Cutting Edge: Homeostasis of Innate Lymphoid Cells Is Imbalanced in Psoriatic Arthritis

Alina Soare, Stefanie Weber, Lisa Maul, Simon Rauber, Ana Maria Gheorghiu, Markus Luber, Ismail Houssni, Arnd Kleyer, Gero von Pickardt, Manuel Gado, David Simon, Jürgen Rech, Georg Schett, Jörg H. W. Distler and Andreas Ramming
J Immunol February 15, 2018, 200 (4) 1249-1254; DOI: https://doi.org/10.4049/jimmunol.1700596

Abstract

Innate lymphoid cells (ILC) have a high potency for cytokine production independent of specific Ag stimulation. Imbalance of ILC subsets may influence cytokine production in humans and hence be associated with the development of inflammatory disease. Evidence for an imbalance of ILC homeostasis in human disease, however, is very limited to date. In this study we show that psoriatic arthritis (PsA), a severe disease of the joints depending on the activation of the IL-23/IL-17 pathway, is characterized by a skewed ILC homeostasis. Circulating ILC3s as potent source of IL-17/IL-22 were elevated in active PsA, whereas ILC2s, which produce proresolving cytokines, were decreased. The ILC2/ILC3 ratio was significantly correlated with clinical disease activity scores and the presence of imaging signs of joint inflammation and bone damage. Multivariable analysis showed that a high ILC2/ILC3 ratio is associated with remission in PsA, suggesting that specific alterations of ILC homeostasis control disease activity in PsA.

Introduction

Psoriatic arthritis (PsA) is a chronic inflammatory disease of the joints and the entheses (1, 2). Immunopathology of PsA is dominated by robust activation of the IL-23/IL-17 axis with TNF-α as an important effector cytokine (3). To date, most of the knowledge of the immunopathology of PsA and the respective role of proinflammatory cytokines comes from clinical trials neutralizing IL-17, IL-23, or TNF-α and yielding improvement of signs and symptoms of disease (4, 5).

Tackling the actual immunopathology in human PsA, however, is still challenging. Current disease activity markers are of limited use for understanding the immunopathology of PsA, as they are focused on quantifying the extent of the clinical manifestations of disease (6–8). Furthermore, direct assessment of the cytokines involved in PsA is difficult due to the very low systemic concentrations of these mediators. Biopsy studies have partly overcome this challenge, thereby showing in situ activation of the aforementioned pathways (9, 10). Nonetheless, joint biopsy is an invasive procedure and limited to few specialized centers. Also, despite being an excellent instrument to assess the local molecular changes in the joints, synovial analysis does not explain how disease can spread from the skin to the joints, which most likely requires trafficking of cells through the circulation, as previously shown for TH17 cells (11).

To tackle this challenge, we established a method to measure and quantify innate lymphoid cells (ILCs) in the circulation of PsA patients. ILCs constitute a rather newly described class of immune cells comprising three lineages with distinct patterns of cytokine production: whereas ILC1s are a source of IFN-γ, ILC2s predominantly synthetize IL-4, IL-5, IL-9, and IL-13. ILC3s, which are induced by IL-23, produce IL-17 and IL-22, and are therefore of substantial interest in PsA (12, 13). Importantly, ILCs were identified to produce disease-related cytokines within the inflamed tissue of PsA patients (14). Under physiological conditions, ILCs are scarce in the peripheral blood (15, 16). However, upon certain perturbations of immune homeostasis, such as chronic inflammation, the pool of resident ILCs can be replenished by the migration of ILCs into the peripheral blood, allowing their easier assessment (16).

In this study we show that PsA is characterized by alterations of circulating ILCs. Although circulating ILCs are generally increased in PsA patients, distinct changes of ILC subpopulations are associated with clinical disease activity as well as imaging signs of inflammation and structural damage. In clinically active PsA, ILC3s were significantly increased at the expense of ILC2s, supporting the concept of IL-23/IL-17 pathway activation as the driving force of inflammation in PsA patients.

Materials and Methods

Characteristics of the cohort of PsA patients and healthy controls

A total of 124 patients satisfying the Classification Criteria for Psoriatic Arthritis and 26 healthy controls were enrolled in the study. There was no significant difference in sex (47.6% male versus 50.0% female) and age distribution (53.6 ± 13.4 versus 47.8 ± 12.4 y) between PsA patients and healthy controls. Blood samples of healthy controls were collected and processed in the same way as for PsA patients. PsA patients had a disease duration of 7.7 ± 8.3 y, a tender joint count of 2.8 ± 4.1 (out of 68 joints), and a swollen joint count of 1.1 ± 3.0 (out of 66 joints). The visual analog scale for pain was 4.4 ± 2.1 and for global assessment was 4.3 ± 2.1, based on a 10 cam scale. Concomitant plaque psoriasis was found in 70.4% of the patients, psoriatic nail dystrophy in 49.1%, enthesitis in 39.3%, and a history of uveitis or iritis in 8.8% of the patients; C-reactive protein levels (6.5 ± 12.4 mg/l), and erythrocyte sedimentation rate (17.6 ± 16.8 mm/h) were collected from all patients.

Disease activity of PsA was assessed by the following well-established clinical scores: the Disease Activity Score 28 (DAS28; 3.0 ± 1.3) based on 28 joints, which is used in both rheumatoid arthritis and PsA (17), the Disease Activity in Psoriatic Arthritis (DAPSA; 13.1 ± 9.1) score including 66/68 joints (7), and the Minimal Disease Activity instrument (MDA; 33.9%) encompassing extra-articular manifestations of PsA beside joint involvement (6). Briefly, 19.4% of PsA patients received treatment with nonsteroidal anti-inflammatory drugs or low-dose glucocorticoids, 26.6% were treated with conventional synthetic disease-modifying antirheumatic drugs (DMARD) and 54.0% with biological DMARD (85.1% TNF-α inhibitors; 14.9% secukinumab/ustekinumab). The study was performed in accordance with the Declaration of Helsinki and ethical approval was obtained from the ethical committee of the University Clinic of Erlangen. Subjects were enrolled in the study after signing the inform consent form.

Blood samples and flow cytometry

Venous whole blood was collected in EDTA precoated blood sample tubes. The collected blood was processed for routine automated complete blood count. Furthermore, 500 μl of whole blood was directly incubated with fluorochrome-labeled Abs (listed in Supplemental Fig. 1A) for 20 min. RBCs were lysed and nucleated cells were fixed using RBC lysis and fixation solution (BioLegend, Fell, Germany). Flow cytometric analysis was performed on a three-laser/12-channel system licensed for diagnostical use (Navios, Beckmann Coulter, Fullerton, CA) and analyzed with Beckman Coulter’s proprietary Kaluza software version 1.5. ILCs were defined as cells with the following marker set: CD45+, CD127+, negative for lineage markers CD3, CD11c, CD14, CD16, CD19, CD20, CD34, CD56, CD94, FcERIa. In addition, ILC1 were defined as the CRTH2− CD117− fraction, ILC2s as the CRTH2+ CD117−, and ILC3s as the CRTH2− CD4− CD117+ fractions, respectively [Supplemental Fig. 1B; (18)]. Appropriate identification of ILC1, ILC2, and ILC3 was additionally assessed by costaining with ILC fate-determining transcription factors T-bet, Gata3, and RORγt (Supplemental Fig. 1C) using the Foxp3 Staining Buffer Set Kit (eBioscience, Frankfurt, Germany) according to the manufacturer’s instructions. Cytokine expression patterns were evaluated after restimulation of PBMCs with 81 nM PMA and 1.3 μM ionomycin in the presence of 5 ng/ml brefeldin A and 2 nM monensin (all from BioLegend) for 4 h (Supplemental Fig. 1C). The intracellular fixation and permeabilization buffer set (eBioscience) was used according to the manufacturer’s instructions. Absolute numbers of cells were calculated as following: % ILC2 × absolute lymphocyte count (automated count) = absolute number of ILC2 per cubic millimeter.

Magnetic resonance imaging scanning and analysis

Magnetic resonance imaging (MRI) scans of the hand were performed with a 1.5 T Magneton Avanto system (Siemens, Erlangen, Germany). T1-weighted axial images (voxel size 0.5 × 0.5 × 3 mm, field-of-view 150 mm, echo time: 13 ms, repetition time: 766 ms, slice thickness: 3 mm) after i.v. gadolinium injection (0.2 ml/kg) were used to assess synovitis, tenosynovitis, and periarticular inflammation. T2-weighted coronal fat saturated (turbo inversion recovery magnitude) sequences (voxel size 0.5 × 0.5 × 2.5 mm, field-of-view 220 mm, echo time: 60 ms, repetition time: 3500 ms, slice thickness 2.5 mm) were used to assess osteitis.

Image analysis focused on the metacarpophalangeal, proximal interphalangeal, and distal interphalangeal joints of the second to fifth fingers. Synovitis and osteitis were assessed using the PsA MRI scoring system [PsAMRIS, (19)]. We assigned a score to synovitis, osteitis, and tenosynovitis on a 0–3 scale (absent, mild, moderate or severe). Periarticular inflammation was just graded as present or absent. The analysis was conducted per patient. All images were evaluated by two blinded and independent readers.

High-resolution peripheral quantitative computed tomography

All patients underwent high-resolution peripheral quantitative computed tomography (HR-pQCT) scans of the metacarpophalangeal joints two and three of the dominant hand through an XtremeCT scanner (SCANCO Medical, Bruetisellen, Switzerland). Image acquisition and analysis have been described in detail by Albrecht et al. (20). Two independent and blinded readers examined the HR-pQCT images for the presence and extent of enthesiophytes and erosions. Enthesiophytes, bony protrusions originating from the cortical shell found at the insertion sites of capsule and ligaments or at the pulleys of extensor tendons, were evaluated. Erosions were defined as breaks of the cortical shell and visible in two planes were evaluated in their numbers and volumes. The volume (in cubic millimeters) assessment was obtained by applying the half-ellipsoid formula. Erosion volume and enthesiophyte size were assessed in the largest lesion of each quadrant (target lesion). All images were analyzed and measured through the open source DICOM viewer Osirix V4.1 (Rosslyn, VA).

Statistical analysis, rank, and multivariate correlations

Differences between two groups were analyzed by the Mann–Whitney U test. Spearman’s rank correlation coefficients were calculated for correlation of continuous variables. Multivariate linear regression and Receiver-Operating Characteristic curve analysis was performed using the IBM SPSS Statistics V.20 software. The p values are expressed as follows: *p < 0.05, **p < 0.01, and ***p < 0.001.

Results and Discussion

Circulating ILC lineages are increased in patients with PsA

We first analyzed circulating total ILCs and ILC lineages in the peripheral blood of 124 PsA patients with different stages of disease activity and compared it to a group of 26 age- and sex-matched healthy controls. The total number of circulating ILCs (Linneg-CD127pos-CD45pos cells) and ILC subpopulations in the peripheral blood was low in healthy controls (Fig. 1A). The cohort of PsA patients as a whole showed a significant elevation of circulating total ILCs as well as of the ILC1, ILC2, and ILC3 subpopulations. ILC3s lacked NKp44 and exhibited weak cytokine production in contrast to ILC1 and ILC2, suggesting that circulating ILC3s are still immature (Supplemental Fig. 1B, 1C).

FIGURE 1.
FIGURE 1.

Circulating total ILCs and ILC subsets in PsA patients according to disease activity. (A) Circulating ILCs (total ILC, ILC1, ILC2, ILC3) in healthy controls (n = 25) and patients with PsA (n = 124). (B) Distribution of disease activity of PsA patients (n = 124) according to DAS28 shown as pie charts. ILC1, ILC2, ILC3 counts stratified into disease activity groups based on DAS28 score. (C) Distribution of disease activity of PsA patients (n = 124) according to DAPSA shown as pie charts. ILC1, ILC2, ILC3 counts stratified into disease activity groups assessed by DAPSA score. Data are shown as scatter dot plot with mean ± SEM. *p < 0.05, **p < 0.01, ***p < 0.001 determined either by one-way ANOVA with Tukey multiple comparison post hoc test or two-tailed Mann–Whitney U test if two groups were compared.

Circulating ILC3s are related to PsA disease activity

Further evaluation of circulating ILCs demonstrated high variations in ILC1, 2, and 3 counts depending on PsA disease activity as measured by DAS28, DAPSA, and MDA state (Fig. 1B, 1C, Supplemental Fig. 2A). Stratification of the PsA population in patients in remission, with low, medium, and high inflammatory disease activity based on DAS28 score revealed that only ILC3 (CRTH2neg-ckitpos), but not ILC1 (CRTH2neg-ckitneg) and ILC2 (CRTH2pos), increase with higher disease activity (Fig. 1B). For ILC2, a tendency to lower ILC2 numbers with higher disease activity was observed as described previously in rheumatoid arthritis (21). Analysis of PsA disease activity according to the DAPSA score, which in contrast to DAS28 has been specifically developed for measuring disease activity in PsA, did yield similar results: ILC3 counts inclined from low to highly active patients compared with patients in remission (Fig. 1C). Furthermore, ILC2 counts were significantly decreased in active patients compared with patients in remission (Fig. 1C). Similar results were achieved using MDA status, showing that PsA patients fulfilling MDA had significantly lower circulating ILC3, but higher ILC2 counts (Supplemental Fig. 2A).

ILC2/3 ratio correlates with clinical composite scores

Linear regression analyses of the relationship between disease activity and circulating ILC counts showed that ILC2s negatively (R = −0.3732; p < 0.0001) and ILC1s and ILC3s positively correlated with DAPSA (R = 0.2622, p = 0.0057; R = 0.4092, p < 0.0001 respectively) (Fig. 2A). The strongest correlation was observed when the ratio of ILC2s to ILC3s was analyzed (R = −0.5709; p < 0.0001) (Fig. 2B). ILC2/3 ratio was also reduced in patients with extra-articular manifestations such as active psoriatic skin disease, presence of enthesitis, or a history of concomitant uveitis (Supplemental Fig. 2B). With respect to treatment, ILC numbers did not differ among patients receiving either nonsteroidal anti-inflammatory drugs or low-dose corticosteroids alone, conventional synthetic or biological DMARDs (Supplemental Fig. 2C, 2D), suggesting that disease activity rather than specific classes of drugs account for the observed changes in circulating ILC numbers.

FIGURE 2.
FIGURE 2.

Correlation of ILC subsets with PsA disease activity. (A) Correlation of ILC1, ILC2, ILC3 counts with disease activity according to DAPSA; (B) correlation of ILC2/ILC3 ratio with disease activity according to DAPSA and ILC2/ILC3 ratios stratified into disease activity groups based on DAPSA score. Data are shown in correlation plots or as scatter dot plots with mean ± SEM. Spearman’s rank correlation coefficients were calculated for correlation of continuous variables. ***p < 0.001 determined by one-way ANOVA with Tukey multiple comparison post hoc test.

ILC2/3 ratio correlates with inflammation and local bone remodeling on imaging

In addition to clinical scores, ILC counts also correlated with radiographic findings obtained by MRI and HR-pQCT. According to PsAMRIS (20), the extent of synovitis significantly inversely correlated with the ILC2/3 ratio (R = −0.6753; p < 0.0001) (Fig. 3A). Patients with current tenosynovitis and presence of bone erosions or osteophytes also showed significantly lower ILC2/3 ratios (R = −0.5828; p = 0.0011, p < 0.001 respectively) (Fig. 3B). In concordance, PsAMRIS score, which includes synovitis and bone damage, was negatively correlated with the ILC2/3 ratio (R = −0.7114; p < 0.0001) (Fig. 3C).

FIGURE 3.
FIGURE 3.

Correlation of the ILC2/ILC3 ratio with imaging data. (A) Association between the ILC2/3 ratio and MRI imaging signs of inflammation including synovitis and tenosynovitis; (B) association between the ILC2/3 ratio and MRI imaging signs of structural damage including bone erosion and osteoproliferation; (C) correlation of ILC2/ILC3 ratio with MRI disease activity according to PsAMRIS. (D and E) Association between the ILC2/3 ratio and (D) bone erosion and osteoproliferation as well as (E) metacarpal or radial bone density obtained by HR-pQCT. Data are shown in correlation plots or as scatter dot plots with mean ± SEM. Spearman’s rank correlation coefficients were calculated for correlation of continuous variables. *p < 0.05, **p < 0.01, ***p < 0.001 determined by two-tailed Mann–Whitney U test.

In addition, potential associations between ILC counts and structural bone changes obtained by HR-pQCT (18) were analyzed. Notably, patients with erosions and/or osteoproliferation exhibited a significantly lower ILC2/3 ratio (Fig. 3D). Average bone density of the metacarpophalangeal bone and the distal radius, however, did not correlate with ILC2/3 ratio, suggesting an association between ILCs and local microstructural bone damage rather than systemic effects on bone density (Fig. 3E).

ILC2/3 ratio as a marker to differentiate between remission and disease activity

Multivariate linear regression was used to investigate the relationship between disease activity (predictor) and ILC2/ILC3 ratio (outcome). Disease activity was modeled as DAS28 or DAPSA for clinical activity, and PsAMRIS synovitis or erosions score for imaging activity. First, univariable linear regression, with each predictor entered separately into the model, was performed. Thereafter, each predictor was entered together with age, gender, and disease duration into multivariable regression analyses. Disease activity measurements (DAS28, DAPSA, PsAMRIS, synovitis score) were significant determinants of ILC2/3 ratio both in univariate regression analyses, and when adjusted for age, gender, and disease duration (Supplemental Fig. 2E). Furthermore, a Receiver-Operating Characteristic curve was used to test the performance of the ILC2/3 ratio as marker of remission in PsA (DAPSA remission level was used) and to find the best cutoff level for ILC2/3 ratio in differentiating between remission and disease activity. ILC2/3 ratio had an area under curve of 0.954 (p < 0.001), and the cutoff 0.57 exhibited highest sensitivity (92.9%) and 84.7% specificity in identifying remission (Supplemental Fig. 2F).

In this study, we show that PsA is accompanied by alterations of circulating ILCs. Specifically, circulating ILC3s significantly increased, whereas circulating ILC2s significantly decreased in active PsA, pointing to a perturbed ILC homeostasis. The cytokine pattern of ILC3s intimately overlaps with the cytokine profile of active PsA, as ILC3s differentiate upon IL-23 exposure and are a source of IL-17 and IL-22. Hence, increased circulating ILC3s may explain higher activity of PsA as well as the spreading of disease from the skin to the joints. In contrast, the decrease of ILC2s in active PsA is in line with the known function of ILC2-related cytokines such as IL-4, IL-5, IL-9, and IL-13 as proresolving agents in arthritis (21, 22). It is therefore conceivable that a high ILC2/ILC3 ratio is associated with remission of PsA, whereas the opposite is the case for active disease.

Circulating ILC3s in PsA patients stained positive for ILC3 fate-determining transcription factor RORγt in contrast to circulating ILC3-like ILC precursors described in healthy individuals (23). The lack of Nkp44 expression and weak cytokine production in circulating ILC3s might indicate that circulating ILC3s are still immature and acquire the capacity to secrete lead cytokines such as IL-17 only after full maturation in target tissues. This observation might be in concordance with the very low concentrations of IL-17/IL-22 in the blood, but high concentrations of IL-17/IL-22 in target tissues of patients with PsA. Given the high plasticity of ILCs, ILC3s could also derive from ILC2s achieving an inflammatory phenotype characterized by the expression of RORγt and proinflammatory IL-17 (24).

In contrast to PsA, major differences within the ILC pool are not observed in patients with psoriasis (25, 26). This might explain the differences in the clinical presentation of psoriatic disease and suggest a potential role of ILCs contributing to the spreading of inflammation into joints. Although the perturbed ILC homeostasis in PsA is interesting from a pathophysiological point of view, it is yet too early to say whether it can be used as a biomarker for immunological disease activity in PsA. Considering that biomarkers are defined as a “characteristic that can be objectively measured as an indicator of normal or pathological biological processes” (27), the observation that ILC2/3 ratio correlated with both composite clinical disease activity scores, but also with imaging signs of inflammation and structural damage is at least reassuring. Also, assessment of ILC2/3 ratio is feasible, requiring only small amounts of peripheral blood to be analyzed. Further validation work, however, is necessary before ILCs can be considered for use as markers of immunological activity in PsA.

Disclosures

J.H.W.D. has consultancy relationships and/or has received research funding from Actelion, Bristol-Myers Squibb, Celgene, Bayer Pharma, Boehringer Ingelheim, JB Therapeutics, Sanofi-Aventis, Novartis, UCB, GlaxoSmithKline, Array Biopharma, and Active Biotech in the area of potential treatments of systemic sclerosis and is stock owner of 4D Science GmbH. The other authors have no financial conflicts of interest.

Acknowledgments

We thank Monica Pascual for excellent technical assistance.

Footnotes

  • This work was supported by Deutsche Forschungsgemeinschaft Grants RA 2506/3-1, RA 2506/4-1, DI 1537/5-1, DI 1537/7-1, DI 1537/8-1, DI 1537/9-1, AK 144/1-1, SCHE 1583/7-1, and CRC1181, Else Kröner-Fresenius-Stiftung Grant 2014_A184, Grant J40 from the Interdisciplinary Center for Clinical Research in Erlangen, Grant 16-10-05-1-Ramming from the ELAN-Program of the Friedrich-Alexander-University Erlangen-Nürnberg, and Novartis Pharmaceuticals. Novartis played no role in study design, data collection, data analysis, or data interpretation.

  • The online version of this article contains supplemental material.

  • Abbreviations used in this article:

    DAPSA
    Disease Activity in Psoriatic Arthritis
    DAS28
    Disease Activity Score 28
    DMARD
    disease-modifying antirheumatic drug
    HR-pQCT
    high-resolution peripheral quantitative computed tomography
    ILC
    innate lymphoid cell
    MDA
    Minimal Disease Activity instrument
    MRI
    magnetic resonance imaging
    PsA
    psoriatic arthritis
    PsAMRIS
    PsA MRI scoring system.

  • Received April 27, 2017.
  • Accepted December 7, 2017.

References

  1. ↵
    1. Gladman, D. D.,
    2. C. Antoni,
    3. P. Mease,
    4. D. O. Clegg,
    5. P. Nash
    . 2005. Psoriatic arthritis: epidemiology, clinical features, course, and outcome. Ann. Rheum. Dis. 64(Suppl. 2): ii14–ii17.
    OpenUrlAbstract/FREE Full Text
  2. ↵
    1. Turkiewicz, A. M.,
    2. L. W. Moreland
    . 2007. Psoriatic arthritis: current concepts on pathogenesis-oriented therapeutic options. Arthritis Rheum. 56: 1051–1066.
    OpenUrlCrossRefPubMed
  3. ↵
    1. Veale, D. J.,
    2. C. Ritchlin,
    3. O. FitzGerald
    . 2005. Immunopathology of psoriasis and psoriatic arthritis. Ann. Rheum. Dis. 64(Suppl. 2): ii26–ii29.
    OpenUrlAbstract/FREE Full Text
  4. ↵
    1. Schett, G.,
    2. D. Elewaut,
    3. I. B. McInnes,
    4. J. M. Dayer,
    5. M. F. Neurath
    . 2013. How cytokine networks fuel inflammation: toward a cytokine-based disease taxonomy. Nat. Med. 19: 822–824.
    OpenUrlCrossRefPubMed
  5. ↵
    1. Gossec, L.,
    2. J. S. Smolen,
    3. S. Ramiro,
    4. M. de Wit,
    5. M. Cutolo,
    6. M. Dougados,
    7. P. Emery,
    8. R. Landewé,
    9. S. Oliver,
    10. D. Aletaha, et al
    . 2016. European league against rheumatism (EULAR) recommendations for the management of psoriatic arthritis with pharmacological therapies: 2015 update. Ann. Rheum. Dis. 75: 499–510.
    OpenUrlAbstract/FREE Full Text
  6. ↵
    1. Coates, L. C.,
    2. J. Fransen,
    3. P. S. Helliwell
    . 2010. Defining minimal disease activity in psoriatic arthritis: a proposed objective target for treatment. Ann. Rheum. Dis. 69: 48–53.
    OpenUrlAbstract/FREE Full Text
  7. ↵
    1. Schoels, M. M.,
    2. D. Aletaha,
    3. F. Alasti,
    4. J. S. Smolen
    . 2016. Disease activity in psoriatic arthritis (PsA): defining remission and treatment success using the DAPSA score. Ann. Rheum. Dis. 75: 811–818.
    OpenUrlAbstract/FREE Full Text
  8. ↵
    1. Helliwell, P. S.,
    2. A. Kavanaugh
    . 2014. Comparison of composite measures of disease activity in psoriatic arthritis using data from an interventional study with golimumab. Arthritis Care Res. (Hoboken) 66: 749–756.
    OpenUrl
  9. ↵
    1. Ciccia, F.,
    2. G. Guggino,
    3. A. Ferrante,
    4. S. Raimondo,
    5. R. Bignone,
    6. V. Rodolico,
    7. S. Peralta,
    8. M. Van Tok,
    9. A. Cannizzaro,
    10. C. Schinocca, et al
    . 2016. Interleukin-9 overexpression and Th9 polarization characterize the inflamed gut, the synovial tissue, and the peripheral blood of patients with psoriatic arthritis. Arthritis Rheumatol. 68: 1922–1931.
    OpenUrl
  10. ↵
    1. Menon, B.,
    2. N. J. Gullick,
    3. G. J. Walter,
    4. M. Rajasekhar,
    5. T. Garrood,
    6. H. G. Evans,
    7. L. S. Taams,
    8. B. W. Kirkham
    . 2014. Interleukin-17+CD8+ T cells are enriched in the joints of patients with psoriatic arthritis and correlate with disease activity and joint damage progression. Arthritis Rheumatol. 66: 1272–1281.
    OpenUrl
  11. ↵
    1. Benham, H.,
    2. P. Norris,
    3. J. Goodall,
    4. M. D. Wechalekar,
    5. O. FitzGerald,
    6. A. Szentpetery,
    7. M. Smith,
    8. R. Thomas,
    9. H. Gaston
    . 2013. Th17 and Th22 cells in psoriatic arthritis and psoriasis. Arthritis Res. Ther. 15: R136.
    OpenUrlCrossRefPubMed
  12. ↵
    1. Spits, H.,
    2. D. Artis,
    3. M. Colonna,
    4. A. Diefenbach,
    5. J. P. Di Santo,
    6. G. Eberl,
    7. S. Koyasu,
    8. R. M. Locksley,
    9. A. N. McKenzie,
    10. R. E. Mebius, et al
    . 2013. Innate lymphoid cells--a proposal for uniform nomenclature. Nat. Rev. Immunol. 13: 145–149.
    OpenUrlCrossRefPubMed
  13. ↵
    1. Diefenbach, A.,
    2. M. Colonna,
    3. S. Koyasu
    . 2014. Development, differentiation, and diversity of innate lymphoid cells. Immunity 41: 354–365.
    OpenUrlCrossRefPubMed
  14. ↵
    1. Leijten, E. F.,
    2. T. S. van Kempen,
    3. M. Boes,
    4. J. M. Michels-van Amelsfort,
    5. D. Hijnen,
    6. S. A. Hartgring,
    7. J. A. van Roon,
    8. M. H. Wenink,
    9. T. R. Radstake
    . 2015. Brief report: enrichment of activated group 3 innate lymphoid cells in psoriatic arthritis synovial fluid. Arthritis Rheumatol. 67: 2673–2678.
    OpenUrl
  15. ↵
    1. Vély, F.,
    2. V. Barlogis,
    3. B. Vallentin,
    4. B. Neven,
    5. C. Piperoglou,
    6. M. Ebbo,
    7. T. Perchet,
    8. M. Petit,
    9. N. Yessaad,
    10. F. Touzot, et al
    . 2016. Evidence of innate lymphoid cell redundancy in humans. Nat. Immunol. 17: 1291–1299.
    OpenUrlCrossRefPubMed
  16. ↵
    1. Gasteiger, G.,
    2. X. Fan,
    3. S. Dikiy,
    4. S. Y. Lee,
    5. A. Y. Rudensky
    . 2015. Tissue residency of innate lymphoid cells in lymphoid and nonlymphoid organs. Science 350: 981–985.
    OpenUrlAbstract/FREE Full Text
  17. ↵
    1. Prevoo, M. L.,
    2. M. A. van ’t Hof,
    3. H. H. Kuper,
    4. M. A. van Leeuwen,
    5. L. B. van de Putte,
    6. P. L. van Riel
    . 1995. Modified disease activity scores that include twenty-eight-joint counts. Development and validation in a prospective longitudinal study of patients with rheumatoid arthritis. Arthritis Rheum. 38: 44–48.
    OpenUrlCrossRefPubMed
  18. ↵
    1. Horsburgh, S.,
    2. S. Todryk,
    3. A. Ramming,
    4. J. H. W. Distler,
    5. S. O’Reilly
    . 2017. Innate lymphoid cells and fibrotic regulation. Immunol. Lett. Available at: http://dx.doi.org/10.1016/j.imlet.2017.08.022. Accessed: August 24, 2017.
  19. ↵
    1. Ostergaard, M.,
    2. F. McQueen,
    3. C. Wiell,
    4. P. Bird,
    5. P. Bøyesen,
    6. B. Ejbjerg,
    7. C. Peterfy,
    8. F. Gandjbakhch,
    9. A. Duer-Jensen,
    10. L. Coates, et al
    . 2009. The OMERACT psoriatic arthritis magnetic resonance imaging scoring system (PsAMRIS): definitions of key pathologies, suggested MRI sequences, and preliminary scoring system for PsA Hands. J. Rheumatol. 36: 1816–1824.
    OpenUrlAbstract/FREE Full Text
  20. ↵
    1. Albrecht, A.,
    2. S. Finzel,
    3. M. Englbrecht,
    4. J. Rech,
    5. A. Hueber,
    6. P. Schlechtweg,
    7. M. Uder,
    8. G. Schett
    . 2013. The structural basis of MRI bone erosions: an assessment by microCT. [Published erratum appears in 2013 Ann. Rheum. Dis. 72: 2056.] Ann. Rheum. Dis. 72: 1351–1357.
    OpenUrlAbstract/FREE Full Text
  21. ↵
    1. Rauber, S.,
    2. M. Luber,
    3. S. Weber,
    4. L. Maul,
    5. A. Soare,
    6. T. Wohlfahrt,
    7. N. Y. Lin,
    8. K. Dietel,
    9. A. Bozec,
    10. M. Herrmann, et al
    . 2017. Resolution of inflammation by interleukin-9-producing type 2 innate lymphoid cells. Nat. Med. 23: 938–944.
    OpenUrl
  22. ↵
    1. Chen, Z.,
    2. D. Andreev,
    3. K. Oeser,
    4. B. Krljanac,
    5. A. Hueber,
    6. A. Kleyer,
    7. D. Voehringer,
    8. G. Schett,
    9. A. Bozec
    . 2016. Th2 and eosinophil responses suppress inflammatory arthritis. Nat. Commun. 7: 11596.
    OpenUrlCrossRefPubMed
  23. ↵
    1. Lim, A. I.,
    2. Y. Li,
    3. S. Lopez-Lastra,
    4. R. Stadhouders,
    5. F. Paul,
    6. A. Casrouge,
    7. N. Serafini,
    8. A. Puel,
    9. J. Bustamante,
    10. L. Surace, et al
    . 2017. Systemic human ILC precursors provide a substrate for tissue ILC differentiation. Cell 168: 1086–1100.e10.
    OpenUrlCrossRef
  24. ↵
    1. Huang, Y.,
    2. L. Guo,
    3. J. Qiu,
    4. X. Chen,
    5. J. Hu-Li,
    6. U. Siebenlist,
    7. P. R. Williamson,
    8. J. F. Urban Jr..,
    9. W. E. Paul
    . 2015. IL-25-responsive, lineage-negative KLRG1(hi) cells are multipotential ‘inflammatory’ type 2 innate lymphoid cells. Nat. Immunol. 16: 161–169.
    OpenUrlCrossRefPubMed
  25. ↵
    1. Villanova, F.,
    2. B. Flutter,
    3. I. Tosi,
    4. K. Grys,
    5. H. Sreeneebus,
    6. G. K. Perera,
    7. A. Chapman,
    8. C. H. Smith,
    9. P. Di Meglio,
    10. F. O. Nestle
    . 2014. Characterization of innate lymphoid cells in human skin and blood demonstrates increase of NKp44+ ILC3 in psoriasis. J. Invest. Dermatol. 134: 984–991.
    OpenUrlCrossRefPubMed
  26. ↵
    1. Teunissen, M. B. M.,
    2. J. M. Munneke,
    3. J. H. Bernink,
    4. P. I. Spuls,
    5. P. C. M. Res,
    6. A. Te Velde,
    7. S. Cheuk,
    8. M. W. D. Brouwer,
    9. S. P. Menting,
    10. L. Eidsmo, et al
    . 2014. Composition of innate lymphoid cell subsets in the human skin: enrichment of NCR(+) ILC3 in lesional skin and blood of psoriasis patients. J. Invest. Dermatol. 134: 2351–2360.
    OpenUrlCrossRefPubMed
  27. ↵
    1. Ermann, J.,
    2. D. A. Rao,
    3. N. C. Teslovich,
    4. M. B. Brenner,
    5. S. Raychaudhuri
    . 2015. Immune cell profiling to guide therapeutic decisions in rheumatic diseases. Nat. Rev. Rheumatol. 11: 541–551.
    OpenUrlCrossRefPubMed
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