A genomic meta-analysis of clinical variables and their association with intrinsic molecular subsets in systemic sclerosis.

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.

Machine learning integration of scleroderma histology and gene expression identifies fibroblast polarisation as a hallmark of clinical severity and improvement.

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.

Machine learning predicts stem cell transplant response in severe scleroderma.

OBJECTIVE: The Scleroderma: Cyclophosphamide or Transplantation (SCOT) trial demonstrated clinical benefit of haematopoietic stem cell transplant (HSCT) compared with cyclophosphamide (CYC). We mapped PBC (peripheral blood cell) samples from the SCOT clinical trial to scleroderma intrinsic subsets and tested the hypothesis that they predict long-term response to HSCT. METHODS: We analysed gene expression from PBCs of SCOT participants to identify differential treatment response. PBC gene expression data were generated from 63 SCOT participants at baseline and follow-up timepoints. Participants who completed treatment protocol were stratified by intrinsic gene expression subsets at baseline, evaluated for event-free survival (EFS) and analysed for differentially expressed genes (DEGs). RESULTS: Participants from the fibroproliferative subset on HSCT experienced significant improvement in EFS compared with fibroproliferative participants on CYC (p=0.0091). In contrast, EFS did not significantly differ between CYC and HSCT arms for the participants from the normal-like subset (p=0.77) or the inflammatory subset (p=0.1). At each timepoint, we observed considerably more DEGs in HSCT arm compared with CYC arm with HSCT arm showing significant changes in immune response pathways. CONCLUSIONS: Participants from the fibroproliferative subset showed the most significant long-term benefit from HSCT compared with CYC. This study suggests that intrinsic subset stratification of patients may be used to identify patients with SSc who receive significant benefit from HSCT.

Systems level analysis of systemic sclerosis shows a network of immune and profibrotic pathways connected with genetic polymorphisms.

Systemic sclerosis (SSc) is a rare systemic autoimmune disease characterized by skin and organ fibrosis. The pathogenesis of SSc and its progression are poorly understood. The SSc intrinsic gene expression subsets (inflammatory, fibroproliferative, normal-like, and limited) are observed in multiple clinical cohorts of patients with SSc. Analysis of longitudinal skin biopsies suggests that a patient's subset assignment is stable over 6-12 months. Genetically, SSc is multi-factorial with many genetic risk loci for SSc generally and for specific clinical manifestations. Here we identify the genes consistently associated with the intrinsic subsets across three independent cohorts, show the relationship between these genes using a gene-gene interaction network, and place the genetic risk loci in the context of the intrinsic subsets. To identify gene expression modules common to three independent datasets from three different clinical centers, we developed a consensus clustering procedure based on mutual information of partitions, an information theory concept, and performed a meta-analysis of these genome-wide gene expression datasets. We created a gene-gene interaction network of the conserved molecular features across the intrinsic subsets and analyzed their connections with SSc-associated genetic polymorphisms. The network is composed of distinct, but interconnected, components related to interferon activation, M2 macrophages, adaptive immunity, extracellular matrix remodeling, and cell proliferation. The network shows extensive connections between the inflammatory- and fibroproliferative-specific genes. The network also shows connections between these subset-specific genes and 30 SSc-associated polymorphic genes including STAT4, BLK, IRF7, NOTCH4, PLAUR, CSK, IRAK1, and several human leukocyte antigen (HLA) genes. Our analyses suggest that the gene expression changes underlying the SSc subsets may be long-lived, but mechanistically interconnected and related to a patients underlying genetic risk.

Increased expression of endoplasmic reticulum stress and unfolded protein response genes in peripheral blood mononuclear cells from patients with limited cutaneous systemic sclerosis and pulmonary arterial hypertension.

OBJECTIVE: Pulmonary arterial hypertension (PAH), a common complication of limited cutaneous systemic sclerosis (lcSSc), is associated with alterations of markers of inflammation and vascular damage in peripheral blood mononuclear cells (PBMCs). Endoplasmic reticulum (ER) stress and the unfolded protein response (UPR) have been implicated in autoimmune and inflammatory diseases. The goal of this study was to assess whether markers of ER stress and the UPR are present in PBMCs from lcSSc patients with PAH. METHODS: PBMCs were purified from 36 healthy controls, 32 lcSSc patients with PAH, and 34 lcSSc patients without PAH. Gene expression in healthy control PBMCs stimulated with thapsigargin was analyzed by DNA microarray. Genes were validated by quantitative real-time reverse transcription-polymerase chain reaction in PBMCs from healthy controls and lcSSc patients. RESULTS: Several ER stress/UPR genes, including BiP, activating transcription factor 4 (ATF-4), ATF-6, and a spliced form of X-box binding protein 1, were up-regulated in PBMCs from lcSSc patients, with the highest levels in patients with PAH. Thapsigargin up-regulated heat-shock proteins (HSPs) and interferon (IFN)-regulated genes in PBMCs from healthy controls. Selected HSP genes (particularly DnaJB1) and IFN-related genes were also found at significantly elevated levels in PBMCs from lcSSc patients, while IFN regulatory factor 4 expression was significantly decreased. There was a positive correlation between DnaJB1 and severity of PAH (measured by pulmonary artery pressure) (r = 0.56, P < 0.05) and between ER stress markers and interleukin-6 levels (r = 0.53, P < 0.0001) in PBMCs from lcSSc patients. CONCLUSION: This study demonstrates an association between select ER stress/UPR markers and lcSSc with PAH, suggesting that ER stress and the UPR may contribute to the altered function of circulating immune cells in lcSSc.

Single-cell epigenomic dysregulation of Systemic Sclerosis fibroblasts via CREB1/EGR1 axis in self-assembled human skin equivalents.

Systemic sclerosis (SSc) is an autoimmune disease characterized by skin fibrosis, internal organ involvement and vascular dropout. We previously developed and phenotypically characterized an in vitro 3D skin-like tissue model of SSc, and now analyze the transcriptomic (scRNA-seq) and epigenetic (scATAC-seq) characteristics of this model at single-cell resolution. SSc 3D skin-like tissues were fabricated using autologous fibroblasts, macrophages, and plasma from SSc patients or healthy control (HC) donors. SSc tissues displayed increased dermal thickness and contractility, as well as increased α-SMA staining. Single-cell transcriptomic and epigenomic analyses identified keratinocytes, macrophages, and five populations of fibroblasts (labeled FB1 - 5). Notably, FB1 APOE-expressing fibroblasts were 12-fold enriched in SSc tissues and were characterized by high EGR1 motif accessibility. Pseudotime analysis suggests that FB1 fibroblasts differentiate from a TGF-ß1-responsive fibroblast population and ligand-receptor analysis indicates that the FB1 fibroblasts are active in macrophage crosstalk via soluble ligands including FGF2 and APP. These findings provide characterization of the 3D skin-like model at single cell resolution and establish that it recapitulates subsets of fibroblasts and macrophage phenotypes observed in skin biopsies.

Clinical and Molecular Findings After Autologous Stem Cell Transplantation or Cyclophosphamide for Scleroderma: Handling Missing Longitudinal Data.

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.

Post-epidemic eosinophilia-myalgia syndrome associated with L-tryptophan.

Eosinophilia-myalgia syndrome (EMS) is characterized by subacute onset of myalgias and peripheral eosinophilia, followed by chronic neuropathy and skin induration. An epidemic of EMS in 1989 was linked to consumption of L-tryptophan that had originated from a single source. Following the ban by the Food and Drug Administration (FDA) on the sale of L-tryptophan, the incidence of EMS declined rapidly. Moreover, no new cases have been described since the FDA ban was lifted in 2005. We report the clinical, histopathologic, and immunogenetic features of a new case of L-tryptophan-associated EMS, along with evidence of activated transforming growth factor ß and interleukin-4 signaling in the lesional skin.

Machine-learning classification identifies patients with early systemic sclerosis as abatacept responders via CD28 pathway modulation.

Here, the efficacy of abatacept in patients with early diffuse systemic sclerosis (dcSSc) was analyzed to test the hypothesis that patients in the inflammatory intrinsic subset would show the most significant clinical improvement. Eighty-four participants with dcSSc were randomized to receive abatacept or placebo for 12 months. RNA-Seq was performed on 233 skin paired biopsies at baseline and at 3 and 6 months. Improvement was defined as a 5-point or more than 20% change in modified Rodnan skin score (mRSS) between baseline and 12 months. Samples were assigned to intrinsic gene expression subsets (inflammatory, fibroproliferative, or normal-like subsets). In the abatacept arm, change in mRSS was most pronounced for the inflammatory and normal-like subsets relative to the placebo subset. Gene expression for participants on placebo remained in the original molecular subset, whereas inflammatory participants treated with abatacept had gene expression that moved toward the normal-like subset. The Costimulation of the CD28 Family Reactome Pathway decreased in patients who improved on abatacept and was specific to the inflammatory subset. Patients in the inflammatory subset had elevation of the Costimulation of the CD28 Family pathway at baseline relative to that of participants in the fibroproliferative and normal-like subsets. There was a correlation between improved ΔmRSS and baseline expression of the Costimulation of the CD28 Family pathway. This study provides an example of precision medicine in systemic sclerosis clinical trials.

Bacterial growth kinetics in ACD-A apheresis platelets: comparison of plasma and PAS III storage.

BACKGROUND: Our objective was to determine the growth kinetics of bacteria in leukoreduced apheresis platelets (LR-AP) in a platelet (PLT) additive solution (PAS; InterSol, Fenwal, Inc.) compared to LR-AP stored in plasma. STUDY DESIGN AND METHODS: Hyperconcentrated, double-dose LR-AP were collected from healthy donors with a separator (AMICUS, Fenwal, Inc.). LR-AP were evenly divided, InterSol was added to half (65% InterSol:35% plasma [PAS]), and PLTs in autologous plasma were used for a paired control (PL). Bacteria were inoculated into each LR-AP PAS/PL pair (0.5-1.6 colony-forming units [CFUs]/mL), and bacterial growth was followed for up to 7 days. Time to the end of the lag phase, doubling times, maximum concentration (conc-max), and time to maximum concentration (time-max) were estimated. RESULTS: Streptococcus viridans did not grow to detectable levels in either PAS or PL units. The other bacteria had no significant overall difference in the conc-max (p = 0.47) or time-max (p = 0.7) between PL and PAS LR-AP; PL had a 0.14 hours faster doubling rate (p = 0.023); and PAS had a 4.7 hours shorter lag time (p = 0.016). CONCLUSION: We observed that five index organisms will grow in LR-AP stored in a 35%:65% ratio of plasma to InterSol where initial bacterial concentrations are 0.5 to 1.6 CFUs/mL. The more rapid initiation of log-phase growth for bacteria within a PAS storage environment resulted in a bacterial concentration up to 4 logs higher in the PAS units compared to the plasma units at 24 hours, but with no difference in the conc-max. This may present an early bacterial detection advantage for PAS-stored PLTs.

Mast Cell Activation in the Systemic Sclerosis Esophagus.

INTRODUCTION: Previously, we discovered similar esophageal gene expression patterns in patients with systemic sclerosis (SSc) and eosinophilic esophagitis (EoE) where eosinophil/mast cell-targeted therapies are beneficial. Because SSc and EoE patients experience similar esophageal symptoms, we hypothesized that eosinophil/mast cell-directed therapy may potentially benefit SSc patients. Herein, we determine the association between esophageal mast cell quantities, gene expression and clinical parameters in order to identify SSc patients who may benefit from eosinophil/mast cell-directed therapy. METHODS: Esophageal biopsies from SSc patients and healthy participants were stained for tryptase, a mast cell marker, and associations with relevant clinical parameters including 24h esophageal pH testing were assessed. Intra-epithelial mast cell density was quantified by semi-automated microscopy. Microarray data were utilized for functional and gene set enrichment analyses and to identify intrinsic subset (IS) assignment, an SSc molecular classification system that includes inflammatory, proliferative, limited and normal-like subsets. RESULTS: Esophageal biopsies from 40 SSc patients (39 receiving proton pump inhibition) and eleven healthy participants were studied. Mast cell numbers in both the upper esophagus (rs = 0.638, p = 0.004) and the entire (upper + lower) esophagus (rs = 0.562, p = 0.019) significantly correlated with acid exposure time percentage. The inflammatory, fibroproliferative, and normal-like ISs originally defined in skin biopsies were identified in esophageal biopsies. Although esophageal mast cell numbers in SSc patients and healthy participants were similar, gene expression for mast cell-related pathways showed significant upregulation in the inflammatory IS of SSc patients compared to patients classified as proliferative or normal-like. DISCUSSION: Esophageal mast cell numbers are heterogeneous in SSc patients and may correlate with acid exposure. Patients with inflammatory IS profiles in the esophagus demonstrate more tryptase staining. Mast cell targeted therapy may be a useful therapeutic approach in SSc patients belonging to the inflammatory IS, but additional studies are warranted.

Regulator combinations identify systemic sclerosis patients with more severe disease.

Systemic sclerosis (SSc) is a heterogeneous autoimmune disorder that results in skin fibrosis, autoantibody production, and internal organ dysfunction. We previously identified 4 "intrinsic" subsets of SSc based upon skin gene expression that are found across organ systems. Gene expression regulators that underlie the SSc-intrinsic subsets, or are associated with clinical covariates, have not been systematically characterized. Here, we present a computational framework to calculate the activity scores of gene expression regulators and identify their associations with SSc clinical outcomes. We found that regulator activity scores can reproduce the intrinsic molecular subsets, with distinct sets of regulators identified for inflammatory, fibroproliferative, limited, and normal-like samples. Regulators most highly correlated with modified Rodnan skin score (MRSS) also varied by intrinsic subset. We identified subgroups of patients with fibroproliferative and inflammatory SSc with more severe pathophenotypes, such as higher MRSS and increased likelihood of interstitial lung disease (ILD). Using an independent cohort, we show that the group with more severe ILD was more likely to show forced vital capacity decline over a period of 36-54 months. Our results demonstrate an association among the activation of regulators, gene expression subsets, and clinical variables that can identify patients with SSc with more severe disease.

Safety and Efficacy of Lenabasum in a Phase II, Randomized, Placebo-Controlled Trial in Adults With Systemic Sclerosis.

OBJECTIVE: To assess the safety and efficacy of lenabasum in diffuse cutaneous systemic sclerosis (dcSSc). METHODS: A randomized, double-blind, placebo-controlled, phase II study was conducted at 9 SSc clinics in the US. Adults with dcSSc of ≤6 years' duration who were receiving stable standard-of-care treatment were randomized to receive lenabasum (n = 27) or placebo (n = 15). Lenabasum doses were 5 mg once daily, 20 mg once daily, or 20 mg twice daily for 4 weeks, followed by 20 mg twice daily for 8 weeks. Safety and efficacy were assessed at weeks 4, 8, 12, and 16. RESULTS: Adverse events (AEs) occurred in 63% of the lenabasum group and 60% of the placebo group, with no serious AEs related to lenabasum. Compared to placebo, lenabasum treatment was associated with greater improvement in the American College of Rheumatology Combined Response Index in diffuse cutaneous Systemic Sclerosis (CRISS) score and other efficacy outcome measures that assessed overall disease, skin involvement, and patient-reported function. The median CRISS score increased in the lenabasum group during the study, reaching 0.33, versus 0.00 in the placebo group, at week 16 (P = 0.07 by 2-sided mixed-effects model repeated-measures analysis). Gene expression in inflammation and fibrosis pathways was reduced, and inflammation and fibrosis were improved on histologic evaluation of skin biopsy specimens, in the lenabasum group compared to the placebo group (all P ≤ 0.05). CONCLUSION: Despite a short trial duration in a small number of patients in this phase II study in dcSSc, our findings indicate that lenabasum improves efficacy outcomes and underlying disease pathology with a favorable safety profile.

Abatacept in Early Diffuse Cutaneous Systemic Sclerosis: Results of a Phase II Investigator-Initiated, Multicenter, Double-Blind, Randomized, Placebo-Controlled Trial.

OBJECTIVE: T cells play a key role in the pathogenesis of early systemic sclerosis. This study was undertaken to assess the safety and efficacy of abatacept in patients with diffuse cutaneous systemic sclerosis (dcSSc). METHODS: In this 12-month, randomized, double-blind, placebo-controlled trial, participants were randomized 1:1 to receive either subcutaneous abatacept 125 mg or matching placebo, stratified by duration of dcSSc. Escape therapy was allowed at 6 months for worsening disease. The coprimary end points were change in the modified Rodnan skin thickness score (MRSS) compared to baseline and safety over 12 months. Differences in longitudinal outcomes were assessed according to treatment using linear mixed models, with outcomes censored after initiation of escape therapy. Skin tissue obtained from participants at baseline was classified into intrinsic gene expression subsets. RESULTS: Among 88 participants, the adjusted mean change in the MRSS at 12 months was -6.24 units for those receiving abatacept and -4.49 units for those receiving placebo, with an adjusted mean treatment difference of -1.75 units (P = 0.28). Outcomes for 2 secondary measures (Health Assessment Questionnaire disability index and a composite measure) were clinically and statistically significantly better with abatacept. The proportion of subjects in whom escape therapy was needed was higher in the placebo group relative to the abatacept group (36% versus 16%). In the inflammatory and normal-like skin gene expression subsets, decline in the MRSS over 12 months was clinically and significantly greater in the abatacept group versus the placebo group (P < 0.001 and P = 0.03, respectively). In the abatacept group, adverse events occurred in 35 participants versus 40 participants in the placebo group, including 2 deaths and 1 death, respectively. CONCLUSION: In this phase II trial, abatacept was well-tolerated, but change in the MRSS was not statistically significant. Secondary outcome measures, including gene expression subsets, showed evidence in support of abatacept. These data should be confirmed in a phase III trial.

A Machine Learning Classifier for Assigning Individual Patients With Systemic Sclerosis to Intrinsic Molecular Subsets.

OBJECTIVE: High-throughput gene expression profiling of tissue samples from patients with systemic sclerosis (SSc) has identified 4 "intrinsic" gene expression subsets: inflammatory, fibroproliferative, normal-like, and limited. Prior methods required agglomerative clustering of many samples. In order to classify individual patients in clinical trials or for diagnostic purposes, supervised methods that can assign single samples to molecular subsets are required. We undertook this study to introduce a novel machine learning classifier as a robust accurate intrinsic subset predictor. METHODS: Three independent gene expression cohorts were curated and merged to create a data set covering 297 skin biopsy samples from 102 unique patients and controls, which was used to train a machine learning algorithm. We performed external validation using 3 independent SSc cohorts, including a gene expression data set generated by an independent laboratory on a different microarray platform. In total, 413 skin biopsy samples from 213 individuals were analyzed in the training and testing cohorts. RESULTS: Repeated cross-fold validation identified consistent and discriminative markers using multinomial elastic net, performing with an average classification accuracy of 87.1% with high sensitivity and specificity. In external validation, the classifier achieved an average accuracy of 85.4%. Reanalyzing data from a previous study, we identified subsets of patients that represent the canonical inflammatory, fibroproliferative, and normal-like subsets. CONCLUSION: We developed a highly accurate classifier for SSc molecular subsets for individual patient samples. The method can be used in SSc clinical trials to identify an intrinsic subset on individual samples. Our method provides a robust data-driven approach to aid clinical decision-making and interpretation of heterogeneous molecular information in SSc patients.

Microbiome dysbiosis is associated with disease duration and increased inflammatory gene expression in systemic sclerosis skin.

BACKGROUND: Infectious agents have long been postulated to be disease triggers for systemic sclerosis (SSc), but a definitive link has not been found. Metagenomic analyses of high-throughput data allows for the unbiased identification of potential microbiome pathogens in skin biopsies of SSc patients and allows insight into the relationship with host gene expression. METHODS: We examined skin biopsies from a diverse cohort of 23 SSc patients (including lesional forearm and non-lesional back samples) by RNA-seq. Metagenomic filtering and annotation was performed using the Integrated Metagenomic Sequencing Analysis (IMSA). Associations between microbiome composition and gene expression were analyzed using single-sample gene set enrichment analysis (ssGSEA). RESULTS: We find the skin of SSc patients exhibits substantial changes in microbial composition relative to controls, characterized by sharp decreases in lipophilic taxa, such as Propionibacterium, combined with increases in a wide range of gram-negative taxa, including Burkholderia, Citrobacter, and Vibrio. CONCLUSIONS: Microbiome dysbiosis is associated with disease duration and increased inflammatory gene expression. These data provide a comprehensive portrait of the SSc skin microbiome and its association with local gene expression, which mirrors the molecular changes in lesional skin.

Transmission of pathogenic bacterial organisms in the anesthesia work area.

BACKGROUND: The current prevalence of hospital-acquired infections and evolving amplification of bacterial resistance are major public health concerns. A heightened awareness of intraoperative transmission of potentially pathogenic bacterial organisms may lead to implementation of effective preventative measures. METHODS: Sixty-one operative suites were randomly selected for analysis. Sterile intravenous stopcock sets and two sites on the anesthesia machine were decontaminated and cultured aseptically at baseline and at case completion. The primary outcome was the presence of a positive culture on the previously sterile patient stopcock set. Secondary outcomes were the number of colonies per surface area sampled on the anesthesia machine, species identification, and antibiotic susceptibility of isolated organisms. RESULTS: Bacterial contamination of the anesthesia work area increased significantly at the case conclusion, with a mean difference of 115 colonies per surface area sampled (95% confidence interval [CI], 62-169; P < 0.001). Transmission of bacterial organisms, including vancomycin-resistant enterococcus, to intravenous stopcock sets occurred in 32% (95% CI, 20.6-44.9%) of cases. Highly contaminated work areas increased the odds of stopcock contamination by 4.7 (95% CI, 1.42-15.42; P = 0.011). Contaminated intravenous tubing was associated with a trend toward increased nosocomial infection rates (odds ratio, 3.08; 95% CI, 0.56-17.5; P = 0.11) and with an increase in mortality (95% CI odds ratio, 1.11-infinity; P = 0.0395). CONCLUSION: Potentially pathogenic, multidrug-resistant bacterial organisms are transmitted during the practice of general anesthesia to both the anesthesia work area and intravenous stopcock sets. Implementation of infection control measures in this area may help to reduce both the evolving problem of increasing bacterial resistance and the development of life-threatening infectious complications.

Belimumab for the Treatment of Early Diffuse Systemic Sclerosis: Results of a Randomized, Double-Blind, Placebo-Controlled, Pilot Trial.

OBJECTIVE: To assess the safety and efficacy of treatment with belimumab in patients with early diffuse cutaneous systemic sclerosis (dcSSc) treated with background mycophenolate mofetil (MMF). METHODS: In this 52-week, investigator-initiated, single-center, double-blind, placebo-controlled, pilot study, 20 patients with dcSSc recently started on MMF were randomized 1:1 to additionally receive belimumab at 10 mg/kg intravenously or placebo. We assessed safety, efficacy, and differential gene expression. RESULTS: In the belimumab group, the median modified Rodnan skin thickness score (MRSS) decreased from 27 (interquartile range [IQR] 26.5, 31) to 18 (IQR 11, 23) (P = 0.039). In the placebo group, the median MRSS decreased from 28 (IQR 22, 28) to 21 (IQR 14, 25) (P = 0.023). The median change in MRSS was -10 (IQR -13, -9) in the belimumab group and -3.0 (IQR -15, -1) in the placebo group (P = 0.411). There were no significant differences between the groups in the number of adverse events (AEs). A significant decrease in expression of B cell signaling and profibrotic genes and pathways was observed in patients with improved MRSS in the belimumab group but not in the placebo group. CONCLUSION: Patients in both treatment groups experienced significant improvements in MRSS. The median difference was greater in the belimumab group but did not achieve statistical significance in this small pilot study. AEs were similar between the groups. Changes in gene expression were consistent with mechanism of action and showed that clinical response to treatment with belimumab is associated with a significant decrease in profibrotic genes and pathways. Additional studies are needed to determine the role of belimumab in the treatment of dcSSc.

Mycophenolate Mofetil Treatment of Systemic Sclerosis Reduces Myeloid Cell Numbers and Attenuates the Inflammatory Gene Signature in Skin.

Fewer than half of patients with systemic sclerosis demonstrate modified Rodnan skin score improvement during mycophenolate mofetil (MMF) treatment. To understand the molecular basis for this observation, we extended our prior studies and characterized molecular and cellular changes in skin biopsies from subjects with systemic sclerosis treated with MMF. Eleven subjects completed ≥24 months of MMF therapy. Two distinct skin gene expression trajectories were observed across six of these subjects. Three of the six subjects showed attenuation of the inflammatory signature by 24 months, paralleling reductions in CCL2 mRNA expression in skin and reduced numbers of macrophages and myeloid dendritic cells in skin biopsies. MMF cessation at 24 months resulted in an increased inflammatory score, increased CCL2 mRNA and protein levels, modified Rodnan skin score rebound, and increased numbers of skin myeloid cells in these subjects. In contrast, three other subjects remained on MMF >24 months and showed a persistent decrease in inflammatory score, decreasing or stable modified Rodnan skin score, CCL2 mRNA reductions, sera CCL2 protein levels trending downward, reduction in monocyte migration, and no increase in skin myeloid cell numbers. These data summarize molecular changes during MMF therapy that suggest reduction of innate immune cell numbers, possibly by attenuating expression of chemokines, including CCL2.

A novel multi-network approach reveals tissue-specific cellular modulators of fibrosis in systemic sclerosis.

BACKGROUND: Systemic sclerosis (SSc) is a multi-organ autoimmune disease characterized by skin fibrosis. Internal organ involvement is heterogeneous. It is unknown whether disease mechanisms are common across all involved affected tissues or if each manifestation has a distinct underlying pathology. METHODS: We used consensus clustering to compare gene expression profiles of biopsies from four SSc-affected tissues (skin, lung, esophagus, and peripheral blood) from patients with SSc, and the related conditions pulmonary fibrosis (PF) and pulmonary arterial hypertension, and derived a consensus disease-associate signature across all tissues. We used this signature to query tissue-specific functional genomic networks. We performed novel network analyses to contrast the skin and lung microenvironments and to assess the functional role of the inflammatory and fibrotic genes in each organ. Lastly, we tested the expression of macrophage activation state-associated gene sets for enrichment in skin and lung using a Wilcoxon rank sum test. RESULTS: We identified a common pathogenic gene expression signature-an immune-fibrotic axis-indicative of pro-fibrotic macrophages (MØs) in multiple tissues (skin, lung, esophagus, and peripheral blood mononuclear cells) affected by SSc. While the co-expression of these genes is common to all tissues, the functional consequences of this upregulation differ by organ. We used this disease-associated signature to query tissue-specific functional genomic networks to identify common and tissue-specific pathologies of SSc and related conditions. In contrast to skin, in the lung-specific functional network we identify a distinct lung-resident MØ signature associated with lipid stimulation and alternative activation. In keeping with our network results, we find distinct MØ alternative activation transcriptional programs in SSc-associated PF lung and in the skin of patients with an "inflammatory" SSc gene expression signature. CONCLUSIONS: Our results suggest that the innate immune system is central to SSc disease processes but that subtle distinctions exist between tissues. Our approach provides a framework for examining molecular signatures of disease in fibrosis and autoimmune diseases and for leveraging publicly available data to understand common and tissue-specific disease processes in complex human diseases.