Differentially expressed genes in systemic sclerosis: Towards predictive medicine with new molecular tools for clinicians

Systemic sclerosis, silica exposure and cellular therapies: The sand in the gears?

Systemic sclerosis (SSc) is a chronic orphan autoimmune disease with the highest mortality rate among rheumatic diseases. SSc-related interstitial-lung disease (ILD) remains among the leading causes of SSc-related mortality with still few therapeutic effective strategies. In patients with crystallin silica exposure, SSc is recognized as an occupational disease according to the French social security system (Table 25A of the general insurance regimen). Lympho-ablative or myeloablative immunosuppression followed by autologous hematopoietic stem-cell transplantation (aHSCT) is the only therapeutic approach with demonstrated efficacy, improved survival with disease modifying effects on SSc-fibrotic manifestations (skin disease and ILD) and quality of life. A documented past and/or present occupational silica exposure, with extensive exposure and/or silica-related ILD and/or with persistent silica content in the broncho-alveolar lavage fluid are contra-indications to aHSCT in SSc patients, due to the risk of silica-related malignancy or of SSc relapse. This article aims to discuss alternative options in SSc patients with a history of silica exposure, and how innovative cellular therapies (mesenchymal stromal cells, CAR cells) could represent new therapeutic options for these patients.

Emerging diagnostic and therapeutic challenges for skin fibrosis in systemic sclerosis

Systemic sclerosis (also called scleroderma, SSc) is a chronic autoimmune disorder characterized by excessive collagen deposition leading to skin fibrosis and various internal organ manifestations. The emergent diagnostics and therapeutic strategies for scleroderma focus on early detection and targeted interventions to improve patient outcomes and quality of life. Diagnostics for SSc have evolved significantly in recent years, driven by advancements in serological markers and imaging techniques. Autoantibody profiling, especially antinuclear antibodies (ANA) and specific scleroderma-associated autoantibodies, aids in identifying subsets of scleroderma and predicting disease progression. Furthermore, novel imaging modalities, such as high-frequency ultrasonography and optical coherence tomography, enable early detection of skin fibrosis and internal organ involvement, enhancing the diagnostic precision and allowing for tailored management. Therapeutic strategies for SSc are multifaceted, targeting immune dysregulation, vascular abnormalities, and fibrotic processes. Emerging biologic agents have shown promise in clinical trials, including monoclonal antibodies directed against key cytokines involved in fibrosis, such as transforming growth factor-β (TGF-β) and interleukin-6 (IL-6). Additionally, small-molecule inhibitors that disrupt fibrotic pathways, like tyrosine kinase inhibitors, have exhibited potential in limiting collagen deposition and preventing disease progression. Stem cell therapy, cell ablation and gene editing techniques hold great potential in regenerating damaged tissue and halting fibrotic processes. Early intervention remains crucial in managing SSc, as irreversible tissue damage often occurs in advanced stages. Novel diagnostic methods, such as biomarkers and gene expression profiling, are being explored to identify individuals at high risk for developing progressive severe disease and intervene proactively. Furthermore, patient-tailored therapeutic approaches, employing a combination of immunosuppressive agents and targeted anti-fibrotic therapies, are being investigated to improve treatment efficacy while minimizing adverse effects. The emergent diagnostics and therapeutic strategies in scleroderma are transforming the management of this challenging disease. Nevertheless, ongoing research and clinical trials are needed to optimize the efficacy and safety of these novel approaches in the complex and diverse spectrum of SSc manifestations.

Development and validation of a new diagnostic prediction model of ENHO and NOX4 for early diagnosis of systemic sclerosis

Objective

Systemic sclerosis (SSc) is a chronic autoimmune disease characterized by fibrosis. The challenge of early diagnosis, along with the lack of effective treatments for fibrosis, contribute to poor therapeutic outcomes and high mortality of SSc. Therefore, there is an urgent need to identify suitable biomarkers for early diagnosis of SSc.

Methods

Three skin gene expression datasets of SSc patients and healthy controls were downloaded from Gene Expression Omnibus (GEO) database (GSE130955, GSE58095, and GSE181549). GSE130955 (48 early diffuse cutaneous SSc and 33 controls) were utilized to screen differentially expressed genes (DEGs) between SSc and normal skin samples. Least absolute shrinkage and selection operator (LASSO) regression and support vector machine recursive feature elimination (SVM-RFE) were performed to identify diagnostic genes and construct a diagnostic prediction model. The results were further validated in GSE58095 (61 SSc and 36 controls) and GSE181549 (113 SSc and 44 controls) datasets. Receiver operating characteristic (ROC) curves were applied for assessing the level of diagnostic ability. Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) was used to verify the diagnostic genes in skin tissues of out cohort (10 SSc and 5 controls). Immune infiltration analysis were performed using CIBERSORT algorithm.

Results

A total of 200 DEGs were identified between SSc and normal skin samples. Functional enrichment analysis revealed that these DEGs may be involved in the pathogenesis of SSc, such as extracellular matrix remodeling, cell-cell interactions, and metabolism. Subsequently, two critical genes (ENHO and NOX4) were identified by LASSO and SVM-RFE. ENHO was found down-regulated while NOX4 was up-regulated in skin of SSc patients and their expression levels were validated by above three datasets and our cohort. Notably, these differential expressions were more pronounced in patients with diffuse cutaneous SSc than in those with limited cutaneous SSc. Next, we developed a novel diagnostic model for SSc using ENHO and NOX4, which demonstrated strong predictive power in above three cohorts and in our own cohort. Furthermore, immune infiltration analysis revealed dysregulated levels of various immune cell subtypes within early SSc skin specimens, and a negative correlation was observed between the levels of ENHO and Macrophages M1 and M2, while a positive correlation was observed between the levels of NOX4 and Macrophages M1 and M2.

Conclusion

This study identified ENHO and NOX4 as novel biomarkers that can be serve as a diagnostic prediction model for early detection of SSc and play a potential role in the pathogenesis of the disease.

Contribution of Telomere Length to Systemic Sclerosis Onset: A Mendelian Randomization Study

Although previous studies have suggested a relationship between telomere shortening and systemic sclerosis (SSc), the association between these two traits remains poorly understood. The objective of this study was to assess the causal relationship between telomere length in leukocytes (LTL) and SSc using the two-sample Mendelian randomization approach, with the genome-wide association study data for both LTL and SSc. The results of inverse-variance weighted regression (OR = 0.716 [95% CI 0.528-0.970], p = 0.031) and the Mendelian randomization pleiotropy residual sum and outlier method (OR = 0.716 [95% CI 0.563-0.911], p = 0.035) indicate an association between telomere length and SSc. Specifically, longer genetically predicted LTL is associated with a reduced risk of SSc. Sensitivity tests highlight the significant roles of the variants rs10936599 and rs2736100 annotated to the TERC and TERT genes, respectively. Our findings suggest an influence of telomere length in leukocytes on the development of SSc.

Skin Gene Expression Profiles in Systemic Sclerosis: From Clinical Stratification to Precision Medicine

Systemic sclerosis, also known as scleroderma or SSc, is a condition characterized by significant heterogeneity in clinical presentation, disease progression, and response to treatment. Consequently, the design of clinical trials to successfully identify effective therapeutic interventions poses a major challenge. Recent advancements in skin molecular profiling technologies and stratification techniques have enabled the identification of patient subgroups that may be relevant for personalized treatment approaches. This narrative review aims at providing an overview of the current status of skin gene expression analysis using computational biology approaches and highlights the benefits of stratifying patients upon their skin gene signatures. Such stratification has the potential to lead toward a precision medicine approach in the management of SSc.