TY - JOUR
T1 - Host-microbe multi-omics and succinotype profiling have prognostic value for future relapse in patients with inflammatory bowel disease
AU - O’Sullivan, Jill
AU - Patel, Shriram
AU - Leventhal, Gabriel E.
AU - Fitzgerald, Rachel S.
AU - Laserna-Mendieta, Emilio J.
AU - Huseyin, Chloe E.
AU - Konstantinidou, Nina
AU - Rutherford, Erica
AU - Lavelle, Aonghus
AU - Dabbagh, Karim
AU - DeSantis, Todd Z.
AU - Shanahan, Fergus
AU - Temko, Andriy
AU - Iwai, Shoko
AU - Claesson, Marcus J.
N1 - Publisher Copyright:
© 2025 The Author(s). Published with license by Taylor & Francis Group, LLC.
PY - 2025
Y1 - 2025
N2 - Crohn’s disease (CD) and ulcerative colitis (UC) are chronic relapsing inflammatory bowel disorders (IBD), the pathogenesis of which is uncertain but includes genetic susceptibility factors, immune-mediated tissue injury and environmental influences, most of which appear to act via the gut microbiome. We hypothesized that host-microbe alterations could be used to prognostically stratify patients experiencing relapses up to four years after endoscopy. We therefore examined multiple omics data, including published and new datasets, generated from paired inflamed and non-inflamed mucosal biopsies from 142 patients with IBD (54 CD; 88 UC) and from 34 control (non-diseased) biopsies. The relapse-predictive potential of 16S rRNA gene and transcript amplicons (standing and active microbiota) were investigated along with host transcriptomics, epigenomics and genetics. While standard single-omics analysis could not distinguish between patients who relapsed and those that remained in remission within four years of colonoscopy, we did find an association between the number of flares and a patient’s succinotype. Our multi-omics machine learning approach was also able to predict relapse when combining features from the microbiome and human host. Therefore multi-omics, rather than single omics, better predicts relapse within 4 years of colonoscopy, while a patient’s succinotype is associated with a higher frequency of relapses.
AB - Crohn’s disease (CD) and ulcerative colitis (UC) are chronic relapsing inflammatory bowel disorders (IBD), the pathogenesis of which is uncertain but includes genetic susceptibility factors, immune-mediated tissue injury and environmental influences, most of which appear to act via the gut microbiome. We hypothesized that host-microbe alterations could be used to prognostically stratify patients experiencing relapses up to four years after endoscopy. We therefore examined multiple omics data, including published and new datasets, generated from paired inflamed and non-inflamed mucosal biopsies from 142 patients with IBD (54 CD; 88 UC) and from 34 control (non-diseased) biopsies. The relapse-predictive potential of 16S rRNA gene and transcript amplicons (standing and active microbiota) were investigated along with host transcriptomics, epigenomics and genetics. While standard single-omics analysis could not distinguish between patients who relapsed and those that remained in remission within four years of colonoscopy, we did find an association between the number of flares and a patient’s succinotype. Our multi-omics machine learning approach was also able to predict relapse when combining features from the microbiome and human host. Therefore multi-omics, rather than single omics, better predicts relapse within 4 years of colonoscopy, while a patient’s succinotype is associated with a higher frequency of relapses.
KW - Crohn’s disease
KW - gut microbiome
KW - host-microbe interactions
KW - inflammatory bowel disease
KW - machine learning
KW - ulcerative colitis
UR - https://www.scopus.com/pages/publications/85215098491
U2 - 10.1080/19490976.2025.2450207
DO - 10.1080/19490976.2025.2450207
M3 - Article
C2 - 39812341
AN - SCOPUS:85215098491
SN - 1949-0976
VL - 17
JO - Gut Microbes
JF - Gut Microbes
IS - 1
M1 - 2450207
ER -