Response to the treatment
The use of biologics, such as anti-TNF, has revolutionized the care of patients with Crohn’s disease. Nevertheless, up to 70% of patients do not respond to such biologic treatment or lose response over time. Current treatment algorithms are largely based on atrial-and-error approach because no biologic parameters have been identified that predict treatment success or failure. As such, many patients receive ineffective treatment for many months to years. This (lack of) strategy has been associated with severe complications such as obstructions and perforations (end organ damage) and need for repeated surgical resections, stomas and cancer.
Personalized medicine, including prediction of treatment response to individual agents could shorten the time period to ‘deep remission’ significantly and would bring along a major improvement in the prognosis of this dreadful condition. HORAIZON team has introduced novel machine learning models, discovering specific epigenetic patterns in the peripheral blood at baseline (before start of treatment) that were associated with treatment response (clinical remission and mucosal repair) to several biologic agents. As such, epigenetic marks hold great promise as predictors of therapy response.The differential patterns that were identified for the individual treatments, would allow personalized treatment in the near future.