Introduction: Progressive fibrosis in systemic sclerosis (SSc) is linked to aberrant transforming growth factor beta (TGF-beta) signaling. Peroxisome proliferator-activated receptor gamma (PPAR-gamma) blocks fibrogenic TGF-beta responses in vitro and in vivo. Reduced expression and function of PPAR-gamma in patients with SSc may contribute to progression of fibrosis. Here we evaluated the levels of adiponectin, a sensitive and specific index of PPAR-gamma activity, as a potential fibrogenic biomarker in SSc. Methods: Adiponectin levels were determined in the sera of 129 patients with SSc and 86 healthy controls, and serial determinations were performed in 27 patients. Levels of adiponectin mRNA in skin biopsies from SSc patients were assessed in an expression profiling microarray dataset. Regulation of adiponectin gene expression in explanted human subcutaneous preadipocytes and fibroblasts was examined by real-time quantitative PCR. Results: Patients with diffuse cutaneous SSc had reduced serum adiponectin levels. A significant inverse correlation between adiponectin levels and the modified Rodnan skin score was observed. In longitudinal studies changes in serum adiponectin levels were inversely correlated with changes in skin fibrosis. Skin biopsies from a subset of SSc patients showed reduced adiponectin mRNA expression which was inversely correlated with the skin score. An agonist ligand of PPAR-gamma potently induced adiponectin expression in explanted mesenchymal cells in vitro. Conclusions: Levels of adiponectin, reflecting PPAR-gamma activity, are correlated with skin fibrosis and might have potential utility as a biomarker in SSc.

Systemic sclerosis (SSc) is a rare autoimmune disease with the highest case-fatality rate of all connective tissue diseases. Current efforts to determine patient response to a given treatment using the modified Rodnan skin score (mRSS) are complicated by interclinician variability, confounding, and the time required between sequential mRSS measurements to observe meaningful change. There is an unmet critical need for an objective metric of SSc disease severity. Here, we performed an integrated, multicohort analysis of SSc transcriptome data across 7 datasets from 6 centers composed of 515 samples. Using 158 skin samples from SSc patients and healthy controls recruited at 2 centers as a discovery cohort, we identified a 415-gene expression signature specific for SSc, and validated its ability to distinguish SSc patients from healthy controls in an additional 357 skin samples from 5 independent cohorts. Next, we defined the SSc skin severity score (4S). In every SSc cohort of skin biopsy samples analyzed in our study, 4S correlated significantly with mRSS, allowing objective quantification of SSc disease severity. Using transcriptome data from the largest longitudinal trial of SSc patients to date, we showed that 4S allowed us to objectively monitor individual SSc patients over time, as (a) the change in 4S of a patient is significantly correlated with change in the mRSS, and (b) the change in 4S at 12 months of treatment could predict the change in mRSS at 24 months. Our results suggest that 4S could be used to distinguish treatment responders from nonresponders prior to mRSS change. Our results demonstrate the potential clinical utility of a novel robust molecular signature and a computational approach to SSc disease severity quantification.

Introduction: The multifunctional nuclear receptor peroxisome proliferator-activated receptor gamma (PPAR-γ) has potent anti-fibrotic effects, and its expression and activity are impaired in patients with systemic sclerosis (SSc). We investigated PPAR-γ gene (PPARG) single nucleotide polymorphisms (SNPs) associated with SSc. Methods: Tag SNPs spanning PPARG were genotyped in a European ancestry US discovery cohort comprising 152 SSc patients and 450 controls, with replication of our top signal in a European cohort (1031 SSc patients and 1014 controls from France). Clinical parameters and disease severity were analyzed to evaluate clinical associations with PPARG variants. Results: In the discovery cohort, a single PPARG intronic SNP (rs10865710) was associated with SSc (p = 0.010; odds ratio = 1.52 per C allele, 95% confidence interval 1.10-2.08). This association was replicated in the French validation cohort (p = 0.052; odds ratio = 1.16 per C allele, 95% confidence interval 1.00-1.35). Meta-analysis of both cohorts indicated stronger evidence for association (p = 0.002; odds ratio = 1.22 per C allele, 95% confidence interval 1.07-1.40). The rs10865710 C allele was also associated with pulmonary arterial hypertension in the French SSc cohort (p = 0.002; odds ratio = 2.33 per C allele, 95% confidence interval 1.34-4.03). Conclusions: A PPARG variant is associated with susceptibility to SSc, consistent with a role of PPAR-γ in the pathogenesis of SSc.

T helper 17 (T _H 17) cells are found in the periphery and synovium of patients with rheumatoid arthritis (RA); however, IL-17–targeted interventions have limited efficacy in established RA. Inflammation can induce T _H 17 cell transdifferentiation into IL-17–negative exT _H 17 cells, but the role of exT _H 17 cells in arthritis is unknown. We performed T _H 17 cell lineage tracing in the SKG mouse model of RA. In arthritic mice, synovial T _H 17 cells transdifferentiate into CD44 ⁺ exT _H 17 cells, which are more arthritogenic and sustain inflammation that is IL-17 independent. The exT _H 17 cell gene signature includes up-regulation of CD44 and sphingosine-1-phosphate receptor 4 (S1PR4) and correlates with the profile of human RA synovial CD4 ⁺ T cells. We demonstrate that cross-talk between T _H 17 cells and fibroblast-like synoviocytes (FLSs) via S1P promotes T _H 17-exT _H 17 cell conversion. CD44 is necessary for exT _H 17 cell–mediated arthritis. Our study suggests that FLS expansion during RA progression promotes T _H 17-exT _H 17 cell conversion. These results could potentially enable RA precision therapy.