Mouse Models of Rheumatoid Arthritis.

Rheumatoid arthritis (RA) is a chronic debilitating autoimmune disorder characterized by synovitis that leads to cartilage and bone erosion by invading fibrovascular tissue. Mouse models of RA recapitulate many features of the human disease. Despite the availability of medicines that are highly effective in many patient populations, autoimmune diseases (including RA) remain an area of active biomedical research, and consequently mouse models of RA are still extensively used for mechanistic studies and validation of therapeutic targets. This review aims to integrate morphologic features with model biology and cover the key characteristics of the most commonly used induced and spontaneous mouse models of RA. Induced models emphasized in this review include collagen-induced arthritis and antibody-induced arthritis. Collagen-induced arthritis is an example of an active immunization strategy, whereas antibody- induced arthritis models, such as collagen antibody-induced arthritis and K/BxN antibody transfer arthritis, represent examples of passive immunization strategies. The coverage of spontaneous models in this review is focused on the TNFΔ (ARE) mouse, in which arthritis results from overexpression of TNF-α, a master proinflammatory cytokine that drives disease in many patients.

Fully-automated, high-throughput micro-computed tomography analysis of body composition enables therapeutic efficacy monitoring in preclinical models.

BACKGROUND: The ability to non-invasively measure body composition in mouse models of obesity and obesity-related disorders is essential for elucidating mechanisms of metabolic regulation and monitoring the effects of novel treatments. These studies aimed to develop a fully automated, high-throughput micro-computed tomography (micro-CT)-based image analysis technique for longitudinal quantitation of adipose, non-adipose and lean tissue as well as bone and demonstrate utility for assessing the effects of two distinct treatments. METHODS: An initial validation study was performed in diet-induced obesity (DIO) and control mice on a vivaCT 75 micro-CT system. Subsequently, four groups of DIO mice were imaged pre- and post-treatment with an experimental agonistic antibody specific for anti-fibroblast growth factor receptor 1 (anti-FGFR1, R1MAb1), control immunoglobulin G antibody, a known anorectic antiobesity drug (rimonabant, SR141716), or solvent control. The body composition analysis technique was then ported to a faster micro-CT system (CT120) to markedly increase throughput as well as to evaluate the use of micro-CT image intensity for hepatic lipid content in DIO and control mice. Ex vivo chemical analysis and colorimetric analysis of the liver triglycerides were performed as the standard metrics for correlation with body composition and hepatic lipid status, respectively. RESULTS: Micro-CT-based body composition measures correlate with ex vivo chemical analysis metrics and enable distinction between DIO and control mice. R1MAb1 and rimonabant have differing effects on body composition as assessed by micro-CT. High-throughput body composition imaging is possible using a modified CT120 system. Micro-CT also provides a non-invasive assessment of hepatic lipid content. CONCLUSIONS: This work describes, validates and demonstrates utility of a fully automated image analysis technique to quantify in vivo micro-CT-derived measures of adipose, non-adipose and lean tissue, as well as bone. These body composition metrics highly correlate with standard ex vivo chemical analysis and enable longitudinal evaluation of body composition and therapeutic efficacy monitoring.