Predictive Modeling of Tacrolimus Dose Requirement Based on High-Throughput Genetic Screening.

Any biochemical reaction underlying drug metabolism depends on individual gene-drug interactions and also on groups of genes interacting together. Based on a high-throughput genetic approach, we sought to identify a set of co-variant single nucleotide polymorphisms predictive of interindividual tacrolimus (Tac) dose requirement variability. Tac blood concentrations (Tac C0) of 229 kidney transplant recipients were repeatedly monitored after transplantation during three months. Given the high dimension of the genomic data in comparison to the low number of observations, and the high multi-colinearity among the variables (gene variants), we have developed an original predictive approach that integrates an ensemble variable selection strategy to reinforce the stability of the variables selection process, and a multivariate modeling. Our predictive models explained up to 70% of total Tac C0/Dose variability with a maximum of 44 genes variants (p-value<0.001 with a permutation test). These models included molecular networks of drug metabolism with oxydoreductase activities, but also the multi-drug resistance ABCC8 transporter, which was found in the most stringent model. Finally, we have identified an intronic variant of the gene encoding SLC28A3, a drug transporter, as a key gene involved in Tac metabolism and we confirmed it in an independent validation cohort. This article is protected by copyright. All rights reserved.