Background: Systemic lupus erythematous (SLE) is an autoimmune disease characterized by the production of autoantibodies directed against various autoantigens. But the expression profiles and functions of circular RNAs (circRNAs) in SLE are still scarce. Objectives: To explore the roles of circRNA in SLE and its potential diagnostic potential in SLE. Methods: SLE patients and healthy control subjects were recruited. CD4+ T cells were isolated, circRNA microarray analysis were used to screen for circRNA candidate in CD4+ T cells. Expression of DNMT1, CD11a and CD70, and methylation level of CD11a and CD70 were detected after transfecting hsa_circ_0012919-targetted siRNA. The network analysis of hsa_circ_0012919 was used by bioinformatics. Luciferase reporter assay and fluorescence in situ hybridization (FISH) assay were used for screening for which miRNAs could bind with hsa_circ_0012919. Results: Twelve circRNAs were up-regulated and two circRNAs were down-regulated in SLE patients group after circRNA microarray analysis. Hsa_circ_0012919 was further confirmed to be significantly different between healthy control and SLE patients (P<0.05) and associated with SLE characters (P<0.05). Down-regulation of hsa_circ_0012919 (i) increased the expression of DNMT1 and reduced the expression of CD70, CD11a, (ii) reversed the DNA hypomethylation of CD11a and CD70 in CD4+ T cells of SLE, but it could be reversed by down-regulation of DNMT1. Hsa_circ_0012919 regulated KLF13 and RANTES by miR-125a. Conclusion: Hsa_circ_0012919 could be regarded as a biomarker for SLE and hsa_circ_0012919 was the competitive endogenous RNA (ceRNA) for miR-125a-3p.

Introduction

Systemic lupus erythematous (SLE), characterized by the production of autoantibodies directed against various autoantigens, is a complex autoimmune disease and have many typical clinical parameters, which affects primarily women of reproductive age [1,2]. Its etiology remains unclear despite large numbers of research probing into its pathogenesis, including environmental, genetic, and hormonal factors, such as UV light (UVB), vitamin D deficiency, viruses, DNA hypomethylation, and abnormal expression of miRNAs [3,4].

MiRNAs and circular RNAs (circRNAs) are both noncoding RNAs, but circRNAs show various distinctions [5]. The functions of miRNAs have already been extensively investigated in many aspects of SLE. Interestingly, circRNAs which form covalently closed RNA circles show higher degree of stability than miRNAs, which means circRNAs could be regarded as much better biomarkers than miRNAs [6–8]. Besides, some circRNAs act as natural miRNA sponges to inhibit related activities of miRNAs [9]. Growing number of studies found out that circRNAs play an important role in the occurrence and development of many diseases, especially cancers [10–13]. However, the expression profiles and functions of circRNAs in SLE are still scarce.

Accumulating evidence has implicated epigenetic factors in the pathogenesis of SLE, and our previous studies have demonstrated SLE-related genes, such as DNMT1, CD70, and CD11a, were associated with the DNA hypomethylation in CD4+ T cells of SLE patients [14,15]. But the exact mechanisms of regulating these genes and DNA hypomethylation in SLE remains unclear. To the best of our knowledge, limited research reported whether circRNAs participated in the pathogenesis of SLE, and the relations between circRNAs and DNA methylation levels in SLE. Therefore, for the first time, we compared the expression profile of circRNAs in the CD4+ T cells of SLE patients and matched control subjects by microarray analysis, then confirmed our results in large samples and explored the diagnostic potential of circRNAs, we further investigated whether circRNA was associated with the expression of SLE-related genes (DNMT1, CD70, and CD11a) and involved in regulating methylation status of CD70 and CD11a. Eventually, we detected whether circRNA could act as the sponge for miRNA in SLE.

Materials and methods

Subjects

Twenty-eight diagnosed SLE patients were recruited from the Department of Dermatology of Shanghai General Hospital and Ruijin Hospital (including newly diagnosed SLE patients, and patients suffering from a long period of time). All the patients were diagnosed as in accordance with the 2012 Systemic Lupus International Collaborating Clinic (SLICC) revised criteria for classification of SLE, and disease activity was assessed by SLE Disease Activity Index (SLEDAI) score. Active disease (scores > 4) or inactive disease (scores ≤ 4) of patients were classified by SLEDAI results. All the lab tests of patients were conducted before taking any medication. Eighteen healthy control subjects which were age- and sex-matched were recruited from the medical staff at the Shanghai General Hospital. Each subject signed an informed consent before participating in the present study. The present study was approved by the Human Ethics Committee of Shanghai General Hospital.

All the included subjects were females. For circRNA microarray analysis, 3 patients and 3 healthy controls were selected at random and 40 other samples (25 patients and 15 healthy controls) were prepared for reverse-transcription PCR (RT-PCR) verification experiments.

Isolation of CD4+ T cells

A total of 10 ml of venous peripheral blood was obtained from each subject and stored in EDTA, and peripheral blood mononuclear cells were separated from blood samples by Ficoll–Paque density centrifugation. CD4+ T cells were isolated using magnetic beads (Miltenyi Biotec; the purity was generally 95% at least) and cultured in human T-cell culture medium (Amaxa) containing 15% FBS and 100 μg/ml penicillin G and streptomycin.

CircRNA microarray analysis

The RNAs of the CD4+ T of three control subjects and three SLE patients were extracted for microarray analysis. The quality and quantity of the RNA were determined by a NanoDrop instrument (Thermo Scientific, Waltham, MA, U.S.A.) and the integrity of the RNA was evaluated by gel electrophoresis. The extracted RNAs were digested, dephosphorylated, denatured, amplified, and labeled with Cy3-dCTP according to the manufacturer’s specifications (Shanghai Personal Biotechnology Cp. Ltd, China). The purified RNAs were hybridized to a microarray (Agilent human circRNA Array V2.0) containing 178340 human circRNA probes. The microarray data of the circRNAs were then analyzed using GeneSpring software V13.0 (Agilent Technologies, Santa Clara, CA, U.S.A.). The thresholds were as follows: fold change: > 2 or < −2; P-values less than or equal to 0.05 were considered significant.

RT-PCR verification

cDNA was synthesized through reverse transcription by GoScript RT System (Promega, U.S.A.). The RNA primer mixture was incubated at 65°C for 10 min, followed by snap-freezing in an ice bath for 2 min. Samples were then incubated at 42°C for 45 min with 4 μl of 5× first-strand buffer, 2 μl of 0.1 mol dNTP and 1 μl RNasin (Takara, China) and distilled water to a total volume of 19 μl. The reverse transcriptase was inactivated at 70°C for 10 min and then chilled on ice. The RT-PCR reaction mixture contained 2.5 μl of qPCR mix, 0.15 μl of gene-specific forward and reverse primers, 1 μl of cDNA and 1.2 μl of distilled water. The primers used in the present study were summarized in Table 1. The amplification protocol included an initial denaturation step at 95°C for 30 s, followed by 40 successive cycles of 95°C for 5 s and 60°C for 20 s. The relative expression levels of circRNAs were determined via RT-PCR. The data were analyzed by Δ cycle threshold (Ct) method.

Table 1
Primers’ sequences for RT-PCR
GeneSequence (5′–3′)
hsa_circ_0012919 F: CAAAGCTTCCGTAGTCGCCTGGAG 
R: CCGGATTGTAACTAGACCAAAGGC 
hsa_circ_0006239 F: CCAATTGTCTCCCGAACTATCGTA 
R: GTGCCATTGTAACGACTAACGCT 
hsa_circ_0002227 F: CCAATTGTCTCCCGAACTATCGTA 
R: GTGCCATTGTAACGACTAACGCT 
DNMT1 F: ACCGCTTCTACTTCCTCGAGGCCTA 
R: GTTGCAGTCCTCTGTGAACACTGTGG 
CD11a F: AAATGGAAGGACCCTGATGCTC 
R: TGTAGCGGATGTGTCTTTGGC 
CD70 F: CAAGTGCAGGTGCCAGAACA 
R: GCCAACATGGTGAAACCCC 
miR-125a F: GCCTCCCTGAGACCCTTTA 
R: GTGTCGTGGAGTCGGCA 
KLF13 F: CCGCAGAGGAAGCACAA 
R: CTTCTTCTCGCCCGTGT 
RANTES F: AGTCGTCTTTGTCACCCGAAA 
R: AGCTCATCTCCAAAGAGTTGATGTAC 
GeneSequence (5′–3′)
hsa_circ_0012919 F: CAAAGCTTCCGTAGTCGCCTGGAG 
R: CCGGATTGTAACTAGACCAAAGGC 
hsa_circ_0006239 F: CCAATTGTCTCCCGAACTATCGTA 
R: GTGCCATTGTAACGACTAACGCT 
hsa_circ_0002227 F: CCAATTGTCTCCCGAACTATCGTA 
R: GTGCCATTGTAACGACTAACGCT 
DNMT1 F: ACCGCTTCTACTTCCTCGAGGCCTA 
R: GTTGCAGTCCTCTGTGAACACTGTGG 
CD11a F: AAATGGAAGGACCCTGATGCTC 
R: TGTAGCGGATGTGTCTTTGGC 
CD70 F: CAAGTGCAGGTGCCAGAACA 
R: GCCAACATGGTGAAACCCC 
miR-125a F: GCCTCCCTGAGACCCTTTA 
R: GTGTCGTGGAGTCGGCA 
KLF13 F: CCGCAGAGGAAGCACAA 
R: CTTCTTCTCGCCCGTGT 
RANTES F: AGTCGTCTTTGTCACCCGAAA 
R: AGCTCATCTCCAAAGAGTTGATGTAC 

Abbreviations: F, forward; R, reverse.

Transfection with hsa_circ_0049224 and DNMT1-specific small interference RNA

Hsa_circ_0012919-targetted, DNMT1-targetted siRNA, and siRNA-NC were purchased from Ambion (Austin, TX, U.S.A.). CD4+ T cells were cultured in 24-well plates and were incubated with mix from HiPerFect Transfection kit (Qiagen, Courtaboeuf, France) containing 20 nM siRNA and 3.0 ml of HiPerFect reagent in 0.5 ml of culture medium. After an incubation period of 48 h, siRNA-NC and siRNA-transfected CD4+ T cells were treated as indicated. SiRNA transfection showed no effect on cell viability under microscopic examination (data not shown).

Western blotting analysis

Proteins of CD4+ T cells were collected from each subject and protein concentration was measured by using Bicinchoninic Acid Protein Assay kit (Beyotime Biotechnology, China). Equal amounts of protein (20 mg) were dissolved in NuPage LDS Sample Buffer (Invitrogen, Carlsbad, CA, U.S.A.) and 10% NuPage Sample Reducing Agent (Invitrogen, Carlsbad, CA, U.S.A.). Lysates were boiled at 70°C for 10 min and loaded to run on 4–12% NuPage Bis-Tris Gels (Invitrogen, Carlsbad, CA, U.S.A.) at 200 V for 40 min. The proteins were transferred on to PVDF membranes (Invitrogen, Carlsbad, CA, U.S.A.) and blocked in 2% BSA in 0.1% Tween-20 (Sigma–Aldrich) and TBS. Membranes were probed with rabbit monoclonal anti-CD70, anti-CD11a, anti-DNMT1, anti-RNATES, and KLF13 (Abcam, Cambridge, MA, U.S.A.) and anti-glyceraldehyde-3-phosphate dehydrogenase (GAPDH) rabbit IgG antibody (FL-335, Santa Cruz Biotechnology, CA, U.S.A.) overnight at 4°C. Anti-rabbit or anti-mouse horseradish peroxidase–conjugated IgG antibody (Santa Cruz Biotechnology, China) which was second antibody was used. Protein bands were detected using the Western Breeze kit (Invitrogen, Carlsbad, CA, U.S.A.). Data were analyzed using Image Lab software (Bio-Rad).

DNA methylation assay

Bisulphite modification and sequencing method was used to detect the DNA methylation level of CD11a and CD70 genes. Genomic DNA was extracted from CD4+ T cells of patients by DNA extraction kit (Boao Biotech, China). Then total DNA was modified by bisulphite using EpiTechR kit (Qiagen, U.S.A.) according to the instructions. The target DNA fragment was then amplified by nested PCR using primers as shown in Table 1. Nested PCR products were purified by Gel Extraction Kit (Qiagen, U.S.A.), ligated with pGEMA_T Easy Vector, and were transfected into DH5α competent cells. After PCR identification, positive recombinant vectors were sequenced.

Luciferase reporter assay

CD4+ T cells transfected with hsa_circ_0012919 or hsa_circ_0012919-mutant were seeded in 96-well and co-transfected with the reporter vector and 50 nm miR-NC, miR-125a-3p, miR-6829-3p, and miR-1237-5p mimic by Lipofectamine 3000 (Invitrogen, Boston, MA) into cells. These miRNA mimics were obtained from Ribobio Co., Ltd. Luciferase activity assay was conducted using Dual Luciferase Assay Systemic (Promega, Madison, WI, U.S.A.).

Fluorescence in situ hybridization

The hybridization was performed overnight with hsa_circ_0012919 and miR-125a probes. The images were obtained with a confocal microscope (Olympus).

Data analysis

All statistical analyses were performed with a statistical software package (SAS version 9.0; SAS Software, Cary, U.S.A.). All the results are expressed as the mean ± S.D. Data were analyzed by ANOVA followed by Student’s unpaired t test for multiple comparisons. Spearman’s rank test was used for correlation studies. P-values less than 0.05 were considered significant.

Result

CircRNA microarray analysis

The present study included 18 healthy subjects and 28 SLE patients. Main clinical and lab parameters of these subjects were displayed in Table 2. Microarray analysis of the expression profiles of circRNAs in CD4+ T cells were performed by using Agilent human circRNA Array. The results showed 12 circRNAs were up-regulated and 2 circRNAs were down-regulated in the SLE patients group (Table 3). The potential candidate biomarkers were selected from the three most up-regulated circRNAs, including hsa_circ_0012919, hsa_circ_0006239, and hsa_circ_0002227 in the present study.

Table 2
Main clinical and lab parameters of these subjects
ParametersSLEHealthy control
n 25 15 
Age 31.4 ± 1.25 32.5 ± 1.10 
SLEDAI 6.5 ± 1.5 NA 
Disease duration (month) 17.6 ± 4.3 NA 
Skin involvement, P/N (n9/16 NA 
Alopecia, P/N (n7/18 NA 
Arthritis, P/N (n12/13 NA 
Lupus nephritis, P/N (n15/10 NA 
Leukopenia, P/N (n20/5 NA 
Anti-ANA, P/N (n24/1 NA 
Anti-dsDNA, P/N (n21/4 NA 
Anti-Sm, P/N (n18/7 NA 
C3 or C4 deficiency, P/N (n19/6 NA 
Medication 
 None NA 
 Prednisone ≤ 30 mg/day 11 NA 
 Prednisone > 30 mg/day NA 
ParametersSLEHealthy control
n 25 15 
Age 31.4 ± 1.25 32.5 ± 1.10 
SLEDAI 6.5 ± 1.5 NA 
Disease duration (month) 17.6 ± 4.3 NA 
Skin involvement, P/N (n9/16 NA 
Alopecia, P/N (n7/18 NA 
Arthritis, P/N (n12/13 NA 
Lupus nephritis, P/N (n15/10 NA 
Leukopenia, P/N (n20/5 NA 
Anti-ANA, P/N (n24/1 NA 
Anti-dsDNA, P/N (n21/4 NA 
Anti-Sm, P/N (n18/7 NA 
C3 or C4 deficiency, P/N (n19/6 NA 
Medication 
 None NA 
 Prednisone ≤ 30 mg/day 11 NA 
 Prednisone > 30 mg/day NA 

Abbreviation: P/N, positive/negative. NA, not applicable.

Table 3
Dysregulated circRNAs analyzed by microarray
circRNAFold changeP-valueRegulation
Hsa_circ_0012919 26.357 0.011 Up 
Hsa_circ_0006239 15.464 0.018 Up 
Hsa_circ_0002227 14.674 0.030 Up 
Hsa_circ_0009289 6.676 0.025 Up 
Hsa_circ_0010957 6.562 0.011 Up 
Hsa_circ_0011524 6.511 0.003 Up 
Hsa_circ_0006452 6.130 0.048 Up 
Hsa_circ_0003048 6.078 0.014 Up 
Hsa_circ_0002205 5.318 0.002 Up 
Hsa_circ_0006357 4.690 0.000 Up 
Hsa_circ_0002794 4.107 0.013 Up 
Hsa_circ_0006510 3.069 0.022 Up 
Hsa_circ_0011018 0.420 0.030 Down 
Hsa_circ_0006895 0.013 0.015 Down 
circRNAFold changeP-valueRegulation
Hsa_circ_0012919 26.357 0.011 Up 
Hsa_circ_0006239 15.464 0.018 Up 
Hsa_circ_0002227 14.674 0.030 Up 
Hsa_circ_0009289 6.676 0.025 Up 
Hsa_circ_0010957 6.562 0.011 Up 
Hsa_circ_0011524 6.511 0.003 Up 
Hsa_circ_0006452 6.130 0.048 Up 
Hsa_circ_0003048 6.078 0.014 Up 
Hsa_circ_0002205 5.318 0.002 Up 
Hsa_circ_0006357 4.690 0.000 Up 
Hsa_circ_0002794 4.107 0.013 Up 
Hsa_circ_0006510 3.069 0.022 Up 
Hsa_circ_0011018 0.420 0.030 Down 
Hsa_circ_0006895 0.013 0.015 Down 

The expressions of selected up-regulated circRNAs verified by RT-PCR

In order to validate the three selected circRNAs, RT-PCR was conducted in the rest SLE patients (n=25) and healthy controls (n=15). The clinical and lab parameters of these subjects were displayed in Table 2. Figure 1A–C shows that the expression level of hsa_circ_0012919 (0.96 ± 0.04 compared with 1.14 ± 0.04; P=0.01), hsa_circ_0006239 (0.87 ± 0.05 compared with 1.13±0.06; P=0.0037), hsa_circ_0002227 (0.86 ± 0.05 compared with 1.05 ± 0.06; P=0.04) between healthy controls and SLE patients were all significantly different (P<0.05) (Figure 1A–C).

The expressions of selected up-regulated circRNAs in healthy controls and SLE patients

Figure 1
The expressions of selected up-regulated circRNAs in healthy controls and SLE patients

(A) The relative expression of hsa_circ_0012919 in healthy controls was lower than that in SLE patients; (B) the relative expression of hsa_circ_0006239 in healthy controls was lower than that in SLE patients; (C) the relative expression of hsa_circ_0002227 in healthy controls was lower than that in SLE patients; (D) the relative expression of hsa_circ_0012919 in active SLE patients was higher than that in inactive patients; (E) the relative expression of hsa_circ_0006239 in active SLE patients was higher than that in inactive patients; (F) there was no significant difference between inactive and active SLE patients in terms of hsa_circ_0002227 expression (*P<0.05, NS means nonsense).

Figure 1
The expressions of selected up-regulated circRNAs in healthy controls and SLE patients

(A) The relative expression of hsa_circ_0012919 in healthy controls was lower than that in SLE patients; (B) the relative expression of hsa_circ_0006239 in healthy controls was lower than that in SLE patients; (C) the relative expression of hsa_circ_0002227 in healthy controls was lower than that in SLE patients; (D) the relative expression of hsa_circ_0012919 in active SLE patients was higher than that in inactive patients; (E) the relative expression of hsa_circ_0006239 in active SLE patients was higher than that in inactive patients; (F) there was no significant difference between inactive and active SLE patients in terms of hsa_circ_0002227 expression (*P<0.05, NS means nonsense).

Diagnostic potential of hsa_circ_0012919 in SLE

In previous experiment, we demonstrated that the expression of these three circRNAs were all significantly different between healthy controls and SLE patients, thus we examined the potential diagnostic potential of these three circRNAs. We compared the expression of three circRNAs amongst healthy controls, inactive, and active SLE patients, and found out the hsa_circ_0012919 (1.23 ± 0.04 compared with 1.01 ± 0.06, P=0.0055; 1.23 ± 0.04 compared with 0.96 ± 0.04, P<0.0001) and hsa_circ_0006239 (1.23 ± 0.06 compared with 0.96±0.04, p<0.0001; 1.23 ± 0.06 compared with 0.87 ± 0.05, P<0.0001) in active SLE patients was higher than inactive SLE patients and healthy controls, while there was no significant difference between healthy controls and inactive SLE patients (P=0.49) (P=0.21) (Figure 1D,E). And there was no significant difference between inactive and active SLE patients in terms of hsa_circ_0002227 expression (1.05 ± 0.11 compared with 1.09 ± 0.08, P=0.72) (Figure 1F).

In order to further assess the potential diagnostic potential of hsa_circ_0012919, expression of hsa_circ_0012919 in SLE patients with or without skin involvement, alopecia, arthritis, lupus nephritis, leukopenia, anti-dsDNA(+), anti-Sm(+), C3 or C4 deficiency, and prednisone ≤ 30 mg/day were compared. The results in Figure 2 show hsa_circ_0012919 expression was significant higher in patients with arthritis, lupus nephritis, anti-dsDNA(+), anti-Sm(+), C3 or C4 deficiency than patients without those symptoms (all P<0.05). Additionally, hsa_circ_0012919 expression had a negative correlation with the levels of C3 and C4 (both P<0.05), and hsa_circ_0012919 expression of patients receiving no medication was obviously higher than those with prednisone ≤ 30 mg/day and > 30 mg/day (P<0.05). These all indicated that hsa_circ_0012919 in SLE could be regarded as a potential biomarker for SLE.

Correlation between expression of hsa_circ_0012919 and clinical and lab parameters of these subjects with SLE (*P<0.05, NS means nonsense)

Figure 2
Correlation between expression of hsa_circ_0012919 and clinical and lab parameters of these subjects with SLE (*P<0.05, NS means nonsense)

(A) A significant positive correlation was seen between the expression of hsa_circ_0012919 and SLEDAI. Expression of hsa_circ_0012919 in SLE patients with or without skin involvement (B), alopecia (C), arthritis (D), lupus nephritis (E), leukopenia (F), anti-dsDNA(+) (G), anti-Sm(+) (H), C3 or C4 deficiency (I) were compared. (J) Expression of hsa_circ_0012919 among SLE patients receiving no medication, with prednisone ≤ 30 mg/day and > 30 mg/day was compared.

Figure 2
Correlation between expression of hsa_circ_0012919 and clinical and lab parameters of these subjects with SLE (*P<0.05, NS means nonsense)

(A) A significant positive correlation was seen between the expression of hsa_circ_0012919 and SLEDAI. Expression of hsa_circ_0012919 in SLE patients with or without skin involvement (B), alopecia (C), arthritis (D), lupus nephritis (E), leukopenia (F), anti-dsDNA(+) (G), anti-Sm(+) (H), C3 or C4 deficiency (I) were compared. (J) Expression of hsa_circ_0012919 among SLE patients receiving no medication, with prednisone ≤ 30 mg/day and > 30 mg/day was compared.

Effect of hsa_circ_0012919 down-regulation on expression of DNMT1, CD11a, and CD70

To analyze the effects of hsa_circ_0012919 on DNMT1, CD11a, and CD70 expression in CD4+ T cells of SLE patients, the relations between the expression of hsa_circ_0012919 and DNMT1, CD11a and CD70 were compared. A strong inverse correlation was seen between the expression of hsa_circ_0012919 and DNMT1 (r = −0.66, P=0.0004), and positive correlations were seen between the expression of hsa_circ_0012919 and CD11a (r = 0.51, P=0.0092), CD70 (r = 0.64, P=0.0005) (Figure 3). Then siRNAs which were specific for hsa_circ_0012919 and siRNA-NC were transfected into CD4+ T cells of SLE patients, and the result showed that transfection efficiency was 51% (Figure 4A). As a consequence of the inhibition, the mRNA and protein expression of DNMT1 significantly increased in inactive and active SLE patients compared with siRNA-NC group (P<0.05, Figure 4B,C,H), in contrast, the mRNA and protein expression of CD11a and CD70 decreased significantly compared with siRNA-NC group (P<0.05, Figure 4D–H). As shown in Figure 4H, the protein expression of DNMT1, relatively lowly expressed in SLE, was almost reversed by hsa_circ_0012919-targetted siRNA, but the protein expression of CD11a, CD70 was almost knocked down by hsa_circ_0012919-targetted siRNA shown by Western blotting. To further determine the relation between hsa_circ_0012919 and DNMT1, it was tested by siRNA toward hsa_circ_0012919 in a dose-dependent manner. CD4+ T cells from SLE patients were regarded as controls, then were treated with siRNA (20, 40, 60, and 80 nM) for 24 h, and DNMT1 expression increased in a dose-dependent manner as depicted in Figure 4I. Collectively, these data strongly suggested that hsa_circ_0012919 played a crucial role in expression of DNMT1, CD11a, and CD70 in SLE CD4+ T cells.

hsa_cir-0012919 expression was correlated with SLE-related genes

Figure 3
hsa_cir-0012919 expression was correlated with SLE-related genes

Correlations between hsa_circ_0012919 and DNMT1 (A), CD11a (B), and CD70 (C).

Figure 3
hsa_cir-0012919 expression was correlated with SLE-related genes

Correlations between hsa_circ_0012919 and DNMT1 (A), CD11a (B), and CD70 (C).

Effects of hsa_circ_0012919 on expression of DNMT1, CD11a and CD70

Figure 4
Effects of hsa_circ_0012919 on expression of DNMT1, CD11a and CD70

(A) Relative expression of hsa_circ_0012919 was lower after transfecting hsa_circ_0012919-targetted siRNA; (B,C) the mRNA and protein expression of DNMT1 increased significantly after transfecting hsa_circ_0012919-targetted siRNA (inactive, n=11; active, n=14); (D,E) the mRNA and protein expression of CD11a decreased significantly after transfecting hsa_circ_0012919-targetted siRNA (inactive, n=11; active, n=14); (F,G) the mRNA and protein expression of CD70 decreased significantly after transfecting hsa_circ_0012919-targetted siRNA (inactive, n=11; active, n=14); (H) expression of DNMT1, CD11a, and CD70 after transfecting hsa_circ_0012919-targetted siRNA was shown by Western blotting. ‘Active’ means active SLE patients were transfected siRNA-NC, ‘active + siRNA’ means active SLE patients were transfected hsa_circ_0012919-targetted siRNA, ‘inactive’ means inactive SLE patients were transfected siRNA-NC, ‘inactive + siRNA’ means inactive SLE patients were transfected hsa_circ_0012919-targetted siRNA; (I) the expression of DNMT1 had an increase in a dose-dependent manner after transfecting hsa_circ_0012919-targetted siRNA (n=25) (*P<0.05, NS means nonsense).

Figure 4
Effects of hsa_circ_0012919 on expression of DNMT1, CD11a and CD70

(A) Relative expression of hsa_circ_0012919 was lower after transfecting hsa_circ_0012919-targetted siRNA; (B,C) the mRNA and protein expression of DNMT1 increased significantly after transfecting hsa_circ_0012919-targetted siRNA (inactive, n=11; active, n=14); (D,E) the mRNA and protein expression of CD11a decreased significantly after transfecting hsa_circ_0012919-targetted siRNA (inactive, n=11; active, n=14); (F,G) the mRNA and protein expression of CD70 decreased significantly after transfecting hsa_circ_0012919-targetted siRNA (inactive, n=11; active, n=14); (H) expression of DNMT1, CD11a, and CD70 after transfecting hsa_circ_0012919-targetted siRNA was shown by Western blotting. ‘Active’ means active SLE patients were transfected siRNA-NC, ‘active + siRNA’ means active SLE patients were transfected hsa_circ_0012919-targetted siRNA, ‘inactive’ means inactive SLE patients were transfected siRNA-NC, ‘inactive + siRNA’ means inactive SLE patients were transfected hsa_circ_0012919-targetted siRNA; (I) the expression of DNMT1 had an increase in a dose-dependent manner after transfecting hsa_circ_0012919-targetted siRNA (n=25) (*P<0.05, NS means nonsense).

Effect of hsa_circ_0012919 down-regulation and DNMT1 on DNA methylation of CD11a and CD70

To determine whether hsa_circ_0012919 was involved in DNA methylation in patients with SLE, correlations between DNA methylation levels of two genes (CD11a and CD70) and the hsa_circ_0012919 expression were analyzed. And strong inverse correlations were seen between the expression of hsa_circ_0012919 and DNA methylation levels of CD11a (r = −0.65, P=0.0004) and CD70 (r = −0.70, P<0.0001) (Figure 5A,B). Meanwhile, DNA methylation levels of these two genes both had an obvious increase (P<0.05) after the hsa_circ_0012919-targetted siRNA was transfected into CD4+ T cells of inactive and active SLE patients compared with siRNA-NC group (Figure 5D,E). Interestingly, this effect was reversed by DNMT1-targetted siRNA, the DNA methylation levels of CD11a and CD70 decreased significantly after transfecting DNMT1-targetted siRNA. As a consequence of the inhibition, the mRNA and protein expression of DNMT1 significantly decreased, the result shows transfection efficiency of DNMT1-targetted siRNA was 56% (Figure 5C). These all indicated that the down-regulation of hsa_circ_0012919 reversed the DNA hypomethylation of CD11a and CD70 in CD4+ T cells of SLE, but this effect could be reversed by DNMT1-targetted siRNA.

Hsa_circ_0012919-targetted siRNA could induce DNA methylation of CD11a and CD70

Figure 5
Hsa_circ_0012919-targetted siRNA could induce DNA methylation of CD11a and CD70

Correlations between hsa_circ_0012919 and methylation level of CD11a (A) and CD70 (B). Methylation level of CD11a (D) and CD70 (E) increased significantly after transfecting hsa_circ_0012919-targetted siRNA in SLE patients, which could be reversed by DNMT1-targetted siRNA (active, n=14; inactive, n=11). (C) PCR and Western blot show the decreased expression of DNMT1 protein in CD4+ T cells after post-transfection of DNMT1 siRNA. Transfection efficiency was 52%. ‘Active’ means active SLE patients were transfected siRNA-NC, ‘active+siRNA1’ means active SLE patients were transfected hsa_circ_0012919-targetted siRNA, ‘active + siRNA1 + siRNA2’ means active SLE patients were transfected hsa_circ_0012919-targetted siRNA and DNMT1-targetted siRNA, ‘inactive’ means inactive SLE patients were transfected siRNA-NC, ‘inactive + siRNA’ means inactive SLE patients were transfected hsa_circ_0012919-targetted siRNA, ‘inactive + siRNA1 + siRNA2’ means inactive SLE patients were transfected hsa_circ_0012919-targetted siRNA and DNMT1-targetted siRNA (*P<0.05).

Figure 5
Hsa_circ_0012919-targetted siRNA could induce DNA methylation of CD11a and CD70

Correlations between hsa_circ_0012919 and methylation level of CD11a (A) and CD70 (B). Methylation level of CD11a (D) and CD70 (E) increased significantly after transfecting hsa_circ_0012919-targetted siRNA in SLE patients, which could be reversed by DNMT1-targetted siRNA (active, n=14; inactive, n=11). (C) PCR and Western blot show the decreased expression of DNMT1 protein in CD4+ T cells after post-transfection of DNMT1 siRNA. Transfection efficiency was 52%. ‘Active’ means active SLE patients were transfected siRNA-NC, ‘active+siRNA1’ means active SLE patients were transfected hsa_circ_0012919-targetted siRNA, ‘active + siRNA1 + siRNA2’ means active SLE patients were transfected hsa_circ_0012919-targetted siRNA and DNMT1-targetted siRNA, ‘inactive’ means inactive SLE patients were transfected siRNA-NC, ‘inactive + siRNA’ means inactive SLE patients were transfected hsa_circ_0012919-targetted siRNA, ‘inactive + siRNA1 + siRNA2’ means inactive SLE patients were transfected hsa_circ_0012919-targetted siRNA and DNMT1-targetted siRNA (*P<0.05).

Hsa_circ_0012919 regulates KLF13 and RANTES by miR-125a

One of the main roles of circRNAs is binding miRNAs to regulate expression of genes. To explore which miRNAs could have been sequestered by hsa_circ_0012919, the network analysis of hsa_circ_0012919 was used by bioinformatics (Figure 6A). Then we utilized public databases circbases (http://www.circbase.org) and RNA22V2 (https://cm.jefferson.edu/rna22v2/) to screen for targetted miRNAs, and the results show miR-125a-3p, miR-6829-3p, and miR-1237-5p had binding sites with hsa_circ_0012919 (Figure 6B). To identify which miRNAs bind to hsa_circ_0012919, we performed a luciferase screening assay, each miRNA mimic was co-transfected with the luciferase reporters into CD4+ T cells of healthy controls, inactive and active SLE patients. Only miR-125a-3p was found to reduce the luciferase activity by 50% compared with control RNA (Figure 6C), while hsa_circ_0012919 did not affect the expression of miR-125a-3p in CD4+ T cells from inactive and active SLE patients (Figure 6D). The interaction between hsa_circ_0012919 and miR-125a was further demonstrated by fluorescence in situ hybridization (FISH) analysis in lupus CD4+ T cells (Figure 6E). We found hsa_circ_0012919 and miR-125a were colocalized in the cytoplasm, which suggested that hsa_circ_0012919 binds to miR-125a. Furthermore, hsa_circ_0012919 had a negative correlation with the expression of miR-125a-3p in lupus CD4+ T cells (r = 0.61, P=0.0012) (Figure 6F). Some scholars demonstrated miR-125a could regulate RNATES and KLF13 and miR-125a-3p functioned as the active fragment of miR-125a, thus we hypothesized that hsa_circ_0012919 regulated RNATES and KLF13 by sponging miR-125a-3p. First, we found hsa_circ_0012919 had a negative correlation with the expression of RNATES and KLF13 in lupus CD4+ T cells (Figure 6G,H). Then PCR and Western blotting showed miR-125a-3p reduced the expression of RNATES and KLF13, and hsa_circ_0012919 reversed and increased the expression RNATES and KLF13 (Figure 6I). In order to prove a direct relationship between hsa_circ_0012919 and miR-125, dose-dependent manner experiments were conducted. The results show RNATES and KLF13 expression was in a dose-dependent manner influenced by miR-125 and hsa_circ_0012919 (Figure 6J,K).

Hsa_circ_0012919 could regulate KLF13 and RANTES by miR-125a

Figure 6
Hsa_circ_0012919 could regulate KLF13 and RANTES by miR-125a

(A) The network analysis of hsa_circ_0012919 binding with possible miRNAs detected by bioinformatics. (B) miR-125a-3p, miR-6829-3p, and miR-1237-5p had binding sites with hsa_circ_0012919. Luciferase screening assay shows that only miR-125a-3p was found to reduce the luciferase activity by 50% (C) and hsa_circ_0012919 did not affect the expression of miR-125a-3p in CD4+ T cells from inactive and active SLE patients (D). (E) The colocalization of hsa_circ_0012919 and miR-125a in lupus CD4+ T cells by FISH. (F) hsa_circ_0012919 had a negative correlation with the expression of miR-125a-3p Hsa_circ_0012919 had a negative correlation with the expression of RNATES (G) and KLF13 (H). Then mRNA and protein level (I) showed that miR-125a-3p reduced the expression of RNATES and KLF13, and hsa_circ_0012919 reversed and increased the expression of RNATES and KLF13. RNATES and KLF13 expression was in a dose-dependent manner influenced by miR-125 and hsa_circ_0012919 (J,K) (*P<0.05).

Figure 6
Hsa_circ_0012919 could regulate KLF13 and RANTES by miR-125a

(A) The network analysis of hsa_circ_0012919 binding with possible miRNAs detected by bioinformatics. (B) miR-125a-3p, miR-6829-3p, and miR-1237-5p had binding sites with hsa_circ_0012919. Luciferase screening assay shows that only miR-125a-3p was found to reduce the luciferase activity by 50% (C) and hsa_circ_0012919 did not affect the expression of miR-125a-3p in CD4+ T cells from inactive and active SLE patients (D). (E) The colocalization of hsa_circ_0012919 and miR-125a in lupus CD4+ T cells by FISH. (F) hsa_circ_0012919 had a negative correlation with the expression of miR-125a-3p Hsa_circ_0012919 had a negative correlation with the expression of RNATES (G) and KLF13 (H). Then mRNA and protein level (I) showed that miR-125a-3p reduced the expression of RNATES and KLF13, and hsa_circ_0012919 reversed and increased the expression of RNATES and KLF13. RNATES and KLF13 expression was in a dose-dependent manner influenced by miR-125 and hsa_circ_0012919 (J,K) (*P<0.05).

Discussion

SLE is an autoimmune disease with abnormal innate and adaptive immune responses, and the overexpression of CD11a, CD70 in CD4+ T cells in SLE may help to produce large amounts of autoantibodies, which induce the pathogenesis of SLE [16,17]. Recently, researchers have demonstrated circRNAs that may play an important role in various kinds of autoimmunity diseases including diabetes and rheumatoid arthritis [7,18,19]. In the present study, we demonstrated hsa_circ_0012919 expression was higher in CD4+ T cells from SLE patients, explored the potential diagnostic potential of hsa_circ_0012919 in SLE patients and its relationship with genes and methylation level, finally we indicated hsa_circ_0012919 regulated RNATES and KLF13 by sponging miR-125a-3p.

Ever since the discovery of circRNAs, considerable efforts have been devoted into identifying the biological functions of circRNAs and their relevance to various kinds of diseases [6]. Recently, Li et al. [20] used circRNA microarrays to screen differentially expressed circRNA in T cells of SLE patients and healthy controls, and found that hsa_circ_0045272 was down-regulated, and that this was related to apoptosis and interleukin-2 secretion. However, we first demonstrated that the expression of circRNAs in CD4+ T cells of SLE was abnormally compared with healthy controls based on microarray results. In the present study, hsa_circ_0012919 was found to be aberrantly up-regulated in CD4+ T cells of SLE patients, then the association between expression of hsa_circ_0012919 with clinical and lab characteristics of SLE was verified, which indicated hsa_circ_0012919 could be used as a noninvasive biomarker for SLE.

Till now the function of hsa_circ_0012919 in diseases remains unknown. CD11a and CD70 are both important molecules involved in SLE, and they play an important role in expansion, differentiation, and activation of CD4+ T cells [21]. Large numbers of studies suggested hypomethylation level of CD11a and CD70 in SLE, leading CD4+ T cells cell into autoreactivity, which is extremely important for the development of SLE [17,22]. DNMT1 was the foremost contributor in the DNA methylation of mammalian, and the low expression of DNMT1 in lupus CD4+ T cells was crucial for development of SLE [23,24]. To elucidate the role of DNMT1, CD70, and CD11a in the pathogenesis of SLE, the relations between hsa_circ_0012919 and SLE-related genes (DNMT1, CD70, and CD11a) were detected. Our data showed hsa_circ_0012919 had a positive relation with expression of CD70, CD11a and a negative relation with expression of DNMT1. Additionally, hsa_circ_0012919-targetted siRNA could reverse the relative low expression of DNMT1, and reduce the expression of CD70, CD11a, both in CD4+ T cells from inactive and active SLE patients. Then down-regulation of hsa_circ_0012919 was founded to induce DNA methylation of CD11a and CD70, but this effect could be reversed by siRNA to DNMT1. We deduced that hsa_circ_0012919 might be associated with the abnormal DNA methylation in CD4+ T cells of SLE and could be regarded as potential therapeutic target in SLE patients.

Evidence has shown that circRNAs bind with miRNAs to regulate target gene expression, which was the best-studied mechanism of functions of circRNAs presently [25]. According to the previous microarray analysis and circbase, we speculated that miR-125a-3p could interact with hsa_circ_0012919, which was confirmed by luciferase activity assays. Recent reports indicate that miR-125a-3p is also broadly conserved amongst vertebrates and may have cellular functions [26]. And it has been demonstrated that miR-125a, the precursor of miR-125a-3p, negatively regulated RANTES expression by targetting KLF13 in activated T cells [27]. Our data suggested miR-125a-3p could reduce the expression of RANTES and KLF13, hsa_circ_0012919 could inhibit the effect of miR-125a-3p on RANTES and KLF13 in lupus CD4+ T cells. RANTES is a typical CC (alapha) family chemokine, which plays an important role in the pathogenesis of SLE, and another transcription factor KLF13 orchestrates the induction of RANTES in activated T cells [28]. Some scholars have demonstrated that KLF13 was the direct target of miR-125a [27]. Here, we showed that as the sponge of miR-125a-3p, hsa_circ_0012919 regulated RANTES and KLF13, which means miR-125a-3p may be intermediate point and hsa_circ_0012919 functions as a competitive endogenous RNA (ceRNA) for miR-125a-3p.

However, there are still limitations in this experiment. First, the number of participants is small and in our future research we will include more patients to continue to verify the expression of these circRNAs. Secondly, we will probe into expression of more SLE-related genes is correlated circRNA, or whether circRNA affects methylation levels of other genes in further investigation.

Conclusion

This is the first study to investigate the expression profiles of circRNAs in the CD4+ T cells of patients with SLE. These findings provide new insights into the role of hsa_circ_0012919 in SLE, suggesting that hsa_circ_0012919 could be used as a potential biomarker for SLE and the ceRNA for miR-125a-3p.

Clinical perspectives

  • SLE is an autoimmune disease characterized by production of autoantibodies directed against various autoantigens. But the expression profiles and functions of circRNAs in SLE are still scarce.

  • The present study is the first to investigate the expression profiles of circRNAs in the CD4+ T cells of patients with SLE. Hsa_circ_0012919 was confirmed to be significantly different between healthy control and SLE patients and associated with lots of SLE characters. Hsa_circ_0012919-targetted siRNA could reverse the low expression of DNMT1 and reduce the expression of CD70, CD11a. Down-regulation of hsa_circ_0012919 in SLE could reverse the DNA hypomethylation of CD11a and CD70 in CD4+ T cells of SLE. Hsa_circ_0012919 could regulate KLF13 and RANTES by miR-125a.

  • These findings provide new insights into the role of hsa_circ_0012919 in SLE, suggesting that hsa_circ_0012919 could be used as a potential biomarker for SLE and the ceRNA for miR-125a-3p.

Competing interests

The authors declare that there are no competing interests associated with the manuscript.

Funding

This work was supported by the National Natural Science Foundation of China [grant numbers 81573031, 81773310].

Author contribution

C.Z. (Chengzhong Zhang), X.W., and C.Z. (Chao Zhang) designed and performed the experiments. Z.W., Y.C., and W.S. analyzed and interpreted the data. C.Z. (Chengzhong Zhang) wrote the manuscript. All authors read and approved the manuscript.

Abbreviations

     
  • circRNA

    circular RNA

  •  
  • ceRNA

    competitive endogenous RNA

  •  
  • DNMT1

    DNA methyltransferase 1

  •  
  • KLF13

    Krueppel-like factor 13

  •  
  • RANTES

    Regulated upon activation normal T-cell expressed and secreted

  •  
  • RT-PCR

    reverse-transcription PCR

  •  
  • siRNA-NC

    small interfering RNA normal control

  •  
  • SLE

    systemic lupus erythematous

  •  
  • SLEDAI

    SLE disease activity index

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Author notes

*

These authors contributed equally to this work.