Highly Multiplexed Image Analysis of Intestinal Tissue Sections in Patients With Inflammatory Bowel Disease

Significant progress has been made since the first report of inflammatory bowel disease (IBD) in 1859, after decades of research that have contributed to the understanding of the genetic and environmental factors involved in IBD pathogenesis. Today, a range of treatments is available for directed therapy, mostly targeting the overactive immune response. However, the mechanisms by which the immune system contributes to disease pathogenesis and progression are not fully understood. One challenge hindering IBD research is the heterogeneous nature of the disease and the lack of understanding of how immune cells interact with one another in the gut mucosa. Introduction of a technology that enables expansive characterization of the inflammatory environment of human IBD tissues may address this gap in knowledge.

We used the imaging mass cytometry platform to perform highly multiplex image analysis of IBD and healthy deidentified intestine sections (6 Crohn's disease compared to 6 control ileum; 6 ulcerative colitis compared to 6 control colon). The acquired images were graded for inflammation severity by analysis of adjacent H&E tissue sections. We assigned more than 300,000 cells to unique cell types and performed analyses of tissue integrity, epithelial activity, and immune cell composition.

The intestinal epithelia of patients with IBD exhibited increased proliferation rates and expression of HLA-DR compared to control tissues, and both features were positively correlated with the severity of inflammation. The neighborhood analysis determined enrichment of regulatory T cell interactions with CD68⁺ macrophages, CD4⁺ T cells, and plasma cells in both forms of IBD, whereas activated lysozyme C⁺ macrophages were preferred regulatory T cell neighbors in Crohn's disease but not ulcerative colitis.

Altogether, our study shows the power of imaging mass cytometry and its ability to both quantify immune cell types and characterize their spatial interactions within the inflammatory environment by a single analysis platform.