Integrated Analysis of Biopsies from Inflammatory Bowel Disease Patients Identifies SAA1 as a Link between Mucosal Microbes with T H 17 and T H 22 Cells

Mei San Tang, Rowann Bowcutt, Jacqueline M. Leung, Martin J. Wolff, Uma M. Gundra, David Hudesman, Lisa B. Malter, Michael A. Poles, Lea Ann Chen, Zhiheng Pei, Antonio G. Neto, Wasif M. Abidi, Thomas Ullman, Lloyd Mayer, Richard A. Bonneau, Ilseung Cho, Png Loke

Research output: Contribution to journalArticlepeer-review

Abstract

Background: Inflammatory bowel diseases (IBD) are believed to be driven by dysregulated interactions between the host and the gut microbiota. Our goal is to characterize and infer relationships between mucosal T cells, the host tissue environment, and microbial communities in patients with IBD who will serve as basis for mechanistic studies on human IBD. Methods: We characterized mucosal CD4 + T cells using flow cytometry, along with matching mucosal global gene expression and microbial communities data from 35 pinch biopsy samples from patients with IBD. We analyzed these data sets using an integrated framework to identify predictors of inflammatory states and then reproduced some of the putative relationships formed among these predictors by analyzing data from the pediatric RISK cohort. Results: We identified 26 predictors from our combined data set that were effective in distinguishing between regions of the intestine undergoing active inflammation and regions that were normal. Network analysis on these 26 predictors revealed SAA1 as the most connected node linking the abundance of the genus Bacteroides with the production of IL17 and IL22 by CD4 + T cells. These SAA1-linked microbial and transcriptome interactions were further reproduced with data from the pediatric IBD RISK cohort. Conclusions: This study identifies expression of SAA1 as an important link between mucosal T cells, microbial communities, and their tissue environment in patients with IBD. A combination of T cell effector function data, gene expression and microbial profiling can distinguish between intestinal inflammatory states in IBD regardless of disease types.

Original languageEnglish (US)
Pages (from-to)1544-1554
Number of pages11
JournalInflammatory Bowel Diseases
Volume23
Issue number9
DOIs
StatePublished - Sep 1 2017

Keywords

  • IBD
  • SAA1
  • mucosal healing
  • supervised learning
  • systems biology

ASJC Scopus subject areas

  • Immunology and Allergy
  • Gastroenterology

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