Novel immunoassays for detection of CUZD1 autoantibodies in serum of patients with inflammatory bowel diseases
Bibliographic record
Abstract
BACKGROUND: Pancreatic autoantibodies (PABs) are detected in patients with inflammatory bowel disease (IBD). Their prevalence is higher in Crohn's disease (CrD) than in ulcerative colitis (UC). Glycoprotein 2 (GP2) and, more recently, CUB and zona pellucida-like domain-containing protein 1 (CUZD1) have been identified as target autoantigens of PAB. The clinical utility of CUZD1 autoantibodies has only recently been assessed by indirect immunofluorescence (IIF) assays. In this study, we developed and validated novel immunoassays for the detection of CUZD1 autoantibodies. METHODS: Recombinant CUZD1 protein was utilized as a solid-phase antigen for the development of two immunoassays for the detection of IgG and IgA CUZD1 autoantibodies. Serum samples from 100 patients with CrD, 100 patients with UC, 129 patients assessed for various autoimmune diseases (vADs) and 50 control individuals were analyzed. RESULTS: Two immunofluorometric assays for the detection of IgG and IgA CUZD1-specific antibodies were developed. CUZD1 autoantibodies were detected in 12.5% (25/200) IBD patients, including 16% of patients with CrD and in 9% of patients with UC (CrD vs. UC, p<0.05), compared with 3.1% (4/129) patients suspected of having vADs (CrD vs. ADs, p<0.05; UC vs. ADs, p=0.08). CUZD1 autoantibody positivity was not found to be related to disease location, age of disease onset or disease phenotype. CONCLUSIONS: This is the first study to describe novel IgA and IgG CUZD1 autoantibody enzyme-linked immunosorbent assay. These immunoassays agree well with standard IIF techniques and can be utilized in multicenter studies to investigate the diagnostic and clinical utility of CUZD1 autoantibodies.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".