Precision Diagnosis and Differentiation of Eosinophilic Colitis and Inflammatory Bowel Disease Using a Tissue-Based Molecular Gene Expression Panel

炎症性肠病 医学 溃疡性结肠炎 基因表达 结肠炎 免疫学 嗜酸性 炎症性肠病 病理 疾病 基因 炎症 发病机制 基因表达谱 克罗恩病 表达式(计算机科学) 炎症反应
作者
Richard J. Taylor,Mari Yamaguchi,Lee A. Denson,Vincent A. Mukkada,Kazuhiro Matsuyama,Yuichiro Tanaka,Glenn T. Furuta,Robert D. Pesek,Seema Sharma Aceves,Nicoleta C. Arva,Mirna Chehade,Margaret H. Collins,Sara Anvari,Evan S. Dellon,Gary W. Falk,Nirmala Prabu Gonsalves,Sandeep K. Gupta,Girish S Hiremath,David A. Katzka,Paneez Khoury
出处
期刊:The Journal of Allergy and Clinical Immunology [Elsevier BV]
标识
DOI:10.1016/j.jaci.2026.09.035
摘要

BACKGROUND: Eosinophilic colitis (EoC) and eosinophil-predominant inflammatory bowel disease (IBD) can show overlapping clinical and histologic features, creating diagnostic uncertainty. Whether tissue gene expression can objectively distinguish these conditions in the setting of colonic eosinophilia remains unclear. OBJECTIVE: We sought to develop and validate a tissue-based molecular diagnostic panel to quantify eosinophilic inflammation and differentiate EoC from IBD-associated colonic eosinophilia. METHODS: This multi-center study analyzed 88 colonic biopsies from a cohort enriched for children and young adults, including 74 patients with EoC or IBD and non-disease controls. We developed a 96-gene qPCR-based platform, the Colonic Eosinophilia Diagnostic Panel (CEDP), and generated molecular EoC and IBD scores. Diagnostic accuracy was determined by area under the receiver operating characteristic curve (AUC). RESULTS: An EoC score developed from 59 genes (e.g., eosinophil-associated gene CLC) distinguished active EoC from non-disease controls (AUC 0.92, 95% CI 0.78-1.0) and quantified the active molecular eosinophilic inflammatory program, correlating with peak eosinophil counts. However, this score did not differentiate EoC from IBD. An IBD score from 18 genes (e.g., DUOXA2) reflecting inflammatory pathways provided complementary discriminatory information and resolved this overlap. This approach distinguished active IBD from all other groups (AUC 0.98, 95% CI 0.76-1.0) and specifically active EoC (AUC 0.99, 95% CI 0.95-1.0), correlated with endoscopic activity, and differentiated IBD with high colonic eosinophil counts. CONCLUSIONS: We developed the CEDP with a tissue-based, two-component molecular framework for evaluating colonic eosinophilia. By measuring eosinophilic inflammatory activity and identifying an IBD-associated molecular signature, this platform can distinguish EoC from IBD beyond conventional histopathology alone.
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