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Novel Genetic Risk Variants Can Predict Anti-TNF Agent Response in Patients With Inflammatory Bowel Disease
Ming-Hsi Wang1, Jessica J Friton2, Laura E Raffals2
1Division of Gastroenterology and Hepatology, Mayo Clinic, Jacksonville, FL, USA.
Background:
It is important to identify patients with inflammatory bowel disease [IBD] refractory to anti-tumour necrosis factor [TNF] therapy, to avoid potential adverse effects and to 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 (odds 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, two [rs116724455 in TNFSF4/18, rs2228416 in PLIN2] were successfully replicated and another four [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 non-responders (mean [standard deviation] 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.
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