Urgent.News

What's breaking now, across thousands of outlets.

Health & Medicine

Concerted changes in the pediatric single-cell intestinal ecosystem before and after anti-TNF blockade

Crohn’s disease is an inflammatory bowel disease (IBD) commonly treated through anti-TNF blockade. However, most patients still relapse and inevitably progress. Comprehensive single-cell RNA-sequencing (scRNA-seq) atlases have largely sampled patients with established treatment-refractory IBD, limiting our understanding of which cell types, subsets, and states at diagnosis anticipate disease…

Crohn's disease, an inflammatory bowel disorder, is often managed through anti-TNF blockade treatment. Despite this approach, many patients still experience relapse and disease progression. A recent study utilized comprehensive single-cell RNA-sequencing (scRNA-seq) atlases to examine pediatric patients with Crohn's disease (pediCD), comparing them to repeat biopsies after treatment and healthy controls with functional gastrointestinal disorders (FGIDs).

By analyzing 201,883 baseline single-cell transcriptomes, researchers employed a principled and unbiased clustering method, ARBOL, to distinguish cell types and states in pediCD, FGID, and treatment-naive states. The findings revealed that treatment-naive pediatric CD and FGID share similar broad cell type composition, but treatment-naive pediCD exhibits significant differences in cell subsets and states compared to FGID.

Through the integration of scRNA-seq analysis with clinical metadata, the study identified a vector of T cell, innate lymphocyte, myeloid, and epithelial cell states in pediCD-TIME samples, which can predict disease severity and response to anti-TNF treatment. By comparing on-treatment biopsies from pediatric patients with those from adult Crohn's disease patients, researchers found that anti-TNF treatment pushes the pediatric cellular ecosystem towards an adult, more treatment-refractory state.

The study concludes that understanding baseline cell states in pediatric CD patients can help predict disease trajectories.

Written by urgent.news from eLife's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.

Read the original at elifesciences.org →

More in Health & Medicine

More from Tuesday 1 September →