A multi-predictor model to predict risk of scleroderma renal crisis in systemic sclerosis: a multicentre, retrospective, cohort study.

OBJECTIVES: Scleroderma renal crisis (SRC) is a life-threatening syndrome. The early identification of patients at risk is essential for timely treatment to improve the outcome. Therefore, it is of great interest to provide a personalised tool to predict risk of SRC in systemic sclerosis (SSc). METHODS: We tried to set up a SRC prediction model based on the PKUPH-SSc cohort of 302 SSc patients. The least absolute shrinkage and selection operator (Lasso) regression was used to optimise disease features. Multivariable logistic regression analysis was applied to build a SRC prediction model incorporating the features of SSc selected in the Lasso regression. Then, a multi-predictor nomogram combining clinical characteristics was constructed and evaluated by discrimination and calibration, with further assessment by external validation in a validation cohort composed of 400 consecutive SSc patients from other 4 tertiary hospitals. RESULTS: A multi-predictor nomogram for evaluating the risk of SRC was successfully developed. In the nomogram, four easily available predictors were contained, including disease duration <2 years, cardiac involvement, anaemia and corticosteroid >15mg/d exposure. The nomogram displayed good discrimination with an area under the curve (AUC) of 0.843 (95% CI: 0.797-0.882) and good calibration. High AUC value of 0.854 (95% CI: 0.690-1.000) could still be achieved in the external validation. The model is now available online for research use. CONCLUSIONS: The multi-predictor nomogram for SRC could be reliably and conveniently used to predict the individual risk of SRC in SSc patients, and be a step towards more personalised medicine.

Exome-Wide Association Analysis Suggests LRP2BP as a Susceptibility Gene for Endothelial Injury in Systemic Sclerosis in the Han Chinese Population.

Genetic factors play a key role in the pathogenesis of autoimmune diseases, whereas the disease-causing variants remain largely unknown. Herein, we performed an exome-wide association study of systemic sclerosis in a Han Chinese population. In the discovery stage, 527 patients with systemic sclerosis and 5,024 controls were recruited and genotyped. In the validation study, an independent sample set of 479 patients and 1,096 controls were examined. In total, we found that four independent signals reached genome-wide significance. Among them, rs7574865 (Pcombined = 3.87 × 10-12) located within signal transducer and activator of transcription 4 gene was identified previously using samples of European ancestry. Additionally, another signal including three SNPs in linkage disequilibrium might be unreported susceptibility loci located in the epidermis differentiation complex region. Furthermore, two SNPs located within exon 3 of IGHM (rs45471499, Pcombined = 1.15 × 10-9) and upstream of LRP2BP (rs4317244, Pcombined = 4.17 × 10-8) were found. Moreover, rs4317244 was identified as an expression quantitative trait locus for LRP2BP that regulates tight junctions, cell cycle, and apoptosis in endothelial cell lines. Collectively, our results revealed three signals associated with systemic sclerosis in Han Chinese and suggested the importance of LRP2BP in systemic sclerosis pathogenesis. Given the limited sample size and discrepancies between previous results and our study, further studies in multiethnic populations are required for verification.