Scholarly article on topic 'Altered Innate Lymphoid Cells subsets in human lymph node biopsies during the at risk and earliest phase of rheumatoid arthritis'

Altered Innate Lymphoid Cells subsets in human lymph node biopsies during the at risk and earliest phase of rheumatoid arthritis Academic research paper on "Clinical medicine"

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Arthritis & Rheumatology
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Academic research paper on topic "Altered Innate Lymphoid Cells subsets in human lymph node biopsies during the at risk and earliest phase of rheumatoid arthritis"

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Arthritis & Rheumatology DOI 10.1002/art.39811

Altered Innate Lymphoid Cells subsets in human lymph node biopsies during the at risk and earliest phase of rheumatoid arthritis

Javier Rodriguez-Carrio1'2'3*, MSc, PhD, Janine S Hàhnlein13*, MSc, Tamara H Ramwadhdoebe13, MSc, Johanna F Semmelink1,3, MSc, Ivy Y. Choi1, MD, Krijn P van Lienden4, MD, PhD, Mario Maas4, Prof., MD, PhD, Danielle M Gerlag15, MD, PhD, Paul P Tak16, Prof., MD, PhD, Teunis B H Geijtenbeek3, Prof. PhD, Lisa G M van

Baarsen1,3, PhD.


1Amsterdam Rheumatology & immunology Center (ARC), Department of Clinical Immunology and Rheumatology, Academic

Medical Center, University of Amsterdam, Amsterdam, Netherlands

2Area of Immunology, Department of Functional Biology, University of Oviedo, Asturias, Spain

department of Experimental Immunology, Academic Medical Center, University of Amsterdam, Amsterdam, Netherlands

"Department of Radiology, Academic Medical Center, University of Amsterdam, Amsterdam, Netherlands

5Current affiliation: Clinical Unit Cambridge, GlaxoSmithKline, Cambridge, U.K.

6Current affiliations: Ghent University, Ghent, Belgium and University of Cambridge, Cambridge, U.K. and GlaxoSmithKline,

Stevenage, U.K.

*authors contributed equally

Corresponding author:

Lisa G. M. van Baarsen, PhD

Amsterdam Rheumatology & immunology Center (ARC)

Department of Clinical Immunology and Rheumatology and the

Department of Experimental Immunology

Academic Medical Center / University of Amsterdam

Meibergdreef 9, Amsterdam, 1105 AZ

The Netherlands


Running title: ILCs subsets in LN biopsies obtained during the earliest phases of rheumatoid arthritis Conflict of interest: none of the authors has any potential financial conflict of interest related to this manuscript.

This article has been accepted for publication and undergone full peer review but has not been through the copyediting, typesetting, pagination and proofreading process which may lead to differences between this version and the Version of Record. Please cite this article as an 'Accepted Article', doi: 10.1002/art.39811 © 2016 American College of Rheumatology

Received: Mar 31, 2016; Revised: Jun 01, 2016; Accepted: Jul 07, 2016

This article is protected by copyright. All rights reserved.


Objectives: Innate lymphoid cells (ILCs) are emerging mediators of immunity and accumulation of inflammatory ILC populations can occur in inflammatory-mediated conditions. Since early lymph node (LN) activation has been rheumatoid arthritis (RA), we aimed to investigate the frequency and distribution of ILCs in LN biopsies during the earliest phases of RA.

¡: Twelve early RA patients, 12 individuals with IgM-rheumatoid factor and/or anti-citrullinated protein antibodies without arthritis (RA-risk group) and 7 healthy controls underwent ultrasound-guided inguinal LN biopsy. ILCs subsets and the expression of VCAM and ICAM by LN endothelial cells and fibroblasts were analyzed by flow cytometry.

Results: Although no differences in total ILCs (Lin-CD45+/lowCD127+) frequency were found, the distribution of the ILC populations changed among groups. RA patients showed lower LTi (c-Kit+NKp44-ILCs) and increased both ILC1 (c-Kit:NKp44-ILCs) and ILC3 (c-Kit+NKp44+ILCs) counts compared with controls (p<0.001, p<0.050 and p<0.050, respectively). RA-risk individuals exhibited increased ILC1 frequency compared with controls (p<0.01). LTi paralleled the expression of adhesion molecules on endothelial and fibroblastic cells.

Conclusions: Already during the at-risk and earliest phase of RA, the ILC distribution in LN changes from a homeostatic towards a more inflammatory profile, thereby supporting a role for ILC in RA pathogenesis.

s: innate lymphoid cells, rheumatoid arthritis, lymph node, pre-clinical arthritis, autoimmunity

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Over the last years, there has been a growing interest in the biology of the innate lymphoid cells (ILCs) as they have been reported to be crucial mediators involved in immunity and tissue remodelling. ILCs share three main characteristics: (i) the absence of somatically rearranged antigen receptors, (ii) a lack of myeloid and dendritic cell phenotypical markers and (iii) their lymphoid morphology. (1) ILCs are not a single population but three main subsets can be identified on the basis of their extracellular markers as well as their transcription factors and cytokine profile: group 1 ILCs (ILC1; comprising classical NK cells and IFNY-producing ILC1), group 2 ILCs (ILC2; producers of Th2 cytokines) and group 3 ILCs (ILC3; including lymphoid tissue-inducers (LTi) and interleukin (IL)-22 and IL-17 producing ILC3) (1).

These subsets are not totally stable cell populations and a certain degree of functional plasticity among them has been described, mainly in response to inflammatory stimuli (2). ILCs can orchestrate inflammation, innate and adaptive responses and homeostatic processes throughout the body (3). LTi are pivotal players of lymphoid tissue development and homeostasis, since they can closely interact with stromal cells leading to upregulation of adhesion molecules on stromal cells and the production of homeostatic chemokines, thereby promoting the attraction and retention of additional cell types (4). However in adult lymphoid tissues, despite being present and capable to secrete different mediators (5), little is known about their function. In addition, whether LTi are altered in inflammatory conditions remains unknown. In contrast, ILC1, ILC2 and ILC3 have been reported to promote immunity to infection in mucosal and surface barriers [reviewed in (1,3)]. Excessive accumulation and/or activation of specific ILC populations has been related to the pathogenesis of a number of diseases such as inflammatory bowel disease, psoriasis and asthma (2,3,6). Some evidence suggest that experimental targeting of these subsets leading to decreased ILC counts resulted in disease alleviation (7), thereby supporting their role in these conditions.

We hypothesize that an altered distribution of ILC subsets may have a role in the pathogenesis of chronic immune-mediated autoimmune diseases, like rheumatoid arthritis (RA). Since in RA, the production of autoantibodies precedes the development of signs and symptoms of clinical disease (8), we have set up a system to study the earliest phases of RA by selecting those individuals who are positive for autoantibodies but have no clinically apparent disease. Such individuals have recently been defined as having a systemic autoimmunity associated with RA (RA-risk) as recommended by the Study Group for Risk Factors for RA (SGRFRA) under the auspices of the EULAR (European League Against Rheumatism) Standing Committee of Investigative Rheumatology (ESCIR) (9). Since the production of autoantibodies is initiated in lymphoid tissue, it is hypothesized that lymph node (LN) activation precedes synovial tissue inflammation. We studied the frequency and distribution of ILC subsets in LN biopsies obtained during the RA-risk phase and during established disease and from healthy volunteers. Overall, our results show an inflammatory-biased ILC profile which may be associated with an impaired LN microenvironment in the earliest phases of RA.

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METHODS Study subjects

We included 12 individuals with systemic autoimmunity associated with RA (RA-risk), which was defined by the presence of IgM rheumatoid factor (IgM-RF) and/or anti-citrullinated protein antibodies (ACPA) positive in subjects with arthralgia but without any evidence of arthritis (9). IgM-RF was measured using IgM-RF ELISA (Sanquin, Amsterdam, the Netherlands (upper limit of normal (ULN) 12.5 IU/mL)) until December 2009 and thereafter using IgM-RF ELISA (Hycor Biomedical, Indianapolis, IN (ULN 49 IU/mL). ACPA was measured using anti-CCP2 ELISA CCPlus (Eurodiagnostica, Nijmegen, the Netherlands (ULN 25 kAU/L)). After a median follow up time of 38.9 months (12.0-51.4 (IQR)) none of these RA-risk individuals had developed RA yet. We included 12 early RA patients, based on American College of Rheumatology and European League Against Rheumatism (ACR/EULAR) 2010 criteria, naive for disease-modifying antirheumatic drugs (DMARD) and biologicals with a disease duration (defined by having an arthritis in any joint) less than one year. Patients and RA-risk individuals were compared to seven seronegative healthy individuals (HC). To be considered as HC, individuals were not allowed to have a history of recent viral infection, autoimmunity or malignancy as well as no present or previous use of DMARDs, biologicals or experimental drugs. The study was approved by the institutional review board of the Academic Medical Center, and all study subjects gave written informed consent. Table 1 shows the demographics of the included subjects.

Sample processing and flow cytometry analysis

All study subjects underwent an ultrasound-guided inguinal LN needle biopsy as previously described (10). Freshly collected LN biopsies were put through a 70 |im cell strainer (BD Falcon, Becton Dickinson, Breda, Netherlands) to obtain a single cell suspension. Then cells were washed in PBA buffer (PBS containing 0.01% NaN3 and 0.5% bovine serum albumin (BSA) (both Sigma Aldrich, Zwijndrecht, Netherlands) and stained extracellular for 30 minutes at 4°C in PBA with directly labelled antibodies. For ILCs we used antibodies against CD3 FITC (clone CLB-T3/2, 16A9, Sanquin, Amsterdam, Netherlands), CD14 FITC (clone CLB-mon/1, 8G3, Sanquin), CD19 FITC (clone HIB19, eBiosciences, Vienna, Austria), CD34 FITC (clone 8G12, Becton Dickinson (BD) Biosciences, Breda, Netherlands), CD127 APC-eFluor780 (clone eBioRDR5, eBiosciences), CD45 V500 (clone HI30, BD Biosciences), CD117/c-kit PE (clone 104D2, eBiosciences) and CD336/NKp44 AlexaFluor647 (clone P44-8, Biolegend, London, UK). For LN fibroblasts and endothelial cells we used CD45 V500, Podoplanin (gp38) AlexaFluor647 (clone NC-08, Biolegend), CD31 (PECAM-1) APC eFluor780 (clone WM-59, eBiosciences), ICAM-1 (CD54) PerCP (clone 1H4, EXBIO, Huissen, Netherlands) and VCAM-1 (CD106) (clone STA, eBiosciences). Cells were measured on a FACS Canto II (BD Biosciences) and data were analyzed using FlowJo software (FlowJo, Ashland, OR).


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Not normally distributed data are presented as median with interquartile range. Differences between study groups were analyzed using Kruskal-Wallis followed by a post Dunn's test. GraphPad Prism software (V.5, La Jolla, California, USA) was used for statistical analysis. P-values<0.05 were considered statistically significant.

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To explore the main ILC subsets, LN cell suspensions were analyzed by flow cytometry following a gating strategy based on phenotypic markers that characterize ILCs subpopulations (1) (Figure 1). First, lineage-negative events were gated and their expression of CD45 and CD127 was assessed, after which the total ILC population was defined as Lin-CD45+/lowCD127+. Next, the ILCs subsets were distinguished based on their al expression of c-Kit and NKp44, thus being lymphoid tissue-inducers (LTi) defined as c-Kit+NKp44-, c-Kit+NKp44+ were considered as ILC3. Finally, c-Kit/NKp44 double-negative cells were considered as ILC1. Lymphoid morphology was confirmed for each subpopulation. Then, CD69 expression was analyzed in total ILCs as well as in individual ILC subsets, using the Lin-CD45- population as the negative control.

First, we observed that the frequency of total ILCs out of Lin- events was not different among the three study groups (HC: 0.19(0.03-0.28)%, RA-risk: 0.06(0.02-0.20)%, RA: 0.02(0.01-0.17)%; p=0.301). Also no difference in the Lin- population was found (p=0.134). Since an important contribution of variability of ILCs numbers was noted as probably due to variability in size of the LN biopsy, the frequency of total ILCs within the total number of cells collected (taking into account the frequency of Lin- events) was calculated, revealing no differences among groups (p=0.510). Next, we analyzed the relative frequencies of the different ILC subsets and, interestingly, we found that their distribution within the total ILC population differed between controls, RA-risk individuals and RA patients (Figure 2A). The LTi population, the most abundant ILC subset, was significantly decreased in RA patients compared with HC and RA-risk individuals, exhibiting a progressive decline according to disease status. On the other hand, ILC1 cells were significantly increased in both RA-risk and RA patients and ILC3 cells were significantly increased in RA compared with RA-risk individuals (Figure 2A). The frequencies of ILC subsets were not related to clinical or demographic parameters (data not shown). Additionally, due to its role in cell activation and retention as well as their relevance on ILC subsets (11), higher CD69 being associated with enhanced functionality, we evaluated the expression of CD69 on these subsets. A higher frequency of CD69+ILCs was found in HC (Figure 2B). When individual ILC subsets were examined, this pattern was only observed in LTi, while ILC1 and ILC3 showed no significant differences. Overall, these results support that the relative distribution of ILC subsets and their expression of CD69 is altered in LN during the at-risk and earliest phase of RA.

Finally, since LTi have been described to influence other non-lymphoid populations (3,12), we aimed to study whether changes in LTi numbers may be related to changes in endothelial and fibroblastic subsets present within the LN. Therefore, VCAM and ICAM expression, quantified as percentage of positive cells for each marker compared to unstained cells, by endothelial (CD45-CD31+) and fibroblastic reticular cells (FRCs, CD45-CD31-gp38+) was assessed in a subgroup of individuals (HC n=4, at risk n=2 and RA n=4). The group of individuals with paired samples did not differ to the initial group in age (p=0.700), gender (p=0.825) or disease status (p=0.419). Interestingly, LTi frequency was positively with the expression of VCAM (r=0.766, p=0.015) and ICAM (r=0.593,


renti. whereas

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p=0.070) on LN endothelial cells. Similarly, LTi numbers correlated with VCAM expression on FRCs (r=0.740, p=0.014). LTi numbers were not related to the frequency of endothelial or FRCs populations (both p>0.050).

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Our data revealed that ILC distribution changes within the LN compartment during the at-risk and earliest phase of RA. To the best of our knowledge, this is the first time ILC disturbances within LN are reported in RA. Although so far none of the RA-risk individuals developed arthritis, these individuals produce autoantibodies specific for RA and thus display features of systemic autoimmunity associated with RA, hence suggesting a role for ILCs during RA development. Moreover, frequency of LTi was associated with the expression of adhesion molecules by stromal cells, which may suggest a potential crosstalk between ILCs and the stromal cell compartment. Since the pool of total ILC was unchanged among the different study groups, our results highlight a role for an ILC imbalance in LN as an early event in RA pathogenesis.

During systemic autoimmunity associated with RA, ILCs within the LN microenvironment seem to exhibit a shift from a more "homeostatic" profile, characterized by a higher frequency of LTi, towards a more "inflammatory/activated" one, characterized by an increased frequency of potentially proinflammatory cytokine-producing ILC subsets (ILC1 and ILC3). Taking into account that NKp44 can be considered as an activation marker, and the fact that RA patients exhibit features of an active adaptive immune response, a link between LN activation and ILC imbalance is supported. Interestingly, dysregulation of ILC subsets and increased ILC3 counts have been recently reported in skin biopsies from psoriasis patients (13). Similarly, increased frequencies of ILC1 and ILC3 frequency has been reported in mucosal or surface barriers in other diseases (2,3). Overall, these lines of evidence suggest a role for ILC accumulation as a pathogenic mechanism in tissue damage in the end-stages of the disease. Of interest, our findings revealed that skewed ILC distribution is an early event in RA pathogenesis.

Moreover, biased ILC distribution is found in the LN, a place where the adaptive immunity is initiated, thus revealing an ILC alteration in a tissue other than the target tissue. Increased frequency of cytokine-producing ILCs has been associated with pathogenic outcomes (2,7,14), whereas their selective inhibition was found to be related to disease abrogation (7,15). Similarly, excessive LN activation may lead to LN damage, which can be restored by LTi (12). Of interest, not only from a structural point of view but recent evidence suggest that LTi may regulate immune cell homeostasis within LN (16,17), including maintenance of T cell memory (18). Thus, the ILC profile may be a pivotal player for regulation of immune homeostasis and function (19). It is challenging to determine the underlying mechanisms driving this ILC imbalance, although changes in cytokine production within the LN microenvironment as a consequence of LN activation preceding RA development (20) may be key in the orchestration of ILC differentiation (2). Interestingly, although evidence is limited, some cytokines altered during LN activation (20,21) are related to certain ILC subsets.

It is difficult to ascertain whether the altered ILC distribution can have an impact on the function of the LN microenvironment from a mechanistic point of view. However, our paired analysis of endothelial and fibroblastic subsets provides some insight. One of the main functions of LTi is the production of lymphotoxin a1p2 (LTaP),

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which promotes the expression of adhesion molecules on stromal cells (2,4), thereby promoting migration and colonization of haematopoietic cells during LN development or after injury. Accordingly, our results highlight an association between LTi frequency and the expression of VCAM and ICAM on endothelial and stromal cells. This finding may be in line with current evidence linking LTi with LN homeostasis, where LTi-derived LTap has a pivotal role. Abrogation of LTap signalling leads to decreased expression of homeostatic chemokines and survival factors by stromal cells, which is essential for LN reestablishment after infections (12). Thus, a disturbed capacity ® of resolving an infection might lead to activation of autoreactive lymphocytes. Therefore, it may be speculated that the reduced LTi counts in RA patients might reflect an impaired function of LN remodelling. Hence, relatively low LTi numbers may aid to an autoimmune prone LN microenvironment through their effects on stromal cells, however this warrants further functional studies. Moreover, it is interesting to note that LTi were not only altered in frequency, but also lower CD69 expression was found in RA-risk and RA patients. Interestingly, high frequency of CD69+ILCs in blood has been related to a better outcome upon haematopoietic stem cell transplantation (11), thus suggesting a link between CD69 expression on ILCs and protective/reparative mechanisms. The decreased LTi numbers and lower CD69 expression is in line with its proposed role as marker for cell retention (22). However, what triggers LTi to downregulate CD69 and potentially cause egress of LTi remains to be determined.

Since we did not analyzed group 2 ILCs, it could be that ILC frequencies, especially ILC1, are overestimated. Another point that deserves to be remarked is the ILC nomenclature adopted in this manuscript. Since there is no consensus about whether adult LTi resemble their fetal counterparts, some authors have proposed alternative terms (LTi-like or NCR-ILC3 cells). However, we preferred to follow the recently proposal for uniform ILC nomenclature by leading experts (1). Actually, the observed association between the LTi frequency and the expression of adhesion molecules on stromal cells, the central role for LTi, supports our decision. ILC functionality in vitro may not be representative to that of in vivo, and the small sample size of the LN needle biopsies hampers isolation of low frequent ILC subsets, which makes functional studies rather challenging. However, our findings warrants further additional studies of ILC functionality.

Overall, the current study is the first to show an imbalance between homeostatic and inflammatory ILC subsets in lymph node biopsies obtained during the at-risk and earliest phase of RA, which may underlie the earliest steps in RA pathogenesis.

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We especially thank the study participants, the radiology department at the AMC for lymph node sampling, the flow cytometry facility at the Haematology department at AMC and the AMC KIR technicians for sample processing. The authors would like to thank Prof. Reina Mebius and Yotam Bar-Ephraim (VUMC, Amsterdam) for their critical revision of the manuscript.

JR-C is supported by fellowships from FPU program (Spanish Ministry of Education) and EFIS-IL short term program. This study was supported by the IMI EU funded project BeTheCure (nr115142), FP7 HEALTH programme under the grant agreement FP7-HEALTH-F2-2012-305549 (Euro-TEAM), Dutch Arthritis Foundation grant 11-1-308 and The Netherlands Organisation for Health Research and Development (ZonMw) Veni project 916.12.109.

Author contributions

All authors have read the journal's policy on disclosure of potential conflicts of interest. All authors were involved in drafting the manuscript or revising it critically for important intellectual content and all the authors gave their approval of the final version of the manuscript to be published. The authors have not financial conflict of interest.

Study conception and design: Gerlag, Tak, van Baarsen.

Acquisition of data: Rodriguez-Carrio, Hähnlein, Ramwadhdoebe, Semmelink, Choi, van Lienden, Maas, Gerlag, Geijtenbeek, Tak, van Baarsen.

s and interpretation of data: Rodriguez-Carrio, Hähnlein, Ramwadhdoebe, Semmelink, Geijtenbeek,

rsen. rsen.


van Baa

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1. Spits H, Artis D, Colonna M, Diefenbach A, Santo JP Di, Eberl G, et al. Innate lymphoid cells--a proposal for uniform nomenclature. Nat Rev Immunol 2013;13:145-9.

2. Bernink JH, Peters CP, Munneke M, Velde A a te, Meijer SL, Weijer K, et al. Human type 1 innate lymphoid cells accumulate in inflamed mucosal tissues. Nat Immunol 2013;14:221-9.

3. Sanati G, Aryan Z, Barbadi M, Rezaei N. Innate lymphoid cells are pivotal actors in allergic, inflammatory and autoimmune diseases. Expert Rev Clin Immunol 2015;8409:1-11.

4. Vondenhoff MF, Greuter M, Goverse G, Elewaut D, Dewint P, Ware CF, et al. LTbetaR signaling induces cytokine expression and up-regulates lymphangiogenic factors in lymph node anlagen. J Immunol 2009;182:5439-45.

5. Lane PJL, Gaspal FM, McConnell FM, Withers DR, Anderson G. Lymphoid tissue inducer cells: Pivotal cells in the evolution of CD4 immunity and tolerance? Front Immunol 2012;3:1-7.

6. Bernink JH, Germar K, Spits H. The role of ILC2 in pathology of type 2 inflammatory diseases. Curr Opin Immunol 2014;31:115-120.

7. Powell N, Walker AW, Stolarczyk E, Canavan JB, G??kmen MR, Marks E, et al. The Transcription Factor T-bet Regulates Intestinal Inflammation Mediated by Interleukin-7 Receptor+ Innate Lymphoid Cells. Immunity 2012;37:674-684.

8. Rantapa-Dahlqvist S, Jong BAW De, Berglin E, Hallmans G, Wadell G, Stenlund H, et al. Antibodies Against Cyclic Citrullinated Peptide and IgA Rheumatoid Factor Predict the Development of Rheumatoid Arthritis. Arthritis Rheum 2003;48:2741-2749.

9. Gerlag DM, Raza K, Baarsen LGM van, Brouwer E, Buckley CD, Burmester GR, et al. EULAR recommendations for terminology and research in individuals at risk of rheumatoid arthritis: report from the Study Group for Risk Factors for Rheumatoid Arthritis. Ann Rheum Dis 2012;71:638-641.

10. Hair MJH de, Zijlstra I a J, Boumans MJH, Sande MGH van de, Maas M, Gerlag DM, et al. Hunting for the pathogenesis of rheumatoid arthritis: core-needle biopsy of inguinal lymph nodes as a new research tool. Ann Rheum Dis 2012;71:1911-2.

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13. Villanova F, Flutter B, Tosi I, Grys K, Sreeneebus H, Perera GK, et al. Characterization of innate lymphoid cells in human skin and blood demonstrates increase of NKp44+ ILC3 in psoriasis. J Invest Dermatol 2014;134:984-991.

14. Fuchs A, Vermi W, Lee JS, Lonardi S, Gilfillan S, Newberry RD, et al. Intraepithelial type 1 innate lymphoid cells are a unique subset of il-12- and il-15-responsive ifn-??-producing cells. Immunity 2013;38:769-781.

15. Perry JSA, Han S, Xu Q, Herman ML, Kennedy LB, Csako G, et al. Inhibition of LTi cell development by CD25 blockade is associated with decreased intrathecal inflammation in multiple sclerosis. Sci Transl Med 2012;4:145ra106.

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16. Dummer W, Ernst B, LeRoy E, Lee D, Surh C. Autologous regulation of naive T cell homeostasis within the T cell compartment. J Immunol 2001;166:2460-2468.

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J, Kuzin I, Moshkani S, Proulx ST, Xing L, Skrombolas D, et al. Expanded CD23(+)/CD21(hi) B cells in inflamed lymph nodes are associated with the onset of inflammatory-erosive arthritis in TNF-transgenic mice and are targets of anti-CD20 therapy. J Immunol 2010;184:6142-6150.

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22. Shioi alpha/bet

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Table 1: Demographic and clinical characteristics of the enrolled individuals.

Continuous variables are expressed as median (25th - 75th pertentile), unless otherwise stated. Categorical variables are summarized as n (%).

Healthy controls n=7

RA-risk n=12

RA patients n=12

Sex (female), Age (years), median (IQR) IgM-RF positive, n(%) IgM-RF level (kU/l), median (IQR) ACPA positive, n(%) ACPA level (kAU/l), median (IQR) ESR (mm/h), median (IQR) CRP (mg/l), median (IQR) 28 Tender Joint Count, median (IQR) 28 Swollen Joint Count, median (IQR) DAS28, median (IQR)

5 (71) 31 (28-40) 0 (0) 1 (1-1) 0 (0) 3 (1-4)

0.6 (0.3-1.4)

8 (67) 44 (34-54)

5 (42) 19 (4-144)

7 (58) 97 (3-389) 5.0 (2.0 - 8.0) 1.9 (0.6 - 5.7)

2 (1 - 2) 0 (0)

10 (83) 54 (35-60)

9 (75) 79 (17-434)

7 (58) 81 (1-686) 13 (9.3 - 21) 6.4 (1.1 - 21.2) 4 (1 - 21) 8 (4 - 10) 4.9 (3.9 - 5.9)

ACPA: anti-citrullinated protein antibodies, DAS28: disease activity score 28-joints, sedimentation rate, CRP: C-reactive protein, IgM-RF: IgM rheumatoid factor, IQR:

ESR: erythrocyte interquartile range.

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Figure legends

Figure 1: Gating strategy for ILC analysis. Lymph node biopsies were processed to obtain a single cell suspension which was immediately stained for ILC markers. Lineage-negative (CD3, CD14, CD19 and CD34) events were gated (A) and their expression of CD45 and CD127 was subsequently assessed to identify the total

ILC population (Lin-CD45+/lowCD127+) (B). Within this population, different ILCs subsets were identified on the

basis of their expression of NKp44 and c-Kit, as indicated (C). The lymphoid morphology was tested in each lation by backgating (D).

Figure 2: Analysis of ILCs subsets in LN. (A) Analysis of LTi, ILC1 and ILC3 subsets in the three groups involved. (B) Analysis of the CD69 frequency within total ILCs and ILCs subsets. Horizontal lines represent median and interquartile range. Differences were assessed by Kruskal-Wallis followed by a post Dunn's test. * p<0.050, ** p<0.010, *** p<0.001

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