• We are sorry, but NCBI web applications do not support your browser and may not function properly. More information
Logo of annrheumdAnnals of the Rheumatic DiseasesCurrent TOCInstructions for authors
Ann Rheum Dis. Jul 2007; 66(7): 886–892.
Published online Feb 26, 2007. doi:  10.1136/ard.2006.063123
PMCID: PMC1955122

Intrarenal cytokine gene expression in lupus nephritis

Abstract

Background

Lupus nephritis is characterised by intrarenal inflammation and lymphocyte activation.

Aim

To examine the profile of cytokine gene expression in glomerulus and tubulointerstitium in patients with lupus nephritis.

Methods

36 consecutive patients with systemic lupus erythematosus having active renal disease were recruited, and they were required to undergo kidney biopsy. Glomerular and tubulointestitial cytokine expression of interleukin (IL)2, 4, 10, 12, 18, interferon γ (IFN)γ, T‐bet (the Th1 transcription factor), GATA‐3 (the Th2 transcription factor), transforming growth factorβ and monocyte chemoattractant protein (MCP)1 were studied by laser microdissection of the renal biopsy specimen, followed by real‐time quantitative PCR.

Results

There were 13 patients with World Health Organization class III nephritis, 14 patients with class IV nephritis and 9 patients with class V nephritis. There was a significant correlation between serum C3, C4 and anti‐double strand DNA antibody level with glomerular expression of T‐bet, IFNγ and IL2. There was a significant correlation between histological activity index and glomerular expression of IL12, IL18, IL10 and MCP1. In addition, the degree of glomerular leucocyte infiltration significantly correlated with glomerular expression of IFNγ, IL10, IL12 and IL18. By contrast, histological chronicity index correlated with the tubulointerstitial expression of IL2, MCP1 and GATA‐3.

Conclusions

Intraglomerular expression of certain target genes correlate with the severity of systemic as well as histological activity, whereas the tubulointerstitial expression of other target genes correlate with the degree of chronic kidney scarring. This result may shed light on the immunopathogenesis of lupus nephritis.

Systemic lupus erythematosus (SLE) is an autoimmune disease characterised by aberrant cytokines milieu and multiple organ involvement.1 Extensive studies have focused on cytokine profile in the peripheral blood of patients with SLE . However, reports on cytokine production in patients with SLE have been inconsistent.2,3,4,5 Cytokine assay of peripheral blood suggests that SLE is a Th2 mediated disease at the early stage,2 but the Th1 pathway may become predominant with the progression of disease and development of active nephritis.6

It is, however, important to note that the organ involvement in SLE is highly variable, and study of peripheral blood mononuclear cells may not be representative of the local immunopathogenesis at specific sites. In the case of lupus nephritis, kidney biopsy is the ideal method to study intrarenal immunologic disturbance. Unfortunately, quantification of cytokine gene expression in kidney tissue could not distinguish glomerular origin, the major site of pathological interest, from tubulointerstitial origin of the cytokines;7 immunohistochemical study allows accurate localisation of the site of cytokine production,8,9 but concomitant analysis of a large number of cytokines is not possible.

Laser‐manipulated microdissection has been developed as a method to cut out a single cell or limited tiny region from a specimen under microscopic observation by a laser beam, and subsequent laser pressure catapulting could push up and collect samples that are microdissected using a strong laser.10 The methods to isolate glomeruli from standard histochemical specimens by laser‐manipulated microdissection and laser pressure catapulting, and to quantify messenger RNA (mRNA) expression in the targeted glomeruli using real‐time quantitative PCR (RT‐QPCR) has been established.10 Recently, Peterson et al11 studied the transcriptional profiles of patients with lupus nephritis by laser‐captured microdissection and complementary DNA microarray analysis of glomeruli from clinical biopsy specimens. However, the expression of many cytokine genes was not specifically examined, and gene expression in tubulointerstitium was not considered. In the present study, we examine the profile of cytokine gene expression in glomerulus and tubulointerstitium in patients with lupus nephritis, and explore its relationship with histological morphology, degree of acute activity and chronic damage.

Patients and methods

Patient selection

We recruited 36 consecutive patients with SLE having active renal disease and required kidney biopsy. All patients fulfilled the American College of Rheumatology diagnostic criteria of SLE.12 The uninvolved pole of five kidneys, which were removed for renal cell carcinoma and had no morphological evidence of renal disease, were used as control.

Clinical and histological assessment

The disease activity of SLE was assessed clinically by the Systemic Lupus Erythematosus Disease Activity Index (SLEDAI)13,14 that was scored on the day of kidney biopsy by an independent physician. Baseline serum creatinine, albumin, urea, complement levels (C3 and C4) and anti‐double strand (ds) DNA antibody titre were also measured. Glomerular filtration rate was estimated from a standard prediction equation.15

Kidney biopsy specimen were evaluated according to the World Health Organization (WHO) classification of lupus nephritis.16 The activity index (AI) and chronicity index (CI) of each biopsy specimen were scored by standard methods.17,18 AI is the sum of semiquantitative manual scores (0–3 each) of the following parameters: endocapillary hypercellularity; leucocyte infiltration, subendothelial hyaline deposits; interstitial inflammation, necrosis and cellular crescents.17 Scores of the last two parameters are counted double, making a total AI of 0–24. Evaluation of biopsy specimens was performed by a single pathologist (FM‐ML).

Laser microdissection

Cryosections of 14 μm thickness were prepared on a cryostat (Leica Microsystems, Wetzlar, Germany) using disposable microtome blades (Leica Microsystem) in RNase‐free conditions, and were mounted on glass slides covered with a polyethylene naphthalate membrane (PALM Microlaser Technologies, Bernried, Germany). All polyethylene naphthalate‐covered slides were treated with ultraviolet irradiation and RNase Away (Invitrogen Life Technologies, Carlsbad, California, USA) before use. Immediately after taking the slides out of the cryostat, the sections were fixed in 70% ethanol. After gentle washing in diethylpyrocarbonate‐treated water, sections were lightly stained with haematoxylin, followed by a short rinse in diethylpyrocarbonate‐treated water and dehydrated in increasing ethanol series. Sections were air‐dried at room temperature.

Laser microdissection of the snap‐frozen kidney biopsy specimens was performed using the PALM Microlaser System (PALM Microlaser Technologies), which is equipped with a pulsed high‐quality laser beam, computer‐controlled microscope stage and micromanipulator. Under direct visual control, areas of interest in the histological specimens were selected through the PALM RoboSoftware (PALM Microlaser Technologies) by moving the computer mouse, and microdissected by cutting the contour of the selected areas with the adjusted laser beam. The isolated tissue was then laser‐catapulted into a microcentrifuge cap filled with guanidine thiocyanate containing lysis buffer for the subsequent RNA isolation. Approximately 5–10 glomerulus and 20 randomly selected tubulointerstitial area were isolated from each specimen. The tissue lysate of glomerulus and tubulointerstitium were kept at −80°C until RNA extraction was performed with the RNeasy Micro Kit (Qiagen, Mississauga, Ontario, Canada), following manufacturer's instruction.

Quantification of intrarenal gene expression

The method of total RNA extraction and reverse transcription was described in our previous studies.8,19 As suggested by previous studies,8,19 we quantified the mRNA expression of interleukin (IL) 2, 4, 10, 12, 18, interferon (IFN)γ, T‐bet (the Th1 transcription factor), GATA‐3 (the Th2 transcription factor), transforming growth factor (TGF)β and monocyte chemoattractant protein (MCP) 1 in glomerulus and tubulointerstitium by real‐time quantitative PCR (RT‐QPCR). Taqman primers and probes of each target were purchased from Applied Biosystems (Foster City, California, USA). The RT‐QPCR of IL2, IL4, IL10, IL12, IL18, IFNγ, TGFβ and MCP‐1 was performed by commercial kits (all from Applied Biosystems) following the manufacturer's instruction. The primer and probe sequence of T‐bet and GATA‐3 has been described in our previous study.20 The mRNA expression for each signal was calculated by using the ΔCt procedure according to manufacturer's instruction, with 18S ribosomal RNA (rRNA) used as the housekeeping gene for normalisation among samples. All primers and probes were tested with purified DNA as the template in RT‐QPCR to ensure that they do not amplify genomic DNA. All results were analysed by Sequence Detection Software V.1.7 (Applied Biosystems).

Gene expression of each target was calculated by using the difference‐in‐threshold‐cycle (ΔCt) procedure, according to manufacturer's instruction. For 18S rRNA and each target, the relative efficiency of amplification over various starting template concentrations was determined. Approximately equal efficiencies for other targets with 18S rRNA amplifications were verified by an absolute value of <0.1 for the slope of log input complementary DNA amount versus ΔCt, which was obtained by subtracting the threshold cycle (Ct) value of 18S rRNA from that of the target. Therefore, it was possible to detect 18S rRNA in the same tube with other targets. The relative quantification of using multiplex reaction with a comparative method was determined by the formula 2−(ΔΔCt), where the ΔΔCt was calculated by the subtraction of ΔCt of the calibrator from ΔCt of the sample.21

Quantification of gene expression in urinary sediment

We further studied the relationship between intrarenal and urinary cytokine gene expression. The methods of urinary sediment isolation and mRNA extraction have been described previously.8,19,20 Briefly, the urine specimen was centrifuged at 3000g for 30 min at 4°C. Total RNA was extracted by the RNeasy Mini Kit (Qiagen), following manufacturer's instruction. Cytokine mRNA expressions were quantified by RT‐QPCR using ABI Prism 7700 Sequence Detector System (Applied Biosystems). Taqman primers and probe of T‐bet, GATA‐3, IFNγ and IL4 were purchased from Applied Biosystems. Level of mRNA expression was normalised to 18S rRNA as housekeeping gene (Applied Biosystems). Results were analysed using Sequence Detection Software V.1.9a (Applied Biosystems). As the amount of mRNA was limited, we did not quantify the expression of other cytokines in the urinary sediment.

Statistical analysis

Statistical analysis was performed by SPSS V.10.0 for Windows software. The results are presented as mean (SD) unless otherwise specified. As the data were highly skewed, correlations of intrarenal mRNA expression with the SLEDAI scores and other serological, urinary or histological parameters were determined by Spearman's rank correlation coefficient. Comparison of intrarenal mRNA expression between groups was performed by Kruskal–Wallis test or Mann–Whitney U test as appropriate. A p value of <0.05 was considered as significant. All probabilities were two‐tailed.

Results

We studied 36 patients with SLE . Table 11 shows the baseline demographic and clinical data of these patients. All patients had at least 5 mm of renal cortex and 5 non‐sclerosed glomeruli for histological study. Their histological diagnoses were WHO class III (n = 13), class IV (n = 14) and class V (n = 9) nephritis. The mean (SD) histological activity and chronicity indices were 6.2 (3.9) and 4.2 (3.1), respectively.

Table thumbnail
Table 1 Baseline demographic and clinical data

For the negative controls, the intrarenal expression of all target genes varied from 0 to 3.5‐fold of the median expression (details not shown). Table 22 gives the intrarenal expression of the target genes of the 36 patients. There was a marked upregulation of glomerular expression of T‐bet in patients with lupus nephritis compared to controls. By contrast, there was a marked downregulation of glomerular expression of IL2, IL18, IL4 and MCP‐1. There was a close internal correlation between glomerular expression of IFNγ, IL10, IL12, IL18, TGFβ and MCP‐1, but not with other target genes (details not shown). A similar pattern of internal correlation was observed between the tubulointerstitial expressions of these genes (details not shown).

Table thumbnail
Table 2 Intrarenal mRNA expression of target genes

Table 33 summarises the relationship between intrarenal cytokine gene expression and serological markers of lupus activity. Serum C3 level had significant inverse correlation with the glomerular expression of T‐bet, IFNγ, IL2, MCP‐1, as well as the tubulointerstitial expression of T‐bet, IFNγ and IL2. Similarly, serum C4 level had significant inverse correlation with the glomerular expression of T‐bet, IFNγ, IL2, IL10, IL12, MCP‐1 and tubulointerstitial expression of T‐bet. Serum anti‐ds‐DNA antibody titre significantly correlated with glomerular expression of T‐bet, IFNγ, GATA‐3, IL2, as well as the tubulointerstitial expression of T‐bet and IL2. By contrast, there was no correlation between the overall SLEDAI score and the expression of any target gene in glomerulus or tubulointerstitium. The baseline glomerular filtration rate inversely correlated with the tubulointerstitial expression of IL10 (r = −0.34, p = 0.04) and MCP1 (r = −0.39, p = 0.014), but not with the expression of any target gene in the glomerulus. The degree of proteinuria did not correlate with the expression of any target gene in the glomerulus or tubulointerstitium.

Table thumbnail
Table 3 Relationship between intrarenal gene expression and serological markers of lupus activity

Relationship with gene expression in urinary sediment

The expression of T‐bet in urinary sediment significantly correlated with that in the glomerulus (r = 0.445, p = 0.007) but not with that in tubulointerstitial space (r = 0.188, p = 0.3). Similarly, the expression of IFNγ in urinary sediment correlated significantly with that in glomerulus (r = 0.505, p = 0.001) but not with that in tubulointerstitial space (r = 0.214, p = 0.2). By contrast, the expression of GATA‐3 in urinary sediment correlated significantly with that in glomerulus (r = 0.400, p = 0.016) as well as with that in tubulointerstitial space (r = 0.367, p = 0.028). The expression of IL4 in urinary sediment also had significant correlation with expressions in both the glomerulus (r = 0.398, p = 0.013) and in tubulointerstitial space (r = 0.336, p = 0.039).

Relationship with histology

In essence, there was no significant difference in the glomerular expression of any target gene between WHO classes (details not shown). Although there was a trend of higher glomerular expression of T‐bet in class IV nephritis (6.8 (4.7) vs 4.7 (4.8), p = 0.3), and lower glomerular expression of IL18 (0.065 (0.058) vs 0.106 (0.094), p = 0.1) and MCP‐1 (0.009 (0.010) vs 0.015 (0.015), p = 0.16) in class V nephritis, the difference was not statistically significant after adjusting for multiple comparison.

For patients with WHO class III and IV nephritis, we also compared the glomerular gene expression between patients with segmental and global glomerular lesions. Patients with segmental lesions had significantly higher glomerular expression of IFNγ, IL12, IL18, as well as IL10 (fig 11).). Expression of T‐bet, IL2 and IL4 were similar between the groups. Glomerular expression of GATA‐3 was marginally higher in patients with global lesions, but the result was not statistically significant. In patients with segmental lesions, we found no difference in the glomerular expression of any target gene between those with necrotising and sclerosis lesions (details not shown), although the number of cases was small in each group. Relationship between glomerular pathology and target gene expression in tubulointerstitium was considered physiologically irrelevant and therefore not analysed.

figure ar63123.f1
Figure 1 Comparison of gene expression in the glomerulus between patients with segmental versus global glomerular lesions: (A) interferon γ; (B) interleukin (IL)10; (C) IL12 and (D) IL18. Gene expressions are expressed as ratio to the ...

Relationship with histological activity and chronicity

There was a close correlation between AI and glomerular expression of IL12, IL18, IL10 and MCP‐1 (fig 22).). The AI had significant but only modest correlation with the expression of IFNγ (r = 0.34, p = 0.05) and TGFβ (r = 0.35, p = 0.05). By contrast, AI did not correlate with the expression of T‐bet, GATA‐3, IL2 or IL4. Among the six items of the AI, leucocyte infiltration showed the best correlation with the expression of target genes in glomerulus, including IFNγ (r = 0.45, p = 0.01), IL12 (r = 0.43, p = 0.012), IL18 (r = 0.47, p = 0.006) and IL10 (r = 0.55, p = 0.001; (fig 33).). Glomerular expression did not correlate with the percentage of glomerulosclerosis, degree of cortical scarring or histological CI for all of the target genes (details not shown).

figure ar63123.f2
Figure 2 Relationship between histological activity index and glomerular expression of: (A) interleukin (IL)10; (B) IL12; (C) IL18; and (D) monocyte chemoattractant protein‐1. Gene expressions are depicted as ratio to the control.
figure ar63123.f3
Figure 3 Relationship between leucocyte infiltration and glomerular expression of: (A) interferon γ; (B) interleukin (IL)12; (C) IL18; and (D) IL10. Gene expressions are depicted as ratio to those in control.

By contrast, CI correlated with the tubulointerstitial expression of IL2 (r = 0.33, p = 0.04) and MCP‐1 (r = 0.39, p = 0.015), and inversely with the tubulointerstitial expression of GATA‐3 (r = −0.35, p = 0.034; fig 44).). Similarly, percentage of cortical fibrosis correlated with the tubulointerstitial expression of IL2 (r = 0.38, p = 0.025) and MCP‐1 (r = 0.45, p = 0.008), and inversely with the tubulointerstitial expression of GATA‐3 (r = −0.43, p = 0.015). There was also an insignificant correlation between the tubulointerstitial expression of TGFβ and CI (r = 0.29, p = 0.075) and percentage of cortical fibrosis (r = 0.33, p = 0.059).

figure ar63123.f4
Figure 4 Relationship between histological chronicity index and tubulointerstitial expression of: (A) GATA‐3; (B) interleukin 2; (C) monocyte chemoattractant protein‐1; and (D) transforming growth factor β. Gene expressions ...

Discussion

In this study, we found that the pattern of intraglomerular cytokine gene expression was not related to the WHO class of lupus nephritis. We did, however, identify a marked difference in the pattern of cytokine gene expression between segmental and global lesions, irrespective of the WHO class (fig 22).). Briefly, segmental lesions had significantly higher intraglomerular expression of IFNγ, IL12, IL18 and IL10; and the glomerular expression of these genes correlated with the histological AI. By contrast, chronic renal damage, as represented by histological CI and percentage of cortical fibrosis, was associated with tubulointerstitial expression of IL2, MCP‐1, and possibly of TGFβ, which is consistent with the current understanding of the pathophysiology of chronic kidney diseases.22,23

The glomerular expression of T‐bet, IFNγ and IL2 correlated with serological markers of lupus activity, such as serum complement levels and anti‐ds‐DNA antibody titre. The pattern of glomerular cytokine gene expression suggests a predominantly Th1 pathway of lymphocyte activation, an observation that is consistent with our previous study on urinary cytokine gene expression.20 It is interesting, however, to note that neither the overall SLEDAI score nor the dosage of corticosteroid treatment correlated with the expression of any of the target genes. In other words, the profile of intrarenal gene expression is not a marker of systemic disease activity, but actually the disease process within the kidney.

Although most of the target genes being examined were different, our results share some similarities to that reported by Peterson et al.11 We found that glomerular expressions of IFNγ and other Th1 cytokines were upregulated in patients with segmental but not global lesions, whereas Peterson et al11 found that type I interferon‐inducible transcripts were upregulated in a subset of patients. It is important, however, to note that global and segmental lesions were not separately analysed in the report of Peterson et al.11 Contrary to usual expectations, we could not observe any change in glomerular TGFβ expression, whereas Peterson et al11 actually found that glomerular TGFβ expression was downregulated in patients with lupus nephritis.

We observed that glomerular GATA‐3 expression was fivefold higher than that of the tubulointerstitium (table 22).). Although GATA‐3 is generally regarded as a marker of Th2 lymphocyte differentiation, the interpretation of GATA‐3 expression in the kidney could be problematic because of the critical constitutive expression of this transcription factor in the kidney, at least during embryogenesis.24

In this study, we could not affirm the cellular origin of the detected mRNA. We believe that the expression of most of the target genes came from the infiltration of mononuclear leucocytes, with possible contribution from endothelium and tubular epithelial cells in the tubulointerstitium. In fact, the gene expression level in our study closely correlated with the leucocyte infiltration subscore of the histological AI. Previous immunohistochemical studies also showed that most of the target genes we studied are expressed exclusively or largely by mononuclear inflammatory cells.25,26

In summary, we found that segmental and global proliferative lupus nephritis had distinct patterns of intraglomerular cytokine gene expression. Segmental lupus nephritis is characterised by a predominantly Th1 pattern of cytokine gene expression, the degree of which correlates with the histological AI.

Acknowledgements

This study was supported in part by the CUHK research accounts 6901031 and 7101215.

We thank Ms Lee Wai Ching for her clerical assistance.

Abbreviations

AI - activity index

CI - chronicity index

ds - double strand

IFN - interferon

IL - interleukin

MCP - monocyte chemoattractant protein

mRNA - messenger RNA

RT‐QPCR - real‐time quantitative PCR

rRNA - ribosomal RNA

SLE - systemic lupus erythematosus

SLEDAI - Systemic Lupus Erythematosus Disease Activity Index

WHO - World Health Organization

Footnotes

Competing interests: None.

References

1. Horwitz D A, Jacob C O. The cytokine network in the pathogenesis of systemic lupus erythematosus and possible therapeutic implications. Springer Semin Immunopathol 1994. 16181–200.200. [PubMed]
2. Horwitz D A, Gray J D, Behrendsen S C, Kubin M, Rengaraju M, Ohtsuka K. et al Decreased production of interleukin‐12 and other Th1‐type cytokines in patients with recent‐onset systemic lupus erythematosus. Arthritis Rheum 1998. 41838–844.844. [PubMed]
3. Wong C K, Ho C Y, Li E K, Lam C W. Elevation of proinflammatory cytokine (IL‐18, IL‐17, IL‐12) and Th2 cytokine (IL‐4) concentrations in patients with systemic lupus erythematosus. Lupus 2000. 9589–593.593. [PubMed]
4. Takahashi S, Fossati L, Iwamoto M, Merino R, Motta R, Kobayakawa T. et al Imbalance towards Th1 predominance is associated with acceleration of lupus‐like autoimmune syndrome in MRL mice. J Clin Invest 1996. 971597–1604.1604. [PMC free article] [PubMed]
5. Peng S L, Szabo S J, Glimcher L H. T‐bet regulates IgG class switching and pathogenic autoantibody production. Proc Natl Acad Sci USA 2002. 995545–5550.5550. [PMC free article] [PubMed]
6. Akahoshi M, Nakashima H, Tanaka Y, Kohsaka T, Nagano S, Ohgami E. et al Th1/Th2 balance of peripheral T helper cells in systemic lupus erythematosus. Arthritis Rheum 1999. 421644–1648.1648. [PubMed]
7. Uhm W S, Na K, Song G W, Jung S S, Lee T, Park M H. et al Cytokine balance in kidney tissue from lupus nephritis patients. Rheumatology (Oxford) 2003. 42935–938.938. [PubMed]
8. Chan R W, Lai F M, Li E K, Tam L S, Wong T Y, Szeto C Y. et al Messenger RNA expression of chemokine and fibrosing factor in the urinary sediment of patients with lupus nephritis. Arthritis Rheum 2004. 502882–2890.2890. [PubMed]
9. Lemay S, Mao C, Singh A K. Cytokine gene expression in the MRL/lpr model of lupus nephritis. Kidney Int 1996. 5085–93.93. [PubMed]
10. Nagasawa Y, Takenaka M, Matsuoka Y, Imai E, Hori M. Quantitation of mRNA expression in glomeruli using laser‐manipulated microdissection and laser pressure catapulting. Kidney Int 2000. 57717–723.723. [PubMed]
11. Peterson K S, Huang J F, Zhu J, D'Agati V, Liu X, Miller N. et al Characterization of heterogeneity in the molecular pathogenesis of lupus nephritis from transcriptional profiles of laser‐captured glomeruli. J Clin Invest 2004. 1131722–1733.1733. [PMC free article] [PubMed]
12. Finotto S, Neurath M F, Glickman J N, Qin S, Lehr H A, Green F H. et al Development of spontaneous airway changes consistent with human asthma in mice lacking T‐bet. Science 2002. 295336–338.338. [PubMed]
13. Hochberg M. Updating the American College of Rheumatology revised criteria for the classification of systemic lupus erythematosus. Arthritis Rheum 1997. 401725–1734.1734. [PubMed]
14. Bombardier C, Gladman D D, Urowitz M B, Caron D, Chang C H. Derivation of the SLEDAI. Arthritis Rheum 1992. 35630–640.640. [PubMed]
15. Levey A S, Bosch J P, Lewis J B, Greene T, Rogers N, Roth D. A more accurate method to estimate glomerular filtration rate from serum creatinine: a new prediction equation. Modification of Diet in Renal Disease Study Group. Ann Intern Med 1999. 130461–470.470. [PubMed]
16. Weening J J, D'Agati V D, Schwartz M M, Seshan S V, Alpers C E, Appel G B. et al International Society of Nephrology Working Group on the Classification of Lupus Nephritis; Renal Pathology Society Working Group on the Classification of Lupus Nephritis. The classification of glomerulonephritis in systemic lupus erythematosus revisited. Kidney Int 2004. 65521–530.530. [PubMed]
17. Grande J P, Balow J E. Renal biopsy in lupus nephritis. Lupus 1998. 7611–617.617. [PubMed]
18. Austin H A, Muenz L R, Joyce K M, Antonovych T T, Kullick M E, Klippel J H. et al Prognostic factors in lupus nephritis. Contribution of renal histologic data. Am J Med 1983. 75382–391.391. [PubMed]
19. Chan R W, Tam L S, Li E K, Lai F M, Chow K M, Lai K B. et al Inflammatory cytokine gene expression in the urinary sediment of lupus nephritis patients. Arthritis Rheum 2003. 481326–1331.1331. [PubMed]
20. Chan R W, Lai F M, Li E K, Tam L S, Chow K M, Li P K, Szeto C C. Imbalance of Th1/Th2 transcription factors in patients with lupus nephritis. Rheumatol 2006. 45951–957.957. [PubMed]
21. Pfaffl M W. A new mathematical model for relative quantification in real‐time RT‐PCR. Nucleic Acids Res 2001. 292002–2007.2007. [PMC free article] [PubMed]
22. Remuzzi G, Bertani T. Pathophysiology of progressive nephropathies. N Engl J Med 1998. 3391448–1456.1456. [PubMed]
23. Benigni A, Remuzzi G. How renal cytokines and growth factors contribute to renal disease progression. Am J Kidney Dis 2001. 37(Suppl 2)S21–S24.S24. [PubMed]
24. Labastie M C, Catala M, Gregoire J M, Peault B. The GATA‐3 gene is expressed during human kidney embryogenesis. Kidney Int 1995. 471597–1603.1603. [PubMed]
25. Masutani K, Akahoshi M, Tsuruya K, Tokumoto M, Ninomiya T, Kohsaka T. et al Predominance of Th1 immune response in diffuse proliferative lupus nephritis. Arthritis Rheum 2001. 442097–2106.2106. [PubMed]
26. Okada H, Konishi K, Nakazato Y, Kanno Y, Suzuki H, Sakaguchi H. et al Interleukin‐4 expression in mesangial proliferative glomerulonephritis. Am J Kidney Dis 1994. 23242–246.246. [PubMed]

Articles from Annals of the Rheumatic Diseases are provided here courtesy of BMJ Group

Formats:

Related citations in PubMed

See reviews...See all...

Cited by other articles in PMC

See all...

Links

  • Compound
    Compound
    PubChem Compound links
  • MedGen
    MedGen
    Related information in MedGen
  • PubMed
    PubMed
    PubMed citations for these articles
  • Substance
    Substance
    PubChem Substance links

Recent Activity

Your browsing activity is empty.

Activity recording is turned off.

Turn recording back on

See more...