Abstract
Systemic lupus erythematosus (SLE) patients exhibit immense heterogeneity which is challenging from the diagnostic perspective. Emerging high throughput sequencing technologies have been proved to be a useful platform to understand the complex and dynamic disease processes. SLE patients categorised based on autoantibody specificities are reported to have differential immuno-regulatory mechanisms. Therefore, we performed RNA-seq analysis to identify transcriptomics of SLE patients with distinguished autoantibody specificities. The SLE patients were segregated into three subsets based on the type of autoantibodies present in their sera (anti-dsDNA+ group with anti-dsDNA autoantibody alone; anti-ENA+ group having autoantibodies against extractable nuclear antigens (ENA) only, and anti-dsDNA+ENA+ group having autoantibodies to both dsDNA and ENA). Global transcriptome profiling for each SLE patients subsets was performed using Illumina® Hiseq-2000 platform. The biological relevance of dysregulated transcripts in each SLE subsets was assessed by ingenuity pathway analysis (IPA) software. We observed that dysregulation in the transcriptome expression pattern was clearly distinct in each SLE patients subsets. IPA analysis of transcripts uniquely expressed in different SLE groups revealed specific biological pathways to be affected in each SLE subsets. Multiple cytokine signaling pathways were specifically dysregulated in anti-dsDNA+ patients whereas Interferon signaling was predominantly dysregulated in anti-ENA+ patients. In anti-dsDNA+ENA+ patients regulation of actin based motility by Rho pathway was significantly affected. The granulocyte gene signature was a common feature to all SLE subsets; however, anti-dsDNA+ group showed relatively predominant expression of these genes. Dysregulation of Plasma cell related transcripts were higher in anti-dsDNA+ and anti-ENA+ patients as compared to anti-dsDNA+ ENA+. Association of specific canonical pathways with the uniquely expressed transcripts in each SLE subgroup indicates that specific immunological disease mechanisms are operative in distinct SLE patients’ subsets. This ‘sub-grouping’ approach could further be useful for clinical evaluation of SLE patients and devising targeted therapeutics.
Highlights
Systemic lupus erythematosus (SLE) is a complex autoimmune disease with diverse presentations of clinical manifestations [1] and wide range of autoantibodies [2]
We performed an unsupervised principal component analysis to identify subset specific phenotypes that is more likely to be represented as a function of all transcripts rather than the separate expression values on PCA plot
PCA reveals that samples of anti-dsDNA+ subgroup were spatially separated from the antiENA+ patient samples
Summary
Systemic lupus erythematosus (SLE) is a complex autoimmune disease with diverse presentations of clinical manifestations [1] and wide range of autoantibodies [2]. Recent emergence of deep sequencing technology has added newer dimensions in unraveling the disease specific events. These tools have allowed identification of novel transcripts, alternative splicing events and information on non coding RNAs (ncRNAs) associated with SLE [8,9,10]. This approach was further employed for identifying rare or novel deleterious variants as genetic causes of SLE [11, 12]
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