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BACKGROUND AND AIMS: Monogenic forms of inflammatory bowel disease (IBD) illustrate the essential roles of individual genes in pathways and networks safeguarding immune tolerance and gut homeostasis. METHODS: To build a taxonomy model we assessed 165 disorders. Genes were prioritized based on penetrance of IBD and disease phenotypes were integrated with multi-omics datasets. Monogenic IBD genes were classified by: (1) overlapping syndromic features; (2) response to hematopoietic stem cell transplantation; (3) bulk RNA-seq of 32 tissues; (4) single-cell RNA-seq of >50 cell subsets from the intestine of healthy individuals and IBD patients (pediatric and adult), and (5) proteomes of 43 immune subsets. The model was validated by addition of newly identified monogenic IBD defects. As a proof-of-concept, we explore the intersection between immunometabolism and antimicrobial activity for a group of disorders (G6PC3/SLC37A4). RESULTS: Our quantitative integrated taxonomy defines the cellular landscape of monogenic IBD gene expression across 102 genes with high and moderate penetrance (81 in the model set and 21 genes in the validation set). We illustrate distinct cellular networks, highlight expression profiles across understudied cell types (e.g., CD8+ T cells, neutrophils, epithelial subsets and endothelial cells) and define genotype-phenotype associations (perianal disease and defective antimicrobial activity). We illustrate processes and pathways shared across cellular compartments and phenotypic groups and highlight cellular immunometabolism with mTOR activation as one of the converging pathways. There is an overlap of genes and enriched cell-specific expression between monogenic and polygenic IBD. CONCLUSION: Our taxonomy integrates genetic, clinical and multi-omic data; providing a basis for genomic diagnostics and testable hypotheses for disease functions and treatment responses.

Original publication

DOI

10.1053/j.gastro.2021.11.014

Type

Journal article

Journal

Gastroenterology

Publication Date

12/11/2021

Keywords

Immunodeficiency, RNAseq, genomics, next-generation sequencing