright and have their heads naturally fixed on the support frame of the tonometer. Both eyes needed to look directly at the fixed light source inside the instrument and maintain natural eye opening and calm breathing. Three consecutive valid IOP readings are taken for each eye, and the average value is used as the final IOP value for that eye. Visual field examination was performed using an automatic visual field instrument, and the average defect (MD) value was recorded.

Sample collection and processing

Plasma sample collection: All research subjects were in a fasting state before the operation, and professional medical staff collected 5 mL of elbow vein blood. After centrifugation, the upper layer of plasma was collected and stored at −80℃ in an ultra-low temperature refrigerator for subsequent experimental detection purposes.

AH sample collection: The surgical doctor performed anterior chamber puncture with a 27G syringe needle to collect 50–100 µL of AH. During the collection process, strict aseptic operation principles were followed to avoid contamination by blood and tissue fluid. The AH sample was immediately placed in an enzyme-free EP tube, marked with relevant information, and quickly stored in a −80℃ ultra-low temperature refrigerator for subsequent experimental detection.

RT-qPCR

Total RNA was extracted using the miRNeasy extraction kit (Qiagen, USA) according to the manufacturer’s instructions. The concentration and purity of the RNA were confirmed by a NanoDrop 2000 (Thermo Fisher, USA). The total RNA was reverse-transcribed into cDNA using the reverse transcription kit (Qiagen, USA). The SYBR Green PCR kit (Qiagen, USA) was used. The expression of NEAT1 and miR-93-5p was detected on the ABI 7500 real-time PCR instrument (Applied Biosystems, USA). GAPDH and U6 were used as reference genes. The relative expression of RNA was calculated using the 2^−ΔΔCt equation. The experiment was repeated three times.

Luciferase reporter gene assay

Construct a wild-type luciferase reporter gene vector (WT-NEAT1) containing the binding site of NEAT1 and miR-93-5p, as well as a mutant type luciferase reporter gene vector (MUT-NEAT1) with the mutated binding site. Transfect the WT-NEAT1 and MUT-NEAT1 vectors separately with miR-93-5p mimic, negative control mimic (mimic NC), miR-93-5p inhibitor, and negative control inhibitor (inhibitor NC) to RGCs. After transfection for 48 h, the luciferase activity of each group of cells was detected using the luciferase assay kit, which employed a dual-luciferase reporter gene.

Cell lines and culture conditions

RGCs were purchased from Zhongjiao Xinzhou Biotechnology Co., Ltd. (Shanghai, China). RGCs were cultured in a constant temperature and humidity incubator at 37 °C and 5% CO₂. The normal group was cultured under conventional conditions without any intervention. To establish the oxidative damage model, 1200 µg/mL of NaIO₃ was added to the culture medium, and the cells were left to act for 24 h²². Then, the medium was replaced with DMEM/F12 medium containing 10% fetal bovine serum, and the cells were further cultured for 48 h.

Cell transfection

RGCs were seeded into 6-well plates, with a cell density of 2 × 10⁵ cells per well, and incubated in a 37 °C incubator overnight. RGCs were transfected with miR-93-5p mimic, miR-93-5p inhibitor, si-NEAT1, and negative control si-NC using the Lipofectamine 3000 transfection reagent (Invitrogen, USA). All of the above-mentioned nucleic acid sequences were synthesized by Shanghai Sangon Biotech Co., Ltd.

Cell viability assay

RGCs were seeded at a density of 1 × 10⁴ cells per well onto a 96-well cell culture plate and cultured in a 37 °C, 5% CO₂ incubator. After the cells reached the specified growth state, CCK-8 cell viability detection reagent was added to each well and incubated in the dark for 2 h. After the incubation, the absorbance values (OD₄₅₀) of each well were measured using a microplate reader at a wavelength of 450 nm. The procedure was repeated three times.

Inflammatory factor

Follow the guidelines provided by the ELISA kit (Thermo Fisher, USA) exactly. Each well of the ELISA plate should contain 100 µL of the sample to be tested, followed by the addition of the particular primary antibodies for TNF-α, IL-6, and IL-1β. Place the plate at a constant temperature of 37 °C for 60 min for incubation. After the incubation is complete, use the washing solution provided by the kit to thoroughly wash the microplate. Then, add 100 µL of the working solution of horseradish peroxidase (HRP)-labeled secondary antibody to each well and incubate at 37 °C for 30 min. After discarding the liquid in the wells, add the chromogenic substrate, and incubate in the dark for 15 min. Once the color reaction stabilizes, immediately add the stop solution to terminate the reaction. The OD value of each well at a wavelength of 450 nm was detected by an enzyme reader (Thermo Fisher, USA).

Oxidative stress indicator detection

Phosphate buffer solution was added to the cells of different treatment groups, and then the cells were homogenized. The expression of superoxide dismutase (SOD) were detected by xanthine oxidase method, and the expression of peroxidase (POD) were detected by colorimetric method. The detection reagents were all purchased from Beijing Solabio Technology Co., Ltd. The detection of SOD and POD expression was carried out in accordance with the corresponding reagent kit instructions.

Data statistics and analysis

This study employed SPSS 26.0 (IBM-SPSS, USA) statistical software and Prism 9.0 (GraphPad Software, USA) drawing software to conduct all data statistical analysis and chart drawing. The difference between the two groups was compared using the independent sample t-test. The differences among multiple groups were compared using one-way analysis of variance (ANOVA). Correlation analysis was performed using Pearson. The receiver operating characteristic curve (ROC) was drawn, and the area under the curve (AUC), sensitivity, and specificity were calculated. Logistic regression analysis clarified the independent factors related to the pathological state of glaucoma. The target genes of miR-93-5p were predicted by combining TargetScan (https://www.targetscan.org), miRDB (https://mirdb.org), and starBase databases (http://starbase.sysu.edu.cn/), and the protein-protein interaction (PPI) network was constructed using the STRING database. The core target genes were screened using the CytoHubba plugin. A P < 0.05 was considered statistically significant.

Results

Expression of NEAT1 and miR-93-5p in AH and plasma of glaucoma patients and their correlation

NEAT1 and miR-93-5p expression were measured by qRT-PCR in AH and plasma from glaucoma patients and the control group. Compared with the control group, the relative expression of NEAT1 in the AH (Fig. 1A) and plasma (Fig. 1B) of the glaucoma patients were significantly increased (P < 0.001), while the relative expression of miR-93-5p in the AH (Fig. 1C) and plasma (Fig. 1D) were significantly decreased (P < 0.001). Further correlation analysis showed that the expression of NEAT1 in the plasma of the glaucoma patients was significantly positively correlated with that in the AH (Fig. 1E, r = 0.7718, P < 0.001), and the expression of miR-93-5p in the plasma was also significantly positively correlated with that in the AH (Fig. 1F, r = 0.7339, P < 0.001). Meanwhile, the expression of NEAT1 and miR-93-5p in the AH (Fig. 1G, r = −0.7166, P < 0.001) and plasma (Fig. 1H, r = −0.6526, P < 0.001) were significantly negatively correlated.

Fig. 1.

The expression characteristics and correlation of NEAT1 and miR-93-5p in aqueous humor (AH) and plasma of glaucoma patients. (A-B) The relative expression levels of NEAT1 in AH (A) and plasma (B) between the control group and the glaucoma group; (C-D) The relative expression levels of miR-93-5p in AH (C) and plasma (D) between the control group and the glaucoma group; (E) Correlation between the expression of NEAT1 in plasma and AH of glaucoma patients; (F) The correlation between the expression of plasma miR-93-5p and AH miR-93-5p in glaucoma patients; (G) Correlation between the expression of NEAT1 and miR-93-5p in AH of glaucoma patients; (H) Correlation between the expression of NEAT1 and miR-93-5p in the plasma of glaucoma patients. Data were expressed as mean ± standard deviation, and the independent sample t-test was used for comparison between groups. Correlation analysis was conducted using the Pearson correlation coefficient. ***P < 0.001.

Analysis of the diagnostic value of NEAT1 and miR-93-5p in plasma

To evaluate the diagnostic efficacy of plasma NEAT1 and miR-93-5p for glaucoma, this study plotted the ROC curve. The AUC of plasma NEAT1 was 0.897, with the cut-off value being 0.865, and the corresponding sensitivity was 95.45% and specificity was 78.41% (Fig. 2A). The AUC of plasma miR-93-5p was 0.857, with the cut-off value being 0.805, and the corresponding sensitivity was 86.87% and specificity was 75.00% (Fig. 2B).

Fig. 2.

ROC curves of plasma NEAT1 and miR-93-5p for the diagnosis of glaucoma. (A) ROC curve of plasma NEAT1 for the diagnosis of glaucoma; (B) ROC curve of plasma miR-93-5p for the diagnosis of glaucoma. The AUC in the figure represents the area under the curve, and the optimal cut-off values, sensitivity, and specificity of each indicator are also indicated.

Plasma miR-93-5p/NEAT1 expression and clinical/inflammatory correlations

The relationships between the expression of miR-93-5p and NEAT1 in plasma and clinical markers and inflammatory factors were examined in this study (Table 1). Based on the median expression levels of miR-93-5p and NEAT1, the patients were divided into low and high expression groups for miR-93-5p (n = 99 each) and for NEAT1 (n = 98 and n = 100, respectively). There were not statistically significant differences in age, gender, smoking history, drinking history, eye disease history, or BCVA (all P > 0.05). However, the MD, IOP, and inflammatory factors were markedly elevated in the groups with low expression of miR-93-5p and high expression of NEAT1 (all P < 0.001).

Table 1.

Association of NEAT1/miR-93-5p with clinical data and inflammatory cytokines.

Variables	miR-93-5p expression		P	NEAT1 expression		P
	Low (n = 99)	High (n = 99)		Low (n = 98)	High (n = 100)
Age	55.26 ± 7.38	55.82 ± 7.96	0.611	55.77 ± 6.63	55.32 ± 8.58	0.684
Gender (male)	46	44	0.887	47	43	0.568
Smoking	33	30	0.760	34	29	0.446
Drinking	26	30	0.636	29	28	0.876
Eye disease history	29	17	0.063	24	22	0.738
MD (dB)	−0.47 ± 0.22	−0.98 ± 0.23	< 0.001	−0.46 ± 0.22	−0.98 ± 0.24	< 0.001
IOP (mm Hg)	21.47 ± 1.12	24.30 ± 1.25	< 0.001	21.54 ± 1.12	24.19 ± 1.43	< 0.001
BCVA	0.45 ± 0.12	0.44 ± 0.11	0.570	0.45 ± 0.10	0.46 ± 0.08	0.413
IL-6 (pg/ml)	370.06 ± 15.82	406.24 ± 18.77	< 0.001	370.13 ± 14.85	405.81 ± 19.96	< 0.001
IL-β (pg/ml)	319.42 ± 15.44	356.88 ± 17.79	< 0.001	320.10 ± 14.76	355.83 ± 19.99	< 0.001
TNF-α (pg/ml)	158.66 ± 6.82	174.70 ± 7.12	< 0.001	158.66 ± 6.83	174.55 ± 7.27	< 0.001

BCVA, best-corrected visual acuity; IOP, intraocular pressure; MD, mean deviation; IL-6, interleukin-6; IL-β, interleukin-1 beta; TNF-α, tumor necrosis factor-alpha.

Data are mean ± standard deviation.

Logistic regression analysis of independent risk factors associated with glaucoma for glaucoma onset

Logistic regression analysis was conducted with patients with simple cataracts as the control group and patients with glaucoma as the case group. The results of the univariate analysis showed that there were no statistically significant differences in age, gender, smoking history, drinking history, eye disease history, BCVA, and levels of inflammatory factors IL-6, IL-1β, and TNF-α between the two groups (all P > 0.05); while the MD, IOP, miR-93-5p, and NEAT1 expression were all related influencing factors for the occurrence of glaucoma (all P < 0.001). Further multivariate logistic regression analysis, after correcting for confounding factors, confirmed that MD (OR = 0.084, P = 0.007), IOP (OR = 1.535, P < 0.001), miR-93-5p (OR = 32.183, P < 0.001), and NEAT1 (OR = 68.718, P < 0.001) were all independent factors related to the pathological state of glaucoma (Table 2).

Table 2.

Results of logistic regression analysis for the mild group and the moderate group.

Variables	Univariate analysis			Multivariate analysis
	OR	95% CI	P	OR	95% CI	P
Age	1.024	0.990–1.058	0.166	-	-	-
Gender	1.200	0.726–1.984	0.477	-	-	-
Smoking	0.899	0.520–1.553	0.702	-	-	-
Drinking	0.982	0.563–1.712	0.948	-	-	-
eye disease history	0.972	0.535–1.767	0.925	-	-	-
BCVA	0.527	0.059–4.662	0.564	-	-	-
IL-6	1.002	0.995–1.010	0.513	-	-	-
IL-β	1.001	0.987–1.015	0.878	-	-	-
TNF-α	1.003	0.995–1.011	0.483	-	-	-
MD	0.077	0.032–0.184	< 0.001	0.084	0.014–0.509	0.007
IOP	1.669	1.463–1.904	< 0.001	1.535	1.279–1.841	< 0.001
miR-93-5p	19.846	10.520–37.440	< 0.001	32.183	8.745–118.443	< 0.001
NEAT1	76.263	32.935–176.591	< 0.001	68.718	18.503–255.217	< 0.001

BCVA, best-corrected visual acuity; IOP, intraocular pressure; MD, mean deviation; IL-6, interleukin-6; IL-β, interleukin-1 beta; TNF-α, tumor necrosis factor-alpha.

The targeted binding of NEAT1 to miR-93-5p

In order to elucidate the targeted regulatory relationship between NEAT1 and miR-93-5p, we first used bioinformatics analysis to predict that their sequences had a complementary binding region (Fig. 3A). In addition, we also conducted a dual luciferase reporter gene assay. The results showed that, compared with the negative control, in the cells transfected with the NEAT1-WT vector, the miR-93-5p mimics significantly reduced the luciferase activity (P < 0.001), while the miR-93-5p inhibitor significantly increased the luciferase activity (P < 0.001). However, in cells transfected with the NEAT1-MUT vector, the miR-93-5p mimic or inhibitor had no significant effect on luciferase activity (Fig. 3B).

Fig. 3.

Verification of the targeted binding of NEAT1 and miR-93-5p. (A) Prediction of the complementary binding sequence between NEAT1 and miR-93-5p; (B) Results of dual luciferase reporter gene assay. Data are presented as mean ± standard deviation. Comparisons between groups were performed using one-way analysis of variance; ***P < 0.001 (compared with mimic NC group), &&& P < 0.001 (compared with inhibitor NC group).

Regulation of NEAT1 on cell function and oxidative stress

In this study, a cell damage model was constructed by treating with NaIO₃, and the regulatory role of NEAT1 on cell functions was investigated. The qRT-PCR results showed that the relative expression of NEAT1 in cells significantly increased after NaIO₃ treatment (P < 0.001), and transfection with si-NEAT1 could significantly reduce the high expression of NEAT1 induced by NaIO₃ (Fig. 4A, P < 0.001). The cell counting experiment indicated that the number of cells significantly decreased after NaIO₃ treatment (P < 0.001), and transfection with si-NEAT1 could significantly restore the cell number (Fig. 4B, P < 0.001). The detection of inflammatory factors showed that the concentrations of IL-1β, IL-6, and TNF-α in the cell supernatant significantly increased after NaIO₃ treatment (P < 0.001), and transfection with si-NEAT1 could significantly reduce the levels of inflammatory factors (Fig. 4C, P < 0.001). The detection of oxidative stress indicators revealed that the levels of SOD and POD in the cells significantly increased (P < 0.001), and transfection with si-NEAT1 could significantly reduce the SOD and POD level (Fig. 4D-E, P < 0.001).

Fig. 4.

Regulation of NEAT1 on cell function and oxidative stress. (A) Relative expression levels of NEAT1 in each group of cells; (B) Changes in cell numbers in each group; (C) Concentrations of inflammatory factors in cell supernatants; (D-E) Levels of SOD (D) and POD (E) in cells. Data are presented as mean ± standard deviation. One-way ANOVA was used for comparisons between groups; **P < 0.01, ***P < 0.001 (compared with the Normal group); ##P < 0.01, ####P < 0.0001 (compared with the NaIO₃ + si-NC group).

miR-93-5p mediates the regulation of NEAT1 on cell viability and oxidative stress

The qRT-PCR results showed that the expression of NEAT1 in the cells after NaIO₃ treatment significantly increased (P < 0.001). Silencing NEAT1 could reduce the expression of NEAT1, and co-transfection of miR-93-5p inhibitor could reverse this effect (Fig. 5A, P < 0.001). At the same time, the expression of miR-93-5p significantly decreased after NaIO₃ treatment (P < 0.001). Silencing NEAT1 or overexpressing miR-93-5p can increase the expression of miR-93-5p, while transfecting the miR-93-5p inhibitor will inhibit this effect (Fig. 5B, P < 0.001). The detection of inflammatory factors showed that the concentrations of IL-1β, IL-6, and TNF-α significantly increased after NaIO₃ treatment (P < 0.001). Silencing NEAT1 or overexpressing miR-93-5p could reduce the levels of inflammatory factors, while co-transfecting miR-93-5p inhibitors reversed this improvement effect (Fig. 5C, P < 0.001). The detection of oxidative stress indicators revealed that after treatment with NaIO₃, the levels of SOD and POD significantly increased (P < 0.001). Silencing NEAT1 or overexpressing miR-93-5p could inhibit the levels of SOD and POD, while co-transfecting miR-93-5p inhibitors would counteract this regulatory effect (Fig. 5D-E, P < 0.001).

Fig. 5.

miR-93-5p mediates the regulation of NEAT1 on cell viability and oxidative stress. (A) The relative expression levels of NEAT1 in each group of cells; (B) The relative expression levels of miR-93-5p in each group of cells; (C) The concentrations of inflammatory factors in the cell supernatant; (D-E) The levels of SOD (D) and POD (E) in the cells. Data are presented as mean ± standard deviation. One-way ANOVA was used for comparison between groups; ***P < 0.001 (compared with the Normal group); ###P < 0.001 (compared with the NaIO₃ + si-NEAT1 group); &&&P < 0.001 (compared with the NaIO₃ + miR-93-5p mimic group).

Prediction of downstream target genes of miR-93-5p

TargetScan, miRDB, and starBase were used to predict potential target genes of miR-93-5p. The Venn diagram shows that 716 genes are the common intersection of the three databases (Fig. 6A). The PPI constructed based on these predicted overlapping genes exhibited complex interactions (Fig. 6B). After further screening of the core candidate target genes, the regulatory network constructed shows that the core candidate target genes of miR-93-5p include CDKN1A, MCL1, CCND1, STAT3, E2F1, HIF1A, ESR1, CCND1, E2F3, RB1 (Fig. 6C).

Fig. 6.

Bioinformatics prediction of target genes of miR-93-5p. (A) Venn diagram showing the common target genes of miR-93-5p predicted by TargetScan, miRDB, and starBase. (B) PPI network analysis of the 716 overlapping genes. (C) The top 10 potential target genes of miR-93-5p candidate targets.

Discussion

Glaucoma is the leading irreversible blinding eye disease worldwide^23,24. RGCs are the key cells that facilitate the transmission of visual information from the retina to the brain²⁵. Their dysfunction directly leads to disorders in the transmission of visual signals, thereby causing visual impairment^26–28. In recent years, the ceRNA network composed of lncRNAs and miRNAs has attracted considerable attention in the regulation of the pathogenesis of ocular diseases²⁹. The NEAT1/miR-93-5p axis is the main focus of this study, which methodically investigates its expression characteristics, targeted regulatory relationships, effects on cell functions, and clinical value in glaucoma patients. It also offers new experimental foundation and concepts for glaucoma diagnosis and treatment.

NEAT1 is a type of functionally well-defined long non-coding RNA, has been proven to regulate downstream miRNAs through the ceRNA mechanism and participate in the progression of various diseases³⁰. In the research on eye diseases, previous studies have indicated that the abnormal expression of NEAT1 is associated with the pathological process of eye diseases such as corneal epithelial wound healing³¹. Knockdown of NEAT1 inhibited the proliferation of ARPE19 cells and the EMT process induced by high glucose, as evidenced by the study³². Bioinformatics analysis of differentially expressed genes was conducted on the serum samples of patients with acute glaucoma. The results showed that NEAT1 was significantly upregulated, with the corresponding¹⁶. Our study further confirmed that the expression of NEAT1 in the AH and plasma of glaucoma patients was significantly increased. The clinical analysis showed that NEAT1 in the plasma has favorable diagnostic performance for glaucoma. The expression of NEAT1 is closely related to the MD, IOP and inflammatory factors (IL-6, IL-1β, TNF-α) in patients with glaucoma. In the cell damage model induced by NaIO₃, the high expression of NEAT1 can inhibit cell viability, promote the release of inflammatory factors, and increase the levels of SOD and POD, while silencing NEAT1 can reverse these effects. It is worth noting that when cells are subjected to mild oxidative stress stimulation, in order to resist the oxidative damage caused by excessive accumulation of reactive oxygen species, they will initiate compensatory antioxidant responses^33,34. They will enhance their own antioxidant capacity by upregulating the activity of antioxidant enzymes and activating antioxidant signaling pathways, thereby maintaining the dynamic balance between the oxidative and antioxidant systems³⁵. Previous studies have shown that the activity of SOD in the serum of patients with primary open-angle glaucoma (POAG) is significantly higher than that of normal controls, which is highly consistent with the results of this study³⁶.

The microRNA miR-93-5p is closely related to the pathological mechanism of glaucoma. Numerous studies have confirmed that in models related to the pathological state of glaucoma, the expression pattern of miR-93-5p shows a downward trend. For instance, a microRNA expression analysis of optic nerve lesions in patients with different degrees of glaucoma revealed that the expression of miR-93-5p was significantly lower than that in the samples of cataracts¹⁹. In the acute intraocular hypertension model, miR-93-5p can also activate the PI3K/Akt pathway by targeting the PDCD4 gene, thereby inhibiting the apoptosis of retinal neurons²⁰. This study confirmed that the expression levels of miR-93-5p in the AH and plasma of glaucoma patients were significantly decreased, and in both sample groups, there was a significant negative correlation between miR-93-5p and NEAT1 expression. In terms of clinical value, miR-93-5p in plasma has a favorable diagnostic performance for glaucoma. Logistic regression analysis confirmed that miR-93-5p is a factor related to the pathological state of glaucoma, and its expression is closely related to the MD, IOP, and inflammatory factors of glaucoma patients. Through the dual luciferase reporter gene experiment, it was confirmed that NEAT1 can directly target and bind to miR-93-5p. At the same time, the regulatory effect of NEAT1 on cell damage is mediated by miR-93-5p, and inhibiting miR-93-5p can counteract the protective effect of silencing NEAT1.

We predicted and screened out the core candidate target genes of miR-93-5p using bioinformatics methods, including CDKN1A, MCL1, CCND1, STAT3, E2F1, HIF1A, ESR1, CCND1, E2F3, RB1. These candidate genes are all involved in key biological processes related to glaucoma, such as cell cycle regulation, proliferation and apoptosis, and inflammatory responses. Previous studies have confirmed that in the conjunctival fibroblasts of patients with glaucomatous fibroplasia, the expression of the secreted protein of the target gene CDKN1A has significantly increased³⁷. Network pharmacology analysis indicates that the roots of Scutellaria baicalensis can inhibit the IL-6/HIF-1α pathway by regulating the core target gene ESR1 (estrogen receptor α), thereby exerting an intervention effect on glaucomatous optic nerve atrophy³⁸. The target gene STAT3 is a crucial regulatory factor in the pathogenesis of glaucoma. Its abnormal activation not only leads to the apoptosis of RGCs and visual function impairment, but also participates in regulating the retinal inflammatory response caused by glaucoma³⁹. The post-translational modification regulation of this target gene is also a core target for intervening in glaucoma inflammatory damage⁴⁰. Based on the above research results, we speculate that NEAT1 may bind to miR-93-5p, relieving its inhibition on downstream core target genes such as STAT3 and ESR1, thereby regulating cell viability, inflammatory response and oxidative stress processes, and ultimately participating in the pathological progression of glaucoma. However, these candidate target genes were entirely predicted through bioinformatics, and further experimental verification is needed to confirm their direct interactions.

Although this study has made certain progress, it still has many limitations. Firstly, in the sample design, the control group only included patients with simple cataracts, without including healthy individuals or patients with other eye diseases. This may mean that the diagnostic value of NEAT1 and miR-93-5p reported in this article may not accurately reflect their ability to distinguish glaucoma from other diseases. These results should be regarded as preliminary diagnostic potential rather than validated screening tools. In the future, we will establish a “glaucoma group - cataract group - healthy group” triple control system and conduct multi-center large-sample research. Secondly, in the mechanism research, the specific functions of downstream target genes and their interaction with the classic pathological pathways have not been deeply verified. In the future, we will verify the regulatory role of the NEAT1/miR-93-5p axis in vivo and in vitro, and analyze the interaction mechanism between downstream target genes and pathways.

Conclusion

Our study suggests that the plasma–aqueous dual-fluid NEAT1/miR-93-5p axis may contribute to the pathogenesis of RGCs degeneration in glaucoma. The expression changes of NEAT1 and miR-93-5p in plasma and AH are significantly correlated, and both have good diagnostic efficacy for glaucoma. NEAT1 can release miR-93-5p by targeting and adsorbing it, thereby inhibiting the downstream target genes to exacerbate inflammatory responses and oxidative stress levels, and ultimately mediating RGCs damage. This research provides new ideas and strategies for the precise diagnosis and treatment of glaucoma.

Author contributions

YC and NW carried out the research design and conception; NW analyzed and interpreted the data regarding; XS performed the examination of sample; YC and XS contributed essential reagents or tools; All authors wrote and revised the manuscript. All authors read and approved the final manuscript.

Data availability

The data used and analyzed can be obtained from the corresponding author under a reasonable request.

Declarations

Competing interests

The authors declare no competing interests.

Ethics approval and consent to participate

The experimental procedures were all in accordance with the guideline of the Ethics Committee of Eye and ENT Hospital and has approved by the Ethics Committee of Eye and ENT Hospital. This study complies with the Declaration of Helsinki. A signed written informed consent was obtained from each patient.