Arthritis suppression by NADPH activation operates through an interferon-β pathway
© Olofsson et al; licensee BioMed Central Ltd. 2007
Received: 18 September 2006
Accepted: 09 May 2007
Published: 09 May 2007
A polymorphism in the activating component of the nicotinamide adenine dinucleotide phosphate (NADPH) oxidase complex, neutrophil cytosolic factor 1 (NCF1), has previously been identified as a regulator of arthritis severity in mice and rats. This discovery resulted in a search for NADPH oxidase-activating substances as a potential new approach to treat autoimmune disorders such as rheumatoid arthritis (RA). We have recently shown that compounds inducing NCF1-dependent oxidative burst, e.g. phytol, have a strong ameliorating effect on arthritis in rats. However, the underlying molecular mechanism is still not clearly understood. The aim of this study was to use gene-expression profiling to understand the protective effect against arthritis of activation of NADPH oxidase in the immune system.
Subcutaneous administration of phytol leads to an accumulation of the compound in the inguinal lymph nodes, with peak levels being reached approximately 10 days after administration. Hence, global gene-expression profiling on inguinal lymph nodes was performed 10 days after the induction of pristane-induced arthritis (PIA) and phytol administration. The differentially expressed genes could be divided into two pathways, consisting of genes regulated by different interferons. IFN-γ regulated the pathway associated with arthritis development, whereas IFN-β regulated the pathway associated with disease protection through phytol. Importantly, these two molecular pathways were also confirmed to differentiate between the arthritis-susceptible dark agouti (DA) rat, (with an Ncf-1 DA allele that allows only low oxidative burst), and the arthritis-protected DA.Ncf-1 E3 rat (with an Ncf1 E3 allele that allows a stronger oxidative burst).
Naturally occurring genetic polymorphisms in the Ncf-1 gene modulate the activity of the NADPH oxidase complex, which strongly regulates the severity of arthritis. We now show that the Ncf-1 allele that enhances oxidative burst and protects against arthritis is operating through an IFN-β-associated pathway, whereas the arthritis-driving allele operates through an IFN-γ-associated pathway. Treatment of arthritis-susceptible rats with an NADPH oxidase-activating substance, phytol, protects against arthritis. Interestingly, the treatment led to a restoration of the oxidative-burst effect and induction of a strikingly similar IFN-β-dependent pathway, as seen with the disease-protective Ncf1 polymorphism.
Rheumatoid arthritis (RA) is one of the commonest autoimmune diseases, with a prevalence of 0.5–1% [1, 2]. RA is a chronic and severely disabling disease of unknown etiology, although both environmental  and genetic factors  are believed to play roles in its cause. There is presently no cure for RA, although a variety of different drugs is used to treat the symptoms. The most common treatments include disease-modifying antirheumatic drugs such as,methotrexate [5, 6]. Other efficient antirheumatic drugs are the recently developed biological-response modifiers, such as tumor necrosis factor (TNF)-α blockers, which reduce both the established inflammation and joint destruction . The drawback of these treatments is an increased risk of infections because the body's defense system is impaired. Other biological-response modifiers targeting other cytokines or costimulatory molecules are currently being clinically tested and evaluated . Despite this range of antirheumatic drugs, there is still a large number of RA patients for whom none of these treatments is effective [9, 10], thus making the development of new therapies essential.
Identification of new targets for development of antirheumatic drugs is hampered by the heterogeneity of RA and the complexity of its molecular pathology. However, recent efforts with linkage-association studies, both in human populations and in animal models, are now giving results in the form of successful identification of autoimmunity-regulating genes [11–15]. The combined results from such studies will eventually lead to a greater understanding of the molecular regulation of this complex disease and they present potential new targets for drug development.
Neutrophil cytosolic factor 1 (Ncf1), also known as p47phox, was one of the first single genes identified to regulate arthritis severity. This finding was a result of linkage analysis and positional cloning in an arthritis model in rats using a cross between the arthritis-susceptible dark agouti (DA) rat and the arthritis-resistant E3 strains DA.Ncf1 E3([14, 16]. NCF-1 is the activating component of the NADPH oxidase complex, which, upon activation, produces reactive oxygen species (ROS) . We found that the dramatic increase in arthritis severity was caused by a decreased capacity of the nicotinamide adenine dinucleotide phosphate (NADPH) oxidase complex to produce ROS. Interestingly, the lower oxidative burst led to a reduction in cell membrane proteins and activation of autoreactive and arthritogenic T cells . Thus, the identified Ncf1 polymorphism and its effect on the immune system by decreased ROS production was concluded to be associated with the regulation of arthritogenic CD4 T cells in the immune priming phase [14, 19].
NADPH oxidase-activating substances such as phytol (3,7,11,15-tetramethyl-2-hexadecene-1-ol), were identified from studies performed on a human neutrophil cell line, and have subsequently been shown to be very efficacious in the treatment of arthritis in rats . However, the mechanism through which these compounds act is still not completely understood.
The intention of this study was to obtain a molecular insight into the anti-inflammatory mechanism of NADPH oxidase activation by phytol in an experimental arthritis model in rats, the pristane-induced arthritis (PIA) model . To analyze the in vivo effects of the NADPH oxidase activator phytol versus the effects of the arthritis-inducing compound pristane, global gene-expression profiling was performed. A biodistribution analysis of phytol was performed to determine which tissue and time point would be most relevant to investigate. Phytol was observed to accumulate slowly in inguinal lymph nodes, with peak levels being reached approximately 11 days after subcutaneous administration, which coincides with the onset period of arthritis. In the global gene-expression profiling, inguinal lymph nodes obtained 10 days after administration were analyzed. This analysis revealed several genes that were differentially expressed in rats with PIA compared with rats injected with phytol. A group of interesting genes was selected and verified by quantitative real-time PCR analysis in three further separate biological experiments, including a comparative study between the DA and DA.Ncf1 E3 congenic rats. The comparison between the two strains was aimed at determining whether the selected genes were differentially expressed in the arthritis-susceptible DA rat versus the arthritis-resistant congenic DA.Ncf1 E3 rat. Such data would indicate whether the NADPH oxidase-activating compound phytol is activating a pathway that is normally inactive in the absence of a fully functional Ncf1.
By studying gene-expression profiles and performing pathway analysis, we have identified the importance of an IFN-β-dependent pathway as one molecular mechanism for the arthritis-ameliorating efficacy of NADPH oxidase-activating compounds.
The discovery that NADPH oxidase-derived ROS have disease-protecting effects in arthritis opens up new possibilities for drug development against autoimmune and inflammatory diseases. To obtain a more detailed understanding of the molecular mechanism of this regulation, gene-expression profiling experiments were performed on inguinal lymph nodes from rats with pharmacologically (phytol) and genetically (Ncf1) modified NADPH oxidase activity.
Biodistribution and NADPH oxidase activation
Global gene-expression profiling
Quantitative real-time PCR validation of differentially expressed genes
Differentially expressed genes selected for further studies of the mechanism involved in pristane-induced arthritis and treatment with phytol.
UniGene ID number
Bone-expressed sequence tag 5
Interferon regulatory factor 7
Interferon-induced protein with tetratricopeptide repeats 3
2',5'-oligoadenylate synthetase 1
Myxovirus (influenza virus) resistance 2
Calcium binding protein a9
Matrix metalloproteinase 12
Chemokine (C-X-C motif) ligand 9
The genes upregulated by injections with pristane were Ass, Cxcl9 and Mmp12
Ass (argininosuccinate synthetase) encodes an enzyme involved in the urea cycle mediating the condensation of citrulline and aspartic acid to form arginine. The expression of Ass is induced by common pro-inflammatory cytokines (interleukin (IL)-1β, interferon (IFN)-γ and TNF-α) [23, 24]. CXCL9 (Chemokine (C–X–C motif) ligand 9, also known as Mig, (monokine induced by IFN-γ)) is a chemokine belonging to the CXC subfamily of chemokines acting through G-protein-coupled receptors . These proteins have chemoattraction and growth-promoting properties and are induced by IFN-γ and, to some extent, TNF-α to attract T cells to sites of inflammation . Higher levels of CXCL9 expression have been observed in the synovial tissues and fluids of patients with RA compared with tissues and fluids from control patients . MMP12 (matrix metalloproteinase 12) belongs to the family of matrix metalloproteinases (MMPs) , which are involved in cell migration and degradation of cartilage and bone by remodeling the extracellular matrix. Inducers of expression of MMPs include IL-1β, TNF-α  and IFN-γ . Abnormal levels of MMPs have been found in patients with autoimmune disorders such as RA and multiple sclerosis .
The genes upregulated by phytol were Best5, Irf7, Ifit3, Oas1, Mx2 and S100a9
Best5 (bone-expressed sequence tag 5) is mainly expressed in bone marrow and spleen and has been proposed to be involved in bone formation. The cytokines IFN-α and IFN-γ have been shown to induce BEST5 expression in osteoblasts .Interferon regulatory factor (IRF)-7 belongs to the IRF family of transcription factors involved in cell growth, antiviral defense and immune activation in lymphoid cells in spleen, thymus, and peripheral blood [33, 34]. IRF7 is part of the pathway activated by viral infection to induce the production of IFN type I (IFNtα/β) by a positive feedback loop . IRF7 was recently reported to be the master regulator of IFN type I-dependent immune responses , and recent publications have shown that an IRF5 polymorphism is strongly associated with systemic lupus erythematosus (SLE) [37, 38]. Interferon-induced protein with tetratricopeptide repeats (IFIT)-3 is induced by IFN-α  and IFN-β but not IFN-γ . However, IRF-7 most probably has a dual role, being both a strong regulator of IFN expression  and being induced by IFN in a positive feedback regulation [35, 41].
The protein 2',5'-oligoadenylate synthetase (OAS)-1 belongs to the OAS family, which was one of the first groups of IFN-induced antiviral proteins to be characterized. The activation of this mechanism is induced by the IFN type I pathway, which is activated upon pathogenic invasion as part of an antiviral response .
Myxovirus resistance (MX)-2 has a functional role in the defense against viral infections and its expression is partly controlled by type I IFNs . MX2 is induced by type I IFNs, and to a less extent by IFN-γ and lipopolysaccharide .
S100a9 is a small calcium-binding protein that belongs to the S100 family. It is primarily expressed by neutrophils but also by activated monocytes and macrophages . S100a9 has been shown to have a chemoattractant function in inflamed tissue, attracting neutrophils and inducing the adhesion of the attracted cells . Elevated levels of S100a9 have been found in the synovial fluid  and plasma  of patients with RA.
Identification of interferon-regulated pathways
To find a connection between the differentially expressed genes bioinformatic tools (Ingenuity Pathway Analysis; Ingenuity systems Inc., CA, USA, and PathwayAssist; Stratagene, CA, USA) and literature studies were used to assign pathways for these genes. Using these analysis tools, large schematic diagrams, covering all published interactions between the identified genes and common denominators, are produced. However, in this study we chose to focus on and validate one common denominator for the regulation of the identified differentially expressed genes, i.e.Ifn types I and type II (Ifnγ) [35, 49]. In addition, this stratification of the bioinformatic information was performed to make it possible to verify these findings using quantitative real-time PCR and to validate the biological importance of the identified pathway in further biological experiments. Hence, the identified central pathways for further studies included the genes increased in expression due to treatment with pristane (Ass, Cxcl9 and Mmp12), which are regulated by Ifn-γ and genes with increased expression due to phytol (Best5, Irf7, Ifit3, Oas1, Mx2 and S100a9), which are induced by IFN-α/β.
Both IFN-α/β and IFN-γ have an important role in the immunological response to pathogens and viruses. However, type I IFNs are mainly produced by plasmacytoid dendritic cells , whereas IFN-γ is produced by macrophages, natural killer (NK) cells and activated T helper (Th) cells. Consequently, the Ifn genes were included in the panel of genes to be further studied.
Besides the genes described above, S100a8 and the Mx2-related gene Mx1 were also analyzed in this time study and shown to be expressed in a similar pattern to that of S100a9 and Mx2, respectively (data not shown). As these genes are closely related, only one of each was followed for further expression characterization. The expression of Ncf1 was also included in this analysis as a control. However, no marked difference in Ncf1 expression was detected between the groups of animals (data not shown).
TNF-α and IL-1 are other cytokines identified as important immunological regulators in the same molecular pathways as the interferons. Transcription of Tnfα and IL-1 is increased in macrophages activated by IFN-α to act synergistically with IFN-γ in initiating a chronic inflammatory response. The expression of Tnfα and IL-1 was also analyzed, but only a small decrease in the expression of Tnfα could be observed after phytol administration, and the expression of IL-1 was below the detection limit (data not shown).
Verification of Ifn type I pathway in Ncf1congenic rats
Ifnα was expressed at a lower level in both the pristane-treated and phytol-treated animals, and in the rats with combined treatment, compared with the untreated control rats (p < 0.01) (Figure 9A). The expression of Ifnβ was significantly higher (p < 0.01) in the pristane-injected or phytol-injected groups than in the untreated control group, while the combined treatment induced even higher expression (Figure 9B). The expression of Ifnγ was significantly higher (p < 0.01) for the rats injected with pristane than for both control and phytol-treated rats (Figure 9C). Interestingly, only Ifnβ showed different expression in the DA.Ncf1 E3 rats compared with DA rats after pristane injection (p < 0.05). The expression level of Ifnβ in DA rats after pristane injection was comparable with that of untreated control rats; however, after phytol administration, the level of Ifnβ was increased to a level equal to that of DA.Ncf1 E3 rats (Figure 9B).
Cell distribution in Ncf1congenic rats
Ncf1 is a gene encoding the activating component of the NADPH oxidase complex. By positional cloning in rat models of arthritis, a polymorphism of Ncf1 was found to regulate arthritis severity . In fact, it was shown that a less functional Ncf1, and the resulting decrease in NADPH oxidase capacity to produce ROS, is a major cause of increased arthritis severity in both rat and mouse models of arthritis, an observation that challenges the general dogma of the inflammatory role of ROS. Furthermore, NADPH-activating substances have both preventive and therapeutic effects on arthritis, which opens up new approaches for disease treatment . However, from the results of the positional cloning of Ncf1 and the data showing strong ameliorating effects of ROS-inducing compounds in animal models, we are still a long way from fully understanding the underlying mechanism of action.
One approach to obtaining a molecular insight into a complex biological system is to use global gene-expression profiling . An advantage of this method is the large set of genes that can be analyzed in the same experimental setup, making it possible to use clustering and pathway analysis of large sets of genes [52, 53]. The assembled biological information can then be stratified into molecular pathways that can be studied and thoroughly validated.
However, the intricate choice of time point and tissue/cell type to be selected for analysis presents a significant hurdle . A further difficulty is the need for biological replicates and the genetic heterogeneity that is involved in human studies. This has naturally led to some skepticism regarding the utility of gene-expression profiling as a method to achieve an understanding of rheumatic diseases . However, recent analysis of gene-expression fingerprints of individual patients with RA might give hope for this still technically evolving method for understanding complex disorders [56–59].
In this study, we used global gene-expression analysis and quantitative real-time PCR techniques in four separate arthritis experiments in rats to investigate the downstream effects of preventive arthritis treatment with the NADPH oxidase activator phytol. Based on biodistribution analyses of phytol after SC administration, global gene-expression analysis was performed on inguinal lymph nodes at a time point just before the estimated day of disease onset. We observed that the expression of our set of differentially expressed genes in our material varies dramatically during the disease progress (Figures 4, 5, 6). Therefore, it is necessary to have information about which time point and tissue to analyze before initiating gene-expression profiling. Furthermore, we also analyzed, in other tissues (i.e. thymus, blood and spleen) the expression of the genes identified as differentially expressed in inguinal lymph nodes, and observed that the expression levels could be quite different or even undetectable in these tissues (data not shown). As a result, it is not possible to extrapolate the information between tissues and time points. In addition, the number of biological replicates used in the compared groups should be high enough to enable statistical analysis. Altogether, these issues make these studies extremely cumbersome to perform, especially when analyzing human samples. By using animal models, a more optimized study design may be provided , as a number of identical (inbred) individuals under the same treatment and environmental conditions are compared and tissue collected at the same time point by the same researcher.
Six genes (Best5, Irf7, Ifit3, Mx2, Oas1 and S100a9) were identified as genes induced by phytol (Table 1). The common inducers of these are IFN-α and IFN-β. These interferons are anti-inflammatory cytokines expressed after pathogenic infections [35, 65, 66]. From the gene-expression data it is not possible to determine whether IRF-7 is upregulated by an increased level of IFN-α/β as a downstream feedback regulator of the IFN-α/β receptor or if increased IFN-β level is the result of an upregulation of IRF-7 [35, 41, 36]. Oas1 and Mx2 are both induced upon viral invasion and IFN type I activation, and are thus regulated by the same pathway . The expression of Best5 can be induced by both IFN-α/β and IFN-γ, but studies have shown IFN-α/β to have the strongest enhancing effect on the expression .
Interestingly, a clear tendency in the expression of Ifnβ between DA and DA.Ncf1 E3 strains was observed after injection with pristane, with the DA.Ncf1 E3 rats having higher expression of Ifnβ than the DA rats (Figure 9B). This difference in expression level clearly resembles the differences observed for the phytol-induced genes Best5, Irf7, Ifit3, Mx2 and Oas1 (Figure 8). It is therefore likely that the downstream effect of the polymorphism in Ncf1, as well as the therapeutic effect of phytol, involves regulation of an IFN-β pathway. This IFN-β-regulated gene profile is interesting with respect to similarities to the patterns that have been identified in patients with SLE and in patients with juvenile arthritis treated with anti-TNF-α [68–71], and in mouse models of SLE . Subpopulations with active RA have also been shown to express increased levels of Ifn type I signature genes in peripheral blood . These reports show an Ifnα/β expression signature, which is very similar to that identified in the rats treated with phytol. However, in our study, the Ifn type I expression profile was linked to disease protection while the SLE Ifn type I profile was linked to disease progression. This may indicate that the interferon balance could be an important threshold denominator of autoimmune diseases, functioning as an essential balance for immune regulation, with an imbalance resulting in either SLE or arthritis. This is also exemplified by a recent study in which pristane was used to induce SLE in mice. In that study, chronic peritoneal administration of pristane elicited increased expression of the type I interferon-inducible genes Mx1, Irf7, IP-10 and Isg-15 as a consequence of SLE . However, despite the similarities in expression pattern, it must be noted that the SLE studies were performed on tissues other than inguinal lymph nodes and on established disease, so that differences in gene profiles could be caused by tissue differences or time-dependent regulation. Also interesting is the fact that the present study points towards a disease-ameliorating pathway that is regulated by IFN-β. Therefore, as the present observation of increased Ifn type I signature genes was observed to be a signal for prevention of disease onset, in contrast to the studies in ongoing SLE and arthritis , one might speculate that increased IFN type I regulation is a way to downregulate an ongoing immune response. Such an attempt to limit the inflammatory response has been suggested previously , and has also been indicated by experiments in our laboratory using Ifnβ-deficient mice, where a prolonged arthritis severity was observed due to Ifnβ deficiency . In fact, treatment with recombinant IFN-β significantly reduces cartilage destruction and bone destruction in collagen-induced arthritis in mice, which suggested a beneficial effect in patients also . However, to date no positive outcome of clinical trials using recombinant IFN-β in RA has been presented [75, 76]. As we have shown that the effect of phytol on Ifnβ-related genes is time-dependent and also correlates with the biodistribution of phytol to the inguinal lymph nodes, it is possible that tissue distribution as well as the dose and frequency of administration are crucial for the efficacy of arthritis treatment via this pathway.
The data presented here, together with gene-expression profiles of SLE, [68–71] and arthritis  strongly suggests the importance of the IFN-α/β pathway as a key mechanism in autoimmune conditions .
The fact that no difference in cell populations was observed to explain the differential levels of mRNA for IFN-β-regulated genes does not prove that alterations in cell populations in the inguinal lymph nodes are not crucial. As IFN-β is mainly produced by plasmacytoid dendritic cells , which were not specifically addressed in this study, more careful analysis of this cell population might provide further insight into the disease-protecting effects of phytol in arthritis.
Increased expression of S100a9 was observed in rats treated with phytol (Figure 5F). However, the expression of S100a9 did not show any difference between DA and DA.Ncf1 E3 rats (Figure 8F), and the expression profile was not similar to that of Ifnβ (Figure 9B). As a result, we consider S100a9 not to be regulated by IFN-β. It is more likely that the increased levels of S100a9 expression is a direct effect of increased concentrations of intracellular Ca2+ induced by the NADPH oxidase-produced ROS [78, 79]. Increased expression of S100a9 is mostly reported to be proinflammatory. However, this knowledge is based on analyses from tissues and blood during ongoing inflammation, while these studies analyzed inguinal lymph nodes prior to disease onset. Hence, the expression levels for different timepoints of the disease process could differ. Even so, S100a9 may be a good biomarker for the in vivo efficacy of administered phytol as an activator of NADPH oxidase specifically in lymph node tissues.
By targeting the NADPH oxidase complex with activating compounds such as phytol, we highlight a new mechanism to treat autoimmune conditions such as arthritis. By extracting and verifying a relevant biological molecular mechanism from gene-expression profiling data, we also indicate a plausible relation between increased levels of ROS and an anti-inflammatory response regulated by an IFN-β pathway. The use of gene-expression profiling to compare treatments in animal models of complex diseases also points to a useful pharmacogenomic approach to extract relevant information about the mechanism of action and to identify potential molecular biomarkers to be used in future animal experiments and clinical trials.
DA rats used in the microarray analysis, the first verifying quantitative real-time PCR study, the time study and the biodistribution study were purchased from Harlan Netherlands, and the DA.Ncf1 E3 rats with background origin from Zentralinstitut Für Versuchstierzucht, Hannover, Germany [80, 81]. All animals were kept in a climate-controlled environment with 12-hour light/dark cycles, housed in polystyrene cages containing wood shavings and fed standard rodent chow and water ad libitum. The rats were free from common pathogens including Sendai virus, Hantaan virus, coronavirus, reovirus, cytomegalovirus and Mycoplasma pulmonalis. The experiments were approved by the local ethics committees (Göteborg, Swedish license 230/2003 and Malmö/Lund, Swedish license M70/2004).
Induction and evaluation of arthritis
Pristane (Sigma-Aldrich, St. Louis, MO, USA) and/or phytol (3,7,11,15-tetramethyl-2-hexadecene-1-ol) (Sigma-Aldrich) were injected into the rats (age 8–12 weeks) by a single subcutaneous injection of 200 μL at the base of the tail. Arthritis development was monitored with a macroscopic scoring system of the four limbs ranging from 0 to 15 (1 point for each swollen or red toe, 1 point for midfoot digit or knuckle, 5 points for a swollen ankle). The scores of the four paws were added, yielding a maximum total score of 60 for each rat .
In the global gene-expression profiling and the first verifying quantitative real-time PCR experiment, five rats per group were used. In the comparative experiment between the DA and the DA.Ncf1 E3 strain, 4–5 rats per group were used. In all three experiments, the analyzed groups were; naïve controls, pristane-treated, phytol-treated and pristane plus phytol-treated animals. All rats were killed 10 days after injection. In the time-resolution study for comparison between pristane and phytol, four animals from each group were killed at 0, 3, 6, 8, 10, 13, 15 and 19 days after injection. The inguinal lymph nodes were immediately surgically removed and stored in a tissue-storage reagent (RNA later; Qiagen, Germany).
DA rats were injected with 200 μL phytol (Sigma-Aldrich) mixed with tritiated phytol (Moravek Biochemicals, CA, USA) to a final dose of 167 μCi/rat. The rats, four each day, were killed at 2, 4, 8, 11 or 17 days after injection, and the inguinal lymph nodes, spleen, heart, thymus, kidney, liver, lung, adipose tissue, muscle, injection-site tissue and blood were collected in equal amounts of saline solution (blood samples had heparin added to prevent coagulation) in pre-weighed tubes. The tissues were weighed, homogenized, and mixed with ready-safe scintillation liquid (Beckman Coulter, CA, USA). Tissue distribution of phytol was determined as counts per minute (cpm) of tritium using a beta counter (LKB Wallac, Turku, Finland) and cpm/g tissue was determined as the relative distribution of phytol. Microautoradiography was performed on three individual rats 10 days after subcutaneous administration with tritiated phytol (167 μCi/rat). The inguinal lymph nodes were snap-frozen in liquid nitrogen and shipped on dry ice to Quest Pharmaceutical Services (Newark, DE, USA). The frozen lymph nodes were embedded in optimum cutting temperature (OCT) embedding media (VWR international, Bristol, CT, USA) for cryosectioning. Sections of 10 μm thickness were heated at 50°C for 10 minutes, coated with photographic emulsion (Kodak NTB; Kodak, New Haven, CT, USA) and dried. The coated slides were exposed at 4°C in lightproof boxes. The exposed slides were stained with hematoxylin and eosin and developed for tritium labeling.
Flow cytometry analysis
Single-cell suspensions were made from inguinal lymph nodes and cells were stained with the anti-rat antibodies OX-1 (anti-LCA, lymphocytes), OX-33 (anti-CD45RA, B-cells), and R73 (anti-αβTCR, T cells) (all BD Pharmingen, San Diego, CA, USA), and with 3.2.3 (anti-NKRP1, NK cells, produced from an in-house hybridoma) for 30 minutes at 4°C. After washing with phosphate-buffered saline (PBS), cells were resuspended in PBS and analyzed in a FACSorter (Becton Dickinson, San Jose, CA, USA). Gates were set for the relevant cell type and analysed as percentage of total lymphocytes.
Total RNA from inguinal lymph nodes was isolated using a commercial kit (RNeasy® Mini Kit; Qiagen, Germany). The protocol for animal tissues was followed with the addition of the optional DNase digestion (RNase-Free DNase Set; Qiagen). The RNA yield was quantified spectrophotometrically (RNA 6000 Nano assay Kit;Agilent Technologies, Palo Alto, CA, USA) and the quality analyzed (2100 Bioanalyzer; Agilent). The average ratio between 28S/18S rRNA was 2.2, indicating high RNA quality. All RNA and cDNA samples were stored at -80°C.
Preparation of cRNA, hybridization and data analysis
In total, 10 μg of total RNA spiked with poly-A controls (pGIBS-TRP, pGIBS-THR, and pGIBS-LYS; American Type Culture Collection) was converted to cDNA, using a T7 promoter-polyT primer (Affymetrix, Santa Clara, CA, USA) and the reverse transcriptase Superscript II (Invitrogen, Paisley, UK), followed by a second-strand cDNA synthesis (Invitrogen). Double- stranded cDNA was in vitro transcribed to biotinylated cRNA (IVT labelling kit; Affymetrix) and then fragmented. The fragmented cRNA was mixed with hybridization spike controls (oligonucleotide B2 and a cRNA cocktail: BioB, BioC, BioD, and Cre; Affymetrix,). Aliquots of each sample were hybridized (16 hours at 45°C) to an array (GeneChip® Rat Expression Set 230A arrays; Affymetrix). The arrays were subsequently washed, stained and scanned according the manufacturer's instructions (GeneChip® Expression Analysis Technical Manual; Affymetrix). The data were analyzed using specific sofware (Robust Multi-Chip Analysis in GeneTraffic® UNO version 3.2–11; Stratagene, La Jolla, CA, USA, and Spotfire DecisionSite for Functional Genomics, version 8.1;Spotfire Inc., Göteborg, Sweden). The intensities were log2 transformed and the mean log2 intensity for each group calculated. The mean log2 fold change was calculated for the phytol-treated animals versus the pristane-treated animals by subtracting the mean log2 intensity for the pristane-treated rats from that for the phytol-treated rats. The total number of probe sets in the used rat Affymetrix chips was 15 923, and the average present call was 45%. Statistical significance of the difference in gene expression was determined using the two-sided Student's t-test. A transcript was considered differentially expressed if the mean absolute fold change was > 1.4 and the p value < 0.05. In addition, the mean intensity in the group showing the highest expression should be > 75. The average log2 fold change between the animals treated with phytol plus pristane versus the animals treated with pristane alone and the corresponding statistical analysis were also calculated, although these data were not used to identify differentially expressed genes.
The global gene-expression profiling data is deposited on-line [ArrayExpress: E-MEXP-78].
Quantitative real-time PCR
Primers used for the quantitative real-time PCR.
Quantitative data is expressed as mean ± SEM and significance analysis was performed using two-sided Student's T-test. * Represents a significance value of * p < 0.05, ** p < 0.01 and *** p < 0.001.
The global gene-expression profiling data is deposited at ArrayExpress (accession number E-MEXP-78).
We thank Camilla Bernhardsson for excellent animal experiments and Andrew Browning for critically reading the manuscript. This work is supported by the Craaford Foundation; Lundberg Foundation; the Kock and Österlund Foundations; The Swedish Association Against Rheumatism; The Swedish Medical Research Council; the Swedish Foundation for Strategic Research; the European Union (grant no. EUROME QLG1-CT2001-01407), and the 6th Framework Program of the European Union, NeuroproMiSe (grant no. LSHM-CT-2005-01863) and AUTOCURE, (grant no. LSHM-CT-2005-018661). This research was supported by the European Community's FP6 funding. This publication reflects only the author's views. The European Community is not liable for any use that may be made of the information herein.
- Firestein GS: Evolving concepts of rheumatoid arthritis. Nature. 2003, 423 (6937): 356-361. 10.1038/nature01661.View ArticlePubMedGoogle Scholar
- Gabriel SE: The epidemiology of rheumatoid arthritis. Rheum Dis Clin North Am. 2001, 27 (2): 269-281. 10.1016/S0889-857X(05)70201-5.View ArticlePubMedGoogle Scholar
- Symmons DP, Bankhead CR, Harrison BJ, Brennan P, Barrett EM, Scott DG, Silman AJ: Blood transfusion, smoking, and obesity as risk factors for the development of rheumatoid arthritis: results from a primary care-based incident case-control study in Norfolk, England. Arthritis and rheumatism. 1997, 40 (11): 1955-1961. 10.1002/art.1780401106.View ArticlePubMedGoogle Scholar
- MacGregor AJ, Snieder H, Rigby AS, Koskenvuo M, Kaprio J, Aho K, Silman AJ: Characterizing the quantitative genetic contribution to rheumatoid arthritis using data from twins. Arthritis and rheumatism. 2000, 43 (1): 30-37. 10.1002/1529-0131(200001)43:1<30::AID-ANR5>3.0.CO;2-B.View ArticlePubMedGoogle Scholar
- Bannwarth B, Labat L, Moride Y, Schaeverbeke T: Methotrexate in rheumatoid arthritis. An update. Drugs. 1994, 47 (1): 25-50.View ArticlePubMedGoogle Scholar
- Pincus T, Marcum SB, Callahan LF: Longterm drug therapy for rheumatoid arthritis in seven rheumatology private practices: II. Second line drugs and prednisone. J Rheumatol. 1992, 19 (12): 1885-1894.PubMedGoogle Scholar
- Feldmann M: Development of anti-TNF therapy for rheumatoid arthritis. Nat Rev Immunol. 2002, 2 (5): 364-371. 10.1038/nri802.View ArticlePubMedGoogle Scholar
- Ruderman EM, Pope RM: The evolving clinical profile of abatacept (CTLA4-Ig): a novel co-stimulatory modulator for the treatment of rheumatoid arthritis. Arthritis Res Ther. 2005, 7 (Suppl 2): S21-25. 10.1186/ar1688.PubMed CentralView ArticlePubMedGoogle Scholar
- Lipsky PE, van der Heijde DM, St Clair EW, Furst DE, Breedveld FC, Kalden JR, Smolen JS, Weisman M, Emery P, Feldmann M, et al: Infliximab and methotrexate in the treatment of rheumatoid arthritis. Anti-Tumor Necrosis Factor Trial in Rheumatoid Arthritis with Concomitant Therapy Study Group. N Engl J Med. 2000, 343 (22): 1594-1602. 10.1056/NEJM200011303432202.View ArticlePubMedGoogle Scholar
- Weinblatt ME, Kremer JM, Bankhurst AD, Bulpitt KJ, Fleischmann RM, Fox RI, Jackson CG, Lange M, Burge DJ: A trial of etanercept, a recombinant tumor necrosis factor receptor:Fc fusion protein, in patients with rheumatoid arthritis receiving methotrexate. N Engl J Med. 1999, 340 (4): 253-259. 10.1056/NEJM199901283400401.View ArticlePubMedGoogle Scholar
- Begovich AB, Carlton VE, Honigberg LA, Schrodi SJ, Chokkalingam AP, Alexander HC, Ardlie KG, Huang Q, Smith AM, Spoerke JM, et al: A missense single-nucleotide polymorphism in a gene encoding a protein tyrosine phosphatase (PTPN22) is associated with rheumatoid arthritis. Am J Hum Genet. 2004, 75 (2): 330-337. 10.1086/422827.PubMed CentralView ArticlePubMedGoogle Scholar
- Suzuki A, Yamada R, Chang X, Tokuhiro S, Sawada T, Suzuki M, Nagasaki M, Nakayama-Hamada M, Kawaida R, Ono M, et al: Functional haplotypes of PADI4, encoding citrullinating enzyme peptidylarginine deiminase 4, are associated with rheumatoid arthritis. Nat Genet. 2003, 34 (4): 395-402. 10.1038/ng1206.View ArticlePubMedGoogle Scholar
- Tokuhiro S, Yamada R, Chang X, Suzuki A, Kochi Y, Sawada T, Suzuki M, Nagasaki M, Ohtsuki M, Ono M, et al: An intronic SNP in a RUNX1 binding site of SLC22A4, encoding an organic cation transporter, is associated with rheumatoid arthritis. Nat Genet. 2003, 35 (4): 341-348. 10.1038/ng1267.View ArticlePubMedGoogle Scholar
- Olofsson P, Holmberg J, Tordsson J, Lu S, Akerstrom B, Holmdahl R: Positional identification of Ncf1 as a gene that regulates arthritis severity in rats. Nat Genet. 2003, 33 (1): 25-32. 10.1038/ng1058.View ArticlePubMedGoogle Scholar
- Ueda H, Howson JM, Esposito L, Heward J, Snook H, Chamberlain G, Rainbow DB, Hunter KM, Smith AN, Di Genova G, et al: Association of the T-cell regulatory gene CTLA4 with susceptibility to autoimmune disease. Nature. 2003, 423 (6939): 506-511. 10.1038/nature01621.View ArticlePubMedGoogle Scholar
- Vingsbo-Lundberg C, Nordquist N, Olofsson P, Sundvall M, Saxne T, Pettersson U, Holmdahl R: Genetic control of arthritis onset, severity and chronicity in a model for rheumatoid arthritis in rats. Nat Genet. 1998, 20 (4): 401-404. 10.1038/3887.View ArticlePubMedGoogle Scholar
- Nauseef WM: Assembly of the phagocyte NADPH oxidase. Histochem Cell Biol. 2004, 122 (4): 277-291. 10.1007/s00418-004-0679-8.View ArticlePubMedGoogle Scholar
- Gelderman KA, Hultqvist M, Holmberg J, Olofsson P, Holmdahl R: T cell surface redox levels determine T cell reactivity and arthritis susceptibility. Proceedings of the National Academy of Sciences of the United States of America. 2006, 103 (34): 12831-12836. 10.1073/pnas.0604571103.PubMed CentralView ArticlePubMedGoogle Scholar
- Hultqvist M, Holmdahl R: Ncf1 (p47phox) polymorphism determines oxidative burst and the severity of arthritis in rats and mice. Cell Immunol. 2005, 233 (2): 97-101. 10.1016/j.cellimm.2005.04.008.View ArticlePubMedGoogle Scholar
- Hultqvist M, Olofsson P, Gelderman KA, Holmberg J, Holmdahl R: A New Arthritis Therapy with Oxidative Burst Inducers. PLoS Med. 2006, 3 (9):
- Vingsbo C, Sahlstrand P, Brun JG, Jonsson R, Saxne T, Holmdahl R: Pristane-induced arthritis in rats: a new model for rheumatoid arthritis with a chronic disease course influenced by both major histocompatibility complex and non-major histocompatibility complex genes. Am J Pathol. 1996, 149 (5): 1675-1683.PubMed CentralPubMedGoogle Scholar
- Morey JS, Ryan JC, Van Dolah FM: Microarray validation: factors influencing correlation between oligonucleotide microarrays and real-time PCR. Biological procedures online. 2006, 8: 175-193. 10.1251/bpo126.PubMed CentralView ArticlePubMedGoogle Scholar
- Husson A, Brasse-Lagnel C, Fairand A, Renouf S, Lavoinne A: Argininosuccinate synthetase from the urea cycle to the citrulline-NO cycle. Eur J Biochem. 2003, 270 (9): 1887-1899. 10.1046/j.1432-1033.2003.03559.x.View ArticlePubMedGoogle Scholar
- Nagasaki A, Gotoh T, Takeya M, Yu Y, Takiguchi M, Matsuzaki H, Takatsuki K, Mori M: Coinduction of nitric oxide synthase, argininosuccinate synthetase, and argininosuccinate lyase in lipopolysaccharide-treated rats. RNA blot, immunoblot, and immunohistochemical analyses. J Biol Chem. 1996, 271 (5): 2658-2662. 10.1074/jbc.271.5.2658.View ArticlePubMedGoogle Scholar
- Liao F, Rabin RL, Yannelli JR, Koniaris LG, Vanguri P, Farber JM: Human Mig chemokine: biochemical and functional characterization. J Exp Med. 1995, 182 (5): 1301-1314. 10.1084/jem.182.5.1301.View ArticlePubMedGoogle Scholar
- Gasperini S, Marchi M, Calzetti F, Laudanna C, Vicentini L, Olsen H, Murphy M, Liao F, Farber J, Cassatella MA: Gene expression and production of the monokine induced by IFN-gamma (MIG), IFN-inducible T cell alpha chemoattractant (I-TAC), and IFN-gamma-inducible protein-10 (IP-10) chemokines by human neutrophils. J Immunol. 1999, 162 (8): 4928-4937.PubMedGoogle Scholar
- Patel DD, Zachariah JP, Whichard LP: CXCR3 and CCR5 ligands in rheumatoid arthritis synovium. Clin Immunol. 2001, 98 (1): 39-45. 10.1006/clim.2000.4957.View ArticlePubMedGoogle Scholar
- Brinckerhoff CE, Matrisian LM: Matrix metalloproteinases: a tail of a frog that became a prince. Nat Rev Mol Cell Biol. 2002, 3 (3): 207-214. 10.1038/nrm763.View ArticlePubMedGoogle Scholar
- Feinberg MW, Jain MK, Werner F, Sibinga NE, Wiesel P, Wang H, Topper JN, Perrella MA, Lee ME: Transforming growth factor-beta 1 inhibits cytokine-mediated induction of human metalloelastase in macrophages. J Biol Chem. 2000, 275 (33): 25766-25773. 10.1074/jbc.M002664200.View ArticlePubMedGoogle Scholar
- Wang Z, Zheng T, Zhu Z, Homer RJ, Riese RJ, Chapman HA, Shapiro SD, Elias JA: Interferon gamma induction of pulmonary emphysema in the adult murine lung. J Exp Med. 2000, 192 (11): 1587-1600. 10.1084/jem.192.11.1587.PubMed CentralView ArticlePubMedGoogle Scholar
- Leppert D, Lindberg RL, Kappos L, Leib SL: Matrix metalloproteinases: multifunctional effectors of inflammation in multiple sclerosis and bacterial meningitis. Brain Res Brain Res Rev. 2001, 36 (2–3): 249-257. 10.1016/S0165-0173(01)00101-1.View ArticlePubMedGoogle Scholar
- Grewal TS, Genever PG, Brabbs AC, Birch M, Skerry TM: Best5: a novel interferon-inducible gene expressed during bone formation. Faseb J. 2000, 14 (3): 523-531.PubMedGoogle Scholar
- Au WC, Moore PA, LaFleur DW, Tombal B, Pitha PM: Characterization of the interferon regulatory factor-7 and its potential role in the transcription activation of interferon A genes. J Biol Chem. 1998, 273 (44): 29210-29217. 10.1074/jbc.273.44.29210.View ArticlePubMedGoogle Scholar
- Zhang L, Pagano JS: IRF-7, a new interferon regulatory factor associated with Epstein-Barr virus latency. Mol Cell Biol. 1997, 17 (10): 5748-5757.PubMed CentralView ArticlePubMedGoogle Scholar
- Taniguchi T, Takaoka A: The interferon-alpha/beta system in antiviral responses: a multimodal machinery of gene regulation by the IRF family of transcription factors. Curr Opin Immunol. 2002, 14 (1): 111-116. 10.1016/S0952-7915(01)00305-3.View ArticlePubMedGoogle Scholar
- Honda K, Yanai H, Negishi H, Asagiri M, Sato M, Mizutani T, Shimada N, Ohba Y, Takaoka A, Yoshida N, et al: IRF-7 is the master regulator of type-I interferon-dependent immune responses. Nature. 2005, 434 (7034): 772-777. 10.1038/nature03464.View ArticlePubMedGoogle Scholar
- Graham RR, Kozyrev SV, Baechler EC, Reddy MV, Plenge RM, Bauer JW, Ortmann WA, Koeuth T, Escribano MF, Collaborative Groups TA, et al: A common haplotype of interferon regulatory factor 5 (IRF5) regulates splicing and expression and is associated with increased risk of systemic lupus erythematosus. Nat Genet. 2006, 38 (5): 550-555. 10.1038/ng1782.View ArticlePubMedGoogle Scholar
- Sigurdsson S, Nordmark G, Goring HH, Lindroos K, Wiman AC, Sturfelt G, Jonsen A, Rantapaa-Dahlqvist S, Moller B, Kere J, et al: Polymorphisms in the tyrosine kinase 2 and interferon regulatory factor 5 genes are associated with systemic lupus erythematosus. Am J Hum Genet. 2005, 76 (3): 528-537. 10.1086/428480.PubMed CentralView ArticlePubMedGoogle Scholar
- Levy D, Larner A, Chaudhuri A, Babiss LE, Darnell JE: Interferon-stimulated transcription: isolation of an inducible gene and identification of its regulatory region. Proceedings of the National Academy of Sciences of the United States of America. 1986, 83 (23): 8929-8933. 10.1073/pnas.83.23.8929.PubMed CentralView ArticlePubMedGoogle Scholar
- de Veer MJ, Sim H, Whisstock JC, Devenish RJ, Ralph SJ: IFI60/ISG60/IFIT4, a new member of the human IFI54/IFIT2 family of interferon-stimulated genes. Genomics. 1998, 54 (2): 267-277. 10.1006/geno.1998.5555.View ArticlePubMedGoogle Scholar
- Sato M, Suemori H, Hata N, Asagiri M, Ogasawara K, Nakao K, Nakaya T, Katsuki M, Noguchi S, Tanaka N, et al: Distinct and essential roles of transcription factors IRF-3 and IRF-7 in response to viruses for IFN-alpha/beta gene induction. Immunity. 2000, 13 (4): 539-548. 10.1016/S1074-7613(00)00053-4.View ArticlePubMedGoogle Scholar
- Witt PL, Marie I, Robert N, Irizarry A, Borden EC, Hovanessian AG: Isoforms p69 and p100 of 2',5'-oligoadenylate synthetase induced differentially by interferons in vivo and in vitro. J Interferon Res. 1993, 13 (1): 17-23.View ArticlePubMedGoogle Scholar
- Melen K, Keskinen P, Ronni T, Sareneva T, Lounatmaa K, Julkunen I: Human MxB protein, an interferon-alpha-inducible GTPase, contains a nuclear targeting signal and is localized in the heterochromatin region beneath the nuclear envelope. J Biol Chem. 1996, 271 (38): 23478-23486. 10.1074/jbc.271.38.23478.View ArticlePubMedGoogle Scholar
- Asano A, Jin HK, Watanabe T: Mouse Mx2 gene: organization, mRNA expression and the role of the interferon-response promoter in its regulation. Gene. 2003, 306: 105-113. 10.1016/S0378-1119(03)00428-1.View ArticlePubMedGoogle Scholar
- Kerkhoff C, Klempt M, Sorg C: Novel insights into structure and function of MRP8 (S100A8) and MRP14 (S100A9). Biochim Biophys Acta. 1998, 1448 (2): 200-211. 10.1016/S0167-4889(98)00144-X.View ArticlePubMedGoogle Scholar
- Ryckman C, Vandal K, Rouleau P, Talbot M, Tessier PA: Proinflammatory activities of S100: proteins S100A8, S100A9, and S100A8/A9 induce neutrophil chemotaxis and adhesion. J Immunol. 2003, 170 (6): 3233-3242.View ArticlePubMedGoogle Scholar
- Berntzen HB, Olmez U, Fagerhol MK, Munthe E: The leukocyte protein L1 in plasma and synovial fluid from patients with rheumatoid arthritis and osteoarthritis. Scand J Rheumatol. 1991, 20 (2): 74-82.View ArticlePubMedGoogle Scholar
- Brun JG, Jonsson R, Haga HJ: Measurement of plasma calprotectin as an indicator of arthritis and disease activity in patients with inflammatory rheumatic diseases. J Rheumatol. 1994, 21 (4): 733-738.PubMedGoogle Scholar
- Baccala R, Kono DH, Theofilopoulos AN: Interferons as pathogenic effectors in autoimmunity. Immunol Rev. 2005, 204: 9-26. 10.1111/j.0105-2896.2005.00252.x.View ArticlePubMedGoogle Scholar
- Colonna M, Krug A, Cella M: Interferon-producing cells: on the front line in immune responses against pathogens. Curr Opin Immunol. 2002, 14 (3): 373-379. 10.1016/S0952-7915(02)00349-7.View ArticlePubMedGoogle Scholar
- Haupl T, Krenn V, Stuhlmuller B, Radbruch A, Burmester GR: Perspectives and limitations of gene expression profiling in rheumatology: new molecular strategies. Arthritis Res Ther. 2004, 6 (4): 140-146. 10.1186/ar1194.PubMed CentralView ArticlePubMedGoogle Scholar
- Devauchelle V, Marion S, Cagnard N, Mistou S, Falgarone G, Breban M, Letourneur F, Pitaval A, Alibert O, Lucchesi C, et al: DNA microarray allows molecular profiling of rheumatoid arthritis and identification of pathophysiological targets. Genes Immun. 2004, 5 (8): 597-608. 10.1038/sj.gene.6364132.View ArticlePubMedGoogle Scholar
- Heller RA, Schena M, Chai A, Shalon D, Bedilion T, Gilmore J, Woolley DE, Davis RW: Discovery and analysis of inflammatory disease-related genes using cDNA microarrays. Proceedings of the National Academy of Sciences of the United States of America. 1997, 94 (6): 2150-2155. 10.1073/pnas.94.6.2150.PubMed CentralView ArticlePubMedGoogle Scholar
- Oertelt S, Selmi C, Invernizzi P, Podda M, Gershwin ME: Genes and goals: an approach to microarray analysis in autoimmunity. Autoimmun Rev. 2005, 4 (7): 414-422. 10.1016/j.autrev.2005.05.004.View ArticlePubMedGoogle Scholar
- Lanchbury J, Hall M, Steer S: Progress and problems in defining susceptibility genes for rheumatic diseases. Rheumatology (Oxford). 2002, 41 (4): 361-364. 10.1093/rheumatology/41.4.361.View ArticleGoogle Scholar
- Batliwalla FM, Baechler EC, Xiao X, Li W, Balasubramanian S, Khalili H, Damle A, Ortmann WA, Perrone A, Kantor AB, et al: Peripheral blood gene expression profiling in rheumatoid arthritis. Genes Immun. 2005, 6 (5): 388-397. 10.1038/sj.gene.6364209.View ArticlePubMedGoogle Scholar
- Olsen N, Sokka T, Seehorn CL, Kraft B, Maas K, Moore J, Aune TM: A gene expression signature for recent onset rheumatoid arthritis in peripheral blood mononuclear cells. Ann Rheum Dis. 2004, 63 (11): 1387-1392. 10.1136/ard.2003.017194.PubMed CentralView ArticlePubMedGoogle Scholar
- Shou J, Bull CM, Li L, Qian HR, Wei T, Luo S, Perkins D, Solenberg PJ, Tan SL, Chen XY, et al: Identification of blood biomarkers of rheumatoid arthritis by transcript profiling of peripheral blood mononuclear cells from the rat collagen-induced arthritis model. Arthritis Res Ther. 2006, 8 (1): R28-10.1186/ar1883.PubMed CentralView ArticlePubMedGoogle Scholar
- van der Pouw Kraan TC, Wijbrandts CA, van Baarsen LG, Voskuyl AE, Rustenburg F, Baggen JM, Ibrahim SM, Fero M, Dijkmans BA, Tak PP, et al: Rheumatoid Arthritis subtypes identified by genomic profiling of peripheral blood cells: Assignment of a type I interferon signature in a subpopulation of patients. Ann Rheum Dis. 2007Google Scholar
- Jirholt J, Lindqvist AB, Holmdahl R: The genetics of rheumatoid arthritis and the need for animal models to find and understand the underlying genes. Arthritis Res. 2001, 3 (2): 87-97. 10.1186/ar145.PubMed CentralView ArticlePubMedGoogle Scholar
- Farber JM: A macrophage mRNA selectively induced by gamma-interferon encodes a member of the platelet factor 4 family of cytokines. Proceedings of the National Academy of Sciences of the United States of America. 1990, 87 (14): 5238-5242. 10.1073/pnas.87.14.5238.PubMed CentralView ArticlePubMedGoogle Scholar
- Flodstrom M, Niemann A, Bedoya FJ, Morris SM, Eizirik DL: Expression of the citrulline-nitric oxide cycle in rodent and human pancreatic beta-cells: induction of argininosuccinate synthetase by cytokines. Endocrinology. 1995, 136 (8): 3200-3206. 10.1210/en.136.8.3200.PubMedGoogle Scholar
- Feldmann M, Brennan FM, Maini RN: Role of cytokines in rheumatoid arthritis. Annu Rev Immunol. 1996, 14: 397-440. 10.1146/annurev.immunol.14.1.397.View ArticlePubMedGoogle Scholar
- Bailey WJ, Ulrich R: Molecular profiling approaches for identifying novel biomarkers. Expert Opin Drug Saf. 2004, 3 (2): 137-151. 10.1517/147403188.8.131.52.View ArticlePubMedGoogle Scholar
- Decker T, Stockinger S, Karaghiosoff M, Muller M, Kovarik P: IFNs and STATs in innate immunity to microorganisms. J Clin Invest. 2002, 109 (10): 1271-1277. 10.1172/JCI200215770.PubMed CentralView ArticlePubMedGoogle Scholar
- Nguyen H, Hiscott J, Pitha PM: The growing family of interferon regulatory factors. Cytokine Growth Factor Rev. 1997, 8 (4): 293-312. 10.1016/S1359-6101(97)00019-1.View ArticlePubMedGoogle Scholar
- Stark GR, Kerr IM, Williams BR, Silverman RH, Schreiber RD: How cells respond to interferons. Annu Rev Biochem. 1998, 67: 227-264. 10.1146/annurev.biochem.67.1.227.View ArticlePubMedGoogle Scholar
- Baechler EC, Batliwalla FM, Karypis G, Gaffney PM, Ortmann WA, Espe KJ, Shark KB, Grande WJ, Hughes KM, Kapur V, et al: Interferon-inducible gene expression signature in peripheral blood cells of patients with severe lupus. Proceedings of the National Academy of Sciences of the United States of America. 2003, 100 (5): 2610-2615. 10.1073/pnas.0337679100.PubMed CentralView ArticlePubMedGoogle Scholar
- Baechler EC, Gregersen PK, Behrens TW: The emerging role of interferon in human systemic lupus erythematosus. Curr Opin Immunol. 2004, 16 (6): 801-807. 10.1016/j.coi.2004.09.014.View ArticlePubMedGoogle Scholar
- Bennett L, Palucka AK, Arce E, Cantrell V, Borvak J, Banchereau J, Pascual V: Interferon and granulopoiesis signatures in systemic lupus erythematosus blood. J Exp Med. 2003, 197 (6): 711-723. 10.1084/jem.20021553.PubMed CentralView ArticlePubMedGoogle Scholar
- Palucka AK, Blanck JP, Bennett L, Pascual V, Banchereau J: Cross-regulation of TNF and IFN-alpha in autoimmune diseases. Proceedings of the National Academy of Sciences of the United States of America. 2005, 102 (9): 3372-3377. 10.1073/pnas.0408506102.PubMed CentralView ArticlePubMedGoogle Scholar
- Nacionales DC, Kelly KM, Lee PY, Zhuang H, Li Y, Weinstein JS, Sobel E, Kuroda Y, Akaogi J, Satoh M, et al: Type I interferon production by tertiary lymphoid tissue developing in response to 2,6,10,14-tetramethyl-pentadecane (pristane). Am J Pathol. 2006, 168 (4): 1227-1240. 10.2353/ajpath.2006.050125.PubMed CentralView ArticlePubMedGoogle Scholar
- Tak PP: IFN-beta in rheumatoid arthritis. Front Biosci. 2004, 9: 3242-3247.View ArticlePubMedGoogle Scholar
- Treschow AP, Teige I, Nandakumar KS, Holmdahl R, Issazadeh-Navikas S: Stromal cells and osteoclasts are responsible for exacerbated collagen-induced arthritis in interferon-beta-deficient mice. Arthritis and rheumatism. 2005, 52 (12): 3739-3748. 10.1002/art.21496.View ArticlePubMedGoogle Scholar
- van Holten J, Pavelka K, Vencovsky J, Stahl H, Rozman B, Genovese M, Kivitz AJ, Alvaro J, Nuki G, Furst DE, et al: A multicentre, randomised, double blind, placebo controlled phase II study of subcutaneous interferon beta-1a in the treatment of patients with active rheumatoid arthritis. Ann Rheum Dis. 2005, 64 (1): 64-69. 10.1136/ard.2003.020347.PubMed CentralView ArticlePubMedGoogle Scholar
- Tak PP, Hart BA, Kraan MC, Jonker M, Smeets TJ, Breedveld FC: The effects of interferon beta treatment on arthritis. Rheumatology (Oxford). 1999, 38 (4): 362-369. 10.1093/rheumatology/38.4.362.View ArticleGoogle Scholar
- Biron CA: Interferons alpha and beta as immune regulators – a new look. Immunity. 2001, 14 (6): 661-664. 10.1016/S1074-7613(01)00154-6.View ArticlePubMedGoogle Scholar
- Brechard S, Bueb JL, Tschirhart EJ: Interleukin-8 primes oxidative burst in neutrophil-like HL-60 through changes in cytosolic calcium. Cell Calcium. 2005, 37 (6): 531-540. 10.1016/j.ceca.2005.01.019.View ArticlePubMedGoogle Scholar
- Foell D, Frosch M, Sorg C, Roth J: Phagocyte-specific calcium-binding S100 proteins as clinical laboratory markers of inflammation. Clin Chim Acta. 2004, 344 (1–2): 37-51. 10.1016/j.cccn.2004.02.023.View ArticlePubMedGoogle Scholar
- Olofsson P, Holmberg J, Pettersson U, Holmdahl R: Identification and isolation of dominant susceptibility loci for pristane-induced arthritis. J Immunol. 2003, 171 (1): 407-416.View ArticlePubMedGoogle Scholar
- Olofsson P, Holmdahl R: Positional cloning of Ncf1 – a piece in the puzzle of arthritis genetics. Scand J Immunol. 2003, 58 (2): 155-164. 10.1046/j.1365-3083.2003.01293.x.View ArticlePubMedGoogle Scholar
- Holmdahl R, Carlsén S, Mikulowska A, Vestberg M, Brunsberg U, Hansson A, Sundvall M, Larsson L, Pettersson U: Genetic analysis of mouse models for rheumatois arthritis. Human Genome Methods. Edited by: Adolph KW. 1998, ©CRC Press LLC, New York, USA, 215-238.Google Scholar
- AppliedBiosystems: User Bulletin #2 ABI PRISM 7700 sequence detection system. 1997, Warrington, UKGoogle Scholar
- Laborda J: 36B4 cDNA used as an estradiol-independent mRNA control is the cDNA for human acidic ribosomal phosphoprotein PO. Nucleic Acids Res. 1991, 19 (14): 3998-10.1093/nar/19.14.3998.PubMed CentralView ArticlePubMedGoogle Scholar
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.