The implication of miR-200a and miR-132 expression and their correlations with NF-κB/TNF-alpha signaling in adults with diabetic nephropathy

Abstract

Aim

The primary factor causing chronic renal failure is diabetic nephropathy (DN) worldwide. However, the current biomarkers for DN have limited diagnostic utility. Thus, this work aimed to clarify the implications of microRNA-200a (miR-200a) and microRNA-132 (miR-132) and their correlation with NF-κB (nuclear factor- kappa beta), and, TNF-α (tumor necrosis factor –alpha) signaling to identify biomarkers able to distinguish late-stage from early- stage DN.

Methods

Fifty healthy controls, and 271 type 2 diabetic (T2D) patients (166 male plus 105 female) were enrolled. Participants were stratified into seven groups according to along with the estimated glomerular filtration rate (eGFR), glycated hemoglobin (HbA1c%), healthy controls, diabetes without DN (G1), diabetes with mild renal impairment (G2), and four DN grades (G3a, G3b, G4, and G5).

Results

Compared to healthy controls, the DN groups exhibited linear increases in serum miR-200a, TNF-α, NF-κB, matrix metalloproteinase (MMP-9) and interleukin-6 (IL-6) levels and reductions in miR-132 serum expression. Among the patients, NF-κB and TNF-α produced a negative correlation with miR-132, while, positive correlation has been discovered with miR-200-a. The operating characteristic of the receiver curve (ROC), proved that, miR-200a also miR-132 had good diagnostic performance in distinguishing early from advanced DN.

Conclusion

MiR-200a as well as miR-132 expression levels, and their correlations with NF-κB/TNF-alpha signaling, were able to differentiate between DN patients with lower eGFR, suggesting their utility as diagnostic and prognostic biomarkers.

1. Introduction

End-stage renal dysfunction and chronic kidney disorder are both greatly influenced by diabetic nephropathy (DN), one of the more typical micro-vascular symptoms of diabetic mellitus (DM) (Ruiz-Ortega et al., 2020). DN affects about 40 % diabetes of the second type (T2D) people (Ito et al., 2020). Traditional hypotheses regarding causes DN include glucose metabolites and hyperglycemia (Shao et al., 2021).

The development of diseases is significantly influenced by inflammation (Vakapalli, 2021). Nuclear factor-kappa beta (NF-κB), a fundamental transcription factor (TF), is crucial for inflammation in DN patients. When upstream factors like oxidative stress (Abd El-Hameed et al., 2020), angiotensin II, in addition to advanced glycation end products, activate it, NF-κB separates from its inhibitors, and accelerates into the nucleus to control gene expression, that contribute to the production of inflammatory substances like chemokines, adhesion molecules [Monocyte chemoattractant protein-1, Tumor necrosis factor-alpha (TNF-α), interleukin-6 (IL-6)], and cytokines (Mikuda et al., 2018). TNF-α, contributes to formation multiple diseases, including, chronic kidney disease (CKD), rheumatoid arthritis, and psoriasis (Pina et al., 2016). One of the cytokines that has been extensively studied in relation to kidney illnesses is IL-6, which is also recognized for causing inflammation, such as the activation of beta cells and hepatic acute phase proteins production, as well its roles in metabolic, regenerative, and neural processes (Petreski et al., 2021).

Chronic albuminuria and ongoing reduction in kidney performance are two features of DN (Selby and Taal, 2020). Albuminuria has historically been regarded as a predictor for glomerular injury and DN development, in spite, a few of the risk factors and pathways that exist in DN subjects, are covered by the albuminuria categorization (Pelle et al., 2022). Thus, novel biomarkers are required for disease prediction, diagnosis, and surveillance.

MicroRNAs, (MiRNAs), are oligonucleotides of smaller non-coding RNA, which play a function in the expression of genes. They are required for physiological activities, however, their imbalance is implicated in multiple serious diseases (Donderski et al., 2022), and significant evidence has implicated miRNAs as it develops, also even evolution of DN (Ishii et al., 2020). MicroRNA-200a (miR-200a) has been shown to bind and destroy Kelch-like ECH-associated protein1 (Keap1) mRNA, during breast cancer (Jiang et al., 2020). MicroRNA-132 (miR-132), has become a type of negative gene regulator, that contributes to the complications and pathology of diabetes (Shi et al., 2021). Angiogenesis, cell proliferation, migration, and apoptosis are among the numerous cellular processes that miR-132 is essential for controlling. Numerous cancers are associated with miR-132 abnormal expression (Moghbeli et al., 2021).

The kidney's matrix metalloproteinases (MMPs), a class of endopeptidases, that are zinc-dependent, possessing comparable biochemical characteristics, are connected to both regular physiological alterations and irregular pathological disorders (Yang et al., 2018). MMP-9 might be crucial for leukocyte migration and regional extracellular matrix proteolysis. Furthermore, numerous investigations have demonstrated that MMP-9 acts as a crucial inflammatory indicator, thus influencing the pathophysiology of DN (Xie et al., 2020).

Characterization of circulating, unencrypted RNA (miR-200a-miR-132) expression levels in patients, their associations with glycemic biomarkers in DN, and their correlation with inflammatory biomarkers and MMPs is not understandable. Thus, it was the purpose of the current research to identify the possible utility of serum miR-200a and miR-132 as vital signs for DN and examine their correlations with NF-κB/TNF-alpha signaling in a cohort of diabetic adults with DN of variable severity.

2. Patients and Methods

2.1. Study population

Overall, 271 outpatients with (T2D) were enrolled in the specialized diabetes and nephrology clinic at Beni-Suef University Hospital's Internal Medicine Department, Egypt. Eligible patients were divided into six severity groups, adapting to their estimated glomerular filtration rate (eGFR) (Haneda et al., 2015). Fifty healthy adult males and females matched for age and sex were included as controls. This research was performed according to rules with the announcement of Helsinki and best practice of clinical recommendations, and hospital ethics committee (BSU:7–2021) gave its approval to the study protocols. Samples of blood were drawn between November 2020 and June 2021 after study approval. During the laboratory visits, the patients’ body parameters were also measured.

2.2. Inclusion and experimental design

Healthy controls (n = 50) were selected based on the absence of significant health-related issues and no signs of diabetes/prediabetes [glycated hemoglobin (HbA1c) below 5.7 %, fasting glucose level blow 110 mg/dl, and postprandial glucose level blow 140 mg/dl] or poor kidney function [eGFR ≥ 90 mL/min/ 1.73 m²)]. Patients with diabetes were divided into a non-nephropathy group (G1: HbA1c > 6.5 %, eGFR ≥ 90 mL/min/ 1.73 m², n = 46), a mild DN group (G2: HbA1c > 6.5 %, eGFR: 60–89 mL/min/1.73 m², n = 50), and a DN group (HbA1c > 6.5 %, eGFR < 60 mL/min/ 1.73 m² n = 175). In turn, the DN group was stratified into severity groups as follows: G3a: HbA1c > 6.5 %, eGFR: 45–59 mL/min/1.73 m² (n = 43); G3b: HbA1c > 6.5 %, eGFR: 30–44 mL/min/1.73 m² (n = 40); G4: HbA1c > 6.5 %, eGFR: 15–29 mL/min/1.73 m² (n = 45); G5 end-stage renal disease (ESRD): HbA1c > 6.5 %, eGFR < 15 mL/min/1.73 m² (n = 47).

2.3. Exclusion criteria

Participants with a history of acute and chronic infections, malignancy, hepatic disease, diabetic retinopathy, or other endocrine dysfunctions were excluded from this study.

2.4. Biochemical assays

Following a night of fasting, two samples of 4 mL of blood were obtained from all contributors, one in ethylenediamine tetraacetic acid (EDTA)-treated tubes, and the other in plain tubes. Samples in plain tubes were left for thirty minutes at room temperature, before being centrifuged at 4,000 rpm for serum isolation; meanwhile, blood samples containing EDTA were frozen at − 80 °C until DNA extraction and HbA1c% determination. HbA1c% was assessed, utilising kits from Stanbio (Boerne, Texas, USA), while blood glucose, sodium, calcium, potassium, urea, uric acid and creatinine were identified in serum samples, using dedicated kits from Spinreact (Girona, Spain). Fasting insulin levels were assayed, using radioimmunoassay kits from Diagnosis, outputs, company (Los Angeles, CA, USA). Insulin resistance, was measured based on the homeostatic model evaluation of insulin resistance, (HOMA-IR) where, HOMA-IR = [(Fasting Insulin, µU/ml) × (Fasting Glucose, mmol/L)]/22.5, according to (Matthews et al., 1985). The Chronic Kidney Disease Cooperation in the Field of Epidemiology (CKD-EPI) equaling method is applied for eGFR calculation in adults. (Levey et al., 2008). NF-κB, TNF-α, as well as IL-6 were measured based on an ELISA kit from Thermo Fisher Scientific Inc. in the United States, which depends on conventional sandwich ELISA technology (Bauer and Herrmann, 1991, Bonavida, 1991).

2.5. miR-200a, miR-132 and, MMP-9 assay

Utilising, Direct-zol RNA, Miniprep Plus kit (Cat # R2072; Zymo Research; Irvine; CA; USA), total RNA, was separated from serum samples, and the potency of the RNA, was evaluated, using a Beckman dual spectrophotometer (Brea, CA, USA). Isolated RNA samples were reverse-transcribed; then, Levels of expression were detected via quantitative real-time PCR, using, RT-PCR (One-Step) kit (Cat # 12594100; Thermo Fisher; USA), and the following primer sequences: F:5′ TAACACTGTCTGGTAACGATGT-3′ and R:5′ ATCGTTACCAGACAGTGTTATT-3′ for miR-200a; F:5′ ACCGTGGCTTTCGATTG-3′ and R:5′ GAACATGTCTGCGTATCTC-3′ for miR-132; F:5′ GGGACGCAGACATCGTCATC-3′andR:5′TCGTCATCGTCGAAATGGGC-3′(NM-000660.2) for MMP-9; F:5′GGCGGCACCACCATGTACCCT-3′ and R:5′ AGG GGCCGGACTCGTCATACT-3′(NM-001101.3) for β-actin (the internal control for MMP-9); F: and R: for GAPDH (the internal control for miR-200a). Expression of miR-132, was normalized with that of U6. The RQ of each target gene was measured and standardized against the specified internal control. according to the calculation [2−ΔΔCt] (Livak and Schmittgen, 2001).

2.6. Statistical analysis

All statistical analysis were conducted using the Statistical Package for the Social Sciences (SPSS) 22.0 (SPSS Inc., Chicago, IL, USA). The significant of statistics was established at P value < 0.05. Demographic and clinical parameters are displayed as the arithmetic mean ± the mean of the standard error (SEM). We compared group means using one-way ANOVA with post-hoc, Duncan’s multiple range test for pairwise comparisons. Associations between NF-κB/TNF-α signaling and target gene expression standard were estimate using Pearson’s correlation coefficient. Receiver operating characteristic curves (ROC) were constructed by drawing sensitivity on the Y-axis versus 1-privacy on the X-axis at various cut-off values. The diagnostic accuracy for each cut-off value was assessed by measuring the region under the ROC curve (AUC). A fulfillment of at least 50 % was considered adequate.

3. Results

Those involved in the study, were 49.40 years old on average, and the majority were males (51.71 %). There were marked variations in BMI (body mass index), diastolic pressure of blood, as well as systolic pressure of blood, among the healthy control, diabetic without DN (G1), diabetic with mild impairment (G2), and DN (G3a, G3b, G4, and G5) groups (P < 0.05) (Table 1). Compared to healthy controls, all diabetic groups exhibited significantly higher fasting blood sugar (FBS), HbA1c%, Homa-IR [Fig. 1(A)–(C)], serum creatinine, urea, uric acid [Fig. 2(A)–(C)], and potassium levels Fig. 3(B) (P < 0.05), and significantly lower serum insulin levels (Fig. 1(D), Egfr Fig. 2(D), and serum calcium level (Fig. 3(C)). Furthermore, it was found that, G2, G3a, G3b, and G4 had significantly higher sodium levels than the healthy controls, while a significant decline was observed in sodium concentrations at G5 (ESRD) compared to healthy controls and patients in the earlier stages of DN (G2, G3a) Fig. 3(A) (P < 0.05).

Table 1.

Clinical characteristics of the subjects.

Groups	Healthy control	G1	G2	G3a	G3b	G4	G G5GgG5
Number of subjects	50	46	50	43	40	45	47
Age (Year)	43.71 ± 1.15a	51.08 ± 0.66b	56.12 ± 0.89c	60.02 ± 0.91d	63.02 ± 0.98e	63.88 ± 0.81e	59.06 ± 0.85d
Gender, n (%)
Male	27(54)	20(43)	26(52)	20(46)	23(57)	24(53)	26(56)
Female	23(46)	26(47)	24(48)	23(54)	17(43)	21(47)	21(44)
BMI (Kg/m2)	28.06 ± 0.33a	33.08 ± 0.52 cd	32.16 ± 0.63bcd	31.41 ± 0.41bc	33.62 ± 0.65d	30.36 ± 0.52b	31.28 ± 0.59bc
SBP (mmHg)	124.22 ± 1.08a	125.69 ± 0.87ab	130.94 ± 1.31b	140.76 ± 1.65c	142.13 ± 1.88c	143.12 ± 2.37c	146.26 ± 3.04c
DBP (mmHg)	82.98 ± 0.55a	82.91 ± 0.58a	85.88 ± 0.75ab	88.18 ± 0.98b	88.85 ± 1.08b	88.24 ± 1.57b	87.16 ± 1.71b
miR-200a (RQ)	0.95 ± 0.01a	1.28 ± 0.01a	1.75 ± 0.05b	4.45 ± 0.14c	5.35 ± 0.14d	5.81 ± 0.18e	9.58 ± 0.22f
miR-132 (RQ)	0.96 ± 0.01f	0.68 ± 0.05e	0.49 ± 0.01d	0.32 ± 0.01c	0.26 ± 0.01c	0.16 ± 0.01b	0.07 ± 0.01a
IL-6 (pg/ml)	40.79 ± 1.68a	139.87 ± 2.47b	141.56 ± 3.83b	215.32 ± 2.02c	231.30 ± 5.59d	307.76 ± 7.38e	381.28 ± 6.74f
TNF-α (pg/ml)	119.48 ± 0.97a	145.79 ± 1.26b	150.07 ± 2.99b	194.01 ± 3.96c	272.05 ± 7.16d	276.67 ± 3.81d	305.51 ± 5.48e
NF-κB (ng/ml)	2.11 ± 0.04a	3.37 ± 0.11b	3.69 ± 0.06c	4.28 ± 0.05d	4.35 ± 0.06d	6.65 ± 0.09e	8.77 ± 0.13f
MMP-9 (RQ)	1.21 ± 0.02a	1.72 ± 0.04b	1.78 ± 0.06b	2.11 ± 0.05c	3.03 ± 0.04d	3.39 ± 0.05e	4.35 ± 0.06f

Data were expressed as mean ± SE. Values which share the same superscript symbol are not significantly different. BMI: body mass index, DBP: diastolic blood pressure, G1: stage 1 (kidney damage with normal or increased GFR ≥ 90), G2: stage 2 (kidney damage with mildly decreased GFR: 60–89), G3a: stage 3a (moderately decreased GFR: 30–59), G3b: stage 3b (moderately to severely decreased GFR: 30–44), G4: stage 4 (severely decreased GFR: 15–29),G5: stage 5 (kidney failure, GFR < 15), all GFR in mL/min/1.73 m², IL-6: interleukin-6, miR-200a: microRNA-200a, miR-132: microRNA-132, MMP-9: Matrix metalloproteinase, NF-κB: Nuclear factor- kabba beta, SBP: systolic blood pressure, TNF-α: Tumor necrosis factor-alpha,

Fig. 1.

Diabetic profiles of healthy controls, diabetic and diabetic nephropathy groups. Data are expressed as mean ± SEM. Insignificant differences between two groups according to Duncan’s post hoc multiple comparison tests are indicated by the same superscript symbol.

Fig. 2.

Kidney profiles of healthy controls, diabetic and diabetic nephropathy groups. Data are expressed as mean ± SEM. Insignificant differences between two groups according to Duncan’s post hoc multiple comparison tests are indicated by the same superscript symbol.

Fig. 3.

Electrolytes profiles of healthy controls, diabetic and diabetic nephropathy groups. Data are expressed as mean ± SEM. Insignificant differences between two groups according to Duncan’s post hoc multiple comparison tests are indicated by the same superscript symbol.

TNF-α, NF-κB, and also IL-6 levels were noticeably elevated in all diabetic patient groups than in healthy controls, suggesting the presence of chronic inflammation. TNF-α, NF-κB, along with IL-6 levels were substantially elevated (P < 0.05) during the late stages of DN (G3b, G4, and G5) than during the early stages (G2 and G3a) (Table 1). Moreover, NF-κB and TNF-α were positively correlated with miR-200a in all DN stages (G1, G2, G3a, G3b, G4, and G5), and these correlations were higher throughout disease progression from the diabetic stage (G1) (NF-κB: r = 0.717, P < 0.001; TNF-α: r = 0.471, P < 0.001) to ESRD (G5) (NF-κB: r = 0.936, P < 0.001; TNF-α: r = 0.912, P < 0.001). Whereas, they appeared a significance negative corrrelation with miR-132 in all DN stages, and these correlations were higher through disease progression from diabetic stage (G1) (NF-κB: r = -0.430, P < 0.001; TNF-α: r = -0.421, P < 0.001) to ESRD (G5) (NF-κB: r = -0.972, P < 0.001; TNF-α: r = -0.956, P < 0.001) as shown in Table 2.

Table 2.

Correlations between miR-200a and miR-132 with NF-κB and TNF-α among studied patients’ groups.

Parameters	NF-κB				TNF-α
	miR-200a		miR-132		miR-200a		miR-132
Groups	r	p	r	p	r	p	r	p
G1	0.717	<0.001***	−0.430	<0.001***	0.471	<0.001***	−0.421	<0.001***
G2	0.670	<0.001***	−0.892	<0.001***	0.692	<0.001***	−0.715	<0.001***
G3a	0.664	<0.001***	−0.955	<0.001***	0.583	<0.001***	−0.855	<0.001***
G3b	0.784	<0.001***	−0.949	<0.001***	0.876	<0.001***	−0.914	<0.001***
G4	0.902	<0.001***	−0.969	<0.001***	0.885	<0.001***	−0.961	<0.001***
G5	0.936	<0.001***	−0.972	<0.001***	0.912	<0.001***	−0.956	<0.001***

Correlation was significant at p < 0.05, p < 0.01, and p < 0.001, respectively. G1: stage 1 (kidney damage with normal or increased GFR ≥ 90), G2: stage 2 (kidney damage with mildly decreased GFR: 60–89), G3a: stage 3a (moderately decreased GFR: 30–59), G3b: stage 3b (moderately to severely decreased GFR: 30–44), G4: stage 4 (severely decreased GFR: 15–29), G5: stage 5 (kidney failure, GFR < 15), all GFR in mL/min/1.73 m².

Serum miR-200a and MMP-9 expression levels were significantly elevated in DN phase (G3a, G3b, G4, and G5) than in healthy controls and in later phase (G3b, G4, and G5) than in the early stages (G2 and G3a). Consistent with this finding, miR-132 expression level, was significantly lower in all diabetic patient groups than in healthy controls. Mir-132 expression level likewise markedly lower (P < 0.05) during the late stages of DN (G3b, G4, G5) than in the early stages (G2 and G3a) (Table 1).

Serum miR-132 levels differentiated participants with DN from healthy controls with 95.57 % sensitivity and 100 % specificity (AUC = 0.959; 95 % interval of confidence [CI] = 0.963–0.994; P < 0.001; Fig. 4(a)). In addition, serum miR-132 levels discriminated late stages of DN (G3b, G4, and G5) from early stages (G2 and G3a) with 93.75 % sensitivity and 92.63 % specificity (AUC = 0.954, P < 0.001; Fig. 4(c)). Similarly, serum miR-200a discriminated participants with DN from healthy controls with 99.63 % sensitivity and 100 % specificity (AUC = 1.000; 95 % [CI] = 1.000–1.000; P < 0.001; Fig. 4(b)), thus suggesting its utility as a diagnostic marker. Indeed, serum miR-200a levels discriminated late stages of DN (G3b, G4, and G5) from early stages (G2 and G3a) with 98.86 % sensitivity and 98.95 % specificity (AUC = 0.999, P < 0.001; Fig. 4(d)).

Fig. 4.

Receiver operating characteristic (ROC) curves for microRNA-132 and microRNA-200a in (a, b) early diabetic groups and (c, d) late-stage diabetic nephropathy groups.

4. Discussion

The most severe complication of diabetes that damages the kidneys and can cause death in individuals is DN, which can be caused by chronic hyperglycemia (Shu et al., 2021). Even though microalbuminuria is regarded as the gold standard for early DN evaluation and diagnosis, its accuracy in predicting disease progression is still limited (Abdelaty et al., 2020). Investigating more sensitive indicators for observing the progression of DN may be useful to enable earlier diagnosis and more efficient treatments (Negeem et al., 2023). So, the goal of this project was to clarify the implication of miR-200a and miR-132 expression and their correlations with NF-κB /TNF-α signaling in DN. According to our knowledge, this research is the first to investigate the expression level for (miR-200a - miR-132) in the serum of 271 Egyptian DN cases with varying eGFR and 50 healthy participants. According to our findings, all diabetic patient groups had noticeable elevations in FBS, HbA1c%, creatinine, urea, uric acid, and potassium when compared to healthy controls.

In contrast, fasting insulin, calcium, and eGFR revealed an apparent decline in all investigated groups compared to healthy controls. Sodium levels in G1, G2, G3a, G3b, and G4 significantly increased when compared to healthy controls. While, stage 5 DN (G5) revealed a substantial decline in sodium levels in contrast to all DN and healthy controls, our observations are in parallel with those of earlier studies (Mahmoud et al., 2022). IL-6, a pro-inflammatory substance, precipitates in the beginning and development of prolonged inflammation, possibly lead to the appearance of micro - and macrovascular complications in diabetics (Winter et al., 2018). Our findings showed that IL-6 levels were high in all stages of DN, unlike in normal controls, and there were notable variations in IL-6 levels between the late and early stages. These outcomes matched those of (Abd El-Hameed, 2020), who decided that, IL-6 levels were related closely to many of diabetes-related factors and may be utilized to distinguish between T2D with and without DN. Long-term inflammation is an essential characteristic of type 2 DN, contributing to the pathogenesis and development of the illness (Lv et al., 2020). ILs, are important regulators of the immune system. IL-6 is strongly associated with DN development in patients (Kreiner et al., 2022). In addition, the results of Laishram et al. supported the connection between T2D and serum IL-6 and decided that determining serum IL-6 levels can be a vital sign for diabetes mellitus diagnosis and prediction as well as a useful management tool (Laishram et al., 2017).

TNF–α, is a cell signaling protein, that causes inflammatory processes and one of the cytokines that contribute to a variety of diseases such as CKD, osteoarthritis, and psoriasis (Pina et al., 2016). Our results showed that all diabetic patient groups had significantly higher TNF-α level, and there were notable variations in TNF-α levels between the late and early stages. Our insights confirm those of (El Edela et al., 2020), who discovered that people with DM and diabetes mellitus-chronic kidney disease (DM-CKD) had significantly higher serum TNF-α levels than those without DM-CKD, indicating that, TNF-α may be a key mediator not only of DN, but also of diabetic hepatopathy according to (Abd El-Hameed et al., 2021). NF-κB is a transcription element that contributes to DN inflammation. Our research showed that, NF-κB expression was significantly elevated in all phases of DN relative to healthy control, and the expression of NF-κB varied significantly between the late and early stages. Our findings support the earlier investigation of (Abd El-Hameed, 2022, Abd El-Hameed, 2020), who showed the ability to use NF-κB as monitoring indicator for kidney dysfunction in individuals with diabetes and the evaluation of gene expression in blood and urine samples to detect early stages of DN. Inflammatory penetration of renal cells and tissues can occur during DN as a result of the large number of inflammatory mediators and cytokines released by impaired tissues and kidney cells. Gradually, this causes more secondary inflammation and apoptosis, which exacerbates kidney tissue injury (Talsma et al., 2018). Signaling pathway of NF-κB is a significant signaling pathway that regulates apoptosis and inflammation in a crucial approach. Under physiological circumstances, the crucial transcription factor NF-κB attaches to its inhibitors and remains dormant (Yi et al., 2014). Following damage, NF-κB is free from inhibitors also triggered by inflammatory factors and cytokines, resulting in the stimulation of the NF-κB signaling path. Stimulated NF-κB passes through the nucleus and connects to its transcription factors, subsequently playing an important function in controlling the expression of downstream inflammatory factors and apoptotic effector Caspase-3, as well as in managing inflammation and apoptosis (Liu et al., 2020).

There is growing indication that miRNAs perform a crucial function in renal physiology and pathology, including the progression of kidney fibrosis (Donderski et al., 2022). Our results confirm that miR-200a expression was noticeably elevated in all stages of DN relative to the control group, and the standard of miR-200a expression varied significantly among the late and early stages. The results reported support those of (Kito et al., 2015), who revealed that the acute kidney injury model significantly increased levels of miR-194, miR-192, and miR-200 in plasma. In diabetic rats, miR-200a is suppressed, declines nuclear factor-erythroid2-related factor 2, raises KEAP1, and exacerbates albuminuria and renal fibrosis; miR-200a improves DN and stimulates Keap1 mRNA degradation (Wu et al., 2016). EMT-related substances like the zinc finger E-box binding homeobox 1 (ZEB1), β-catenin, and TGF-β2 that negatively modulate E-cadherin, are among the targets of miR-200a (Guo et al., 2018). Furthermore, (Civantos et al., 2017) discovered that sitagliptin therapy was linked to antioxidant response modulation in the diabetic kidney, including down-regulation of microRNA-21 (miR-21); a novel Keap-1 inhibitor; miR-200a, simultaneously with the clinical and the morphological enhancement. In contrast, miR-200a has been found to be downregulated in the kidneys of DN and unilateral ureter obstruction models (Chen et al., 2020), as well as in NRK52E cells exposed to TGF-1/2, which has been shown to promote EMT and fibrogenesis. Additionally, hepatocyte nuclear factor 1 homeobox B (HNF-1), which is necessary to the progressive of cystic kidney disease, controls the differentiation of the epithelium in the mammalian nephron. MiR-200a expression is reduced in renal epithelial cells and kidneys from HNF-1 knockout mice (Hajarnis et al., 2015).

MiR-132, is an self-growing (endogenous) small RNA that organize gene expression post-transcriptionally, through regulated mRNA breakdown or transcription inhibition (Qian et al., 2017). Angiogenesis, cell proliferation, migration, and apoptosis are just a few of the processes that miR-132 is essential in controlling in cells. Numerous cancers have been linked to the abnormal expression of miR-132 (Moghbeli et al., 2021). Our investigation approved significant down-regulation of miR-132 expression, in all DN stages relative to that in healthy controls. Furthermore, there is a substantial variation in miR-132 expression among the early and late stages. Our results matched the conclusion published by Zhou et al. who observed that miR-132 expression was substantially decreased in placenta tissues and the serum of gestational diabetes mellitus (GDM) patients in comparison to healthy pregnant ladies (Zhou et al., 2019). Furthermore, a negative relationship was observed between concentration of fasting glucose and miR-132 levels in GDM patients. High blood sugar exacerbated MMP-9 expression by suppressing miR-132 levels (Dou et al., 2021). In contrast, (Florijn et al., 2020) found that increased miR-132 circulating levels were related to T2D with nephropathy, and that focusing it reduced blood sugar and enhanced insulin production. Moreover, (Salama et al., 2020) discovered that, T2D patients with mild mental disorders, had notably elevated median miR-132 expression than those with normal mental faculties or those without diabetes who have normal mental faculties. MiR-132 has been shown to influence cell proliferation through injury recovery by managing the extracellular signal-regulated kinase pathways and signal transducer and activator of transcription 3 (STAT3), as well as systematically control STAT3/ERK pathways, genes regulating TGF-signaling, along with cell proliferation (Foxo3/p300) responsible for supporting trans-differentiation and the growth of myofibroblasts throughout kidney fibrosis generation (Xu et al., 2021). Our findings also revealed that, NF-κB and TNF-α levels exhibited a negative correlation with miR-200a, in contrast, positive correlation produced with miR-132 in all the investigated groups. Diabetes alters information about the genome and influences the expression, and functions of different miRNAs via host gene intron transcription (Baker et al., 2017). MiRNAs with unusual expression in the kidney and serum, such as let-7p; miR-33a; miR-140-5p; miR-451: miR-29c; miR-155-3p; miR-31; and miR-146a the mRNA likewise, pro-inflammatory cytokine expression by stimulating or preventing comparable signal transduction mechanisms, increasing cytokine production in the kidney (Zhou et al., 2021).

The MMP-9 gene exists on 20q13.12 chromosome, modifications in SNPs that affect the expression of the MMP-9 gene may control MMP-9 expression and function in DN (Schveigert et al., 2013). Our investigations demonstrated that, MMP-9 expression was markedly elevated in all DN patients' stages relative to healthy controls, and standards of MMP-9 expression varied significantly between the late and the initial period of disease, which goes with result of (Feng et al., 2016) who found in a Han Chinese population that, the MMP-9 1562C/T SNP was related to DN, and the T allele was disease- protective, whereas the C allele exacerbated it.

Finally, ROC analysis results demonstrated that serum miR-200a and miR-132 allow for differentiation between DN cases from healthy controls. Due to its superior ability to distinguish patients from control subjects, serum miR-200a showed diagnostic potential in discriminating late stages from early stages. However, serum miR-132 could differentiate healthy from patient subjects, has an AUC of 0.979, 95.57 % sensitivity, and 100 % specificity. Additionally, miR-132 could differentiate late stages from the early stages having an AUC of 0.954, 93.75 % sensitivity, and 92.63 % specificity. Hence, miR-200a and miR-132 serum expression of DN patients in Egyptian population may be promising circulating biomarkers that can successfully detect and follow disease progression at an early stage.

However, this study has some limitations, including the sample size. Therefore, further large-scale studies and clinical trials are needed; moreover, the functional impacts of these markers on putative target genes and pathways should be evaluated.

5. Conclusion

Serum miR-200a, IL-6, MMP-9, NF-κB, and TNF-α were elevated in DN patients, while, serum miR-132 level was reduced relative to healthy controls. Moreover, these changes were higher in the late phases of the illness than in the early phases. Additionally, the plasma expression of NF-κB, and TNF-α was found to be associated positively with miR-200a and negatively associated with miR-132. Our findings indicate that miR-200a and miR-132 may be utilized as diagnostic biomarkers in distinguishing the late stages of DN from those in the early stages.

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.