Neutrophil extracellular traps are involved in the occurrence of rheumatoid arthritis-associated interstitial lung disease

doi:10.21203/rs.3.rs-5003689/v1

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Research Article

Neutrophil extracellular traps are involved in the occurrence of rheumatoid arthritis-associated interstitial lung disease

https://doi.org/10.21203/rs.3.rs-5003689/v1

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Background

The excessive formation of neutrophil extracellular traps (NETs) has been demonstrated to be a pathogenic mechanism in both rheumatoid arthritis (RA) and interstitial lung disease (ILD). However, whether NETs contribute to RA-associated ILD (RA-ILD) and the underlying mechanisms driving NETs formation remain unclear. This study aimed to assess the involvement of NETs in RA-ILD and elucidate the underlying mechanisms.

Methods

Single-cell sequencing was used to identify changes in the quantity and function of neutrophils in the lung tissue of a zymosan A (ZYM)-induced interstitial pneumonia arthritis model, along with the detection of NETs components in the lung tissues. Additionally, nuclear receptor 4A3 (NR4A3) expression in HL-60 cells was interfered with to detect the effects on NETs components and the transformation of MRC-5 cells into myofibroblasts. The clinical relevance of plasma myeloperoxidase-DNA (MPO-DNA), citrullinated histone 3 (Cit-H3), and cell-free DNA was evaluated in patients with RA-nonspecific interstitial pneumonia (NSIP) and RA-usual interstitial pneumonia (UIP), RA-organizing pneumonia (OP), RA-other patterns, and healthy cohorts using commercial enzyme-linked immunosorbent assay (ELISA).

Results

In the ZYM-treated SKG mouse model, which recapitulates key features of RA-ILD, an increased neutrophils population in lung tissue was primarily responsible for NETs formation. Mechanistically, interference with NR4A3 expression was found to promoted NETs formation in HL-60 cells, subsequently enhancing MRC-5 cell differentiation into myofibroblasts. Clinically, plasma levels of MPO-DNA and Cit-H3 were elevated in patients with RA-NSIP and RA-UIP compared to healthy subjects. ROC curve analysis further revealed that plasma MPO-DNA combined with RF and anti-CCP, as well as Cit-H3 combined with RF and anti-CCP, served as superior diagnostic panels for NSIP and UIP in RA-ILD patients, respectively.

Conclusions

These findings suggest that targeting NETs could provide a novel therapeutic approach for ILD in RA patients.

Nuclear receptor 4

neutrophil extracellular traps

rheumatoid arthritis

interstitial lung disease

Interstitial lung disease (ILD) is a common yet often overlooked complication associated with rheumatoid arthritis (RA)^{[1, 2]}. Notably, the survival rate for RA-ILD has been reported to be as low as that of idiopathic pulmonary fibrosis (IPF)^{[3, 4]}. Despite the devastating impact of RA-ILD, its underlying pathophysiology remains poorly understood. Advanced insights into the molecular mechanisms underlying RA-ILD hold significant potential for identifying new targets for therapeutic development.

Although the mechanism underlying the aberrant regulation of inflammatory cascades and tissue remodeling in various forms of RA-ILD remains obscure, current evidence suggests that neutrophils contribute to a complex interplay between inflammation and fibrosis^{[5, 6]}. For instance, increased blood neutrophil counts have been associated with poor outcomes in patients with RA-ILD^[6]. Neutrophil deployment is tightly regulated through three major strategies: phagocytosis, degranulation and release of neutrophil extracellular traps (NETs)^[7]. NETs are large, extracellular, web-like structures composed of cytosolicand granule proteins that are assembled on a scaffold of decondensed chromatin^[8]. Recent discoveries support that NETs can contribute to the pathogenesis of immune-related diseases, including RA^[9], anti-neutrophil cytoplasmic antibody (ANCA)-associated ILD^[10], and polymyositis (PM)-associated ILD^[11]. Pérez-Sánchez et al. reported that 6 months of therapy with tocilizumab (TCZ) or infliximab improved disease activity, decreased inflammatory mediators, and decreased DNA release into the extracellular space by decreasing NETs formation in RA patients^[12]. More importantly, the clinical application of the drug development of NETs as therapeutic targets for RA is a trend for future research^[13]. In the context of ILD, Zhang et al., demonstrated that components of NETs, such as myeloperoxidase (MPO) and histones, are instrumental in the activating lung fibroblasts and their differentiation into myofibroblasts^[14]. Additionally, NETs induce the downregulation of the epithelial marker E-cadherin and upregulation of the mesenchymal marker alpha-smooth muscle actin (α-SMA) in pulmonary epithelial cells^[15]. Taken together, accumulating evidence suggests that NETs may contribute to the development of RA-ILD.

Nuclear receptor 4A3 (NR4A3[nuclear receptor subfamily 4 group A member], also known as NOR-1[Neuron-Derived Orphan Receptor 1]), along with NR4A1 and NR4A2, are transcription factors (TFs) belonging to the NR4A orphan nuclear receptor subfamily^[16]. Although NR4A3 is expressed in various cell types, the functional characterization of this molecule remains limited. Recent studies have shown that NR4A3 is upregulated in cultured Ins-1 cells and human pancreatic islets treated with IL-1β and TNF-α. Interestingly, NR4A3 knockdown mitigates cytokine-mediated apoptosis, whereas NR4A3 overexpression promotes apoptotic cell death^[17]. These findings suggest that NR4A3 exerts a pro-apoptotic effect. Moreover, one study demonstrated that oxidative stress-induced upregulation of early growth response protein 1 (EGR1) promotes NR4A3-mediated apoptosis of nucleus pulposus cells in the context of intervertebral disc degeneration^[18]. Notably, elevated levels of oxidative stress are also associated with the excessive formation of NETs in inflammatory and autoimmune diseases^[19]. These data suggest that NR4A3 may be involved in the formation of NETs.

Hence, the primary objective of this study was to explore the correlation between NETs and RA-ILD, investigate the mechanisms underlying NETs formation, and assess the clinical prospects of our findings.

2.1 Animal welfare statement and generation of a zymosan A-induced interstitial pneumonia arthritic mouse model.

All mouse protocols were approved by the Use of Laboratory Animal Committee of Ningxia University in accordance with the guidelines of the National Institutes of Health Guide for the Care and Use of Laboratory Animals (KYLL-2024-1033). All mice were purchased from CLEA Japan Inc (Tokyo, Japan), and housed in a special pathogen-free facility with a 12/12h light/dark cycle with food and water ad libitum in the animal facility at Ningxia Medical University (Yinchuan, China). To generate an arthritic mouse model of interstitial pneumonia, 8-week-old SKG/jcl mice (n = 12) were intraperitioneally administered 7.5 mg of zymosan A (ZYM) (Alfa Aesar, Lancashire, UK) dissolved in 0.5 mL of phosphate buffered saline (PBS). The control mice (n = 12) were administered 0.5 mL of PBS. We examined body weight and paw size once a week. The arthritis score for each of the four paws was recorded, and the scoring system was as follows: 0 = normal joints; 1 = slight swelling or erythema of the ankle or midfoot; 2 = slight swelling of the ankle and foot; 3 = modest swelling and erythema; and 4 = severe swelling and erythema^[20]. The maximum score was 16 for each mouse. The mice were euthanized via carbon dioxide (CO₂) inhalation at the end of the experiment. The blood, knee joint, brain, heart, kidney, liver, spleen, colon and lung were harvested for pathological and molecular analysis at 8 and 16 weeks post-ZYM challenge.

2.2 Lung and joint histopathological analysis.

Mouse lung tissues were fixed in 4% paraformaldehyde (PFA) solution before they were either embedded in optimal cutting temperature (OCT) compound or dehydrated and processed for paraffin embedding. Five-micrometer-thick sections were prepared and stained using hematoxylin and eosin (H&E) staining, Masson’s trichrome staining, or other methods as described elsewhere^[21]. The severity of interstitial injury and fibrosis in lung tissues was assessed by evaluating inflammatory cell infiltration and using the Ashcroft scale, with scores ranging from 0 to 4 for interstitial injury and 0 to 8 for fibrosis, on the basis of histological images of the lung as previously described^[22].

Joint tissues were fixed in 10% formalin, decalcified with EDTA decalcification solution, embedded in paraffin, and cut into five-micrometer-thick slices. H&E and toluidine blue-O (TBO) staining were performed. To assess the degree of joint inflammation and joint destruction, inflammatory cell infiltration and cartilage damage were scored by two independent and blinded pathologists as previously described. Both joint inflammation and joint destruction were evaluated on a scale of 0–4, as previously described^[23].

2.3 Measuring anti-CCP, RF, histone H3, cell-free DNA and MPO-DNA concentrations.

The concentrations of anti-citrullinated protein (anti-CCP) antibody, RF, MPO-DNA, citrullinated histone H3 (Cit-H3), and cell-free DNA were measured by an enzyme-linked immunosorbent assay (ELISA) with appropriate commercially available kits, following the manufactures’ instructions. The ELISA kits for detecting mouse anti-CCP and RF were obtained from Shanghai JiangLai Biotechnology Co.,Ltd (Shanghai, China), while the kits for detecting MPO-DNA, Cit-H3 and cell-free DNA were obtained from Shanghai HengYuan Biotechnology Co.,Ltd (Shanghai, China). The protein concentration in each sample was determined by comparison with the standard curve.

2.4 Evaluations with micro-CT scanning.

At 16 weeks postinjections, the knee joints of the mice were harvested and fixed in 4% paraformaldehyde. The samples were scanned via micro- CT (µCT 40; Scanco, Zurich, Switzerland) as described previously^[24]. The scanner was set to a resolution of 10 µm with a voltage of 70 kV and an electric current of 114 µA. The region of interest (ROI) was defined to cover the entire subchondral bone in the tibial plateaus. The three-dimensional structural parameters analyzed included the bone volume (BV), bone volume/total tissue volume (BV/TV), trabecular thickness (Tb.Th), and trabecular separation (Tb.Sp).

2.5 RNA isolation and RT-PCR

Total RNA was isolated using the MiniBEST Universal RNA Extraction Kit (TaKaRa) according to the manufacturer’s instructions. Quantitative RT-PCR with SYBR Green Master Mix (TaKaRa, Dalian, China) was performed using the StepOnePlus RT-PCR System. The relative quantity of target mRNAs was calculated using the delta-delta Ct method. The primer sequences are displayed in Supplementary Table S1.

2.6 Western blotting.

Proteins were extracted from both cell lines and tissues using RIPA lysis buffer (Thermo Fisher Science, USA) under cold conditions, After centrifugation at 12000g for 10 min, the protein samples were subjected to immunoblotting. Protein concentration was determined using a BCA protein assay kit (Thermo Fisher Science, USA). Subsequently, the protein samples were loaded onto PAGE gels (Epizyme Biomedical Technology, Shanghai, China) and transferred to 0.22 µm Immobilon PVDF membranes (Millipore Sigma, USA). After blocking with 5% milk, the membranes were incubated in primary antibodies at appropriate dilutions overnight at 4℃. Next, secondary antibodies were applied at room temperature for approximately 1h, and the immunoreactivity was visualized using an ECL system (Thermo Fisher Scientific, Waltham, MA). Relative expression of target protein was measured semi-quantitatively by densometric analysis of blots. The intensity of blot area was calculated by optical densitometry using ImageJ Software version 2.0.0 (http://rsb.info.nib.gov/ij). The ration of the net intensity of each sample to that of housekeeping gene GAPDH served as an internal loading control. The values are reported as densitometric arbitrary units (A.U.). Relative target protein expression in the experimental group was divided by that in the control group to calculate the fold change in target protein abundance. Primary and secondary antibodies used for immunoblotting are listed in Supplementary Table S2.

2.7 Immunoflurescence staining.

Fixed lung tissues that were embedded in OCT compound were cryosectioned at a thickness of 8 µm for immunofluorescence (IF). Cryosections were air-dried at RT for 30 min, re-fixed in 4% PFA for 10 min, and finally permeabilized in 0.2% Triton X-100/PBS for 20 min at RT. Sections were then blocked by incubating them in 5% donkey serum in PBS for 1h before being probed with primary antibodies in dilutant buffer (1% donkey serum, 0.03% Triton X-100, and 1mM Cacl₂ in PBS) overnight at 4℃. The sections were washed and then incubated with fluorescent dye-conjugated secondary antibodies at RT for 2h. The slides were washed in PBS three times for 5min, mounted with VECTASHIELD Antifade Mounting Medium with DAPI (Vector Laboratories), imaged under a Leica TCS SP2 A0BS Confocal System, and processed using Leica Confocal Software v.2.6.1 (Leica). Primary antibodies and secondary antibodies used for IF are listed in Supplementary Table S2.

2.8 Immunohistochemistry.

Paraffin-embedded tissue specimens were sectioned, deparaffinized with xylene, and rehydrated in decreasing concentrations of ethanol followed by 3 washes with 1×PBS. Antigen retrieval was performed in boiling sodium citrate buffer (10 mmol/L sodium citrate, 0.05% Tween-20, PH 6.0) or using Proteinase-K (20 µg/mL). The sections were then blocked with 3% fetal bovine serum in 1×PBS for 30 minutes, followed by overnight incubation at 4 ℃. After 3 washes with 1×PBS, the sections were further incubated with biotin or HRP-conjugated secondary antibodies for 30min at RT. Antibody staining was then developed with DAB substrate (Zsbio, Beijing, China) for HRP-conjugated secondary antibodies or incubated with an Avidin-Biotin Complex Staining Kit (ABC Kit; Vector Laboratories, Burlingame, CA) before DAB development as per the manufacturer’s instructions. Primary antibodies and secondary antibodies used for IHC are listed in Supplementary Table S2.

2.9 Human subjects.

The study and protocol were approved by the Ethics Committee for Conducting Human Research at General Hospital of Ningxia Medical University (KYLL-2024-1033). All patient participants provided written consent for the collection and analysis of their blood samples for publication, in accordance with the protocol (KYLL-2024-1033) outlined by the Ethics Committee for the Conduct of Human Research. The investigator of this study maintains human research records, including signed and dated consent documents for 10 years. All cases who fulfilled the 2010 American Collage of Rheumatology (ACR)/ European League Against Rheumatism (EULAR) and/or 1987 ACR revised criteria were collected from the outpatient rheumatology and respiratory clinic of General Hospital of Ningxia Medical University between November 2022 to July 2024^[25]. Pulmonary involvement was evaluated in all patients by high-resolution computed tomography (HRCT). The assessments and subsequent reclassification of HRCT images according to the 2013 IIP classification^[26] were independently analyzed by two senior radiologists at the General Hospital of Ningxia Medical University, with 8 and 15 years of experience, respectively. Ultimately, 25 RA-nonspecific interstitial pneumonia (NSIP), 24 RA-usual interstitial pneumonia (UIP), 12 RA-organizing pneumonia (OP), and 12 RA-other patterns patients were qualified and included in this study (Figure S1). Clinical characteristics and laboratory data were abstracted from medical records. The demographics of individuals involved in this study are outlined in Supplementary Figure S2.

2.11 Single-cell suspension preparation.

The preparation of single-cell suspension was followed by previous protocols^[27]. Briefly, Lung lobes from the control and ZYM-treated mice were digested with collagenase-type IA and deoxyribonuclease I (Thermo Fisher Scientific Inc., Waltham, MA, USA), followed by trypsinization. The cell suspension was then filtered using a 40 µm cell strainer, washed, centrifuged, and finally resuspended in magnetic-activated cell sorting buffer (Miltenyi Biotec, Bergisch Gladbach, North Rhine-Westphalia, Germany) for single-cell RNA sequencing (ScRNA-Seq) analysis.

2.12 Construction of single-cell libraries and sequencing.

In brief, single-cell suspensions and beads were mixed with each other by adjusting co-encapsulation occupancy to 0.05. After individual droplets were collected, messenger RNA was reverse transcribed into complementary DNA, followed by cDNA amplification. Finally, a 3’gene expression library was prepared using the Chromium Next GEM Single Cell 3’Kit v3.1 (10× Genomics, Pleas-anton, CA, USA). Sequencing was conducted by using a NovaSeq 6,000 (Illumina, San Diego, CA, USA) by OE Biotech Co., Ltd. (Shanghai, China).

2.13 ScRNA-seq data quality control analysis.

Raw sequencing reads of mouse lung tissues were aligned to the mouse genome reference (GENCODE, mm10) and processed into a single-cell matrix via Cell Ranger (version 7.0.0) with the default parameters. Considering the presence of double droplets, empty droplets, dead cells, low-quality cells with the nFeature_RNA > 4000, percent.mt > 10 and nFeature_RNA < 1000 were excluded. A total of 37,735 cells were finally identified after filtration in the dataset. Subsequently, the data was normalized, the dimensionality was reduced, and cell clustering was performed using Seurat (v.4.1.1)^[28]. Additionally, the clusters with relatively low gene numbers and absence of specific marker genes were also removed.

2.14 Integration and cell type annotation.

To integrate each sample and correct for batch effects, the top 2000 highly variable genes (HVGs) were identified using the Seurat function FindVariableGenes (mean.function = FastExpMean, dispersion.function = FastLogVMR). To remove the batch effects from the ScRNA-Seq data, the mutual nearest neighbors (MNN) method presented by Haghverdi et al., was performed with the R package batchelor (version 1.6.3)^[29]. Graph-based clustering was performed to cluster cells according to their gene expression profile with the FindClusters function. Cells were visualized using a 2-dimensional uniform manifold approximation and projection (UMAP) algorithm with the RunUMAP function. Finally, the FindAllMarkers function (test.use = presto) was used to identify marker genes of each cluster.

2.15 Differentially expressed genes analysis.

Differentially expressed genes (DEGs) were selected using the function FindMarkers (test.use = presto). A P value < 0.05 and |log2fold change|>0.58 were set as the threshold for significantly differential expression.

2.16 Gene ontology enrichment analysis.

Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of differentially expressed genes (DEGs) were conducted using R using R (version 4.0.3), utilizing the hypergeometric distribution as the statistical method.

2.17 Microarray data and identification of hub genes.

The transcription profile dataset of lung tissues in RA-UIP, IPF-UIP and non-UIP control groups (GSE199152) was obtained from NCBI GEO database (http://www.ncbi.nlm.nih.gov/geo/). The platform is GPL16791, which included 27 subjects, of which 3 were RA-UIP patients, 20 were IPF patients, and 4 were non-UIP controls. DEGs were identified by comparing the expression values in lung tissues between RA-UIP and non-UIP control using the limma R package (http://www.bioconductor.org/packages/release/bioc/html/limma.html) in Bioconductor. The screening criteria set as adjusted P < 0.05 and FC > 1.

2.18 Cell culture and siRNA transfection.

The human promyelocytic (HL-60) and fetal lung (MRC-5) cell lines were purchased from Pricella Bioscience Inc, (Wuhan, China) and cultured in Iscoves’s Modified Dulbecco’s Medium (IMDM) (Gibco, USA) supplemented with 20% fetal bovine serum (FBS) (Gibco, USA) and 1% antibiotic-antimycotic solution at 37℃, 5% CO2. Transfection of HL-60 cells with either si-Control or si-Nr4a3 (Sangon, Shanghai, China) was performed using Lipofectamine 3000 regent (L3000015, Invitrogen) according to the instruction manual.

2.19 Statistics.

Except for the scRNA-seq data, experimental data were analyzed using two-tailed unpaired Student’s t-tests, one-way or two-way ANOVA by GraphPad Prism software (version 9.5, GraphPad Software, Inc., San Diego, CA) and “ggplot2”, “ggtext”, stats” and “car” packages in R (version 4.2.1). Data are expressed as mean ± standard errors, and differences were considered statistically significant when P < 0.05. All experiments, except for the scRNA-seq, were performed independently at least three times.

3.1 Establishing joint swelling and interstitial pneumonia in SKG mice

To investigate the development of lung disease in the setting of arthritis, we induced chronic arthritis and interstitial pneumonia in SKG mice under SPF conditions at 8 and 16 weeks of age using the intraperitoneal administration of ZYM (Fig. 1a). Mice challenged with ZYM had significantly poor performance of growth compared with mice receiving PBS (P < 0.0001) (Fig. 1b). Arthritis score in ZYM-treated mice was markedly higher than that in PBS controls (P < 0.0001) (Fig. 1c). Diagnostic indicators, including circulating anti-CCP antibody (Figure. 1d) and RF (Fig. 1e), were significantly elevated in ZYM-treated mice at 8 and 16 weeks post challenge compared to controls (P < 0.0001 and P < 0.0001, respectively). Additionally, the mortality rate of PBS-treated mice was 100% during the observation period of 16 weeks, while only 50% of the ZYM-treated mice survived to the end of study (P = 0.0275) (Fig. 1f). Histological observations revealed prominent inflammatory cell infiltration in the knee joints, colon and spleen of mice after ZYM challenge 8 weeks (Figs. 1g and S3). Of note, SKG mice administered ZYM 16 weeks revealed systemic manifestations characteristic of human RA, such as joint swelling and deformity, colonic inflammation, splenomegaly, inflammatory liver and interstitial pneumonitis (Figs. 1g and S3). Furthermore, TBO analysis revealed distinct articular cartilage destruction, while Masson staining demonstrated a significant expression of blue collagen fibers around the vascular wall and in the thickened alveolar interstitium following 16 weeks of ZYM treatment (Fig. 1g). Consistently, histopathological analysis showed a significant increase in the inflammatory score of knee joints in ZYM-treated mice at week 8 (2.6 ± 0.54) compared with that in PBS-treated controls (0.2 ± 0.44) (P < 0.0001) (Fig. 1h). At week 16 post-ZYM challenge, mice exhibited an elevated inflammatory score (3.6 ± 0.54) and articular cartilage score (3.4 ± 0.54) in knee joint, as well as an increased inflammatory score (3.0 ± 0.71) and fibrotic score (2.4 ± 0.55) in lung, compared with those of controls (P < 0.0001, P < 0.0001, P < 0.0001 and P < 0.0001) (Fig. 1g). Micro-CT scanning revealed that ZYM induced significant bone resorption, as shown by the increased osteolysis in subchondral bone of tibia (Fig. 1I). Statistically, the BV of subchondral bone in tibial plateau was 1.49 ± 0.04 mm³ in the ZYM group, which was significantly lower than the 1.88 ± 0.08 mm³ observed in the PBS control group (P = 0.0021) (Fig. 1j). Other parameters, including BV/TV, Tb.N, and Tb.Sp, also indicated bone destruction in the ZYM group (Fig. 1k-1m). Furthermore, by IF citrullinated peptides increased in lungs of mice at week 16 post-ZYM challenge (Fig. 1n and 1o). Immunoblotting further revealed an increased abundance of TGF-β1 and the profibrogenic factor alpha smooth muscle actin (α-SMA) in lungs of mice at week 16 post-ZYM challenge compared to controls (Fig. 1p and 1q). These results confirmed that SKG mice administered ZYM for16 weeks developed robust ILD in our SPF mouse facility.

3.2 Single-cell transcriptomic profiling increased neutrophils in SKG mice with joint swelling and interstitial pneumonia

To obtain a high-resolution map of the mouse lung under both normal and pathological conditions, we employed the single-cell RNA sequencing (scRNA-seq). Lung tissues of SKG mice were obtained 16 weeks after ZYM or PBS, rapidly digested into a single-cell suspension, and analyzed using a single-tube protocal with unique transcript counting through barcoding with unique molecular identifiers (UMIs) using 10×Genomics Chromium platform (Fig. 2a). After quality filtering, a total of 37,735 cells were analyzed for transcriptional profiling, with an average of 5,789 genes per cell. Among these, 17,770 cells from SKG PBS-treated mice and 19,965 cells from SKG ZYM-treated mice were profiled and visualized using the uniform manifold approximation and projection (UMAP) algorithm, categorized by cell type according to a previous report^[30]. We identified 11 major cell types within the lung, including B lymphocytes (B cells), dendritic cells, endothelium cells, epithelial cells, fibroblasts, macrophages, monocytes, neutrophil, natural killer (NK) cells, pericytes, plasma cells, smooth muscle cells, and T lymphocytes (T cells) (Fig. 2b). Detailed marker genes in each cell type were also listed (Fig. 2c). Moreover, the highest DEGs in each cluster between ZYM and PBS-treated mice were calculated to manually annotate clusters with their respective cellular identities (Fig. 2d). Finally, we analyzed and compared relative cell numbers in PBS- and ZYM-treated lung samples. As shown in Figure. 2e, ZYM treatment dramatically increased the number of neutrophils while reducing the numbers of B cells and pericytes. Based on the expression of cell-type-specific top genes, GO enrichment analysis was conducted to reveal their physiological functions. Notably, neutrophils were significantly enriched in netrophil aggregation (GO BP) and neutrophil activation involved immune response (GO GSVA) (Fig. 2f). Collectively, these data demonstrated an augmented population of neutrophils within lung tissue in ZYM-induced interstitial pneumonia arthritic mouse model.

3.3 Increased neutrophil extracellular traps in SKG mice with joint swelling and interstitial pneumonia

The above data suggest that ZYM-induced neutrophils were primarily involved in functions related to NETs. We next collected bronchoalveolar lavage fluid (BALF), blood, and lung tissue 16 weeks after ZYM exposure to assess the levels of neutrophil count and NETs (Fig. 3a). As shown in Figs. 3B-D, ZYM induced significant neutrophil infiltration in BALF (P < 0.0001) (Figs. 3b and 3c), along with a marked increase in the abundance of the neutrophil marker Ly6g in lung tissue (P < 0.0001) (Fig. 3d). ELISA analysis revealed elevated levels of MPO-DNA, a component of NETs, in both serum (Fig. 3e) and BALF (Fig. 3f) 16 weeks after the ZYM challenge compared with those after PBS treatment (P = 0.0281 and P = 0.0095, respectively). Interestingly, no statistical difference was found in the lung MPO-DNA concentration between ZYM-treated SKG mice and PBS-treated SKG mice (Fig. 3g). Molecular analysis of NETs components with immunohistochemistry and immunoblotting assay showed increased protein levels of Cit-H3 and PADI4 (Fig. 3h-j), as well as increased transcript levels of padi4 in the lungs of ZYM-treated mice at 16 weeks compared to the PBS group (Fig. 3k). These data suggest that NETs might contribute to the development of interstitial pneumonia during the progression of joint swelling in SKG mice.

3.4 NR4A3 inhibits neutrophil extracellular trap secretion induced by PMA

RA-UIP is one of the most common forms of ILD with a worse prognosis^[28]. We analyzed data from the NCBI GEO profile (GSE199152) to identify DEGs in lung tissues from RA-UIP patients compared to non-UIP controls. A total of 300 DEGs were identified, consisting of 98 up-regulated genes and 202 down-regulated genes (Fig. 4a). The seven co-DEGs were identified in neutrophil by comparing DEGs from our ScRNA-seq analysis with those identified via bulk RNA-seq analysis of lung tissue. These co-DEGs included immunoglobulin heavy constant mu (IGHM), fos proto-oncogene (FOS), alpha arrestin domain containing 2 (ARRDC2), SMAD family member 6 (SMAD6), FOXF1 adjacent noncoding developmental regulatory RNA (FENDRR), nuclear receptor subfamily 4 group A member 3 (NR4A3) and complement C3 (C3) (Fig. 4b). GO analysis suggested that the seven co-DEGs were mainly involved in cellular response to reactive oxygen species and response to oxidative stress (Fig. 4c), indicating their potential role in NETs formation. IF further revealed an increased numbers of NR4A3 and LY6G double-positive neutrophils in blood vessels, but not in the bronchi, alveolar space and septum (Fig. 4d and 4e). To investigate the role of NR4A3 in NETs formation, we inhibited Nr4a3 expression by siRNA (si-Nr4a3) in HL-60 cells. The first Nr4a3 siRNA demonstrated significant efficiency in silencing endogenous NR4A3 protein in HL-60, and therefore, was used in study (Figure S4). Inhibition of Nr4a3 led to an increased number of Hoechst and SYTOX Green double-positive cells after 2h of PMA stimulation (Fig. 4f and 4g). IF staining further indicated that Nr4a3 knockdown enhanced PADI4 expression (Fig. 4h and 4i). Collectively, these data suggest that NR4A3 inhibits the formation of NETs.

3.5 NETs from Nr4a3-depleted HL-60 cells induced by PMA could induced MRC-5 cells into myofibroblasts.

Activated fibroblasts play a central role in the progression of pulmonary fibrosis^[31]. Therefore, we further investigated the potential impact of NETs on the differentiation of MRC-5. Supernatants were collected from HL-60 cells transfected with Scr siRNA or Nr4a3 siRNA in the presence or absence of PMA. Subsequently, these supernatants were mixed with MRC-5 cell culture medium at a 1:1 ratio. We then assessed the myofibroblasts markers fibronectin (FN) and collagen1 (COL1A1) in MRC-5 cells after 48h of exposure to the mixed supernatants (Fig. 5a). IF staining showed that supernatants from PMA-treated HL-60 cells transfected with Nr4a3 siRNA induced MRC-5 cells into myofibroblasts, as indicted by increased abundance of FN and COL1A1, compared to the supernatants from HL-60 cells treated with PMA alone (Fig. 5b). Collagen gel contraction assay further corroborated an increased collagen gel contraction in supernatant from HL-60 treated with PMA and transfected with Nr4a3 siRNA, compared to those treated with PMA alone (P < 0.0001) (Fig. 5c-d). These data suggest that NR4A3-mediated NETs secretion suppresses the transformation of MRC-5 cells into myofibroblasts.

3.6 Increased circulation MPO-DNA in RA-NSIP patients and Cit-H3 in RA-UIP patients

Unlike what is seen in SKG mice with joint swelling and interstitial pneumonia, there was no statistical difference found in plasma neutrophil counts between RA-ILD patients with different imaging features and healthy individuals (Figure S4). In order to determine whether NETs was correlated with RA-ILD activity, plasma concentrations of MPO-DNA, Cit-H3, and cell-free DNA were evaluated in RA-ILD patients with different imaging features and healthy subjects. A significantly more abundant plasma MPO-DNA was determined in RA-ILD patients compared to healthy cohorts (P < 0.00001) (Fig. 6a). More importantly, a strikingly higher level of plasma MPO-DNA was found in RA-NSIP patients relative to healthy cohorts (P < 0.00001) (Fig. 6b). Similar to plasma MPO-DNA, there was statistical difference found in plasma Cit-H3 and cell-free DNA between healthy individuals and RA-ILD patients (P = 0.0147 and P < 0.0001) (Figs. 6c and 6e), but unlike what is seen in RA-NSIP, moderately more abundance of plasma Cit-H3 and cell-free DNA were determined in RA-UIP patients in comparison with healthy subjects (P = 0.0007 and P < 0.00001) (Figs. 6d and 6f). Next, we analyzed the correlations of RA-ILD serological risk features-RF and anti-CCP-with MPO-DNA, Cit-H3 and cell-free DNA in both positive and negative groups. RF was positively correlated with anti-CCP in MPO-DNA-positive RA-NSIP group (R = 0.952, P = 0.001), whereas RF was negatively correlated with anti-CCP in MPO-DNA-negative RA-NSIP group (R=-0.587, P = 0.013) (Fig. 6g). Additionally, a strong positive correlation between RF and anti-CCP was observed in the Cit-H3-positive RA-UIP group (R = 0.770, P = 0.014), while a strong negative correlation was found in the Cit-H3-negative RA-UIP group (R=-0.754, P = 0.002) ( Fig. 6h). Unexpectedly, no significant association between RF and anti-CCP was observed in RA-UIP patients based on cell-free DNA status (R = 0.468, P = 0.081 and R = 0.127, P = 0.733) (Fig. 6i). To evaluate the clinical significance of the MPO-DNA and Cit-H3, we analyzed the sensitivity and specificity of these circulating factors in identifying RA-ILD patients with UIP and NSIP. Of note, the area under the curve (AUC) was 0.850 (range: 0.730–0.970) with an incorporation of circulating MPO-DNA into RF and CCP for RA-NSIP diagnosis (Fig. 6j). Equally noteworthy, the including of circulating Cit-H3 in the combination of RF and CCP showed AUC of 0.887 for RA-UIP diagnosis(range: 0.780–0.993) (Fig. 6k). The above results support a link between circulation MPO-DNA and RA-NSIP activity, as well as Cit-H3 and RA-UIP activity.

The developmental mechanisms of RA-ILD remain unclear, in part due to the lack of appropriate animal models^[32]. Conventional models, such as collagen-induced arthritis (CIA), effectively induce inflammatory arthritis but fail to adequately represent the pulmonary fibrosis that can develop as a complication of RA^[32]. This limitation highlights the need for more suitable experimental models to better investigate the pathogenesis of RA-ILD. In this study, we used SKG mice to establish a model of chronic progressive joint disorder, which was accompanied by the development of cellular and fibrotic interstitial pneumonia. Consistent with previous reports, although SKG mice exhibit increased collagen deposition, they do not develop a fibrotic UIP phenotype, even 16 weeks post-ZYM injection. Both the lung pathology observed in SKG mice and human NSIP are characterized by inflammatory cells infiltration and varying amounts of collagen in areas of cell accumulation, suggesting that the pattern of lung disease in SKG mice mirrors the fibrotic NSIP pathology seen in human RA-ILD^[33–35]. Serological features in patients with RA-ILD, such as RF and anti-CCP antibody^[36], were also elevated in SKG mice administered ZYM. Moreover, increased levels of anti-CCP antibody targeting pan-citrullinated proteins, along with key markers of fibrotic lung disease of TGF-β and α-SMA, were found in lung tissues of ZYM-injected SKG mice. Although few studies have explored TGF-β in human NSIP and fibrotic NSIP, its presence in lung tissue has been documented^[37]. Herein, we demonstrated that arthritis SKG mice develop a persistent, restrictive mixed cellular and fibrotic interstitial pneumonia that closely resembles RA-ILD, in line with previous reports^{[20, 32, 34]}.

Although the mechanism underlying aberrant regulation of inflammatory cascades and tissue remodeling in various forms of RA-ILD remain obscure, existing data suggest neutrophils contribute to a complex interplay between inflammation and fibrosis^[38]. Previous studies have shown that increased blood neutrophil counts were associated with poor outcomes in patients with RA-ILD^[6]. In addition, increased neutrophil counts in BALF correlated with poor patient outcomes with IPF^[39]. These findings differ from our results that showed no difference in the number of neutrophils from blood between RA-ILD patients and HC controls. This discrepancy may be partly attributed to the small sample size and the potential effects of certain therapeutic drugs. Notably, our study demonstrated a significant increase in neutrophil counts in lung tissue and BALF of SKG mice after ZYM stimulation. GO enrichment analysis further revealed that neutrophils mainly involved in neutrophil aggregation and neutrophil activation involved immune response. The two processes are crucial for the formation of NETs, as they involve the aggregation and activation of neutrophils, which are prerequisites for the formation of NETs^[40]. It is true that serum and BALF levels of MPO-DNA, lung levels of PADI4 and Cit-H3 protein, as well as mRNA level of padi4 in lung were significantly elevated in SKG mice after ZYM exposure. However, no significant difference was observed in lung MPO-DNA level of SKG mice exposure to ZYM. This may be attributed to the interaction between MPO and DNA within neutrophils during the process of NETs formation, which ultimately leads to the extracellular release of the MPO-DNA complex^[41].

The formation of NETs is a complex process involving multiple molecular mechanisms and signaling pathways, such as pathogens, reactive oxygen species, activation of specific receptors, heavy metals, pesticides, inflammatory factors and autoimmune responses^{[15, 42]}. In conditional Nr4a1 and Nr4a3 knockout mice, codepletion of Nr4a1 and Nr4a3 promotes acute changes in hematopoietic stem cell (HSC) homeostasis, including the loss of HSC quiescence, accumulation of oxidative stress, and DNA damage, while maintaining the regenerative and differentiation capacity of stem cells^[43]. Sadhan Das et al. showed that the knockdown of growth factor-and pro-inflammatory cytokine-induced vascular cell-expressed RNA (Giver) reduced the expression of genes involved in oxidative stress (Nox1) and inflammation (IL-6, Ccl2, Tnf) but increased Nr4a3 expression^[44]. Our present results showed that Nr4a3 inhibition led to an increased expression of NETs. This observation is in agreement with recent study proposing a role for NR4A3 in diabetes induced atrial cardiomyopathy by maintaining mitochondrial energy metabolism and reducing oxidative stress. Previous studies have demonstrated NETs may regulate the fibrotic process by causing pro-inflammtory effects, injuring pulmonary epithelium and endothelium, promoting pulmonary epithelial-mesenchymal transition (EMT), activating lung fibroblasts, or inducing autophagy^[45]. Interleukin (IL)-17 was expressed in NETs and promoted the fibrotic activity of differentiated fibroblasts^[46]. In line with an increased NR4A3 in HL-60 cells inhibited NETs secretion to suppress the transformation of MRC-5 into myofibroblasts.

To our knowledge, this is the first report concening enhanced NETs formation in RA-ILD. In this study, it was especially noteworhty that more abundant plasma MPO-DNA and Cit-H3 were found in RA-NSIP and RA-UIP patients than HC, respectively. Equally noteworthy, the ROC curves further revealed that the presence of RF, anti-CCP antibody, and MPO-DNA were helpful for the diagnosis of NSIP in RA-ILD patients, while the presence of RF, anti-CCP antibody, and Cit-H3 were useful for diagnosing UIP in RA-ILD patients. Most studies report NSIP and UIP as being the most common patterns, coexistence of UIP and NSIP is common in RA-ILD^[47]. RF and anti-CCP antibody are not only critical biomarkers for the diagnosis of RA^[48], but their elevated levels are also closely associated with the risk of developing RA-ILD, making them signifiant risk factors for RA-ILD patients^{[36, 49, 50]}. Therefore, we will further expand our sample size and combine the detection of MPO-DNA, Cit-H3, RF, and anti-CCP antibody differential diagnosis of clinical RA-NSIP and RA-UIP patients, which may provide assistance for personalized treatment in clinical settings.

There were several limitations in the current study. First, this study was conducted with a small sample size at a single centre and the lack of follow-up data. Future studies with larger patient cohort and long-term follow-up with RA-ILD indexes are needed. Second, although plasma MPO-DNA and Cit-H3 were elevated in patients diagnosed with RA-NSIP and RA-UIP, the lack of RA-ILD lung biopsy and BALF, limited us to assess the correlation NETs and the local pathological changed within the lungs. Third, underlying molecular mechanisms remain largely unknown regarding how NR4A3 lead to a sreduction in the formation of NETs. According to literature reports on NR4A3, we hypothesize that NR4A3 may indirectly inhibit the formation of NETs by downregulating the activity of NOX2 and further reducing the generation of ROS.

Collectively, despite these potential shortcomings, we clearly demonstrate that the pathological phenotypes of ZYM-treated SKG mice closely resemble those of RA-ILD. Moreover, the expression of NR4A3, which mediates the formation of NETs and regulates the transformation of fibroblasts into myofibroblasts, plays a significant role in the process of ILD in RA. Additionally, incorporating MPO-DNA with RF and anti-CCP, and Cit-H3 with RF and anti-CCP, proved to be better diagnostic panels for identifying NSIP and UIP in RA-ILD, respectively. Pharmacotherapeutic targeting of NETs or the use of NR4A3 antagonists might be promising therapeutic approaches for attenuating RA-ILD, particularly in individuals with NSIP and UIP patterns.

ACPA: anticitrullinate protein antibodies; ACR: American College of Rheumatology; ARRDC2: arrestin domain containing 2; AUC: area under the curve; Cit-H3: citrullinated histon3; C3: complement C3; FC: fold change; FOS: fos proto-oncogene; HRCT: high-resolution computed tomography; ILD: interstitial lung disease; IPF: idiopathic pulmonary fibrosis; MPO: myeloperoxidase; NE: neutrophil elastase; NETs: neutrophil extracellular traps; NR4A3: nuclear receptor subfamily 4 group A member 3; NSIP: nonspecific interstitial pneumonia; PADI4: protein arginine deiminase; PFTs: pulmonary function tests; RA: rheumatoid arthritis; RF: rheumatoid factor; ROC: receiver operating characteristic; ROS: reactive oxygen species; SMAD6: SMAD family member 6.

Ethics approval and consent to participate

All procedures were approved by the Ethic Committee for the Conduct of Human Research at General Hospital of Ningxia Medical University (KYLL-2024-1033)). Informed consent was obtained from all patients for their data to be used for research.

Consent for publication

Written informed consent was obtained from all participants involved in this study for the use and publication of their clinical data, including blood samples, blood test results, and basic clinical information. The participants were informed about the nature of the study and the potential for their anonymized data to be published in an academic journal. We have taken all necessary precautions to ensure that no identifying information, such as names or personal identifiers, is included in the manuscript, thereby preserving the anonymity of the participants.

Availability of data and materials

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Competing of Interests

The authors declare that they have no competing interests.

Funding

This study was supported by grants from the Research Project of the Department of Education of the Autonomous Region for Higher Education Institution (NYG2024161), the Nature Science Foundation of China (82460020), and the Autonomous Region Key Research and Development Plan (2023BEG03014).

Authors’contributions

J. X., and M. N. collected clinical data, Z. Z. and L. Y. performed the serological analysis. H. Z. and J. Y. collected plasma samples. J. X., analyzed data and drafted the manuscript. J. C., the designed experiments and revised the manuscript. S. C.analyzed data and interpreted data.

Acknowledgements

We would like to express our sincere gratitude to Department of Key Laboratory of Ningxia Stem Cell and Regenerative Medicine, Institute of Medical Sciences, General Hospital of Ningxia Medical University, for their invaluable support and contributes to this study.

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No competing interests reported.

FigureS1.tif
Figure S1. Patients were enrolled in this study. A flow diagram of the enrollment of participants categorized by HRCT patterns and clinical diagnostic data in this study. HRCT: high-resolution computed tomography; ILD: interstitial lung disease; RA: rheumatoid arthritis; UIP: usual interstitial pneumonia; NSIP: nonspecific interstitial pneumonia; OP: organizing pneumonia.
FigureS2.tif
Figure S2. Baseline demographic and clinical features of RA-ILD patients. A binary representation is used where “1” indicates the presence of specific demographic or clinical information for a sample, and “0” denotes the absence of such information. RA-ILD: rheumatoid arthritis-associated interstitial lung disease.
FigureS3.tif
Figure S3. Representative images of tissues from various organs. H&E-stained sections of the brain, heart, liver, spleen, kidney, and colon at 8w and 16w after ZYM stimulation. Scale bars in the the first, third, fifth, and seventh panel, 1mm; scale bars in the second, fourth, sixth, and eighth panel, 50um. ZYM: zymosan A.
FigureS4.tif
Figure S4. Effect of Nr4a3 shRNA on mRNA expression in HL-60 cells. Transfection of human promyelocytic leukemia (HL-60) cells with Nr4a3 shRNA resulted in a significant downregulation of Nr4a3 mRNA expression compared with that in cells transfected with control shRNA (n=3).
Gelsandbots.docx
SupplementaryTables.docx
FigureS5.tif
Figure S5. Plasma neutrophil counts in different cohorts. The number of plasma neutrophils in healthy cohorts (n=41), RA-UIP patients (n=25), RA-NSIP patients (n=24), RA-OP patients (n=12) and RA-ILD patients with other patterns (n=12). ns: not significant; RA: rheumatoid arthritis; UIP: usual interstitial pneumonia; NSIP: nonspecific interstitial pneumonia; OP=organizing pneumonia.

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Neutrophil extracellular traps are involved in the occurrence of rheumatoid arthritis-associated interstitial lung disease

Status:

Version 1

Abstract

Background

Methods

Results

Conclusions

Figures

1. Introduction

2. Materials and methods

2.1 Animal welfare statement and generation of a zymosan A-induced interstitial pneumonia arthritic mouse model.

2.2 Lung and joint histopathological analysis.

2.3 Measuring anti-CCP, RF, histone H3, cell-free DNA and MPO-DNA concentrations.

2.4 Evaluations with micro-CT scanning.

2.5 RNA isolation and RT-PCR

2.6 Western blotting.

2.7 Immunoflurescence staining.

2.8 Immunohistochemistry.

2.9 Human subjects.

2.11 Single-cell suspension preparation.

2.12 Construction of single-cell libraries and sequencing.

2.13 ScRNA-seq data quality control analysis.

2.14 Integration and cell type annotation.

2.15 Differentially expressed genes analysis.

2.16 Gene ontology enrichment analysis.

2.17 Microarray data and identification of hub genes.

2.18 Cell culture and siRNA transfection.

2.19 Statistics.

3. Results

3.1 Establishing joint swelling and interstitial pneumonia in SKG mice

3.2 Single-cell transcriptomic profiling increased neutrophils in SKG mice with joint swelling and interstitial pneumonia

3.3 Increased neutrophil extracellular traps in SKG mice with joint swelling and interstitial pneumonia

3.4 NR4A3 inhibits neutrophil extracellular trap secretion induced by PMA

3.5 NETs from Nr4a3-depleted HL-60 cells induced by PMA could induced MRC-5 cells into myofibroblasts.

3.6 Increased circulation MPO-DNA in RA-NSIP patients and Cit-H3 in RA-UIP patients

4. Discussion

5. Conclusions

Abbreviations

Declarations

References

Additional Declarations

Supplementary Files

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