Background & aims: Despite the success of biological therapies in treating inflammatory bowel disease, managing patients remains challenging due to the absence of reliable predictors of therapy response.
Methods: In this study, we prospectively sampled 2 cohorts of patients with inflammatory bowel disease receiving the anti-integrin α4β7 antibody vedolizumab. Samples were subjected to mass cytometry; single-cell RNA sequencing; single-cell variable, diversity, and joining sequencing; serum proteomics; and multidimensional flow cytometry to comprehensively assess vedolizumab-induced immunologic changes in the peripheral blood and their potential associations with treatment response.
Results: Vedolizumab treatment led to substantial alterations in the abundance of circulating immune cell lineages and modified the T-cell receptor diversity of gut-homing CD4+ memory T cells. Through integration of multimodal parameters and machine learning, we identified a significant increase in proliferating CD4+ memory T cells among nonresponders before treatment compared with responders. This predictive T-cell signature demonstrated an activated T-helper 1/T-helper 17 cell phenotype and exhibited elevated levels of integrin α4β1, potentially making these cells less susceptible to direct targeting by vedolizumab.
Conclusions: These findings provide a reliable predictive classifier with significant implications for personalized inflammatory bowel disease management.
Keywords: CD4(+) Memory T Cells; Cell Migration and Homing; Inflammatory Bowel Disease; Integrin α4β7; Machine Learning; Single-Cell Profiling; Therapy Response; Vedolizumab.
Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.