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DNA Research Advance Access originally published online on February 23, 2006
DNA Research 2005 12(6):429-439; doi:10.1093/dnares/dsi020
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© The Author 2006. Kazusa DNA Research Institute
The online version of this article has been published under an open access model. Users are entitled to use, reproduce, disseminate, or display the open access version of this article for non-commercial purposes provided that: the original authorship is properly and fully attributed; the Journal and Oxford University Press are attributed as the original place of publication with the correct citation details given; if an article is subsequently reproduced or disseminated not in its entirety but only in part or as a derivative work this must be clearly indicated. For commercial re-use, please contact journals.permissions@oxfordjournals.org

Isolation and Expression Profiling of Genes Upregulated in the Peripheral Blood Cells of Systemic Lupus Erythematosus Patients

Taeko Ishii1,3, Hiroaki Onda4,5, Akie Tanigawa4, Shiro Ohshima1,6,8, Hiroshi Fujiwara11, Toru Mima6, Yoshinori Katada7, Hitoshi Deguchi10, Masaki Suemura11, Tadao Miyake12, Kunio Miyatake9, Ichiro Kawase1, Hanjun Zhao4, Yoshiaki Tomiyama2, Yukihiko Saeki8 and Hiroshi Nojima4,5,*

1Department of Molecular Medicine, Graduate School of Medicine, Osaka University Suita, Japan
2Department of Hematology and Oncology, Graduate School of Medicine, Osaka University Suita, Japan
3Division of Allergy, Osaka Prefectural Medical Center for Respiratory and Allergic Diseases Habikino, Japan
4Innovation Plaza Osaka Izumi, Japan
5Department of Molecular Genetics, Research Institute for Microbial Diseases, Osaka University Suita, Japan
6Department of Rheumatology Kawachinagano, Japan
7Department of Allergology Kawachinagano, Japan
8Department of Clinical Research Kawachinagano, Japan
9NHO Osaka-Minami Medical Center Kawachinagano, Japan
10Department for Immunologic Diseases, Kinki-Central Hospital Itami, Japan
11Department of Internal Medicine, Nissay Hospital Osaka, Japan
12Department of Rheumatology, Osaka General Medical Center Osaka, Japan

Received 1 September 2005; revised 25 October 2005


   Abstract
Top
 Abstract
1. Introduction
 2. Materials and Methods
 3. Results
 4. Discussion
 Supplementary material
 Acknowledgements
 References
 
We have identified the genes whose expressions are augmented in the blood cells of the patients with systemic lupus erythematosus (SLE) using the ‘stepwise subtraction’ technique along with microarray analysis. The expression levels of these genes were assessed by quantitative real-time reverse transcription polymerase chain reaction (RT–PCR) in 31 SLE patients and 30 healthy controls. We found that the transcription levels of following eight genes were significantly increased in SLE patients; interferon (IFN)-{alpha}-inducible protein 27 (IFI27), IFN-{alpha}-inducible protein IFI-15K (G1P2), IFN stimulated gene 20 kDa (ISG20), epithelial stromal interaction 1 (EPSTI1), defensin-{alpha} (DEFA3), amphiregulin (AREG) and two genes of unknown function (BLAST accession nos AL050290 and AY358224 = SLED1). In comparison with idiopathic thrombocytopenic purpura (ITP), an organ-specific autoimmune disease, IFI27, G1P2 and SLED1 were preferentially upregulated in SLE. In contrast, AREG and AL050290 were more highly expressed in ITP than in SLE. We correlated changes in gene expression and clinical/laboratory features of SLE and found that expression of ISG20, EPSTI1 and SLED1 are significantly correlated with lymphocyte counts. Genes linked to IFN are well known to influence SLE, but several other novel genes unrelated to IFN signaling we report here would be useful to understand the pathophysiology of SLE.

Key words: stepwise subtraction; microarray; SLE; ITP; interferon; G0S2; amphiregulin


   1. Introduction
Top
 Abstract
 1. Introduction
2. Materials and Methods
 3. Results
 4. Discussion
 Supplementary material
 Acknowledgements
 References
 
Systemic lupus erythematosus (SLE) is a systemic inflammatory autoimmune disease, characterized by production of multiple diverse autoantibodies against several self-antigens and resultant injury to various organ systems, including skin, joints, kidney and central nervous system. The pathogenesis of SLE is correlated with both genetic predispositions and environmental influences.1Go The contribution of these two factors may differ between individuals, but the resulting malfunctions in the immune system and the production of autoantibodies plays a pivotal role in the pathogenesis of SLE. Previous studies have revealed that symptoms resembling SLE appear in a variety of immunological disorders,1Go–3Go but the mechanisms of SLE pathogenesis are not known, and the cause of the diversity of symptoms is unclear.

Recent reports using cDNA/oligonucleotide array analysis on gene expression profiles in peripheral blood mononuclear cells (PBMC) from SLE patients have identified candidate genes responsible for SLE pathophysiology.4Go–7Go Several interferon (IFN) related genes are highly overexpressed in the peripheral blood and kidney glomeruli of SLE patients, supporting a central role for IFN in SLE.8Go,9Go Activation of the IFN-{alpha} pathway defines a subgroup of SLE patients whose condition is characterized by increased disease severity.10Go In some SLE patients, activated T cells seem to resist anergy and apoptosis by markedly upregulating and sustaining cyclooxygenase-2 expression.11Go However, the pathological significance of these changes in gene expression remains controversial and whether the changes are specific to SLE is open to question.12Go,13Go

We have developed a novel variation of the subtractive hybridization technique called stepwise subtraction for comprehensive gene discovery, wherein the subtraction process is systematically repeated in a stepwise manner to isolate essentially all of the genes whose expression is specifically upregulated relative to a control population.14Go This technique has proven useful in the discovery of genes specifically expressed during cancer metastasis, meiosis and spermatogenesis.14Go,16Go This technique complements cDNA microarray analysis because it can isolate novel genes that were not identified by microarray screening.17Go Here, we applied the stepwise subtraction method together with microarray analysis to identify a set of genes differentially expressed in SLE, including several candidates which have not been previously associated with SLE. The expression of these genes was confirmed and quantified with real-time reverse transcription polymerase chain reaction RT–PCR and the expression levels were compared to indicators of SLE pathology. In addition, we investigated patients with idiopathic thrombocytopenic purpura (ITP), which is an organ-specific autoimmune disease. We compared the levels of gene expression in SLE patients with those in ITP patients and identified changes in gene expression that are specific to each condition.


   2. Materials and Methods
Top
 Abstract
 1. Introduction
 2. Materials and Methods
3. Results
 4. Discussion
 Supplementary material
 Acknowledgements
 References
 
2.1 Human subjects: patients and healthy controls
Blood was obtained from 133 SLE patients (8 men and 125 women) and eight healthy controls (4 men and 4 women) (Supplementary Table 1, set A), for stepwise subtractive hybridization and microarray analysis. For real-time RT–PCR, 31 SLE patients (1 man and 30 women) were randomly selected from set A. Independently, blood samples from 25 ITP patients (8 men and 17 women), and 30 healthy controls (all women) were analyzed (Supplementary Table 1B, set B). Written informed consent was obtained from all participating subjects. This study was performed according to the guidelines of Osaka University Graduate School of Medicine, which abides by the Helsinki Declaration on ethical principles for medical research involving human subjects. All SLE patients fulfilled the American College of Rheumatology classification criteria for SLE.18Go ITP patients were diagnosed based on idiopathic thrombocytopenia (platelets <100 x 109/l) and megakaryocytic hyperplasia or normoplasia in the bone marrow, when other causes had been excluded. Clinical manifestations and laboratory features of the SLE patients were also examined, including the SLE disease activity index (SLEDAI) score,19Go counts of peripheral lymphocytes, dosages of oral glucocorticoid or immunosuppressants, ages of the patients and length of time from disease onset.

2.2 RNA isolation and multiple tissue cDNA panels
Heparinized venous blood (10 ml) was mixed with an equal volume of 2% dextran/saline solution and incubated at room temperature for 30 min to precipitate red blood cells. PBMC in the supernatant were purified by density-gradient centrifugation on Percoll (density = 1.064 g/ml). Total RNA was extracted from the PMBC pellets by adding guanidine-thiocyanate solution and the samples were used for cDNA library preparation and subtractive hybridization or acid guanidinium-phenol-chloroform extraction for real-time RT–PCR.20Go To analyze the expression pattern of some SLE-upregulated genes, PCR was performed on multiple tissue cDNA panels (Clontech Laboratories, Palo Alto, CA, USA) using the coding sense and antisense primers for 25–40 cycles (see Figure 5) at 95°C for 30 s, 55°C for 30 s and 72°C for 1 min. ExTaq DNA polymerase was purchased from TaKaRa Co. Ltd (Otsu, Japan).

2.3 Preparation of cDNA library and stepwise subtraction
An SLE cDNA library was constructed from PBMC of 133 SLE patients (Supplementary Table 1, Set A) using the linker-primer method with a pAP3neo vector, as described previously.20Go We also prepared mRNA from PBMC of healthy controls (Supplementary Table 1, Set A) and biotinylated the mRNA with photobiotin to perform cDNA subtractions.20Go To analyze the quality of the first-stage subtracted cDNA library, cDNA inserts from 480 randomly selected cDNA clones were restriction digested with EcoRI and NotI, and the fragments isolated from 1% agarose gels. The fragments were then 32P-labeled to use as probes for northern analysis to identify SLE specific clones (see Figure 1B). The stepwise subtraction of this cDNA library was performed as described previously.14Go We isolated almost all of the SLE specific clones included in the original cDNA library from the first and second subtraction, since only a few independent cDNA clones were detected in the third subtraction. The DNA sequences of the SLE specific clones were determined using an automated DNA sequencer (ABI PRISM 377; Applied Biosystems, Foster City, CA, USA).


Figure 1
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  		Figure 1. Northern blots of individual AILE cDNA clones to compare the expression levels of the genes in SLE patients and normal controls (see Supplementary Table 1, Set A). A northern blot with GAPDH probe is shown as a loading control.

 
2.4 DNA microarray analysis
The quality of the RNA samples was examined using the RNA 6000 Nano LabChip Kit (p/n 5065-4476) on the Agilent 2100 Bioanalyzer (G2940BA; Agilent Technologies, Inc., Palo Alto, CA, USA). Total RNA (500 ng) from PBMC of 133 SLE patients or 8 healthy volunteers was reverse-transcribed using oligo-dT primers containing the T7 RNA polymerase promoter sequence, and the cDNAs were then subjected to in vitro transcription using T7 RNA polymerase to label cDNAs with Cy3 or Cy5 (CyDye, Amersham Pharmacia Biotech, Piscataway, NJ, USA). Cy-labeled cRNA from SLE patients (1 µg) was mixed with the same amount of reverse color Cy-labeled product from an equal amount of pooled cRNA from healthy volunteers. Labeled cRNAs were fragmented to an average size of approximately 50–100 nt by heating at 60°C in the presence of 10 mM ZnCl2, and the samples were then added to a hybridization buffer containing 1 M NaCl, 0.5% sodium sarcosine, 50 mM MES (pH 6.5) and formamide to a final concentration of 30%, in a final volume 3 ml. Hybridizations with the Agilent's whole human genome microarray (Hu44K) were conducted at 40°C. Sequences for microarrays were selected from RefSeq (a collection of non-redundant mRNA sequences; http://www.ncbi.nlm.nih.gov/gquery.fcgi?term=RefSeq) and from expressed sequence tag (EST) contigs (http://www.phrap.org/est_assembly/human/gene_number_methods.html). Each mRNA or EST contig was represented on the Hu44K microarray by a single 60mer oligonucleotide chosen by the oligonucleotide probe design program. After hybridization, slides were washed and scanned using an Agilent confocal laser scanner (G2565BA). Fluorescence intensities on scanned images were quantified, corrected for background noise and normalized. Fluorophore reversal (dye swap) duplicates were used in two-color DNA microarray experiments.

2.5 Quantitative real-time PCR
Relative quantitation with real-time RT–PCR was performed using an ABI PRISM 7900 (PE Applied Biosystems, Foster City, CA, USA) and the Assay-on-Demand TaqMan probe and relevant primers, according to the manufacturer's instructions. Total RNA (500 ng) obtained by acid guanidinium-phenol-chloroform extraction was reverse-transcribed using the High Capacity cDNA Archive Kit (ABI). The cDNA was used as a template for PCR in a 50 µl reaction using 2x Master Mix according to the manufacturer's instructions (TaKaRa). PCR consisted of initial denaturation (95°C, 10 min), then 40 cycles of denaturation (95°C, 15 s) and annealing/extension (60°C, 1 min). Each sample was assayed in quadruplicate and the median threshold cycle (CT) values were used to calculate the fold change (FC) between patient and control samples. Standard deviation and standard error were also calculated. A standard curve from the amplification data for each primer was generated using a dilution series of total RNA from PBMC as templates, FC values were normalized to GAPDH levels using the standard curve method according to the manufacturer's protocol.

2.6 Purification of T cells and B cells, and their characteristics
PBMC from three SLE patients were isolated by density-gradient centrifugation with Ficoll-Paque (Pharmacia Biotech, Uppsala, Sweden). T or B cells were purified by magnetic cell sorting (MACS) using a StemSepTM Kit (Stem Cell Technologies Inc., British Columbia, Canada). We found that more than 95 or 93% of T or B cells purified by MACS were CD3 positive or CD19 positive, respectively. Purified CD3/CD19 positive populations were analyzed by flow cytometry (FACScan Cytometer, Becton Dickinson Immunocytometry System, Mountain View, CA, USA).

2.7 Statistical analysis
Significant differences were determined using the Mann–Whitney U-test or Spearman's rank correlation. Data are presented as the mean ± standard deviation (SD). P < 0.05 was considered to be statistically significant.


   3. Results
Top
 Abstract
 1. Introduction
 2. Materials and Methods
 3. Results
4. Discussion
 Supplementary material
 Acknowledgements
 References
 
3.1 Identification of SLE specific genes by stepwise subtraction and DNA microarray analysis
To identify the putative SLE specific genes that are upregulated in PBMC of SLE patients compared to healthy volunteers, we applied stepwise subtractive hybridization.14Go Briefly, we prepared a pooled cDNA library using mRNA from 133 SLE patients (Supplementary Table 1, Set A) using the linker-primer method with a pAP3neo vector. Subtractive hybridization used biotinylated mRNA from 8 healthy volunteers (4 males and 4 females; Set A), generating the first subtracted cDNA library, as described previously.20Go The SLE-upregulated genes were identified by northern blot analysis using DNA inserts from randomly selected cDNA clones of the subtracted cDNA library. We performed the stepwise subtraction three times. Since we did not obtain any new SLE-upregulated genes in the third subtracted cDNA library (data not shown), the analysis was terminated at this point. We identified 25 SLE-upregulated genes by northern blot analysis (Figure 1) and named them AILE genes (augmented expression in SLE). As listed in Table 1. AILE1 (G0S2) is a lymphocyte G0/G1 switch gene whose expression may be required to commit cells to enter the G1 phase of the cell cycle.21Go AILE4 (IFI-15K) and AILE11 (ISG20) are IFN-inducible genes. AILE8, AILE9, AILE14 and AILE18 are human leukocyte antigen (HLA) related genes. AILE6, AILE24 and AILE25 are erythroblast related genes, whereas AILE19 and AILE20 are thymosin related genes.


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  		Table 1. List of AILE genes identified by stepwise subtraction

 
We also performed DNA microarray analysis using the Agilent Hu44K array with the same samples of pooled RNA obtained from SLE patients and healthy volunteers. The list of the genes that were upregulated 7.8-fold or more in SLE patients relative to controls (top 50) is shown in Table 2. Five IFN-{alpha}-inducible genes (IFIG) (AK095039, IFIT1, IFIT4, IFI44 and G1P2) were identified as SLE-upregulated genes. Notably, G0S2 (AILE1), G1P2 (AILE4), JunB (AILE21) and PRG1 were identified as SLE-upregulated genes by both stepwise subtraction and microarray analysis. AY358224, which showed the most significant difference between SLE patients and normal volunteers in the microarray screening, encodes an uncharacterized protein. Because AY358224 showed SLE-dependent upregulation we named it SLED1 (see below).


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  		Table 2. List of SLE-upregulated genes identified by DNA microarray analysis

 
3.2 Expression profiles of SLE-upregulated genes in individual SLE patients
To determine whether upregulation of each of these genes is widespread in SLE or occurs in only a few patients, we performed quantitative real-time RT–PCR using individually prepared RNA samples from the SLE patients and healthy controls. We selected 31 SLE patients from the same hospital (Supplementary Table 1, Set B) and 30 young females (age 18–20) as controls, in addition to the original controls (Set A). We tested 16 AILE genes (Table 1) and 6 SLE-upregulated genes (Table 2) for SLE specific upregulation by semi-quantitative PCR. We did not test the genes that encoded ribosomal proteins, hemoglobin gamma, ferritin, MLA-F or proteoglycan 1, because they are not considered to be causative for SLE. As shown in Supplementary Figure 1, the standard deviation for quadruplicate measurements from the same individual was small, and this reproducibility indicates that the values provide a reliable measure of gene expression levels.

As shown in Figure 2, the IFI27, epithelial-stromal interaction 1 (EPSTI1), G1P2 (AILE4), ISG20 (AILE11), SLED1 and DEFA3 (AILE7) genes showed enhanced expression in many of the SLE patients. IFI27, G1P2 and ISG20 are IFIG; which is consistent with previous work showing that IFN-{alpha} is the predominant stimulus for FIG expression in lupus.9Go Moreover, we found that expression of defensin-3{alpha} (DEFA33), which is a major product of immature granulocytes and has antimicrobial activity, is enhanced in the PBMC of many SLE patients. EPSTI1 is one of the upregulated genes in invasive breast carcinomas,22Go but this is the first report correlating upregulation of EPSTI1 with SLE.


Figure 2
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  		Figure 2. Expression levels of SLE-upregulated genes. (A) The expression levels of the genes that are more highly upregulated in SLE than ITP. This group includes IFI27, IFN-{alpha}-inducible protein G1P2 (AILE4) and SLED1 (AY358224). Note the scale breaks for IFI27 SLE samples. (B) The expression levels of the genes that are similarly upregulated in both SLE and ITP. This group includes EPSTI1, DEFA3 and ISG20. (C) The expression levels of the genes that are more highly upregulated in ITP than SLE. This group includes AILE3 and AREG. Filled circles denote the mean value of samples analyzed in quadruplicate from each individual. The open circle and bar signify the average + SD for each group, i.e. control, SLE or ITP. *P < 0.05; control versus SLE, **P < 0.01; control versus SLE, ***P < 0.001; control versus SLE, {dagger}P < 0.05; SLE versus ITP, {dagger}{dagger}P < 0.01; SLE versus ITP, {dagger}{dagger}{dagger}P < 0.001; SLE versus ITP.

 
Expression of AILE1 (G0S2) was enhanced in many SLE patients compared to the original 8 healthy controls (Set A), as shown in Supplementary Figure 2. These data are consistent with the northern blot analysis showing a dramatic upregulation of AILE1 in SLE patients. However, when expression levels were compared to those of eight Set B controls, expression levels were similar to SLE patients. When we performed another series of real time RT–PCR assays with 30 Set B controls, they showed slightly enhanced expression relative to SLE patients. Thus, changes in G0S2 expression do not appear to be correlated to SLE. Other tested genes did not show any significant increase as compared to healthy controls (Supplementary Figure 3).

3.3. Comparison with ITP
We next compared the expression levels of these genes in each SLE and ITP patient, and found three trends. Type A genes, comprised of IFI27, G1P2 and SLED1, are upregulated in SLE relative to ITP (Figure 2A). These genes can be used as SLE specific gene markers to distinguish SLE from ITP. Type B genes, which include EPSTI1, DEFA3 and ISG20, showed similar levels of expression in both SLE and ITP (Figure 2B). These genes can be used as gene markers to identify both SLE and ITP. Type C genes, consisting of AILE3 and amphiregulin (AREG), are more conspicuously upregulated in ITP than SLE (Figure 2C). These genes can be used as ITP specific gene markers to distinguish ITP from SLE.

3.4. Correlation analysis
The correlations among expression levels of these genes showed that the genes linked to IFN (IFI27, G1P2 and ISG20) displayed strong positive correlations in upregulation of gene expression (Figure 3A). EPSTI1 expression also showed a strong positive correlation with G1P2 and ISG20 expression, suggesting that EPSTI1 is somehow correlated with IFN relevant events. SLED1 expression displayed a weak but significant positive correlation with ISG20 expression (Figure 3B).


Figure 3
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  		Figure 3. Positive correlations among expression of SLE upregulated genes. (A) Expression of IFI27 showed a strong positive correlation with G1P2 (r = 0.661) and a weak correlation with ISG20 (r = 0.377) expression. In addition, EPSTI1 expression showed a strong positive correlation with that of G1P2 and ISG20 (r = 0.85 and 0.681, respectively). (B) SLED1 expression displayed a weak positive correlation with ISG20 expression (r = 0.495). All correlations were significant (P < 0.05).

 
Next, we examined correlations of these genes with clinical manifestations, including the SLE disease activity index (SLEDAI), numbers of fulfilled classification criteria for SLE (NFCCS), presence or absence of lupus nephritis, counts of peripheral lymphocytes, dosages of oral steroid, ages of the patients and length of time since disease onset. We found significant negative correlations between lymphocyte counts and expression levels of ISG20, EPSTI1 and SLED1 (Figure 4A). We also found a reasonably good negative correlation between the NFCCS and the expression level of AREG (Figure 4B). Other clinical symptoms showed no significant correlations.


Figure 4
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  		Figure 4. Correlation between the levels of gene expression and clinical data. (A) Significant negative correlations were observed between lymphocyte (Ly) counts and the levels of ISG20 (r = –0.358), EPSTI1 (r = –0.39) and SLED1 (r = –0.396). (B) A negative correlation was also detected between numbers of SLE disease criteria and the level of AREG (r = –0.366). All correlations were significant (P < 0.05).

 
3.5. Expression pattern in PBMC
To analyze the expression pattern in human blood cell fractions of SLE-upregulated genes whose expressions are enhanced in many of the SLE patients (Figure 2A and B), we performed RT–PCR on multiple tissue cDNA panels (MTC from Clontech) and blood cell RNA of SLE patients (Figure 5). RT–PCR identified IFI27 and G1P2 genes as being expressed ubiquitously in most of the MTC blood cell fractions (Figure 5, lanes 1–9) and in SLE (Figure 5, lanes 13–15). The expression of SLED1 is weak and localized to specific cell subsets, namely, monocytes (lane 4) and T and B cells (lanes 2–4). This result is consistent with the observation of SLED1 expression in the whole blood fraction (total blood leukocytes) of an SLE patient (lane 13). EPSTI1 was expressed in most cell types, except for activated CD4+ T cells (lane 8), and was detected prominently in the total blood leukocyte fraction (lane 13) in SLE patients, suggesting that the dramatically increased expression (5–50-fold) of the EPSTI1 gene (Figure 2B) results from monocytes rather than from B or T cells. ISG20 is expressed in T and B cells but not in monocytes (lane 4), similar to SLE patients (lanes 14 and 15). DEFA3 is expressed in suppressor T cells (lane 2), B cells (lane 5), and more prominently in other blood cells (lane 1), but expression of DEFA3 in T and B cells increased in SLE patients (lanes 13–15). These results indicate that the expression pattern of these genes are not largely altered in SLE patients


Figure 5
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  		Figure 5. RT–PCR amplification of IFI27, EPSTI1, G1P2, ISG20, SLED1, DEFA3, AILE3 and AREG. GAPDH was amplified as a loading control. The multiple tissue cDNA panel for human blood fractions (MTC, Clontech)(lanes 1–12) and SLE patients' blood fractions (lanes 13–15) were examined. 30 cycles of amplification were used for PCR, except as noted at the right of the panels: (#) 40 cycles, (*) 35 cycles or ($) 25 cycles. Lane 1, mononuclear cells (B, T cells and monocytes). Lane 2, resting CD8+ cells (T-suppressor/cytotoxic). Lane 3, resting CD4+ cells (T-helper/inducer). Lane 4, resting CD14+ cells (monocytes). Lane 5, resting CD19+ cells (B cells). Lane 6, activated mononuclear cells. Lane 7, activated CD4+ cells. Lane 8, activated CD8+ cells. Lane 9, activated CD19+ cells. Lane 10, human placenta control cDNA. Lane 11, plasmid harboring tested cDNA insert (size control). Lane 12, vector alone (negative control). Lane 13, whole blood cells of SLE patients. Lane 14, B cell fraction of SLE patients. Lane 15, T cell fraction of SLE patients. Lane 16, plasmid carrying relevant cDNA (positive control). Lane 17, vector alone (negative control).

 

   4. Discussion
Top
 Abstract
 1. Introduction
 2. Materials and Methods
 3. Results
 4. Discussion
Supplementary material
 Acknowledgements
 References
 
In the present study, we comprehensively isolated and analyzed the expression levels of genes that are upregulated in the PBMC of SLE patients, using stepwise subtractive hybridization in combination with oligonucleotide microarray analysis. This study identified many novel SLE-upregulated genes, in addition to IFN responsive genes, such as IFI27, G1P2 and ISG20, which had been previously identified as upregulated in SLE using microarray analysis.4Go–6Go The importance of the type I IFN system in the etiology of SLE has garnered much attention.8Go,23Go The serum levels of IFN-{alpha}, a major effector in response to viral infection, is correlated with SLE disease activity, and IFN-{alpha} therapy sometimes produces autoimmune side effects, which resemble genuine SLE, including production of autoantibodies.24Go However, we did not isolate the transcript for IFN itself as an SLE-upregulated gene. The major IFN-producing cells, i.e. natural IFN-{alpha} producing cells (NIPC), are continuously activated in SLE, producing IFN.25Go The activator for NIPC remains to be elucidated but candidates are autoantibodies, unmethylated CpG motifs, or the presence of necrotic or apoptotic cells. NIPC, which are reported to resemble immature dendritic cells in phenotype,26Go are a very minor component of PBMC. This may be why IFN mRNA was not detected.

We identified DEFA3, a major product of immature granulocytes, as an SLE-upregulated gene, which supports the previous data.5Go Here, we found that DEFA3 was also upregulated in ITP. DEFA3 was also upregulated in PBMC of rheumatoid arthritis patients.27Go Thus, DEFA3 upregulation might be a general feature of autoimmune diseases. EPSTI1 expression is enhanced in breast cancer upon direct interaction between tumor cells and stromal cells in the tumor environment assay.22Go EPSTI1 is also upregulated in small intestine, spleen, salivary gland, testes and placenta, though its function remains to be elucidated.

AREG is a heparin-binding, heparin-inhibited member of the epidermal growth factor family and an autocrine growth factor for human keratinocytes. AREG plays an important role in psoriatic hyperplasia, and inhibition of AREG activity could be an efficacious therapeutic strategy for psoriasis.28Go Our results suggest that inhibition of AREG activity may also be a therapeutic strategy for SLE or ITP. AILE3 encodes an uncharacterized protein that belongs to the acetyltransferase family. SLED1 encodes a small protein originally identified by the secreted protein discovery initiative (SPDI) (Genentech, Inc., CA, USA) as a secreted or transmembrane protein. Characterization of these proteins remains for future studies.

We classified the SLE upregulated genes by comparison to ITP and identified three groups. The genes which are more highly upregulated in SLE than ITP (IFI27, G1P2 and SLED1), might influence systemic inflammation. Among them, IFI27 is most significantly upregulated. Genes which displayed the same levels of transcriptional upregulation in SLE and ITP (EPSTI1, ISG20 and DEFA3), might be genes that are generally upregulated in autoimmune diseases. Genes showing more enhanced expression in ITP than SLE (AILE3 and AREG), might be correlated with the organ-specific destruction of thrombocytes.

Taken together, we identified several novel SLE-upregulated genes whose expression profiling may provide a useful measure of the pathophysiology of SLE. Using the combination of stepwise subtractive hybridization and microarray analysis, the genes we detected should be very specifically correlated with SLE. Genes linked to IFN are well known to influence SLE, but here we isolated several other novel genes unrelated to IFN signaling. Further investigation is needed to clarify their roles in the pathogenesis of SLE.


   Supplementary material
Top
 Abstract
 1. Introduction
 2. Materials and Methods
 3. Results
 4. Discussion
 Supplementary material
Acknowledgements
 References
 
Supplementary material is available online at www.dnaresearch.oxfordjournals.org.


   Acknowledgements
Top
 Abstract
 1. Introduction
 2. Materials and Methods
 3. Results
 4. Discussion
 Supplementary material
 Acknowledgements
References
 
The authors thank the patients and healthy volunteers who participated in this study. The authors also thank Ms Tomoko Motoyama for technical assistance, Dr Katsuhiko Ishihara for technical advice and Dr Patrick Hughes for critically reading the manuscript. The authors also thank Dr Daisuke Okuzaki of DNA-chip Development Center for Infectious Diseases (RIMD, Osaka University) for technical advice. This work was supported by Innovation Plaza Osaka of Japan Science and Technology Agency (JST), and grants-in-aid for Scientific Research on Priority Areas, Scientific Research (S), Exploratory Research and Science and Technology Incubation Program in Advanced Regions, from the Ministry of Education, Science, Sports and Culture.


   Footnotes
 
*To whom correspondence should be addressed. Tel. +81-6-6875-3980, Fax. +81-6-6875-5192, E-mail: snj-0212{at}biken.osaka-u.ac.jp

Communicated by Mitsuo Oshimura


   References
Top
 Abstract
 1. Introduction
 2. Materials and Methods
 3. Results
 4. Discussion
 Supplementary material
 Acknowledgements
 References
 

  1. Rekvig, O.P. and Nossent, J.C. 2003, Anti-double stranded DNA antibodies, nucleosomes, and systemic lupus erythematosus: a time for new paradigms?, Arthritis Rheum., 48, 300–312.[CrossRef][Web of Science][Medline]
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