A comprehensive pharmacogenomic study indicates roles for SLCO1B1, ABCG2 and SLCO2B1 in rosuvastatin pharmacokinetics

SLCO1B1 and ABCG2 genotype-informed phenotypes are related to variation in ramipril exposure

Ramipril is an angiotensin-converting enzyme inhibitor used for hypertension and heart failure management. To date, scarce literature is available on pharmacogenetic associations affecting ramipril. The goal of this study was to investigate the effect of 120 genetic variants in 34 pharmacogenes (i.e., genes encoding for enzymes like CYPs or UGTs and transporters like ABC or SLC) on ramipril pharmacokinetic variability and adverse drug reaction (ADR) incidence. Twenty-nine healthy volunteers who had participated in a single-dose bioequivalence clinical trial of two formulations of ramipril were recruited. A univariate and multivariate analysis searching for associations between genetic variants and ramipril pharmacokinetics was performed. SLCO1B1 and ABCG2 genotype-informed phenotypes strongly predicted ramipril exposure. Volunteers with the SLCO1B1 decreased function (DF) phenotype presented around 1.7-fold higher dose/weight-corrected area under the curve (AUC/DW) than volunteers with the normal function (NF) phenotype (univariate p-value [puv] < 0.001, multivariate p-value [pmv] < 0.001, β = 0.533, R2 = 0.648). Similarly, volunteers with ABCG2 DF + poor function (PF) phenotypes presented around 1.6-fold higher AUC/DW than those with the NF phenotype (puv = 0.011, pmv < 0.001, β = 0.259, R2 = 0.648). Our results suggest that SLCO1B1 and ABCG2 are important transporters to ramipril pharmacokinetics, and their genetic variation strongly alters its pharmacokinetics. Further studies are required to confirm these associations and their clinical relevance.

Genotype-Guided Model for Prediction of Tacrolimus Initial Dosing After Lung Transplantation

The determination of the appropriate initial dose for tacrolimus is crucial in achieving the target concentration promptly and avoiding adverse effects and poor prognosis. However, the trial-and-error approach is still common practice. This study aimed to establish a prediction model for an initial dosing algorithm of tacrolimus in patients receiving a lung transplant. A total of 210 lung transplant recipients were enrolled, and 26 single nucleotide polymorphisms (SNP) from 18 genes that could potentially affect tacrolimus pharmacokinetics were genotyped. Associations between SNPs and tacrolimus concentration/dose ratio were analyzed. SNPs that remained significant in pharmacogenomic analysis were further combined with clinical factors to construct a prediction model for tacrolimus initial dose. The dose needed to reach steady state tacrolimus concentrations and achieve the target range was used to validate model prediction efficiency. Our final model consisted of 7 predictors-CYP3A5 rs776746, SLCO1B3 rs4149117, SLC2A2 rs1499821, NFATc4 rs1955915, alanine aminotransferase, direct bilirubin, and hematocrit-and explained 41.4% variance in the tacrolimus concentration/dose ratio. It achieved an area under the receiver operating characteristic curve of 0.804 (95% confidence interval, 0.746-0.861). The Hosmer-Lemeshow test yielded a nonsignificant P value of .790, suggesting good fit of the model. The predicted dose exhibited good correlation with the observed dose in the early postoperative period (r = 0.748, P less than .001). Our study provided a genotype-guided prediction model for tacrolimus initial dose, which may help to guide individualized dosing of tacrolimus in the lung transplant population in clinical practice.

Understanding the impact of ABCG2 polymorphisms on drug pharmacokinetics: focus on rosuvastatin and allopurinol

INTRODUCTION

In addition to the well-established understanding of the pharmacogenetics of drug-metabolizing enzymes, there is growing data on the effects of genetic variation in drug transporters, particularly ATP-binding cassette (ABC) transporters. However, the evidence that these genetic variants can be used to predict drug effects and to adjust individual dosing to avoid adverse events is still limited.

AREAS COVERED

This review presents a summary of the current literature from the PubMed database as of February 2024 regarding the impact of genetic variants on ABCG2 function and their relevance to the clinical use of the HMG-CoA reductase inhibitor rosuvastatin and the xanthine oxidase inhibitor allopurinol.

EXPERT OPINION

Although there are pharmacogenetic guidelines for the ABCG2 missense variant Q141K, there is still some conflicting data regarding the clinical benefits of these recommendations. Some caution appears to be warranted in homozygous ABCG2 Q141K carriers when rosuvastatin is administered at higher doses and such information is already included in the drug label. The benefit of dose adaption to lower possible side effects needs to be evaluated in prospective clinical studies.

Genome-Wide Association Study of Atorvastatin Pharmacokinetics: Associations With SLCO1B1, UGT1A3, and LPP

In a genome-wide association study of atorvastatin pharmacokinetics in 158 healthy volunteers, the SLCO1B1 c.521T>C (rs4149056) variant associated with increased area under the plasma concentration-time curve from time zero to infinity (AUC0-∞) of atorvastatin (P = 1.2 × 10-10), 2-hydroxy atorvastatin (P = 4.0 × 10-8), and 4-hydroxy atorvastatin (P = 2.9 × 10-8). An intronic LPP variant, rs1975991, associated with reduced atorvastatin lactone AUC0-∞ (P = 3.8 × 10-8). Three UGT1A variants linked with UGT1A3*2 associated with increased 2-hydroxy atorvastatin lactone AUC0-∞ (P = 3.9 × 10-8). Furthermore, a candidate gene analysis including 243 participants suggested that increased function SLCO1B1 variants and decreased activity CYP3A4 variants affect atorvastatin pharmacokinetics. Compared with individuals with normal function SLCO1B1 genotype, atorvastatin AUC0-∞ was 145% (90% confidence interval: 98-203%; P = 5.6 × 10-11) larger in individuals with poor function, 24% (9-41%; P = 0.0053) larger in those with decreased function, and 41% (16-59%; P = 0.016) smaller in those with highly increased function SLCO1B1 genotype. Individuals with intermediate metabolizer CYP3A4 genotype (CYP3A4*2 or CYP3A4*22 heterozygotes) had 33% (14-55%; P = 0.022) larger atorvastatin AUC0-∞ than those with normal metabolizer genotype. UGT1A3*2 heterozygotes had 16% (5-25%; P = 0.017) smaller and LPP rs1975991 homozygotes had 34% (22-44%; P = 4.8 × 10-5) smaller atorvastatin AUC0-∞ than noncarriers. These data demonstrate that genetic variation in SLCO1B1, UGT1A3, LPP, and CYP3A4 affects atorvastatin pharmacokinetics. This is the first study to suggest that LPP rs1975991 may reduce atorvastatin exposure. [Correction added on 6 April, after first online publication: An incomplete sentence ("= 0.017) smaller in heterozygotes for UGT1A3*2 and 34% (22%, 44%; P × 10-5) smaller in homozygotes for LPP noncarriers.") has been corrected in this version.].

Rosuvastatin-induced rhabdomyolysis: case report and call for proactive multifactorial risk assessment and preventive management of statin therapy in high-risk patients

Cholesterol-lowering statins are frequently prescribed for primary and secondary prevention of ischaemic vascular events. Whereas most patients tolerate statins without problems, statin-associated myopathy is well documented, as are several risk factors. We present a case report of an 80-90-year-old man with coronary artery disease who rapidly developed severe rhabdomyolysis during treatment with rosuvastatin while in intensive care. He had several concomitant risk factors for statin-induced myopathy including high dosage, old age, renal and hepatic impairment, and a pharmacogenetic SLCO1B1*1 a/*5 variant. Single known risk factors have a low predictive value for statin-induced myopathy and may therefore be underestimated in clinical practice. However, adverse drug reactions frequently involve the joint action of a multitude of environmental and genetic component causes, and statin-induced myopathy should be regarded as a multicausal event. We therefore advocate a proactive multifactorial risk assessment to guide and individualise statin therapy in high-risk patients.

Impacts of ABCG2 loss of function variant (p. Gln141Lys, c.421 C > A, rs2231142) on lipid levels and statin efficiency: a systematic review and meta-analysis

BACKGROUND

The latest evidence indicates that ATP-binding cassette superfamily G member 2 (ABCG2) is critical in regulating lipid metabolism and mediating statin or cholesterol efflux. This study investigates whether the function variant loss within ABCG2 (rs2231142) impacts lipid levels and statin efficiency.

METHODS

PubMed, Cochrane Library, Central, CINAHL, and ClinicalTrials.gov were searched until November 18, 2023.

RESULTS

Fifteen studies (34,150 individuals) were included in the analysis. The A allele [Glu141Lys amino acid substitution was formed by a transversion from cytosine (C) to adenine (A)] of rs2231142 was linked to lower levels of high-density lipoprotein cholesterol (HDL-C), and higher levels of low-density lipoprotein cholesterol (LDL-C) and total cholesterol (TC). In addition, the A allele of rs2231142 substantially increased the lipid-lowering efficiency of rosuvastatin in Asian individuals with dyslipidemia. Subgroup analysis indicated that the impacts of rs2231142 on lipid levels and statin response were primarily in Asian individuals.

CONCLUSIONS

The ABCG2 rs2231142 loss of function variant significantly impacts lipid levels and statin efficiency. Preventive use of rosuvastatin may prevent the onset of coronary artery disease (CAD) in Asian individuals with dyslipidemia.

Non-targeted metabolomics for the identification of plasma metabolites associated with organic anion transporting polypeptide 1B1 function

Our aim was to evaluate biomarkers for organic anion transporting polypeptide 1B1 (OATP1B1) function using a hypothesis-free metabolomics approach. We analyzed fasting plasma samples from 356 healthy volunteers using non-targeted metabolite profiling by liquid chromatography high-resolution mass spectrometry. Based on SLCO1B1 genotypes, we stratified the volunteers to poor, decreased, normal, increased, and highly increased OATP1B1 function groups. Linear regression analysis, and random forest (RF) and gradient boosted decision tree (GBDT) regressors were used to investigate associations of plasma metabolite features with OATP1B1 function. Of the 9152 molecular features found, 39 associated with OATP1B1 function either in the linear regression analysis (p < 10-5) or the RF or GBDT regressors (Gini impurity decrease > 0.01). Linear regression analysis showed the strongest associations with two features identified as glycodeoxycholate 3-O-glucuronide (GDCA-3G; p = 1.2 × 10-20 for negative and p = 1.7 × 10-19 for positive electrospray ionization) and one identified as glycochenodeoxycholate 3-O-glucuronide (GCDCA-3G; p = 2.7 × 10-16). In both the RF and GBDT models, the GCDCA-3G feature showed the strongest association with OATP1B1 function, with Gini impurity decreases of 0.40 and 0.17. In RF, this was followed by one GDCA-3G feature, an unidentified feature with a molecular weight of 809.3521, and the second GDCA-3G feature. In GBDT, the second and third strongest associations were observed with the GDCA-3G features. Of the other associated features, we identified with confidence two representing lysophosphatidylethanolamine 22:5. In addition, one feature was putatively identified as pregnanolone sulfate and one as pregnenolone sulfate. These results confirm GCDCA-3G and GDCA-3G as robust OATP1B1 biomarkers in human plasma.

Differential effects of OATP2B1 on statin accumulation and toxicity in a beta cell model

An increased risk of new-onset diabetes mellitus has been recently reported for statin therapy, and experimental studies have shown reduced glucose-stimulated insulin secretion (GSIS) and mitochondrial dysfunction in beta cells with effects differing among agents. Organic anion transporting polypeptide (OATP) 2B1 contributes to hepatic uptake of rosuvastatin, atorvastatin and pravastatin, three known substrates. Since OATP2B1 is present in beta cells of the human pancreas, we investigated if OATP2B1 facilitates the local accumulation of statins in a rat beta cell model INS-1 832/13 (INS-1) thereby amplifying statin-induced toxicity. OATP2B1 overexpression in INS-1 cells via adenoviral transduction showed 2.5-, 1.8- and 1.4-fold higher cellular retention of rosuvastatin, atorvastatin and pravastatin, respectively, relative to LacZ control, while absolute intracellular concentration was about twice as high for the lipophilic atorvastatin compared to the more hydrophilic rosuvastatin and pravastatin. After 24 h statin treatment at high concentrations, OATP2B1 enhanced statin toxicity involving activation of intrinsic apoptosis (caspase 3/7 activation) and mitochondrial dysfunction (NADH dehydrogenase activity) following rosuvastatin and atorvastatin, which was partly reversed by isoprenoids. OATP2B1 had no effect on statin-induced reduction in GSIS, mitochondrial electron transport chain complex expression or caspase 9 activation. We confirmed a dose-dependent reduction in insulin secretion by rosuvastatin and atorvastatin in native INS-1 with a modest change in cellular ATP. Collectively, our results indicate a role of OATP2B1, which is abundant in human beta cells, in statin accumulation and statin-induced toxicity but not insulin secretion of rosuvastatin and atorvastatin in INS-1 cells.

Mining local exome and HLA data to characterize pharmacogenetic variants in Saudi Arabia

Pharmacogenomics (PGx) is a promising field of precision medicine where efficacy of drugs is maximized while side effects are minimized for individual patients. Knowledge of the frequency of PGx-relevant variants (pharmacovariants) in the local population is a pre-requisite to informed policy making. Unfortunately, such knowledge is largely lacking from the Middle East. Here, we describe the use of a large clinical exome database (n = 13,473) and HLA haplotypes (n = 64,737) from Saudi Arabia, one of the largest countries in the Middle East, along with previously published data from the local population to ascertain allele frequencies of known pharmacovariants. In addition, we queried another exome database (n = 816) of well-phenotyped research subjects from Saudi Arabia to discover novel candidate variants in known PGx genes (pharmacogenes). Although our results show that only 26% (63/242) of class 1A/1B PharmGKB variants were identified, we estimate that 99.57% of the local population have at least one such variant. This translates to a minimum estimated impact of 9% of medications dispensed by our medical center annually. We also highlight the contribution of rare variants where 71% of the pharmacogenes devoid of common pharmacovariants had at least one potentially deleterious rare variant. Thus, we show that approaches that go beyond the use of commercial PGx kits that have been optimized for other populations should be implemented to ensure universal and equitable access of all members of the local population to personalized prescription practices.

Ticagrelor Increases Exposure to the Breast Cancer Resistance Protein Substrate Rosuvastatin

Ticagrelor and rosuvastatin are often used concomitantly after atherothrombotic events. Several cases of rhabdomyolysis during concomitant ticagrelor and rosuvastatin have been reported, suggesting a drug-drug interaction. We showed recently that ticagrelor inhibits breast cancer resistance protein (BCRP) and organic anion transporting polypeptide (OATP) 1B1, 1B3, and 2B1-mediated rosuvastatin transport in vitro. The aim of this study was to investigate the effects of ticagrelor on rosuvastatin pharmacokinetics in humans. In a randomized, crossover study, 9 healthy volunteers ingested a single dose of 90 mg ticagrelor or placebo, followed by a single 10 mg dose of rosuvastatin 1 hour later. Ticagrelor 90 mg or placebo were additionally administered 12, 24, and 36 hours after their first dose. Ticagrelor increased rosuvastatin area under the plasma concentration-time curve (AUC) and peak plasma concentration 2.6-fold (90% confidence intervals: 1.8-3.8 and 1.7-4.0, P = 0.001 and P = 0.003), and prolonged its half-life from 3.1 to 6.6 hours (P = 0.009). Ticagrelor also decreased the renal clearance of rosuvastatin by 11% (3%-19%, P = 0.032). The N-desmethylrosuvastatin:rosuvastatin AUC0-10h ratio remained unaffected by ticagrelor. Ticagrelor had no effect on the plasma concentrations of the endogenous OATP1B substrates glycodeoxycholate 3-O-glucuronide, glycochenodeoxycholate 3-O-glucuronide, glycodeoxycholate 3-O-sulfate, and glycochenodeoxycholate 3-O-sulfate, or the sodium-taurocholate cotransporting polypeptide substrate taurocholic acid. These data indicate that ticagrelor increases rosuvastatin concentrations more than twofold in humans, probably mainly by inhibiting intestinal BCRP. Because the risk for rosuvastatin-induced myotoxicity increases along with rosuvastatin plasma concentrations, using ticagrelor concomitantly with high doses of rosuvastatin should be avoided.

Inhibition of efflux transporters by poly ADP-ribose polymerase inhibitors

Poly ADP-ribose polymerase (PARP) inhibitors have been approved for the treatment of various cancers. They share a similar mechanism of action but have differences in pharmacokinetic characteristics and potential for drug-drug interactions (DDI). This study evaluated the potential ATP-binding cassette transporter-mediated interactions between PARP inhibitors (niraparib, olaparib and rucaparib) and statins (atorvastatin and rosuvastatin). We studied the inhibitory activity of PARP inhibitors on breast cancer resistance protein (BCRP), multidrug resistance-associated protein 3 (MRP3) and P-glycoprotein (P-gp) using vesicular transport assays and determined the concentrations required for 50% inhibition (IC50 ). Then, we predicted the increase of statin exposure followed by the administration of PARP inhibitors using a mechanistic static model. Rucaparib was the strongest inhibitor of BCRP-mediated rosuvastatin transport (IC50 13.7 μM), followed by niraparib (42.6 μM) and olaparib (216 μM). PARP inhibitors did not affect MRP3. While niraparib appeared to inhibit P-gp, the inhibition showed large variability. The inhibition of intestinal BCRP by rucaparib, niraparib and olaparib was predicted to elevate rosuvastatin exposure by 52%, 37% and 24%, respectively. The interactions between PARP inhibitors and rosuvastatin are probably of minor clinical significance alone, but combined with other predisposing factors, they may increase the risk of rosuvastatin-associated adverse effects.

Real-world pharmacogenetics of statin intolerance: effects of SLCO1B1, ABCG2 , and CYP2C9 variants

OBJECTIVE

The association of SLCO1B1 c.521T>C with simvastatin-induced muscle toxicity is well characterized. However, different statins are subject to metabolism and transport also by other proteins exhibiting clinically meaningful genetic variation. Our aim was to investigate associations of SLCO1B1 c.521T>C with intolerance to atorvastatin, fluvastatin, pravastatin, rosuvastatin, or simvastatin, those of ABCG2 c.421C>A with intolerance to atorvastatin, fluvastatin, or rosuvastatin, and that of CYP2C9*2 and *3 alleles with intolerance to fluvastatin.

METHODS

We studied the associations of these variants with statin intolerance in 2042 patients initiating statin therapy by combining genetic data from samples from the Helsinki Biobank to clinical chemistry and statin purchase data.

RESULTS

We confirmed the association of SLCO1B1 c.521C/C genotype with simvastatin intolerance both by using phenotype of switching initial statin to another as a marker of statin intolerance [hazard ratio (HR) 1.88, 95% confidence interval (CI) 1.08-3.25, P  = 0.025] and statin switching along with creatine kinase measurement (HR 5.44, 95% CI 1.49-19.9, P  = 0.011). No significant association was observed with atorvastatin and rosuvastatin. The sample sizes for fluvastatin and pravastatin were relatively small, but SLCO1B1 c.521T>C carriers had an increased risk of pravastatin intolerance defined by statin switching when compared to homozygous reference T/T genotype (HR 2.11, 95% CI 1.01-4.39, P  = 0.047).

CONCLUSION

The current results can inform pharmacogenetic statin prescribing guidelines and show feasibility for the methodology to be used in larger future studies.

Pharmacogenomics: Driving Personalized Medicine

Personalized medicine tailors therapies, disease prevention, and health maintenance to the individual, with pharmacogenomics serving as a key tool to improve outcomes and prevent adverse effects. Advances in genomics have transformed pharmacogenetics, traditionally focused on single gene-drug pairs, into pharmacogenomics, encompassing all "-omics" fields (e.g., proteomics, transcriptomics, metabolomics, and metagenomics). This review summarizes basic genomics principles relevant to translation into therapies, assessing pharmacogenomics' central role in converging diverse elements of personalized medicine. We discuss genetic variations in pharmacogenes (drug-metabolizing enzymes, drug transporters, and receptors), their clinical relevance as biomarkers, and the legacy of decades of research in pharmacogenetics. All types of therapies, including proteins, nucleic acids, viruses, cells, genes, and irradiation, can benefit from genomics, expanding the role of pharmacogenomics across medicine. Food and Drug Administration approvals of personalized therapeutics involving biomarkers increase rapidly, demonstrating the growing impact of pharmacogenomics. A beacon for all therapeutic approaches, molecularly targeted cancer therapies highlight trends in drug discovery and clinical applications. To account for human complexity, multicomponent biomarker panels encompassing genetic, personal, and environmental factors can guide diagnosis and therapies, increasingly involving artificial intelligence to cope with extreme data complexities. However, clinical application encounters substantial hurdles, such as unknown validity across ethnic groups, underlying bias in health care, and real-world validation. This review address the underlying science and technologies germane to pharmacogenomics and personalized medicine, integrated with economic, ethical, and regulatory issues, providing insights into the current status and future direction of health care. SIGNIFICANCE STATEMENT: Personalized medicine aims to optimize health care for the individual patients with use of predictive biomarkers to improve outcomes and prevent adverse effects. Pharmacogenomics drives biomarker discovery and guides the development of targeted therapeutics. This review addresses basic principles and current trends in pharmacogenomics, with large-scale data repositories accelerating medical advances. The impact of pharmacogenomics is discussed, along with hurdles impeding broad clinical implementation, in the context of clinical care, ethics, economics, and regulatory affairs.

Rhabdomyolysis during concomitant ticagrelor and rosuvastatin: A breast cancer resistance protein-mediated drug interaction?

We present 3 patients diagnosed with rhabdomyolysis 1-6 months after the initiation of concomitant rosuvastatin and ticagrelor medication. A literature review and Food and Drug Administration adverse event reporting system revealed >40 reports of rhabdomyolysis during concomitant ticagrelor and rosuvastatin, including 3 with a fatal outcome. We show that ticagrelor inhibits breast cancer resistance protein-, organic anion transporting polypeptide (OATP) 1B1-, 1B3- and 2B1-mediated transport of rosuvastatin in vitro with half-maximal unbound inhibitory concentrations of 0.36, 4.13, 7.5 and 3.26 μM, respectively. A static drug interaction model predicted that ticagrelor may inhibit intestinal breast cancer resistance protein and thus increase rosuvastatin plasma exposure 2.1-fold, whereas the OATP-mediated hepatic uptake of rosuvastatin should not be inhibited due to relatively low portal ticagrelor concentrations. Taken together, concomitant use of ticagrelor with rosuvastatin may increase the systemic exposure to rosuvastatin and the risk of rosuvastatin-induced rhabdomyolysis. Further studies are warranted to investigate the potential pharmacokinetic interaction between ticagrelor and rosuvastatin in humans.

Drug-drug interactions that alter the exposure of glucuronidated drugs: Scope, UDP-glucuronosyltransferase (UGT) enzyme selectivity, mechanisms (inhibition and induction), and clinical significance

Drug-drug interactions (DDIs) arising from the perturbation of drug metabolising enzyme activities represent both a clinical problem and a potential economic loss for the pharmaceutical industry. DDIs involving glucuronidated drugs have historically attracted little attention and there is a perception that interactions are of minor clinical relevance. This review critically examines the scope and aetiology of DDIs that result in altered exposure of glucuronidated drugs. Interaction mechanisms, namely inhibition and induction of UDP-glucuronosyltransferase (UGT) enzymes and the potential interplay with drug transporters, are reviewed in detail, as is the clinical significance of known DDIs. Altered victim drug exposure arising from modulation of UGT enzyme activities is relatively common and, notably, the incidence and importance of UGT induction as a DDI mechanism is greater than generally believed. Numerous DDIs are clinically relevant, resulting in either loss of efficacy or an increased risk of adverse effects, necessitating dose individualisation. Several generalisations relating to the likelihood of DDIs can be drawn from the known substrate and inhibitor selectivities of UGT enzymes, highlighting the importance of comprehensive reaction phenotyping studies at an early stage of drug development. Further, rigorous assessment of the DDI liability of new chemical entities that undergo glucuronidation to a significant extent has been recommended recently by regulatory guidance. Although evidence-based approaches exist for the in vitro characterisation of UGT enzyme inhibition and induction, the availability of drugs considered appropriate for use as 'probe' substrates in clinical DDI studies is limited and this should be research priority.

The frequency of rs2231142 in ABCG2 among Native Hawaiian and Pacific Islander subgroups: implications for personalized rosuvastatin dosing

Statins are among the most commonly prescribed medications worldwide. Rosuvastatin is a moderate- to high-intensity statin depending on the prescribed dose. Statin-associated muscle symptoms are the main side effects, contributing to low adherence to statins. The missense variant rs2231142 in ABCG2 affects the functionality of the ABCG2 transporter, altering the pharmacokinetics and pharmacodynamics of rosuvastatin. This special report aims to accentuate the importance of considering the ABCG2 genotype upon prescribing rosuvastatin in high cardiovascular disease risk subgroups, specifically Native Hawaiian and Pacific Islander populations. Based on the reported frequencies of rs2231142 in ABCG2, it may be justifiable to initiate low-dose rosuvastatin in Samoans relative to Marshallese or Native Hawaiians. Interpopulation differences in pharmacogenetic allele frequencies underscore the need to disaggregate broad population categories to achieve health equity in treatment outcomes.