Abstract

BackgroundDiagnosis of chronic intestinal inflammation, which characterizes inflammatory bowel disease (IBD), along with prediction of disease state is hindered by the availability of predictive serum biomarker. Serum biomarkers predictive of disease state will improve trials for therapeutic intervention, and disease monitoring, particularly in genetically susceptible individuals. Chronic inflammation during IBD is considered distinct from infectious intestinal inflammation thereby requiring biomarkers to provide differential diagnosis. To address whether differential serum biomarkers could be identified in murine models of colitis, immunological profiles from both chronic spontaneous and acute infectious colitis were compared and predictive serum biomarkers identified via multivariate modeling.Methodology/Principal FindingsDiscriminatory multivariate modeling of 23 cytokines plus chlorotyrosine and nitrotyrosine (protein adducts from reactive nitrogen species and hypochlorite) in serum and tissue from two murine models of colitis was performed to identify disease-associated biomarkers. Acute C. rodentium-induced colitis in C57BL/6J mice and chronic spontaneous Helicobacter-dependent colitis in TLR4−/− x IL-10−/− mice were utilized for evaluation. Colon profiles of both colitis models were nearly identical with chemokines, neutrophil- and Th17-related factors highly associated with intestinal disease. In acute colitis, discriminatory disease-associated serum factors were not those identified in the colon. In contrast, the discriminatory predictive serum factors for chronic colitis were neutrophil- and Th17-related factors (KC, IL-12/23p40, IL-17, G-CSF, and chlorotyrosine) that were also elevated in colon tissue. Chronic colitis serum biomarkers were specific to chronic colitis as they were not discriminatory for acute colitis.Conclusions/SignificanceImmunological profiling revealed strikingly similar colon profiles, yet distinctly different serum profiles for acute and chronic colitis. Neutrophil- and Th17-related factors were identified as predictive serum biomarkers of chronic colitis, but not acute colitis, despite their presence in colitic tissue of both diseases thereby demonstrating the utility of mathematical modeling for identifying disease-associated serum biomarkers.

Highlights

  • Intestinal inflammation develops from known causes such as infection with enteropathogenic E. coli (EPEC) or from unknown causes as in inflammatory bowel diseases (IBD)

  • Development of disease was monitored by change in body weight with C. rodentium infected (Cr+) mice losing 3% of initial body weight by 14 days postinfection (DPI) compared with uninfected mice gaining 4% (P,0.01, Figure S1B)

  • Comprehensive measurement and deconvolution of these potential biomarkers via multivariate analysis allows predictions of disease state and evaluation of therapeutic endpoints. In this proof of principle study immunologic parameters in serum and tissue were evaluated for their utility in modeling and predicting severity of histological lesions and colon disease severity from two forms of microbial-induced colitis: acute C. rodentium colitis and chronic Helicobacter-dependent colitis

Read more

Summary

Introduction

Intestinal inflammation develops from known causes such as infection with enteropathogenic E. coli (EPEC) or from unknown causes as in inflammatory bowel diseases (IBD). Immune mediators in C. rodentium-induced colitis have been extensively studied in mice with targeted knockouts of innate and adaptive cells, as well as cytokines, cytokine receptors, and pattern recognition receptors. These studies have shown that bacterial clearance and disease resolution require both protective antibodies and an IFN-c mediated T effector cell response [9,10,11,12] whereas other immunological mediators prevent early mortality through maintenance of epithelial barrier function [13,14,15,16]. Diagnosis of chronic intestinal inflammation, which characterizes inflammatory bowel disease (IBD), along with prediction of disease state is hindered by the availability of predictive serum biomarker.

Methods
Results
Conclusion
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call