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

C. Damon; M. Luck; L. Toullec; I. Etienne; M. Büchler; B. Hurault de Ligny; G. Choukroun; A. Thierry; C. Vigneau; B. Moulin; A.-E. Heng; J.-F. Subra; C. Legendre; A. Monnot; A. Yartseva; M. Bateson; P. Laurent-Puig; D. Anglicheau; P. Beaune; M. Loriot; E. Thervet; N. Pallet

doi:10.1111/ajt.14040

Journal articles

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

C. Damon ¹ M. Luck L. Toullec I. Etienne M. Büchler ² B. Hurault de Ligny ³ G. Choukroun ⁴ A. Thierry ⁵ C. Vigneau ^{6, 7} B. Moulin A.-E. Heng ⁸ J.-F. Subra ⁹ C. Legendre ¹⁰ A. Monnot A. Yartseva M. Bateson P. Laurent-Puig ¹¹ D. Anglicheau ¹¹ P. Beaune ¹² M. Loriot E. Thervet ¹³ N. Pallet

1 GReD - Génétique, Reproduction et Développement - Clermont Auvergne

2 Service de néphrologie et immunologie clinique

3 Service de Néphrologie-Dialyse-Transplantation rénale [CHU Caen]

4 Mécanismes physiologiques et conséquences des calcifications cardiovasculaires: rôle des remodelages cardiovasculaires et osseux

5 CHU Poitiers - Centre hospitalier universitaire de Poitiers

6 CHU Pontchaillou [Rennes]

7 Irset - Institut de recherche en santé, environnement et travail

8 Service de Néphrologie, Hôpital Gabriel Montpied, CHU de Clermont-Ferrand, Clermont-Ferrand, France

9 Service de Néphrologie [Angers]

10 LDO - Domaines Océaniques

11 UPD5 - Université Paris Descartes - Paris 5

12 aucun

13 Service de Transplantation Rénale

Abstract : Any biochemical reaction underlying drug metabolism depends on individual gene-drug interactions and on groups of genes interacting together. Based on a high-throughput genetic approach, we sought to identify a set of covariant 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 over 3 mo. Given the high dimension of the genomic data in comparison to the low number of observations and the high multicolinearity among the variables (gene variants), we developed an original predictive approach that integrates an ensemble variable-selection strategy to reinforce the stability of the variable-selection process and multivariate modeling. Our predictive models explained up to 70% of total variability in Tac C0 per dose with a maximum of 44 gene variants (p-value <0.001 with a permutation test). These models included molecular networks of drug metabolism with oxidoreductase activities and the multidrug-resistant ABCC8 transporter, which was found in the most stringent model. Finally, we 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.

Keywords : clinical research/practice translational research/science genetics genomics immunosuppression/immune modulation immunosuppressive regimens pharmacology

Document type :

Journal articles

Domain :

Life Sciences [q-bio] / Toxicology

Complete list of metadatas

https://hal-univ-rennes1.archives-ouvertes.fr/hal-02445539
Contributor : Cécile Vigneau <>
Submitted on : Monday, January 20, 2020 - 11:41:27 AM
Last modification on : Friday, June 19, 2020 - 3:47:35 PM

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

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

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