A51 ROLE OF GUT MICROBIOTA IN THE EPISODIC NATURE OF SYMPTOMS IN IRRITABLE BOWEL SYNDROME
Bibliographic record
Abstract
Abstract Background Irritable bowel syndrome (IBS) is a complex functional gastrointestinal disorder with likely heterogenous pathophysiology, multiple symptoms, and comorbidities. Growing evidence shows that the gut microbiota composition and function are altered in IBS patients. However, identifying the critical drivers of clinical expression remains challenging due to the episodic occurrence of IBS symptoms, the inherent variability in composition of gut microbiota across individuals, and high sensitivity of gut microbiota to dietary and environmental cues. Aims To identify whether changes in gut microbiota composition accompany or, predict the occurrence of symptoms. Methods 28 IBS patients (IBS-D n=20, IBS-C n=8) and 10 healthy controls (HC) were followed longitudinally for 25 weeks, collecting stool samples, and recording their symptoms weekly. Stool microbiota profiles were assessed by 16S rRNA gene sequencing using Illumina platform. The sequences were preprocessed, filtered, and annotated using DADA2 and phyloseq pipelines; statistical analyses were performed using FactomineR and microbiomeanalyst packages in R. Statistical significance was set at p<0.05. Results Multifactorial analysis of clinical data classified 950 samples in 6 clusters. Distribution of samples among the clusters was based on Bristol stool scale defining symptomatic periods (scores <3 and >4 indicating abnormal stool) and asymptomatic periods (scores 3 or 4), with several gut and mood symptoms varying significantly between the two categories. IBS-D patients, but not IBS-C patients presented with changes in symptoms severity, such as pain, diarrhea, constipation, and anxiety during the symptomatic periods. Depression scores were, however, higher in IBS-C compared to IBS-D patients. In contrast, immune makers such as fecal b-defensin-2 and calprotectin were higher during asymptomatic periods in IBS-D, but not in IBS-C patients. Bacterial diversity profiles differed among IBS patients (IBS-D and IBS-C) and HC, namely Shannon index and Bray-Curtis distance, but they did not change significantly between the symptomatic and asymptomatic periods within each subtype. Despite this, several bacterial taxa unique to each cluster were identified using linear mixed models. Conclusions Our results demonstrate the need to study patterns of co-occurrence of IBS symptoms and their severity during symptomatic and asymptomatic periods to better understand the role of identified bacterial taxa in the symptom generation. Identifying their temporal changes and cross-feeding patterns in individual patients will shed light on the underlying mechanistic role of gut microbiota in IBS, which might be otherwise obscured by group generalizations. Funding Agencies CIHR
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".