Pediatric Statin Administration: Navigating a Frontier with Limited Data

Functional Consequences of Pravastatin Isomerization on OATP1B1-Mediated Transport

Pravastatin acid (PVA) can be isomerized to its inactive metabolite 3'α-iso-pravastatin acid (3αPVA) under acidic pH conditions. Previous studies reported interindividual differences in circulating concentrations of PVA and 3αPVA. This study investigated the functional consequences of PVA isomerization on OATP1B1-mediated transport. We characterized 3αPVA inhibition of OATP1B1-mediated PVA uptake into human embryonic kidney 293 cells expressing the four different OATP1B1 proteins (*1a, *1b, *5, and *15). 3αPVA inhibited OATP1B1-mediated PVA uptake in all four OATP1B1 gene products but with lower IC₅₀/K_i values for OATP1B1*5 and *15 than for the reference proteins (*1a and *1b). PVA and 3αPVA were transported by all four OATP1B1 proteins. Kinetic experiments revealed that maximal transport rates (V_max values) for OATP1B1 variants *5 and *15 were lower than for *1a and *1b for both substrates. Apparent affinities for 3αPVA transport were similar for all four variants. However, the apparent affinity of OATP1B1*5 for 3αPVA was higher (lower K_m value) than for PVA. These data confirm that PVA conversion to 3αPVA can have functional consequences on PVA uptake and impacts OATP1B1 variants more than the reference protein, thus highlighting another source variation that must be taken into consideration when optimizing the PVA dose-exposure relationship for patients. SIGNIFICANCE STATEMENT: 3'α-iso-pravastatin acid inhibits pravastatin uptake for all OATP1B1 protein types; however, the IC₅₀ values were significantly lower in OATP1B1*5 and *15 transfected cells. This suggests that a lower concentration of 3'α-iso-pravastatin is needed to disrupt OATP1B1-mediated pravastatin uptake, secondary to decreased cell surface expression of functional OATP1B1 in variant-expressing cells. These data will refine previous pharmacokinetic models that are utilized to characterize pravastatin interindividual variability with an ultimate goal of maximizing efficacy at the lowest possible risk for toxicity.

Impact of SLCO1B1 Genetic Variation on Rosuvastatin Systemic Exposure in Pediatric Hypercholesterolemia

This study investigated the impact of SLCO1B1 genotype on rosuvastatin systemic exposure in hypercholesterolemic children and adolescents. Participants (8–21 years) with at least one allelic variant of SLCO1B1 c.521T>C (521TC, n = 13; 521CC, n = 2) and wild type controls (521TT, n = 13) completed a single oral dose pharmacokinetic study. The variability contributed by SLCO1B1 c.521 sequence variation to rosuvastatin (RVA) systemic exposure among our pediatric cohort was comparable to previous studies in adults. RVA concentration‐time curve from 0–24 hours (AUC_0–24) was 1.4‐fold and 2.2‐fold higher in participants with c.521TC and c.521CC genotype compared 521TT participants, respectively. Interindividual variability of RVA exposure within SLCO1B1 genotype groups exceeded the ~ 1.5‐fold to 2‐fold difference in mean RVA exposure observed among SLCO1B1 genotype groups, suggesting that other factors also contribute to interindividual variability in the rosuvastatin dose‐exposure relationship. A multivariate model performed confirmed SLCO1B1 c.521T>C genotype as the primary factor contributing to RVA systemic exposure in this pediatric cohort, accounting for ~ 30% of the variability RVA AUC_0–24. However, of the statins investigated to date in the pediatric population, RVA has the lowest magnitude of variability in systemic exposure.

Factors Affecting Pediatric Dyslipidemia Screening and Treatment

Identification and management of dyslipidemia in childhood can reduce future cardiovascular risk. We performed a retrospective cohort study of children ages 2 to 18 years during 2009 to 2013 to evaluate factors that affect screening and treatment of pediatric dyslipidemia related to 2011 National Heart, Lung, and Blood Institute (NHLBI) guidelines. Logistic regression analysis determined the impact of NHLBI-identified factors on odds of being screened, elevated low-density lipoprotein cholesterol (LDL-C), and receiving pharmacotherapy. A total of 1 736 032 children were included; 113 780 (6.6%) were screened for dyslipidemia. Screening in 9 to 11 year olds increased from 2009 to 2012. Of children screened, 18 801 (16.5%) had elevated LDL-C; 425 (2.3%) were treated pharmacologically. Parental dyslipidemia, diabetes mellitus, chronic kidney disease, Kawasaki disease, human immunodeficiency virus infection, nephrotic syndrome, liver, thyroid, and other endocrine disorders increased odds of screening. Older age, nephrotic syndrome, chronic kidney disease, diabetes mellitus, and hypertension increased odds of having elevated LDL-C and receiving treatment. Pediatric dyslipidemia screening rates remain low.

Ontogeny-related pharmacogene changes in the pediatric liver transcriptome

OBJECTIVES

The majority of drug dosing studies are based on adult populations, with modification of the dosing for children based on size and weight. This rudimentary approach for drug dosing children is limited, as biologically a child can differ from an adult in far more aspects than just size and weight. Specifically, understanding the ontogeny of childhood liver development is critical in dosing drugs that are metabolized through the liver, as the rate of metabolism determines the duration and intensity of a drug's pharmacologic action. Therefore, we set out to determine pharmacogenes that change over childhood development, followed by a secondary agnostic analysis, assessing changes transcriptome wide.

MATERIALS AND METHODS

A total of 47 human liver tissue samples, with between 10 and 13 samples in four age groups spanning childhood development, underwent pair-end sequencing. Kruskal-Wallis and Spearman's rank correlation tests were used to determine the association of gene expression levels with age. Gene set analysis based on the pathways in KEGG utilized the gamma method. Correction for multiple testing was completed using q-values.

RESULTS

We found evidence for increased expression of 'very important pharmacogenes', for example, coagulation factor V (F5) (P=6.7×10(-7)), angiotensin I converting enzyme (ACE) (P=6.4×10(-3)), and solute carrier family 22 member 1 (SLC22A1) (P=7.0×10(-5)) over childhood development. In contrast, we observed a significant decrease in expression of two alternative CYP3A7 transcripts (P=1.5×10(-5) and 3.0×10(-5)) over development. The analysis of genome-wide changes detected transcripts in the following genes with significant changes in mRNA expression (P<1×10(-9) with false discovery rate<5×0(-5)): ADCY1, PTPRD, CNDP1, DCAF12L1 and HIP1. Gene set analysis determined ontogeny-related transcriptomic changes in the renin-angiotensin pathway (P<0.002), with lower expression of the pathway, in general, observed in liver samples from younger participants.

CONCLUSION

Considering that the renin-angiotensin pathway plays a central role in blood pressure and plasma sodium concentration, and our observation that ACE and PTPRD expression increased over the spectrum of childhood development, this finding could potentially impact the dosing of an entire class of drugs known as ACE-inhibitors in pediatric patients.

Genomics and Precision Medicine to Direct Statin Use in the Young

The delivery of precision medicine to pediatric cardiology remains complex with a number of challenges ahead. With recent advances in whole genome sequencing, rapid acquisition of a patient's genomic data is possible. However, the challenge remains how we best implement this new data into clinical practice. Predicting drug disposition and response of the individual patient requires a thorough knowledge of the entire dose-exposure-response relationship of each individual drug and knowledge of the factors that make each individual unique. This goal of precision medicine is even more complex in the developing child where drug disposition and response pathways may still be maturing. Herein, we will illustrate the challenges and pitfalls that may occur when trying to deliver pediatric precision medicine using the statins as a prototype.