P334 The longitudinal analysis of fecal microbiota in response to ustekinumab treatment in patients with Crohn’s disease
Bibliographic record
Abstract
Abstract Background Emerging evidence supports that treatment of Crohn’s disease (CD) can alter the intestinal microbiota, which can play a significant role in the pathogenesis and therapeutic outcomes of CD. Ustekinumab (UST) has also been reported to modify the intestinal microbiota during a short-term treatment period. However, the long-term impact of UST treatment on the intestinal microbiota has rarely been studied. Methods We prospectively enrolled patients with CD who were planning to start UST treatment and collected fecal samples before (baseline) and after UST administration at week 20 and week 52. Fecal bacterial taxonomic diversity and composition were analyzed through 16S ribosomal ribonucleic acid (rRNA) gene amplicon sequencing. The difference in the intestinal microbiota between clinical remitters and non-remitters defined by Crohn’s disease activity index (CDAI) was investigated, along with the longitudinal changes in the intestinal microbiota. Results A total of 124 fecal samples acquired from 43 patients were analyzed (median age 30 years, male 76.7%, median CDAI at baseline 183.2). Clinical remission was observed in 34.9% (n=15/43), 61.0% (n=25/41), and 60.0% (n=24/40) at baseline, week 20, and week 52, respectively. Shannon’s alpha diversity index increased significantly at week 20 and week 52 compared to baseline (both P<0.001). Compared to non-remitters, a significant increase of Shannon’s alpha diversity index was also observed among remitters (P=0.044) across all time points, while no significant difference was noted at each time point. The beta diversity analysis based on the Bray-Curtis distance revealed a significant difference among remitters at week 20 (P=0.027), however, there were no significant differences at other time points. Compared to the baseline, the abundance of the Firmicutes phylum was higher at week 20 (P=0.048) and 52 (P=0.019). The Lactobacillus genus (P=0.042), and Lactobacillus gasseri group (P=0.016) were significantly less abundant in remitters, while the Lachnospiraceae family (P=0.017) was more abundant in remitters. At week 20, Bifidobacterium genus (P=0.027) and Bifidobacterium pseudolongum group (P=0.040) were significantly more abundant in remitter while the Lactobacillus genus was less abundant (P=0.009) in remitter (Figure 1). Conclusion The alteration of fecal microbiota after UST treatment may have the potential to serve as a biomarker for predicting clinical remission. Financial Support This study was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (NRF-2021R1A2C2095096), the grant (2020IT0012) from the Asan Institute for Life Sciences, Seoul, Korea and the grant (CR 2017-4) from CELLTRION PHARM, Inc., Chungcheongbuk-do, Korea.
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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 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".