A154 PROTEOMIC IDENTIFICATION OF INFLAMMATORY AND FIBROSTENOTIC BLOOD SERUM BIOMARKERS IN CROHN’S DISEASE
Bibliographic record
Abstract
Abstract Background Crohn’s disease (CD) is an incurable relapsing-remitting inflammatory bowel disease (IBD) where patients may experience bowel damage with symptoms such as abdominal pain, chronic diarrhea, extraintestinal manifestations and life-long disability. CD is heterogeneous with three distinct phenotypes including a stricturing phenotype marked by intestinal fibrosis. This fibrotic morphology is generally more unresponsive to drug treatment; delaying a patient’s remission, control of the disease and often requiring surgical intervention. Thus, early and accurate identification of fibrostenosis in CD is important to optimize patient treatment and predict response to therapy. Aims The aim of our study is to distinguish inflammatory and intestinal fibrostenosis in CD patients using serum protein biomarkers. Methods Blood sera from 17 inflammatory and 17 fibrostenotic CD patients were collected. The phenotypic classification was confirmed by intestinal ultrasound and endoscopy. Samples were subjected to Shotgun Proteomics, an unbiased proteomics approach that allows for relative protein quantification. Proteins from each condition were isotopically labelled with formaldehyde (light +28 Da and heavy +34 Da), pooled and digested with trypsin. Following liquid chromatography and tandem mass spectrometry, peptides were then identified by MaxQuant software with a false discovery rate of 1%. Excel (Microsoft), Prism (Graphpad) and Metascape software were used for data filtering and analysis. Results Proteomic processing allowed for the identification of novel protein biomarkers in the inflammatory and stricture CD phenotypes. Inflammation was correlated with activation of the complement pathway and fatty acid metabolism; marked by increased levels of immunoglobulin gamma 4 chain (IGHG4), mitochondrial creatinine kinase (CKMT1), apolipoprotein A (LPA) and glutathione peroxidase 3 (GPX3) proteins. Fibrostenosis showed no distinct metabolic pathway, but an elevated expression of SWI/SNF-related matric associated actin (SMARCA5), haptoglobin related protein (HPR), immunoglobulin kappa and immunoglobulin heavy constant proteins. Conclusions Our data indicate that inflammation and strictures in CD may be driven by distinct signaling pathways. We identified specific protein signatures for the two phenotypes, which may aid in predicting those who are at risk of developing strictures and in the development of phenotype-specific treatment for CD patients. Future validation of these proteins will be performed to assess this unique protein profile. Funding Agencies McCaig Institute for Bone and Joint Health
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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 | 0.001 |
| 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".