Early diagnosis of systemic sclerosis, where do we stand today?

The association between the neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, and monocyte-to-lymphocyte ratio and systemic sclerosis and its complications: a systematic review and meta-analysis

Introduction

The identification of new, easily measurable biomarkers might assist clinicians in diagnosing and managing systemic sclerosis (SSc). Although the full blood count is routinely assessed in the evaluation of SSc, the diagnostic utility of specific cell-derived inflammatory indices, i.e., neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and monocyte-to-lymphocyte ratio (MLR), has not been critically appraised in this patient group.

Methods

We conducted a systematic review and meta-analysis of studies investigating the NLR, PLR, and MLR, in SSc patients and healthy controls and in SSc patients with and without relevant complications. PubMed, Scopus, and Web of Science were searched from inception to 23 February 2024. Risk of bias and certainty of evidence were assessed using validated tools.

Results

In 10 eligible studies, compared to controls, patients with SSc had significantly higher NLR (standard mean difference, SMD=0.68, 95% CI 0.46 to 0.91, p<0.001; I2 = 74.5%, p<0.001), and PLR values (SMD=0.52, 95% CI 0.21 to 0.83, p=0.001; I2 = 77.0%, p=0.005), and a trend towards higher MLR values (SMD=0.60, 95% CI -0.04 to 1.23, p=0.066; I2 = 94.1%, p<0.001). When compared to SSc patients without complications, the NLR was significantly higher in SSc with interstitial lung disease (ILD, SMD=0.31, 95% CI 0.15 to 0.46, p<0.001; I2 = 43.9%, p=0.11), pulmonary arterial hypertension (PAH, SMD=1.59, 95% CI 0.04 to 3.1, p=0.045; I2 = 87.6%, p<0.001), and digital ulcers (DU, SMD=0.43, 95% CI 0.13 to 0.74, p=0.006; I2 = 0.0%, p=0.49). The PLR was significantly higher in SSc patients with ILD (SMD=0.42, 95% CI 0.25 to 0.59, p<0.001; I2 = 24.8%, p=0.26). The MLR was significantly higher in SSc patients with PAH (SMD=0.63, 95% CI 0.17 to 1.08, p=0.007; I2 = 66.0%, p=0.086), and there was a trend towards a higher MLR in SSc patients with ILD (SMD=0.60, 95% CI -0.04 to 1.23, p=0.066; I2 = 94.1%, p<0.001).

Discussion

Pending the results of appropriately designed prospective studies, the results of this systematic review and meta-analysis suggest that blood cell-derived indices of inflammation, particularly the NLR and PLR, may be useful in the diagnosis of SSc and specific complications.

Systematic review registration

https://www.crd.york.ac.uk/PROSPERO/, identifier CRD42024520040.

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.

Predicting the Progression of Very Early Systemic Sclerosis: Current Insights

Systemic sclerosis (SSc) is a complex autoimmune connective tissue disease with distinct pathological hallmarks (ie, inflammation, vasculopathy, fibrosis) that may predominate at different stages in the disease course with varying severity. Initial efforts to classify patients with SSc identified a subset of patients with very early SSc. These patients possessed signs of SSc (eg, Raynaud phenomenon, SSc specific autoantibodies and/or nailfold capillary abnormalities) without fulfilling complete SSc classification criteria. Recognizing the inherent value in early diagnosis and intervention in SSc, researchers have endeavored to identify risk factors for progression from very early SSc to definite SSc. The present review summarizes the clinical phenotype of patients with very early and early SSc. Through a scoping review of recent literature, this review also describes risk factors for progression to definite SSc with a focus on the specific clinical features that arise early in the SSc disease course (eg, diffuse cutaneous sclerosis, interstitial lung disease, esophageal dysfunction, renal crisis, cardiac involvement). In addition to clinical risk factors, this review provides evidence for how biological data (ie, serological, genomic, proteomic profiles, skin bioengineering methods) can be integrated into risk assessment models in the future. Furthering our understanding of biological features of very early SSc will undoubtedly provide novel insights into SSc pathogenesis and may illuminate new therapeutic targets to prevent progression of SSc.