Host-microbe multi-omics and succinotype profiling have prognostic value for future relapse in patients with inflammatory bowel disease
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 microbiom...
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2025-12-01
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| Series: | Gut Microbes |
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| Online Access: | https://www.tandfonline.com/doi/10.1080/19490976.2025.2450207 |
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| author | Jill O’Sullivan Shriram Patel Gabriel E. Leventhal Rachel S. Fitzgerald Emilio J. Laserna-Mendieta Chloe E. Huseyin Nina Konstantinidou Erica Rutherford Aonghus Lavelle Karim Dabbagh Todd Z. DeSantis Fergus Shanahan Andriy Temko Shoko Iwai Marcus J. Claesson |
| author_facet | Jill O’Sullivan Shriram Patel Gabriel E. Leventhal Rachel S. Fitzgerald Emilio J. Laserna-Mendieta Chloe E. Huseyin Nina Konstantinidou Erica Rutherford Aonghus Lavelle Karim Dabbagh Todd Z. DeSantis Fergus Shanahan Andriy Temko Shoko Iwai Marcus J. Claesson |
| author_sort | Jill O’Sullivan |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-1f17ad1c3f234fd68cd122d106f34782 |
| institution | Kabale University |
| issn | 1949-0976 1949-0984 |
| language | English |
| publishDate | 2025-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Gut Microbes |
| spelling | doaj-art-1f17ad1c3f234fd68cd122d106f347822025-01-15T12:22:04ZengTaylor & Francis GroupGut Microbes1949-09761949-09842025-12-0117110.1080/19490976.2025.2450207Host-microbe multi-omics and succinotype profiling have prognostic value for future relapse in patients with inflammatory bowel diseaseJill O’Sullivan0Shriram Patel1Gabriel E. Leventhal2Rachel S. Fitzgerald3Emilio J. Laserna-Mendieta4Chloe E. Huseyin5Nina Konstantinidou6Erica Rutherford7Aonghus Lavelle8Karim Dabbagh9Todd Z. DeSantis10Fergus Shanahan11Andriy Temko12Shoko Iwai13Marcus J. Claesson14School of Microbiology, University College Cork, Cork, IrelandSchool of Microbiology, University College Cork, Cork, IrelandPharmaBiome AG, Schlieren, Zurich, SwitzerlandSchool of Microbiology, University College Cork, Cork, IrelandSchool of Microbiology, University College Cork, Cork, IrelandSchool of Microbiology, University College Cork, Cork, IrelandSchool of Microbiology, University College Cork, Cork, IrelandDepartment of Informatics, Second Genome Inc, South San Francisco, California, USAAPC Microbiome Ireland, University College Cork, Cork, IrelandDepartment of Informatics, Second Genome Inc, South San Francisco, California, USADepartment of Informatics, Second Genome Inc, South San Francisco, California, USAAPC Microbiome Ireland, University College Cork, Cork, IrelandDepartment of Electrical and Electronic Engineering, University College Cork, Cork, IrelandDepartment of Informatics, Second Genome Inc, South San Francisco, California, USASchool of Microbiology, University College Cork, Cork, IrelandCrohn’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.https://www.tandfonline.com/doi/10.1080/19490976.2025.2450207Crohn’s diseaseulcerative colitisinflammatory bowel diseasegut microbiomehost-microbe interactionsmachine learning |
| spellingShingle | Jill O’Sullivan Shriram Patel Gabriel E. Leventhal Rachel S. Fitzgerald Emilio J. Laserna-Mendieta Chloe E. Huseyin Nina Konstantinidou Erica Rutherford Aonghus Lavelle Karim Dabbagh Todd Z. DeSantis Fergus Shanahan Andriy Temko Shoko Iwai Marcus J. Claesson Host-microbe multi-omics and succinotype profiling have prognostic value for future relapse in patients with inflammatory bowel disease Gut Microbes Crohn’s disease ulcerative colitis inflammatory bowel disease gut microbiome host-microbe interactions machine learning |
| title | Host-microbe multi-omics and succinotype profiling have prognostic value for future relapse in patients with inflammatory bowel disease |
| title_full | Host-microbe multi-omics and succinotype profiling have prognostic value for future relapse in patients with inflammatory bowel disease |
| title_fullStr | Host-microbe multi-omics and succinotype profiling have prognostic value for future relapse in patients with inflammatory bowel disease |
| title_full_unstemmed | Host-microbe multi-omics and succinotype profiling have prognostic value for future relapse in patients with inflammatory bowel disease |
| title_short | Host-microbe multi-omics and succinotype profiling have prognostic value for future relapse in patients with inflammatory bowel disease |
| title_sort | host microbe multi omics and succinotype profiling have prognostic value for future relapse in patients with inflammatory bowel disease |
| topic | Crohn’s disease ulcerative colitis inflammatory bowel disease gut microbiome host-microbe interactions machine learning |
| url | https://www.tandfonline.com/doi/10.1080/19490976.2025.2450207 |
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