Work

Single-cell immune repertoire atlas maps coordinated circulating adaptive immune states in inflammatory bowel disease

Year: 2026

Type: preprint

Abstract: SUMMARY Single-cell studies have defined immune states in inflammatory bowel disease (IBD), but how adaptive receptor histories organize circulating immunity remains unclear. We generated a single-cell transcriptomic atlas of peripheral blood from 249 participants with Crohn’s disease, ulcerative colitis, or non-IBD control status, including 182 with productive TCR and BCR recovery. Expanded TCR clonotypes marked inflammatory-memory and cytotoxic states, while distinct but similar paired TCRs shared inflammatory programs across participants. BCR lineage maturation linked IgA-associated mucosal and plasma B cell programs to somatic mutation and class switching, distinguishing maturation-associated biology from clonal expansion. Helper, regulatory, and cytotoxic T-cell programs covaried with B-cell states, and inferred interactions nominated reciprocal antigen-presentation and helper pathways. Repertoire-based machine learning distinguished diagnosis, inflammation, and contemporaneous six-month treatment-response status. Together, this atlas connects receptor architecture to coordinated systemic immune remodeling, establishes a foundation for repertoire-informed patient stratification, and prioritizes candidate mechanisms of IBD pathogenesis. GRAPHICAL ABSTRACT Highlights Paired single-cell receptors map circulating adaptive immune states across IBD TCR expansion and paired-chain convergence identify inflammatory programs BCR lineage maturation links plasma programs to mutation and class switching Repertoire features benchmark diagnosis and clinical-state classification In Brief Gubatan et al. present a peripheral blood single-cell transcriptome and paired immune-receptor atlas across IBD and controls. Clone-aware analyses connect TCR expansion and sequence similarity to inflammatory programs, distinguish B-cell phenotype from lineage maturation, and link participant-level T–B covariation to an inferred ligand– receptor interactome. Machine learning models with repertoire features classify diagnosis, inflammatory status, and contemporaneous six-month treatment-response status.

Source: bioRxiv (Cold Spring Harbor Laboratory)

DOI: 10.64898/2026.09.20.753043