Previous 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).
In 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.
Receiver 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).
Incorporating 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.
Article first published online 20 March 2013Supplemental Digital Content is Available in the Text.
*Division of Gastroenterology and Hepatology, Inflammatory Bowel Disease Center, University of North Carolina School of Medicine, Chapel Hill, North Carolina;
†Mount Sinai Hospital IBD Group, Zane Cohen Centre for Digestive Diseases, University of Toronto, Toronto, Ontario, Canada;
‡Prometheus Laboratories Inc., San Diego, California; and
§Stockfisch Consulting, Escondido, California.
Reprints: Scott Plevy, MD, Division of Gastroenterology and Hepatology, Inflammatory Bowel Disease Center, University of North Carolina School of Medicine, 103 Mason Farm Road, CB# 7032, 7341C MBRB, Chapel Hill, NC 27599 (e-mail: firstname.lastname@example.org).
Supplemental digital content is available for this article. Direct URL citations appear in the printed text and are provided in the HTML and PDF versions of this article on the journal's Web site (www.ibdjournal.org).
Supported by Prometheus Laboratories Inc, San Diego, CA.
S. Lockton, E. Chuang, F. Princen, S. Singh, L. Croner, J. Stachelski, M. Brown, and C. Triggs are employees of Prometheus Laboratories Inc. T. Stockfisch is an employee of Stockfisch Consulting and provided bioinformatics consulting services funded by Prometheus laboratories Inc. S. Plevy and M. S. Silverberg have received consulting fees and research support from Prometheus Laboratories Inc.
S. Plevy and M. S. Silverberg contributed equally to this study and are co-corresponding authors for this article.
Writing support was provided by Anthony Stonehouse and Rebecca Watson. Dr. Stonehouse and Dr. Watson are employees of Watson & Stonehouse Enterprises, LLC.
Received August 15, 2012
Accepted August 22, 2012