Early prediction of inflammation by unprecedented unbiased linking of tissue molecular composition and structure

The identification of molecular signatures that aid early diagnosis of complex tissue pathologies, such as inflammatory diseases, poses a major scientific and clinical challenge due to their genetic and phenotypic heterogeneity. We have been able to unprecedentedly discover a distinct tissue state occurring before the onset of inflammatory clinical symptoms by integrating quantitative proteomics with advanced microscopy analyses. Through monitoring colonic extracellular matrix (ECM) remodeling in colitis animal models we have unexpectedly revealed that pre-symptomatic tissues display a unique ECM signature in terms of molecular composition, morphology and stiffness. By applying advanced computational analyses we were able to project quantitative proteomics data onto an axis correlating with spatially resolved tissue damage originating from the ECM. These results bridge the gap between tissue structure and composition while outlining the predictive power of the cellular microenvironment in early diagnostics of inflammatory diseases.