Changes in the gut microbiome associated with infliximab in patients with bipolar disorder
Bibliographic record
Abstract
OBJECTIVES: Available information exists supporting the gut-brain axis, but additional information is needed to explore how the gut microbiome changes when exposed to mood disorder treatments. We sought to explore the effects of a novel treatment for bipolar disorder (BD), infliximab, on the gut microbiome. METHODS: Participants with a primary diagnosis of BD (n = 15) who participated in a 12-week, randomized placebo-controlled trial evaluating the efficacy of adjunctive infliximab in the treatment of BD were recruited and followed. Stool samples were collected prior to randomization and at 12 weeks. 16S rRNA sequencing was employed in order to analyze the gut microbial community profile. RESULTS: A total of 17 participants were randomized to infliximab (n = 9; mean [SD] age, 47.6 [10.3] years; 8 female) or to placebo (n = 8; mean [SD] age, 45.9 [10.7] years; 7 female) but two participants from the infliximab group were lost to follow-up post randomization. Across all time points, there were no differences in the diversity on either Shannon or Simpson's Diversity indices. Comparison of Aitchison distances revealed a lack of clustering of the microbiota by time point, but did reveal a small overall effect of treatment that was not significantly different at individual time points. There were also no effects of either time or treatment on differential abundance at either the amplicon sequence variant or genus level. CONCLUSIONS: These observations indicate that no community-wide changes in the microbiota diversity and profile were detected after the use of infliximab treatment.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".