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

Variant-based heritability assessment of dexmedetomidine and fentanyl clearance in pediatric patients

Despite complex pathways of drug disposition, clinical pharmacogenetic predictors currently rely on only a few high effect variants. Quantification of the polygenic contribution to variability in drug disposition is necessary to prioritize target drugs for pharmacogenomic approaches and guide analytic methods. Dexmedetomidine and fentanyl, often used in postoperative care of pediatric patients, have high rates of inter-individual variability in dosing requirements. Analyzing previously generated population pharmacokinetic parameters, we used Bayesian hierarchical mixed modeling to measure narrow-sense (additive) heritability (h SNP 2 ) of dexmedetomidine and fentanyl clearance in children and identify relative contributions of small, moderate, and large effect-size variants toh SNP 2 . We used genome-wide association studies (GWAS) to identify variants contributing to variation in dexmedetomidine and fentanyl clearance, followed by functional analyses to identify associated pathways. For dexmedetomidine, median clearance was 33.0 L/h (interquartile range [IQR] 23.8-47.9 L/h) andh SNP 2 was estimated to be 0.35 (90% credible interval 0.00-0.90), with 45% ofh SNP 2 attributed to large-, 32% to moderate-, and 23% to small-effect variants. The fentanyl cohort had median clearance of 8.2 L/h (IQR 4.7-16.7 L/h), with estimatedh SNP 2 of 0.30 (90% credible interval 0.00-0.84). Large-effect variants accounted for 30% ofh SNP 2 , whereas moderate- and small-effect variants accounted for 37% and 33%, respectively. As expected, given small sample sizes, no individual variants or pathways were significantly associated with dexmedetomidine or fentanyl clearance by GWAS. We conclude that clearance of both drugs is highly polygenic, motivating the future use of polygenic risk scores to guide appropriate dosing of dexmedetomidine and fentanyl.

Nongenetic and genetic predictors of haemodynamic instability induced by propofol and opioids: A retrospective clinical study

AIM

Propofol and opioids are commonly used in anaesthesia, but are highly susceptible to haemodynamic instability, thereby threatening the patient's surgical safety and prognosis. The purpose of this study was to investigate the predictors of haemodynamic instability and establish its predictive model.

METHODS

A total of 150 Chinese patients undergoing thyroid or breast surgery participated in the study, with target-controlled infusion concentrations of propofol, opioids dosage, heart rate (HR), mean arterial pressure (MAP) and Narcotrend Index recorded at key points throughout the procedure. The Agena MassARRAY system was used to genotype candidate single nucleotide polymorphisms related to pharmacodynamics and pharmacokinetics of propofol and opioids.

RESULTS

Among nongenetic factors, baseline HR (R = -.579, P < .001) and baseline MAP (R = -.725, P < .001) had a significant effect on the haemodynamic instability. Among genetic factors, the CT/CC genotype of GABRB1 rs4694846 (95% confidence interval [CI]: -11.309 to -3.155), AA/AG of OPRM1 rs1799971 (95%CI: 0.773 to 10.290), AA of CES2 rs8192925 (95%CI: 1.842 to 9.090) were associated with higher HR instability; the AA/GG genotype of NR1I2 rs6438550 (95%CI: 0.351 to 7.761), AA of BDNF rs2049046 (95%CI: -9.039 to -0.640) and GG of GABBR2 rs1167768 (95%CI: -10.146 to -1.740) were associated with higher MAP instability. The predictive models of HR and MAP fluctuations were developed, accounting for 45.0 and 59.2% of variations, respectively.

CONCLUSION

We found that cardiovascular fundamentals and genetic variants of GABRB1, GABBR2, OPRM1, BDNF, CES2 and NR1I2 are associated with cardiovascular susceptibility, which can provide a reference for haemodynamic management in clinical anaesthesia.

Pharmacogenomic profile of actionable molecular variants related to drugs commonly used in anesthesia: WES analysis reveals new mutations

Background: Genetic interindividual variability is associated with adverse drug reactions (ADRs) and affects the response to common drugs used in anesthesia. Despite their importance, these variants remain largely underexplored in Latin-American countries. This study describes rare and common variants found in genes related to metabolism of analgesic and anaesthetic drug in the Colombian population. Methods: We conducted a study that included 625 Colombian healthy individuals. We generated a subset of 14 genes implicated in metabolic pathways of common medications used in anesthesia and assessed them by whole-exome sequencing (WES). Variants were filtered using two pipelines: A) novel or rare (minor allele frequency-MAF <1%) variants including missense, loss-of-function (LoF, e.g., frameshift, nonsense), and splice site variants with potential deleterious effect and B) clinically validated variants described in the PharmGKB (categories 1, 2 and 3) and/or ClinVar databases. For rare and novel missense variants, we applied an optimized prediction framework (OPF) to assess the functional impact of pharmacogenetic variants. Allelic, genotypic frequencies and Hardy-Weinberg equilibrium were calculated. We compare our allelic frequencies with these from populations described in the gnomAD database. Results: Our study identified 148 molecular variants potentially related to variability in the therapeutic response to 14 drugs commonly used in anesthesiology. 83.1% of them correspond to rare and novel missense variants classified as pathogenic according to the pharmacogenetic optimized prediction framework, 5.4% were loss-of-function (LoF), 2.7% led to potential splicing alterations and 8.8% were assigned as actionable or informative pharmacogenetic variants. Novel variants were confirmed by Sanger sequencing. Allelic frequency comparison showed that the Colombian population has a unique pharmacogenomic profile for anesthesia drugs with some allele frequencies different from other populations. Conclusion: Our results demonstrated high allelic heterogeneity among the analyzed sampled, enriched by rare (91.2%) variants in pharmacogenes related to common drugs used in anesthesia. The clinical implications of these results highlight the importance of implementation of next-generation sequencing data into pharmacogenomic approaches and personalized medicine.

PharmVar GeneFocus: CYP3A5

The Pharmacogene Variation Consortium (PharmVar) catalogs star (*) allele nomenclature for the polymorphic human CYP3A5 gene. Genetic variation within the CYP3A5 gene locus impacts the metabolism of several clinically important drugs, including the immunosuppressants tacrolimus, sirolimus, cyclosporine, and the benzodiazepine midazolam. Variable CYP3A5 activity is of clinical importance regarding tacrolimus metabolism. This GeneFocus provides a CYP3A5 gene summary with a focus on aspects regarding standardized nomenclature. In addition, this review also summarizes recent changes and updates, including the retirement of several allelic variants and provides an overview of how PharmVar CYP3A5 star allele nomenclature is utilized by the Pharmacogenomics Knowledgebase (PharmGKB) and the Clinical Pharmacogenetics Implementation Consortium (CPIC).

Precision Medicine in Pediatric Cardiology

Precision medicine is a developing strategy for individualized treatment of a wide range of diseases. Congenital heart disease is the most common of all congenital defects and carries a high degree of variability in outcomes because of unidentified causes. Advances have identified individual genetic and environmental factors that have helped understand variations in morbidity and mortality in pediatric cardiology. A focus on genomics and pharmacogenetics has also been key to risk prediction and improvement in drug safety and efficacy in the pediatric population. With the rapidly evolving understanding of these individual factors, there also come challenges in implementation of personalized medicine into our health care model. This review outlines the key features of precision medicine in pediatric cardiology and highlights the clinical effects of these findings in patients with congenital heart disease. [Pediatr Ann. 2022;51(10):e390-e395.].