Systemic sclerosis - the dermatological perspective

Vitiligo and systemic sclerosis: Are they associated?- Lessons from a population-based study

BACKGROUND

The epidemiological relationship of vitiligo with systemic sclerosis (SSc) remains to be precisely evaluated.

OBJECTIVE

To investigate the bidirectional association between vitiligo and SSc.

METHODS

A population-based study was carried out to compare vitiligo patients (n = 20,851) with age-, sex- and ethnicity-matched control subjects (n = 102,475) regarding the incidence of new-onset and the prevalence of preexisting SSc. Adjusted hazard ratios (HRs) and adjusted odds ratios (ORs) were calculated by the Cox regression and logistic regression, respectively.

RESULTS

The incidence rate of new-onset SSc was calculated at 2.4 (95% CI, 1.6-3.4) and 0.4 (95% CI, 0.3-0.6) cases per 10,000 person-years among patients with vitiligo and controls, respectively. Patients with vitiligo had an increased risk of SSc (fully adjusted HR, 5.37; 95% CI, 3.03-9.54; p < 0.001). Correspondingly, a history of SSc predicted elevated odds of developing vitiligo (fully adjusted OR, 2.09; 95% CI, 1.23-3.55; p = 0.006). Relative to other patients with vitiligo, those with vitiligo and comorbid SSc were older and had a higher prevalence of ischaemic heart disease, hyperlipidaemia, and hypertension.

CONCLUSIONS

A robust bidirectional association exists between vitiligo and SSc. This knowledge is valuable for physicians managing patients with both conditions. Patients with vitiligo and comorbid SSc might be monitored for cardiovascular and metabolic comorbidities.

A signal recognition particle-related joint model of LASSO regression, SVM-RFE and artificial neural network for the diagnosis of systemic sclerosis-associated pulmonary hypertension

Background: Systemic sclerosis-associated pulmonary hypertension (SSc-PH) is one of the most common causes of death in patients with systemic sclerosis (SSc). The complexity of SSc-PH and the heterogeneity of clinical features in SSc-PH patients contribute to the difficulty of diagnosis. Therefore, there is a pressing need to develop and optimize models for the diagnosis of SSc-PH. Signal recognition particle (SRP) deficiency has been found to promote the progression of multiple cancers, but the relationship between SRP and SSc-PH has not been explored. Methods: First, we obtained the GSE19617 and GSE33463 datasets from the Gene Expression Omnibus (GEO) database as the training set, GSE22356 as the test set, and the SRP-related gene set from the MSigDB database. Next, we identified differentially expressed SRP-related genes (DE-SRPGs) and performed unsupervised clustering and gene enrichment analyses. Then, we used least absolute shrinkage and selection operator (LASSO) regression and support vector machine-recursive feature elimination (SVM-RFE) to identify SRP-related diagnostic genes (SRP-DGs). We constructed an SRP scoring system and a nomogram model based on the SRP-DGs and established an artificial neural network (ANN) for diagnosis. We used receiver operating characteristic (ROC) curves to identify the SRP-related signature in the training and test sets. Finally, we analyzed immune features, signaling pathways, and drugs associated with SRP and investigated SRP-DGs' functions using single gene batch correlation analysis-based GSEA. Results: We obtained 30 DE-SRPGs and found that they were enriched in functions and pathways such as "protein targeting to ER," "cytosolic ribosome," and "coronavirus disease-COVID-19". Subsequently, we identified seven SRP-DGs whose expression levels and diagnostic efficacy were validated in the test set. As one signature, the area under the ROC curve (AUC) values for seven SRP-DGs were 0.769 and 1.000 in the training and test sets, respectively. Predictions made using the nomogram model are likely beneficial for SSc-PH patients. The AUC values of the ANN were 0.999 and 0.860 in the training and test sets, respectively. Finally, we discovered that some immune cells and pathways, such as activated dendritic cells, complement activation, and heme metabolism, were significantly associated with SRP-DGs and identified ten drugs targeting SRP-DGs. Conclusion: We constructed a reliable SRP-related ANN model for the diagnosis of SSc-PH and investigated the possible role of SRP in the etiopathogenesis of SSc-PH by bioinformatics methods to provide a basis for precision and personalized medicine.

Association between Appendicitis and Incident Systemic Sclerosis

Objective: This nationwide study aimed to investigate the association between newly diagnosed systemic sclerosis (SSc) and previous appendicitis history. Methods: A total of 1595 patients who were newly diagnosed with SSc were recruited as the SSc cases from the 2003 to 2012 claims data of the entire population in Taiwan. The other 15,950 individuals who had never been diagnosed with SSc during 2003 and 2012 were selected as the non-SSc controls to match the SSc cases. We defined that the index date as the first date of SSc diagnosis of SSc cases and the first date of ambulatory visit for any reason of non-SSc controls. Conditional logistic regression analysis was applied for the association between appendicitis and the risk of the incident SSc, tested by estimating odds ratios (ORs) with 95% confidence intervals (CIs). Potential confounders, including the Charlson comorbidity index (CCI), a history of periodontal disease, salmonella infection, and intestinal infection, were controlled. We further designed sensitivity analyses by varying the definition of appendicitis according to the status of receiving primary appendectomy. Results: The mean age was 51 years in the case and control groups. Females accounted for 77.5%. A total of 17 (1.1%) out of 1595 SSc cases and 81 (0.5%) out of 15,950 non-SSc controls had a history of appendicitis before the index date had a history of appendicitis. A significant association between appendicitis and the risk of SSc was confirmed (OR, 2.03; 95% CI, 1.14–3.60) after adjusting potential confounders. CCI ≥ 1 (OR, 8.48; 95% CI, 7.50–9.58) and periodontal disease (OR, 1.55; 95% CI, 1.39–1.74) were also significantly associated with the risk of SSc. The association between appendicitis and SSc risk remained robust using various definitions of appendicitis. Conclusion: Our study demonstrated appendicitis was associated with the incident SSc. CCI ≥ 1 and periodontal disease also contributed to the risk of developing SSc.