Scientists have identified a range of gut bacteria and metabolites that could dramatically improve the detection and treatment of gastrointestinal diseases (GIDs), including gastric cancer (GC), colorectal cancer (CRC), and inflammatory bowel disease (IBD).
The study found distinct microbiome and metabolome “signatures” for each disease, as well as several biomarkers that overlap between conditions — opening the door to earlier, less invasive diagnosis and more personalised treatment.
Researchers from the University of Birmingham Dubai, the University of Birmingham (UK), and University Hospitals Birmingham NHS Foundation Trust analysed patient microbiome and metabolome data using advanced machine learning and AI.
Their cross-disease modelling revealed that algorithms trained on GC data could accurately identify IBD biomarkers, while CRC-trained models could detect GC biomarkers with high precision.
“Current methods like endoscopy and biopsies are effective but invasive, costly, and can miss early-stage disease,” said lead co-author Dr Animesh Acharjee. “Our analysis highlights shared disease mechanisms and identifies key microbial and metabolic biomarkers that could make diagnosis faster, easier, and more accurate.”
Key findings:
– Gastric cancer: Enrichment of bacteria from the Firmicutes, Bacteroidetes, and Actinobacteria groups, alongside changes in metabolites such as dihydrouracil and taurine — some also linked to IBD.
– Colorectal cancer: Significant presence of Fusobacterium and Enterococcus, plus metabolites like isoleucine and nicotinamide — overlapping in part with GC markers.
– Inflammatory bowel disease: Increased Lachnospiraceae bacteria, and metabolites such as urobilin and glycerate — some involved in cancer-related pathways.
Computer simulations of gut microbial growth and metabolite flux revealed substantial metabolic differences between healthy and diseased states, further underscoring the potential of these biomarkers for clinical use.
The team believes their approach could lead to the creation of “universal” diagnostic tools for multiple GIDs. They plan to test the biomarkers in larger, more diverse patient groups and explore their relevance in other related diseases.
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The study is published in Journal of Translational Medicine.
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