ArticleJournal of translational medicine2017
Design and validation of a disease network of inflammatory processes in the NSG-UC mouse model.
Article in Journal of translational medicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 18 citations in OpenAlex.
- Murine and Humanized Mouse Models in Autoimmune Disease Research and Therapeutics Development.Biology · 2026Review
- Validation of a model of rheumatoid arthritis using mice reconstituted with patient peripheral blood mononuclear cells.Disease models & mechanisms · 2025Article
- Humanized NSG Mouse Models as a Preclinical Tool for Translational Research in Inflammatory Bowel Diseases.International journal of molecular sciences · 2023Article
- NOD/scid IL-2RγImmunity, inflammation and disease · 2021Article
- The Combination of Patient Profiling and Preclinical Studies in a Mouse Model Based on NOD/Scid IL2Rγ null Mice Reconstituted With Peripheral Blood Mononuclear Cells From Patients With Ulcerative Colitis May Lead to Stratification of Patients for Treatment With Adalimumab.Inflammatory bowel diseases · 2020Article
- Autoantibodies as diagnostic markers and potential drivers of inflammation in ulcerative colitis.PloS one · 2020Article
- Intestinal autophagy links psychosocial stress with gut microbiota to promote inflammatory bowel disease.Cell death & disease · 2019Article
- Immunomodulation of Interleukin-34 and its Potential Significance as a Disease Biomarker and Therapeutic Target.International journal of biological sciences · 2019Review
- Targeting ulcerative colitis by suppressing glucose uptake with ritonavir.Disease models & mechanisms · 2018Article
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Authors and funding
7 authors at 5 institutions in 1 country.
Funding
Abstract
backgroundUlcerative colitis (UC) is a highly progressive inflammatory disease that requires the interaction of epithelial, immune, endothelial and muscle cells and fibroblasts. Previous studies suggested two inflammatory conditions in UC-patients: 'acute' and 'remodeling' and that the design of a disease network might improve the understanding of the inflammatory processes. The objective of the study was to design and validate a disease network in the NOD-SCID IL2rγ
methodsLeukocytes were isolated from the spleen of NSG-UC mice and subjected to flow cytometric analysis. RT-PCR and RNAseq analysis were performed from distal parts of the colon. Based on these analyses and the effects of interleukins, chemokines and growth factors described in the literature, a disease network was designed. To validate the disease network the effect of infliximab and pitrakinra was tested in the NSG-UC model. A clinical- and histological score, frequencies of human leukocytes isolated from spleen and mRNA expression levels from distal parts of the colon were determined.
resultsAnalysis of leukocytes isolated from the spleen of challenged NSG-UC mice corroborated CD64, CD163 and CD1a expressing CD14+ monocytes, CD1a expressing CD11b+ macrophages and HGF, TARC, IFNγ and TGFß1 mRNA as inflammatory markers. The disease network suggested that a proinflammatory condition elicited by IL-17c and lipids and relayed by cytotoxic T-cells, Th17 cells and CD1a expressing macrophages and monocytes. Conversely, the remodeling condition was evoked by IL-34 and TARC and promoted by Th2 cells and M2 monocytes. Mice benefitted from treatment with infliximab as indicated by the histological- and clinical score. As predicted by the disease network infliximab reduced the proinflammatory response by suppressing M1 monocytes and CD1a expressing monocytes and macrophages and decreased levels of IFNγ, TARC and HGF mRNA. As predicted by the disease network inflammation aggravated in the presence of pitrakinra as indicated by the clinical and histological score, elevated frequencies of CD1a expressing macrophages and TNFα and IFNγ mRNA levels.
conclusionsThe combination of the disease network and the NSG-UC animal model might be developed into a powerful tool to predict efficacy or in-efficacy and potential mechanistic side effects.
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