The CCL2-driven monocyte-macrophage axis in progressive fibrosing hypersensitivity pneumonitis

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Santos, Catarina Gouveia Cardoso, Ana Pinto, Luciana Oliveira, and 22 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6908974/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 11 Apr, 2026 Read the published version in Respiratory Research → Version 1 posted 23 You are reading this latest preprint version Abstract Background Hypersensitivity pneumonitis is characterized by immune dysregulation that often leads to irreversible lung tissue scarring. While elevated monocytes play a key role in idiopathic pulmonary fibrosis, their contribution in progressive fibrotic hypersensitivity pneumonitis, along with the role of the CCL2 chemoattractant, requires clarification. Methods Immune characterization of circulating and lung markers of 71 patients with fibrotic hypersensitivity pneumonitis followed longitudinally over median 35.8 months (57.7% progressed, 31% exacerbated), comparing with controls, non-fibrotic cases and idiopathic pulmonary fibrosis. Results Elevated serum CCL2 strongly associated with disease progression and acute exacerbations, with baseline levels above 1080.69 pg/mL predicting progression and shorter survival. Despite significant variability in CCL2 levels over time, their elevation near progression was consistent, suggesting a role for this chemokine in the fibrotic cascade. Moreover, classical monocytes from patients with progressive disease displayed higher CCR2 expression, and peripheral blood mononuclear cells from these patients showed enhanced CCL2-driven chemotaxis. Bronchoalveolar lavage immunophenotyping identified enriched CCR2 + monocyte-derived precursors in fibrotic hypersensitivity pneumonitis, implicating this cellular population in disease severity. Genetic analysis of CCL2/CCR2 revealed no association between their expression and known polymorphisms. Mechanistically, elevated CCL2 may drive disease progression by recruiting CCR2 + monocytes, contributing to the profibrotic microenvironment. Conclusions These findings underscore the CCL2/CCR2 axis as a promising biomarker pathway for disease monitoring in fibrotic hypersensitivity pneumonitis, which could guide therapeutic interventions and stratification of high-risk patients. CC-chemokine ligand 2 (CCL2) / monocyte chemoattractant protein-1 (MCP-1) hypersensitivity pneumonitis monocytes macrophages pulmonary fibrosis Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 INTRODUCTION Hypersensitivity pneumonitis (HP) is a complex immune-mediated interstitial lung disease (ILD) triggered by repeated inhalation of environmental antigens in genetically susceptible individuals [ 1 – 3 ]. While non-fibrotic HP is often reversible with antigen avoidance, the fibrotic form is characterized by irreversible lung damage and fibrosis [ 1 , 4 ], with striking similarities to idiopathic pulmonary fibrosis (IPF), the archetypal progressive fibrosing ILD. In fact, fibrotic HP was reported to have comparable rate of forced vital capacity (FVC) decline and survival as IPF [ 5 – 7 ], and episodes of acute exacerbations also occur, which are linked with poor prognosis [ 8 ]. Antifibrotic therapy has shown to slow lung function decline in identical magnitude in IPF and progressive fibrotic HP [ 6 , 9 ]. Conversely, despite limited supporting evidence, immunosuppressive drugs are often the frontline approach in fibrotic HP, providing 12-months response or stabilization in less than half of the patients [ 10 ] and high rates of early treatment discontinuation due to either toxicity or inefficacy [ 11 ]. The identification of HP patients who are likely to experience progressive fibrosis remains difficult, as reliable biomarkers for disease progression are lacking. While certain clinical features, such as the presence of usual interstitial pneumonia (UIP) patterns on high-resolution computed tomography (HRCT), and absent bronchoalveolar lavage fluid (BALF) lymphocytosis, have been associated with worse outcomes in fibrotic HP [ 10 , 12 ], these markers are not sufficient to fully predict which patients will worsen under immunosuppressive treatment. Emerging evidence highlights the pivotal role of monocyte/macrophage dynamics in fibrotic ILDs, with CC-chemokine ligand 2 (CCL2) identified as a key driver of monocyte recruitment and macrophage activation in IPF [ 13 – 15 ]. However, the contribution of this axis to fibrotic HP remains largely unexplored. In this study, we sought to explore potential pathways linked with progressive fibrosing HP, aiming to improve early identification of patients who have higher risk of progression and could eventually benefit from timely intervention with antifibrotic therapies. We envisage that advancing our understanding of the pathophysiology of fibrotic HP progression will support the development of precision medicine in this field. METHODS Study design, cohorts and biological sampling FIBRALUNG (Fibrosing ILD Biomarkers That Rule Acceleration, https://fibralung.pt) is a longitudinal observational cohort study that follows patients with ILDs across six hospitals in Northern Portugal (NCT05635032, registration date 2023-10-27) [16] We prospectively included 58 adult participants with fibrotic HP who were treatment-naïve for disease-modifying drugs at enrolment (FL cohort), and followed them for at least 24 months, or until death or lung transplant (figure 1). To capture the extreme phenotype of disease progression, we further enriched this cohort with 13 patients experiencing acute exacerbations. Healthy controls were also included for comparative analysis in cytokines/chemokines measurements (n=32), genetic studies (n=91), and migration assay (n=3). Additionally, a comparative study of BALF flow cytometry was performed in 7 newly diagnosed fibrotic HP patients, 6 non-fibrotic HP and 5 IPF cases, and 3 no-ILD controls. Further details regarding controls and comparative groups are provided in the Supplementary materials (supplementary figure S1). All diagnoses were established in a multidisciplinary team meeting at the coordinating centre [1,4]. Progression was assessed at every appointed hospital visit with HRCT scan or lung function testing according to the recent progressive pulmonary fibrosis diagnostic guidelines [17]. Time to progression was determined from the first medical appointment till ≥2 of the defined progression criteria was met. Acute exacerbation or mortality due to respiratory causes were also considered as a progressive event. Responsiveness to therapy was defined as an increase of at least 5% in FVC or 10% in diffusing lung capacity for carbon monoxide (DLCO), accompanied by improved symptoms or HRCT findings. Stable disease was considered when neither progression nor responsiveness was observed. Biological samples were collected every six months from fibrotic HP patients in the FL cohort for a minimum of 24 months. In the progressors group, the time point closest to disease progression was identified as the “near-progression” sample. Cytokines/chemokines measurement and analysis Peripheral blood was collected into a BD Vacutainer® SST™ II Advance tubes and centrifuged to separate serum. BALF was collected at baseline according to previous described methodology [18]. Serum and BALF aliquots were analyzed using the LEGENDplex™ Human Inflammatory panel 1 (13-plex) (BioLegend). Data were acquired in a FACS CANTO 2 flow cytometer and analyzed using FlowJo™ v10.10 software (BD Biosciences). DNA extraction and single nucleotide peptide (SNP) genotyping Genomic DNA was extracted from peripheral ethylenediaminetetraacetic acid (EDTA)-anticoagulated blood using QIAamp® DNA Blood Kit (Qiagen). SNPs genotyping in CCL2 and its receptor, CCR2 , were performed by Axiom TM Human Genotyping SARS-COV-2 Array (Thermo Fisher Scientific), which includes >800,000 SNPs. Peripheral blood mononuclear cells (PBMCs) isolation and migration assay Peripheral blood samples were collected in EDTA-treated tubes (BD Vacutainer), and the PBMC fraction was isolated using Lympholyte-H density gradient (CEDARLANE). Migration assays were performed in 24-well plates with 5-μm pore-sized chamber inserts (Costar, Corning, Inc.). A total of 7.5 × 10 5 cells per well were seeded in the transwell upper chamber. Medium supplemented with 10% FBS, with or without 10 and 100 ng/mL human recombinant CCL2 (Peprotech), were added to the lower chamber. Cells were incubated at 37 °C with 5% CO 2 for 3 hours, after which cells in the lower compartment were collected, and those adhering to the lower side of the membrane were scraped. The percentage of migrating cells was assessed by the ratio between the number of cells recovered from the lower compartment and the number of cells seeded in the control well. Flow cytometry Immune cell composition and CCR2 levels of expression were assessed by flow cytometry in BALF and whole blood. Red blood cell lysis in peripheral blood samples was performed with RBC lysis buffer from BioLegend. ViaDye™ Red Fixable Viability Dye (Cytek) was used to assess live cells. Additional details are provided in the Supplementary materials. Data was acquired in the spectral cell analyzer Aurora (Cytek) and analyzed using FlowJo™ v10.10 software (BD Biosciences). Statistical analysis An estimative of the annual variation of FVC and/or DLCO was objectively assessed by calculating the slope-intercept equation from at least three pulmonary function tests performed during follow-up. Missing lung function data were not imputed. Overall mortality was established using censor date of Aug 15, 2024. Receiver operating characteristics (ROC) curve analysis was used to select the optimal cut-off point of soluble mediators with Youden’s J statistic, which maximizes sensitivity and specificity. We generated hazard ratios (HR) to compare patients assigned to groups based on the optimal cut-point. Kaplan-Meier method and log-rank tests were used to assess progression-free survival (PFS) and overall survival (OS), which was defined as the time between baseline sampling and the occurrence of disease progression, including acute exacerbation, or all cause-mortality, respectively. These analyses were performed with the use of SPSS (version 26). Results from cytokine measurements and flow cytometry were analyzed with GraphPad Prism™ v9.0.1 software. Specific statistic tests were applied as appropriate, as indicated in each figure’s legend. Statistical results with a P-value ≤ 0.05 were significant. RESULTS Prospective cohort characteristics The total study population comprised 71 patients with fibrotic HP with a median follow-up time of 35.8 months, during which 41 patients (57.7%) progressed, 23 (32.4%) experienced acute exacerbation (including 10 cases occurring during follow-up of the prospective FL cohort — Fig. 1 a-b — in addition to 13 patients who were only enrolled upon exacerbation — Fig. 1 c-D), 18 died and 1 underwent lung transplantation. Demographics, exposures, comorbidities and other clinical features are summarized in Table 1 . A positive family history for any fibrotic ILD was described in 8.5% and 25% presented autoimmune features. Concerning the environmental context, less than half reported smoking history (44.1%), and most cases had avian exposure (78.9%), followed by exposure to moulds (46.5%), and only in a few (7%) were not possible to identify the antigen source. Inhalation of inorganic dust was reported in 42.3% cases. Although considered a hallmark of HP [ 1 ], among those who underwent BALF analysis as part of their diagnostic process, only 16% had lymphocytosis ≥ 30%. Table 1 Clinical features of fibrotic hypersensitivity pneumonitis patients. Continuous variables are presented as median (range). The frequencies describe the number of cases for each finding divided by the total number of patients for whom data were available. Variable All (n = 71) FL cohort (n = 58) Exacerbations (n = 13) Age, years 70.9 (31–80) 69.9 (31–80) 73.8 (58–78) Male gender, n (%) 32 (45.1) 29 (50) 3 (23.1) BMI 29.1 (16.6–43.9) 29.3 (21.5–43.9) 27.9 (16.6–33.8) Ever smoker, n (%) 30 (44.1) 26 (46.4) 4 (33.3) Exposure, n (%) Avian 56 (78.9) 47 (81) 9 (69.2) Fungal/moist 33 (46.5) 26 (44.8) 7 (53.8) Unknown/cryptogenic 5 (7) 3 (5.2) 2 (15.4) Inorganic 30 (42.3) 22 (37.9) 8 (61.5) Comorbidities, n (%) Cardiovascular disease * 51 (71.8) 43 (74.1) 8 (61.5) OSAS 31 (53.4) 25 (51) 6 (66.7) GERD 26 (36.6) 23 (39.7) 3 (23.1) Diabetes mellitus 25 (35.2) 20 (34.5) 5 (38.5) Autoimmune features 16 (25) 15 (29.4) 1 (7.7) Neoplasm ** 15 (21.1) 13 (22.4) 2 (15.4) Chronic kidney disease 3 (4.2) 3 (5.2) 0 COPD 5 (7) 4 (6.9) 1 (7.7) Chronic liver disease 2 (2.8) 1 (1.7) 1 (7.7) Lung function tests FVC, % predicted 84.5 (33.2–119) 86.1 (48.2–119) 58.3 (33.2-100.5) FEV1, % predicted 85.3 (39.4-125.5) 88.9 (55.1-125.5) 63.1 (39.4-104.1) FEV1/FVC, % 85.6 (55.3–100) 86 (55.3–100) 85.2 (71.8–93.9) TLC, % predicted 79.4 (40.9-113.2) 80 (48.7-113.2) 53.3 (40.9-105.3) RV, % predicted 79.7 (33.1–170) 81.6 (47.1–170) 48.2 (33.1-121.6) DL CO , % predicted 55.5 (9.0-94.1) 57.1 (23.6–94.1) 41.5 (9.0-66.7) HRCT patterns, n (%) CPFE, n (%) 12 (17.1) 9 (15.8) 3 (23.1) UIP-like, n (%) 37 (53.6) 25 (44.6) 12 (92.3) Blood cell counts WBC, cells x10 9 /L 8.04 (4.7-21.43) 7.67 (4.70-15.92) 11.02 (5.91–21.43) Neutrophils, cells x10 9 /L 5.08 (1.21–19.99) 4.69 (2.58–13.83) 7.98 (1.21–19.99) Eosinophils, cells x10 9 /L 0.17 (0-0.61) 0.19 (0.01–0.61) 0.02 (0-0.24) Lymphocytes, cells x10 9 /L 1.89 (0.26–3.41) 1.98 (0.86–3.41) 1.83 (0.26–3.04) Monocytes, cells x10 9 /L 0.59 (0.13–2.34) 0.51 (0.13–1.16) 0.71 (0.17–2.34) BALF Total cells count, x10 5 cells/mL 1.80 (0.20–8.64) 1.80 (0.20–8.64) 1.60 (0.20–3.80) Macrophages, % 70.6 (6–96) 70.6 (6–96) 80 (47.4–88.4) Lymphocytes, % 14 (1.6–93) 13.8 (1.6–93) 14.6 (2–72) Neutrophils, % 5.7 (0-47.4) 5.6 (0-47.4) 6 (1.2–20) Eosinophils, % 2.8 (0–17) 3 (0–17) 1.6 (0.2–9.6) Mastocytes, % 0 (0-5.4) 0 (0-5.4) 0 (0-0.2) FL cohort: FIBRALUNG cohort (prospective cohort); BMI: body mass index; OSAS: obstructive sleep apnea syndrome; GERD: gastroesophageal reflux disease; COPD: chronic obstructive pulmonary disease; FVC: forced vital capacity; FEV1: forced expiratory volume in the first second; TLC: total lung capacity; RV: residual volume; DLCO: diffusing lung capacity for carbon monoxide; CPFE – combined pulmonary fibrosis and emphysema; UIP: usual interstitial pneumonia; WBC: white blood cell count; BALF: bronchoalveolar lavage fluid. * Cardiovascular disease – presence of any of the following: arterial hypertension, ischemic heart disease, heart failure, peripheral artery disease, cerebrovascular disease or atrial fibrillation. ** Neoplasm – diagnosis of either solid or lymphoproliferative tumor. Considering the FL cohort (Fig. 1 b), followed-up prospectively from baseline, the median progression-free survival (PFS) was 43.9 months (95% confidence interval 30.6–57.1), with a 1-year and 2-year progression rates of 12.1% and 31%, respectively. At time of censoring, only 23 (39.7%) remained stable and 7 (12.1%) were responsive to treatment. Almost all patients were under immunosuppressive treatment (86%) and roughly one-third (32.4%) started antifibrotics. Elevated serum CCL2 levels are associated with disease progression and acute exacerbation in fibrotic HP To investigate whether alterations on systemic inflammatory mediators may associate with fibrotic HP progression, we used a multiplex assay to measure the serum levels of several cytokines/chemokines across different disease stages, including samples at baseline, those collected closest to progression (near-progression), and during acute exacerbation events. Among the 13 molecules tested (supplementary figure S2), CCL2 emerged as the strongest predictor of progression: healthy controls (mean 479.6 pg/mL) and baseline samples from fibrotic HP patients (mean 970.1 pg/mL) showed significantly lower CCL2 levels than those collected near-progression (mean 1811 pg/mL) and during acute exacerbations (mean 1834 pg/mL) (Fig. 2 a). None of the other measured analytes revealed such a robust increase in near-progression or exacerbation groups in comparison to baseline. Notably, CCL2 levels often remained elevated after corticosteroid pulses in exacerbations (Fig. 2 a). As illustrated in Fig. 2 b, baseline CCL2 levels increased markedly within the first 6 months of follow-up, with the median trajectory (black line, open squares) indicating an upward trend as disease evolves. Error bands reveal substantial inter-patient variability, with lower CCL2 levels observed among responsive cases (yellow circles) during the initial 18 months of follow-up, when compared to ongoing stable (blue circles) and progressors (red circles). A temporary decrease in CCL2 levels was observed at 12 and 18 months, aligning with an increased number of patients on immunosuppressive and antifibrotic therapies, until it rose again at 18–24 months despite ongoing treatments. Increased sensitivity to CCL2 may influence targeted cell recruitment to the lung environment To investigate whether, immune cell migration in HP patients was affected by increased levels of CCL2 we conducted transwell migration assays using PBMCs from healthy controls and fibrotic HP patients in different disease stages (before/after a progression event). Cell migration was evaluated at two CCL2 concentrations (10 ng/mL and 100 ng/mL). As shown in Fig. 3 a, PBMCs from fibrotic HP patients demonstrated significantly enhanced migration in response to CCL2 as compared to controls, exhibiting a clear dose-dependent increase in migrating cells. Notably, PBMCs from patients who had already experienced disease progression showed a particularly robust migratory response as compared to no-ILD controls indicating an elevated sensitivity to CCL2-mediated chemotaxis in progressors. We hypothesised that this enhanced migration could be driven by differential expression of CCR2, the CCL2 receptor. Supporting this assumption, flow cytometric analysis of whole blood monocyte subsets from these patients revealed a significantly higher expression of CCR2 on classical monocytes and a tendency towards increased expression on intermediate monocytes in post-progression fibrotic HP patients (Fig. 3 b), despite similar frequencies of monocytes, and CCR2 + monocytes, were observed across patient groups (Fig. 3 c). Bronchoalveolar microenvironment in fibrotic HP patients is enriched with CCR2 + CD206 − CD169 + cells We next measured CCL2 concentrations in BALF fluid from fibrotic HP patients at baseline, stratifying the patients in groups according to their disease trajectories over 24 months. CCL2 levels in the baseline BALF (Fig. 4 a) were notably higher in patients with disease progression (mean 427.1 pg/mL) compared to those with responsive (mean 131.9 pg/mL) or stable disease (mean 147.5 pg/mL). To further explore the role of alveolar CCL2 at promoting immune cell recruitment, we next conducted an immunophenotyping analysis of BALF using fresh samples from 7 newly diagnosed fibrotic HP patients, 6 non-fibrotic HP cases, 5 IPF cases, and 3 controls without ILD (general immune cell populations frequencies and simplified gating strategy for monocyte/macrophages are shown in supplementary figure S3). No significant differences in cell frequencies or CCR2 expression in alveolar macrophages (CD206 + CD169 + ) (Fig. 4 b) or monocytes (CD206 − CD169 − HLA-DR + CD14 + ) was found between disease groups (Fig. 4 c). However, fibrotic HP patients showed a trend toward an increased percentage of CD206 + CD169 − cells, with IPF cases reaching a statistically significant elevation. Notably, this subset had markedly higher CCR2 expression in both fibrotic HP and IPF groups (Fig. 4 d, middle graph) which led us to hypothesize that these cells may represent a transitional population being recruited from the peripheral blood to the alveoli in response to CCL2. In support of this, the morphological comparison of the CD206 + CD169 − cell population with alveolar macrophages and monocytes grounded on cell size [ 19 ] showed that this population aligned more closely with monocyte characteristics (supplementary figure S3b). Collectively, our results suggest that higher levels of local CCL2 may attract CCR2 + CD206 + CD169 − cells to the alveolus, and that these cells may serve as monocyte-derived precursors to CD206 + CD169 + alveolar macrophages, contributing to the evolving immune landscape in fibrotic HP. CCL2 and CCR2 protein levels are not related with annotated genetic polymorphisms To explore whether a genetic basis may underlie the observed elevations in CCL2 levels and increased CCR2 expression, we analyzed DNA from peripheral blood of no-ILD controls and fibrotic HP patients and questioned the genotype of selected annotated SNPs for CCL2 and CCR2 in Axiom Human Genotyping SARs-COV-2. Two CCL2 SNPs ( rs1024611 and rs4586 ) and one CCR2 SNP ( rs1799864 ), that have been previously associated with either elevated systemic CCL2 levels or increased susceptibility and worse outcomes in chronic inflammatory diseases [ 20 – 23 ] were selected to be analyzed. Selected SNP revealed no significant impact on baseline serum CCL2 concentrations in our study population (supplementary figure S4). These results indicate that the elevated CCL2 and CCR2 expression observed in fibrotic HP is likely driven by mechanisms independent of genetic predisposition. Predictors of progression and survival analysis based on CCL2 serum levels To investigate the potential of CCL2 as a predictive marker for HP disease stage, we evaluated baseline and exacerbation serum CCL2 levels using a ROC curve to identify the optimal cut-off of 1080.69 pg/mL for 1-year progression prediction (supplementary figure S5). CCL2 concentrations above that threshold had a significantly negative impact on the OS (Fig. 5 a), even after adjusting for age and baseline FVC (adjusted HR 5.89, 95% CI 1.38–25.09, P = 0.016). Higher CCL2 levels also showed a tendency toward greater average FVC decline, both in absolute values (mL) and in percentage change per year (Fig. 5 b). DISCUSSION This study provides evidence of a dysregulated CCL2/CCR2/monocyte axis in patients with progressive fibrosing HP, which likely underlies the increased peripheral blood monocytes migration to the alveolar milieu. CCL2, also known as monocyte chemoattractant protein-1 (MCP-1), is a potent chemotactic agent for various immune cells, including monocytes/macrophages, T-cells, natural killer cells, and fibrocytes [ 24 – 28 ]. Through its interaction with its receptor, CCR2, CCL2 orchestrates immune cell recruitment to sites of tissue injury contributing to inflammation, cell activation, and angiogenesis, acting as a key mediator in the fibrotic cascade [ 29 ]. Additionally, by enhancing the sensitivity to transforming growth factor β (TGF-β), CCL2 facilitates the recruitment of fibrocytes and promotes fibroblast activation, while limiting their apoptosis [ 30 , 31 ]. In this way, CCL2 contributes to the excessive deposition of extracellular matrix proteins, the hallmark of pathological fibrosis. CCL2 was shown to be highly expressed in alveolar epithelial cells from fibrotic areas of IPF lungs [ 13 ], and CCL2 BALF concentrations were significantly increased in IPF patients [ 14 , 15 ]. Approximately one-third of fibrotic HP patients in our cohort experienced disease progression within two years of baseline evaluation, consistent with an IPF-like progressive phenotype. These patients demonstrated a trend toward higher BALF CCL2 levels compared to those who remained stable or responded to treatment. However, the invasiveness of BALF sampling pose significant challenges for its routine use for follow-up. Contrarily, serum CCL2 levels provide a more feasible parameter to monitor disease progression. We observed substantial variability in serum CCL2 concentrations over time, with significantly elevated levels near progression events, including acute exacerbations. Stratification using an CCL2 serum cut-off value of 1080.69 pg/mL revealed that patients with higher concentrations tended to exhibit faster FVC decline and shorter survival, aligning with previous findings in IPF, where elevated BALF CCL2 correlated with mortality [ 32 ]. Furthermore, we explored a broader inflammatory landscape by measuring the serum levels of multiple cytokines and chemokines using a multiplex ELISA. While most cytokines were significantly elevated near disease progression compared to baseline, such as IL18 and IL6, their levels did not consistently increase during exacerbation phases, unlike CCL2, which may reflect distinct biological mechanisms in the inflammatory and fibrotic signalling. Despite these variations, the consistent elevation of CCL2 throughout advanced disease stages underscores its potential as a predictive marker for disease worsening and progression in fibrotic HP. Future studies should further dissect the differential inflammatory signatures underlying chronic progression versus acute exacerbations to refine predictive biomarkers and therapeutic targets. To further explore the biological relevance of the increased levels of CCL2, and the mechanisms underlying progression in fibrotic HP, we evaluated the ability of PBMCs from fibrotic HP patients to migrate in an ex vivo migration assay in response to recombinant CCL2. Transwell migration assay demonstrated an enhanced migratory capacity of PBMCs from HP patients who had already experienced progression, suggesting another mechanism preceding exacerbation. Although CCL2 was initially characterized as monocytes chemoattractant, subsequent studies have revealed an even higher activity on T-cells [ 33 ]. However, in our cohort, only 16% of patients presented BALF lymphocytosis > 30%, suggesting that monocytes/macrophages likely play a more dominant role in the fibrotic phase of the disease. This observation is further supported by our findings that progressive patients displayed increased CCR2 expression on classical and, possibly, on intermediate monocyte subsets, highlighting the involvement of these cells in disease progression. These results were also corroborated by BALF flow cytometry data, which revealed elevated CCR2 expression on monocyte-derived subsets in fibrotic HP patients. Cellular size comparison indicated that those BALF cells (CD206 + CD169 − ) more closely resemble monocytes than alveolar macrophages, suggesting that they represent monocyte-derived precursors to alveolar macrophages [ 19 ]. In IPF patients, this subset was significantly elevated, indicating shared immune mechanisms between fibrotic HP and IPF. The enhanced CCR2 expression on CD206 + CD169 − cells highlights the potentially higher recruitment of these cells to the lung in response to elevated CCL2 levels, reinforcing the role of the CCL2/CCR2 axis in shaping the immune landscape of fibrotic HP. Interestingly, we found no association between these findings and genetic variations in CCL2 or CCR2 SNPs, emphasizing the role of post-transcriptional or environmental factors in modulating CCL2 and CCR2 expression, rather than by genetic predisposition, in contrast to what is described for other genes [ 34 – 36 ]. Lung CCR2 + cells were described to be significantly elevated in the bleomycin-induced fibrosis mouse model and, interestingly, administration of oral CCR2 inhibitor reduced lung CCR2 + cell populations and fibrosis in a similar magnitude as nintedanib [ 37 ]. These findings are also consistent with experimental models of genetic CCR2 deficiency and highlight the critical role of CCR2 + cells in lung fibrosis development [ 38 ]. However, while CCR2 + cell-targeted therapies have shown success in addressing fibrosis in the liver, kidney, and heart [ 39 ], their potential in lung fibrosis remains unclear. Despite promising observational and preclinical data, the anti-CCL2 monoclonal antibody carlumab failed to show protective effects in IPF, with trials prematurely halted due to greater FVC decline in the treatment group compared to placebo [ 40 ]. Intriguingly, patients receiving carlumab exhibited higher serum CCL2 concentrations than those on placebo, suggesting the activation of bypass mechanisms circumventing CCL2 blockade. Similarly, in our study, we observed an initial median decrease in CCL2 levels when patients started immunosuppressive drugs, followed by a rebound increase after 12–18 months, despite ongoing treatment, including with antifibrotics. Notably, fibrotic HP patients classified as responders to immunosuppressive therapy initially displayed lower CCL2 levels than stable or progressor groups. However, after 18 months, their CCL2 levels converged with those of the other groups, suggesting that the benefits of immunosuppressive treatment may be transient, and that progression occurs irrespective of initial disease stage. Considering the demonstrated benefits of antifibrotic therapies in progressive pulmonary fibrosis [ 41 , 42 ], we speculate that, like IPF, a subset of fibrotic HP patients may achieve better disease control with antifibrotic drugs rather than immunosuppression from baseline. This hypothesis warrants investigation through a randomized clinical trial. Interestingly, elevated peripheral monocytes in IPF and HP patients have been linked to poor survival and adverse outcomes. Retrospective studies in IPF have demonstrated associations between higher monocyte counts in peripheral blood and increased risks of disease progression, hospitalization, and mortality [ 43 – 45 ]. Likewise, our previous data [ 46 ] have indicated that elevated peripheral monocytes in HP are associated with poor clinical outcomes, reinforcing the significance of monocyte levels and CCL2/CCR2-mediated recruitment as critical prognostic indicators. Altogether, we demonstrate for the first time that the serum levels of CCL2 may be useful to predict clinical outcomes in fibrotic HP, as our findings suggest that temporal changes in circulating concentrations of CCL2 reflect the risk of disease progression. Furthermore, we propose a model for the detrimental role of CCL2 in HP: HP patients displaying a progressive fibrotic phenotype show increased peripheral and alveolar CCL2 levels and CCR2 expression in monocytes, which leads to enhanced migration and activation of these cells to the lung, where they likely contribute to the profibrotic immune landscape in fibrotic HP. Our data support CCL2 as a potential risk biomarker, and CCR2 + cell-targeted therapies as compelling candidates to treat lung fibrosis. Declarations Ethics approval and consent to participate: The study protocol was reviewed and approved by the Ethics Committee of the Institution (approval number: 72/19) and performed in accordance with the Helsinki Declaration. All subjects provided their informed consent for inclusion in the study at enrolment. Consent for publication: Not applicable. Availability of data and materials: All data supporting the findings of this study are available within the paper and its Supplementary Information. Competing interests: Authors claim no conflict of interests. Funding: This work was supported by the national funds through FCT – Fundação para a Ciência e a Tecnologia, I.P., within the scope of project PTDC/MEC-RES/0158/2020, Fundação Amélia de Mello and D. José de Mello grants and Portuguese Society of Pulmonology. M. Saraiva is funded by FCT through CEEC. Author’s contributions: R.F.S. and H.N.B. conceptualized and designed the study. R.F.S. conducted the experiments. R.F.S., C.G.C., A.P., D.B.C., and H.N.B. collected clinical data and performed data analysis. L.O., M.G., A.C., O.K., and M.B. handled the collection and processing of biological samples. H.N.B., A.T.A., N.M., P.C.M., I.N., V.C., L.F., F.F., and A.M. contributed to patient selection. P.F., F.V.N., and A.L.M. provided control samples. S.G., C.S.M., A.C., and A.M. participated in discussions regarding final diagnosis and progression criteria. R.F.S. and H.N.B. wrote the manuscript and designed the figures, while M.S., L.D., and A.M. edited the paper and provided conceptual input. Acknowledgements: We would like to express our gratitude to Ana Luísa Fernandes, Ana Loureiro, Delfina Branco, Filipa Aguiar, Francisca Lopes Teixeira, Inês Rodrigues, Pedro Ramalho, Sandra Macedo, Sara Cabral, Sílvia Silva and Tiago Oliveira for their invaluable contributions in recruiting cases and providing samples from patients with hypersensitivity pneumonitis. Their efforts were instrumental to the success of this study. We thank Gil Castro for proofreading the manuscript. References Raghu G, Remy-Jardin M, Ryerson CJ, et al. Diagnosis of Hypersensitivity Pneumonitis in Adults. An Official ATS/JRS/ALAT Clinical Practice Guideline. Am J Respir Crit Care Med 2020; 202: e36–e69. Morais A, Winck JC, Delgado L, et al. 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Purification and amino acid analysis of two human glioma-derived monocyte chemoattractants. J Exp Med 1989; 169: 1449–59. Allavena P, Bianchi G, Zhou D, et al. Induction of natural killer cell migration by monocyte chemotactic protein-1, -2 and -3. Eur J Immunol 1994; 24: 3233–6. Gendelman HE, Ding S, Gong N, et al. Monocyte chemotactic protein-1 regulates voltage-gated K+ channels and macrophage transmigration. J Neuroimmune Pharmacol 2009; 4: 47–59. Moore BB. Following the path of CCL2 from prostaglandins to periostin in lung fibrosis. Am J Respir Cell Mol Biol 2014; 50: 848–52. Murray LA, Argentieri RL, Farrell FX, et al. Hyper-responsiveness of IPF/UIP fibroblasts: interplay between TGFbeta1, IL-13 and CCL2. Int J Biochem Cell Biol 2008; 40: 2174–82. Liu X, Das AM, Seideman J, et al. The CC chemokine ligand 2 (CCL2) mediates fibroblast survival through IL-6. Am J Respir Cell Mol Biol 2007; 37: 121–8. Shinoda H, Tasaka S, Fujishima S, et al. 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Moore BB, Paine R, Christensen PJ, et al. Protection from pulmonary fibrosis in the absence of CCR2 signaling. J Immunol 2001; 167: 4368–77. Bajpai G, Bredemeyer A, Li W, et al. Tissue Resident CCR2- and CCR2+ Cardiac Macrophages Differentially Orchestrate Monocyte Recruitment and Fate Specification Following Myocardial Injury. Circ Res 2019; 124:263–78. Raghu G, Martinez FJ, Brown KK, et al. CC-chemokine ligand 2 inhibition in idiopathic pulmonary fibrosis: a phase 2 trial of carlumab. Eur Respir J 2015; 46: 1740–50. Fernández Pérez ER, Crooks JL, Lynch DA, et al. Pirfenidone in fibrotic hypersensitivity pneumonitis: a double-blind, randomised clinical trial of efficacy and safety. Thorax 2023; 78: 1097–104. Wells AU, Flaherty KR, Brown KK, et al. Nintedanib in patients with progressive fibrosing interstitial lung diseases-subgroup analyses by interstitial lung disease diagnosis in the INBUILD trial: a randomised, double-blind, placebo-controlled, parallel-group trial. Lancet Respir Med 2020; 8: 453–60. Kreuter M, Lee JS, Tzouvelekis A, et al. Monocyte Count as a Prognostic Biomarker in Patients with Idiopathic Pulmonary Fibrosis. Am J Respir Crit Care Med 2021; 204: 74–81. Barratt SL, Creamer AW, Adamali HI, et al. Use of peripheral neutrophil to lymphocyte ratio and peripheral monocyte levels to predict survival in fibrotic hypersensitivity pneumonitis (fHP): a multicentre retrospective cohort study. BMJ Open Respir Res 2021; 8: e001063. Scott MKD, Quinn K, Li Q, et al. Increased monocyte count as a cellular biomarker for poor outcomes in fibrotic diseases: a retrospective, multicentre cohort study. Lancet Respir Med 2019; 7: 497–508. Pinto A, Aguiar F, Cardoso C, et al. Monocyte/macrophage axis as potential drivers of Progressive Fibrosing Hypersensitivity Pneumonitis. Eur Respir J 2023; 62(suppl 67): PA1164. Additional Declarations No competing interests reported. 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00:23:05","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6908974/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6908974/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12931-026-03555-z","type":"published","date":"2026-04-11T15:58:01+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":91328759,"identity":"c13da40e-9dac-41c7-b554-566432090fa8","added_by":"auto","created_at":"2025-09-15 10:24:09","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1437041,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCharacterization of the main cohorts included in the study.\u003c/strong\u003e (a) Schematic representation of the prospective FIBRALUNG (FL) cohort, comprising 58 fibrotic hypersensitivity pneumonitis (HP) patients. (b) Swimmer plot illustrating individual patient trajectories. Different colors indicate the disease status at the last follow-up (yellow: responders; blue: ongoing stable; red: progressors). Among progressors, progression-free survival (in weeks) is represented by dotted bars. Patients who experienced acute exacerbations are also indicated, and fatal events are highlighted to depict survival. (c) Schematic representation of the exacerbation cohort, corresponding to patients enrolled during acute exacerbations, along with the corresponding swimmer plot (d).\u003c/p\u003e","description":"","filename":"Fig1.png","url":"https://assets-eu.researchsquare.com/files/rs-6908974/v1/55619cb56d22abc7abfeb1ce.png"},{"id":91329094,"identity":"bf208174-db4e-47b6-9287-15e8e2aa8868","added_by":"auto","created_at":"2025-09-15 10:32:10","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":465882,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eElevated CCL2 circulating levels in fibrotic hypersensitivity pneumonitis (HP) patients are associated with disease progression and exacerbation. \u003c/strong\u003eSerum levels of the chemokine CCL2 were measured by ELISA. Detection level (DL) is 1.1 pg/mL. (a) Patients were stratified according to disease phase: baseline samples from 58 patients (light blue circles), samples collected near a progression event from 23 patients (dark blue circles), and samples taken during acute exacerbation from 14 patients (black circles), which includes one patient of the prospective FL cohort followed from baseline. Exacerbation samples collected following corticosteroid pulses are showed in open circles. Thirty-two controls included are displayed in orange circles. Each dot represents one patient. Violin plots include horizontal lines indicating the median and quartiles, mean values are displayed below each condition. Data were analyzed with Kruskal-Wallis and Dunn’s multiple comparison test, *P \u0026lt; 0.05, ***P \u0026lt; 0.005, ****P \u0026lt; 0.001. (b) Samples were distributed based on the time of collection: baseline samples were taken during the diagnostic workup, and follow-up samples were collected every 6 (±3) months. The overall median values for all the patients at each time-point is represented by the black line with white open squares. The filled grey area corresponds to the error bands. Corresponding number of patients at each time-point and frequency of those receiving treatment (immunosuppressive or antifibrotic drugs) are shown below the graph. Oscillation of the serum levels of the chemokine CCL2 stratified by disease status in fibrotic HP patients is shown by dashed lines (yellow circles: responsive; blue circles: ongoing stable; red circles: progressor).\u003c/p\u003e","description":"","filename":"Fig2.png","url":"https://assets-eu.researchsquare.com/files/rs-6908974/v1/21c0a5a01c6ac12550c30be7.png"},{"id":91328763,"identity":"020e838c-4095-4402-9509-418c56c08264","added_by":"auto","created_at":"2025-09-15 10:24:10","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":806649,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eEnhanced responsiveness to CCL2 and monocyte CCR2 expression in fibrotic hypersensitivity pneumonitis (HP) patients with progressive phenotype. \u003c/strong\u003e(a) Transwell migration assays were performed using peripheral blood mononuclear cells (PBMCs) from No-ILD controls and fibrotic HP patients, before and after a progression event. CCL2 was added to the lower chamber at concentrations of 10 or 100 ng/mL and cell migration was assessed after 3 hours. The percentage of migrating cells was determined by calculating the ratio between the number of cells recovered from the lower compartment and the total number of cells seeded in control well. Cells adhering to the membrane's lower side were also included in the analysis. Each dot represents an individual patient. Results are presented as means ± standard deviation. (b) and (c) Flow cytometry analysis of whole blood in No-ILD Control subjects (white circles) and fibrotic HP patients (responsive/ongoing stable in blue circles, and progressors in red circles). (b) gMFI of CCR2 in CCR2-expressing monocytes (classical and intermediate) (left) with representative expression heatmaps within monocytes subsets shown in contour plots (right). (c) Frequencies of the different monocyte's subsets in live CD45\u003csup\u003e+\u003c/sup\u003e cells (left graph) and corresponding frequency of CCR2\u003csup\u003e+ \u003c/sup\u003emonocytes (right graph). Each dot represents one patient and horizontal lines indicate the respective mean ± SD. Data were analyzed with Kruskal-Wallis and Dunn’s multiple comparison test or with 2way ANOVA following by Šídák's multiple comparisons test, *P \u0026lt; 0.05, **P \u0026lt; 0.005. gMFI: geometric mean fluorescence intensity. Classical monocytes: CD14\u003csup\u003e+\u003c/sup\u003eCD16\u003csup\u003e-\u003c/sup\u003e; Intermediate monocytes: CD14\u003csup\u003e+\u003c/sup\u003eCD16\u003csup\u003e+\u003c/sup\u003e; Non classical monocytes: CD14\u003csup\u003elow/-\u003c/sup\u003eCD16\u003csup\u003e+\u003c/sup\u003e\u003c/p\u003e","description":"","filename":"Fig3.png","url":"https://assets-eu.researchsquare.com/files/rs-6908974/v1/50da3b82c57b4af862793c71.png"},{"id":91328770,"identity":"1763f2cb-d22d-49f5-ab29-e3fda6c60152","added_by":"auto","created_at":"2025-09-15 10:24:10","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":780676,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eBronchoalveolar lavage (BAL) CCL2 levels and CD206\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e+ \u003c/strong\u003e\u003c/sup\u003e\u003cstrong\u003eCD169\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e- \u003c/strong\u003e\u003c/sup\u003e\u003cstrong\u003eCCR2-expressing cells are increased in\u0026nbsp; hypersensitivity pneumonitis (HP) patients with progressive fibrosis. \u003c/strong\u003e(a) BAL fluid levels of CCL2 were measured by ELISA at baseline. Fibrotic HP patients were stratified according to disease progression over a minimum 24-months follow-up: 6 patients with a responsive phenotype (yellow circles), 15 patients with ongoing stable disease (blue circles), and 16 classified as progressors (red circles). Each dot represents an individual patient. Violin plots include horizontal lines showing the median and quartiles, with mean values displayed below each condition. Detection level (DL) is 1.1.pg/mL. (b,c,d) Flow cytometry analysis of bronchoalveolar lavage cells of No-ILD Control subjects (white circles), non-fibrotic HP (green circles), fibrotic HP (blue circles) and idiopathic pulmonary fibrosis (IPF) patients (pink circles). Frequencies of alveolar macrophages (CD206\u003csup\u003e+\u003c/sup\u003e CD169\u003csup\u003e+\u003c/sup\u003e) (b), monocytes (CD206\u003csup\u003e-\u003c/sup\u003eCD169\u003csup\u003e- \u003c/sup\u003eHLA-DR\u003csup\u003e+ \u003c/sup\u003eCD14\u003csup\u003e+\u003c/sup\u003e) (c), CD206\u003csup\u003e+\u003c/sup\u003e CD169\u003csup\u003e-\u003c/sup\u003e cells (d) in live CD45\u003csup\u003e+\u003c/sup\u003e cells (left graphs) with corresponding frequency of CCR2\u003csup\u003e+ \u003c/sup\u003ecells (middle graphs). gMFI of CCR2 in CCR2-expressing cells are shown in corresponding right graphs. Each dot represents one patient and horizontal lines indicate the respective mean ± SD. Data were analyzed with Kruskal-Wallis and Dunn’s multiple comparison test, *P \u0026lt; 0.05. gMFI: geometric mean fluorescence intensity.\u003c/p\u003e","description":"","filename":"Fig4.png","url":"https://assets-eu.researchsquare.com/files/rs-6908974/v1/1b7f8b42a91d166ce11015b7.png"},{"id":91328767,"identity":"4d1f9557-1457-4b48-9a0a-c7c323a51333","added_by":"auto","created_at":"2025-09-15 10:24:10","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":481770,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSerum CCL2 concentrations above 1080.69 pg/mL were significantly associated with overall survival. \u003c/strong\u003e(a)\u003cstrong\u003e \u003c/strong\u003eKaplan-Meier estimate of time to all-cause mortality (overall survival, left), or time to progression, exacerbation or mortality due to respiratory causes (progression-free survival, right), stratified according to baseline serum concentration of CCL2. Data were analyzed with log-rank test. Crude hazard ratio (HR) and adjusted HR (controlled for age and FVC) values are displayed. (b)\u003cstrong\u003e \u003c/strong\u003eComparison of mean (SE, standard error) rate of decline in force vital capacity (FVC) (mL or %) per year between CCL2 level groups.\u003c/p\u003e","description":"","filename":"Fig5.png","url":"https://assets-eu.researchsquare.com/files/rs-6908974/v1/752f63394722a90d801edcd7.png"},{"id":106808889,"identity":"8d78f1f6-248b-449a-9ff0-0e510f45cd34","added_by":"auto","created_at":"2026-04-13 16:04:34","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":5538773,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6908974/v1/f73d5957-5419-4658-a2b9-8a1e543cfc08.pdf"},{"id":91328781,"identity":"d6846fad-8bdc-4ee7-9539-e06c2b8e6fb7","added_by":"auto","created_at":"2025-09-15 10:24:11","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":1969230,"visible":true,"origin":"","legend":"","description":"","filename":"SantosetalOnlineDataSupplement.docx","url":"https://assets-eu.researchsquare.com/files/rs-6908974/v1/b3e1dc00727242b73b343317.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"The CCL2-driven monocyte-macrophage axis in progressive fibrosing hypersensitivity pneumonitis","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eHypersensitivity pneumonitis (HP) is a complex immune-mediated interstitial lung disease (ILD) triggered by repeated inhalation of environmental antigens in genetically susceptible individuals [\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. While non-fibrotic HP is often reversible with antigen avoidance, the fibrotic form is characterized by irreversible lung damage and fibrosis [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e], with striking similarities to idiopathic pulmonary fibrosis (IPF), the archetypal progressive fibrosing ILD. In fact, fibrotic HP was reported to have comparable rate of forced vital capacity (FVC) decline and survival as IPF [\u003cspan additionalcitationids=\"CR6\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], and episodes of acute exacerbations also occur, which are linked with poor prognosis [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Antifibrotic therapy has shown to slow lung function decline in identical magnitude in IPF and progressive fibrotic HP [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Conversely, despite limited supporting evidence, immunosuppressive drugs are often the frontline approach in fibrotic HP, providing 12-months response or stabilization in less than half of the patients [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e] and high rates of early treatment discontinuation due to either toxicity or inefficacy [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe identification of HP patients who are likely to experience progressive fibrosis remains difficult, as reliable biomarkers for disease progression are lacking. While certain clinical features, such as the presence of usual interstitial pneumonia (UIP) patterns on high-resolution computed tomography (HRCT), and absent bronchoalveolar lavage fluid (BALF) lymphocytosis, have been associated with worse outcomes in fibrotic HP [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], these markers are not sufficient to fully predict which patients will worsen under immunosuppressive treatment.\u003c/p\u003e\u003cp\u003eEmerging evidence highlights the pivotal role of monocyte/macrophage dynamics in fibrotic ILDs, with CC-chemokine ligand 2 (CCL2) identified as a key driver of monocyte recruitment and macrophage activation in IPF [\u003cspan additionalcitationids=\"CR14\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. However, the contribution of this axis to fibrotic HP remains largely unexplored. In this study, we sought to explore potential pathways linked with progressive fibrosing HP, aiming to improve early identification of patients who have higher risk of progression and could eventually benefit from timely intervention with antifibrotic therapies. We envisage that advancing our understanding of the pathophysiology of fibrotic HP progression will support the development of precision medicine in this field.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eStudy design, cohorts and biological sampling\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFIBRALUNG (Fibrosing ILD Biomarkers That Rule Acceleration, https://fibralung.pt) is a longitudinal observational cohort study that follows patients with ILDs across six hospitals in Northern Portugal (NCT05635032, registration date 2023-10-27) [16] We prospectively included 58 adult participants with fibrotic HP who were treatment-na\u0026iuml;ve for disease-modifying drugs at enrolment (FL cohort), and followed them for at least 24 months, or until death or lung transplant (figure 1). To capture the extreme phenotype of disease progression, we further enriched this cohort with 13 patients experiencing acute exacerbations. Healthy controls were also included for comparative analysis in cytokines/chemokines measurements (n=32), genetic studies (n=91), and migration assay (n=3). Additionally, a comparative study of BALF flow cytometry was performed in 7 newly diagnosed fibrotic HP patients, 6 non-fibrotic HP and 5 IPF cases, and 3 no-ILD controls. Further details regarding controls and comparative groups are provided in the Supplementary materials (supplementary figure S1). All diagnoses were established in a multidisciplinary team meeting at the coordinating centre [1,4].\u003c/p\u003e\n\u003cp\u003eProgression was assessed at every appointed hospital visit with HRCT scan or lung function testing\u0026nbsp;according to the recent progressive pulmonary fibrosis diagnostic guidelines [17]. Time to progression was determined from the first medical appointment till \u0026ge;2 of the defined progression criteria was met. Acute exacerbation or mortality due to respiratory causes were also considered as a progressive event. Responsiveness to therapy was defined as an increase of at least 5% in FVC or 10% in diffusing lung capacity for carbon monoxide (DLCO), accompanied by improved symptoms or HRCT findings. Stable disease was considered when neither progression nor responsiveness was observed. Biological samples were collected every six months from fibrotic HP patients in the FL cohort for a minimum of 24 months. In the progressors group, the time point closest to disease progression was identified as the \u0026ldquo;near-progression\u0026rdquo; sample.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eCytokines/chemokines measurement and analysis\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePeripheral blood was collected into a BD Vacutainer\u0026reg; SST\u0026trade; II Advance tubes and centrifuged to separate serum. BALF was collected at baseline according to previous described methodology [18]. Serum and BALF aliquots were analyzed using the LEGENDplex\u0026trade; Human Inflammatory panel 1 (13-plex) (BioLegend). Data were acquired in a FACS CANTO 2 flow cytometer and analyzed using FlowJo\u0026trade; v10.10 software (BD Biosciences).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eDNA extraction and single nucleotide peptide (SNP) genotyping\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGenomic DNA was extracted from peripheral ethylenediaminetetraacetic acid (EDTA)-anticoagulated blood using QIAamp\u0026reg; DNA Blood Kit (Qiagen). SNPs genotyping in \u003cem\u003eCCL2\u003c/em\u003e and its receptor, \u003cem\u003eCCR2\u003c/em\u003e, were performed by Axiom\u003csup\u003eTM\u003c/sup\u003e Human Genotyping SARS-COV-2 Array (Thermo Fisher Scientific), which includes \u0026gt;800,000 SNPs.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003ePeripheral blood mononuclear cells (PBMCs) isolation and migration assay\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePeripheral blood samples were collected in EDTA-treated tubes (BD Vacutainer), and the PBMC fraction was isolated using Lympholyte-H density gradient (CEDARLANE). Migration assays were performed in 24-well plates with 5-\u0026mu;m pore-sized chamber inserts (Costar, Corning, Inc.). A total of 7.5 \u0026times; 10\u003csup\u003e5\u003c/sup\u003e cells per well were seeded in the transwell upper chamber. Medium supplemented with 10% FBS, with or without 10 and 100 ng/mL human recombinant CCL2 (Peprotech), were added to the lower chamber. Cells were incubated at 37 \u0026deg;C with 5% CO\u003csub\u003e2\u003c/sub\u003e for 3 hours, after which cells in the lower compartment were collected, and those adhering to the lower side of the membrane were scraped. The percentage of migrating cells was assessed by the ratio between the number of cells recovered from the lower compartment and the number of cells seeded in the control well.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eFlow cytometry\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eImmune cell composition and CCR2 levels of expression were assessed by flow cytometry in BALF and whole blood. Red blood cell lysis in peripheral blood samples was performed with RBC lysis buffer from BioLegend. ViaDye\u0026trade; Red Fixable Viability Dye (Cytek) was used to assess live cells. Additional details are provided in the Supplementary materials. Data was acquired in the spectral cell analyzer Aurora (Cytek) and analyzed using FlowJo\u0026trade; v10.10 software (BD Biosciences).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eStatistical analysis\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAn estimative of the annual variation of FVC and/or DLCO was objectively assessed by calculating the slope-intercept equation from at least three pulmonary function tests performed during follow-up. Missing lung function data were not imputed. Overall mortality was established using censor date of Aug 15, 2024.\u003c/p\u003e\n\u003cp\u003eReceiver operating characteristics (ROC) curve analysis was used to select the optimal cut-off point of soluble mediators with Youden\u0026rsquo;s J statistic, which maximizes sensitivity and specificity. We generated hazard ratios (HR) to compare patients assigned to groups based on the optimal cut-point. Kaplan-Meier method and log-rank tests were used to assess progression-free survival (PFS) and overall survival (OS), which was defined as the time between baseline sampling and the occurrence of disease progression, including acute exacerbation, or all cause-mortality, respectively. These analyses were performed with the use of SPSS (version 26). Results from cytokine measurements and flow cytometry were analyzed with GraphPad Prism\u0026trade; v9.0.1 software. Specific statistic tests were applied as appropriate, as indicated in each figure\u0026rsquo;s legend. Statistical results with a P-value \u0026le; 0.05 were significant.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003eProspective cohort characteristics\u003c/h2\u003e\u003cp\u003eThe total study population comprised 71 patients with fibrotic HP with a median follow-up time of 35.8 months, during which 41 patients (57.7%) progressed, 23 (32.4%) experienced acute exacerbation (including 10 cases occurring during follow-up of the prospective FL cohort \u0026mdash; Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea-b \u0026mdash; in addition to 13 patients who were only enrolled upon exacerbation \u0026mdash; Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ec-D), 18 died and 1 underwent lung transplantation. Demographics, exposures, comorbidities and other clinical features are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. A positive family history for any fibrotic ILD was described in 8.5% and 25% presented autoimmune features. Concerning the environmental context, less than half reported smoking history (44.1%), and most cases had avian exposure (78.9%), followed by exposure to moulds (46.5%), and only in a few (7%) were not possible to identify the antigen source. Inhalation of inorganic dust was reported in 42.3% cases. Although considered a hallmark of HP [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e], among those who underwent BALF analysis as part of their diagnostic process, only 16% had lymphocytosis\u0026thinsp;\u0026ge;\u0026thinsp;30%.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003e\u003cb\u003eClinical features of fibrotic hypersensitivity pneumonitis patients.\u003c/b\u003e Continuous variables are presented as median (range). The frequencies describe the number of cases for each finding divided by the total number of patients for whom data were available.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"8\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003eAll (n\u0026thinsp;=\u0026thinsp;71)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003eFL cohort (n\u0026thinsp;=\u0026thinsp;58)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003eExacerbations (n\u0026thinsp;=\u0026thinsp;13)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAge, years\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e70.9 (31\u0026ndash;80)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e69.9 (31\u0026ndash;80)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003e73.8 (58\u0026ndash;78)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eMale gender, n (%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e32 (45.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e29 (50)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003e3 (23.1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eBMI\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e29.1 (16.6\u0026ndash;43.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e29.3 (21.5\u0026ndash;43.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003e27.9 (16.6\u0026ndash;33.8)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eEver smoker, n (%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e30 (44.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e26 (46.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003e4 (33.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eExposure, n (%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eAvian\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e56 (78.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e47 (81)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003e9 (69.2)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eFungal/moist\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e33 (46.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e26 (44.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003e7 (53.8)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eUnknown/cryptogenic\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e5 (7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e3 (5.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003e2 (15.4)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eInorganic\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e30 (42.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e22 (37.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003e8 (61.5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eComorbidities, n (%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eCardiovascular disease\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e51 (71.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e43 (74.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003e8 (61.5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eOSAS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e31 (53.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e25 (51)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003e6 (66.7)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eGERD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e26 (36.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e23 (39.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003e3 (23.1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eDiabetes mellitus\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e25 (35.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e20 (34.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003e5 (38.5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eAutoimmune features\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e16 (25)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e15 (29.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003e1 (7.7)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eNeoplasm\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e15 (21.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e13 (22.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003e2 (15.4)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eChronic kidney disease\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e3 (4.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e3 (5.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eCOPD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e5 (7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e4 (6.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003e1 (7.7)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eChronic liver disease\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e2 (2.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e1 (1.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003e1 (7.7)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eLung function tests\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eFVC, % predicted\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e84.5 (33.2\u0026ndash;119)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e86.1 (48.2\u0026ndash;119)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003e58.3 (33.2-100.5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eFEV1, % predicted\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e85.3 (39.4-125.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e88.9 (55.1-125.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003e63.1 (39.4-104.1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eFEV1/FVC, %\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e85.6 (55.3\u0026ndash;100)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e86 (55.3\u0026ndash;100)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003e85.2 (71.8\u0026ndash;93.9)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eTLC, % predicted\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e79.4 (40.9-113.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e80 (48.7-113.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003e53.3 (40.9-105.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eRV, % predicted\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e79.7 (33.1\u0026ndash;170)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e81.6 (47.1\u0026ndash;170)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003e48.2 (33.1-121.6)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eDL\u003csub\u003eCO\u003c/sub\u003e, % predicted\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e55.5 (9.0-94.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e57.1 (23.6\u0026ndash;94.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003e41.5 (9.0-66.7)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHRCT patterns, n (%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eCPFE, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e12 (17.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e9 (15.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003e3 (23.1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eUIP-like, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e37 (53.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e25 (44.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003e12 (92.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eBlood cell counts\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eWBC, cells x10\u003csup\u003e9\u003c/sup\u003e/L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e8.04 (4.7-21.43)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e7.67 (4.70-15.92)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003e11.02 (5.91\u0026ndash;21.43)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eNeutrophils, cells x10\u003csup\u003e9\u003c/sup\u003e/L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e5.08 (1.21\u0026ndash;19.99)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e4.69 (2.58\u0026ndash;13.83)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003e7.98 (1.21\u0026ndash;19.99)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eEosinophils, cells x10\u003csup\u003e9\u003c/sup\u003e/L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e0.17 (0-0.61)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e0.19 (0.01\u0026ndash;0.61)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003e0.02 (0-0.24)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eLymphocytes, cells x10\u003csup\u003e9\u003c/sup\u003e/L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e1.89 (0.26\u0026ndash;3.41)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e1.98 (0.86\u0026ndash;3.41)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003e1.83 (0.26\u0026ndash;3.04)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eMonocytes, cells x10\u003csup\u003e9\u003c/sup\u003e/L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e0.59 (0.13\u0026ndash;2.34)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e0.51 (0.13\u0026ndash;1.16)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003e0.71 (0.17\u0026ndash;2.34)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eBALF\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal cells count, x10\u003csup\u003e5\u003c/sup\u003e cells/mL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e1.80 (0.20\u0026ndash;8.64)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e1.80 (0.20\u0026ndash;8.64)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u003cp\u003e1.60 (0.20\u0026ndash;3.80)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c8\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eMacrophages, %\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e70.6 (6\u0026ndash;96)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e70.6 (6\u0026ndash;96)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003e80 (47.4\u0026ndash;88.4)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eLymphocytes, %\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e14 (1.6\u0026ndash;93)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e13.8 (1.6\u0026ndash;93)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003e14.6 (2\u0026ndash;72)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eNeutrophils, %\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e5.7 (0-47.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e5.6 (0-47.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003e6 (1.2\u0026ndash;20)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eEosinophils, %\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e2.8 (0\u0026ndash;17)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e3 (0\u0026ndash;17)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003e1.6 (0.2\u0026ndash;9.6)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eMastocytes, %\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e0 (0-5.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e0 (0-5.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003e0 (0-0.2)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"8\"\u003eFL cohort: FIBRALUNG cohort (prospective cohort); BMI: body mass index; OSAS: obstructive sleep apnea syndrome; GERD: gastroesophageal reflux disease; COPD: chronic obstructive pulmonary disease; FVC: forced vital capacity; FEV1: forced expiratory volume in the first second; TLC: total lung capacity; RV: residual volume; DLCO: diffusing lung capacity for carbon monoxide; CPFE \u0026ndash; combined pulmonary fibrosis and emphysema; UIP: usual interstitial pneumonia; WBC: white blood cell count; BALF: bronchoalveolar lavage fluid.\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"8\"\u003e\u003csup\u003e*\u003c/sup\u003e Cardiovascular disease \u0026ndash; presence of any of the following: arterial hypertension, ischemic heart disease, heart failure, peripheral artery disease, cerebrovascular disease or atrial fibrillation.\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"8\"\u003e\u003csup\u003e**\u003c/sup\u003e Neoplasm \u0026ndash; diagnosis of either solid or lymphoproliferative tumor.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eConsidering the FL cohort (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb), followed-up prospectively from baseline, the median progression-free survival (PFS) was 43.9 months (95% confidence interval 30.6\u0026ndash;57.1), with a 1-year and 2-year progression rates of 12.1% and 31%, respectively. At time of censoring, only 23 (39.7%) remained stable and 7 (12.1%) were responsive to treatment. Almost all patients were under immunosuppressive treatment (86%) and roughly one-third (32.4%) started antifibrotics.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eElevated serum CCL2 levels are associated with disease progression and acute exacerbation in fibrotic HP\u003c/h2\u003e\u003cp\u003eTo investigate whether alterations on systemic inflammatory mediators may associate with fibrotic HP progression, we used a multiplex assay to measure the serum levels of several cytokines/chemokines across different disease stages, including samples at baseline, those collected closest to progression (near-progression), and during acute exacerbation events. Among the 13 molecules tested (supplementary figure S2), CCL2 emerged as the strongest predictor of progression: healthy controls (mean 479.6 pg/mL) and baseline samples from fibrotic HP patients (mean 970.1 pg/mL) showed significantly lower CCL2 levels than those collected near-progression (mean 1811 pg/mL) and during acute exacerbations (mean 1834 pg/mL) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea). None of the other measured analytes revealed such a robust increase in near-progression or exacerbation groups in comparison to baseline. Notably, CCL2 levels often remained elevated after corticosteroid pulses in exacerbations (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea). As illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb, baseline CCL2 levels increased markedly within the first 6 months of follow-up, with the median trajectory (black line, open squares) indicating an upward trend as disease evolves. Error bands reveal substantial inter-patient variability, with lower CCL2 levels observed among responsive cases (yellow circles) during the initial 18 months of follow-up, when compared to ongoing stable (blue circles) and progressors (red circles). A temporary decrease in CCL2 levels was observed at 12 and 18 months, aligning with an increased number of patients on immunosuppressive and antifibrotic therapies, until it rose again at 18\u0026ndash;24 months despite ongoing treatments.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eIncreased sensitivity to CCL2 may influence targeted cell recruitment to the lung environment\u003c/h2\u003e\u003cp\u003eTo investigate whether, immune cell migration in HP patients was affected by increased levels of CCL2 we conducted transwell migration assays using PBMCs from healthy controls and fibrotic HP patients in different disease stages (before/after a progression event). Cell migration was evaluated at two CCL2 concentrations (10 ng/mL and 100 ng/mL). As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea, PBMCs from fibrotic HP patients demonstrated significantly enhanced migration in response to CCL2 as compared to controls, exhibiting a clear dose-dependent increase in migrating cells. Notably, PBMCs from patients who had already experienced disease progression showed a particularly robust migratory response as compared to no-ILD controls indicating an elevated sensitivity to CCL2-mediated chemotaxis in progressors. We hypothesised that this enhanced migration could be driven by differential expression of CCR2, the CCL2 receptor. Supporting this assumption, flow cytometric analysis of whole blood monocyte subsets from these patients revealed a significantly higher expression of CCR2 on classical monocytes and a tendency towards increased expression on intermediate monocytes in post-progression fibrotic HP patients (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb), despite similar frequencies of monocytes, and CCR2\u003csup\u003e+\u003c/sup\u003e monocytes, were observed across patient groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003eBronchoalveolar microenvironment in fibrotic HP patients is enriched with CCR2\u003csup\u003e+\u003c/sup\u003eCD206\u003csup\u003e\u0026minus;\u003c/sup\u003eCD169\u003csup\u003e+\u003c/sup\u003e cells\u003c/h2\u003e\u003cp\u003eWe next measured CCL2 concentrations in BALF fluid from fibrotic HP patients at baseline, stratifying the patients in groups according to their disease trajectories over 24 months. CCL2 levels in the baseline BALF (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea) were notably higher in patients with disease progression (mean 427.1 pg/mL) compared to those with responsive (mean 131.9 pg/mL) or stable disease (mean 147.5 pg/mL). To further explore the role of alveolar CCL2 at promoting immune cell recruitment, we next conducted an immunophenotyping analysis of BALF using fresh samples from 7 newly diagnosed fibrotic HP patients, 6 non-fibrotic HP cases, 5 IPF cases, and 3 controls without ILD (general immune cell populations frequencies and simplified gating strategy for monocyte/macrophages are shown in supplementary figure S3). No significant differences in cell frequencies or CCR2 expression in alveolar macrophages (CD206\u003csup\u003e+\u003c/sup\u003eCD169\u003csup\u003e+\u003c/sup\u003e) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eb) or monocytes (CD206\u003csup\u003e\u0026minus;\u003c/sup\u003eCD169\u003csup\u003e\u0026minus;\u003c/sup\u003eHLA-DR\u003csup\u003e+\u003c/sup\u003eCD14\u003csup\u003e+\u003c/sup\u003e) was found between disease groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ec). However, fibrotic HP patients showed a trend toward an increased percentage of CD206\u003csup\u003e+\u003c/sup\u003eCD169\u003csup\u003e\u0026minus;\u003c/sup\u003e cells, with IPF cases reaching a statistically significant elevation. Notably, this subset had markedly higher CCR2 expression in both fibrotic HP and IPF groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ed, middle graph) which led us to hypothesize that these cells may represent a transitional population being recruited from the peripheral blood to the alveoli in response to CCL2. In support of this, the morphological comparison of the CD206\u003csup\u003e+\u003c/sup\u003eCD169\u003csup\u003e\u0026minus;\u003c/sup\u003e cell population with alveolar macrophages and monocytes grounded on cell size [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e] showed that this population aligned more closely with monocyte characteristics (supplementary figure S3b).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eCollectively, our results suggest that higher levels of local CCL2 may attract CCR2\u003csup\u003e+\u003c/sup\u003eCD206\u003csup\u003e+\u003c/sup\u003eCD169\u003csup\u003e\u0026minus;\u003c/sup\u003e cells to the alveolus, and that these cells may serve as monocyte-derived precursors to CD206\u003csup\u003e+\u003c/sup\u003eCD169\u003csup\u003e+\u003c/sup\u003e alveolar macrophages, contributing to the evolving immune landscape in fibrotic HP.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003eCCL2 and CCR2 protein levels are not related with annotated genetic polymorphisms\u003c/h2\u003e\u003cp\u003eTo explore whether a genetic basis may underlie the observed elevations in CCL2 levels and increased CCR2 expression, we analyzed DNA from peripheral blood of no-ILD controls and fibrotic HP patients and questioned the genotype of selected annotated SNPs for \u003cem\u003eCCL2\u003c/em\u003e and \u003cem\u003eCCR2\u003c/em\u003e in Axiom Human Genotyping SARs-COV-2. Two \u003cem\u003eCCL2\u003c/em\u003e SNPs (\u003cem\u003ers1024611\u003c/em\u003e and \u003cem\u003ers4586\u003c/em\u003e) and one \u003cem\u003eCCR2\u003c/em\u003e SNP (\u003cem\u003ers1799864\u003c/em\u003e), that have been previously associated with either elevated systemic CCL2 levels or increased susceptibility and worse outcomes in chronic inflammatory diseases [\u003cspan additionalcitationids=\"CR21 CR22\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] were selected to be analyzed. Selected SNP revealed no significant impact on baseline serum CCL2 concentrations in our study population (supplementary figure S4). These results indicate that the elevated CCL2 and CCR2 expression observed in fibrotic HP is likely driven by mechanisms independent of genetic predisposition.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003ePredictors of progression and survival analysis based on CCL2 serum levels\u003c/h2\u003e\u003cp\u003eTo investigate the potential of CCL2 as a predictive marker for HP disease stage, we evaluated baseline and exacerbation serum CCL2 levels using a ROC curve to identify the optimal cut-off of 1080.69 pg/mL for 1-year progression prediction (supplementary figure S5). CCL2 concentrations above that threshold had a significantly negative impact on the OS (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea), even after adjusting for age and baseline FVC (adjusted HR 5.89, 95% CI 1.38\u0026ndash;25.09, P\u0026thinsp;=\u0026thinsp;0.016). Higher CCL2 levels also showed a tendency toward greater average FVC decline, both in absolute values (mL) and in percentage change per year (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eb).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThis study provides evidence of a dysregulated CCL2/CCR2/monocyte axis in patients with progressive fibrosing HP, which likely underlies the increased peripheral blood monocytes migration to the alveolar milieu. CCL2, also known as monocyte chemoattractant protein-1 (MCP-1), is a potent chemotactic agent for various immune cells, including monocytes/macrophages, T-cells, natural killer cells, and fibrocytes [\u003cspan additionalcitationids=\"CR25 CR26 CR27\" citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Through its interaction with its receptor, CCR2, CCL2 orchestrates immune cell recruitment to sites of tissue injury contributing to inflammation, cell activation, and angiogenesis, acting as a key mediator in the fibrotic cascade [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Additionally, by enhancing the sensitivity to transforming growth factor β (TGF-β), CCL2 facilitates the recruitment of fibrocytes and promotes fibroblast activation, while limiting their apoptosis [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. In this way, CCL2 contributes to the excessive deposition of extracellular matrix proteins, the hallmark of pathological fibrosis. CCL2 was shown to be highly expressed in alveolar epithelial cells from fibrotic areas of IPF lungs [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], and CCL2 BALF concentrations were significantly increased in IPF patients [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eApproximately one-third of fibrotic HP patients in our cohort experienced disease progression within two years of baseline evaluation, consistent with an IPF-like progressive phenotype. These patients demonstrated a trend toward higher BALF CCL2 levels compared to those who remained stable or responded to treatment. However, the invasiveness of BALF sampling pose significant challenges for its routine use for follow-up. Contrarily, serum CCL2 levels provide a more feasible parameter to monitor disease progression. We observed substantial variability in serum CCL2 concentrations over time, with significantly elevated levels near progression events, including acute exacerbations. Stratification using an CCL2 serum cut-off value of 1080.69 pg/mL revealed that patients with higher concentrations tended to exhibit faster FVC decline and shorter survival, aligning with previous findings in IPF, where elevated BALF CCL2 correlated with mortality [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eFurthermore, we explored a broader inflammatory landscape by measuring the serum levels of multiple cytokines and chemokines using a multiplex ELISA. While most cytokines were significantly elevated near disease progression compared to baseline, such as IL18 and IL6, their levels did not consistently increase during exacerbation phases, unlike CCL2, which may reflect distinct biological mechanisms in the inflammatory and fibrotic signalling. Despite these variations, the consistent elevation of CCL2 throughout advanced disease stages underscores its potential as a predictive marker for disease worsening and progression in fibrotic HP. Future studies should further dissect the differential inflammatory signatures underlying chronic progression versus acute exacerbations to refine predictive biomarkers and therapeutic targets.\u003c/p\u003e\u003cp\u003eTo further explore the biological relevance of the increased levels of CCL2, and the mechanisms underlying progression in fibrotic HP, we evaluated the ability of PBMCs from fibrotic HP patients to migrate in an \u003cem\u003eex vivo\u003c/em\u003e migration assay in response to recombinant CCL2. Transwell migration assay demonstrated an enhanced migratory capacity of PBMCs from HP patients who had already experienced progression, suggesting another mechanism preceding exacerbation. Although CCL2 was initially characterized as monocytes chemoattractant, subsequent studies have revealed an even higher activity on T-cells [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. However, in our cohort, only 16% of patients presented BALF lymphocytosis\u0026thinsp;\u0026gt;\u0026thinsp;30%, suggesting that monocytes/macrophages likely play a more dominant role in the fibrotic phase of the disease. This observation is further supported by our findings that progressive patients displayed increased CCR2 expression on classical and, possibly, on intermediate monocyte subsets, highlighting the involvement of these cells in disease progression. These results were also corroborated by BALF flow cytometry data, which revealed elevated CCR2 expression on monocyte-derived subsets in fibrotic HP patients. Cellular size comparison indicated that those BALF cells (CD206\u003csup\u003e+\u003c/sup\u003eCD169\u003csup\u003e\u0026minus;\u003c/sup\u003e) more closely resemble monocytes than alveolar macrophages, suggesting that they represent monocyte-derived precursors to alveolar macrophages [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. In IPF patients, this subset was significantly elevated, indicating shared immune mechanisms between fibrotic HP and IPF. The enhanced CCR2 expression on CD206\u003csup\u003e+\u003c/sup\u003eCD169\u003csup\u003e\u0026minus;\u003c/sup\u003e cells highlights the potentially higher recruitment of these cells to the lung in response to elevated CCL2 levels, reinforcing the role of the CCL2/CCR2 axis in shaping the immune landscape of fibrotic HP. Interestingly, we found no association between these findings and genetic variations in \u003cem\u003eCCL2\u003c/em\u003e or \u003cem\u003eCCR2\u003c/em\u003e SNPs, emphasizing the role of post-transcriptional or environmental factors in modulating CCL2 and CCR2 expression, rather than by genetic predisposition, in contrast to what is described for other genes [\u003cspan additionalcitationids=\"CR35\" citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eLung CCR2\u003csup\u003e+\u003c/sup\u003e cells were described to be significantly elevated in the bleomycin-induced fibrosis mouse model and, interestingly, administration of oral CCR2 inhibitor reduced lung CCR2\u003csup\u003e+\u003c/sup\u003e cell populations and fibrosis in a similar magnitude as nintedanib [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. These findings are also consistent with experimental models of genetic \u003cem\u003eCCR2\u003c/em\u003e deficiency and highlight the critical role of CCR2\u003csup\u003e+\u003c/sup\u003e cells in lung fibrosis development [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. However, while CCR2\u003csup\u003e+\u003c/sup\u003e cell-targeted therapies have shown success in addressing fibrosis in the liver, kidney, and heart [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e], their potential in lung fibrosis remains unclear. Despite promising observational and preclinical data, the anti-CCL2 monoclonal antibody carlumab failed to show protective effects in IPF, with trials prematurely halted due to greater FVC decline in the treatment group compared to placebo [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. Intriguingly, patients receiving carlumab exhibited higher serum CCL2 concentrations than those on placebo, suggesting the activation of bypass mechanisms circumventing CCL2 blockade. Similarly, in our study, we observed an initial median decrease in CCL2 levels when patients started immunosuppressive drugs, followed by a rebound increase after 12\u0026ndash;18 months, despite ongoing treatment, including with antifibrotics. Notably, fibrotic HP patients classified as responders to immunosuppressive therapy initially displayed lower CCL2 levels than stable or progressor groups. However, after 18 months, their CCL2 levels converged with those of the other groups, suggesting that the benefits of immunosuppressive treatment may be transient, and that progression occurs irrespective of initial disease stage. Considering the demonstrated benefits of antifibrotic therapies in progressive pulmonary fibrosis [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e], we speculate that, like IPF, a subset of fibrotic HP patients may achieve better disease control with antifibrotic drugs rather than immunosuppression from baseline. This hypothesis warrants investigation through a randomized clinical trial.\u003c/p\u003e\u003cp\u003eInterestingly, elevated peripheral monocytes in IPF and HP patients have been linked to poor survival and adverse outcomes. Retrospective studies in IPF have demonstrated associations between higher monocyte counts in peripheral blood and increased risks of disease progression, hospitalization, and mortality [\u003cspan additionalcitationids=\"CR44\" citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. Likewise, our previous data [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e] have indicated that elevated peripheral monocytes in HP are associated with poor clinical outcomes, reinforcing the significance of monocyte levels and CCL2/CCR2-mediated recruitment as critical prognostic indicators.\u003c/p\u003e\u003cp\u003eAltogether, we demonstrate for the first time that the serum levels of CCL2 may be useful to predict clinical outcomes in fibrotic HP, as our findings suggest that temporal changes in circulating concentrations of CCL2 reflect the risk of disease progression. Furthermore, we propose a model for the detrimental role of CCL2 in HP: HP patients displaying a progressive fibrotic phenotype show increased peripheral and alveolar CCL2 levels and CCR2 expression in monocytes, which leads to enhanced migration and activation of these cells to the lung, where they likely contribute to the profibrotic immune landscape in fibrotic HP. Our data support CCL2 as a potential risk biomarker, and CCR2\u003csup\u003e+\u003c/sup\u003e cell-targeted therapies as compelling candidates to treat lung fibrosis.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eEthics approval and consent to participate:\u0026nbsp;\u003c/em\u003e\u003c/strong\u003eThe study protocol was reviewed and approved by the Ethics Committee of the Institution (approval number: 72/19) and performed in accordance with the Helsinki Declaration. All subjects provided their informed consent for inclusion in the study at enrolment.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eConsent for publication:\u0026nbsp;\u003c/em\u003e\u003c/strong\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAvailability of data and materials:\u0026nbsp;\u003c/em\u003e\u003c/strong\u003eAll data supporting the findings of this study are available within the paper and its Supplementary Information.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eCompeting interests:\u003c/em\u003e\u003c/strong\u003eAuthors claim no conflict of interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eFunding:\u003c/em\u003e\u003c/strong\u003e This work was supported by the national funds through FCT – Fundação para a Ciência e a Tecnologia, I.P., within the scope of project PTDC/MEC-RES/0158/2020, Fundação Amélia de Mello and \u0026nbsp;D. José de Mello grants and Portuguese Society of Pulmonology. M. Saraiva is funded by FCT through CEEC.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAuthor’s contributions:\u0026nbsp;\u003c/em\u003e\u003c/strong\u003eR.F.S. and H.N.B. conceptualized and designed the study. R.F.S. conducted the experiments. R.F.S., C.G.C., A.P., D.B.C., and H.N.B. collected clinical data and performed data analysis. L.O., M.G., A.C., O.K., and M.B. handled the collection and processing of biological samples. H.N.B., A.T.A., N.M., P.C.M., I.N., V.C., L.F., F.F., and A.M. contributed to patient selection. P.F., F.V.N., and A.L.M. provided control samples. S.G., C.S.M., A.C., and A.M. participated in discussions regarding final diagnosis and progression criteria. R.F.S. and H.N.B. wrote the manuscript and designed the figures, while M.S., L.D., and A.M. edited the paper and provided conceptual input.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAcknowledgements:\u003c/em\u003e\u003c/strong\u003e We would like to express our gratitude to Ana Luísa Fernandes, Ana Loureiro, Delfina Branco, Filipa Aguiar, Francisca Lopes Teixeira, Inês Rodrigues, Pedro Ramalho, Sandra Macedo, Sara Cabral, Sílvia Silva and Tiago Oliveira for their invaluable contributions in recruiting cases and providing samples from patients with hypersensitivity pneumonitis. Their efforts were instrumental to the success of this study. We thank Gil Castro for proofreading the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eRaghu G, Remy-Jardin M, Ryerson CJ, et al. Diagnosis of Hypersensitivity Pneumonitis in Adults. 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Pirfenidone in fibrotic hypersensitivity pneumonitis: a double-blind, randomised clinical trial of efficacy and safety. \u003cem\u003eThorax\u003c/em\u003e 2023; 78: 1097\u0026ndash;104.\u003c/li\u003e\n \u003cli\u003eWells AU, Flaherty KR, Brown KK, et al. Nintedanib in patients with progressive fibrosing interstitial lung diseases-subgroup analyses by interstitial lung disease diagnosis in the INBUILD trial: a randomised, double-blind, placebo-controlled, parallel-group trial. \u003cem\u003eLancet Respir Med\u003c/em\u003e 2020; 8: 453\u0026ndash;60.\u003c/li\u003e\n \u003cli\u003eKreuter M, Lee JS, Tzouvelekis A, et al. Monocyte Count as a Prognostic Biomarker in Patients with Idiopathic Pulmonary Fibrosis. \u003cem\u003eAm J Respir Crit Care Med\u003c/em\u003e 2021; 204: 74\u0026ndash;81.\u003c/li\u003e\n \u003cli\u003eBarratt SL, Creamer AW, Adamali HI, et al. Use of peripheral neutrophil to lymphocyte ratio and peripheral monocyte levels to predict survival in fibrotic hypersensitivity pneumonitis (fHP): a multicentre retrospective cohort study. \u003cem\u003eBMJ Open Respir Res\u003c/em\u003e 2021; 8: e001063.\u003c/li\u003e\n \u003cli\u003eScott MKD, Quinn K, Li Q, et al. Increased monocyte count as a cellular biomarker for poor outcomes in fibrotic diseases: a retrospective, multicentre cohort study. \u003cem\u003eLancet Respir Med\u003c/em\u003e 2019; 7: 497\u0026ndash;508.\u003c/li\u003e\n \u003cli\u003ePinto A, Aguiar F, Cardoso C, et al. Monocyte/macrophage axis as potential drivers of Progressive Fibrosing Hypersensitivity Pneumonitis. \u003cem\u003eEur Respir J\u0026nbsp;\u003c/em\u003e2023; 62(suppl 67): PA1164.\u003cstrong\u003e\u003c/strong\u003e\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"respiratory-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"rere","sideBox":"Learn more about [Respiratory Research](http://respiratory-research.biomedcentral.com/)","snPcode":"12931","submissionUrl":"https://submission.nature.com/new-submission/12931/3","title":"Respiratory Research","twitterHandle":"@RespiratoryBMC","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"CC-chemokine ligand 2 (CCL2) / monocyte chemoattractant protein-1 (MCP-1), hypersensitivity pneumonitis, monocytes, macrophages, pulmonary fibrosis","lastPublishedDoi":"10.21203/rs.3.rs-6908974/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6908974/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eHypersensitivity pneumonitis is characterized by immune dysregulation that often leads to irreversible lung tissue scarring. While elevated monocytes play a key role in idiopathic pulmonary fibrosis, their contribution in progressive fibrotic hypersensitivity pneumonitis, along with the role of the CCL2 chemoattractant, requires clarification.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eImmune characterization of circulating and lung markers of 71 patients with fibrotic hypersensitivity pneumonitis followed longitudinally over median 35.8 months (57.7% progressed, 31% exacerbated), comparing with controls, non-fibrotic cases and idiopathic pulmonary fibrosis.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eElevated serum CCL2 strongly associated with disease progression and acute exacerbations, with baseline levels above 1080.69 pg/mL predicting progression and shorter survival. Despite significant variability in CCL2 levels over time, their elevation near progression was consistent, suggesting a role for this chemokine in the fibrotic cascade. Moreover, classical monocytes from patients with progressive disease displayed higher CCR2 expression, and peripheral blood mononuclear cells from these patients showed enhanced CCL2-driven chemotaxis. Bronchoalveolar lavage immunophenotyping identified enriched CCR2\u0026thinsp;+\u0026thinsp;monocyte-derived precursors in fibrotic hypersensitivity pneumonitis, implicating this cellular population in disease severity. Genetic analysis of \u003cem\u003eCCL2/CCR2\u003c/em\u003e revealed no association between their expression and known polymorphisms. Mechanistically, elevated CCL2 may drive disease progression by recruiting CCR2\u0026thinsp;+\u0026thinsp;monocytes, contributing to the profibrotic microenvironment.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eThese findings underscore the CCL2/CCR2 axis as a promising biomarker pathway for disease monitoring in fibrotic hypersensitivity pneumonitis, which could guide therapeutic interventions and stratification of high-risk patients.\u003c/p\u003e","manuscriptTitle":"The CCL2-driven monocyte-macrophage axis in progressive fibrosing hypersensitivity pneumonitis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-15 10:23:40","doi":"10.21203/rs.3.rs-6908974/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision 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