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Record W4318539792 · doi:10.1093/ecco-jcc/jjac190.0448

P318 Protein FingerPrint assays reflecting neutrophil activity, mucosal damage, and tissue fibrosis are surrogate biomarkers for mucosal healing in pediatric Crohn’s disease

2023· article· en· W4318539792 on OpenAlexaff
Joachim Høg Mortensen, Gili Focht, Martin Pehrsson, A M Griffiths, Marta Sorokina Alexdóttir, Ahmad Quteineh, Peter Church, R Baldassano, Joshua R. Silverstein, M.A. Karsdal, Deb Turner

Bibliographic record

VenueJournal of Crohn s and Colitis · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammatory Bowel Disease
Canadian institutionsHospital for Sick Children
Fundersnot available
KeywordsMedicineUlcerative colitisGastroenterologyCrohn's diseaseFibrosisInflammatory bowel diseaseVisual analogue scaleInternal medicineBiomarkerColitisImmunohistochemistryInflammationPathologyDiseaseImmunologyBiologySurgery

Abstract

fetched live from OpenAlex

Abstract Background Mucosal healing (MH) has become a treatment goal for inflammatory bowel disease (IBD), especially for ulcerative colitis. However, MH is less feasible to assess frequently in patients with Crohn’s disease (CD). In this study, we investigated Protein Fingerprint Assays (PFA) of collagen degradation and formation, and neutrophil and macrophage activity markers in the ImageKids study as non-invasive markers of MH. Methods This is a proteomics planned sub-study of the multi-center prospective ImageKids study which included serum samples from children with CD (n=178) undergoing MRE and ileocolonoscopy concurrently (ImageKids study: NCT01881490). Serum from healthy age and gender-matched controls were obtained from BioIVT (n=83). PFA panel for mucosal damage (C1M, C3M, C4M, C6M, ELP-3), Immune cell activity panel (CPa9-HNE, VICM, C4G), and tissue fibrosis panel (PRO-C1, PRO-C3, PRO-C4, PRO-C5, PRO-C6, PRO-C11, PRO-C22) were determined. MH was classified as having an SES-CD score of 0 and global radiologist assessment of inflammation in the MRE of 0, using a visual analogue scale (VAS) 0-100mm, and mucosal damage (MD) was defined as having SES-CD or MRE VAS>0. Spearman rho correlations, one-way ANOVA with Tukey correction, and receiver operator characteristics (ROC) curves were applied for statistical analysis. Results Some of the previous biomarkers demonstrated to correlate with the SES-CD score and ulcer size (C1M, C3M, C6M, PRO-C4, VICM, PRO-C1, PRO-C3). CPa9-HNE, ELP-3, and PRO-C22 also correlate with the SES-CD score (table 1). The combined SES-CD and MRE VAS score of MH correlated positively with CPa9-HNE (r=0.30, p<0.0001), VICM (r=0.39, p<0.0001), C1M (r=0.29, p=0.0001), C3M (r=0.22, p=0.0022), C6M (r=0.35 p<0.0001), PRO-C4 (r=0.2, p<0.0001), PRO-C22 (r=0.32, p<0.0001), (figure 1 and 2) and showed significantly lower serum levels in pCD patients with MH compared to patients with mild, moderate, or severe mucosal damage (p<0.001) (figure 2). PRO-C3 correlated negatively with the combined SES-CD and MRE VAS score (r=-0.17, p=0.0211). These PFA biomarkers were combined in a multivariate regression model, demonstrating increased accuracy to identify patients in MH healing compared to the individual biomarkers (p<0.001, MH vs. MD: AUC=0.82 [CI:0.69-0.95), MH+Mild MD vs. moderate+severe MD: AUC=0.77 [0.70-0.84], (figure 3). Conclusion PFA biomarkers of Neutrophil activity (CPa9-HNE), Macrophage activity (VICM), mucosal damage (C1M, C3M, C4M, C6M, ELP-3), and tissue fibrosis (PRO-C3, PRO-C22) are potential surrogate biomarkers for identifying pCD patients with mucosal healing and for monitoring of mucosal damage and stenosis.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.017
GPT teacher head0.292
Teacher spread0.274 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations1
Published2023
Admission routes1
Has abstractyes

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