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MicroRNA expression profiles of peripheral blood mononuclear cells in patients with systemic lupus erythematosus Dongmei Liu, Haiyan Zhao, Shuai Zhao, Xiaofei Wang ∗ Department of Rheumatology and Immunology, Shengjing Hospital, China Medical University, Shenyang 110004, People’s Republic of China
a r t i c l e
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Article history: Received 30 December 2013 Received in revised form 24 February 2014 Accepted 25 February 2014 Available online xxx Keywords: SLE Microarray miRNA Gene ontology analysis Pathway analysis
a b s t r a c t Systemic lupus erythematosus (SLE) is an autoimmune disease characterized by the presence of autoantibodies against numerous self-antigens. Evidence underlines the importance of microRNAs (miRNAs) in the pathogenesis of SLE, but the exact etiology of this disease is unknown. Therefore, this study was conducted to explore regulation of abnormal miRNAs in SLE using microarray analysis. Peripheral blood mononuclear cells (PBMCs) from SLE patients and their matched controls were isolated appropriately. Total RNAs from each cell sample were extracted and used for microarray analysis. A total of 29 miRNAs were identified to be down-regulated in PBMCs of SLE patients as compared with healthy controls (P < 0.05, fold change > 2). No significant up-regulated miRNAs were found in SLE patients. Results of gene ontology analysis indicated that the potential target genes of these miRNAs mainly enriched in the development process, transcription regulator activity, ligand binding, etc. Meanwhile, these putative genes were also found to be involved in diverse signaling transduction pathways, including multiple cancer pathways, Wnt and mitogen-activated protein kinase signaling pathways, etc. This study revealed possible dysregulated biological processes and pathways in SLE that were targeted by the differentially expressed miRNAs, indicating the involvement of these miRNAs in the pathogenesis of SLE. © 2014 Elsevier GmbH. All rights reserved.
Introduction Systemic lupus erythematosus (SLE), an autoimmune disease, is characterized by multiple immunologic abnormalities, including loss of immunological tolerance to self-nuclear antigens (Bertsias et al., 2010), aberrant lymphocyte activation and autoantibody production (Kow and Mak, 2013; Murphy et al., 2013; Shirota et al., 2013), and a sustained type I interferon response (Ronnblom et al., 2011; Kirou and Gkrouzman, 2013). Though SLE affects all human races, it is more prevalent in women, particularly during their childbearing years, with a female to male ratio of 9:1 (Gurevitz et al., 2013). Current treatments for this disease are effective at reducing morbidity and mortality but fail to provide a cure (Xiong and Lahita, 2014). The etiology of SLE remains elusive and requires to be elucidated. MicroRNAs (miRNA) are endogenous, small non-coding RNAs of typical 22 nucleotides in length (Allegra et al., 2012). It is widely accepted that miRNAs participate in the regulation of
∗ Corresponding author at: Department of Rheumatology and Immunology, Shengjing Hospital, China Medical University, 36 Sanhao Street, Shenyang 110004, People’s Republic of China. E-mail address: [email protected] (X. Wang).
diverse cellular processes by binding to the 3 untranslated region (UTR) of certain subsets of messenger RNAs (mRNAs) (Bushati and Cohen, 2007; Filipowicz et al., 2008; Ameres and Zamore, 2013). Increasing evidence has demonstrated that the abnormal expression of miRNAs is associated with the pathogenesis of multiple immunological diseases (Xiao and Rajewsky, 2009), including SLE (Shen et al., 2012). Microarray technology is a powerful highthroughput tool that is able to monitor the expression of thousands of small non-coding RNAs simultaneously in a single experiment (Liu et al., 2008). The miRNA expression profiles in SLE patients are being analyzed by using the microarray technology, and the corresponding results are utilized to distinguish SLE from other immunoinflammatory phenotypes. Carlsen et al. (2013) have identified 2 up-regulated and 5 down-regulated circulating miRNAs in the cell-free plasma samples from patients with SLE (Carlsen et al., 2013). Moreover, a report from Dai et al. (2007) has shown that 9 miRNAs are up-regulated and 7 miRNAs are down-regulated in the peripheral blood mononuclear cells (PBMCs) in SLE patients when compared with healthy individuals (Dai et al., 2007). These researches suggest that miRNAs may participate in the pathogenesis of human SLE. However, the previous data of miRNA microarrays related to SLE are poorly overlapped. A possible explanation for the inconsistent results may rise from ethnicities and the individual differences between experimental subjects. Therefore, to better
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2 Table 1 Characteristics of SLE patients and healthy controls. Characteristics
SLE patients (n = 3)
Healthy controls (n = 3)
Gender Age (years) SLEDAI (range)
Female 37 ± 19.8 9.3 ± 1.2 (8–10)
Female 34 ± 17.1 Negative
SLE, systemic lupus erythematosus; SLEDAI, systemic lupus erythematosus disease activity index.
understand the mechanisms underlying the development of SLE, in the present study, we continued to search for miRNAs that may be involved in the pathogenesis of SLE. In this study, the total RNAs in the PBMCs from SLE patients and healthy subjects were extracted. After integrity assessment, RNAs of equivalent amount from each cell sample were subjected to miRNA microarray analysis. Materials and methods
Fig. 1. Principal component analysis (PCA) of miRNA expression data set. A red dot represents a control sample whereas a blue dot represents a sample from a systemic lupus erythematosus (SLE) patient. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
Human subjects: SLE patients and healthy controls The research protocol was approved by Institutional Review Board of China Medical University, and all participants provided written informed consent. Three Chinese women diagnosed with SLE were admitted to Shengjing Hospital of China Medical University and enrolled in our present study. They had never been treated with disease-modifying antirheumatic drugs or other immunosuppressive drugs. The diagnosis of the three patients was made according to the classification criteria of SLE developed by the American College of Rheumatology (Hochberg, 1997). Three healthy subjects who matched with the SLE patients by gender and age were recruited as controls. The systemic lupus disease activity index (SLEDAI) score and age of the patients are shown in Table 1. Blood sample collection and RNA isolation Five milliliter venous blood was obtained from the SLE patients and controls, using ethylenediaminetetraacetic acid (EDTA) as the anticoagulant. Immediately after collection of the samples, PBMCs were isolated by Ficoll-Histopaque (Sigma–Aldrich, St. Louis, MO, USA) density gradient centrifugation from the venous blood. Total RNAs were then extracted from these cells by using the Total RNA Purification Kit (Norgen Biotek Corp., Ontario, Canada) according to the manufacturer’s instructions. The integrity of the total RNAs was measured by Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA). MiRNA microarray procedures Total RNAs were dephosphorylated with phosphatase at 37 ◦ C for 30 min and subsequently labeled by using the Labeling Spike-In Kit (Agilent Technologies) according to the manufacturer’s protocol. The labeled RNAs were then desalted with spin column, dried in a vacuum concentrator, and redissolved in nuclease-free water. Then, the RNAs (100 ng) were hybridized to Agilent Human miRNA Version 19.0 (Agilent Technologies) which contains 2006 human miRNA probes at 55 ◦ C for 20 h. Thereafter, the arrays were washed with Agilent’s Gene Expression Wash Buffer Kits (Agilent Technologies). The information of microarray image was converted into spot intensity values using Agilent Microarray Scan Control Software Version 8.0 (Agilent Technologies). The signal after background subtraction was imported directly into the GeneSpring GX11.0 software (Agilent Technologies).
Quantitative real-time polymerase chain reaction (PCR) The expression levels of differentially expressed microRNAs were validated using quantitative real-time PCR in all cell samples (three SLE patients and three healthy controls). cDNAs were synthesized from total RNAs using Super M-MLV reverse transcriptase kit (BioTeke, Beijing, China). SYBR Green (Solarbio, Beijing, China) was used for real-time PCR on Exicycler TM 96 (Bioneer, Daejeon, Korea). The expression level of each miRNA was normalized to that of U6, an endogenous RNA species. Triplicate reactions were conducted on each sample, and the data were analyzed through the comparative threshold cycle (Ct) method. The relative expression level of each miRNA was measured through the equation 2−Ct (Ct = CtmiRNA − CtU6 ).
Data handling and statistical analysis Raw data were quantile normalized using GeneSpring 12.0 software (Agilent Technologies, Santa Clara, CA, USA), and then imported into the GeneSpringTM GX 11.0 software. The principal component analysis (PCA) was adopted to visually assess similarities and differences of the six cell samples. Given the small sample size, unpaired t-test was used to filter the differentially expressed miRNAs between SLE patients and healthy controls, and Bonferroni multiple testing was used to correct the data. The miRNAs with statistically significant P value (P < 0.05) and fold change (>2-fold) were selected for further analysis. Average linkage hierarchical clustering was performed and the Pearson centered distance metric was used to measure the similarity between the miRNA expression profiles samples based on log-transformed signal values across the differentially expressed miRNAs. The target genes of the differentially expressed microRNAs were predicted using TargetScan (http://www.targetscan.org/). Gene ontology (GO) analysis and Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis were performed to display the miRNA-gene regulatory network. Generally, Fisher’s exact test and 2 test were used to classify the GO category and the significant pathways, and the false discovery rate (FDR) analysis was calculated to correct the P-value. Smaller FDR means smaller error in judging the P-value. The GOs and pathways with P < 0.05 and FDR < 0.05 were selected.
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D. Liu et al. / Acta Histochemica xxx (2014) xxx–xxx Table 2 Twenty-nine miRNAs were down-regulated in PMBCs from SLE patients versus healthy controls. miRNA
Fold change (log 2)
P value
hsa-miR-127-3p hsa-miR-1271-5p hsa-miR-1301 hsa-miR-136-5p hsa-miR-146b-5p hsa-miR-154-3p hsa-miR-154-5p hsa-miR-181a-2-3p hsa-miR-31-5p hsa-miR-337-5p hsa-miR-376a-3p hsa-miR-376b-3p hsa-miR-376c-3p hsa-miR-379-5p hsa-miR-381-3p hsa-miR-382-5p hsa-miR-409-5p hsa-miR-410 hsa-miR-421 hsa-miR-431-5p hsa-miR-432-5p hsa-miR-485-3p hsa-miR-487b hsa-miR-493-5p hsa-miR-495-3p hsa-miR-539-5p hsa-miR-543 hsa-miR-654-3p hsa-miR-758-3p
6.41 5.08 4.64 5.4 2.15 5.59 5.44 4.32 6.39 5.4 2.62 4.71 2.42 6.1 6.05 6.03 4.6 7.57 4.64 6.37 6.44 5.43 1.85 6.23 2.32 4.53 5.36 6.92 4.7
0.002359 0.003637 0.004555 0.006859 0.042345 0.00317 0.00377 0.00845 0.0038 0.006737 0.027329 0.007538 0.036464 0.003439 0.004829 0.003386 0.016137 0.001467 0.003309 0.002605 0.002273 0.004065 0.032313 0.00234 0.035215 0.010264 0.003594 0.001914 0.01146
PMBCs, peripheral blood mononuclear cells; SLE, systemic lupus erythematosus.
Results Global differences in miRNA expression Regarding the high incidence of SLE in women, PBMCs from 3 Chinese female SLE patients were collected for this study. Human miRNA arrays (containing 2006 miRNA probes) were used to explore miRNA expression patterns in PBMCs from SLE patients and healthy controls. The intersection between the two groups was submitted to PCA. PCA is a mathematical algorithm that reduces the dimensionality of the data while retaining most of the variation in the data set. By using PCA, it is possible to visually assess similarities and differences between samples and to determine whether samples can be grouped (Ringner, 2008). The present PCA results showed clear segregation of PBMCs in SLE patients from the ones in healthy controls (Fig. 1), indicating that the samples used in the present study were appropriately prepared and selected. Differential expression of miRNAs in PBMCs from SLE patients In this study, the differential expression profile of miRNAs in PBMCs from SLE patients comparing with healthy subjects was obtained by using a miRNA array. We found 29 differentially expressed miRNAs that were all down-regulated (P < 0.05, fold change > 2) in patients with SLE (Table 2) in this study. Quantitative real-time PCR was performed to verify the differential expression of the candidate miRNAs. Six of the 29 differentially expressed miRNAs in PBMCs were selected on the basis of previous correlations with SLE and their expression levels, or were supervised by the following pathway analysis. As indicated in Fig. 2, the results obtained from the validation of quantitative real-time PCR were consistent with the miRNA array analysis (Fig. 2). The cluster diagram based on the differentially expressed miRNAs was obtained by using cluster 3.0 software. As shown in Fig. 3, the
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Table 3 Twelve significant GOs targeted by the down-regulated miRNAs. GO ID
GO term
P value
FDR
GO:0032502
Development process Transcription regulator activity Ligand binding Biological regulation Cellular physiological process Cell part Cell Synaptic junction Organelle Multicellular organismal process Cellular component organization Synapse part
1.19E−22
9.33E−20
9.33E−20
5.60E−17
1.23E−18 4.93E−15
7.38E−16 3.82E−12
4.74E−14
3.71E−11
7.15E−12 7.60E−12 1.29E−10 8.22E−10 1.55E−09
4.46E−09 4.73E−09 8.04E−08 5.12E−07 1.21E−06
2.15E−07
1.68E−04
2.12E−05
0.013185
GO:0030528 GO:0005488 GO:0065007 GO:0009987
GO:0044464 GO:0005623 GO:0045202 GO:0043226 GO:0032501 GO:0016043
GO:0044456
P value < 0.05, false discovery rate (FDR) < 0.05.
SLE patients contributed to a cluster, corresponding to our earlier PCA results (Fig. 3). Next, the target genes of these differentially expressed miRNAs were predicted on line with TargetScan. A total of 2083 target genes were identified to be regulated by 11 out of the 29 differentially expressed miRNAs, including hsa-miR-543, hsa-miR-410, hsa-miR-485-3p, hsa-miR-654-3p, hsa-miR-409-5p, hsa-miR-487b, hsa-miR-1301, hsa-miR-127-3p, hsa-miR-337-5p, hsa-miR-421 and hsa-miR-146b-5p. These putative genes were sorted by total context + score. The total number of genes that were regulated by hsa-miR-543, hsa-miR-410 and hsa-miR-485-3p was over 1700, suggesting that these three miRNAs may have the most important regulatory functions. Functional categorization by microarray-based GO analysis To determine the physiological processes involving the target genes, we performed GO analysis in this study. Twelve significant GOs (P value < 0.05, FDR < 0.05) were identified, including development process, transcription regulator activity, ligand binding, biological regulation, cellular physiological process, etc. (Table 3). These results illustrated that the genes targeted by the differentially expressed miRNAs were involved in various biological processes. Significantly enriched KEGG pathways A separate functional analysis by KEGG pathway revealed that these target genes were highly enriched in 6 signaling pathways (P < 0.05, FDR < 0.05) (Fig. 4). A total of 36 putative genes were found to be enriched in the pathways of multiple cancers, including in colorectal cancer, pancreatic cancer, glioma, thyroid cancer, acute and chronic myeloid leukemia, basal cell carcinoma and melanoma, etc. (Fig. 5). Additionally, 17 out of the 36 target genes were regulated by hsa-miR-410, suggesting a vital role of this miRNA in cancer pathways related to the pathogenesis of SLE. Discussion Previous discoveries have indicated that the aberrant expression of miRNAs is associated with the pathogenesis of SLE (Shen et al., 2012). Therefore, to profile miRNA expression in PBMCs taken from patients with SLE, miRNA microarray analysis was performed in the present study. By comparing miRNA expression patterns in PBMCs from patients with SLE versus healthy controls,
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Fig. 2. Quantitative real-time PCR validation for differentially expressed miRNAs. All the data are expressed as mean ± standard deviation (SD) (n = 3/group). SLE, systemic lupus erythematosus. P < 0.05 is considered significant.
Fig. 3. Cluster analysis of miRNA microarray data. Each row represents a single miRNA and each column represents a peripheral blood mononuclear cell (PBMC) sample. Pseudocolors indicate differential expression: red represents expression level above mean expression of a miRNA across all samples; green represents expression level below mean expression; black represents mean expression. Distance metric, Pearson centered; linkage rule, average. SLE, systemic lupus erythematosus. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
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Fig. 4. Pathway analysis based on the potential target genes. Significant pathways targeted by the down-regulated miRNAs (P < 0.05, FDR < 0.05). Lg P is the negative logarithm of P value, and a bigger Lg P value indicates a smaller P value. MAPK, mitogen-activated protein kinase; FDR, false discovery rate.
29 differentially expressed miRNAs were identified. All of these miRNAs were decreased in SLE patients. However, based on our results, no significant up-regulated miRNAs were found in PBMCs obtained from SLE patients. To explore cell-intrinsic abnormalities, many comparative microarray studies have been conducted to identify the miRNAs of differentially expression in the PBMCs (Hai-yan et al., 2011; Stagakis et al., 2011) or purified leukocyte subsets (Zhao et al., 2010, 2011) among patients with SLE, patients with other autoimmune diseases and healthy individuals. A deregulation of miRNAs involved in the pathogenesis of SLE has been
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observed (Miao et al., 2013). Nonetheless, data from these earlier researches and our present study were poorly overlapped. The discrepancy may be the different genetic background and clinical characteristics of experimental subjects and the different laboratory techniques. Moreover, the number of SLE patients in our study was relatively small, and therefore further research conducted in a larger population is needed to validate our present results. Although, as demonstrated in several prior studies (Luo et al., 2011; Wang et al., 2012), miR-155 and miR-146a participate in the SLE pathogenesis, our data showed no significant expression alteration of these two miRNAs. One explanation for the discrepant results may be the intrinsic variability of the SLE pathology. Despite these inconsistencies, our results confirmed a previous reported research from Lashine et al. (2011) by showing that miR-181-a-23p was significantly decreased in PMBCs isolated from SLE patients. Therefore, we hypothesize that miR-181-a-2-3p is involved in the pathogenesis of SLE, and its function is expected to be verified by future research. A total of 2083 genes were found to be regulated by 11 out of the 29 differentially expressed miRNAs. GO analysis was then utilized to examine the potential molecular functions and biological processes of these target genes. These genes were observed to regulate a wide range of biological processes, and their molecular attributes were mainly annotated as development processes, transcription regulator activity, ligand binding, etc. Such findings suggested that these biological processes may contribute to the pathogenesis of SLE.
Fig. 5. Signal pathways in various cancer types. Genes in red are the ones targeted by differentially expressed miRNAs, whereas genes in purple are not. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
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Since the GOs may overlap, the KEGG pathway analysis was performed to integrate individual components into a unified pathway (Kanehisa et al., 2006). A total of 6 significant dysregulated signaling pathways were observed in SLE. Importantly, our data showed that 36 genes targeted by the down-regulated miRNAs were enriched in pathways of multiple cancers, including Wnt and MAPK signaling pathways. Morphologic changes that occur within the glomerulus during the development of lupus nephritis have been shown to be mediated by the Wnt pathway (Tveita and Rekvig, 2011). In addition, abnormal activation of p38 MAPK has been postulated to contribute to the inflammation of SLE, resulting in progressive tissue and organ damage to develop lupus nephritis and autoimmune hepatitis (Jin et al., 2011). The above studies have revealed that disorders of the above two cell signal transduction pathways contribute to the initiation and progression of systemic and endorgan disease manifestations in SLE. Intriguingly, 17 out of the 36 predicted genes were found as the targets for has-mir-410. This miRNA has been reported to be a prognostic marker in neuroblastoma (Gattolliat et al., 2011) and function as a tumor suppressor in human gliomas (Chen et al., 2012). However, as far as we are aware, it is the first time to show its involvement in the deregulated signaling pathways related to SLE. Further experiments are being conducted by our group to explore the precise function of has-mir-410 and to unravel its regulatory mechanisms in SLE. In conclusion, we identified 29 miRNAs differentially expressed in SLE patients, whose expression profiles may provide a basis for developing novel prognostic biomarkers of SLE. Functional bioinformatic analyses demonstrated that target genes regulated by these miRNAs were involved in various biological processes and signaling pathways, though the exact regulatory mechanisms need to be fully studied.
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MicroRNA expression profiles of peripheral blood mononuclear cells in patients with systemic lupus erythematosus Dongmei Liu, Haiyan Zhao, Shuai Zhao, Xiaofei Wang ∗ Department of Rheumatology and Immunology, Shengjing Hospital, China Medical University, Shenyang 110004, People’s Republic of China
a r t i c l e
i n f o
Article history: Received 30 December 2013 Received in revised form 24 February 2014 Accepted 25 February 2014 Available online xxx Keywords: SLE Microarray miRNA Gene ontology analysis Pathway analysis
a b s t r a c t Systemic lupus erythematosus (SLE) is an autoimmune disease characterized by the presence of autoantibodies against numerous self-antigens. Evidence underlines the importance of microRNAs (miRNAs) in the pathogenesis of SLE, but the exact etiology of this disease is unknown. Therefore, this study was conducted to explore regulation of abnormal miRNAs in SLE using microarray analysis. Peripheral blood mononuclear cells (PBMCs) from SLE patients and their matched controls were isolated appropriately. Total RNAs from each cell sample were extracted and used for microarray analysis. A total of 29 miRNAs were identified to be down-regulated in PBMCs of SLE patients as compared with healthy controls (P < 0.05, fold change > 2). No significant up-regulated miRNAs were found in SLE patients. Results of gene ontology analysis indicated that the potential target genes of these miRNAs mainly enriched in the development process, transcription regulator activity, ligand binding, etc. Meanwhile, these putative genes were also found to be involved in diverse signaling transduction pathways, including multiple cancer pathways, Wnt and mitogen-activated protein kinase signaling pathways, etc. This study revealed possible dysregulated biological processes and pathways in SLE that were targeted by the differentially expressed miRNAs, indicating the involvement of these miRNAs in the pathogenesis of SLE. © 2014 Elsevier GmbH. All rights reserved.
Introduction Systemic lupus erythematosus (SLE), an autoimmune disease, is characterized by multiple immunologic abnormalities, including loss of immunological tolerance to self-nuclear antigens (Bertsias et al., 2010), aberrant lymphocyte activation and autoantibody production (Kow and Mak, 2013; Murphy et al., 2013; Shirota et al., 2013), and a sustained type I interferon response (Ronnblom et al., 2011; Kirou and Gkrouzman, 2013). Though SLE affects all human races, it is more prevalent in women, particularly during their childbearing years, with a female to male ratio of 9:1 (Gurevitz et al., 2013). Current treatments for this disease are effective at reducing morbidity and mortality but fail to provide a cure (Xiong and Lahita, 2014). The etiology of SLE remains elusive and requires to be elucidated. MicroRNAs (miRNA) are endogenous, small non-coding RNAs of typical 22 nucleotides in length (Allegra et al., 2012). It is widely accepted that miRNAs participate in the regulation of
∗ Corresponding author at: Department of Rheumatology and Immunology, Shengjing Hospital, China Medical University, 36 Sanhao Street, Shenyang 110004, People’s Republic of China. E-mail address: [email protected] (X. Wang).
diverse cellular processes by binding to the 3 untranslated region (UTR) of certain subsets of messenger RNAs (mRNAs) (Bushati and Cohen, 2007; Filipowicz et al., 2008; Ameres and Zamore, 2013). Increasing evidence has demonstrated that the abnormal expression of miRNAs is associated with the pathogenesis of multiple immunological diseases (Xiao and Rajewsky, 2009), including SLE (Shen et al., 2012). Microarray technology is a powerful highthroughput tool that is able to monitor the expression of thousands of small non-coding RNAs simultaneously in a single experiment (Liu et al., 2008). The miRNA expression profiles in SLE patients are being analyzed by using the microarray technology, and the corresponding results are utilized to distinguish SLE from other immunoinflammatory phenotypes. Carlsen et al. (2013) have identified 2 up-regulated and 5 down-regulated circulating miRNAs in the cell-free plasma samples from patients with SLE (Carlsen et al., 2013). Moreover, a report from Dai et al. (2007) has shown that 9 miRNAs are up-regulated and 7 miRNAs are down-regulated in the peripheral blood mononuclear cells (PBMCs) in SLE patients when compared with healthy individuals (Dai et al., 2007). These researches suggest that miRNAs may participate in the pathogenesis of human SLE. However, the previous data of miRNA microarrays related to SLE are poorly overlapped. A possible explanation for the inconsistent results may rise from ethnicities and the individual differences between experimental subjects. Therefore, to better
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Please cite this article in press as: Liu D, et al. MicroRNA expression profiles of peripheral blood mononuclear cells in patients with systemic lupus erythematosus. Acta Histochemica (2014), http://dx.doi.org/10.1016/j.acthis.2014.02.009
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2 Table 1 Characteristics of SLE patients and healthy controls. Characteristics
SLE patients (n = 3)
Healthy controls (n = 3)
Gender Age (years) SLEDAI (range)
Female 37 ± 19.8 9.3 ± 1.2 (8–10)
Female 34 ± 17.1 Negative
SLE, systemic lupus erythematosus; SLEDAI, systemic lupus erythematosus disease activity index.
understand the mechanisms underlying the development of SLE, in the present study, we continued to search for miRNAs that may be involved in the pathogenesis of SLE. In this study, the total RNAs in the PBMCs from SLE patients and healthy subjects were extracted. After integrity assessment, RNAs of equivalent amount from each cell sample were subjected to miRNA microarray analysis. Materials and methods
Fig. 1. Principal component analysis (PCA) of miRNA expression data set. A red dot represents a control sample whereas a blue dot represents a sample from a systemic lupus erythematosus (SLE) patient. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
Human subjects: SLE patients and healthy controls The research protocol was approved by Institutional Review Board of China Medical University, and all participants provided written informed consent. Three Chinese women diagnosed with SLE were admitted to Shengjing Hospital of China Medical University and enrolled in our present study. They had never been treated with disease-modifying antirheumatic drugs or other immunosuppressive drugs. The diagnosis of the three patients was made according to the classification criteria of SLE developed by the American College of Rheumatology (Hochberg, 1997). Three healthy subjects who matched with the SLE patients by gender and age were recruited as controls. The systemic lupus disease activity index (SLEDAI) score and age of the patients are shown in Table 1. Blood sample collection and RNA isolation Five milliliter venous blood was obtained from the SLE patients and controls, using ethylenediaminetetraacetic acid (EDTA) as the anticoagulant. Immediately after collection of the samples, PBMCs were isolated by Ficoll-Histopaque (Sigma–Aldrich, St. Louis, MO, USA) density gradient centrifugation from the venous blood. Total RNAs were then extracted from these cells by using the Total RNA Purification Kit (Norgen Biotek Corp., Ontario, Canada) according to the manufacturer’s instructions. The integrity of the total RNAs was measured by Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA). MiRNA microarray procedures Total RNAs were dephosphorylated with phosphatase at 37 ◦ C for 30 min and subsequently labeled by using the Labeling Spike-In Kit (Agilent Technologies) according to the manufacturer’s protocol. The labeled RNAs were then desalted with spin column, dried in a vacuum concentrator, and redissolved in nuclease-free water. Then, the RNAs (100 ng) were hybridized to Agilent Human miRNA Version 19.0 (Agilent Technologies) which contains 2006 human miRNA probes at 55 ◦ C for 20 h. Thereafter, the arrays were washed with Agilent’s Gene Expression Wash Buffer Kits (Agilent Technologies). The information of microarray image was converted into spot intensity values using Agilent Microarray Scan Control Software Version 8.0 (Agilent Technologies). The signal after background subtraction was imported directly into the GeneSpring GX11.0 software (Agilent Technologies).
Quantitative real-time polymerase chain reaction (PCR) The expression levels of differentially expressed microRNAs were validated using quantitative real-time PCR in all cell samples (three SLE patients and three healthy controls). cDNAs were synthesized from total RNAs using Super M-MLV reverse transcriptase kit (BioTeke, Beijing, China). SYBR Green (Solarbio, Beijing, China) was used for real-time PCR on Exicycler TM 96 (Bioneer, Daejeon, Korea). The expression level of each miRNA was normalized to that of U6, an endogenous RNA species. Triplicate reactions were conducted on each sample, and the data were analyzed through the comparative threshold cycle (Ct) method. The relative expression level of each miRNA was measured through the equation 2−Ct (Ct = CtmiRNA − CtU6 ).
Data handling and statistical analysis Raw data were quantile normalized using GeneSpring 12.0 software (Agilent Technologies, Santa Clara, CA, USA), and then imported into the GeneSpringTM GX 11.0 software. The principal component analysis (PCA) was adopted to visually assess similarities and differences of the six cell samples. Given the small sample size, unpaired t-test was used to filter the differentially expressed miRNAs between SLE patients and healthy controls, and Bonferroni multiple testing was used to correct the data. The miRNAs with statistically significant P value (P < 0.05) and fold change (>2-fold) were selected for further analysis. Average linkage hierarchical clustering was performed and the Pearson centered distance metric was used to measure the similarity between the miRNA expression profiles samples based on log-transformed signal values across the differentially expressed miRNAs. The target genes of the differentially expressed microRNAs were predicted using TargetScan (http://www.targetscan.org/). Gene ontology (GO) analysis and Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis were performed to display the miRNA-gene regulatory network. Generally, Fisher’s exact test and 2 test were used to classify the GO category and the significant pathways, and the false discovery rate (FDR) analysis was calculated to correct the P-value. Smaller FDR means smaller error in judging the P-value. The GOs and pathways with P < 0.05 and FDR < 0.05 were selected.
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D. Liu et al. / Acta Histochemica xxx (2014) xxx–xxx Table 2 Twenty-nine miRNAs were down-regulated in PMBCs from SLE patients versus healthy controls. miRNA
Fold change (log 2)
P value
hsa-miR-127-3p hsa-miR-1271-5p hsa-miR-1301 hsa-miR-136-5p hsa-miR-146b-5p hsa-miR-154-3p hsa-miR-154-5p hsa-miR-181a-2-3p hsa-miR-31-5p hsa-miR-337-5p hsa-miR-376a-3p hsa-miR-376b-3p hsa-miR-376c-3p hsa-miR-379-5p hsa-miR-381-3p hsa-miR-382-5p hsa-miR-409-5p hsa-miR-410 hsa-miR-421 hsa-miR-431-5p hsa-miR-432-5p hsa-miR-485-3p hsa-miR-487b hsa-miR-493-5p hsa-miR-495-3p hsa-miR-539-5p hsa-miR-543 hsa-miR-654-3p hsa-miR-758-3p
6.41 5.08 4.64 5.4 2.15 5.59 5.44 4.32 6.39 5.4 2.62 4.71 2.42 6.1 6.05 6.03 4.6 7.57 4.64 6.37 6.44 5.43 1.85 6.23 2.32 4.53 5.36 6.92 4.7
0.002359 0.003637 0.004555 0.006859 0.042345 0.00317 0.00377 0.00845 0.0038 0.006737 0.027329 0.007538 0.036464 0.003439 0.004829 0.003386 0.016137 0.001467 0.003309 0.002605 0.002273 0.004065 0.032313 0.00234 0.035215 0.010264 0.003594 0.001914 0.01146
PMBCs, peripheral blood mononuclear cells; SLE, systemic lupus erythematosus.
Results Global differences in miRNA expression Regarding the high incidence of SLE in women, PBMCs from 3 Chinese female SLE patients were collected for this study. Human miRNA arrays (containing 2006 miRNA probes) were used to explore miRNA expression patterns in PBMCs from SLE patients and healthy controls. The intersection between the two groups was submitted to PCA. PCA is a mathematical algorithm that reduces the dimensionality of the data while retaining most of the variation in the data set. By using PCA, it is possible to visually assess similarities and differences between samples and to determine whether samples can be grouped (Ringner, 2008). The present PCA results showed clear segregation of PBMCs in SLE patients from the ones in healthy controls (Fig. 1), indicating that the samples used in the present study were appropriately prepared and selected. Differential expression of miRNAs in PBMCs from SLE patients In this study, the differential expression profile of miRNAs in PBMCs from SLE patients comparing with healthy subjects was obtained by using a miRNA array. We found 29 differentially expressed miRNAs that were all down-regulated (P < 0.05, fold change > 2) in patients with SLE (Table 2) in this study. Quantitative real-time PCR was performed to verify the differential expression of the candidate miRNAs. Six of the 29 differentially expressed miRNAs in PBMCs were selected on the basis of previous correlations with SLE and their expression levels, or were supervised by the following pathway analysis. As indicated in Fig. 2, the results obtained from the validation of quantitative real-time PCR were consistent with the miRNA array analysis (Fig. 2). The cluster diagram based on the differentially expressed miRNAs was obtained by using cluster 3.0 software. As shown in Fig. 3, the
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Table 3 Twelve significant GOs targeted by the down-regulated miRNAs. GO ID
GO term
P value
FDR
GO:0032502
Development process Transcription regulator activity Ligand binding Biological regulation Cellular physiological process Cell part Cell Synaptic junction Organelle Multicellular organismal process Cellular component organization Synapse part
1.19E−22
9.33E−20
9.33E−20
5.60E−17
1.23E−18 4.93E−15
7.38E−16 3.82E−12
4.74E−14
3.71E−11
7.15E−12 7.60E−12 1.29E−10 8.22E−10 1.55E−09
4.46E−09 4.73E−09 8.04E−08 5.12E−07 1.21E−06
2.15E−07
1.68E−04
2.12E−05
0.013185
GO:0030528 GO:0005488 GO:0065007 GO:0009987
GO:0044464 GO:0005623 GO:0045202 GO:0043226 GO:0032501 GO:0016043
GO:0044456
P value < 0.05, false discovery rate (FDR) < 0.05.
SLE patients contributed to a cluster, corresponding to our earlier PCA results (Fig. 3). Next, the target genes of these differentially expressed miRNAs were predicted on line with TargetScan. A total of 2083 target genes were identified to be regulated by 11 out of the 29 differentially expressed miRNAs, including hsa-miR-543, hsa-miR-410, hsa-miR-485-3p, hsa-miR-654-3p, hsa-miR-409-5p, hsa-miR-487b, hsa-miR-1301, hsa-miR-127-3p, hsa-miR-337-5p, hsa-miR-421 and hsa-miR-146b-5p. These putative genes were sorted by total context + score. The total number of genes that were regulated by hsa-miR-543, hsa-miR-410 and hsa-miR-485-3p was over 1700, suggesting that these three miRNAs may have the most important regulatory functions. Functional categorization by microarray-based GO analysis To determine the physiological processes involving the target genes, we performed GO analysis in this study. Twelve significant GOs (P value < 0.05, FDR < 0.05) were identified, including development process, transcription regulator activity, ligand binding, biological regulation, cellular physiological process, etc. (Table 3). These results illustrated that the genes targeted by the differentially expressed miRNAs were involved in various biological processes. Significantly enriched KEGG pathways A separate functional analysis by KEGG pathway revealed that these target genes were highly enriched in 6 signaling pathways (P < 0.05, FDR < 0.05) (Fig. 4). A total of 36 putative genes were found to be enriched in the pathways of multiple cancers, including in colorectal cancer, pancreatic cancer, glioma, thyroid cancer, acute and chronic myeloid leukemia, basal cell carcinoma and melanoma, etc. (Fig. 5). Additionally, 17 out of the 36 target genes were regulated by hsa-miR-410, suggesting a vital role of this miRNA in cancer pathways related to the pathogenesis of SLE. Discussion Previous discoveries have indicated that the aberrant expression of miRNAs is associated with the pathogenesis of SLE (Shen et al., 2012). Therefore, to profile miRNA expression in PBMCs taken from patients with SLE, miRNA microarray analysis was performed in the present study. By comparing miRNA expression patterns in PBMCs from patients with SLE versus healthy controls,
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Fig. 2. Quantitative real-time PCR validation for differentially expressed miRNAs. All the data are expressed as mean ± standard deviation (SD) (n = 3/group). SLE, systemic lupus erythematosus. P < 0.05 is considered significant.
Fig. 3. Cluster analysis of miRNA microarray data. Each row represents a single miRNA and each column represents a peripheral blood mononuclear cell (PBMC) sample. Pseudocolors indicate differential expression: red represents expression level above mean expression of a miRNA across all samples; green represents expression level below mean expression; black represents mean expression. Distance metric, Pearson centered; linkage rule, average. SLE, systemic lupus erythematosus. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
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Fig. 4. Pathway analysis based on the potential target genes. Significant pathways targeted by the down-regulated miRNAs (P < 0.05, FDR < 0.05). Lg P is the negative logarithm of P value, and a bigger Lg P value indicates a smaller P value. MAPK, mitogen-activated protein kinase; FDR, false discovery rate.
29 differentially expressed miRNAs were identified. All of these miRNAs were decreased in SLE patients. However, based on our results, no significant up-regulated miRNAs were found in PBMCs obtained from SLE patients. To explore cell-intrinsic abnormalities, many comparative microarray studies have been conducted to identify the miRNAs of differentially expression in the PBMCs (Hai-yan et al., 2011; Stagakis et al., 2011) or purified leukocyte subsets (Zhao et al., 2010, 2011) among patients with SLE, patients with other autoimmune diseases and healthy individuals. A deregulation of miRNAs involved in the pathogenesis of SLE has been
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observed (Miao et al., 2013). Nonetheless, data from these earlier researches and our present study were poorly overlapped. The discrepancy may be the different genetic background and clinical characteristics of experimental subjects and the different laboratory techniques. Moreover, the number of SLE patients in our study was relatively small, and therefore further research conducted in a larger population is needed to validate our present results. Although, as demonstrated in several prior studies (Luo et al., 2011; Wang et al., 2012), miR-155 and miR-146a participate in the SLE pathogenesis, our data showed no significant expression alteration of these two miRNAs. One explanation for the discrepant results may be the intrinsic variability of the SLE pathology. Despite these inconsistencies, our results confirmed a previous reported research from Lashine et al. (2011) by showing that miR-181-a-23p was significantly decreased in PMBCs isolated from SLE patients. Therefore, we hypothesize that miR-181-a-2-3p is involved in the pathogenesis of SLE, and its function is expected to be verified by future research. A total of 2083 genes were found to be regulated by 11 out of the 29 differentially expressed miRNAs. GO analysis was then utilized to examine the potential molecular functions and biological processes of these target genes. These genes were observed to regulate a wide range of biological processes, and their molecular attributes were mainly annotated as development processes, transcription regulator activity, ligand binding, etc. Such findings suggested that these biological processes may contribute to the pathogenesis of SLE.
Fig. 5. Signal pathways in various cancer types. Genes in red are the ones targeted by differentially expressed miRNAs, whereas genes in purple are not. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
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Since the GOs may overlap, the KEGG pathway analysis was performed to integrate individual components into a unified pathway (Kanehisa et al., 2006). A total of 6 significant dysregulated signaling pathways were observed in SLE. Importantly, our data showed that 36 genes targeted by the down-regulated miRNAs were enriched in pathways of multiple cancers, including Wnt and MAPK signaling pathways. Morphologic changes that occur within the glomerulus during the development of lupus nephritis have been shown to be mediated by the Wnt pathway (Tveita and Rekvig, 2011). In addition, abnormal activation of p38 MAPK has been postulated to contribute to the inflammation of SLE, resulting in progressive tissue and organ damage to develop lupus nephritis and autoimmune hepatitis (Jin et al., 2011). The above studies have revealed that disorders of the above two cell signal transduction pathways contribute to the initiation and progression of systemic and endorgan disease manifestations in SLE. Intriguingly, 17 out of the 36 predicted genes were found as the targets for has-mir-410. This miRNA has been reported to be a prognostic marker in neuroblastoma (Gattolliat et al., 2011) and function as a tumor suppressor in human gliomas (Chen et al., 2012). However, as far as we are aware, it is the first time to show its involvement in the deregulated signaling pathways related to SLE. Further experiments are being conducted by our group to explore the precise function of has-mir-410 and to unravel its regulatory mechanisms in SLE. In conclusion, we identified 29 miRNAs differentially expressed in SLE patients, whose expression profiles may provide a basis for developing novel prognostic biomarkers of SLE. Functional bioinformatic analyses demonstrated that target genes regulated by these miRNAs were involved in various biological processes and signaling pathways, though the exact regulatory mechanisms need to be fully studied.
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