Correlation Between Single-Nucleotide Polymorphisms Within miR-30a and Related Target Genes and Risk or Prognosis of Nephrotic Syndrome

Abstract

This study was aimed to figure out the association of single-nucleotide polymorphisms (SNPs) within miR-30a and its downstream molecules (i.e., Notch1, Snail1, p53, CD73, and TET1) with susceptibility to and prognosis of nephrotic syndrome (NS). In the aggregate, 265 patients and 281 healthy controls were gathered, and related laboratory indicators were examined. The miR-30a, Notch1, Snail1, TET1, p53, and CD73 expressions were also evaluated by quantitative real-time polymerase chain reaction (qRT-PCR), immunohistochemistry, or enzyme-linked immunosorbent assay. Besides, the SNPs were genotyped by RT-PCR with aid of ABI-PRISM^™ 377 DNA sequencing instrument. As a result, the NS patients were correlated with remarkably higher 24-h protein excretion, random urine protein/creatinine (UPCR), and serum creatinine, along with lower estimated glomerular filtration rate and serum albumin, when compared with normal subjects (p < 0.05). Furthermore, significant correlations were present between miR-30a expression and the expressions of Notch1 (r _s = −0.350), p53 (r _s = −0.339), CD73 (r _s = −0.300), TET1 (r _s = −0.249), and Snail1 (r _s = −0.829) (all p < 0.05). The SNPs of miR-30a [i.e., rs2222722 (C>T)], Notch1 [i.e., rs3124599 (G>A), rs3124591 (C>T), and rs139994842 (G>A)], Snail1 [i.e., rs6020178 (T>C)], p53 [i.e., rs1042522 (C>G)], and CD73 [i.e., rs9444348 (G>A) and rs4431401 (T>C)] were significantly correlated with both differed NS risk and altered hormone sensitivity to NS (all p < 0.05). Moreover, haplotype AC of CD73 and haplotype ATG of Notch1 were the helpful factors against NS (p < 0.05), yet haplotype GT of CD73 functioned oppositely (p < 0.05). The haplotype AT of CD73 was beneficial to the NS patients for that the carriers could be treated with hormones without severe complications (p < 0.05). Conclusively, the SNPs situated within miR-30a and its downstream molecules (i.e., Notch1, Snail1, p53, CD73, and TET1) could become the promising biomarkers for both NS diagnosis and prediction of NS prognosis.

Introduction

Nephrotic syndrome (NS) is clinically generated by substantial proteinuria (>3.5 g/24 h), hypoproteinemia (i.e., plasma albumin <30 g/L), and hyperlipemia (i.e., serum cholesterol >6.5 mmol/L) (Clement et al., 2011). The NS patients are generally accompanied with pathological changes of minor glomerular and glomerular basement membrane (GBM), which further contributed to formation of proteinuria and finally affected lipolysis efficiency and lipid utilization (Thoenes, 1989). Primary NS (PNS), an original disease within glomerulus, accounts for up to 40% of renal biopsy-confirmed glomerular diseases, yet its pathogenic mechanisms were still far from clear (Hadoux et al., 2010; Wu et al., 2011). In fact, PNS could be diagnosed after determining the etiologies and excluding secondary factors or hereditary diseases, nonetheless, this approach is deficient in sensitivity and specificity. For another, renal biopsy, which includes light microscopic, ultrastructural examination and immunohistochemical examinations, is advantageous in diagnosing PNS with high accuracy, yet its invasive feature is liable to induce diverse complications. Therefore, seeking for a technique to sensitively and specifically diagnose early-stage PNS is of large significance to guiding the treatment and prognosis of PNS.

Over 1000 types of miRNAs discovered within the human genome were estimated to regulate 74–92% of protein-coding genes, and they broadly participated in diverse physiological processes, including cell proliferation, cell apoptosis, cell differentiation, immunity, and metabolism (Ferland-McCollough et al., 2010). The role of miRNAs in regulating the kidney function has also been gradually deepened (Bhatt et al., 2011). For instance, miR-30a expression level was significantly boosted within children who were at the initial stage of PNS, yet it dropped after conduction of inductive therapy that contained adequate hormones. Thus it was suggested that miR-30a expression could be correlated with hormone responsiveness and prognosis of PNS (Luo et al., 2013).

Of note, it has been documented that Notch1, Snail1, p53, CD73, and TET1 were the targeted molecules of miR-30a, although so far the investigated diseases were confined to colorectal cancer, myocardial fibrosis, or idiopathic pulmonary fibrosis (Li et al., 2010; Wang et al., 2015; Yuan et al., 2015; Xie et al., 2017; Zhang et al., 2017). Nonetheless, within the renal tissues of diabetic rats, a remarkable correlation could be discovered between the Snail1 protein level and the urine protein level, which was a major etiology of NS (Fang et al., 2008). Moreover, NS was also a disorder bred by renal cancer (Kuroda et al., 2004), and Notch1, Snail1, p53, CD73, and TET1 were all indicated to participate in the progression of renal cell carcinoma (Erdem et al., 2013; Westerhoff et al., 2014; Fan et al., 2015; Song et al., 2017; Wang et al., 2017). Therefore, it was hypothesized that miR-30a could function to modify the five molecules and regulate the prevalence of NS, and it could be further suspected that the crucial single-nucleotide polymorphisms (SNPs) located within miR-30a, Notch1, Snail1, p53, CD73, and TET1 were probable to elevate the NS incidence by altering the expressional levels of miR-30a, Notch1, Snail1, p53, CD73, and TET1.

On the whole, this investigation was aimed to explore several SNPs of miR-30a, Notch1, Snail1, p53, CD73, and TET1 that were gathered from the previously published reports, and to figure out if their aberrations were associated with dysfunctional kidney and NS development. Through this way, a highly accurate technique could be designed to assist in diagnosing NS and in predicting the NS prognosis.

Materials and Methods

Basic clinical characteristics

This study retrospectively collected 265 PNS patients confirmed with renal biopsy and 281 healthy controls from Liaocheng People's Hospital within the period from February 2016 to November 2016. In line with the laboratory examination, the incorporated subjects should (1) possess ≥3.5 g 24-h urine protein; (2) obtain ≤30 g/L plasma albumin; (3) be accompanied with edema or hyperlipidemia; (4) be at the age of 18–65 years; and (4) have <176.8 μmol/L serum creatinine (SCr). Moreover, the participants would be excluded if (1) they were attacked with secondary and hereditary nephropathy, including diabetic nephropathy, lupus nephritis, hepatitis B-related renal disease, and anaphylactic purpura nephritis; (2) they were conflated with severe primary diseases in heart, brain, liver, and hematopoietic system; (3) they were women at the stage of gestation or sucking; and (4) they had mental abnormalities and did not cooperate with the treatment. The implementation of this study has obtained the approval of Liaocheng People's Hospital and the ethics committee of Liaocheng People's Hospital.

Laboratory measurements

About 3 mL elbow vein blood were gathered from the subjects at early morning when the subjects' stomachs were empty. A fully automatic biochemical analyzer (model number: 7600; Hitachi Corp.) was employed to detect urine protein and 24-h protein excretion levels. Gas chromatography-propyl ethylene diamine thin-layer chromatography was arranged to quantify SCr, and serum albumin was determined applying bromocresol green method. Moreover, the estimated glomerular filtration rate (eGFR) was calculated following the equation, eGFR = 175 × (SCr/88.4)^−1.154 × age^−0.203 × 0.742.

Assessment of miR-30a, Notch1, and Snail1 expressions with quantitative real-time polymerase chain reaction

The miR-30a, Notch1, and Snail1 levels were determined by quantitative real-time polymerase chain reaction (qRT-PCR) with the primers displayed in Supplementary Table S1 (Supplementary Data are available online at www.liebertpub.com/dna) (Invitrogen, China). The reaction system (10 μL) for RT-PCR mainly included the following: diethyl phosphorocyanidate (DEPC) water (3.5 μL), 5× PCR buffer (2 μL), 10 mmol/L dNTP (1 μL), reverse transcription primer (1 μL), reverse transcription enzyme (0.5 μL), and RNA (2 μL). The reaction procedures were enlisted as follows: (1) at 16°C for 30 min; (2) at 42°C for 30 min; and (3) at 85°C for 5 min. The reaction system of RT-PCR (20 μL) consisted of 10× PCR buffer (2 μL), 25 mmol/L MgCl₂ (1.2 μL), 10 mmol/L dNTP (0.4 μL), Taq enzyme (0.3 μL), probe (0.33 μL), cDNA(1 μL), and PCR water (14.77 μL). The cycle process was conducted with 40 cycles of 95°C for 5 min, 95°C for 15 s, and 60°C for 1 min. Ultimately, the 2^−ΔΔCt method was exploited to quantify the miR-30a, Notch1, and Snail1 expressional levels.

Evaluation of the p53 and CD73 levels with enzyme-linked immunosorbent assay

Human p53 and CD73 expressions were measured with the ELISA kit manufactured by R&D Biotech Systems, Inc. (Minneapolis).

Determination of the TET1 levels with immunohistochemistry

The immunohistochemistry results relevant to TET1 level were quantified according to the immunoreactive score (IRS) scoring method recommended by Remmele and Stegner (1987). In particular, staining intensity (SI) and percentage of positive cells (PP) were comprehensively taken into account. SI was graded into four grades of 0 (staining: colorless), 1 (staining: faint yellow), 2 (staining: claybank), and 3 (staining: sepia), and PP was classified into four grades of 1 (PP: 1–24%), 2 (PP: 25–49%), 3 (PP: 50–74%), and 4 (PP: 75–100%). IRS, the product of SI and PP, was finally categorized into four grades of − (0–3 score), + (4 score), ++ (6 score), and +++ (≥8 score).

Genotyping

About 5–10 mL peripheral blood of each subject were fetched, and 1% potassium oxalate was prepared for anticoagulation. The standard salting-out method was performed to extract the genome DNAs. The primers (Supplementary Table S1) were designed with the Primer Premier 6 software and were synthesized with assistance of Sangon Biotech (China). The PCR reaction system (25 μL) consisted of 50 ng genomic DNA, 0.2 μmol/L forward primer, 0.2 μmol/L reverse primer, 100 μmol/L dNTPs, 1.5 mmol/L, and 1.25 U Taq polymerase (Perkin Elmer Corp.). Based on the GeneAmp2400 PCR system (Perkin Elmer Corp.), the PCR reaction went along the following procedures: (1) predegeneration at 95°C for 5 min; (2) 35 cycles of degeneration at 94°C for 1 min, annealing at 53°C for 1.5 min, and extension at 72°C for 1.5 min; and (3) extension at 72°C for 5 min. Exactly 1 μL PCR product for each sample was prepared for electrophoresis within the 1.0 g/L agarose gel and ethidium bromide was then applied for staining. To construct heteroduplex DNAs, per-tube PCR product was first degenerated at 95°C for 3 min and was then renaturated at the speed of −0.5°C/min. Subsequently, all the PCR products were directly sequenced on the ABI-PRISM^™ 377 DNA sequencing instrument.

Treatment

All the patients were guaranteed with adequate rest, light diet, and intake of low-salt and low-fat food. The hormone treatment was managed as 1.0 mg/(kg · day) prednisone at the initial stage (the maximum) or 0.8 mg/(kg · day) methylprednisolone for an 8-week treatment course. If the subjects' urine protein level recovered, the NS patients would be classified into the hormone-sensitive group; otherwise, they would be categorized into the hormone-resistant group.

Statistical analysis

The whole statistical analyses were managed with SPSS11.5 software package. The measurement data were expressed as mean ± standard deviation, and inter-group comparisons were conducted with application of t test. The enumeration data were described with case number or percentage, and they were compared with chi-square test among groups. The haplotypes of related genes would be analyzed if their frequencies within cases and controls were both larger than 0.03. The haplotype analyses were all performed based on Shesis software (http://analysis.bio-x.cn/myAnalysis.php). It would be regarded as statistically significant when p < 0.05.

Results

Clinical features of the subjects

The NS patients and normal controls were well matched concerning their ages and sex ratio (p > 0.05) (Table 1). However, the patients' 24-h protein excretion, random urine protein/creatinine (UPCR), and SCr were generally higher than the control group (p < 0.05), and the eGFR and serum albumin levels of normal subjects significantly outnumbered those of NS patients (p < 0.05). Moreover, the NS participants could be pathologically classified into 94 with mesangial proliferative glomerulonephritis (MPGN), 67 with podocyte lesion (PCL), 58 with glomerular interstitial nephritis (IGN), and 46 with glomerular lesions (GMC). Among the 265 NS patients, ∼57.35% of the investigated ones showed symptoms of hormone sensitivity, while the rest were resistant to hormone.

Table 1.

The Main Clinical Characteristics of All Included Patients and Healthy People

Clinical characteristics	Nephrotic syndrome group	Normal group	t test/χ² test	p-Value
Number	265	281
Age (years)	24.28 ± 5.15	25.30 ± 7.31	1.76	0.079
Gender
Male	169	177
Female	96	104	0.04	0.849
Laboratory measurements
24-h protein excretion (g/24 h)	5.46 ± 0.11	0.06 ± 0.02	808.90	<0.001
Random UPCR (g/g)	1.31 ± 0.40	0.87 ± 0.26	15.32	<0.001
SCr (mg/dL)	1.14 ± 0.28	0.86 ± 0.34	10.47	<0.001
eGFR (mL/min per 1.73 m²)	70.50 ± 16.22	91.34 ± 15.61	5.30	<0.001
Serum albumin (g/dL)	2.61 ± 0.08	4.73 ± 0.13	227.90	<0.001
Pathological type
MPGN	94	—
PCL	67	—
IGN	58	—
GMC	46	—
Drug resistance
Hormone sensitive	152	—
Hormone resistance	113	—

The bold font indicates a result with statistical meaning.

SCr, serum creatinine; eGFR, estimated glomerular filtration rate; MPGN, mesangial proliferative glomerulonephritis; PCL, podocyte lesion; IGN, glomerular interstitial nephritis; GMC, glomerular lesions; UPCR, urine protein/creatinine.

Comparison of the expressional levels relevant to miR-30a, Notch1, Snail1, p53, CD73, and TET1 between NS patients and healthy controls

As Table 2 was illustrated, the expression levels of miR-30a, Notch1, Snail1, p53, and CD73 were greatly upregulated within the NS group, when compared with the healthy controls (all p < 0.05). In contrast, the TET1 level followed the trend that the expressional levels of the above-mentioned molecules in the control group were largely beyond those of the case group (p < 0.05). Besides, miR-30a expression was remarkably correlated with the expressions of Notch1 (r _s = −0.350), p53 (r _s = −0.339), CD73 (r _s = −0.300), TET1 (r _s = −0.249), and Snail1 (r _s = −0.829) (all p < 0.05) (Fig. 1).

FIG. 1.

miR-30a expression was negatively correlated with the expressions of Notch1 (A), p53 (B), CD73 (C), TET1 (D), and Snail1 (E).

Table 2.

Comparison Between Nephrotic Syndrome Patients and Healthy People About the Expression Level of miR-30a, Notch1, Snail1, p53, CD73, and TET1

Factors	Nephrotic syndrome	Normal	t test	p Value	OR ^a	95% CI	p Value
miR-30a	1.57 ± 0.80	1.00 ± 0.08	11.88	<0.001	11.30	6.59–19.36	<0.001
Notch1	1.86 ± 0.52	0.50 ± 0.23	39.9	<0.001	35.97	21.11–61.29	<0.001
Snail1	9.65 ± 1.48	0.00 ± 0.00	109.3	<0.001	457.45	0.00 to +∞	0.987
p53 (pg/mL)	36.82 ± 7.14	15.31 ± 3.46	45.19	<0.001	2.30	1.79–2.94	<0.001
CD73 (pg/mL)	1.44 ± 0.69	0.73 ± 0.31	15.66	<0.001	14.19	8.75–23.01	<0.001
TET1	3.56 ± 0.67	5.27 ± 0.86	25.81	<0.001	0.05	0.03–0.08	<0.001

The bold font indicates a result with statistical meaning.

The OR results reflect the regression analysis between expression level of the factors and the risk of nephrotic syndrome.

OR, odds ratio; CI, confidence interval.

Association of SNPs and haplotypes within miR-30a, Notch1, Snail1, p53, CD73, and TET1 with the onset of NS

Regarding the rs2222722 (C>T) of miR-30a, its T allele was associated with reduced NS prevalence in comparison to the C allele (odds ratio [OR] = 0.55, 95% confidence interval [CI]: 0.42–0.72, p < 0.001) (Table 3). Considering Notch1, the mutant alleles of rs3124591 (C>T) and rs139994842 (G>A) tended to significantly increase NS risk when compared with their wild alleles (OR = 1.42, 95% CI: 1.07–1.90, p = 0.016; OR = 1.33, 95% CI: 1.03–1.72, p = 0.031), while the mutant allele of rs3124599 functioned oppositely (OR = 0.47, 95% CI: 0.37–0.61, p < 0.001). In addition, both Snail1 rs6020178 (T>C) and p53 rs1042522 (C>G) were tightly linked with incremental susceptibility to NS under the allelic model (OR = 1.36, 95% CI: 1.06–1.73, p = 0.014; OR = 1.41, 95% CI: 1.10–1.80, p = 0.007). As far as CD73 was concerned, the mutant alleles of either rs9444348 (G>A) or rs4431401 (T>C) were regarded as the protective elements for NS (OR = 0.69, 95% CI: 0.52–0.91, p = 0.008; OR = 0.63, 95% CI: 0.49–0.81, p < 0.001), whereas TET1 rs5030882 (C>T) probably acted as the hazardous factor for NS (OR = 1.64, 95% CI: 1.19–2.26, p = 0.003). Furthermore, haplotype AC of CD73 and haplotype ATG of Notch1 were both indicated as the advantageous factor in fighting against NS, yet haplotype GT of CD73 might enable the subjects to more easily suffer from NS (Table 4).

Table 3.

The Association of Single-Nucleotide Polymorphisms Within miR-30a, Notch1, Snail1, p53, CD73, and TET1 with the Onset of Nephrotic Syndrome

			Sample size		Frequency of mutant allele		Allelic model				Homozygote model				Recessive model
Gene	rs number	Allele change	Case	Control	Case	Control	OR	LL	UL	p Value	OR	LL	UL	p Value	OR	LL	UL	p Value
miR-30a	rs2222722	C>T	265	281	0.22	0.34	0.55	0.42	0.72	<0.001	0.50	0.35	0.70	<0.001	0.40	0.21	0.78	0.006
	rs1358379	T>C	265	281	0.15	0.13	1.17	0.83	1.65	0.360	1.19	0.81	1.74	0.371	1.28	0.39	4.24	0.687
Notch1	rs3124599	G>A	265	281	0.27	0.44	0.47	0.37	0.61	<0.001	0.40	0.28	0.57	<0.001	0.34	0.19	0.58	<0.001
	rs3124607	G>A	265	281	0.58	0.61	0.89	0.70	1.13	0.324	0.84	0.53	1.32	0.444	0.86	0.61	1.22	0.403
	rs61751489	C>T	265	281	0.67	0.63	1.16	0.91	1.49	0.235	1.22	0.73	2.04	0.436	1.21	0.86	1.70	0.269
	rs3124591	C>T	265	281	0.81	0.75	1.42	1.07	1.90	0.016	1.97	0.89	4.36	0.087	1.45	1.03	2.05	0.033
	rs139994842	G>A	265	281	0.72	0.66	1.33	1.03	1.72	0.031	1.62	0.91	2.86	0.097	1.37	0.98	1.92	0.068
Snai1	rs6125849	G>A	265	281	0.32	0.29	1.19	0.92	1.54	0.194	1.18	0.84	1.65	0.333	1.46	0.81	2.65	0.206
	rs4647959	T>C	265	281	0.28	0.33	0.80	0.62	1.03	0.086	0.76	0.54	1.06	0.109	0.73	0.41	1.30	0.282
	rs6020178	T>C	265	281	0.43	0.36	1.36	1.06	1.73	0.014	1.66	1.17	2.36	0.004	1.24	0.77	1.97	0.375
p53	rs1042522	C>G	265	281	0.39	0.31	1.41	1.10	1.80	0.007	1.27	0.91	1.79	0.162	2.42	1.42	4.11	0.001
	rs1642785	C>G	265	281	0.36	0.31	1.26	0.98	1.62	0.076	1.30	0.93	1.83	0.125	1.44	0.84	2.48	0.182
	rs2287499	G>C	265	281	0.74	0.71	1.18	0.91	1.54	0.220	1.09	0.63	1.89	0.749	1.26	0.90	1.77	0.173
CD73	rs9444348	G>A	265	281	0.21	0.28	0.69	0.52	0.91	0.008	0.57	0.40	0.80	0.001	0.97	0.52	1.79	0.911
	rs4431401	T>C	265	281	0.29	0.40	0.63	0.49	0.81	<0.001	0.50	0.36	0.71	<0.001	0.75	0.47	1.19	0.222
	rs9450282	A>G	265	281	0.69	0.74	0.80	0.61	1.04	0.092	0.61	0.33	1.13	0.113	0.81	0.58	1.13	0.209
TET1	rs10762236	G>T	265	281	0.77	0.81	0.75	0.56	1.01	0.056	0.57	0.26	1.29	0.174	0.74	0.52	1.05	0.094
	rs7913568	C>T	265	281	0.69	0.64	1.23	0.96	1.58	0.106	1.30	0.76	2.20	0.338	1.31	0.93	1.84	0.119
	rs3998860	A>G	265	281	0.72	0.77	0.79	0.60	1.04	0.093	0.74	0.37	1.46	0.383	0.75	0.54	1.06	0.099
	rs5030882	C>T	265	281	0.86	0.80	1.64	1.19	2.26	0.003	1.38	0.58	3.28	0.465	1.83	1.26	2.65	0.001

The bold font indicates a result with statistical meaning.

LL, lower limit; UL, upper limit.

Table 4.

The Association of Haplotype Within CD73 and Notch1 With the Onset of Nephrotic Syndrome

			Case		Control
Gene	rs number	Haplotype	Frequency	Number	Frequency	Number	OR	LL	UL	p-Value
CD73	rs9444348_rs4431401	GT	0.56	149	0.43	121	1.70	1.21	2.38	0.002
		GC	0.23	61	0.29	81	0.74	0.50	1.09	0.122
		AT	0.15	39	0.17	48	0.85	0.53	1.34	0.473
		AC	0.06	16	0.11	31	0.52	0.28	0.97	0.038
Notch1	rs3124599_rs3124591_rs139994842	GCG	0.04	10	0.05	13	0.81	0.35	1.88	0.620
		GCA	0.10	26	0.09	26	1.07	0.60	1.89	0.824
		GTG	0.17	44	0.14	40	1.20	0.75	1.91	0.443
		GTA	0.43	113	0.28	78	1.93	1.35	2.76	<0.001
		ACA	0.04	10	0.07	20	0.51	0.23	1.11	0.087
		ATG	0.06	16	0.11	32	0.50	0.27	0.93	0.027
		ATA	0.16	42	0.22	61	0.68	0.44	1.05	0.080

The bold font indicates a result with statistical meaning.

The distribution of genotypes located within miR-30a, Notch1, Snail1, p53, CD73, and TET1 among the pathological types of NS

The heterozygote CT of miR-30a rs2222722 was scattered quite dissimilarly from homozygote CC among NS patients with MPGN, PCL, IGN, and GMC (p = 0.002) (Table 5). With respect to p53 rs1042522, the percentages of genotypes CG and GG were, respectively, considerably distinct among the four pathological types when compared with genotype CC (p < 0.05). Besides, the heterozygotes of CD73 rs9444346 (i.e., GA) and rs4431401 (i.e., TC) appeared to be distinctly distributed among the pathological types, with wide genotypes as the reference (both p = 0.001). Finally, it was observed that the mutant homozygote TT of TET1 rs5030882 could possibly endow the NS subjects with significantly different pathological types (p < 0.05).

Table 5.

The Association of Single-Nucleotide Polymorphisms Within miR-30a, Notch1, Snail1, p53, CD73, and TET1 With the Pathological Type of Nephrotic Syndrome

				Pathological type
Gene	rs number	Allele change	Genotype	MPGN	PCL	IGN	GMC	χ² test	p-Value
miR-30a	rs2222722	C>T	11	72	34	28	27
			12	19	28	26	18	15.04	0.002
			22	3	5	4	1	4.71	0.195
Notch1	rs3124599	G>A	11	58	29	32	22
			12	31	30	23	20	4.29	0.232
			22	5	8	3	4	4.73	0.193
	rs3124591	C>T	11	7	6	2	3
			12	34	19	21	23	2.56	0.465
			22	53	42	35	20	1.44	0.697
	rs139994842	G>A	11	11	8	7	6
			12	40	29	30	17	0.43	0.934
			22	43	30	21	23	0.26	0.967
Snai1	rs6020178	T>C	11	25	18	23	16
			12	51	37	26	25	3.12	0.373
			22	18	12	9	5	3.04	0.385
p53	rs1042522	C>G	11	38	34	26	7
			12	29	30	27	27	12.97	0.005
			22	27	3	5	12	24.86	<0.001
CD73	rs9444348	G>A	11	66	42	27	38
			12	25	19	24	3	17.64	0.001
			22	3	6	7	5	6.53	0.089
	rs4431401	T>C	11	38	41	32	35
			12	39	17	20	6	16.57	0.001
			22	17	9	6	5	5.87	0.118
TET1	rs5030882	C>T	11	4	2	1	2
			12	9	22	11	12	3.93	0.270
			22	81	43	46	32	14.13	0.003

The bold font indicates a result with statistical meaning.

1 means wild allele; 2 means mutant allele.

Association of SNPs and haplotypes within miR-30a, Notch1, Snail1, p53, CD73, and TET1 with the hormone sensitivity to NS

In accordance with Table 6, heterozygote TC of miR-30a rs2222722 was accompanied with enhancive hormone sensitiveness when compared with the homozygote CC (OR = 1.82, 95% CI: 1.07–3.10, p = 0.027). Similarly, genotype GA of CD73 rs9444348 was more likely to encourage the occurrence of hormone sensitiveness than genotype GG (OR = 2.58; 95% CI: 1.42–4.69; p = 0.002). The homozygotes AA of Notch1 rs139994842 and CC of Snail1 rs6020178 could render the NS subjects more susceptible to hormone treatments (AA vs. CC, OR = 2.89, 95% CI: 1.29–6.44, p = 0.008; CC vs. TT, OR = 2.30, 95% CI: 1.04–5.09, p = 0.037). Also, the haplotype AT of CD73 made up of rs9444348 and rs4431401 served as the positive aspect for NS patients who were treated with hormones (OR = 2.19, 95% CI: 1.04–4.59, p = 0.036), since the hormone therapy could work quite well owing to their sensitivity to hormones (Table 7).

Table 6.

The Association of Single-Nucleotide Polymorphisms Within miR-30a, Notch1, Snail1, p53, CD73, and TET1 With the Hormone Sensitivity to Nephrotic Syndrome

				Drug resistance
Gene	rs number	Allele change	Genotype	Hormone sensitive	Hormone resistant	OR	95% CI	χ² test	p-Value
miR-30a	rs2222722	C>T	11	83	78
			12	60	31	1.82	1.07–3.10	4.90	0.027
			22	9	4	2.11	0.63–7.15	1.51	0.219
Notch1	rs3124599	G>A	11	85	56
			12	56	48	0.77	0.46–1.28	1.02	0.314
			22	11	9	0.81	0.31–2.07	0.20	0.652
	rs3124591	C>T	11	10	8
			12	57	40	1.14	0.41–3.14	0.06	0.800
			22	85	65	1.05	0.39–2.80	0.01	0.928
	rs139994842	G>A	11	15	17
			12	53	63	0.95	0.44–2.09	0.01	0.905
			22	84	33	2.89	1.29–6.44	7.00	0.008
Snai1	rs6020178	T>C	11	44	38
			12	76	63	1.04	0.60–1.80	0.02	0.883
			22	32	12	2.30	1.04–5.09	4.35	0.037
p53	rs1042522	C>G	11	66	39
			12	64	49	0.77	0.45–1.33	0.87	0.350
			22	22	25	0.52	0.26–1.04	3.43	0.064
CD73	rs9444348	G>A	11	86	87
			12	51	20	2.58	1.42–4.69	10.00	0.002
			22	15	6	2.53	0.94–6.83	3.54	0.060
	rs4431401	T>C	11	84	62
			12	46	36	0.94	0.55–1.63	0.04	0.833
			22	22	15	1.08	0.52–2.26	0.04	0.832
TET1	rs5030882	C>T	11	4	5
			12	23	31	0.93	0.22–3.84	0.01	0.917
			22	125	77	2.03	0.53–7.79	1.10	0.294

The bold font indicates a result with statistical meaning.

1 means wild allele; 2 means mutant allele.

Table 7.

The Association of Haplotype Within miR-30a, Notch1, Snail1, p53, CD73, and TET1 With the Hormone Sensitiveness to Nephrotic Syndrome

			Hormone sensitive group		Hormone resistance group
Gene	rs number	Haplotype	Frequency	Number	Frequency	Number	OR	LL	UL	p-Value
CD73	rs9444348_rs4431401	GT	0.51	78	0.61	69	0.67	0.41	1.10	0.114
		GC	0.22	33	0.25	28	0.84	0.47	1.50	0.557
		AT	0.19	29	0.10	11	2.19	1.04	4.59	0.036
		AC	0.08	12	0.04	5	1.85	0.63	5.41	0.254
Notch1	rs3124599_rs3124591_rs139994842	GCG	0.05	8	0.08	9	0.64	0.24	1.72	0.375
		GCA	0.14	21	0.10	11	1.49	0.69	3.22	0.313
		GTG	0.15	23	0.23	26	0.60	0.32	1.11	0.102
		GTA	0.41	62	0.30	34	1.60	0.96	2.68	0.073
		ACA	0.05	7	0.04	5	1.04	0.32	3.37	0.944
		ATG	0.05	8	0.09	11	0.52	0.20	1.33	0.163
		ATA	0.14	22	0.12	14	1.20	0.58	2.46	0.624

The bold font indicates a result with statistical meaning.

Discussion

Podocytes, the terminally differentiated epithelial cells, reside in the visceral layer of the Bowman's capsule (Waters et al., 2008). Various molecules (e.g., α1β3 integrin, integrin ligase, and dystroglycan) located within the basement membrane of podocytic process are crucial to maintain the accurate localization of podocytes, and they appear to be pivotal for the presence of proteinuria (Kojima et al., 2004; Yang et al., 2005; Kanasaki et al., 2008). For instance, the abnormally expressed α1β3 integrin could lead to irregular assembling of podocytes, fragmentation of GBM, and finally proteinuria (Chen et al., 2006). Apart from functioning as the static molecular sieve to prevent proteinuria, podocytes could also restrain the passing of negatively charged proteins (e.g., podocalyxin and podoplanin) in a charge-barrier manner (Song et al., 2010). In addition, the skeletal proteins of podocytes are also linked with alleviated or aggravated development of proteinuria, including actin, α-actinin-4, and synaptopodin (Letavernier et al., 2007; Arias et al., 2009; Ferrandi et al., 2010). All in all, since proteinuria served as a prominent characteristic of NS, the normal functioning of podocytes was suspected to contribute much to the reduced prevalence of NS by maintaining the absence of proteinuria.

miR-30a expressions were enriched in the kidney, lung, liver, and heart of mice, and they were also existent within the kidney of humans, rats, and zebra fish (Sun et al., 2004; Naraba and Iwai, 2005; Wienholds et al., 2005; Agrawal et al., 2009). It was authenticated that podocyte-specific mice whose Dicer was knocked out were observed with foot process fusion, vacuolization, and formation of crescents. Then, the mice presented symptoms of proteinuria and rapidly progressed into end-stage renal disorder. Correspondingly, miR-30a expressed within tubular epithelial cells and sertoli cells were nearly unobservable about 3 weeks after knockout, insinuating that miR-30a was crucial to maintain the normal functions of sertoli cells (Harvey et al., 2008). Moreover, miR-30 family could modify the growth and development of Xenopus laevis protonephridium, especially the differentiation and proliferation of renal tubules (Agrawal et al., 2009). Furthermore, miR-30a-5p was upregulated within the urine of focal segmental glomerular sclerosis patients, and the patients sensitive to hormone therapy were associated with the remarkably dropped miR-30a-5p expression about 8 weeks after the treatment. It was implied that miR-30 could be an injury-related biomarker, and it might predict the treatment efficacy of hormones (D'Agati, 2003; Zhang et al., 2014b).

Interestingly, miR-30 family could lessen the apoptosis of podocytes by directly suppressing the activity of Notch1 and p53 signaling pathways (Fig. 2) (Shi et al., 2013). The conformational variation of Notch receptors owing to combination with ligands would emit the intracellular domain of Notch and hinder the expressions of genes relevant to cell differentiation, cell proliferation, and cell apoptosis (Niranjan et al., 2008; Waters et al., 2012). Furthermore, Lin et al. (2010) discovered that under hyperglycemic conditions, the activated Notch signaling pathway within immortal podocytes would cut down the podocalyxin expressions and induce podocyte lesions. Besides, the highly activated Notch pathway induced by high glucose could be inhibited, after rendering Janus activator 2 and I-type depressor of transforming growth factor (TGF) 2 (Niranjan et al., 2008). Since Janus kinase/activating transcription factor pathway synthesized with Notch signaling to regulate the apoptosis of enterocytes, and TGFβ1 mediated the Notch signaling-modified retarded growth of epithelial cells, it was hypothesized that Notch signaling might coordinate with multiple pathways to cause podocyte lesions (Niimi et al., 2007; Jiang et al., 2009).

FIG. 2.

miR-30a interacted with CD73, TET1, Notch1, p53, and Snail1 to inhibit cell apoptosis. Black arrows represented the hindering action, and gray arrows were symbolic of the promoting action.

In addition, p53, a crucial nuclear transcription factor, not only impacted cell apoptosis in a Snail1-dependent manner (Kim et al., 2011) but also interacted with Notch1 and mastered its expression (Lefort et al., 2007). The zinc finger domain of Snail1 could combine with the CAGGTG sequence within E-cadherin promoter region, thereby downregulating the E-cadherin expression and initiating the epithelial mesenchymal transition (EMT) process (Barrallo-Gimeno and Nieto, 2005). Snail1 was also upregulated within the renal tubular cells of diverse nephropathy models, and it was involved with elevated prevalence of EMT within renal tubular epithelial cells and renal fibrosis (Lange-Sperandio et al., 2007; Ohnuki et al., 2012). Moreover, overexpressed Snail1 was observed within the injured podocytes of the puromycin amino nucleoside nephritis mouse models, which was suggestive of its role in encouraging the podocyte lesions (Matsui et al., 2007). Besides, p53 was subject to the modulation of TET1 in contributing to altered proliferation of gastric cancer cells, and this procedure was completed by demethylation-coupled DNA repair, implying that TET1 was also implicated in changing the apoptotic frequency of podocytes for its effect on p53 (Fu et al., 2014).

As for CD73, which was anchored onto the outside surfaces of cell membrane by glycosylphosphatidylinositol, it participated in both the salvage synthesis pathway metabolized by purine nucleotides and such physiological functions as transmembrane signal transduction and cell adhesion (Naito and Lowenstein, 1981; Airas et al., 2000; Zhou et al., 2001; Niemela et al., 2004). More than that, CD73, the surface marker of mesenchymal stem cells, was found to be expressed within the urine-derived stem cells (USCs) (Zhang et al., 2008). The USCs were superior to other somatic stem cells in treating chronic kidney disease (CKD), and they were potential indicators for early-stage renal damages that were related with CKD (Zhang et al., 2014a). Thus, it was suspected that CD73 might also be symbolic of the renal lesions caused by NS.

Even though there appeared a reaction trajectory among the studied molecules (i.e., miR-30a, CD73, Snail1, Notch1, p53, and TET1), it was only a conjecture, and certain systematic analyses were in demand to explain them based on in vivo and in vitro studies. With respect to the clinical study itself, the limited sample size and constrained ethnicities of the subjects were employed to account for the interrelationship between biomarkers and NS, which could generate bias when the study results were applicable to other populations. Finally, we could not neglect one aspect that the miR-30a was also the downstream molecule of lncRNAs or even circRNAs, and the functional mechanism should be expanded, so that the desirable biomarkers could be explored to assist in the early diagnosis and treatment for NS.

All in all, several works have been done to test the role of miR-30a, CD73, Snail1, Notch1, p53, and TET1 for NS diagnosis and prognosis, further in-depth investigations were still in demand.

Footnotes

Authors' Contributions

Conceived and designed the experiments: R.Y., H.H., M.W., and Z.M.; performed the experiments: R.Y., H.H., and M.W.; analyzed the data: R.Y. and H.H.; drafted the article: Z.M. All authors read and approved the final article.

Disclosure Statement

No competing financial interests exist.

References

Agrawal

, Tran

, and Wessely

(2009). The miR-30 miRNA family regulates Xenopus pronephros development and targets the transcription factor Xlim1/Lhx1. Development, 136, 3927–3936.

Airas

, Niemela

, and Jalkanen

(2000). CD73 engagement promotes lymphocyte binding to endothelial cells via a lymphocyte function-associated antigen-1-dependent mechanism. J Immunol, 165, 5411–5417.

Arias

L.F.

, Vieco

B.E.

, and Arteta

A.A.

(2009). [Expression of nephrin, podocin and a-actinine-4 in renal tissue of patients with proteinuria]. Nefrologia, 29, 569–575(Article in Spanish).

Barrallo-Gimeno

, and Nieto

M.A.

(2005). The Snail genes as inducers of cell movement and survival: implications in development and cancer. Development, 132, 3151–3161.

Bhatt

, Mi

Q.S.

, and Dong

(2011). microRNAs in kidneys: biogenesis, regulation, and pathophysiological roles. Am J Physiol Renal Physiol, 300, F602–F610.

Chen

C.A.

, Tsai

J.C.

, Su

P.W.

, Lai

Y.H.

, and Chen

H.C.

(2006). Signaling and regulatory mechanisms of integrinalpha3beta1 on the apoptosis of cultured rat podocytes. J Lab Clin Med, 147, 274–280.

Clement

L.C.

, Avila-Casado

, Mace

, Soria

, Bakker

W.W.

, Kersten

, et al. (2011). Podocyte-secreted angiopoietin-like-4 mediates proteinuria in glucocorticoid-sensitive nephrotic syndrome. Nat Med, 17, 117–122.

D'Agati

(2003). Pathologic classification of focal segmental glomerulosclerosis. Semin Nephrol, 23, 117–134.

Erdem

, Oktay

, Yildirim

, Uzunlar

A.K.

, and Kayikci

M.A.

(2013). Expression of AEG-1 and p53 and their clinicopathological significance in malignant lesions of renal cell carcinomas: a microarray study. Pol J Pathol, 64, 28–32.

10.

Fan

, He

, and Xu

(2015). Restored expression levels of TET1 decrease the proliferation and migration of renal carcinoma cells. Mol Med Rep, 12, 4837–4842.

11.

Fang

K.Y.

, Lou

J.L.

, Xiao

, Shi

M.J.

, Gui

H.Z.

, Guo

, et al. (2008). [Transforming growth factor-beta1 and Snail1 mediate tubular epithelial-mesenchymal transition in diabetic rats]. Sheng Li Xue Bao (Article in Chinese), 60, 125–134.

12.

Ferland-McCollough

, Ozanne

S.E.

, Siddle

, Willis

A.E.

, and Bushell

(2010). The involvement of microRNAs in type 2 diabetes. Biochem Soc Trans, 38, 1565–1570.

13.

Ferrandi

, Cusi

, Molinari

, Del Vecchio

, Barlassina

, Rastaldi

M.P.

, et al. (2010). alpha- and beta-Adducin polymorphisms affect podocyte proteins and proteinuria in rodents and decline of renal function in human IgA nephropathy. J Mol Med, 88, 203–217.

14.

H.L.

, Ma

, Lu

L.G.

, Hou

, Li

B.J.

, Jin

W.L.

, et al. (2014). TET1 exerts its tumor suppressor function by interacting with p53-EZH2 pathway in gastric cancer. J Biomed Nanotechnol, 10, 1217–1230.

15.

Hadoux

, Vignot

, and De La Motte Rouge

(2010). Renal cell carcinoma: focus on safety and efficacy of temsirolimus. Clin Med Insights Oncol, 4, 143–154.

16.

Harvey

S.J.

, Jarad

, Cunningham

, Goldberg

, Schermer

, Harfe

B.D.

, et al. (2008). Podocyte-specific deletion of dicer alters cytoskeletal dynamics and causes glomerular disease. J Am Soc Nephrol, 19, 2150–2158.

17.

Jiang

, Patel

P.H.

, Kohlmaier

, Grenley

M.O.

, McEwen

D.G.

, and Edgar

B.A.

(2009). Cytokine/Jak/Stat signaling mediates regeneration and homeostasis in the Drosophila midgut. Cell, 137, 1343–1355.

18.

Kanasaki

, Kanda

, Palmsten

, Tanjore

, Lee

S.B.

, Lebleu

V.S.

, et al. (2008). Integrin beta1-mediated matrix assembly and signaling are critical for the normal development and function of the kidney glomerulus. Dev Biol, 313, 584–593.

19.

Kim

N.H.

, Kim

H.S.

, Li

X.Y.

, Lee

, Choi

H.S.

, Kang

S.E.

, et al. (2011). A p53/miRNA-34 axis regulates Snail1-dependent cancer cell epithelial-mesenchymal transition. J Cell Biol, 195, 417–433.

20.

Kojima

, Davidovits

, Poczewski

, Langer

, Uchida

, Nagy-Bojarski

, et al. (2004). Podocyte flattening and disorder of glomerular basement membrane are associated with splitting of dystroglycan-matrix interaction. J Am Soc Nephrol, 15, 2079–2089.

21.

Kuroda

, Ueno

, Okada

, Shimada

, Akita

, Tsukamoto

, et al. (2004). Nephrotic syndrome as a result of membranous nephropathy caused by renal cell carcinoma. Int J Urol, 11, 235–238.

22.

Lange-Sperandio

, Trautmann

, Eickelberg

, Jayachandran

, Oberle

, Schmidutz

, et al. (2007). Leukocytes induce epithelial to mesenchymal transition after unilateral ureteral obstruction in neonatal mice. Am J Pathol, 171, 861–871.

23.

Lefort

, Mandinova

, Ostano

, Kolev

, Calpini

, Kolfschoten

, et al. (2007). Notch1 is a p53 target gene involved in human keratinocyte tumor suppression through negative regulation of ROCK1/2 and MRCKalpha kinases. Genes Dev, 21, 562–577.

24.

Letavernier

, Bruneval

, Mandet

, Duong Van Huyen

J.P.

, Peraldi

M.N.

, Helal

, et al. (2007). High sirolimus levels may induce focal segmental glomerulosclerosis de novo. Clin J Am Soc Nephrol, 2, 326–333.

25.

, Donath

, Li

, Qin

, Prabhakar

B.S.

, and Li

(2010). miR-30 regulates mitochondrial fission through targeting p53 and the dynamin-related protein-1 pathway. PLoS Genet, 6, e1000795.

26.

Lin

C.L.

, Wang

F.S.

, Hsu

Y.C.

, Chen

C.N.

, Tseng

M.J.

, Saleem

M.A.

, et al. (2010). Modulation of notch-1 signaling alleviates vascular endothelial growth factor-mediated diabetic nephropathy. Diabetes, 59, 1915–1925.

27.

Luo

, Wang

, Chen

, Zhong

, Cai

, Chen

, et al. (2013). Increased serum and urinary microRNAs in children with idiopathic nephrotic syndrome. Clin Chem, 59, 658–666.

28.

Matsui

, Ito

, Kurihara

, Imai

, Ogihara

, and Hori

(2007). Snail, a transcriptional regulator, represses nephrin expression in glomerular epithelial cells of nephrotic rats. Lab Invest, 87, 273–283.

29.

Naito

, and Lowenstein

J.M.

(1981). 5′-Nucleotidase from rat heart. Biochemistry, 20, 5188–5194.

30.

Naraba

, and Iwai

(2005). Assessment of the microRNA system in salt-sensitive hypertension. Hypertens Res, 28, 819–826.

31.

Niemela

, Henttinen

, Yegutkin

G.G.

, Airas

, Kujari

A.M.

, Rajala

, et al. (2004). IFN-alpha induced adenosine production on the endothelium: a mechanism mediated by CD73 (ecto-5′-nucleotidase) up-regulation. J Immunol, 172, 1646–1653.

32.

Niimi

, Pardali

, Vanlandewijck

, Heldin

C.H.

, and Moustakas

(2007). Notch signaling is necessary for epithelial growth arrest by TGF-beta. J Cell Biol, 176, 695–707.

33.

Niranjan

, Bielesz

, Gruenwald

, Ponda

M.P.

, Kopp

J.B.

, Thomas

D.B.

, et al. (2008). The Notch pathway in podocytes plays a role in the development of glomerular disease. Nat Med, 14, 290–298.

34.

Ohnuki

, Umezono

, Abe

, Kobayashi

, Kato

, Miyauchi

, et al. (2012). Expression of transcription factor Snai1 and tubulointerstitial fibrosis in progressive nephropathy. J Nephrol, 25, 233–239.

35.

Remmele

, and Stegner

H.E.

(1987). [Recommendation for uniform definition of an immunoreactive score (IRS) for immunohistochemical estrogen receptor detection (ER-ICA) in breast cancer tissue]. Pathologe, 8, 138–140(Article in German).

36.

Shi

, Yu

, Zhang

, Qi

, Xavier

, Ju

, et al. (2013). Smad2-dependent downregulation of miR-30 is required for TGF-beta-induced apoptosis in podocytes. PLoS One 8, e75572.

37.

Song

, Ye

, Cui

, Lu

, Zhang

, Ding

, et al. (2017). Ecto-5′-nucleotidase (CD73) is a biomarker for clear cell renal carcinoma stem-like cells. Oncotarget, 8, 31977–31992.

38.

Song

Y.R.

, You

S.J.

, Lee

Y.M.

, Chin

H.J.

, Chae

D.W.

, Oh

Y.K.

, et al. (2010). Activation of hypoxia-inducible factor attenuates renal injury in rat remnant kidney. Nephrol Dial Transplant, 25, 77–85.

39.

Sun

, Koo

, White

, Peralta

, Esau

, Dean

N.M.

, et al. (2004). Development of a micro-array to detect human and mouse microRNAs and characterization of expression in human organs. Nucleic acids Res 32, e188.

40.

Thoenes

(1989). [The pathology of glomerulonephritis]. Der Internist, 30, 127–139(Article in German).

41.

Wang

, Zhu

, Zhang

, Zheng

, Ma

, Su

, et al. (2017). MicroRNA-30e-3p inhibits cell invasion and migration in clear cell renal cell carcinoma by targeting Snail1. Oncol Lett, 13, 2053–2058.

42.

Wang

, Li

, and Tang

(2015). MiR-30a upregulates BCL2A1, IER3 and cyclin D2 expression by targeting FOXL2. Oncol Lett, 9, 967–971.

43.

Waters

A.M.

, Wu

M.Y.

, Huang

Y.W.

, Liu

G.Y.

, Holmyard

, Onay

, et al. (2012). Notch promotes dynamin-dependent endocytosis of nephrin. J Am Soc Nephrol, 23, 27–35.

44.

Waters

A.M.

, Wu

M.Y.

, Onay

, Scutaru

, Liu

, Lobe

C.G.

, et al. (2008). Ectopic notch activation in developing podocytes causes glomerulosclerosis. J Am Soc Nephrol, 19, 1139–1157.

45.

Westerhoff

, Tretiakova

, Hart

, Gwin

, Liu

, Zhou

, et al. (2014). The expression of FOXL2 in pancreatic, hepatobiliary, and renal tumors with ovarian-type stroma. Hum Pathol, 45, 1010–1014.

46.

Wienholds

, Kloosterman

W.P.

, Miska

, Alvarez-Saavedra

, Berezikov

, de Bruijn

, et al. (2005). MicroRNA expression in zebrafish embryonic development. Science, 309, 310–311.

47.

Y.Q.

, Wang

, Xu

H.F.

, Jin

X.M.

, and Zhou

H.Z.

(2011). Frequency of primary glomerular disease in northeastern China. Braz J Med Biol Res, 44, 810–813.

48.

Xie

, Qin

, Luo

, Huang

, He

, Yang

, et al. (2017). MicroRNA-30a regulates cell proliferation and tumor growth of colorectal cancer by targeting CD73. BMC Cancer, 17, 305.

49.

Yang

, Guo

, Blattner

S.M.

, Mundel

, Kretzler

, and Wu

(2005). Formation and phosphorylation of the PINCH-1-integrin linked kinase-alpha-parvin complex are important for regulation of renal glomerular podocyte adhesion, architecture, and survival. J Am Soc Nephrol, 16, 1966–1976.

50.

Yuan

C.T.

, Li

X.X.

, Cheng

Q.J.

, Wang

Y.H.

, Wang

J.H.

, and Liu

C.L.

(2015). MiR-30a regulates the atrial fibrillation-induced myocardial fibrosis by targeting snail 1. Int J Clin Exp Pathol, 8, 15527–15536.

51.

Zhang

, Wei

, Li

, Zhou

, and Zhang

(2014a). Urine-derived stem cells: a novel and versatile progenitor source for cell-based therapy and regenerative medicine. Genes Dis, 1, 8–17.

52.

Zhang

, Liu

, Zhang

, Li

, Liu

, et al. (2017). miR-30a as potential therapeutics by targeting TET1 through regulation of Drp-1 promoter hydroxymethylation in idiopathic pulmonary fibrosis. Int J Mol Sci, 18, pii:E633.

53.

Zhang

, Zhang

, Chen

, Li

, Tu

, Liu

, et al. (2014b). Evaluation of microRNAs miR-196a, miR-30a-5P, and miR-490 as biomarkers of disease activity among patients with FSGS. Clin J Am Soc Nephrol, 9, 1545–1552.

54.

Zhang

, McNeill

, Tian

, Soker

, Andersson

K.E.

, Yoo

J.J.

, et al. (2008). Urine derived cells are a potential source for urological tissue reconstruction. J Urol, 180, 2226–2233.

55.

Zhou

, Tokunaga

, Maeda

, and Arai

(2001). [Distribution of 5′-nucleotidase activity in greater omentum of rats]. Kaibogaku Zasshi, 76:381–388 (Article in Japanese).

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