Development and initial validation of diagnostic gene signatures for systemic lupus erythematosus
Authors: Bin Wang, Shiju Chen, Qing Zheng, Zhenyu Gao, Rongjuan Chen, Jingxiu Xuan, Yuan Liu, Guixiu Shi
Journal: Annals of the Rheumatic Diseases (2019)

Development and initial validation of diagnostic gene signatures for systemic lupus erythematosusSystemic lupus erythematosus (SLE) is a complex and heterogeneous rheumatic disease with variable clinical features.The correct diagnosis of SLE is still challenging, partially due to the complexity and heterogeneity of SLE pathogenesis.A new classification criteria for SLE with excellent sensitivity and specificity has been recently proposed by the European League Against Rheumatism and the American College of Rheumatology. 1 Apart from autoantibodies such as anti-double-stranded DNA antibodies, novel molecular biomarkers may help to improve the performance of SLE classification criteria, but they are not included in the new classification criteria, which is largely attributed to the limited availability in the clinical setting or insufficient evidence. 1Transcriptome studies using either microarray or RNA sequencing mainly aim to investigate the aberrant RNA expression levels of genes on a genome-wide scale, and have been widely used in the clinical research of rheumatic diseases.Studies using transcriptome analysis also have provided deeper insights into the pathogenic mechanism of SLE.Differently expressed genes (DEGs) derived from microarray-based peripheral blood transcriptome data can also be used as diagnostic or prognostic biomarkers for autoimmune diseases, but their use in SLE is still not well established. 2 3In this study, we aimed to develop a genetic signature for SLE diagnosis through bioinformatic analyses of whole blood transcriptome data.To overcome the limited clinical utility caused by the low consistency and the risk of noise discovery in microarray-based studies, robust rank aggregation (RRA) analysis was used to integrate data from multiple transcriptome datasets.RRA is a useful integration approach in pooling data from heterogeneous datasets and can help to identify the mostly aberrantly expressed genes between patients with SLE and controls across multiple datasets, which may lead to a SLE diagnostic gene signature with both high reproducibility and high stability. 4Fourteen whole blood transcriptome datasets with at least 20 patients with SLE and 10 controls were integrated with RRA, which included GSE110685, GSE112087, GSE99967, GSE110169, GSE88884, GSE65391, GSE72509, GSE45291, GSE49454, GSE61635, CorrespondenceFigure 1 Assessment of the diagnostic performance of gene signatures in systemic lupus erythematosus (SLE) in six microarray datasets.(A) Diagnostic performance of RRAtop10, RRAWGCNA10 and IFI44L alone in GSE45291 (292 patients with SLE and 20 controls).(B) Diagnostic performance of RRAtop10, RRAWGCNA10 and IFI44L alone in GSE49454 (157 patients with SLE and 20 controls).(C) Diagnostic performance of RRAtop10, RRAWGCNA10 and IFI44L alone in GSE61635 (79 patients with SLE and 30 controls).(D) Diagnostic performance of RRAtop10, RRAWGCNA10 and IFI44L alone in GSE65391 (118 patients with SLE and 32 controls).(E) Diagnostic performance of RRAtop10, RRAWGCNA10 and IFI44L alone in GSE88884 (1760 patients with SLE and 60 controls).(F) Diagnostic performance of RRAtop10, RRAWGCNA10 and IFI44L alone in GSE110169 (82 patients with SLE and 77 controls).Receiver operating characteristic curve analyses were performed using the enrichment score of RRAtop10 and RRAWGCNA10 in each individual calculated through Gene Set Variation Analysis.AUC, area under the curve.on August 20,