GG-09 Comparative analysis of gene expression in lupus-affected tissues reveals common and disparate pathways of inflammation. (31st August 2016)

• Record Type: Journal Article
• Authors: Grammer, Amrie; Heuer, Sarah; Robl, Robert; Bachali, Prathyusha; Madamanchi, Sushma; Kretzler, Matthias; Berthier, Celine; Chong, Benjamin; Davis, Laurie; Lauwerys, Bernard; Catalina, Micelle; Lipsky, Peter
• Is Part Of: Lupus science & medicine. Volume 3(2016)Supplement 1
• Page Start: A31
• Page End: A32
• Publication Date: 2016-08-31
• Subjects: Systemic lupus erythematosus -- Periodicals; 616.772005
• DOI: 10.1136/lupus-2016-000179.61
• Languages: English
• ISSNs: 2398-8851

Abstract

Abstract : Background: Immunologic mechanisms causing tissue damage in autoimmune diseases such as SLE are not fully understood. The hypothesis to be tested is that gene expression analysis of lupus-affected tissues will generate novel insights into targets of immunological intervention. Materials and methods: To gain additional insight, gene expression profiles obtained from lupus affected skin, synovium and kidney were obtained, compared to meta-analysed data obtained from active lupus B, T and myeloid cells, and cross-referenced to various pathway analytic tools including Molecular Signature (MS © )-Scoring, Ingenuity Pathway Analysis © Upstream Regulator (IPA © -UR) analysis, and Library of Integrated Network of Cellular Signatures (LINCS). Results: More than 300 arrays from lupus patients and appropriate controls were analysed to determine differentially expressed (DE) genes [8279 discoid lupus skin, 5465 synovial lupus arthritis, 6381 glomerulus (G) lupus nephritis, 5587 tubulointerstitum (TI) lupus nephritis]. Notably, the majority of lupus affected tissue DE genes were detected in more than one tissue and 439 were differentially expressed in all tissues. Tissue lymphocyte infiltration was documented by cell markers as well as by published unique gene expression signatures (BIG-C © ). Common up-regulated transcripts in affected tissues displayed a variety of functions including pattern recognition receptors, p38/MAPK14 activation, endothelial endocytosis, and TLR activation. Unique targets of intervention were discovered when up-regulated transcripts in all lupus tissues were cross-referenced to molecular pathway and drug interaction databases. Canonical signalling pathways, published to be important for lupus pathogenesis, such as CD40L-CD40, IL-6, and IL-12/23 were visualised in IPA. Both MS © -scoring and IPA © -UR analysis predicted that signalling mediated by CD40 and IL12R occur in lupus skin, synovium and kidney glomeruli. LINCS connectivity analysed the effect of in vitro knockdown of ligand-receptor pairs and compared the genes affected with lupus tissue DE lists. Lupus nephritis (LN) kidney glomeruli received a LINCS connectivity score of −77 for CD40, implying that DE genes in this tissue have a high likelihood of being regulated by CD40-induced signalling. Skin and lupus nephritis kidney glomeruli received LINCS connectivity scores of −73 and −97, respectively, for the key signalling molecule required for IL6 signalling, IL6ST/gp130. All lupus-affected tissues had negative connectivity scores (skin, −98; synovium, −89; LN glomeruli, −91 and LN TI, −87) for IL12α. Examination of curated functional groups from the STRING output of common up-regulated transcripts in lupus tissue using IPA's BioProfiler © function predicted therapeutic targets and drugs for all three ligand-receptor pairs examined by MS © -scoring, IPA © -UR and LINCS. Conclusions: This approach demonstrated that there are pathways common to all lupus tissue, and there are pathways involved in inflammatory response of some but not all tissues. Further analysis should generate a model of lupus immunopathogenesis and could identify therapies that may be useful in all lupus patients versus those with involvement of specific tissues.