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The pathophysiology of silicosis is poorly understood, limiting development of therapies for those who have been exposed to the respirable particle. We explored mechanisms of silica-induced pulmonary fibrosis in human lung samples collected from patients with occupational exposure to silica and in a longitudinal mouse model of silicosis using multiple modalities including whole-lung single-cell RNA sequencing and histological, biochemical, and physiologic assessments. In addition to pulmonary inflammation and fibrosis, intratracheal silica challenge induced osteoclast-like differentiation of alveolar macrophages and recruited monocytes, driven by induction of the osteoclastogenic cytokine, receptor activator of nuclear factor κB ligand (RANKL) in pulmonary lymphocytes, and alveolar type II cells. Anti-RANKL monoclonal antibody treatment suppressed silica-induced osteoclast-like differentiation in the lung and attenuated pulmonary fibrosis. We conclude that silica induces differentiation of pulmonary osteoclast-like cells leading to progressive lung injury, likely due to sustained elaboration of boneresorbing proteases and hydrochloric acid. Interrupting osteoclast-like differentiation may therefore constitute a promising avenue for moderating lung damage in silicosis. [ABSTRACT FROM AUTHOR]

Objective: Among individuals with systemic sclerosis (SSc) randomized to cyclophosphamide (CYC) (n = 34) or hematopoietic stem cell transplantation (HSCT) (n = 33), we examined longitudinal trends of clinical, pulmonary function, and quality of life measures while accounting for the influence of early failures on treatment comparisons. Methods: Assuming that data were missing at random, mixed‐effects regression models were used to estimate longitudinal trends for clinical measures when comparing treatment groups. Results were compared to observed means and to longitudinal trends estimated from shared parameter models, assuming that data were missing not at random. Longitudinal trends for SSc intrinsic molecular subsets defined by baseline gene expression signatures (normal‐like, inflammatory, and fibroproliferative signatures) were also studied. Results: Available observed means for pulmonary function tests appeared to improve over time in both arms. However, after accounting for participant loss, forced vital capacity in HSCT recipients increased by 0.77 percentage points/year but worsened by –3.70/year for CYC (P = 0.004). Similar results were found for diffusing capacity for carbon monoxide and quality of life indicators. Results for both analytic models were consistent. HSCT recipients in the inflammatory (n = 20) and fibroproliferative (n = 20) subsets had superior long‐term trends compared to CYC for pulmonary and quality of life measures. HSCT was also superior for modified Rodnan skin thickness scores in the fibroproliferative subset. For the normal‐like subset (n = 22), superiority of HSCT was less apparent. Conclusion: Longitudinal trends estimated from 2 statistical models affirm the efficacy of HSCT over CYC in severe SSc. Failure to account for early loss of participants may distort estimated clinical trends over the long term. [ABSTRACT FROM AUTHOR]

Objectives Four intrinsic molecular subsets (inflammatory, fibroproliferative, limited, normal-like) have previously been identified in SSc and are characterized by unique gene expression signatures and pathways. The intrinsic subsets have been linked to improvement with specific therapies. Here, we investigated associations between baseline demographics and intrinsic molecular subsets in a meta-analysis of published datasets. Methods Publicly available gene expression data from skin biopsies of 311 SSc patients measured by DNA microarray were classified into the intrinsic molecular subsets. RNA-sequencing data from 84 participants from the ASSET trial were used as a validation cohort. Baseline clinical demographics and intrinsic molecular subsets were tested for statistically significant associations. Results Males were more likely to be classified in the fibroproliferative subset (P  = 0.0046). SSc patients who identified as African American/Black were 2.5 times more likely to be classified as fibroproliferative compared with White/Caucasian patients (P  = 0.0378). ASSET participants sera positive for anti-RNA pol I and RNA pol III autoantibodies were enriched in the inflammatory subset (P  = 5.8 × 10−5, P  = 9.3 × 10−5, respectively), while anti-Scl-70 was enriched in the fibroproliferative subset. Mean modified Rodnan Skin Score (mRSS) was statistically higher in the inflammatory and fibroproliferative subsets compared with normal-like (P  = 0.0027). The average disease duration for inflammatory subset was less than fibroproliferative and normal-like intrinsic subsets (P  = 8.8 × 10−4). Conclusions We identified multiple statistically significant differences in baseline demographics between the intrinsic subsets that may represent underlying features of disease pathogenesis (e.g. chronological stages of fibrosis) and have implications for treatments that are more likely to work in certain SSc populations. [ABSTRACT FROM AUTHOR]

Objective: We sought to determine histologic and gene expression features of clinical improvement in early diffuse cutaneous systemic sclerosis (dcSSc; scleroderma).Methods: Fifty-eight forearm biopsies were evaluated from 26 individuals with dcSSc in two clinical trials. Histologic/immunophenotypic assessments of global severity, alpha-smooth muscle actin (aSMA), CD34, collagen, inflammatory infiltrate, follicles and thickness were compared with gene expression and clinical data. Support vector machine learning was performed using scleroderma gene expression subset (normal-like, fibroproliferative, inflammatory) as classifiers and histology scores as inputs. Comparison of w-vector mean absolute weights was used to identify histologic features most predictive of gene expression subset. We then tested for differential gene expression according to histologic severity and compared those with clinical improvement (according to the Combined Response Index in Systemic Sclerosis).Results: aSMA was highest and CD34 lowest in samples with highest local Modified Rodnan Skin Score. CD34 and aSMA changed significantly from baseline to 52 weeks in clinical improvers. CD34 and aSMA were the strongest predictors of gene expression subset, with highest CD34 staining in the normal-like subset (p<0.001) and highest aSMA staining in the inflammatory subset (p=0.016). Analysis of gene expression according to CD34 and aSMA binarised scores identified a 47-gene fibroblast polarisation signature that decreases over time only in improvers (vs non-improvers). Pathway analysis of these genes identified gene expression signatures of inflammatory fibroblasts.Conclusion: CD34 and aSMA stains describe distinct fibroblast polarisation states, are associated with gene expression subsets and clinical assessments, and may be useful biomarkers of clinical severity and improvement in dcSSc. [ABSTRACT FROM AUTHOR]

Objectives: Determine global skin transcriptome patterns of early diffuse systemic sclerosis (SSc) and how they differ from later disease.Methods: Skin biopsy RNA from 48 patients in the Prospective Registry for Early Systemic Sclerosis (PRESS) cohort (mean disease duration 1.3 years) and 33 matched healthy controls was examined by next-generation RNA sequencing. Data were analysed for cell type-specific signatures and compared with similarly obtained data from 55 previously biopsied patients in Genetics versus Environment in Scleroderma Outcomes Study cohort with longer disease duration (mean 7.4 years) and their matched controls. Correlations with histological features and clinical course were also evaluated.Results: SSc patients in PRESS had a high prevalence of M2 (96%) and M1 (94%) macrophage and CD8 T cell (65%), CD4 T cell (60%) and B cell (69%) signatures. Immunohistochemical staining of immune cell markers correlated with the gene expression-based immune cell signatures. The prevalence of immune cell signatures in early diffuse SSc patients was higher than in patients with longer disease duration. In the multivariable model, adaptive immune cell signatures were significantly associated with shorter disease duration, while fibroblast and macrophage cell type signatures were associated with higher modified Rodnan Skin Score (mRSS). Immune cell signatures also correlated with skin thickness progression rate prior to biopsy, but did not predict subsequent mRSS progression.Conclusions: Skin in early diffuse SSc has prominent innate and adaptive immune cell signatures. As a prominently affected end organ, these signatures reflect the preceding rate of disease progression. These findings could have implications in understanding SSc pathogenesis and clinical trial design. [ABSTRACT FROM AUTHOR]

The pathophysiology of silicosis is poorly understood, limiting development of therapies for those who have been exposed to the respirable particle. We explored mechanisms of silica-induced pulmonary fibrosis in human lung samples collected from patients with occupational exposure to silica and in a longitudinal mouse model of silicosis using multiple modalities including whole-lung single-cell RNA sequencing and histological, biochemical, and physiologic assessments. In addition to pulmonary inflammation and fibrosis, intratracheal silica challenge induced osteoclast-like differentiation of alveolar macrophages and recruited monocytes, driven by induction of the osteoclastogenic cytokine, receptor activator of nuclear factor κΒ ligand (RANKL) in pulmonary lymphocytes, and alveolar type II cells. Anti-RANKL monoclonal antibody treatment suppressed silica-induced osteoclast-like differentiation in the lung and attenuated pulmonary fibrosis. We conclude that silica induces differentiation of pulmonary osteoclast-like cells leading to progressive lung injury, likely due to sustained elaboration of bone-resorbing proteases and hydrochloric acid. Interrupting osteoclast-like differentiation may therefore constitute a promising avenue for moderating lung damage in silicosis.