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. 2021 Nov 18;16(11):e0260254. doi: 10.1371/journal.pone.0260254

Association between inflammatory cytokines and immune–checkpoint molecule in rheumatoid arthritis

Haruki Matsumoto 1, Yuya Fujita 1, Tomoyuki Asano 1, Naoki Matsuoka 1, Jumpei Temmoku 1, Shuzo Sato 1, Makiko Yashiro–Furuya 1, Kohei Yokose 1, Shuhei Yoshida 1, Eiji Suzuki 2, Toru Yago 1, Hiroshi Watanabe 1, Atsushi Kawakami 3, Kiyoshi Migita 1,*
Editor: Pierre Busson4
PMCID: PMC8601500  PMID: 34793561

Abstract

Background

Anti-citrullinated peptide antibodies (ACPA) and inflammatory cytokines play important roles in the development of rheumatoid arthritis (RA). T cell immunoglobulin and mucin–domain containing–3 (TIM–3) is an immune-checkpoint molecule involved in inhibitory signaling. Galectin–9 (Gal–9) mediated ligation of TIM–3 induces the amelioration of autoimmune diseases. TIM–3 is expressed in synovial osteoclasts and involved in the rheumatoid bone destruction. The aim of this study was to investigate the relationships between inflammatory cytokines and immune–checkpoint molecules in RA patients.

Methods

Serum levels of interleukin–6 (IL–6), tumor necrosis factor–α (TNF–α), soluble TIM–3 (sTIM–3) and Gal–9 were determined by ELISA. Patients were stratified into two groups based on ACPA titers: low-medium ACPA (ACPA <200 U/mL) and high ACPA (ACPA ≥200 U/mL). Serum levels of cytokines or immune-checkpoint molecules were evaluated between RA patients with low-medium ACPA titers and high ACPA titers.

Results

Elevated serum levels of inflammatory cytokines were correlated with DAS28–ESR in RA patients. Although serum levels of sTIM–3 were elevated in RA patients, significant correlations between sTIM–3 and cytokines (IL–6 or TNF–α) were observed exclusively in RA patients with low-medium ACPA titers (<200 U/mL). Serum levels of IL–6 and TNF–α levels were significantly correlated with elevated Gal–9 levels regardless of ACPA status. A significant correlation between IL–6 and Gal–9 was observed in RA patients without advanced joint damage. Conversely, a significant correlation between TNF–α and Gal–9 was observed in RA patients with advanced joint damage.

Conclusions

Our data indicated that there are positive correlations between circulating inflammatory cytokines and checkpoint molecules in RA patients and these interactions can be modulated by ACPA status or joint damage stage.

Background

Rheumatoid arthritis (RA) is an autoimmune inflammatory disease that results in joint destruction and disability [1]. RA is characterized by the production of auto–antibodies and cytokine–mediated synovial or systemic inflammation [2]. Cytokine networks play an important role in the pathogenesis of RA [3]. Sustained production of proinflammatory cytokines was shown to correlate with rheumatoid inflammation [4]. Previous studies have shown that the manipulation of serum cytokine levels is the main mechanism of action of biologics or targeted synthetic disease–modifying antirheumatic drugs (tsDMARDs) for RA [5, 6]. Increased levels of cytokines, including tumor necrosis factor–α (TNF–α) and interleukin–6 (IL–6), reflect the rheumatoid synovial inflammation and have been shown to be associated with RA disease activity or response to anti–cytokine therapy [3, 4, 7, 8]. However, the association between circulating cytokines levels and RA disease phenotype is not well characterized. TNF–α plays a key role in the pathogenesis of RA [3]. TNF–α affects different cell types and is produced mainly by monocytes, macrophages, and T cells [9, 10]. IL-6 is another cytokine which is considered as disease driving cytokine in RA [11]. In RA, IL–6 is increased in synovium and blood, and its level correlates with clinical disease activity and joint damage [7, 12].

Anti–citrullinated peptide antibodies (ACPA) are useful for the diagnosis of RA and have been shown to be associated with progression of joint destruction or therapeutic response in patients with RA [13]. However, the interactions between ACPA status and proinflammatory cytokines during RA disease progression are yet to be fully clarified [14]. Rheumatoid synovitis and articular damage are mediated through several cell types, including T cells, B cells, monocytes, and osteoclasts [15]. Immune–checkpoint molecules may play a role in the interaction between these immune cells and their activation [16, 17]. T cell immunoglobulin and mucin–domain containing–3 (TIM–3) is an immune–checkpoint molecule involved in negative regulation of immune responses [18]. Galectin–9 (Gal–9), a ligand of TIM–3, induces the amelioration of autoimmune diseases [19]. TIM–3 was detected in osteoclasts and its mononuclear precursor cells in rheumatoid synovium, and the Gal–9/TIM–3 pathway regulatory system controls osteoclastogenesis and inflammatory bone destruction in RA [20]. In our previous report, serum Gal–9 and sTIM–3 were significantly elevated in RA patients compared with healthy subjects [21, 22]. A relationship between proinflammatory cytokines and Gal–9/TIM–3 has been reported in RA patients [23, 24], so we hypothesized that immune–checkpoint molecules are possible modulators of immunopathology in RA through their interactions with cytokines. In this study we investigated the influence of these combined biomarkers, including autoantibodies, cytokines, and immune-checkpoint molecules, on the disease activity of RA.

Materials and methods

RA patients and healthy subjects

This observational single–center study included 132 consecutive RA patients. Patients were enrolled between February 2012 and June 2020, with follow–up ending in June 2020. We retrospectively reviewed the records of these RA patients. All patients were treated in Department of Rheumatology, Fukushima Medical School from June 2009 to June 2020. All the patients met the 2010 ACR/EULAR classification criteria for the disease [25]. Probable RA or overlap syndromes; complication of autoimmune/autoinflammatory diseases, cancer, and other diseases that may affect immune checkpoint molecules and cytokines were excluded.

The following clinico–demographic data were collected from the Medical Records Unit at Fukushima University Hospital: age at the time of blood test, age at onset of RA, duration of RA, gender, and Disease Activity Score–28 for Rheumatoid Arthritis with erythrocyte sedimentation rate (DAS28-ESR). As controls, 19 healthy subjects (7 males, 12 females, median age 40 years, interquartile range [IQR]; 33–42 years) were included. This study was conducted in accordance with the principles of the Declaration of Helsinki. Ethical approval for this study (No.2019097) was provided by the Ethics Committee of Fukushima Medical University. In this study, patient`s information was collected on a medical record basis and serological biomarkers were measured using stored remaining serum of blood used for daily clinical practice. For this reason, there were many patients who were no longer attending our hospital, and we informed the participants of the study by disclosing the information on our website. This has been approved by the Ethics committee of our hospital.

Measurement of clinical disease activity

All patients underwent clinical assessment at baseline, including 28–joint swollen and tender joint counts (28–SJC and 28–TJC, respectively), physician and patient global assessment with visual analogue scales (0–100 mm) and ESR (mm/h). The composite disease activity indices were subsequently calculated: DAS28–ESR, the group of 3.2≤ DAS28–ESR ≤5.1 points was defined as moderate disease activity while the group of 5.1< DAS28–ESR was defined as severe disease activity. The anti–CCP antibodies were analyzed using commercially available second–generation chemiluminescent enzyme immunoassay kits (STACIA® MEBLuxTM CCP test, Medical and Biological Laboratories, Aichi, Japan) according to the manufacturer’s instructions. The results were reported qualitatively where negative or positive for anti-CCP antibody was defined as <4.5U/ml or ≥4.5 U/ml, respectively. Radiographs were taken of both hands of each patient.

Two rheumatologists, blinded to the patient’s identify and functional status, independently graded each hand radiographs and assigned as Steinbrocker radiographic stage [26]. Stage I is the early RA stage which do not occur joint damage. In Stage II, bone erosion is seen on hand radiographs, but no joint deformity. In Stage III, joint deformity is observed and, in Stage IV, bone ankylosis is observed.

ELISA methods

Serum concentrations of Gal–9 (No. DGAL90), sTIM-3 (No. DTIM30), IL–6 (No. HS600C) and TNF–α (No. HSTA00E) were measured using enzyme–linked immnunosorbent assay kit (R&D Systems, Minneapolis, MN, USA) according to the manufacturer’s instructions. The mean of minimum detectable dose (MDD) in this study was as follows: IL–6, <0.06 pg/mL; TNF–α, <0.092 pg/mL; Gal–9, <0.205 ng/mL; and sTIM–3, <0.265 pg/mL.

Statistical analysis

Results were non–normally distributed and are presented throughout the manuscript with median and interquartile range [IQR], and were compared by the Mann-Whitney U test. Correlations between continuous variables were analyzed by the Spearman’s rank correlation test. All data entry and statistical analyses were performed using SPSS Statistics version 22.0 (IBM, Armonk, NY). In all the analyses, a 2–tailed p < 0.05 was considered statistically significant.

Results

Characteristics of patients with RA

Table 1 shows the demographic and clinical data of the 132 RA patients (35 males and 97 females) enrolled in this study. The median age at the blood test was 66 (56–73) years. The median course of RA disease was 7 (2–11) years and median DAS28-ESR levels were 3.0 (2.1–3.8). Fifty–eight (43.9%) patients had moderate or severe disease activity. The proportion of ACPA–negative (<4.5 U/mL) patients was 11% (14 of 132). The proportion of patients with elevated ACPA titers (≥200 U/mL) was 33% (43 of 132). The use of biologics was 31.8% (42 of 132) and subdivided into anti–TNF–α antibody group (n = 17), anti–IL–6 receptor antibody group (n = 10), and others (n = 15).

Table 1. Baseline characteristics of 132 Japanese patients with RA.

Characteristics Value
Age at blood test (years), median (IQR) 66 (56–73)
Age at onset (years), median (IQR) 57 (47–65)
Female, n (%) 97 (73.5)
Smoker, n (%) 48 (36.4)
RA–ILD, n (%) 32 (24.2)
Duration of RA (year), median (IQR) 7 (2–11)
ESR (mm/h), median (IQR) 17 (8.25–30)
RF (IU/mL), median (IQR) 43.5 (11–156.3)
Anti CCP–Ab (U/mL), median (IQR) 58.9 (2.45–344)
Corticosteroid, n (%) 61 (46.2)
Methotrexate, n (%) 68 (51.5)
Biologics, n (%) 42 (31.8)
    Anti–TNF–α antibody 17 (12.9)
    Anti–IL–6 receptor antibody 10 (7.5)
    Other 15 (11.4)
DAS28–ESR, median (IQR) 3.0 (2.1–3.8)
Steinbrocker stage Ⅰ:39, Ⅱ:43, Ⅲ:2, Ⅳ:14
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CCP = cyclic citrullinated peptide, DAS28 = Disease Activity Score, ESR = erythrocyte sedimentation rate, RF = rheumatoid factor, ILD = interstitial lung disease, IQR = interquartile range.

Serum levels of cytokines

The baselines serum levels of cytokines and immune-checkpoint molecules in healthy controls were as follows. The median [IQR], minimum and maximum baseline–IL–6 values were 0.432 pg/mL [<0.06–1.295 pg/mL], less than 0.06 pg/mL and 3.645 pg/mL respectively. On the other hand, TNF–α was undetectable in healthy subjects. The median [IQR], minimum and maximum baseline–Gal–9 values were 3.843 ng/mL [3.224–4.559 ng/mL], 2.439 ng/mL and 6.277 ng/mL, and baseline–sTIM–3 values were 870.547 pg/mL [643.592–2058.551 pg/mL], 390.551 pg/mL and 2269.525 pg/mL respectively. To assess the cytokine profiles correspondeing to RA phenotype, we measured the serum levels of IL–6 and TNF–α in RA patients. Serum levels of IL–6 was significantly higher in RA patients (median [IQR], 8.37 [1.87–23.84] pg/mL) than healthy controls (median [IQR], 0.43 [0.06–1.30] pg/mL) (S1 Fig). Although serum TNF-α level was not detected in HC, patients with RA showed elevated serum levels of TNF–α (median [IQR], 0.48 [0.15–0.99] pg/mL). There were no significant differences in serum levels of IL-6 or TNF-a between RA patients with and without RF. Fig 1 shows the relationship between serum levels of IL–6 and TNF–α in RA patients. To confirm the distribution of IL–6 and TNF–α, the patients treated with anti–IL–6 antibodies and anti–TNF–α antibodies were excluded. Interestingly, circulating levels of IL–6 and TNF–α were elevated independently each other; a majority of RA patients presented with high level of IL–6 plus low TNF–α level or high level of TNF–α plus low IL–6 level. Only few RA patients had high levels of both cytokines.

Fig 1. Relationship between serum levels of TNF–α and IL–6 in RA patients.

Fig 1

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The serum levels of IL–6 and TNF–α were elevated and be not correlated with each other.

Serum levels of co-inhibitory checkpoint molecules (S2A and2B Fig)

Consistent with previous reports [21], serum levels of Gal–9 in RA patients (median [IQR], 7.84 [5.69–10.38] pg/mL) were significantly higher than those in HC (median [IQR]; 3.84 [3.22–4.56] pg/mL). Similarly, serum levels of sTIM–3 in RA patients (median [IQR], 2,628 [1,891–3,664] pg/mL) were significantly higher than those in HC (median [IQR], 871 [644–2,059] pg/mL) [22].

Correlation of serum levels of cytokines with biomarkers in RA patients

Table 2 shows the correlation of baseline serum levels of cytokines and biomarkers. There was a significant positive correlation between cytokines (IL–6 or TNF–α) and co–inhibitory checkpoint molecules (Gal–9 and sTIM–3). However, there was no significant correlation between serum levels of cytokines (IL–6 or TNF–α) and ACPA titers.

Table 2. Correlation of baseline serum levels of cytokines biomarkers.

IL–6 TNF–α Gal–9
rs P value rs P value rs P value
IL–6 - - 0.275 0.001 0.326 <0.001
TNF–α 0.275 0.001 - - 0.358 <0.001
Gal–9 0.326 <0.001 0.358 <0.001 - -
sTIM–3 0.281 0.001 0.215 0.015 0.517 <0.001
ACPA -0.044 0.620 0.029 0.744 0.294 0.001
sTIM–3 ACPA
rs P value rs P value
IL–6 0.281 0.001 -0.044 0.620
TNF–α 0.215 0.015 0.029 0.744
Gal–9 0.517 <0.001 0.294 0.001
sTIM–3 - - 0.236 0.007
ACPA 0.236 0.007 - -
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The results were obtained using Spearman`s correlation coefficient. ACPA = anti-citrullinated peptide antibodies. Gal–9 = galectin–9, IL–6 = interleukin–6, sTIM–3 = serum T cell immunoglobulin mucin–3, TNF–α = tumor necrosis factor–α.

In our previous study, we found that the association between serum levels of Gal–9 or sTIM–3 and ACPA was modulated by the status of ACPA titers [21, 22]. The cutoff value of ACPA titer (200 U/mL) was determined according to the ability to extract the strongest correlation among Gal-9 or sTIM-3 and ACPA titer. We investigated the correlation between circulating cytokines and clinical parameters after dividing RA patients into two groups, based on the presence or absence of high ACPA titers (≥200 U/mL) [21, 22]. As shown in Fig 2, there were significant correlations between serum levels of cytokines (IL–6 or TNF–α) and RA disease activity (DAS28–ESR), and these correlations were not modulated by the high status of ACPA titer (≥200 U/mL). Serum levels of cytokines (IL–6 or TNF–α) were significantly correlated with those of Gal-9 (Fig 3). As shown in Fig 4, there were significant correlations between serum levels of cytokines (IL–6 or TNF–α) and sTIM–3 in RA patients with low–medium levels of ACPA titers (<200 U/mL). However, there was no significant correlation between serum levels of cytokines (IL–6 or TNF–α) and sTIM–3 under the high status of ACPA titers (≥200 IU/mL).

Fig 2. Relationship between serum levels of cytokines (IL–6 or TNF–α) and RA disease activity (DAS28–ESR) in the sub–grouped RA patients according to the titers of ACPA.

Fig 2

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There were significant positive correlations between serum levels of cytokines (IL–6 or TNF–α) and RA disease activity (DAS28–ESR), and these correlations were not modulated by the status of ACPA titer. The correlations were determined using Spearman’s rank correlation test.

Fig 3. Relationship between serum levels of cytokines (IL–6 or TNF–α) and Gal–9 in the sub–grouped RA patients according to the titers of ACPA.

Fig 3

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There were significant correlations between serum levels of cytokines (IL–6 or TNF–α) and Gal–9, and these correlations were not modulated by the high status of ACPA titers. The correlations were determined using Spearman’s rank correlation test.

Fig 4. Relationship between serum levels of cytokines (IL–6 or TNF–α) and sTIM–3 in the sub–grouped RA patients according to the titers of ACPA.

Fig 4

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There were significant correlations between serum levels of cytokines (IL–6 or TNF–α) and sTIM–3 in RA patients with low-medium levels of ACPA titers (<200 U/mL). However, there was no significant correlation between serum levels of cytokines (IL–6 or TNF–α) and sTIM–3 in RA patients with high titers of ACPA (≥200 IU/mL). The correlations were determined using Spearman’s rank correlation test.

Relationship between cytokines and Gal–9 according to the joint destruction stage

Serum Gal–9 levels were significantly higher in RA patients with advanced joint damage (stage II–IV) compared to those without joint damage (Stage I) (S3 Fig). We hypothesized that the elevated levels of Gal–9 in RA patients with advanced joint damage were linked with serum levels of cytokines. We compared the serum levels of cytokines between RA patients with or without advanced rheumatoid joint damage (Stage I versus Stage II–IV). Serum levels of TNF-α in RA patients with advanced joint damage (Stage II–IV) were significantly higher than those in patients without advanced joint damage (Stage I) (p = 0.0265, S4A Fig). Similarly, serum levels of IL–6 in RA patients with advanced joint damage were higher than those in patients without advanced joint damage; however, the difference between the 2 groups was not statistically significant (p = 0.1733, S4B Fig).

RA patients with advanced joint damage (Stage II–IV) showed elevated serum levels of Gal–9. Therefore, we assessed the correlation between cytokines and Gal–9 under the differential rheumatoid joint damage stage. As known in Fig 5A, RA patients without advanced joint damage showed a positive correlation between IL–6 and Gal–9. In contrast, there was a significant correlation between TNF–α and Gal–9 in RA patients with advanced rheumatoid joint damage (Stage II–IV) (Fig 5B). This positive correlation between TNF–α and Gal–9 was more markedly observed (Fig 6) in RA patients with high ACPA titers (≥200 IU/mL).

Fig 5. Relationship between serum levels of cytokines (IL–6 or TNF–α) and Gal–9 in RA patients with or without advanced joint damage.

Fig 5

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(A) There was a significant correlation between IL–6 and Gal–9 in RA patients without advanced joint damage (Stage I). (B) Conversely, there was a significant correlation between TNF–α and Gal–9 in RA patients with advanced rheumatoid joint damage (Stage II–IV). The correlations were determined using Spearman’s rank correlation test.

Fig 6. Relationship between serum levels of cytokines (IL–6 or TNF–α) and Gal–9 in RA patients with high ACPA titers (≥200 IU/mL).

Fig 6

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(A) There was a significant correlation between IL–6 and Gal–9 in RA patients without advanced joint damage (Stage I). (B) In contrast, there was a significant correlation between TNF–α and Gal–9 in RA patients with advanced rheumatoid joint damage (Stage II–IV). The correlations were determined using Spearman’s rank correlation test.

Discussion

Dysregulated cytokine production plays an important role in the progression of RA [4]. Given the complexity and heterogeneous nature of RA, it is unlikely that a single cytokine may explain the pathophysiology of RA [27]. Among these cytokines, the interplay between TNF–α and IL–6 is known to play a significant role in the inflammatory processes in RA [3, 4, 7, 8, 28]. Anti–TNF–α therapy resulted in the resolution of elevated levels of IL–6 and acute–phase reactant showing the central role of TNF–α in the pathogenesis of RA [29]. Although IL–6 has not been found to have a crucial role in the effector phase of experimental arthritis, blockade of IL–6 receptor is effective in improving clinical symptoms in RA patients. These findings suggest an independent involvement of IL–6 in rheumatoid inflammation in a fraction of RA patients. Our results indicated the differential regulation of serum levels of TNF–α and IL–6 in patients with established RA. Serum concentrations of TNF–α were relatively low for determination by detection methods contributing to the conflicting outcomes of investigations using RA patients’ sera [27]. In this context, we determined the serum TNF–α concentrations using high–sensitive ELISA method. Our data revealed that majority of RA patients presented with low or marginal levels of serum TNF–α levels, however, circulating TNF–α was detectable in a few patients with RA. In the sub–group of RA patients with low serum levels of TNF–α, IL–6 was randomly distributed and be correlated with rheumatoid inflammatory markers such as ESR. Although there was no significant association between ACPA titers and circulating TNF–α or IL–6 levels, our data demonstrated the associations of these cytokines and co-inhibitory checkpoint molecules under particular ACPA status.

Serum Gal–9 levels were correlated with TNF–α and IL–6, independent of the ACPA titer status. However, elevated levels of sTIM–3 showed positive correlations with these cytokines only in RA patients without high titer of ACPA (<200 U/mL). Shedding of TIM–3 is found LPS–activated CD14⁺ monocytes or TIM–3 expressing T cell in patients with GVHD after hematopoietic cell transplantation [30, 31]. TIM–3 is a co–inhibitory receptor that is expressed on T cells or innate immune cells, where it has been shown to regulation of their immune responses [32]. TIM–3 expression on CD4⁺ and CD8⁺ T cells in peripheral blood or synovial fluid was shown to be increased in RA patients [33]. Furthermore, the percentage of TIM–3 expressing CD4⁺ and CD8⁺ T cells was negatively correlated with RA disease activity [34]. It was also demonstrated that the expression levels of TIM–3 on T cells was also inversely correlated with plasma TNF levels in RA patients [34]. Taken together, our data suggest that TIM–3 shedding process can be differentially regulated by ACPA status and serum levels of sTIM–3 could be linked with the elevated levels of inflammatory cytokines in RA patients without high titers of ACPA (<200 U/mL).

Additionally, we found that the correlation between Gal–9 and inflammatory cytokines was modulated by the rheumatoid joint damage stage. Strong association of Gal–9 with circulating TNF–α, but not with IL–6, was demonstrated in RA patients with advanced joint damage (Stage II–IV). This tendency was more dominant in RA patients with high titers of ACPA (≥200 IU/mL). Conversely, serum levels of Gal–9 showed a stronger correlation with IL–6 in RA patients without advanced joint damage (Stage I). These findings suggest that the interaction between IL–6 and Gal–9 may be involved in rheumatoid inflammation in the early stage of RA. In contrast, interaction between TNF–α and Gal–9 may be involved in RA progression in advanced stages of joint destruction. The dual role of Gal–9, in correlating with inflammatory cytokines or ACPA titers may define the hierarchical position of RA phenotype or progression. These data suggest that the interplay between inflammatory cytokines and checkpoint molecules may differentially contribute to the rheumatoid inflammatory and articular destruction processes.

Gal–9 and these inflammatory cytokines seem to be upregulated during rheumatoid inflammation [35, 36]. However, the mechanism by which these molecules are regulated under the inflammatory or autoimmune conditions in various RA patients is not understood. Circulating Gal–9 could be a useful biomarker to monitor disease activity and facilitate personalized treatment [37]. Gal–9 is anti–inflammatory as suggested in RA model mice, collagen–induced arthritis, in which Gal–9 injection suppressed osteoclasto genesis through the Gal–9/TIM–3 pathway [20]. Conversely, in RA patients, decreased Gal-9/TIM-3 signaling has been observed since the expression levels of TIM–3 on CD4+ T cells were lower compared to those from healthy controls [38–40]. Although its function is not fully elucidated, Gal–9 is a potent immune regulator and modulates rheumatoid inflammation and joint destruction [35].

TNF–α was shown to induce the secretion of Gal–9 by mesenchymal stem cells in vitro [41]. Conversely, TNF–α downregulated the surface expressions of TIM–3 on T cells probably by shedding mechanism [28]. Although the expression of TIM–3 on immune cells were not investigated in our study, the co–inhibitory Gal–9/TIM–3 pathways can be downregulated by decoy function of circulating sTIM–3. Gal–9 seems to be reciprocally upregulated to regulate the rheumatoid inflammation; however, sTIM–3, which is elevated in RA patients, can competitive inhibit this co–inhibitory Gal–9/TIM–3 pathway. Further studies are required to elucidate the mechanism by which these cytokines and immune–checkpoint molecules co–modulate the rheumatoid inflammatory processes.

Several potential limitations of this study should be considered while interpreting the results. First, the patient population was relatively small. A larger study is required to provide more definitive evidence. Second, although this study should be designed as age-matched case control study, which could not be performed due to the enrollment of elderly RA patients. Therefore, the possibility of biased matching processes cannot be excluded. Third, all patients with RA and healthy individuals in this study were Japanese; additional studies in other ethnic groups are required to verify these findings. Fourth, a majority of the patients were already undergoing treatment; therefore, our findings may not be generalizable to untreated RA patients. Finally, future studies should examine the longitudinal changes in serum Gal-9, sTIM-3, IL-6, and TNF-α levels in patients with RA and assess their clinical course.

Conclusions

Serum levels of the co–inhibitory checkpoint molecules were elevated and corelated with circulating inflammatory cytokines, IL–6 or TNF–α in RA patients. These interactions seem to be modulated by ACPA status or RA joint damage stage.

Supporting information

S1 Fig. Serum levels of IL-6 among RA patients (n = 132) and healthy controls (HCs, n = 19).

Serum levels of IL-6 in RA patients were significantly higher compared to those in healthy HCs. Statistical significance was determined by Mann-Whitney U test.

(TIFF)

Click here for additional data file. (3.8MB, tiff)
S2 Fig. Serum levels of Gal-9 and sTIM-3 in RA patients (n = 132) and HCs (n = 19).

(A) Serum levels of Gal-9 in RA patients were significantly higher compared to those in HCs. (B) Serum levels of sTIM-3 in RA patients were significantly higher compared to those in HCs. Statistical significance was determined by Mann-Whitney U test.

(TIFF)

Click here for additional data file. (5.5MB, tiff)
S3 Fig. Serum levels of Gal-9 between RA patients (n = 132) with or without advanced joint damage (Stage II-IV).

Serum levels of Gal-9 were significantly higher in RA patients with advanced joint damage (stage II–IV) compared to those without advanced joint damage (Stage I). Statistical significance was determined by Mann-Whitney U test.

(TIFF)

Click here for additional data file. (4.8MB, tiff)
S4 Fig. Serum levels of cytokines (IL-6 or TNF-α) in RA patients with or without advanced joint damage.

(A) Serum levels of TNF-α in RA patients with advanced joint damage were significantly higher than those in RA patients without advanced joint damage. (B) Serum levels of IL-6 in RA patients with advanced joint damage (Stage II-IV) were higher than those in RA patients without advanced joint damage (Stage I); however, there was no significant difference. Statistical significance was determined by Mann-Whitney U test.

(TIFF)

Click here for additional data file. (5.8MB, tiff)
S1 File

(DOCX)

Click here for additional data file. (27KB, docx)

Acknowledgments

We are grateful to Ms Sachiyo Kanno for her technical assistance in this study.

Data Availability

All relevant data are within the manuscript and its Supporting Information files.

Funding Statement

The study was supported by the Japan Grant-in-Aid for Scientific Research(C 17K09981). KM is received this grant. URL:https://www.jsps.go.jp/english/e-grants/ They did not play any role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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Decision Letter 0

Pierre Busson

11 Aug 2021

PONE-D-21-21033

Association between inflammatory cytokines and immune-checkpoint molecule in rheumatoid arthritis

PLOS ONE

Dear Dr. Migita,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised by the reviewer.

I think that it is of special importance to pay attention to his general recommendation to highlight the main conclusions of your study, peraphs with choosing to delete some graphs.

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2. We noticed you have some minor occurrence of overlapping text with the following previous publication(s), which needs to be addressed:

- https://arthritis-research.biomedcentral.com/articles/10.1186/s13075-020-02158-3

- https://journals.lww.com/md-journal/Fulltext/2020/10300/T_cell_immunoglobulin_and_mucin_domain_3_is.44.aspx

In your revision ensure you cite all your sources (including your own works), and quote or rephrase any duplicated text outside the methods section. Further consideration is dependent on these concerns being addressed.

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Additional Editor Comments:

To be revised according to the recommendations of the reviewer. Higlight key messages and if necessary reduce the number of graphs.

[Note: HTML markup is below. Please do not edit.]

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Reviewer #1: Partly

**********

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Reviewer #1: Yes

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Reviewer #1: Yes

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Reviewer #1: Reviewer Recommendation and Comments for Manuscript Number PONE-D-21-21033

Matsumoto et al. represents measurements of Gal-9, sTim-3, IL-6 and TNFa and radiographic staging in 132 patients with established and actively treated RA.

The key finding is that different associations between serum cytokines and soluble immune-checkpoint molecules is altered by their ACPA-status and in general differ between patients notably on different treatments.

In general, an interesting subject but with the descriptive data included in the present paper it is difficult to draw any robust conclusions on the relationship between serum cytokines, soluble immune-checkpoint molecules and ACPA-status.

A short method sections furthers challenges the conclusions being made.

Interesting data that would be of interest to the field but that in its current form needs revisions to increase the impact and sharpens the conclusions.

MAJOR COMMENTS

• In light of the hypotheses – why measure Gal-9 (which is neither an immune-checkpoint molecule nor a cytokine)? Further Gal-9 is not mentioned in the introduction or background session. Why Tim-3 out of multiple interesting immune checkpoint molecules (PD-1, 4-1BB, OX-40 ect). – please elaborate.

• Due to the cross-sectional study design, it is difficult to relate these measurements to progression of RA as indicated in the last part of the background session. Further, on page 20 in the discussion it is stated that … these data suggests that the interplay between inflammatory cytokines and checkpoint molecules may differentially contribute to the RA inflammation and articular destruction processes and page 3 in the conclusions …They may be usefull markers for predicting the phenotype and personalized treatment of RA.

But since possible interactions, phenotypes or personalized treatment were never studied by the present paper together with the cross-sectional design of the study makes these statements a bit speculative. Association is not the same as causality.

In this light the multiple sections on interactions and possible biomarker potential are a bit speculative and not well substantiated by the data presented.

In general, consider aligning the hypotheses and conclusions to better reflect the descriptive design and results being presented.

• Biologics are grouped without mentioning what specific treatment the patients were given at the time of serum acquisition. This is of key importance since many patients receive anti-IL6 or Anti-TNF that would immensely affect the measurements of exactly these to cytokines. Further CRP is not useful in patient on IL-6 treatments. Please clarify the treatments and consider omitting the anti-IL-6 and TNF treated patients from the analyses.

• Considerable difference between the age of the healthy controls and the patients please comment on the potential role of this in the present paper.

• ELISA: What were the cut-off values? Did you test for interference by rheumatoid factor and heterophilic antibodies? – of particular interest since sero-positive and sero-negative patients are being compared.

(Kragstrup, T. W., Vorup-Jensen, T., Deleuran, B., & Hvid, M. (2013). A simple set of validation steps identifies and removes false results in a sandwich enzyme- linked immunosorbent assay caused by anti- animal IgG antibodies in plasma from arthritis patients. SpringerPlus, 2(1), 1–1. http://doi.org/10.1186/2193-1801-2-263)

• Why make a continuous variable as ACPA-titers into a dichotomic? – please elaborate. Are there any correlation between the titers of ACPA and the cytokines / soluble immune checkpoint molecules or Gal-9? Would be interesting to address?

• TNFα is generally being considered a driver of IL-6 (Charles, P., Elliott, M. J., Davis, D., Potter, A., Kalden, J. R., Antoni, C., et al. (1999). Regulation of cytokines, cytokine inhibitors, and acute-phase proteins following anti-TNF-alpha therapy in rheumatoid arthritis. J. Immunol. 163 (3), 1521–1528.). Please elaborate and discuss the finding that the patients either had high IL-6 or TNF but not both.

• If the different serum cytokines, soluble immune-checkpoint molecules and Gal-9 are combined which combination have the highest predictive value towards high disease activity or structural damage. – This could be a need place for the present paper to increase the value/impact of the results presented.

• Consider to focus on one aspect and reducing the numbers of graphs with relatively limited importance for the conclusions to avoid data overload and blurring of the key massages.

MINOR COMMENTS

•

• MMP3 is mentioned as a biomarker of joint damage page 6 and in table 1 but never mentioned in figures or the result session later in the paper – consider include or omit completely.

• How is moderate or severe disease activity defined?, how is overlap syndrome being defined?

• Consider getting the manuscript corrected grammatically to sharpen small errors?

• Please relate the cytokine and Gal-9 levels to other publications on RA patients measuring these proteins.

• Consider putting your figures in a table to increase the comparison between different correlations and the impact of ACPA and remove figures to supplementary.

• Change the scale on the y-aksis of figure 1 to increase the área between 0-100 were the vast majority of the data is situated.

**********

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Reviewer #1: No

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PLoS One. 2021 Nov 18;16(11):e0260254. doi: 10.1371/journal.pone.0260254.r002

Author response to Decision Letter 0

17 Sep 2021

Response to Journal Requirements.

We wish to express our appreciation to your insightful comments on our paper. The comments have helped us significantly improve the paper.

Comment

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at

https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf

and

https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf

Response

I appreciate for your critical comment. It has been reworked to meet the style of PLOS ONE`s style.

Comment

2. We noticed you have some minor occurrence of overlapping text with the following previous publication(s), which needs to be addressed:

- https://arthritis-research.biomedcentral.com/articles/10.1186/s13075-020-02158-3

- https://journals.lww.com/md-journal/Fulltext/2020/10300/T_cell_immunoglobulin_and_mucin_domain_3_is.44.aspx

In your revision ensure you cite all your sources (including your own works), and quote or rephrase any duplicated text outside the methods section. Further consideration is dependent on these concerns being addressed.

Response

I appreciate your pertinent comment. We have quoted or rephrased as necessary outside the methods section.

Comment

3. Please provide additional details regarding participant consent. In the Methods section, please ensure that you have specified (1) whether consent was informed and (2) what type you obtained (for instance, written or verbal). If your study included minors, state whether you obtained consent from parents or guardians. If the need for consent was waived by the ethics committee, please include this information.

Response

Thank you for your comment. In this study, patient information was collected on a medical record basis and serological biomarkers were measured using stored remaining serum of blood used for medical treatment. For this reason, there were many patients who were no longer attending our hospital, and we informed the participants of the study by disclosing the information on our website. This is also mentioned in the article.

Comment

4. We note that you have stated that you will provide repository information for your data at acceptance. Should your manuscript be accepted for publication, we will hold it until you provide the relevant accession numbers or DOIs necessary to access your data. If you wish

to make changes to your Data Availability statement, please describe

these changes in your cover letter and we will update your Data Availability statement to reflect the information you provide.

Response

I apologize for the inconvenience. Minimal data used in this study were prepared and sent to you.

Response to Reviewer.

We wish to express our appreciation to your insightful comments on our paper. The comments have helped us significantly improve the paper.

Major comments.

Comment

• In light of the hypotheses – why measure Gal-9 (which is neither an immune-checkpoint molecule nor a cytokine)? Further Gal-9 is not mentioned in the introduction or background session. Why Tim-3 out of multiple interesting immune checkpoint molecules (PD-1, 4-1BB, OX-40 ect). – please elaborate.

Response

I appreciate your significant comment. TIM-3 was detected in osteoclasts and its mononuclear precursor cells in rheumatoid synovium, and the Gal-9/TIM-3 pathway regulatory system controls osteoclastogenesis and inflammatory bone destruction in RA. In fact, in our previous report, serum Gal-9 and sTIM-3 were significantly elevated in RA patients compared with healthy subjects. Therefore, we also focused on the Gal-9/TIM-3 pathway in this study. This information is also added in this article.

Comment

• Due to the cross-sectional study design, it is difficult to relate these measurements to progression of RA as indicated in the last part of the background session. Further, on page 20 in the discussion it is stated that … these data suggests that the interplay between inflammatory cytokines and checkpoint molecules may differentially contribute to the RA inflammation and articular destruction processes and page 3 in the conclusions …They may be useful markers for predicting the phenotype and personalized treatment of RA. But since possible interactions, phenotypes or personalized treatment were never studied by the present paper together with the cross-sectional design of the study makes these statements a bit speculative.

Association is not the same as causality. In this light the multiple sectionson interactions and possible biomarker potential are a bit speculative and not well substantiated by the data presented.

In general, consider aligning the hypotheses and conclusions to better reflect the descriptive design and results being presented.

Response

In the case of unclear causality, the description was changed to suggest the possibility of an association rather than a causality. As you pointed out, the following sentence in the conclusion is nothing but a conjecture and was deleted from the text. “Measurement of serum IL-6 and TNF-α concentrations in combination with checkpoint molecules may help predict the phenotypic alternations of RA.”

Comment

• Biologics are grouped without mentioning what specific treatment the patients were given at the time of serum acquisition. This is of key importance since many patients receive anti-IL6 or Anti-TNF that would immensely affect the measurements of exactly these to cytokines.

Further CRP is not useful in patient on IL-6 treatments. Please clarify the treatments and consider omitting the anti-IL-6 and TNF treated patients from the analyses.

Response

Thank you for your significant comment. Biologics was subdivided into anti-TNF-α antibody group (n=17), anti-IL-6 antibody group (n=10), and others (n=15). In addition, we remake Figure 2 by excluded the anti-TNF-α antibody group and anti-IL-6 antibody group. There was no significant difference in the distribution of IL-6 and TNF-α between the new figure and the old Figure 2. In addition, we used the DAS28-ESR instead of the DAS28-CRP to evaluate disease activity because, as you pointed out, the inclusion of the IL-6-treated group would make the evaluation of activity by CRP levels inappropriate.

Comment

• Considerable difference between the age of the healthy controls and the patients please comment on the potential role of this in the present paper.

Response

I appreciate for your comment. The healthy controls were volunteers who collected serum samples from the employees of our institution. Therefore, their ages are younger than peak age of RA patients. As you pointed out, the age of the control group is younger than that of RA patients, so, this item has been added to the limitation section.

Comment

• ELISA: What were the cut-off values? Did you test for interference by rheumatoid factor and heterophilic antibodies? – of particular interest since sero-positive and sero-negative patients are being compared. (Kragstrup, T. W., Vorup-Jensen, T., Deleuran, B., & Hvid, M. (2013).

A simple set of validation steps identifies and removes false results in a sandwich enzyme- linked immunosorbent assay caused by anti- animal IgG antibodies in plasma from arthritis patients. SpringerPlus, 2(1), 1–1. http://doi.org/10.1186/2193-1801-2-263)

(Kragstrup, T. W., Vorup-Jensen, T., Deleuran, B., & Hvid, M. (2013).

A simple set of validation steps identifies and remove false results in a sandwich enzyme-linked immunosorbent assay caused by anti animal IgG antibodies in plasma from arthritis patients. SpringerPlus, 2(1), 1-1. http://doi.org/10.1186/2193-1801-2-263)

Response

Thank you for your significant comment. The detection limit of each product used in the ELISA and the detection limit in this study have been added to the text.

Gal-9, sTIM-3, IL-6 and TNF-α was compared between the RF positive and negative groups, but no significant difference was observed between two groups. So, we concluded that there was no RF interference in the ELISA.

Comment

• Why make a continuous variable as ACPA-titers into a dichotomic? – please elaborate. Are there any correlation between the titers of ACPA and the cytokines / soluble immune checkpoint molecules or Gal-9? Would be interesting to address?

Response

ACPA titers do not correlate with cytokine (IL-6 and TNF-α) in this study. Previous reports by our department showed that the correlation between ACPA and immune checkpoint molecules (Gal-9 and sTIM-3) was clearly dichotomized by setting ACPA 200 U/mL as a cut off. Therefore, we judged that the cutoff titer of ACPA 200 U/mL is appropriate for clarify the correlation between cytokines and immune checkpoint molecules in this study.

Comment

• TNFΑ is generally being considered a driver of IL-6 (Charles, P., Elliott, M. J., Davis, D., Potter, A., Kalden, J. R., Antoni, C., et al. (1999). Regulation of cytokines, cytokine inhibitors, and acute-phase proteins following anti-TNF-alpha therapyin rheumatoid arthritis. J. Immunol. 163 (3), 1521–1528.). Please elaborate and discuss the finding that the patients either had high IL-6 or TNF but not both.

Response

I appreciate for your pertinent comment. Anti-TNF-α therapy resulted in the resolution of elevated levels of IL-6 and acute-phase reactant showing the central role of TNF-α in the pathogenesis of RA. Although IL-6 has not been found to have a crucial role in the effector phase of experimental arthritis, blockade of IL-6 receptor is effective in improving clinical symptoms in RA patients. These findings suggest an independent involvement of IL-6 in rheumatoid inflammation in a subset of RA patients. However, the distribution of IL-6 and TNF-α showed that IL-6 and TNF-α were visually elevated independently. As mentioned earlier, this trend was also observed when the anti-IL-6 and anti-TNF-α antibody groups were excluded.

Comment

• If the different serum cytokines, soluble immune-checkpoint molecules and Gal-9 are combined which combination have the highest predictive value towards high disease activity or structural damage. – This could be a need place for the present paper to increase the value/impact of the results presented.

Response

Thank you for your comment. The highest correlation with DAS28-ESR, an index of disease activity, were found for IL-6 (r=0.394, p<0.001) in ACPA<200 U/mL and TNF-α (r=0.260, p=0.018) in ACPA≥200 U/mL. Gal-9 is positively correlated with each cytokine at low and high ACPA titer and may be an indicator of disease activity. Thus, in ACPA <200 U/mL, the combination of IL-6 and Gal-9 may be useful in predicting disease activity and structural damage in patients. In contrast, in ACPA≥200 U/mL, the combination of TNF-α and Gal-9 in patients may be useful.

Comment

• Consider to focus on one aspect and reducing the numbers of graphs with relatively limited importance for the conclusions to avoid data overload and blurring of the key massages.

Response

Thank you for your comment. As you pointed out, we have narrowed down the data and focused the discussion on important items.

Miner comments.

Comment

• MMP3 is mentioned as a biomarker of joint damage page 6 and in table 1 but never mentioned in figures or the result session later in the paper – consider include or omit completely.

Response

Thank you for your significant comment. MMP-3 was excluded from the list, including Table 1.

Comment

• How is moderate or severe disease activity defined?, how is overlap syndrome being defined?

Response

I appreciate your comment. The group of 3.2 ≤ DAS28-ESR ≤ 5.1 points was defined as moderate disease activity, and the group of 5.1 < DAS28-ESR was defined as severe disease activity. Together, they are described as moderate or severe activity. Overlap syndrome is a complication of autoimmune/autoinflammatory diseases, cancer, and other diseases that may affect immune checkpoints and cytokines. This is added in methods.

Comment

• Consider getting the manuscript corrected grammatically to sharpen small errors?

Response

Thank you for your comment. Some grammatical corrections have been made.

Comment

• Please relate the cytokine and Gal-9 levels to other publications on RA patients measuring these proteins.

Response

Thank you for your pertinent comment. The previous report on proinflammatory cytokines and Gal-9/TIM-3 was added to Background.

Comment

• Consider putting your figures in a table to increase the comparison between different correlations and the impact of ACPA and remove figures to supplementary.

Response

Thank you for your significant comment. Some figures have been moved to supplementary to clarify the issues.

Comment

• Change the scale on the y-aksis of figure 1 to increase the Área between 0-100 were the vast majority of the data is situated.

Response

I appreciate for your comment. Figure 1 has been corrected as you suggested and moved to supplemental.

Attachment

Submitted filename: Response to Reviewer ver2.docx

Click here for additional data file. (22.4KB, docx)

Decision Letter 1

Pierre Busson

8 Nov 2021

Association between inflammatory cytokines and immune–checkpoint molecule in rheumatoid arthritis

PONE-D-21-21033R1

Dear Dr. Migita,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Please find below some suggestions of minor corrections.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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Kind regards,

Pierre Busson, MD, PhD, Res Director

Academic Editor

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Additional Editor Comments (optional):

Suggestions of corrections:

- Abstract p.2 line 6 : « …osteoclasts and is involved …» instead of « …osteoclasts and be involved …»

- Abstract p.2 line 7 :”…to investigate the relationships between…”instead of ”…to investigate the association between…”

- Introduction p.4 line 17 “…involved in negative regulation of …” instead of “…involved in negative regulator of …”

- Introduction p.5 line 5 “…A relationship between…” instead of “…The relationship between…”

- Materials and Methods p.7 line 6 “…disease activity while the group…” instead of “…disease activity; and the group…”

- Results p.10 line 9 “…corresponding to…” instead of “…corresponded to …”

- Discussion p.17, line 17 :”…in a fraction of RA patients…” instead of “…in a certain of RA patients…”

- Conclusion p.22, line 5 : “…with circulating inflammatory cytokines…” instead of “…with circulating inflammatory arthritis…”

Reviewers' comments:

Acceptance letter

Pierre Busson

10 Nov 2021

PONE-D-21-21033R1

Association between inflammatory cytokines and immune–checkpoint molecule in rheumatoid arthritis

Dear Dr. Migita:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

If we can help with anything else, please email us at plosone@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Pierre Busson

Academic Editor

PLOS ONE

Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Supplementary Materials

    S1 Fig. Serum levels of IL-6 among RA patients (n = 132) and healthy controls (HCs, n = 19).

    Serum levels of IL-6 in RA patients were significantly higher compared to those in healthy HCs. Statistical significance was determined by Mann-Whitney U test.

    (TIFF)

    Click here for additional data file. (3.8MB, tiff)
    S2 Fig. Serum levels of Gal-9 and sTIM-3 in RA patients (n = 132) and HCs (n = 19).

    (A) Serum levels of Gal-9 in RA patients were significantly higher compared to those in HCs. (B) Serum levels of sTIM-3 in RA patients were significantly higher compared to those in HCs. Statistical significance was determined by Mann-Whitney U test.

    (TIFF)

    Click here for additional data file. (5.5MB, tiff)
    S3 Fig. Serum levels of Gal-9 between RA patients (n = 132) with or without advanced joint damage (Stage II-IV).

    Serum levels of Gal-9 were significantly higher in RA patients with advanced joint damage (stage II–IV) compared to those without advanced joint damage (Stage I). Statistical significance was determined by Mann-Whitney U test.

    (TIFF)

    Click here for additional data file. (4.8MB, tiff)
    S4 Fig. Serum levels of cytokines (IL-6 or TNF-α) in RA patients with or without advanced joint damage.

    (A) Serum levels of TNF-α in RA patients with advanced joint damage were significantly higher than those in RA patients without advanced joint damage. (B) Serum levels of IL-6 in RA patients with advanced joint damage (Stage II-IV) were higher than those in RA patients without advanced joint damage (Stage I); however, there was no significant difference. Statistical significance was determined by Mann-Whitney U test.

    (TIFF)

    Click here for additional data file. (5.8MB, tiff)
    S1 File

    (DOCX)

    Click here for additional data file. (27KB, docx)
    Attachment

    Submitted filename: Response to Reviewer ver2.docx

    Click here for additional data file. (22.4KB, docx)

    Data Availability Statement

    All relevant data are within the manuscript and its Supporting Information files.

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