P700 The GEM Project: Stool metabolomic profile is associated with microbiome risk score and with future onset of Crohn’s disease in healthy first-degree relatives
Bibliographic record
Abstract
Abstract Background We recently developed and validated a microbial composition-based risk score (MRS) that predicts future risk of Crohn’s disease (CD) development among healthy first-degree relatives (FDR) of CD patients. We hypothesized that stool metabolomic profiles may mediate the effect of microbiome-based risk on future onset of CD. Methods Healthy FDRs of CD patients were recruited as part of the CCC-GEM Project. Stool metabolomics data were available in the nested case-control cohort (a subset of CCC-GEM cohort) whereby FDRs who later developed CD (n=56) were matched approximately 1:1 by age, sex, follow-up duration, and geographical location with control FDRs remaining healthy (n=66). Stool metabolomics were assessed using the Metabolon’s DiscoveryHD4™ platform, and the stool microbiome characterized by 16s rDNA amplicon sequencing. A multivariable conditional logistic regression model was evaluated on the disease development as a function of individual stool metabolites. Spearman correlation evaluated the rank values between stool metabolites and the MRS. Results 122 healthy FDRs (median age 15 years, 60% female) were followed for a median 5.2 years. Among 1,029 stool metabolites that were analyzed, 79 were associated with future risk of CD (p<0.05); however, none remained significant after adjustment for false-discovery rate. Considering the exploratory nature of this study with limited sample size, we focused on the top seven metabolites associated with CD onset (p<0.01). Of these, two stool metabolites (dimethylglycine, methylmyristate) were associated with increased risk of CD onset while five (cytosine, guanine, cytidine, hydroxyglutarate, nervonate) were associated with decreased risk of CD development. The two metabolites positively associated with CD onset were also positively correlated with the MRS, while the five metabolites negatively associated with CD onset, were also negatively correlated with the MRS. Meanwhile, 24 stool metabolites had significant correlation with MRS (false-discovery rate-corrected p<0.2). Among those, a total of four stool metabolites (cytosine, guanine, methymyristate, cytidine) overlapped with the top seven stool metabolites associated with CD onset. Conclusion Changes in stool metabolite profiles may predict future risk of CD. A subset of these metabolites has significant correlation with the MRS with consistent direction of effect. This may suggest that these particular stool metabolites mediate the putative effects of the gut microbiome on CD risk. Further validation in the entire GEM cohort is warranted.
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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 | 0.004 |
| 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".