Novel Genetic Risk Variants Can Predict Anti-TNF Agent Response in Patients With Inflammatory Bowel Disease.
J Crohns Colitis. 2019 Jan 21;:
Authors: Wang MH, Friton JJ, Raffals LE, Leighton JA, Pasha SF, Picco MF, Cushing KC, Monroe K, Nix BD, Newberry RD, Faubion WA
Background: It is important to identify patients with inflammatory bowel disease (IBD) refractory to anti-tumor necrosis factor (TNF) therapy to avoid potential adverse effects and adopt different treatment strategies. We aimed to identify and validate clinical and genetic factors to predict anti-TNF response in patients with IBD.
Materials and Methods: Mayo Clinic and Washington University IBD genetic association study cohorts were used as discovery and replicate datasets, respectively. Clinical factors included sex, age at diagnosis, disease duration and phenotype, disease location, bowel resection, tobacco use, family history of IBD, extraintestinal manifestations, and response to anti-TNF therapy.
Results: Of 474 patients with IBD treated with anti-TNF therapy, 41 (8.7%) were refractory to therapy and 433 (91.3%) had response. Multivariate analysis showed history of immunomodulator use (odd ratio 10.2, P=8.73E-4) and bowel resection (odds ratio 3.24, P=4.38E-4) were associated with refractory response to anti-TNF agents. Among genetic loci, 2 (rs116724455 in TNFSF4/18, rs2228416 in PLIN2) were successfully replicated and another 4 (rs762787, rs9572250, rs144256942, rs523781) with suggestive evidence were found. An exploratory risk model predictability (area under the curve) increased from 0.72 (clinical predictors) to 0.89 after adding genetic predictors. Through identified clinical and genetic predictors, we constructed a preliminary anti-TNF refractory score to differentiate anti-TNF nonresponders (mean [SD] score, 5.49 [0.99]) from responders (2.65 [0.39]; P=4.33E-23).
Conclusions: Novel and validated genetic loci, including variants in TNFSF, were found associated with anti-TNF response in patients with IBD. Future validation of the exploratory risk model in a large prospective cohort is warranted.
PMID: 30689765 [PubMed – as supplied by publisher]