A210 ADLERCREUTZIA IS DEPLETED IN UC PATIENTS, EVEN BEFORE CLINICAL DIAGNOSIS, AND INVERSELY CORRELATES WITH FECAL ELASTOLYTIC ACTIVITY
Bibliographic record
Abstract
Abstract Background A combination of genetics, environmental, and immune factors contribute to the development of ulcerative colitis (UC). Host proteolytic imbalance has been reported in active UC. Preliminary results from our lab suggest microbial proteolytic activity is increased before as well as after onset of UC, and transfer of this activity to mice contributes to inflammation. Aims Our aim was to correlate the elastolytic activity of fecal samples from individuals at risk for IBD, before and after onset of ulcerative colitis, with their fecal microbiota profiles Methods We first investigated proteolytic activity in fecal samples from individuals at risk to develop UC (pre-UC, n=12) prior to disease onset and after UC diagnosis (post-UC, n=7) and matched healthy controls (n=66). Microbial community analysis was performed by sequencing the V4 region of the 16S rRNA gene region using Illumina MiSeq platform. Sequences were analyzed with QIIMEv1.9.0. We measured bacterial proteolytic activity, using a FITC-elastin assay. Results Microbial community analysis revealed that the overall diversity (both richness and evenness) in UC patients was decreased compared to healthy controls as well as pre-UC patients. The relative abundance of the genus Adlercreutzia was decreased by 3.1 fold in pre-UC patients compared to healthy controls and was further decreased in post-UC (3.8 fold). The presence of Adlercreutzia was also found to be negatively correlated (r=-0.47, p<0.0001) with elastolytic activity in stool supernatant, suggesting a possible protective role in the disease. Conclusions We found novel potentially protective bacteria, Adlercreutzia, which was depleted in UC patients, even before clinical diagnosis and correlated negatively with proinflammatory elastolytic activity described previously in IBD. The protective mechanisms are under investigation. On behalf of the CCC-GEM Project consortiumand Supported by a CCC GIA to EFV Funding Agencies CCC
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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 | 0.000 | 0.001 |
| 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 | 0.000 |
| 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".