Literature DB >> 34877660

Effect of CYP3A5 and CYP3A4 Genetic Variants on Fentanyl Pharmacokinetics in a Pediatric Population.

Michael L Williams1, Prince J Kannankeril2,3, Joseph H Breeyear4,5, Todd L Edwards4,5,6, Sara L Van Driest2,3,4, Leena Choi1.   

Abstract

Fentanyl is an anesthetic/analgesic commonly used in surgical and recovery settings. CYP3A4 and CYP3A5 encode enzymes, which metabolize fentanyl; genetic variants in these genes impact fentanyl pharmacokinetics in adults. Pharmacokinetic (PK) studies are difficult to replicate in children due to the burden of additional blood taken solely for research purposes. The aim of this study is to test the effect of CYP3A5 and CYP3A4 genetic variants on fentanyl PKs in children using opportunistically collected samples. Fentanyl concentrations were measured from remnant blood specimens and dosing data were extracted from electronic health records. Variant data defining CYP3A4*1G and CYP3A5*3 and *6 alleles were available from prior genotyping; alleles with no variant were defined as *1. The study cohort included 434 individuals (median age 9 months, 52% male subjects) and 1,937 fentanyl concentrations were available. A two-compartment model was selected as the base model, and the final covariate model included age, weight, and surgical severity score. Clearance was significantly associated with either CYP3A5*3 or CYP3A5*6 alleles, but not the CYP3A4*1G allele. A genotype of CYP3A5*1/*3 or CYP3A5*1/*6 (i.e., intermediate metabolizer status) was associated with a 0.84-fold (95% confidence interval (CI): 0.71-1.00) reduction in clearance vs. CYP3A5*1/*1 (i.e., normal metabolizer status). CYP3A5*3/*3, CYP3A5*3/*6, or CYP3A5*6/*6 (i.e., poor metabolizer status) was associated with a 0.76-fold (95% CI: 0.58-0.99) reduction in clearance. In the final model, expected clearance was 8.9 and 6.8 L/hour for a normal and poor metabolizer, respectively, with median population covariates (9 months old, 7.7 kg, low surgical severity).
© 2021 The Authors. Clinical Pharmacology & Therapeutics © 2021 American Society for Clinical Pharmacology and Therapeutics.

Entities:  

Mesh:

Substances:

Year:  2022        PMID: 34877660      PMCID: PMC8940650          DOI: 10.1002/cpt.2506

Source DB:  PubMed          Journal:  Clin Pharmacol Ther        ISSN: 0009-9236            Impact factor:   6.903


  31 in total

1.  Ways to fit a PK model with some data below the quantification limit.

Authors:  S L Beal
Journal:  J Pharmacokinet Pharmacodyn       Date:  2001-10       Impact factor: 2.745

2.  Impact of CYP3A5 and ABCB1 gene polymorphisms on fentanyl pharmacokinetics and clinical responses in cancer patients undergoing conversion to a transdermal system.

Authors:  Yoshiaki Takashina; Takafumi Naito; Yasuaki Mino; Tatsuya Yagi; Kazunori Ohnishi; Junichi Kawakami
Journal:  Drug Metab Pharmacokinet       Date:  2012-01-24       Impact factor: 3.614

3.  Principal components analysis corrects for stratification in genome-wide association studies.

Authors:  Alkes L Price; Nick J Patterson; Robert M Plenge; Michael E Weinblatt; Nancy A Shadick; David Reich
Journal:  Nat Genet       Date:  2006-07-23       Impact factor: 38.330

4.  Evaluation of FOCEI and SAEM Estimation Methods in Population Pharmacokinetic Analysis Using NONMEM® Across Rich, Medium, and Sparse Sampling Data.

Authors:  Waroonrat Sukarnjanaset; Thitima Wattanavijitkul; Sutep Jarurattanasirikul
Journal:  Eur J Drug Metab Pharmacokinet       Date:  2018-12       Impact factor: 2.441

5.  Pharmacokinetics of fentanyl in neonatal humans and lambs: effects of age.

Authors:  I S Gauntlett; D M Fisher; R E Hertzka; E Kuhls; M J Spellman; C Rudolph
Journal:  Anesthesiology       Date:  1988-11       Impact factor: 7.892

6.  The fentanyl story.

Authors:  Theodore H Stanley
Journal:  J Pain       Date:  2014-12       Impact factor: 5.820

7.  Polymorphisms associated with fentanyl pharmacokinetics, pharmacodynamics and adverse effects.

Authors:  Miriam Saiz-Rodríguez; Dolores Ochoa; Coral Herrador; Carmen Belmonte; Manuel Román; Enrique Alday; Dora Koller; Pablo Zubiaur; Gina Mejía; María Hernández-Martínez; Francisco Abad-Santos
Journal:  Basic Clin Pharmacol Toxicol       Date:  2018-10-30       Impact factor: 4.080

8.  Characterizing Fentanyl Variability Using Population Pharmacokinetics in Pediatric Burn Patients.

Authors:  Kristin N Grimsrud; Kelly M Lima; Nam K Tran; Tina L Palmieri
Journal:  J Burn Care Res       Date:  2020-01-30       Impact factor: 1.819

9.  Development of a System for Postmarketing Population Pharmacokinetic and Pharmacodynamic Studies Using Real-World Data From Electronic Health Records.

Authors:  Leena Choi; Cole Beck; Elizabeth McNeer; Hannah L Weeks; Michael L Williams; Nathan T James; Xinnan Niu; Bassel W Abou-Khalil; Kelly A Birdwell; Dan M Roden; C Michael Stein; Cosmin A Bejan; Joshua C Denny; Sara L Van Driest
Journal:  Clin Pharmacol Ther       Date:  2020-02-11       Impact factor: 6.875

10.  Effect of the Most Relevant CYP3A4 and CYP3A5 Polymorphisms on the Pharmacokinetic Parameters of 10 CYP3A Substrates.

Authors:  Miriam Saiz-Rodríguez; Susana Almenara; Marcos Navares-Gómez; Dolores Ochoa; Manuel Román; Pablo Zubiaur; Dora Koller; María Santos; Gina Mejía; Alberto M Borobia; Cristina Rodríguez-Antona; Francisco Abad-Santos
Journal:  Biomedicines       Date:  2020-04-22
View more
  1 in total

Review 1.  PharmVar GeneFocus: CYP3A5.

Authors:  Cristina Rodriguez-Antona; Jessica L Savieo; Volker M Lauschke; Katrin Sangkuhl; Britt I Drögemöller; Danxin Wang; Ron H N van Schaik; Andrei A Gilep; Arul P Peter; Erin C Boone; Bronwyn E Ramey; Teri E Klein; Michelle Whirl-Carrillo; Victoria M Pratt; Andrea Gaedigk
Journal:  Clin Pharmacol Ther       Date:  2022-02-24       Impact factor: 6.903

  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.