P269 Predicting IBD years before diagnosis using routine blood tests

Abstract

Abstract Background Recent studies such as the GEM project have identified microbial, serological and metabolomic markers that may help predict inflammatory bowel disease (IBD) well in advance of diagnosis, with the ultimate goal of pre-disease prevention. In this population-based study, we used the epi-Israeli IBD Research Nucleus (IIRN) validated cohort to explore the utility of routine blood tests as markers for pre-diagnostic IBD prediction. Methods We included all blood tests from all IBD patients diagnosed from 2005-2020 insured in three of the four Israeli health maintenance organizations (HMOs), and individually matched each to two non-IBD controls. Test results were collected and collated by number of months pre-diagnosis, then reported over time until diagnosis. Means were compared using Welch's t-test with false discovery rate correction to account for multiple comparisons. Trends over time were analyzed to detect tests that showed divergence between cases and controls at least one year before diagnosis. Results Pre-diagnosis results from 142 different blood tests were collected for 7,630 Crohn’s disease (CD) patients and 6,026 ulcerative colitis (UC) patients (mean age 33.3±17.4 years for CD and 38 ± 17.9 years for UC). Median duration of pre-diagnosis data collection was 50 (IQR 11-96) months for CD and 48 (IQR11-96) months for UC. Of the 142 tests, 24 (17%) showed significant differences between CD and controls at least one year pre-diagnosis (Figure 1); these included not only inflammation-related tests such as ESR, hemoglobin and albumin, but also seemingly unrelated tests such as bilirubin, cholesterol and creatinine. In UC patients, no tests showed statistically significant differences at least one year pre-diagnosis. Conclusion We were able to detect changes in blood tests collected as part of routine care long before CD diagnosis, opening the possibility of detecting early signals of future CD in patients undergoing routine blood tests. These may be used for developing screening and prediction models for prevention strategies. This research was partially supported by the Israeli Council for Higher Education (CHE) via the Data Science Research Center, Ben-Gurion University of the Negev, Israel. The epi-IIRN project has been funded by an educational grant from the Leona M. and Harry B. Helmsley Charitable Trust.