Genetic prediction profile for adalimumab response in Slovenian Crohn’s disease patients

Abstract

Introduction Response to anti-TNF therapy is crucial for life expectancy and life quality in patients with severe Crohn’s disease. We investigated if a previously reported gene expression profile predictive for infliximab response could be also applied to adalimumab response in an independent cohort. Methods Forty-seven Slovene Crohn’s disease patients indicated for adalimumab therapy were enrolled in the study. Inflamed and non-inflamed colon biopsy samples were obtained during routine colonoscopy prior to adalimumab treatment. Response to adalimumab was measured with IBDQ. Gene expression in inflamed and non-inflamed colon biopsy samples was measured with RT-qPCR. Genotypes were extracted from previously available genotype data. Statistical analysis was performed with SPSS software. The R package e1071 was used to train bootstrap aggregated support vector machines (SVM). Results SVM prediction model analysis was used to analyze pooled, non-inflamed, and inflamed colon tissue datasets using IBDQ response after 4, 12, 20 and 30 weeks of adalimumab treatment. The bagging approach was used in an endeavor to obtain 100 % accuracy using 10 × 100 or 100 × 100 iterations. Average adalimumab response prediction accuracy is 75.5 % for pooled samples, 90.5 % for inflamed samples, and 100 % for non-inflamed samples. Moreover, models trained on selected SNPs from analyzed genes had an average accuracy of 92.8 %, confirming the involvement of genetic regions mapping the reported genes. Finally, using combined gene expression and SNP data we observed 100 % adalimumab response prediction accuracy for pooled, inflamed, and non-inflamed datasets. Discussion Our study supports the reported genetic anti-TNF response profile and extends it for adalimumab prediction.

Gene Ontology Analysis Highlights Biological Processes Influencing Responsiveness to Biological Therapy in Psoriasis

“…Genetic biomarkers associated with response to biological therapy are the topic of numerous publications [ 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 ], and their identification could pave the way to personalized medicine [ 47 , 48 , 49 ]. To the best of our knowledge, we are the first to perform a gene ontology analysis based on the genes previously reported to be associated with response to biologics in psoriasis.…”

Cholecalciferol Supplementation Induced Up-Regulation of SARAF Gene and Down-Regulated miR-155-5p Expression in Slovenian Patients with Multiple Sclerosis

“…Primers were synthesized by Sigma (Merck, Darmstadt, Germany). Primers for the reference genes ACTB and B2M were obtained from a previous study [ 36 ]. RT-qPCR assays were carried out using LightCycler 480 SYBR Green I Master Mix and LightCycler 480 real-time thermocycler (Roche, Basel, Switzerland) according to manufacturer’s instructions.…”

Precision medicine in inflammatory bowel disease

“…So, Gorenjak et al . used machine learning support vector machines algorithm, and developed a prediction model consisting of the expression and genotype data of four potential genes [ 202 ]. This model showed a surprisingly high accuracy of 100% in predicting adalimumab response.…”