Abstract
Objective
High-throughput sequencing was used to screen expressing differences of miRNA, lncRNA, and mRNA in CD19+ B peripheral blood samples of newly diagnosed immune thrombocytopenia (ITP) patients and healthy controls. The study aimed to explore the regulatory role of ceRNA network in the pathogenesis of dysfunctional CD19 + B lymphocytes of ITP patients.
Methods
CD19+ B lymphocytes were isolated from peripheral blood samples of ITP patients and their healthy counterparts. High-throughput sequencing was used to screen for the expression of miRNA, lncRNA, and mRNA of ITP patients and healthy controls, which were analysed by the ceRNA network. Moreover, qPCR was used to verify the differential expression of miRNA, lncRNA, and mRNA in ITP patients and healthy controls. The correlation between differentially expressed miRNA, lncRNA, mRNA, and B lymphocyte subsets was also analysed.
Results
The CD19+ B lymphocytes of 4 newly diagnosed ITP patients and 4 healthy controls were sequenced and analysed. There were 65 differentially expressed lncRNA and 149 mRNA forming a ceRNA network showed that 12 lncRNA and 136 differentially expressed mRNA were closely associated. Similarly, miR-144-3p, miR-374c-3p, and miR-451a were highly expressed in ITP patients, as confirmed by qPCR, which was consistent with the high-throughput sequence results. LOC102724852 and CCL20 were highly expressed in ITP patients, while LOC105378901, LOC112268311, ALAS2, and TBC1D3F were not as compared to healthy controls, which was consistent with the high-throughput sequence results. In addition, the expression of miR-374c-3p, LOC112268311, LOC105378901, and CXCL3 were correlated with the percentage of B lymphocyte subsets.
Conclusions
The ceRNA network of miRNA, lncRNA, and mRNA in peripheral CD19 + B lymphocytes plays an essential role in the pathogenesis of ITP.
1. Introduction
Immune thrombocytopenia (ITP) is a common autoimmune disease caused by decreased platelet formation or increased platelet destruction. The clinical manifestations of this disease range from mild skin and mucocutaneous petechiae to severe visceral or intracranial haemorrhage. Bone marrow pathology typically shows an increased number of megakaryocytes accompanied by megakaryocytes maturation disorder [Citation1]. Plausible aetiologies of ITP include underlying genetic susceptibility, drugs, infections, oxidative stress, and abnormal immune regulation [Citation2]. The role of B lymphocytes in ITP is key and it mainly plays an inhibitory role in ITP. Specifically, B lymphocytes can participate in the humoral and cellular immune responses of ITP patients through the secretion of antibodies and antigen presentation. In particular, abnormal B lymphocytes produce platelet-related antibodies, thereby destroying platelets, which has become the classic pathogenesis of ITP [Citation3,Citation4].
Non-coding RNA include MicroRNA (miRNA), long chain non coding RNA (lncRNA) and circular RNA (circRNA), they do not have the function of coding proteins in the transcriptome. MiRNA is a small non-coding RNA, which can participate in regulation in the nucleus by regulating the expression of downstream mRNA. Some miRNA also play a role in the pathogenesis of autoimmune diseases such as ITP [Citation5–7]. Meanwhile, lncRNA is a non-coding RNA located in the nucleus or cytoplasm with a length of more than 200 nucleotides. It is widely involved in cell growth, development, differentiation, apoptosis and other processes, and the regulation in cells are complex and diverse [Citation8]. A very important function of lncRNA is that it can competitively bind miRNA, thereby inhibiting the function of miRNA and the expression of subsequent downstream target mRNA [Citation9].
MiRNA, lncRNA and mRNA are closely related and interact with each other, and together constitute competitive endogenous RNA (ceRNA) [Citation10]. In the ceRNA network, many miRNA combined with lncRNA, thus inhibit the function of miRNA and regulate the expression of downstream target mRNA of miRNA [Citation11]. Studies have shown that the ceRNA network can regulate gene expression and post-transcriptional modification in many autoimmune diseases. For example, ceRNA can participate in the pathogenesis of systemic lupus erythematosus, and can play a role in synovial tissue of patients with rheumatoid arthritis [Citation12,Citation13]. In terms of ITP, bioinformatic have been used to mine the ceRNA network in T lymphocytes of ITP patients, and it has been initially found that ceRNA network plays key roles in the immunity of ITP patients [Citation14]. But whether the ceRNA network regulates CD19 + B lymphocytes in ITP remains unclear.
In this study, high-throughput sequencing was used to screen differentially expressed miRNA, lncRNA, and mRNA in Peripheral blood collected CD19 + B lymphocytes of newly diagnosed ITP patients and healthy controls in determining the regulatory role of ceRNA network in dysfunctional CD19 + B lymphocytes of ITP patients.
2. Materials and methods
2.1. Materials
Lymphocyte Separation Medium, Human (Solarbio, P8610). Red Blood Cell Lysis Buffer (Solarbio, R1010). CD19 MicroBeads, Human (Miltenyi, 130-055-301). MS Columns (Miltenyi, 130-042-201). AutoMACS Running Buffer (Miltenyi, 130-091-221). Trizol (Invitrogen, 15596026). FastKing RT Kit (With gDNase) (TIANGEN KR116). SYBR Green (TIANGEN FP209). IM B Cells Tube, 25 Tests, RUO (Beckman Coulter, B53318).
2.2. Collection of ITP patients and healthy volunteers
High-throughput sequencing: 4 newly diagnosed ITP patients (nITP) and 4 healthy controls were selected. Among the 4 patients, 1 was male and 3 were female. The average age is 41(18-67) years and the average platelet count is 26 (9–46) × 109/L. qPCR verification: 20 ITP patients were also selected, 10 were nITP, and the other 10 were ITP patients in complete remission (cr-ITP). Furthermore, 10 healthy volunteers were also selected.
Flow cytometry of B lymphocyte subsets: 20 nITP and 20 healthy controls were selected. All nITP were diagnosed according to the diagnostic criteria of ITP (international consensus in 2019) [Citation15]. cr-ITP was defined as a platelet count of (100–300) × 109/L after treatment. Ethics Committee approved this research, and all subjects have signed informed consent.
2.3. Isolation and purification of CD19 + B lymphocytes
Peripheral venous blood (10 mL) was collected from ITP patients and healthy controls, and mononuclear cells were isolated using a lymphocyte separation medium. Mononuclear cells were suspended in 1 mL pre-cooled MACS separating buffer and thoroughly mixed. An 80 mL separation buffer and 20 mL of CD19 microbeads per 107 cells were added, thoroughly mixed, and incubated at 4 °C in the dark for 15 min. 1mL of separation buffer was added and centrifuged at 1500 rpm for 5 min to wash these cells. The supernatant was discarded and the cells were washed again. Cells were resuspended in 500 mL of separation buffer, and CD19 + B lymphocytes were isolated according to the manufacturer’s instructions. The purity of B lymphocytes was determined by flow cytometry.
2.4. Extraction of total RNA
Total RNA from each sample was extracted using TRIzol. RNA concentration and A260/A280 ratio were determined using a spectrophotometer. The concentration, purity, and integrity of RNA for each group were analysed using an Agilent 2100 bioanalyzer.
2.5. High-throughput sequencing and libraries construction of miRNA, lncRNA, and mRNA
High-throughput sequencing and quantitative analysis of RNA libraries were performed using the BGISEQ-500 sequencing system. miRNA, lncRNA, and mRNA were screened at the same time. Differentially expressed RNA was defined as differential multiple ≥2 and corrected p value (Q value) <0.05.
2.6. qPCR was used to verify the expression of three differentially expressed RNA in peripheral blood CD19 + B lymphocytes
Peripheral blood was collected from ITP patients and healthy controls, and mononuclear cells were extracted. Then, CD19 + B lymphocytes were isolated by magnetic beads, and total RNA was extracted by Trizol and then reversely transcribed into cDNA. Bio-Rad CFX fluorescence quantitative PCR instrument was used to carry out the qPCR reaction. 2–ΔΔCT was used to calculate the relative expression of each RNA.
2.7. Flow cytometry and correlation analysis of B lymphocyte subsets in ITP patients and healthy controls
Peripheral blood B lymphocyte subsets in 20 ITP patients and 20 healthy controls were collected and detected by flow cytometry. 5 mL fresh peripheral blood from ITP patients and healthy controls were collected. Using “IM B Cell Tubes, 25 Tests, Ruo (Beckman Colter, USA)”, and flow cytometry were performed to detect B lymphocyte subpopulations. There are 11 items of “IM B Cell Tubes, 25 Tests, Ruo” in the flow cytometry detection, including CD19 + B cells, CD5 + CD19 + B cells, Naïve B cells, Marginal zone B cells, Breg cells, CD21 low B cells, Memory B cells, Class-switched memory B cells, Class-unswitched memory B cells, Transitional B cells, and Plasma cells. Flow cytometry was performed according to the instructions of "IM B Cell Tubes, 25 Tests, Ruo". Afterwards, the correlation between differentially expressed lncRNA, miRNA, mRNA, and B lymphocyte subpopulations was analyzed.
2.8. KEGG pathway enrichment analysis and the target factors of differentially expressed miRNA
Three target factor prediction software TargetScan, miRDB, and mirTarBase were used to predict the target factors of miR-144-3p, miR-374c-3p, and miR-451a. Afterward, the target factors predicted by the three software formed a collection of targets lncRNA and mRNA. The KEGG pathway enrichment analysis was performed to find typical target factors related to B lymphocytes and autoimmune diseases. RNA expressions were calculated as mentioned above.
2.9. Statistical analyses
SPSS 24.0 was used to analyse all collected data. Measurement data were expressed by (X ± S). Using Shapiro–Wilk for normality analysis and Levene for homogeneity of variance analysis. Using one-way ANOVA compare multiple sets of data and LSD t test for statistically significant comparisons of multiple sets of data. The comparison of two sets of data was using Student’s t test. Pearson correlation analysis was used and scatter plots were drawn. A p < 0.05 indicates a statistically significant difference.
3. Results
3.1. The expression of various types of RNA in ITP patients and healthy controls
High-throughput sequencing was performed on peripheral blood CD19 + B lymphocytes of ITP patients and healthy controls. Results of the total and specific expression of miRNA, lncRNA, and mRNA in ITP patients and healthy controls are shown in . The number of miRNA in each of the 4 ITP patients and the 4 healthy controls were closely related.
Table 1. Number of various types of RNA in ITP patients and healthy controls.
3.2. Differentially expressed miRNA between ITP patients and healthy controls
A total of 4 differentially expressed miRNA were screened between ITP patients and healthy controls. Compared with healthy controls, 1 miRNA was up-regulated, and 3 miRNA were down-regulated (see for details). Cluster heat map of the differentially expressed miRNA in 4 cases of ITP patients and healthy controls are shown in .
Figure 1. Cluster heat map of differentially expressed miRNA. The red part represents the up-regulation of differentially expressed miRNA, and the blue represents down-regulation. The white part represents no significant change of differentially expressed miRNA.
Table 2. Differentially expressed miRNA between ITP patients and healthy controls.
3.3. Differentially expressed lncRNA and mRNA between ITP patients and healthy controls
High-throughput sequencing showed 65 differentially expressed lncRNA, 40 up-regulated, and 25 down-regulated. The number of differentially expressed mRNA was 149, among which 82 were up-regulated, and 67 were down-regulated. The cluster heat maps of differentially expressed lncRNA and mRNA are shown in and Citation2b. The specific information of typical expressed lncRNA and mRNA with large differences in two groups of peripheral blood B lymphocytes is shown in .
Figure 2. a: Cluster heat map of differentially expressed lncRNA. b: Cluster heat map of differentially expressed mRNA.
Table 3. Typical differentially expressed lncRNA and mRNA in peripheral blood B lymphocytes of two groups.
3.4. Differentially expressed miRNA, lncRNA and mRNA form a ceRNA network
The selected 4 differentially expressed miRNA, 65 differentially expressed lncRNA, and 149 differentially expressed mRNA were analysed and obtained a ceRNA interaction network, as shown in . Typical differentially expressed lncRNA and mRNA in this ceRNA network are shown in .
Figure 3. a: The original ceRNA network of differentially expressed miRNA, lncRNA, and mRNA. Polygons in the figure represent differentially expressed miRNA, quadrilaterals represent differentially expressed lncRNA, and circles represent differentially expressed mRNA. Gray lines represent differentially expressed RNA connected in the ceRNA network. b: The grid ceRNA network of differentially expressed miRNA, lncRNA, and mRNA. c: The group ceRNA network of differentially expressed miRNA, lncRNA, and mRNA.
Table 4. Typical differentially expressed lncRNA and mRNA in ceRNA network.
3.5. qPCR results of differentially expressed miRNA
Compared with healthy controls, the expression of miR-144-3p, miR-374c-3p, and miR-451a in nITP was decreased. Compared with nITP, the expression of miR-144-3p, miR-374c-3p, and miR-451a in cr-ITP was increased. The difference was statistically significant and consistent with the sequencing results. The expression of miR-4488 in three groups was not statistically significant, as shown in .
Figure 4. The expression of miR-144-3p, miR-374c-3p, and miR-451a in nITP, cr-ITP and healthy controls. The expression of miR-144-3p in nITP (0.02 ± 0.03) was significantly lower than healthy controls (1.20 ± 1.15) and cr-ITP (0.81 ± 0.88) (p < 0.05). the expression of miR-374c-3p (0.17 ± 0.31) in nITP was significantly lower than healthy controls (1.60 ± 1.39) and cr-ITP (1.06 ± 0.96) (p < 0.05). the expression of miR-451a in nITP (0.03 ± 0.06) was significantly lower than healthy controls (1.13 ± 0.94) and cr-ITP (0.37 ± 0.44) (p < 0.05).
3.6. qPCR results of typical differentially expressed lncRNA
Compared with healthy controls, the expression of LOC102724852 in nITP increased. Compared with nITP, the expression of LOC102724852 in cr-ITP decreased. Compared with healthy controls, the expression of LOC112268311 and LOC105378901 in nITP decreased. Compared with nITP, the expression of LOC105378901 in cr-ITP increased. The difference is statistically significant and consistent with the sequencing results. The expression of LOC105371235 and LOC102724297 in three groups were not statistically significant, as shown in .
Figure 5. The expression of LOC102724852, LOC112268311, and LOC105378901 in both nITP and cr-ITP groups as well as healthy controls. The expression of LOC102724852 in nITP (2.65 ± 2.23) was significantly higher than healthy controls (1.46 ± 1.07) and cr-ITP (0.63 ± 0.82) (p < 0.05). the expression of LOC112268311 (0.52 ± 0.88) in nITP was significantly lower than healthy controls (1.37 ± 0.85) (p < 0.05). the expression of LOC105378901 (0.70 ± 0.48) in nITP was significantly lower than healthy controls (1.30 ± 0.74) and cr-ITP (2.13 ± 1.98) (p < 0.05).
3.7. qPCR results of typical differentially expressed mRNA
Compared with healthy controls, the expression of CCL20 in nITP increased. Compared with nITP, the expression of CCL20 in cr-ITP decreased. Compared with healthy controls, the expression of TBC1D3F and ALAS2 in nITP decreased. Compared with nITP, the expression of TBC1D3F in cr-ITP increased. The difference is statistically significant and consistent with the sequencing results. The expressions of SAPCD1, CXCL3, and RIMBP3C in three groups were not statistically significant, as shown in .
Figure 6. The expression of CCL20, ALAS2, TBC1D3F in nITP, cr-ITP, and healthy controls. The expression of CCL20 (2.91 ± 2.89) in nITP patients was significantly higher than healthy controls (1.34 ± 0.89) and cr-ITP (0.84 ± 0.97) (p < 0.05). the expression of ALAS2 (0.51 ± 0.56) in nITP was significantly lower than healthy controls (1.57 ± 1.35) (p < 0.05). the expression of TBC1D3F (0.57 ± 0.27) in nITP patients was significantly lower than healthy controls (1.13 ± 0.58) and cr-ITP (1.63 ± 0.79) (p < 0.05).
3.8. Results of B lymphocyte subsets in nITP and healthy controls
B lymphocyte subsets in ITP patients and healthy controls were detected by flow cytometry, as shown in . Compared with healthy controls, the expression of CD19 + B lymphocytes in nITP was increased, and the difference was statistically significant.
Table 5. Results of B lymphocyte subsets in ITP patients and healthy controls.
3.9. Correlation analysis of differentially expressed miRNA, lncRNA, mRNA, and B lymphocyte subsets
Correlation analysis was conducted between the expression of differentially expressed miRNA, lncRNA, mRNA, and all B lymphocyte subsets indexes in nITP group. The expression of miR-374c-3p was positively correlated with CD19 + B lymphocytes. The expression of LOC112268311 was positively correlated with Memory B cells/B CELL. The expression of LOC105378901 was positively correlated with Naïve B cells/B CELL, while the expression of LOC105378901 was negatively correlated with Class-switched memory B cells/B CELL. The expression of CXCL3 was positively correlated with CD19 + B lymphocytes, as shown in .
Figure 7. a: Scatter plot showing the correlation analysis between miR-374c-3p and CD19 + B lymphocytes. In this figure, Spearman (r = 0.644, p = 0.002). b: Scatter plot of correlation analysis between LOC112268311 and Memory B cells/B CELL, Spearman (r = 0.519, p = 0.033). c: Scatter plot showing the correlation analysis between LOC105378901 and Naïve B cells/B CELL. In this figure, Spearman (r = 0.500, p = 0.025). d: Scatter plot of correlation analysis between LOC105378901 and Class-switched memory B cells/B CELL, Spearman (r = –0.496, p = 0.026). e: Scatter plot showing the correlation analysis between CXCL3 and CD19 + B lymphocytes, Spearman (r = 0.602, p = 0.011).
3.10. Targets of miR-144-3p, miR-374c-3p and miR-451a
The targets of lncRNA and mRNA by miR-144-3p, miR-374c-3p, and miR-451a are shown in . KEGG pathway enrichment analysis on target lncRNA and mRNA of 3 miRNA were used. Then, the typical target lncRNA and mRNA related to B lymphocytes and autoimmune diseases were further screened out, as shown in .
Table 6. The targets by miR-144-3p, miR-374c-3p and miR-451a.
Table 7. KEGG pathway enrichment analysis of the typical target factors in 3 miRNA.
3.11. qPCR results of typical target factors in miR-144-3p
Compared with healthy controls, the expression of typical target factor FZD4 in nITP was increased. Compared with nITP, the expression of FZD4 in cr-ITP was decreased. The difference was statistically significant, opposite to the expression of miR-144-3p. Compared with healthy controls, the expression of β-catenin in nITP was increased. Compared with nITP, the expression of β-catenin in cr-ITP was decreased. The difference was statistically significant and consistent with the expression of FZD4, as shown in . The expression of Wnt1 in three groups was not statistically significant.
Figure 8. The expression of FZD4 and β-catenin in nITP, cr-ITP, and healthy controls. The expression of FZD4 in nITP (7.68 ± 6.83) was significantly higher than healthy controls (1.08 ± 0.66) and cr-ITP (0.55 ± 0.75) (p < 0.05). the expression of β-catenin in nITP patients (1.72 ± 0.95) was significantly higher than healthy controls (0.51 ± 0.36) and cr-ITP (0.60 ± 0.32) (p < 0.05).
3.12. qPCR results of typical target factors in miR-374c-3p
Compared with healthy controls, the expression of the typical target factor FAM98A in nITP was increased. Compared with nITP, the expression of FAM98A in cr-ITP was decreased. The difference was statistically significant, opposite to the expression of miR-374c-3p. Compared with healthy controls, the expression of miR-374c-3p typical target factor LOC107984634 in nITP patients was increased. The difference was statistically significant, opposite to the expression of miR-374c-3p. As shown in .
Figure 9. The expression of FAM98A and LOC107984634 in nITP, cr-ITP, and healthy controls. The expression of FAM98A in nITP (3.43 ± 2.57) was significantly higher than healthy controls (1.22 ± 0.72) and cr-ITP (0.63 ± 0.73) (p < 0.05). the expression of LOC107984634 (8.48 ± 7.83) in nITP was significantly higher than healthy controls (1.25 ± 1.10) (p < 0.05).
4. Discussion
ITP is a common haemorrhagic autoimmune disease with poorly understood pathogenesis. B lymphocytes not only produce antibodies but also play inhibitory and regulatory roles in the immunity of ITP patients [Citation16,Citation17]. Previous studies have found that various miRNA and mRNA have been screened, showing expression in the mesenchymal stem cells and plasma-derived exosomes of ITP patients [Citation18,Citation19]. However, the merging roles of miRNA, lncRNA, and mRNA in B lymphocytes of ITP patients is still unclear.
This study screened 1336 miRNA, 23163 lncRNA, and 19439 mRNA from CD19 + B lymphocytes of 4 ITP patients. At the same time, 1360 miRNA, 23107 lncRNA, and 19401 mRNA were screened from CD19 + B lymphocytes of 4 healthy controls. Further research found 4 differentially expressed miRNA in B lymphocytes of ITP patients with differential multiple ≥2 and Q value < 0.05. The expression of hsa-miR-144-3p, hsa-miR-374c-3p, and hsa-miR-451a were all down-regulated, while the expression of hsa-miR-4488 was up-regulated. We verified these four miRNA by qPCR and found the expressions of miR-144-3p, miR-374c-3p, and miR-451a in peripheral blood CD19 + B lymphocytes of ITP patients were consistent with sequencing results.
It has been reported that miR-144-3p plays an immunomodulatory role in autoimmune diseases such as rheumatoid arthritis and graves’ disease. Moreover, miR-144-3p also plays a role in bone marrow mesenchymal cells of aplastic anaemia [Citation20–22]. Similarly, miR-374c is an important immune factor and can promote the differentiation of immune cells Th17 in experimental autoimmune encephalomyelitis [Citation23,Citation24]. As an immune factor, miR-451a was found to be abnormally expressed in patients with systemic lupus erythematosus and was also correlated with the expression of CD4+/CD8 + T lymphocytes [Citation25]. These 3 miRNA play important roles in the immune system, inflammation, and autoimmune disease. Therefore, we believe these miRNA may drive the immune dysfunction in ITP, but the exact mechanism remains to be further elucidated.
Differential multiple ≥2 and Q value < 0.05 was noted, and of the 65 differentially expressed lncRNA in peripheral blood B lymphocytes of two groups, 40 were up-regulated, and 25 were down-regulated. Also, among the 65 lncRNA, LOC102724852 was highly expressed, while LOC105378901 was not. Similarly, among the differentially expressed mRNA, the expression of SAPCD1, CCL20, and CXCL3 was significantly higher, while TBC1D3F was not. We confirmed the differentially expressed lncRNA and mRNA by qPCR and found the expression of LOC102724852, LOC112268311, LOC105378901, CCL20, TBC1D3F, and ALAS2 in peripheral blood CD19 + B lymphocytes of ITP patients were consistent with the sequencing results.
CCL20 has lymphocytic chemotactic properties, participates in immune regulation and inflammation, and regulates the proliferation of T and B lymphocytes [Citation26]. Moreover, the level of CCL20 in joint synovial fluid of patients with rheumatoid arthritis was increased, suggesting that CCL20 participates in the pathogenesis of rheumatoid arthritis [Citation27]. Our study found that the expression of CCL20 was increased in B lymphocytes of new ITP patients. Therefore, CCL20 may become new therapeutic targets and novel directions in understanding the pathogenesis of ITP.
Collectively, ceRNA is composed of many different transcriptomes, including miRNA, lncRNA, and mRNA. This study used differentially expressed miRNA, lncRNA, and mRNA in peripheral blood CD19 + B lymphocytes of new ITP patients and healthy controls to construct a ceRNA network. Due to the small number of differentially expressed miRNA, we did not find these miRNA to be directly connected with differentially expressed lncRNA and mRNA. However, from this ceRNA network, 12 differentially expressed lncRNA and 136 differentially expressed mRNA were related. The relatively central node was TP63, TLR10, and HMMR. TLR10 is a regulatory receptor related to inflammation and immunity, mainly expressed in B lymphocytes [Citation28]. It was found that the expression of TLR10 in various types of the B cell subsets was increased, and positively correlated with the disease activity of patients with rheumatoid arthritis [Citation29]. Our study also found that TLR10 was more closely connected in our ceRNA network. Therefore, TLR10 may also become a new target and direction for the study of ITP pathogenesis.
Consistent with previous studies, antibody-mediated platelet destruction is the main pathogenesis of ITP. We found that the proportion of B cells was indeed elevated in ITP patients, but there were no significant abnormalities in the proportion of each subgroup. Correlation analysis of clinical indexes of differentially expressed miRNA, lncRNA, mRNA, and B lymphocyte subsets of ITP patients found that the expression of miR-374c-3p was positively correlated with the proportion of CD19 + B lymphocytes. The expression of LOC112268311 was positively correlated with Memory B cells/B CELL. The expression of LOC105378901 was positively correlated with naïve B cells/B CELL, and negatively correlated with Class-switched memory B cells/B CELL. The expression of CXCL3 was positively correlated with the ratio of CD19 + B lymphocytes, heralding the potential role of various B lymphocyte subtypes and lncRNA in ITP patients, but it requires further research.
This study also analysed the differentially expressed miR-144-3p and miR-374c-3p at a relatively deeper level. Among the typical target factors of miR-144-3p, frizzled 4 (FZD4) is a transmembrane receptor located on the surface of the cell membrane. FZD4 bind to the extracellular Wnt1 and activates Wnt/β-catenin signalling, blocking the degradation and phosphorylation of β-catenin, thus allowing β-catenin to enter the nucleus and participate in cellular regulation [Citation30]. Also, FZD4 act as the target of miRNA-101, miRNA-505 and miRNA-1286 [Citation31–33]. In addition, the expression of FZD4 and miR-144-3p was found opposite to peripheral blood CD19 + B lymphocytes of ITP patients. Conversely, the expression of β-catenin in peripheral blood CD19 + B lymphocytes of ITP patients was consistent with the expression of FZD4. Therefore, we speculate that miR-144-3p inhibited the expression of target factor FZD4 and indirectly promoted FZD4-mediated Wnt/β-catenin signalling, leading to the entry of β-catenin protein into the nucleus for cellular regulation.
The typical target factor FAM98A of miR-374c-3p, can also be used as a target factor of miR-26a and miR-142-3p [Citation34,Citation35]. Moreover, the expression of FAM98A in peripheral blood CD19 + B lymphocytes of ITP patients was found to be the opposite of miR-374C-3p. However, the expression of LOC107984634 in peripheral blood CD19 + B lymphocytes of ITP patients was consistent with the expression of FAM98A. Therefore, it is plausible to suggest that as a target lncRNA of miR-374c-3p, LOC107984634 indirectly promotes the expression of FAM98A, which is also a target of miR-374c-3p, through competitive absorption of miR-374c-3p.
5. Conclusion
In our study, we extracted B lymphocytes from peripheral blood of ITP patients and screened out differentially expressed miRNA, lncRNA and mRNA by high-throughput sequencing. After preliminary validation by qPCR, we found that miR-144-3p, miR-374c-3p, miR-451a and CCL20 can play an important role in the immune regulation of B lymphocytes in ITP patients. We constructed a ceRNA network with differentially expressed miRNA, lncRNA and mRNA screened by ourselves, and finally found that TLR10 and other factors can play a central role in our ceRNA network. We further found that the screened differentially expressed miRNA, lncRNA and mRNA were also correlated in various subtype of B lymphocytes. Furthermore, the deeper roles of miR-144-3p and miR-374c-3p in B lymphocytes were analysed. In conclusion ceRNA network of differentially expressed miRNA, lncRNA and mRNA participate in the pathogenesis of B lymphocyte-mediated ITP by modulating subgroups of B lymphocyte and other related signalling pathways. Further research is needed to understand the crucial regulatory role of ceRNA network in B lymphocytes of patients with immune thrombocytopenia.
Data availability statement
The data used to support the findings of this study are included within this article. And the raw data used to support the findings of this study are available from the first author upon request.
The manuscript has been submitted solely to this journal and is not published in the press or submitted elsewhere, and confirm that all the research meets the ethical guidelines, including adherence to the legal requirements of the study country. There is no conflict of interest among the 11 authors of this article entitled “Regulatory role of ceRNA network in B lymphocytes of patients with immune thrombocytopenia”: Xin He, Nianbin Li, Donglan Liu, Mengtong Zang, Manjun Zhao, Ningyuan Ran, Chunyan Liu, Limin Xing, Huaquan Wang, Ting Wang, Zonghong Shao.
All persons gave their informed consent prior to their inclusion in this study.
Details that might disclose the identity of the subjects under study should be omitted.
Include the following: Informed consent was obtained from all patients for being included in this study.
Additional information
Funding
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