| Literature DB >> 22723521 |
Celine C Berthier1, Ramalingam Bethunaickan, Tania Gonzalez-Rivera, Viji Nair, Meera Ramanujam, Weijia Zhang, Erwin P Bottinger, Stephan Segerer, Maja Lindenmeyer, Clemens D Cohen, Anne Davidson, Matthias Kretzler.
Abstract
Lupus nephritis (LN) is a serious manifestation of systemic lupus erythematosus. Therapeutic studies in mouse LN models do not always predict outcomes of human therapeutic trials, raising concerns about the human relevance of these preclinical models. In this study, we used an unbiased transcriptional network approach to define, in molecular terms, similarities and differences among three lupus models and human LN. Genome-wide gene-expression networks were generated using natural language processing and automated promoter analysis and compared across species via suboptimal graph matching. The three murine models and human LN share both common and unique features. The 20 commonly shared network nodes reflect the key pathologic processes of immune cell infiltration/activation, endothelial cell activation/injury, and tissue remodeling/fibrosis, with macrophage/dendritic cell activation as a dominant cross-species shared transcriptional pathway. The unique nodes reflect differences in numbers and types of infiltrating cells and degree of remodeling among the three mouse strains. To define mononuclear phagocyte-derived pathways in human LN, gene sets activated in isolated NZB/W renal mononuclear cells were compared with human LN kidney profiles. A tissue compartment-specific macrophage-activation pattern was seen, with NF-κB1 and PPARγ as major regulatory nodes in the tubulointerstitial and glomerular networks, respectively. Our study defines which pathologic processes in murine models of LN recapitulate the key transcriptional processes active in human LN and suggests that there are functional differences between mononuclear phagocytes infiltrating different renal microenvironments.Entities:
Mesh:
Year: 2012 PMID: 22723521 PMCID: PMC3392438 DOI: 10.4049/jimmunol.1103031
Source DB: PubMed Journal: J Immunol ISSN: 0022-1767 Impact factor: 5.422