ArticleInflammatory bowel diseases2013
Combined serological, genetic, and inflammatory markers differentiate non-IBD, Crohn's disease, and ulcerative colitis patients.
Article in Inflammatory bowel diseases, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 61 papers.
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Who cites it
61 citing papers in PubMed, 123 citations in OpenAlex.
- Serological profiling of Crohn's disease and ulcerative colitis patients reveals anti-microbial antibody signatures.World journal of gastroenterology · 2022Trial
- JNK2 Is a Stress Integrator Driving Atrial Fibrillation Pathogenesis in Aging via Gut-Heart Crosstalk.Circulation · 2026Article
- Serum proteomics in paediatric inflammatory bowel disease from a case-control study: biomarker discovery and ulcerative colitis-Crohn's disease differentiation.EBioMedicine · 2026Article
- Anti-OmpC antibodies in Crohn's disease and ulcerative colitis: evidence from a systematic review and meta-analysis.Crohn's & colitis 360 · 2026Article
- Serum Anti-<italic>Saccharomyces cerevisiae</italic> Antibody Is Associated with Disease Severity in Patients with Primary Sclerosing Cholangitis.Digestive diseases (Basel, Switzerland) · 2026Article
- Resistant Starch and Microbiota-Derived Secondary Metabolites: A Focus on Postbiotic Pathways in Gut Health and Irritable Bowel Syndrome.International journal of molecular sciences · 2025Review
- Artificial intelligence in inflammatory bowel disease.Saudi journal of gastroenterology : official journal of the Saudi Gastroenterology Association · 2025Review
- Diagnostic Methods and Biomarkers in Inflammatory Bowel Disease.Diagnostics (Basel, Switzerland) · 2025Review
- Article
- Enhancing Calprotectin's Predictive Power as a Biomarker of Endoscopic Activity in Ulcerative Colitis: A Machine Learning Use Case.Biomedicines · 2024Article
- Noninvasive Stool RNA Test Approximates Disease Activity in Patients With Crohn's Disease.Gastro hep advances · 2024Article
- Profiling the inflammatory bowel diseases using genetics, serum biomarkers, and smoking information.iScience · 2023Article
- Performance of Machine Learning Algorithms for Predicting Disease Activity in Inflammatory Bowel Disease.Inflammation · 2023Article
- Mass-Cytometry-Based Quantification of Global Histone Post-Translational Modifications at Single-Cell Resolution Across Peripheral Immune Cells in IBD.Journal of Crohn's & colitis · 2023Article
- The effect of olsalazine of chinese generic drugs on ulcerative colitis induced by dextran sulfate sodium salt in BALB/c mice.Acta cirurgica brasileira · 2023Article
- Serological Biomarker-Based Machine Learning Models for Predicting the Relapse of Ulcerative Colitis.Journal of inflammation research · 2023Article
- Diagnosis and Monitoring of Ulcerative Colitis.Clinics in colon and rectal surgery · 2022Review
- Article
- Inflammatory bowel disease biomarkers.Medicinal research reviews · 2022Review
- Machine Learning Prediction Model for Inflammatory Bowel Disease Based on Laboratory Markers. Working Model in a Discovery Cohort Study.Journal of clinical medicine · 2021Article
1 more citing papers are in PubMed but not listed here.
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Authors and funding
11 authors at 3 institutions in 2 countries.
Funding
Abstract
backgroundPrevious studies have demonstrated that serological markers can assist in diagnosing inflammatory bowel disease (IBD). In this study, we aim to build a diagnostic tool incorporating serological markers, genetic variants, and markers of inflammation into a computational algorithm to examine patterns of combinations of markers to (1) identify patients with IBD and (2) differentiate patients with Crohn's disease (CD) from ulcerative colitis (UC).
methodsIn this cross-sectional study, patient blood samples from 572 CD, 328 UC, 437 non-IBD controls, and 183 healthy controls from academic and community centers were analyzed for 17 markers: 8 serological markers (ASCA-IgA, ASCA-IgG, ANCA, pANCA, OmpC, CBir1, A4-Fla2, and FlaX), 4 genetic markers (ATG16L1, NKX2-3, ECM1, and STAT3), and 5 inflammatory markers (CRP, SAA, ICAM-1, VCAM-1, and VEGF). A diagnostic Random Forest algorithm was constructed to classify IBD, CD, and UC.
resultsReceiver operating characteristic analysis compared the diagnostic accuracy of using a panel of serological markers only (ASCA-IgA, ASCA-IgG, ANCA, pANCA, OmpC, and CBir1) versus using a marker panel that in addition to the serological markers mentioned above also included gene variants, inflammatory markers, and 2 additional serological markers (A4-Fla2 and FlaX). The extended marker panel increased the IBD versus non-IBD discrimination area under the curve from 0.80 (95% confidence interval [CI], ±0.05) to 0.87 (95% CI, ±0.04; P < 0.001). The CD versus UC discrimination increased from 0.78 (95% CI, ±0.06) to 0.93 (95% CI, ±0.04; P < 0.001).
conclusionsIncorporating a combination of serological, genetic, and inflammation markers into a diagnostic algorithm improved the accuracy of identifying IBD and differentiating CD from UC versus using serological markers alone.
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