Multiomic study of skin, peripheral blood, and serum: is serum proteome a reflection of disease process at the end-organ level in systemic sclerosis?

Immune Profiling of Patients with Systemic Sclerosis through Targeted Proteomic Analysis

High-throughput proteomic analysis could offer new insights into the pathogenesis of systemic sclerosis (SSc) and reveal non-invasive biomarkers for diagnosis and severity. This study aimed to assess the protein signature of patients with SSc compared to that of healthy volunteers, decipher various disease endotypes using circulating proteins, and determine the diagnostic performance of significantly expressed plasma analytes. We performed targeted proteomic profiling in a cohort of fifteen patients with SSc and eighteen controls using the Olink® (Olink Bioscience, Uppsala, Sweden)Target 96 Inflammation Panels. Seventeen upregulated proteins involved in angiogenesis, innate immunity, and co-stimulatory pathways discriminated between patients with SSc and healthy controls (HCs) and further classified them into two clusters, a low-inflammatory and a high-inflammatory endotype. Younger age, shorter disease duration, and lack of reflux esophagitis characterized patients in the low-inflammatory endotype. TNF, CXCL9, TNFRSF9, and CXCL10 positively correlated with disease progression, while the four-protein panel comprising TNF, CXCL9, CXCL10, and CX3CL1 showed high diagnostic performance. Collectively, this study identified a distinct inflammatory signature in patients with SSc that reflects a persistent T helper type 1 (Th 1) immune response irrespective of disease duration, while the multi-protein panel might improve early diagnosis in SSc.

Distinct molecular subtypes of systemic sclerosis and gene signature with diagnostic capability

Background

As Systemic Sclerosis (SSc) is a connective tissue ailment that impacts various bodily systems. The study aims to clarify the molecular subtypes of SSc, with the ultimate objective of establishing a diagnostic model that can inform clinical treatment decisions.

Methods

Five microarray datasets of SSc were retrieved from the GEO database. To eliminate batch effects, the combat algorithm was applied. Immune cell infiltration was evaluated using the xCell algorithm. The ConsensusClusterPlus algorithm was utilized to identify SSc subtypes. Limma was used to determine differential expression genes (DEGs). GSEA was used to determine pathway enrichment. A support vector machine (SVM), Random Forest(RF), Boruta and LASSO algorithm have been used to select the feature gene. Diagnostic models were developed using SVM, RF, and Logistic Regression (LR). A ROC curve was used to evaluate the performance of the model. The compound-gene relationship was obtained from the Comparative Toxicogenomics Database (CTD).

Results

The identification of three immune subtypes in SSc samples was based on the expression profiles of immune cells. The utilization of 19 key intersectional DEGs among subtypes facilitated the classification of SSc patients into three robust subtypes (gene_ClusterA-C). Gene_ClusterA exhibited significant enrichment of B cells, while gene_ClusterC showed significant enrichment of monocytes. Moderate activation of various immune cells was observed in gene_ClusterB. We identified 8 feature genes. The SVM model demonstrating superior diagnostic performance. Furthermore, correlation analysis revealed a robust association between the feature genes and immune cells. Eight pertinent compounds, namely methotrexate, resveratrol, paclitaxel, trichloroethylene, formaldehyde, silicon dioxide, benzene, and tetrachloroethylene, were identified from the CTD.

Conclusion

The present study has effectively devised an innovative molecular subtyping methodology for patients with SSc and a diagnostic model based on machine learning to aid in clinical treatment. The study has identified potential molecular targets for therapy, thereby offering novel perspectives for the treatment and investigation of SSc.

The Role of Autophagy and Apoptosis in Affected Skin and Lungs in Patients with Systemic Sclerosis

Systemic sclerosis (SSc) is a complex autoimmune inflammatory disorder with multiple organ involvement. Skin changes present the hallmark of SSc and coincide with poor prognosis. Interstitial lung diseases (ILD) are the most widely reported complications in SSc patients and the primary cause of death. It has been proposed that the processes of autophagy and apoptosis could play a significant role in the pathogenesis and clinical course of different autoimmune diseases, and accordingly in SSc. In this manuscript, we review the current knowledge of autophagy and apoptosis processes in the skin and lungs of patients with SSc. Profiling of markers involved in these processes in skin cells can be useful to recognize the stage of fibrosis and can be used in the clinical stratification of patients. Furthermore, the knowledge of the molecular mechanisms underlying these processes enables the repurposing of already known drugs and the development of new biological therapeutics that aim to reverse fibrosis by promoting apoptosis and regulate autophagy in personalized treatment approach. In SSc-ILD patients, the molecular signature of the lung tissues of each patient could be a distinctive criterion in order to establish the correct lung pattern, which directly impacts the course and prognosis of the disease. In this case, resolving the role of tissue-specific markers, which could be detected in the circulation using sensitive molecular methods, would be an important step toward development of non-invasive diagnostic procedures that enable early and precise diagnosis and preventing the high mortality of this rare disease.

Scleroderma Skin: How Is Treatment Best Guided by Data and Implemented in Clinical Practice?

As skin involvement is the hall mark of systemic sclerosis (SSc) and changes of skin involvement have shown to correlate with internal organ involvement, assessing the extend of skin involvement is key. Although the modified Rodnan skin score is a validated tool used to evaluate the skin in SSc, it has its drawbacks. Novel imagine methods are promising but should be further evaluated. As for molecule markers for skin progression there are conflicting data on the predictive significance of baseline SSc skin gene expression profiles, but immune cell type signature in SSc skin correlates with progression.

Distinct genome-wide DNA methylation and gene expression signatures in classical monocytes from African American patients with systemic sclerosis

BACKGROUND

Systemic sclerosis (SSc) is a multisystem autoimmune disorder that has an unclear etiology and disproportionately affects women and African Americans. Despite this, African Americans are dramatically underrepresented in SSc research. Additionally, monocytes show heightened activation in SSc and in African Americans relative to European Americans. In this study, we sought to investigate DNA methylation and gene expression patterns in classical monocytes in a health disparity population.

METHODS

Classical monocytes (CD14+ + CD16-) were FACS-isolated from 34 self-reported African American women. Samples from 12 SSc patients and 12 healthy controls were hybridized on MethylationEPIC BeadChip array, while RNA-seq was performed on 16 SSc patients and 18 healthy controls. Analyses were computed to identify differentially methylated CpGs (DMCs), differentially expressed genes (DEGs), and CpGs associated with changes in gene expression (eQTM analysis).

RESULTS

We observed modest DNA methylation and gene expression differences between cases and controls. The genes harboring the top DMCs, the top DEGs, as well as the top eQTM loci were enriched for metabolic processes. Genes involved in immune processes and pathways showed a weak upregulation in the transcriptomic analysis. While many genes were newly identified, several other have been previously reported as differentially methylated or expressed in different blood cells from patients with SSc, supporting for their potential dysregulation in SSc.

CONCLUSIONS

While contrasting with results found in other blood cell types in largely European-descent groups, the results of this study support that variation in DNA methylation and gene expression exists among different cell types and individuals of different genetic, clinical, social, and environmental backgrounds. This finding supports the importance of including diverse, well-characterized patients to understand the different roles of DNA methylation and gene expression variability in the dysregulation of classical monocytes in diverse populations, which might help explaining the health disparities.

Proteomic aptamer analysis reveals serum markers that characterize preclinical systemic sclerosis (SSc) patients at risk for progression toward definite SSc

BACKGROUND

The study of molecular mechanisms characterizing disease progression may be relevant to get insights into systemic sclerosis (SSc) pathogenesis and to intercept patients at very early stage. We aimed at investigating the proteomic profile of preclinical systemic sclerosis (PreSSc) via a discovery/validation two-step approach.

METHODS

SOMAcan aptamer-based analysis was performed on a serum sample of 13 PreSSc (discovery cohort) according to 2001 LeRoy and Medsger criteria (characterized solely by Raynaud phenomenon plus a positive nailfold capillaroscopy and SSc-specific antibodies without any other sign of definite disease) and 8 healthy controls (HCs) age, gender, and ethnicity matched. Prospective data were available up to 4±0.6 years to determine the progression to definite SSc according to the EULAR/ACR 2013 classification criteria. In proteins with relative fluorescence units (RFU) > |1.5|-fold vs HCs values, univariate analysis was conducted via bootstrap aggregating models to determine the predicting accuracy (progression vs non-progression) of categorized baseline protein values. Gene Ontologies (GO terms) and Reactome terms of significant proteins at the adjusted 0.05 threshold were explored. Significant proteins from the discovery cohort were finally validated via ELISAs in an independent validation cohort of 50 PreSSc with clinical prospective data up to 5 years. Time-to-event analysis for interval-censored data was used to evaluate disease progression.

RESULTS

In the discovery cohort, 286 out of 1306 proteins analyzed via SomaScan, were differentially expressed versus HCs. Ten proteins were significantly associated with disease progression; analysis through GO and Reactome showed differentially enriched pathways involving angiogenesis, endothelial cell chemotaxis, and endothelial cell chemotaxis to fibroblast growth factor (FGF). In the validation cohort, endostatin (HR=10.23, CI95=2.2-47.59, p=0.003) was strongly associated with disease progression, as well as bFGF (HR=0.84, CI95=0.709-0.996, p=0.045) and PAF-AHβ (HR=0.372, CI95=0.171-0.809, p=0.013) CONCLUSIONS: A distinct protein profile characterized PreSSc from HCs and proteins associated with hypoxia, vasculopathy, and fibrosis regulation are linked with the progression from preclinical to definite SSc. These proteins, in particular endostatin, can be regarded both as markers of severity and molecules with pathogenetic significance as well as therapeutic targets.

Type 1 interferon activation in systemic sclerosis: a biomarker, a target or the culprit

PURPOSE OF REVIEW

Activation of the type 1 interferon (T1 IFN) pathway has been implicated in the pathogenesis of systemic sclerosis (SSc) by an increasing number of studies, most of which share key findings with similar studies in systemic lupus erythematosus (SLE). Here we will focus on the evidence for T1 IFN activation and dysregulation in SSc, and the rationale behind targeting the pathway going forward.

RECENT FINDINGS

An increased expression and activation of T1 IFN-regulated genes has been shown to be present in a significant proportion of SSc patients. TI IFN activation markers have been found to predict and correlate with response to immunosuppressive treatment as well as severity of organ involvement. As inhibition of the IFN-α receptor has been proven to be effective in active SLE, benefit may be seen in targeting the IFN pathway in SSc.

SUMMARY

The role played by T1 IFN and its regulatory genes in SSc is becoming increasingly evident and strikingly similar to the role observed in SLE. This observation, together with the benefit of type 1 IFN targeting in SLE, supports the notion of a potential therapeutic benefit in targeting T1 IFN in SSc.

Integrated analysis of dermal blister fluid proteomics and genome-wide skin gene expression in systemic sclerosis: an observational study

Background

Skin fibrosis is a hallmark feature of systemic sclerosis. Skin biopsy transcriptomics and blister fluid proteomics give insight into the local environment of the skin. We have integrated these modalities with the aim of developing a surrogate for the modified Rodnan skin score (mRSS), using candidate genes and proteins from the skin and blister fluid as anchors to identify key analytes in the plasma.

Methods

In this single-centre, prospective observational study at the Royal Free Campus, University College London, London, UK, transcriptional and proteomic analyses of blood and skin were performed in a cohort of patients with systemic sclerosis (n=52) and healthy controls (n=16). Weighted gene co-expression network analysis was used to explore the association of skin transcriptomics data, clinical traits, and blister fluid proteomic results. Candidate hub analytes were identified as those present in both blister and skin gene sets (modules), and which correlated with plasma (module membership >0·7 and gene significance >0·6). Hub analytes were confirmed using RNA transcript data obtained from skin biopsy samples from patients with early diffuse cutaneous systemic sclerosis at 12 months.

Findings

We identified three modules in the skin, and two in blister fluid, which correlated with a diagnosis of early diffuse cutaneous systemic sclerosis. From these modules, 11 key hub analytes were identified, present in both skin and blister fluid modules, whose transcript and protein levels correlated with plasma protein concentrations, mRSS, and showed statistically significant correlation on repeat transcriptomic samples taken at 12 months. Multivariate analysis identified four plasma analytes as correlates of mRSS (COL4A1, COMP, SPON1, and TNC), which can be used to differentiate disease subtype.

Interpretation

This unbiased approach has identified potential biological candidates that might be drivers of local skin pathogenesis in systemic sclerosis. By focusing on measurable analytes in the plasma, we generated a promising composite plasma protein biomarker that could be used for assessment of skin severity, case stratification, and as a potential outcome measure for clinical trials and practice. Once fully validated, the biomarker score could replace a clinical score such as the mRSS, which carries substantial variability.

Funding

GlaxoSmithKline and UK Medical Research Council.

Peripheral blood gene expression profiling shows predictive significance for response to mycophenolate in systemic sclerosis-related interstitial lung disease

OBJECTIVES

To characterise the peripheral blood cell (PBC) gene expression changes ensuing from mycophenolate mofetil (MMF) or cyclophosphamide (CYC) treatment and to determine the predictive significance of baseline PBC transcript scores for response to immunosuppression in systemic sclerosis (SSc)-related interstitial lung disease (ILD).

METHODS

PBC RNA samples from baseline and 12-month visits, corresponding to the active treatment period of both arms in Scleroderma Lung Study II, were investigated by global RNA sequencing. Joint models were created to examine the predictive significance of baseline composite modular scores for the course of forced vital capacity (FVC) per cent predicted measurements from 3 to 12 months.

RESULTS

134 patients with SSc-ILD (CYC=69 and MMF=65) were investigated. CYC led to an upregulation of erythropoiesis, inflammation and myeloid lineage-related modules and a downregulation of lymphoid lineage-related modules. The modular changes resulting from MMF treatment were more modest and included a downregulation of plasmablast module. In the longitudinal analysis, none of the baseline transcript module scores showed predictive significance for FVC% course in the CYC arm. In contrast, in the MMF arm, higher baseline lymphoid lineage modules predicted better subsequent FVC% course, while higher baseline myeloid lineage and inflammation modules predicted worse subsequent FVC% course.

CONCLUSION

Consistent with the primary mechanism of action of MMF on lymphocytes, patients with SSc-ILD with higher baseline lymphoid module scores had better FVC% course, while those with higher myeloid cell lineage activation score had poorer FVC% course on MMF.

Cellular and Molecular Diversity in Scleroderma

With the increasing armamentarium of high-throughput tools available at manageable cost, it is attractive and informative to determine the molecular underpinnings of patient heterogeneity in systemic sclerosis (SSc). Given the highly variable clinical outcomes of patients labelled with the same diagnosis, unravelling the cellular and molecular basis of disease heterogeneity will be crucial to predicting disease risk, stratifying management and ultimately informing a patient-centered precision medicine approach. Herein, we summarise the findings of the past several years in the fields of genomics, transcriptomics, and proteomics that contribute to unraveling the cellular and molecular heterogeneity of SSc. Expansion of these findings and their routine integration with quantitative analysis of histopathology and imaging studies into clinical care promise to inform a scientifically driven patient-centred personalized medicine approach to SSc in the near future.