Microbiota and metabolite-based prediction tool for colonic polyposis with and without a known genetic driver

Microbiota and metabolite-based prediction tool for colonic polyposis with and without a known genetic driver

Despite extensive investigations into the microbiome and metabolome changes associated with colon polyps and colorectal cancer (CRC), the microbiome and metabolome profiles of individuals with colonic polyposis, including those with (Gene-pos) and without (Gene-neg) a known genetic driver, remain co...

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Main Authors: Bryson W. Katona, Ashutosh Shukla, Weiming Hu, Thomas Nyul, Christina Dudzik, Alex Arvanitis, Daniel Clay, Michaela Dungan, Marina Weber, Vincent Tu, Fuhua Hao, Shuheng Gan, Lillian Chau, Anna M. Buchner, Gary W. Falk, David L. Jaffe, Gregory Ginsberg, Suzette N. Palmer, Xiaowei Zhan, Andrew D. Patterson, Kyle Bittinger, Josephine Ni
Format: Article
Language:English
Published: Taylor & Francis Group 2025-12-01
Series:Gut Microbes
Subjects:
Polyposis
microbiome
metabolome
biomarker
alanine
leucine
Online Access:https://www.tandfonline.com/doi/10.1080/19490976.2025.2474141
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Summary:Despite extensive investigations into the microbiome and metabolome changes associated with colon polyps and colorectal cancer (CRC), the microbiome and metabolome profiles of individuals with colonic polyposis, including those with (Gene-pos) and without (Gene-neg) a known genetic driver, remain comparatively unexplored. Using colon biopsies, polyps, and stool from patients with Gene-pos adenomatous polyposis (N = 9), Gene-neg adenomatous polyposis (N = 18), and serrated polyposis syndrome (SPS, N = 11), we demonstrated through 16S rRNA sequencing that the mucosa-associated microbiota in individuals with colonic polyposis is representative of the microbiota associated with small polyps, and that both Gene-pos and SPS cohorts exhibit differential microbiota populations relative to Gene-neg polyposis cohorts. Furthermore, we used these differential microbiota taxa to perform linear discriminant analysis to differentiate Gene-neg subjects from Gene-pos and from SPS subjects with an accuracy of 89% and 93% respectively. Stool metabolites were quantified via 1H NMR, revealing an increase in alanine in SPS subjects relative to non-polyposis subjects, and Partial Least Squares Discriminant Analysis (PLS-DA) analysis indicated that the proportion of leucine to tyrosine in fecal samples may be predictive of SPS. Use of these microbial and metabolomic signatures may allow for better diagnostric and risk-stratification tools for colonic polyposis patients and their families as well as promote development of microbiome-targeted approaches for polyp prevention.
ISSN:1949-0976
1949-0984

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