Serological Biomarkers of Tissue Turnover Identify Responders to Anti-TNF Therapy in Crohn's Disease: A Pilot Study
Wouter T. van Haaften, Joachim Høg Mortensen, Anders Dige, Henning Grønbæk, Christian Lodberg Hvas, Anne‐Christine Bay‐Jensen, M.A. Karsdal, Peter Olinga, Tina Manon‐Jensen, Gerard Dijkstra
Abstract
INTRODUCTION: Anti-tumor necrosis factor (TNF) therapy is effective in inducing remission in Crohn's disease in 60% of patients. No serological biomarkers are available, which can predict response to anti-TNF. We aimed to investigate serological markers of collagen turnover reflecting tissue inflammation as predictors of response to anti-TNF. METHODS: In 2 retrospective observational cohorts, markers for matrix metalloproteinase-degraded type III and IV collagens (C3M and C4M, respectively) and for formation of type III and IV collagens (PRO-C3 and PRO-C4, respectively) were measured in serum and compared with standard C-reactive protein in patients with active Crohn's disease who started infliximab (IFX, n = 21) or adalimumab (ADA, n = 21). Disease activity was classified by the Harvey-Bradshaw index (active disease ≥5); response was defined as clinical remission. RESULTS: Seventeen patients (81%) treated with IFX were in remission at week 14; 15 patients (71%) treated with ADA were in remission at week 8. Serum C4M at baseline was increased in nonresponders compared with responders (IFX: 35.0 ± 2.4 vs 23.2 ± 2.6, P = 0.04, ADA: 53.0 ± 3.2 vs 34.1 ± 2.8, P = 0.006). C4M levels at baseline predicted response in both cohorts (IFX: odds ratio 39 [95% confidence interval, 2.4-523.9] P = 0.02, cutoff 35.2 nmol/L; ADA: odds ratio 26 [95% confidence interval, 1.8-332.5], P = 0.01, cutoff 46.9 nmol/L). C-reactive protein was not able to predict response to anti-TNF. DISCUSSION: Response to anti-TNF therapy within the first 14 weeks of treatment can be predicted based on baseline levels of basement membrane marker C4M. This marker could be used as biomarker for response to anti-TNF and could aid in early therapy decision making. Validation in larger well-defined cohorts is needed.