Association of polymorphisms in C1orf106, IL1RN, and IL10 with post-induction infliximab trough level in Crohn's disease patients

Gastroenterol Rep (Oxf). 2019 Oct 29;8(5):367-373. doi: 10.1093/gastro/goz056. eCollection 2020 Oct.

Abstract

Background: Trough levels of the post-induction serum infliximab (IFX) are associated with short-term and long-term responses of Crohn's disease patients to IFX, but the inter-individual differences are large. We aimed to elucidate whether single gene polymorphisms (SNPs) within FCGR3A, ATG16L1, C1orf106, OSM, OSMR, NF-κB1, IL1RN, and IL10 partially account for these differences and employed a multivariate regression model to predict patients' post-induction IFX levels.

Methods: The retrospective study included 189 Crohn's disease patients undergoing IFX therapy. Post-induction IFX levels were measured and 41 tag SNPs within eight genes were genotyped. Associations between SNPs and IFX levels were analysed. Then, a multivariate logistic-regression model was developed to predict whether the patients' IFX levels achieved the threshold of therapy (3 μg/mL).

Results: Six SNPs (rs7587051, rs143063741, rs442905, rs59457695, rs3213448, and rs3021094) were significantly associated with the post-induction IFX trough level (P = 0.015, P < 0.001, P = 0.046, P = 0.022, P = 0.011, P = 0.013, respectively). A multivariate prediction model of the IFX level was established by baseline albumin (P = 0.002), rs442905 (P = 0.025), rs59457695 (P = 0.049), rs3213448 (P = 0.056), and rs3021094 (P = 0.047). The area under the receiver operating characteristic curve (AUROC) of this prediction model in a representative training dataset was 0.758. This result was verified in a representative testing dataset, with an AUROC of 0.733.

Conclusions: Polymorphisms in C1orf106, IL1RN, and IL10 play an important role in the variability of IFX post-induction levels, as indicated in this multivariate prediction model of IFX levels with fair performance.

Keywords: inflammatory bowel disease; infliximab; multivariate prediction model; single nucleotide polymorphism; trough level.