Genotype-specific immune responses at the intestinal barrier predispose to colitis in mouse models of chronic granulomatous disease
Bibliographic record
Abstract
ABSTRACT: Chronic granulomatous disease (CGD) is an inborn error of immunity that is caused by defects in any 1 of the 5 subunits (gp91phox, p47phox, p22phox, p67phox, p40phox) that form the NAD phosphate oxidase complex 2 (NOX2) or in the chaperone protein essential for reactive oxygen species (ROS) that supports its assembly. These defects lead to severely reduced phagocyte-derived ROS production. Almost 50% of patients with CGD have inflammatory bowel disease (IBD) associated with dysbiosis, and the age of IBD onset may vary according to the CGD genotype. Although we previously demonstrated that the intestinal microbiota determines colitis susceptibility in CGD mice, the underlying mechanisms remain unknown. We hypothesized that NOX2 defects are associated with distinct intestinal microbiome signatures and immune responses, which impact colitis severity. Chemical colitis susceptibility was evaluated in 2 strains of CGD mice (gp91phox-/- and p47phox-/-) with distinct microbiotas from 2 different animal facilities, while also evaluating the impact of microbiota standardization and colitogenic microbiota transfer on mucosal immune responses at the intestinal barrier. Although p47phox-/- and gp91phox-/- mice that harbored a colitogenic microbiota had increased colitis severity, the intestinal epithelial cells from p47phox-/- mice produced more ROS, which was associated with increased NOX isoform gene expression. In contrast, gp91phox-/- mice had decreased mucin production and a mucosal immune response profile suggestive of increased inflammasome activation at the intestinal barrier when compared with control and p47phox-/- mice. Our findings suggest that the microbiota impacts colitis susceptibility in a CGD genotype-specific manner, thereby potentially explaining differences in the timing of IBD onset in patients with different CGD genotypes and identifying potential novel and personalized therapeutic targets.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".