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Exome sequencing allows detection of relevant pharmacogenetic variants in epileptic patients

The Pharmacogenomics Journal volume 22, pages 258–263 (2022)Cite this article

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Abstract

Beyond the identification of causal genetic variants in the diagnosis of Mendelian disorders, exome sequencing can detect numerous variants with potential relevance for clinical care. Clinical interventions can thus be conducted to improve future health outcomes for patients and their at-risk relatives, such as predicting late-onset genetic disorders accessible to prevention, treatment or identifying differential drug efficacy and safety. To evaluate the interest of such pharmacogenetic information, we designed an “in house” pipeline to determine the status of 122 PharmGKB (Pharmacogenomics Knowledgebase) variant-drug combinations in 31 genes. This pipeline was applied to a cohort of 90 epileptic patients who had previously an exome sequencing (ES) analysis, to determine the frequency of pharmacogenetic variants. We performed a retrospective analysis of drug plasma concentrations and treatment efficacy in patients bearing at least one relevant PharmGKB variant. For PharmGKB level 1A variants, CYP2C9 status for phenytoin prescription was the only relevant information. Nineteen patients were treated with phenytoin, among phenytoin-treated patients, none were poor metabolizers and four were intermediate metabolizers. While being treated with a standard protocol (10–23 mg/kg/30 min loading dose followed by 5 mg/kg/8 h maintenance dose), all identified intermediate metabolizers had toxic plasma concentrations (20 mg/L). In epileptic patients, pangenomic sequencing can provide information about common pharmacogenetic variants likely to be useful to guide therapeutic drug monitoring, and in the case of phenytoin, to prevent clinical toxicity caused by high plasma levels.

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Fig. 1: Description of the study design.
Fig. 2: Kinetics of phenytoin concentration in the 4 patients. Primary vertical axis representing the phenytoin concentration and secondary vertical axis representing the administered dose.

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Data availability

For data sharing requests, please contact SV or YD at simon.verdez@chu-dijon.fr or yannis.duffourd@u-bourgogne.fr respectively.

Code availability

Code is available at the following link: http://gitlab.gad-bioinfo.org/gad-public/pharmAnnot/tree/public

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Acknowledgements

We thank the University of Burgundy Centre de Calcul (CCuB) for providing technical support and management of the informatics platform. This work was supported by grants from Dijon University Hospital, the ISITE-BFC (PIA ANR) and the European Union through the FEDER programs. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. The authors thank Suzanne Rankin from the Dijon University Hospital, Nicole Dorssers from simon fraser university and Cynthia Reichling for proofreading the manuscript.

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Authors and Affiliations

  1. UMR1231 GAD, Inserm, Université Bourgogne-Franche Comté, Dijon, France

    Simon Verdez, Quentin Thomas, Philippine Garret, Emilie Tisserant, Antonio Vitobello, Frédéric Tran Mau-Them, Christophe Philippe, Patrick Callier, Christel Thauvin-Robinet, Laurence Faivre & Yannis Duffourd

  2. Unité Fonctionnelle Innovation en Diagnostic Génomique des Maladies Rares, FHU-TRANSLAD, CHU Dijon Bourgogne, Dijon, France

    Simon Verdez, Quentin Thomas, Philippine Garret, Emilie Tisserant, Antonio Vitobello, Frédéric Tran Mau-Them, Christophe Philippe, Patrick Callier, Christel Thauvin-Robinet & Yannis Duffourd

  3. Laboratoire CERBA, Saint-Ouen l’Aumone, France

    Philippine Garret

  4. Université Paris-Saclay, Inserm, CESP, Team MOODS, Faculté de médecine, 94270, Le Kremlin-Bicêtre, Paris, France

    Céline Verstuyft

  5. CHU de Dijon, Centre d’Investigation Clinique, module plurithématique, 21000, Dijon, France

    Marc Bardou & Maxime Luu

  6. CHU de Dijon, Centre d’Investigation Clinique, module Epidémiologie Clinique/Essais cliniques, 21000, Dijon, France

    Marc Bardou, Maxime Luu & Abderrahmane Bourredjem

  7. Inserm CIC1432, 21000, Dijon, France

    Abderrahmane Bourredjem

  8. Centre de référence maladies rares « déficiences intellectuelles de causes rares », Centre de Génétique, FHU-TRANSLAD, CHU Dijon Bourgogne, Dijon, France

    Christel Thauvin-Robinet

  9. Centre de Référence maladies rares « Anomalies du Développement et syndromes malformatifs », Centre de Génétique, FHU-TRANSLAD, CHU Dijon Bourgogne, Dijon, France

    Christel Thauvin-Robinet & Laurence Faivre

  10. Inserm U1248, service de pharmacologie et toxicologie, université de Limoges, CHU de Limoges, F-87042, Limoges, France

    Nicolas Picard

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  1. Simon Verdez
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Contributions

SV, PG, LF, NP and YD designed the study. SV, QT performed the clinical analysis. AV, FTMT, CP, interpreted exome data. FTMT, AV and CP performed the molecular laboratory work. SV, YD and ET performed the bioinformatics analysis. All the authors contributed to the writing and review of the paper.

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Correspondence to Simon Verdez or Yannis Duffourd.

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Verdez, S., Thomas, Q., Garret, P. et al. Exome sequencing allows detection of relevant pharmacogenetic variants in epileptic patients. Pharmacogenomics J 22, 258–263 (2022). https://doi.org/10.1038/s41397-022-00280-w

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