Project Summary/Abstract Ulcerative colitis (UC) is a complex disorder impacting millions of people worldwide resulting in significant costs, chronic debilitating symptoms, and complications such as colon cancer. Even with biologic therapies targeting immune signaling pathways, variability in patient responses is highly prevalent and remission rates remain low (~40%). Therefore, personalized biomarker development is an area of unmet clinical need. Macrophages have been identified as a crucial intermediary of pro-inflammatory (M1) and anti-inflammatory (M2) phenotypes in UC. Due to the significant overlap between M1 and M2 signaling even in histologically identical tissues, biomarkers focused on transcriptomics alone are limited. Chromatin, the genome folded into 3-D, regulates how genes interact with transcription factors and polymerases to synthesize RNA. Since cytokine signaling converges on transcription-factor cascades, understanding chromatin structure in UC may serve as a rational framework for biomarker development. The goal of this proposal is to establish a cohesive framework that links transcriptomic states with chromatin structure for biomarker development in UC. Preliminary work shows that chromatin packing domains are the primary regulator of transcriptional reactions in cells. The stochastic returns-excluded volume (SR-EV) model can produce the structure of chromatin packing domains observed on electron microscopy at high-throughout (>100k independent configurations). We hypothesize that it’s possible model and predict macrophage transcriptomic behavior in UC by combining SR-EV with in situ transcriptomic and chromatin measurements. We test this hypothesis through three separate but inter-related aims. Aim 1 focuses on expanding the capabilities of SR-EV to predict domains associated with M1 and M2 macrophage transcriptomic patterns. Aim 2 studies the mechanisms governing packing domain formation in macrophages and the ability to manipulate expression