Association of Anti-glycan Antibodies and Inflammatory Bowel Disease Course
Bibliographic record
Abstract
BACKGROUND AND AIMS: The usefulness of anti-glycan antibodies alone or combined with anti-Saccharomyces cerevisiae [ASCA] or perinuclear antineutrophil cytoplasmic [pANCA] antibodies for diagnosis of inflammatory bowel disease [IBD], differentiation between Crohn's disease [CD] and ulcerative colitis [UC], disease stratification including IBD phenotype, and also for determination of the course of the disease, remain unclear. METHODS: A large panel of serological anti-glycan carbohydrate antibodies, including anti-mannobioside IgG antibodies [AMCA], anti-chitobioside IgA [ACCA], anti-laminaribioside IgG antibodies [ALCA], anti-laminarin [anti-L] and anti-chitine [anti-C] were measured in the serum from a cohort of 195 patients with IBD] [107 CD and 88 UC]. The respective accuracy of isolated or combined markers for diagnosis, disease differentiation, stratification disease phenotype, and severity of the disease course, defined by a wide panel of criteria obtained from the past medical history, was assessed. RESULTS: The positivity of at least one anti-glycan antibody was detected in a significant higher proportion of CD and UC compared with healthy controls [p < 0.0001 and p < 0.0007, respectively]. Whereas ASCA and ANCA antibody status had the highest efficacy to be associated with CD in comparison with UC (area under receiver operating characteristic curve [AUROC] = 0.70 for each], the adjunction of anti-laminarin antibody substantially improved the differentiation between CD and UC [AUROC = 0.77]. Titres of ACCA [> 51U/ml] and anti-laminarin [> 31U/ml] were significantly linked with a higher association with steroid dependency (odds ratio [OR] =2.0 [1.0-4.0], p = 0.03 and OR = 2.4 [1.1-5.2], p = 0.02, respectively]. We further defined the respective performance of anti-glycan antibodies to discriminate between patients with severe or not severe CD and UC course and determined the associated optimal cut-off values: severe CD course was significantly more likely in case of AMCA > 77U/ml [OR = 4.3; p = 0.002], ASCA > 63U/ml [OR = 3.5; p < 0.009] and at a lesser degree ACCA > 50U/ml [OR = 2.8; p < 0.02] and severe UC course was significantly associated with AMCA > 52U/ml [OR = 3.4; p = 0.04] and ACCA > 25U/ml [OR = 3.0; p < 0.04]. CONCLUSIONS: Anti-glycan antibodies are valuable serological markers, especially AMCA antibodies that may help clinicians to promptly classify patients into high risk for severe disease.
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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".