Inflammation and ectopic lymphoid structures in rheumatoid arthritis synovial tissues dissected by genomics technology: Identification of the interleukin-7 signaling pathway in tissues with lymphoid neogenesis


  • The views expressed herein are those of the authors.



In ∼25% of synovial tissues from rheumatoid arthritis (RA) patients, infiltrates of T cells, B cells, and follicular dendritic cells (FDCs) are spatially organized into structures resembling lymph nodes with germinal centers. The remainder of the tissues lack FDCs and show either a diffuse or an aggregated T cell and B cell infiltrate. To gain more insight into this specific disease process, we sought to identify the genes expressed in RA tissues with ectopic lymphoid structures.


Gene expression profiling of RA synovial tissues was determined by complementary DNA microarray analysis and quantitative real-time polymerase chain reaction. The presence of lymphoid follicles and localization of interleukin-7 (IL-7) in synovial tissue sections was determined by immunofluorescence staining using specific antibodies.


Findings of gene expression analysis confirmed previous reports that tissues with lymphoid structures showed elevated expression of CXCL13, CCL21, CCR7, and lymphotoxin α and β messenger RNA. In addition, the tissues also showed enhanced expression of the chemokines CXCL12 and CCL19 and the associated receptors CXCR4 and CXCR5, which are important for the attraction of T cells, B cells, and dendritic cells. Pathway analysis revealed increased expression of genes involved in JAK/STAT signaling, T cell– and B cell–specific pathways, Fcε receptor type I signaling in mast cells, and IL-7 signal transduction in the tissues with ectopic lymphoid follicles, accompanied by increased expression of IL-7 receptor α (IL-7Rα)/IL-2Rγ chains and IL-7. Protein expression of IL-7 in RA tissues was localized within fibroblast-like synoviocytes, macrophages, and blood vessels and was colocalized with extracellular matrix structures around the B cell follicles.


Activation of the IL-7 pathway may play an important role in lymphoid neogenesis, analogous to its role in the development of normal lymphoid tissue.

Rheumatoid arthritis (RA) is a chronic systemic autoimmune disease of unknown etiology. Patient variability in clinical presentation and differential response to treatment suggest that RA is a heterogeneous disease. The heterogeneous character of RA is also evident from the type of cellular infiltrates in the synovial tissues. In ∼25% of patients, cellular infiltrates show a high degree of cellular organization, resembling structures normally observed in lymph nodes and comprising distinct T cell and B cell areas and a network of follicular dendritic cells (FDCs) within the B cell area and are therefore referred to as ectopic or tertiary lymphoid structures. In the remainder of the patients, the tissues do not contain FDCs and show either a diffuse lymphocytic infiltrate or an aggregated T cell and B cell infiltrate (1, 2). Lymphoid structures in the synovium are likely to contribute to the pathogenesis of RA by local production of (auto)antibodies. However, the factors that contribute to the formation of lymphoid follicles in RA are not fully understood.

Ectopic lymphoid structures are not specific for RA, but are commonly associated with chronic inflammation, since they have also been identified in other chronic inflammatory diseases, such as Sjögren's syndrome (3), Hashimoto thyroiditis (4, 5), Helicobacter pylori–induced gastritis (6), chronic hepatitis C (7), multiple sclerosis (8, 9), and Crohn's disease (10) (for review, see ref. 11).

The existence of germinal center–like structures is indicative of a high level of organization within these ectopic lymphoid structures, allowing B cells that are in close contact with FDCs to become activated and produce (auto)antibodies. Most of our knowledge of lymphoid tissue development is derived from murine studies. During embryonic development, a stringently regulated developmental program is initiated that eventually results in the formation of highly organized lymphoid tissue (for review, see ref. 12). It has become clear that one of the first events is the initial clustering of inducer cells (IL-7R+,CD3–,CD4+,CD45+) and organizer cells (VCAM-1+,ICAM-1+ stromal cells). Interleukin-7 receptor (IL-7R) signaling is essential for induction of the initial expression of lymphotoxin (LT) α1β2 on inducer cells, which allows triggering of the LTβ receptor (LTβR) expressed on organizer cells. LTβR signaling in concert with interactions between α4β1 and vascular cell adhesion molecule 1 (VCAM-1) leads to the production of chemokines, such as CXCL13, CCL19, CCL21, and CXCL12, by stromal organizer cells, which mediate the cellular influx, leading to the formation of cellular aggregates. For the subsequent formation of distinct areas into which B and T lymphocytes can lodge, an interaction between inducer cells or B cells and stromal cells has been implicated (13, 14). It is likely that similar developmental programs are also operative during the formation of tertiary lymphoid structures at sites of inflammation, although the cellular subsets that initiate this structure formation may differ.

There is a close relationship between inflammation and lymphoid organogenesis, since chemokines and adhesion molecules are crucially involved in both processes. Indeed, a higher expression of the cytokines LTα and LTβ and the chemokines CXCL13 and CCL21 was observed in RA tissues with germinal centers (2, 15–17).

In the present study, we examined gene expression profiles in RA synovium with different types of lymphoid infiltrates. We used microarray analysis to examine which molecular pathways are used and which genes determine the different types of lymphoid organization.


Synovial tissue samples.

Twelve patients with RA who were undergoing total joint replacement surgery were included in the gene expression profiling study, as described previously (18, 19). Patients met the American College of Rheumatology (ACR; formerly, the American Rheumatism Association) 1987 criteria for RA (20, 21). The characteristics of the patients (duration of disease, erythrocyte sedimentation rate, and white blood cell count) were not different between the different tissue groups (see description below). Tissue samples were snap-frozen in liquid nitrogen, and the frozen blocks were stored in liquid nitrogen until they were sectioned for analysis by immunofluorescence. All patients gave their informed consent, and the Medical Ethics Committee approved the study protocol.

Gene expression profiling of RA synovial tissue samples.

The details of isolating messenger RNA (mRNA), labeling, and hybridizing have been described elsewhere (18, 19). Briefly, synovial tissues (∼1 gm) were dissected and quickly frozen in liquid nitrogen and stored at −80°C. Total cellular RNA and mRNA were isolated from the tissues with TRIzol reagent (Gibco BRL, Carlsbad, CA) and with the FastTrack 2.0 kit (Invitrogen, Carlsbad, CA), respectively, according to the manufacturers' instructions. For gene expression profiling by DNA microarray analysis, fluorescent complementary DNA (cDNA) probes were prepared from 1 μg of experimental mRNA sample by oligo(dT)-primed polymerization using Superscript II reverse transcriptase in the presence of Cy5-labeled dCTP (as described at A common reference mRNA sample consisting of a mixture of mRNA isolated from 11 different cell lines, synovial tissue, fibroblasts, and activated peripheral blood mononuclear cells was labeled with Cy3.

Microarray procedures, data analysis, and statistical analysis.

We combined the data from 2 previous tissue profiling studies (18, 19). All data are publicly available at the Stanford Microarray Database (22) (available at Genes with at least 80% of the data present were included, and only genes with an absolute value that was at least 2 times higher than the median expression of that gene in at least 1 array were selected. All genes were expressed relative to their median expression level across the arrays of the same microarray platform, allowing us to combine the data from the 2 platforms.

Statistical analysis of microarray data was performed using Significance Analysis of Microarrays (SAM) (available at∼tibs/SAM) (23). For visualization of the results, we used Cluster and TreeView software (24) (available at to perform hierarchical cluster analysis. Pathway level analysis of gene expression data was performed by gene set enrichment analysis (25), using pathways from Kegg and Biocarta databases.

Quantitative real-time polymerase chain reaction (PCR).

For these studies, 20 ng of mRNA was transcribed into cDNA using a RevertAid First-Strand cDNA synthesis kit (MBI Fermentas, St. Leon-Rot, Germany). Briefly, mRNA was heated at 70°C for 5 minutes with 1 μl of oligo(dT) primers (0.5 μg/μl) and 1 μl of random hexamers (0.2 μg/μl) in a final volume of 12 μl and chilled at 4°C for 1 minute. Next, reverse transcription of mRNA was performed in a total volume of 20 μl containing first-strand buffer, 2 μl of dNTP (10 mM), 20 units of RNase inhibitor, and 200 units of H Minus Moloney murine leukemia virus reverse transcriptase. The samples were incubated at 42°C for 60 minutes and then for 10 minutes at 70°C.

Quantitative real-time PCR was performed with an ABI Prism 7900 Sequence Detection System (PE Applied Biosystems, Foster City, CA). The reaction mixture was composed of SYBR Green Mastermix, 250 or 500 nM of each primer, and cDNA in a total volume of 20 μl, according to the manufacturer's instructions. For each gene, a standard curve was used to calculate gene expression levels, thus correcting for different primer efficiencies. Gene expression levels were expressed relative to GAPDH. The primer pairs shown in Table 1 were synthesized by Invitrogen (Breda, The Netherlands). When real-time PCR data were combined with microarray data, real-time PCR data were expressed as log2 expression values, analogous to the microarray data.

Table 1. Primers used in the present study
Gene*Size, bpForward primerReverse primer
  • *

    IL-7 = interleukin-7; IL-7Rα = interleukin-7 receptor α.


Immunofluorescence staining of synovial tissues.

Cryostat sections (5 μm) were mounted on gelatin-coated glass slides. The sections were dried, fixed in dehydrated acetone for 10 minutes, and air dried for an additional 10 minutes. To prevent nonspecific binding of antibody, sections were blocked with 10% normal goat serum (Invitrogen) for 20 minutes. Sections were then incubated with primary antibody for 1 hour at room temperature, followed by an additional 1 hour of incubation with fluorescence-labeled conjugates. Sections were embedded in Vectashield (Vector, Burlingame, CA) and examined with a Nikon Eclipse E800 microscope (Nikon Europe).

The following primary antibodies were used: anti-CD21L (1:20 dilution; kindly provided by Dr. Y.-J. Liu, Center for Cancer Immunology Research, University of Texas, M. D. Anderson Cancer Center, Houston, TX), anti-CD3 (1:10 dilution; BD PharMingen, San Diego, CA), biotinylated anti-CD19 (1:25 dilution; Diaclone, Besançon, France), biotinylated anti-CD8 (1:25 dilution; BD PharMingen), anti–type IV collagen (1:100 dilution; DakoCytomation, Glostrup, Denmark), and anti–IL-7 (1:50 dilution; Affinity BioReagents, Golden, CO). For detection of the primary antibodies, we used Alexa 488–labeled goat anti-mouse Ig (1:400 dilution; Molecular Probes, Eugene, OR), Alexa 594–labeled goat anti-rat Ig (1:100 dilution; Molecular Probes), and fluorescein isothiocyanate–labeled streptavidin (1:100 dilution; Vector). Control staining for each antibody was performed by omitting the primary antibody. The specificity of the IL-7 antibody was secured, since preincubation of the antibody with an excess amount of recombinant human IL-7 (Strathmann Biotec, Hamburg, Germany) prevented tissue staining.


Characterization of synovial tissues by CD21L mRNA measurements and immunofluorescence.

To determine the presence of organized lymphoid follicles in 12 synovial RA tissues for which microarray data were available (18, 19), we performed quantitative real-time PCR for the long CD21 isoform (CD21L). This isoform of CD21 contains an additional exon and represents the first characterized human FDC-specific molecule, which may confer unique functions of FDCs in germinal center development (26). Takemura et al (2) showed that CD21L mRNA is selectively expressed in germinal center–containing synovial tissues from RA patients and is absent in other types of infiltrates. We detected significant levels of CD21L mRNA in 4 tissues, whereas the other 8 tissues were negative (Figure 1).

Figure 1.

Characterization of synovial tissue types by immunohistochemical staining and levels of mRNA for CD21L in synovial tissues from patients with rheumatoid arthritis. A, D, and E, Staining of T cells (CD3; red) and B cells (CD19; green). B, Staining of B cells (CD19; green) and follicular dendritic cells (FDCs) (CD21L; red). C, Staining of FDCs (CD21L; red) and T cells (CD8; green). (Original magnification × 200.) F, Expression of mRNA for CD21L in each of the 12 RA synovial tissues, as determined by quantitative real-time polymerase chain reaction. Tissue sources were Leydenburg Hospital (LB) and Leiden University Medical Center (LU).

To confirm the presence of lymphoid follicles and to establish the type of infiltrate in the CD21L-negative tissues, we performed immunofluorescence staining using antibodies specific for T cells (CD3), B cells (CD19), and the FDC marker CD21L (Figure 1). Tissues with marked expression of CD21L mRNA indeed showed the typical organization of cellular infiltrates of T cells surrounding a B cell area containing FDCs, thus resembling structures normally observed in lymph nodes.

In the remaining 8 tissues that were CD21L-negative by real-time PCR, no CD21L-expressing FDCs could be detected by immunofluorescence, which supports the lack of CD21L expression as determined by real-time PCR. These tissues could be further subdivided into 4 tissues that contained T cell and B cell aggregates and 4 tissues that showed a diffuse type of infiltrate. The typical localization of CD8 cells outside the B cell area of the lymphoid follicles has been reported previously in RA (27).

Distinctive cytokine and chemokine (receptor) expression in tissues with ectopic lymphoid structures.

To further draw parallels between developmental processes and inflammatory reactions, we performed real-time PCR experiments to evaluate mRNA expression levels of molecules that have been implicated in the development of lymph nodes (Figure 2). We confirmed the previously described increased expression of LTα, LTβ, CXCL13, CCL21, and CCR7 in RA tissues containing ectopic lymphoid structures, whereas mRNA encoding the LTβ receptor was equally expressed in all synovial tissues (results not shown) (2, 15–17).

Figure 2.

Distinct chemokine and chemokine receptor expression in the 3 rheumatoid arthritis tissue types (those with follicular infiltrates [Foll; n = 4], those with aggregated infiltrates [Aggr; n = 4], and those with diffuse infiltrates [Diff; n = 4]). Real-time polymerase chain reaction data are expressed relative to GAPDH. Values are the mean and SEM of 4 samples per group. ∗ = P < 0.05; ∗∗ = P < 0.01; ∗∗∗ = P < 0.001 versus tissues containing follicular infiltrates.

These cytokines and chemokines are essential during normal lymph node development. We had now established that CXCR5, the receptor for CXCL13, is also increased in lymphoid follicle–positive tissues. Another key role in lymphocyte trafficking to secondary lymphoid organs is played by CCR7 and its ligands CCL19 and CCL21, which exhibit chemotactic activity for T cells, B cells, and mature dendritic cells. We confirmed the increased expression of CCR7, and we also showed that the other CCR7 ligand CCL19 is increased in these tissues as well.

These results confirm the previously described chemokine expression levels in germinal center–containing RA synovial tissues. In addition, this is the first demonstration of the elevated expression of chemokines CXCL12 and CCL19 and of chemokine receptors CXCR4 (receptor for CXCL12) and CXCR5 (receptor for CXCL13) in these tissues.

Differential activity of multiple processes as revealed by large-scale gene expression profiling.

After having established that despite the small sample size, the expression levels of genes of importance for lymphoid tissue development were consistent with published data, we next analyzed large-scale gene expression data by microarrays. SAM analysis was used to identify genes that are expressed at significantly different levels between the 3 types of tissues (multiclass analysis). In this analysis, we included the real-time PCR data. We detected 734 cDNA that were expressed at significantly different levels between the 3 tissue types (at a false discovery rate of <5%). To visualize the results, we performed hierarchical clustering of these genes, positioning genes with a correlated expression profile across the arrays in adjacent rows (Figure 3A).

Figure 3.

Statistical analysis of large-scale gene expression profiles in patients with rheumatoid arthritis (RA). Significant genes were hierarchically clustered (using Cluster and TreeView software) to show the correlated expression profiles. A, Graphic overview of the genes that showed significantly different expression in the 3 tissue types (those with follicular infiltrates [Foll; n = 4], those with aggregated infiltrates [Aggr; n = 4], and those with diffuse infiltrates [Diff; n = 4]), as analyzed by multiclass Significance Analysis of Microarrays (SAM). Cluster A is the immune response genes, cluster B the extracellular matrix (ECM) genes, and cluster C the complement/growth factor genes. B, Graphic overview of the genes that showed significantly different expression in 2 of the tissue types (those with follicular infiltrates [n = 4] and those with aggregated infiltrates [n = 4]), as analyzed by 2-class SAM. Red indicates relatively high expression, green indicates low expression, black indicates intermediate expression, and gray indicates missing data. Tissue sources were Leydenburg Hospital (LB) and Leiden University Medical Center (LU).

This analysis revealed differential expression of genes involved in several processes. Cluster A represents genes that are expressed at higher levels in tissues with lymphoid follicles, including genes involved in the adaptive immune response, such as those involved in antigen presentation (HLA class I and II molecules), and immunoglobulins. Chemotactic activity is indicated by the elevated expression of CCL4L/macrophage inflammatory protein 1β (MIP-1β), CXCL5, CXCL13, IL-16, CXCL12, CXCR4, and CXCR5. The JAK/STAT pathway was also overrepresented in the tissues with lymphoid follicles, as indicated by the enhanced expression of STAT-1, STAT-3, STAT-6, and protein tyrosine phosphatase N6/SH2 domain–containing phosphatase 1. Interestingly, a cytokine receptor that is capable of activating the JAK/STAT pathway and is of crucial importance in lymph node development, the IL-7 receptor, as well as its coreceptor IL-2Rγ, were also expressed at increased levels in the follicular tissues.

We identified proangiogenic and antiangiogenic factors that support the differential formation of new blood vessels in the tissue types. The proangiogenic factor TEK tyrosine kinase was preferentially expressed in tissues with lymphoid follicles. In contrast, diffusely infiltrated tissues showed enhanced expression of the antiangiogenic factors thrombospondin 1 and thrombospondin 2, along with thrombospondin 3, indicating repression of angiogenesis (28).

Diffusely infiltrated tissues did not express genes involved in inflammation; instead, these tissues showed signs of extracellular matrix remodeling, as indicated by the expression of matrix metalloproteinase 9, different types of collagen (types I, IV, V, VI, XI, and XII), secreted protein, acidic and rich in cysteine/osteonectin, and laminin α2 (Figure 3A, cluster B). The tissues with aggregated types of infiltrates shared some gene expression levels with germinal center tissues and other genes with diffusely infiltrated tissues. However, they showed a selectively up-regulated expression of genes involved in complement activation, such as clusterin and C1q α, β, and γ polypeptides (Figure 3A, cluster C).

Selective expression of genes in tissues with lymphoid follicles.

When gene expression levels and cellular composition were compared, tissues with lymphoid follicles showed greater similarity to aggregated types of infiltrates than to diffuse infiltrates. We therefore analyzed by SAM the differences between the aggregated and lymphoid follicle–positive tissues (Figure 3B). It turned out that 74 genes were expressed at significantly different levels, most of them showing enhanced expression in tissues with lymphoid follicles, while only 5 genes were expressed at lower levels (matrix γ-carboxyglutamic acid protein and 4 genes of unknown function). Increased expression was identified for several chemokines: CXCL13, CCL19, CCL21, and monocyte chemoattractant protein 4 (MCP-4)/CCL13, the β-chemokines MIP-1α and RANTES, the chemokine receptors CXCR4, CCR7, and CXCR5, and a molecule important for signaling of several chemokine receptors, regulator of G protein signaling 1. B cell activation was indicated by the increased expression of several immunoglobulin heavy and light chains. The expression of hemogen may suggest the presence of precursor stem cells (29). Among the cytokines, LTβ was listed, while the only cytokine receptor pair that came out as significant was the IL-7R/IL-2Rγ with IL-7, indicating its importance in follicle structures in RA.

Findings of pathway analysis.

To gain more insight into the biologic role of the gene expression signatures, we performed pathway level analysis, using gene set enrichment analysis (25). For this analysis, real-time PCR data for cytokines and chemokines were again combined with the microarray data, including IL-7R, IL-7, and the IL-2Rγ chain. We observed a number of significant pathways, represented by the expression profiles of tissues containing lymphoid follicles, as compared with tissues lacking these structures (Table 2). The JAK/STAT signaling pathway was the most significant pathway, followed by the T cell receptor signaling pathway, the Ras-independent pathway in natural killer cell–mediated cytotoxicity, Fcε receptor type I signaling in mast cells, IL-7 signal transduction, the B cell receptor signaling pathway, the IL-2Rβ chain in T cell activation, and the costimulatory signal during T cell activation. Figures 4A and B present a graphic overview of the JAK/STAT and IL-7 signal transduction pathways.

Table 2. Significant pathways in rheumatoid arthritis synovial tissues containing lymphoid follicles*
 Size, bpPFDR q value
  • *

    Gene set enrichment analysis was performed on all genes expressed by tissues with follicular infiltrates as compared with tissues lacking these structures, in order to determine significant pathways. FDR = false discovery rate; NK = natural killer; FcεRI = Fcε receptor type I; IL-7 = interleukin-7; BCR = B cell receptor; IL-2Rβ = interleukin-2 receptor β.

JAK/STAT signaling pathway310.0140.07
T cell receptor signaling pathway140.0280.10
Ras-independent pathway in NK cell–mediated cytotoxicity80.0000.10
FcεRI signaling in mast cells90.0000.12
IL-7 signal transduction80.0250.17
BCR signaling pathway80.0350.18
IL-2Rβ chain in T cell activation110.0000.19
Costimulatory signal during T cell activation120.0480.21
Figure 4.

Results of pathway analysis in rheumatoid arthritis synovial tissues, as determined by gene set enrichment analysis. Gene set enrichment analysis was performed on all genes expressed by tissues with follicular infiltrates (Foll) as compared with tissues lacking these structures, but containing aggregated (Aggr) or diffuse (Diff) infiltrates. See Table 2 for the significant pathways in tissues containing lymphoid follicles. The interleukin-7 (IL-7) signaling pathway was found to be the most important cytokine-driven process in follicular tissues. Shown is a detailed graphic overview of A, the IL-7 signal transduction pathway and B, the JAK/STAT signaling pathway. Red indicates high expression; blue indicates low expression.

Synovial localization of IL-7.

Because of the crucial role of IL-7 in normal lymphoid organ development, we determined the localization of IL-7 in diffuse and aggregated infiltrates and lymphoid follicle–containing tissues. We confirmed the presence of IL-7 in some of the fibroblast-like synoviocytes and macrophages and in blood vessel endothelial cells (results not shown) (30). The diffusely infiltrated synovial tissues showed a patchy staining pattern, whereas the aggregate-containing and lymphoid follicle–containing tissues showed a more consistent IL-7 staining throughout the whole tissue. In contrast to the strictly cellular staining of IL-7 in tissues with diffuse and aggregated infiltrates, a large proportion of IL-7 in lymphoid follicle–containing tissues was extracellular, with a reticular pattern. Therefore, we determined the extracellular matrix component type IV collagen to identify the location of IL-7. IL-7 was localized in an extracellular matrix formed by a double-layered circular structure around the B cell follicle. Similar structures were identified in tonsils (Figures 5C and D). Such stainings were not found in tissues with diffuse and aggregated infiltrates (Figures 5A and B). Double staining for IL-7 and laminin showed the same pattern (results not shown).

Figure 5.

Immunofluorescence staining of rheumatoid arthritis synovial tissues and tonsil for interleukin-7 (IL-7) and type IV collagen. Staining for IL-7 (red) and type IV collagen (green) in synovial tissues containing A, diffuse infiltrates, B, aggregated infiltrates, and C, lymphoid follicles is shown in comparison with staining in D, tonsil. The B cell region (B) (enclosed by the broken line) and the T cell region (T) were localized by B cell/T cell staining of consecutive slides. (Original magnification × 20 in A, B, and C; × 10 in D.)


We previously reported that expression profiles of synovial tissues from RA patients show a high degree of heterogeneity (18, 19). In this study, we analyzed the expression profiles related to the type of tissue infiltrates in synovial tissues and revealed a correlation of several cytokines and chemokines with the existence of lymphoid follicular structures in the synovium of RA patients.

Recently, it was demonstrated that there is increased angiogenesis in aggregated and follicular infiltrates within the synovium, compared with diffusely infiltrated synovium, which is related to a reduced expression of the angiogenic inhibitor thrombospondin 2 (28). We confirmed and extended these observations by showing increased expression of the proangiogenic factor TIE/TEK, the receptor for angiopoietins, in follicular synovium and decreased expression of the antiangiogenic factors thrombospondins 1 and 2, accompanied by reduced expression of thrombospondin 3, in tissues with lymphoid tissues and aggregated types of infiltrates.

The present study confirms the increased expression of CXCL13, CCL21, CCR7, LTα, and LTβ in RA tissues that contain lymphoid follicles (2, 15–17). In addition, we observed increased expression of the chemokines CXCL12, CCL19, MCP-4/CCL13, the CCR5 ligands MIP-1α and RANTES, and the chemokine receptors CXCR4 (ligand for CXCL12) and CXCR5 (the receptor for CXCL13) in these tissues. These results are consistent with the current model of normal lymph node development, in which B cell and T cell homing to secondary lymphoid tissues is dependent on constitutively expressed CCL19 and CCL21 in the T cell zone, attracting CCR7+ cells, and CXCL13 in the follicular compartment, attracting CXCR5+ cells (13, 31, 32). Thus, the enhanced expression of CXCL13 in tissues with ectopic lymphoid follicles may explain the elevated levels of CXCR5 mRNA in these tissues, due to the influx of CXCR5+ B cells and activated T cells. These findings are also consistent with the observation that both CXCR5 and CXCL13 are necessary for the formation of B cell follicles in mice (33).

LTα1β2 causes growth and maturation of the follicular stromal cells and up-regulation of FDC markers (34). It has been postulated that prolonged interaction of LTα1β2 with the LTβR on stromal cells will, over time, lead to a gradual shift from most cells using the classic NF-κB signaling pathway at early time points to an increasing number of cells initiating an alternative NF-κB pathway downstream of the LTβR (35). As a consequence, sustained levels of LTα1β2 may tip the balance from inflammatory to homeostatic chemokines, resulting in the predominant production of chemokines that are implicated in lymphoid organogenesis and homeostasis, such as CXCL13, CCL21, and CCL19 (36). Thus, a local microenvironment that permits lymphoid organization becomes established.

If prolonged ligation of LTβR is the critical factor in the development of both lymphoid organs and germinal center structures during chronic inflammation, then the question arises how the sustained expression of LTα1β2 is realized in the follicular infiltrates. Blockade of IL-7R early during development totally blocks the induction of LTα/β on lymphoid tissue inducer cells, and thus, all subsequent events that depend on LTα/β and are necessary for the further formation of lymphoid organs (37). Furthermore, ectopic expression of IL-7 in mice induces the development of lymphoid infiltrates at the site of expression, while in the absence of IL-7, development of lymphoid lineages and lymph nodes is severely affected (38–40). The enhanced transcript levels of IL-7 and the IL-7R/IL-2Rγ chain in the lymphoid follicle–containing synovial tissues are therefore likely to contribute to the increased LTα1β2 expression, thus creating an environment that is beneficial for the attraction and organization of leukocytes within the follicular structure. In support of this, we found a strong correlation between IL-7 mRNA expression and LTβ expression (r = 0.90, P < 0.0001) (data not shown).

Consistent with our findings, enhanced levels of IL-7 have been detected in synovial fluid from a subgroup of RA patients (approximately one-third of the RA patients) as compared with synovial fluid from osteoarthritis (OA) patients (30), while fibroblast-like synoviocytes from a subpopulation of RA patients produce increased amounts of IL-7 (41) as compared with fibroblast-like synoviocytes from OA patients. In this study, we show that increased levels of IL-7 and the IL-7R are associated with tissues that contain lymphoid structures.

IL-7 may also contribute to the inflammatory process in RA. It has been demonstrated that interferon-γ and tumor necrosis factor α are produced in synovial fluid mononuclear cells upon treatment with IL-7 (42).

Binding of IL-7 to the IL-7Rα/IL-2Rγ chain results in activation of the JAK/STAT pathway (43). We identified an up-regulation of this pathway in tissues with lymphoid follicles. In fact, within our list of genes of the JAK/STAT pathway, IL-7R was the most significantly up-regulated cytokine receptor gene, followed by its coreceptor, IL-2Rγ chain, suggesting that the interaction between IL-7 and IL-7R contributed the most to this pathway and, thus, determines the cytokine specificity of this pathway. There was no differential mRNA expression for the alternative ligand of the IL-7R, thymic stromal lymphopoietin protein (data not shown), suggesting that IL-7 is the operating ligand for the IL-7Rα chain within these infiltrates.

The present study confirms that both fibroblast-like synoviocytes and macrophages contribute to the production of IL-7 (30). There was also marked IL-7 staining of blood vessels, which may relate to the capacity of IL-7 to bind to extracellular matrix molecules, such as heparan sulfate proteoglycans (44). In tissues with lymphoid follicles, we showed for the first time that IL-7 is colocalized with the extracellular matrix components type IV collagen and laminin in a circular structure surrounding the B cell follicle, a phenomenon we also observed in lymphoid organs, such as the tonsil. This structure is reminiscent of the cortical ridge identified at the T cell–B cell interface in murine lymph nodes (45), providing a reticular network of extracellular matrix fibers that support the cellular architecture. The cortical ridge is enriched for dendritic cells that present antigen to T cells. Since antigen-specific B cell and T cell interactions occur at this B cell–T cell interface, IL-7 may contribute to the survival of T cells (46), thus sustaining B cell activation. In addition, interaction between extracellular matrix–bound IL-7 and T cells may induce the adhesive properties of these cells (47), which suggests the possibility of involvement of IL-7 in the arrangement of T cells around the B cell follicle.

The notion that IL-7 plays a crucial role in the pathogenesis of arthritis is supported by observations in a spontaneous arthritis model. In gp130-mutated mice, increased gp130/STAT-3 signaling in nonhematopoietic cells is responsible for the production of IL-7, which, in turn, is crucial for development of the disease (48). We suggest that the observed expression of IL-7 in fibroblast-like synoviocytes could be the driving force for generating an environment in which B cells and T cells can survive, interact, and organize into tertiary lymphoid structures.

From the list of genes and pathways distinguishing tissues with lymphoid follicles from tissues lacking these structures, it has become clear that several processes take place that act in concert to maintain the highly organized structures. Overall, the results point to a crucial role of the interaction between LTα/β and LTβR, the interaction between the chemokines CXCL13, CXCL12, CCL19, and CCL21 and their respective receptors CXCR5, CXCR4, and CCR7, and in particular, the IL-7 signaling pathway in organizing and maintaining lymphoid follicles in the RA synovium.


Dr. van der Pouw Kraan had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Study design. Mebius, van der Pouw Kraan.

Acquisition of data. Timmer, Baltus, Huizinga, Verweij, van der Pouw Kraan.

Analysis and interpretation of data. Timmer, Baltus, Vondenhoff, Huizinga, Tak, Mebius, van der Pouw Kraan.

Manuscript preparation. Timmer, Baltus, Huizinga, Tak, Verweij, Mebius, van der Pouw Kraan.

Statistical analysis. Van der Pouw Kraan.