RAID Prediction: Pilot Study of Fecal Microbial Signature With Capacity to Predict Response to Anti-TNF Treatment

Abstract

Background and Aims Crohn’s disease and ulcerative colitis evolve with alternate outbreaks and remissions of variable duration in both cases. Despite the advances, about 10-30% of patients do not respond to the treatment after the induction period. Besides, between 20% to 50% further patients need an optimization of the dose to respond the treatment. Recent studies have pointed gut microbiota can play a role in the anti-TNF treatment response. This study aimed to define a bacterial signature that could be used to predict the response of patients to anti-TNF treatment. Methods There were obtained 38 stool samples from 38 IBD patients before starting anti-TNF treatments: Adalimumab, Golimumab or Infliximab. Patients were differentiated in 2 groups: responders and non-responders to biological treatment. From each sample, DNA was purified and used in a qPCR for the quantification of the 8 microbial markers. Results In this proof of concept, the predictive ability to identify anti-TNF treatment responders was analyzed. An algorithm consisting in the combination of 4 bacterial markers showed a high capacity to discriminate between responders and non- responders. The algorithm proved high sensitivity and specificity reporting values of 93.33% and 100% respectively, with a positive predictive value of 100% and a negative predictive value of 75% for predicting response to biologic treatment. Conclusions A specific bacterial signature could beneficiate patients with inflammatory bowel disease predicting the therapeutic effectiveness of an anti-TNF treatment, leading to a personalized therapy, improving the patients’ quality of life, saving costs and gaining time in patient improvement.

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“…Clinically relevant results have been obtained in cancer research, e.g., the success of therapy with Anti-programmed Cell Death Protein-1 (PD−1) has been shown to depend significantly on the baseline composition of the patient’s gut microbiota [ 57 – 60 ]. MIME has also been successfully used to predict the response of IBD patients to a low FODMAP diet [ 61 ] or anti-TNF treatment [ 62 ], the efficacy of synbiotic treatment of gastrointestinal disease in children [ 63 ], or the prediction of the clinical outcome of bariatric surgery [ 64 ]. The gut microbiota may serve as a biomarker for selecting the most effective drugs for the treatment of rheumatoid arthritis [ 65 ], and gut bacterial signatures have even been described to characterize the diagnosis and predict treatment outcomes in bipolar depression [ 66 ].…”

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“…In a proof-of-concept study, Busquets et al . designed an algorithm to identify bacterial biomarkers of non-responding IBD patients to anti-TNF agents involving 38 IBD patients [ 142 ] . Based on this, patients prone to respond have high counts of F. prausnitzii and Ruminococcus and a low abundance of Methanobrevibacter smithii .…”

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“…More recently, Busquets et al . developed an algorithm comprising four microbial markers and used it to differentiate responders from non-responders, with a favorable sensitivity and specificity (93.33% and 100%) [ 203 ]. Furthermore, Bouhnik et al .…”