S1465 Gut Microbiome Dysbiosis as a Diagnostic Signature in Early Inflammatory Bowel Disease
Bibliographic record
Abstract
Introduction: Inflammatory bowel disease (IBD), encompassing ulcerative colitis (UC) and Crohn’s disease (CD), is a persistent inflammatory condition of the digestive tract that is increasing in prevalence worldwide. Early diagnosis remains a challenge, limiting timely intervention. Growing research indicates that gut microbial dysbiosis may precede clinical onset, offering promise as a non-invasive biomarker. This review aims to assess microbiome alterations during early or preclinical IBD. Methods: We conducted a systematic review on the basis of Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. As part of this process, we thoroughly searched 3 major databases-Embase, PubMed, and the Cochrane library for studies that were published between 2018 and 2024. Included studies examined gut microbiota in early or newly diagnosed IBD patients compared to healthy controls. We individually analysed the studies, collected relevant information, and evaluated their quality utilizing the Newcastle-Ottawa Scale and the Cochrane Risk of Bias tool. Results: Twenty studies involving 4,689 participants (2,713 IBD patients, 1,976 controls) met inclusion criteria. Seventeen studies reported significantly reduced alpha diversity in early IBD, with one meta-analysis noting a combined mean difference of −0.45 (95% CI: −0.65 to −0.29; P < 0.001). Beta diversity analyses revealed distinct microbial community structures in IBD groups (P < 0.01 in 12 studies). Taxonomic analyses showed consistent depletion of beneficial commensals, including Faecalibacterium prausnitzii, Roseburia, and Bacteroidetes, in ≥14 studies. Fourteen studies reported enrichment of potentially pathogenic taxa such as Escherichia coli and Ruminococcus gnavus. Furthermore, twelve studies observed a decreased presence of Blautia and Coprococcus, which yield short-chain fatty acids (SCFAs), in early Crohn’s disease, with statistical significance (P < 0.05). Conclusion: This review highlights consistent patterns of microbial dysbiosis in early IBD. The reduction in alpha diversity, loss of anti-inflammatory taxa, and increase in pathobionts precede symptom onset, suggesting their utility as early diagnostic markers. Identifying these microbial signatures offers potential for non-invasive, preclinical screening and risk stratification strategies. Additional longitudinal research is necessary to confirm these biomarkers and incorporate microbiome profiling into individualized preventive healthcare.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.007 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".