Genomewide Association Study of Simvastatin Pharmacokinetics

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.].

Transporter Genes and statin-induced Hepatotoxicity

PURPOSE

Hepatotoxicity has emerged as a major cause of statin treatment interruption. Although organic anion-transporting polypeptide 1B1 (SLCO1B1), multidrug resistance protein 1 (ABCB1), and breast cancer resistance protein (ABCG2) have been identified as transporters of statins, knowledge of their role in statin-associated hepatotoxicity remains limited. Therefore, we aimed to conduct a comprehensive analysis to elucidate the association between hepatotoxicity and SLCO1B1, ABCB1, and ABCG2 polymorphisms.

METHODS

This study retrospectively analyzed prospectively collected samples. We selected 10 single nucleotide polymorphisms (SNPs) of SLCO1B1, 9 SNPs of ABCB1, and 12 SNPs of ABCG2. We developed two models for multivariable analyses (Model I: clinical factors only; Model II: both clinical and genetic factors), and the attributable risk (%) of variables in Model II was determined.

RESULTS

Among 851 patients, 66 (7.8%) developed hepatotoxicity. In Model I, lipophilic statins, atrial fibrillation (Afib), and diabetes mellitus showed a significant association with hepatotoxicity. In Model II, lipophilic statins and Afib, SLCO1B1 rs11045818 A allele, SLCO1B1 rs4149035 T allele, and ABCG2 rs2622629 TT genotype were associated with higher hepatotoxicity risk. Among them, the SLCO1B1 rs11045818 A allele exhibited the highest attributable risk (93.2%). The area under the receiver operating characteristic curve in Model I was 0.62 (95% CI: 0.55-0.69), and it was increased to 0.71 in Model II (95% CI: 0.64-0.77).

CONCLUSION

This study investigated the correlation between hepatotoxicity and polymorphisms of transporter genes in patients taking statins. The findings could help improve personalized treatments for patients receiving statin therapy.

SLCO1B1 Exome Sequencing and Statin Treatment Response in 64,000 UK Biobank Patients

The solute carrier organic anion transporter family member 1B1 (SLCO1B1) encodes the organic anion-transporting polypeptide 1B1 (OATP1B1 protein) that transports statins to liver cells. Common genetic variants in SLCO1B1, such as *5, cause altered systemic exposure to statins and therefore affect statin outcomes, with potential pharmacogenetic applications; yet, evidence is inconclusive. We studied common and rare SLCO1B1 variants in up to 64,000 patients from UK Biobank prescribed simvastatin or atorvastatin, combining whole-exome sequencing data with up to 25-year routine clinical records. We studied 51 predicted gain/loss-of-function variants affecting OATP1B1. Both SLCO1B1*5 alone and the SLCO1B1*15 haplotype increased LDL during treatment (beta*5 = 0.08 mmol/L, p = 6 × 10-8; beta*15 = 0.03 mmol/L, p = 3 × 10-4), as did the likelihood of discontinuing statin prescriptions (hazard ratio*5 = 1.12, p = 0.04; HR*15 = 1.05, p = 0.04). SLCO1B1*15 and SLCO1B1*20 increased the risk of General Practice (GP)-diagnosed muscle symptoms (HR*15 = 1.22, p = 0.003; HR*20 = 1.25, p = 0.01). We estimated that genotype-guided prescribing could potentially prevent 18% and 10% of GP-diagnosed muscle symptoms experienced by statin patients, with *15 and *20, respectively. The remaining common variants were not individually significant. Rare variants in SLCO1B1 increased LDL in statin users by up to 1.05 mmol/L, but replication is needed. We conclude that genotype-guided treatment could reduce GP-diagnosed muscle symptoms in statin patients; incorporating further SLCO1B1 variants into clinical prediction scores could improve LDL control and decrease adverse events, including discontinuation.

Bioequivalence Study of Two Formulations of Simvastatin 20 mg Tablet in Healthy Filipino Participants under Fasting Conditions: A Randomized, Open-label, Two-way Crossover Study

Objectives

Bioequivalence studies provide evidence that generic drugs can produce the same blood levels as the innovator, suggesting similar efficacy and safety and indicating interchangeability without the need to titrate dosing. This study aimed to compare the rate and extent of absorption of two simvastatin 20 mg tablets of Pascual Laboratories, Inc. with two Zocor 20 mg tablets of Merck Sharp & Dohme (I.A.) Corp. in healthy Filipinos. The study also monitored the safety and tolerability of the medications, under the same conditions. Proof of bioequivalence is required by FDA Philippines to establish the interchangeability of generic products and their innovators.

Methods

Twenty-four healthy participants were administered with a single oral dose of two 20 mg simvastatin tablets under fasting conditions, in a randomized, open-label, blind-endpoint analysis, two-way crossover study, with a washout period of one week. Pharmacokinetic blood sampling was done up to 24 h post-dose. Simvastatin was measured using Liquid Chromatography-Tandem Mass Spectrometry with a validated method. The geometric mean ratios for maximum plasma concentration (Cmax) and area under the plasma-concentration-time curve from time zero to the last observed concentration at time 24 h (AUC0-24) were used for bioequivalence.

Results

All 24 participants, 12 males and 12 females, completed the study. Mean age was 24.21 years, mean weight was 58.81 kg, and mean BMI was 23.16 kg/m2. The ratios of Cmax and AUC0-24 were 102.17% (90% CI: 89.19-117.03), and 101.29% (90% CI: 86.87-118.10), respectively, and were both within the bioequivalence limits of 80% to 125%. No adverse event was reported and both formulations were well-tolerated.

Conclusion

Simvastatin 20 mg tablet of Pascual Laboratories, Inc. and the innovator Zocor 20 mg tablet are bioequivalent. Single two-tablet doses of both products are safe and well tolerated.

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.

Solanidine is a sensitive and specific dietary biomarker for CYP2D6 activity

BACKGROUND

Individual assessment of CYP enzyme activities can be challenging. Recently, the potato alkaloid solanidine was suggested as a biomarker for CYP2D6 activity. Here, we aimed to characterize the sensitivity and specificity of solanidine as a CYP2D6 biomarker among Finnish volunteers with known CYP2D6 genotypes.

RESULTS

Using non-targeted metabolomics analysis, we identified 9152 metabolite features in the fasting plasma samples of 356 healthy volunteers. Machine learning models suggested strong association between CYP2D6 genotype-based phenotype classes with a metabolite feature identified as solanidine. Plasma solanidine concentration was 1887% higher in genetically poor CYP2D6 metabolizers (gPM) (n = 9; 95% confidence interval 755%, 4515%; P = 1.88 × 10-11), 74% higher in intermediate CYP2D6 metabolizers (gIM) (n = 89; 27%, 138%; P = 6.40 × 10-4), and 35% lower in ultrarapid CYP2D6 metabolizers (gUM) (n = 20; 64%, - 17%; P = 0.151) than in genetically normal CYP2D6 metabolizers (gNM; n = 196). The solanidine metabolites m/z 444 and 430 to solanidine concentration ratios showed even stronger associations with CYP2D6 phenotypes. Furthermore, the areas under the receiver operating characteristic and precision-recall curves for these metabolic ratios showed equal or better performances for identifying the gPM, gIM, and gUM phenotype groups than the other metabolites, their ratios to solanidine, or solanidine alone. In vitro studies with human recombinant CYP enzymes showed that solanidine was metabolized mainly by CYP2D6, with a minor contribution from CYP3A4/5. In human liver microsomes, the CYP2D6 inhibitor paroxetine nearly completely (95%) inhibited the metabolism of solanidine. In a genome-wide association study, several variants near the CYP2D6 gene associated with plasma solanidine metabolite ratios.

CONCLUSIONS

These results are in line with earlier studies and further indicate that solanidine and its metabolites are sensitive and specific biomarkers for measuring CYP2D6 activity. Since potato consumption is common worldwide, this biomarker could be useful for evaluating CYP2D6-mediated drug-drug interactions and to improve prediction of CYP2D6 activity in addition to genotyping.

A Case Report of Drug Interactions Between Nirmatrelvir/Ritonavir and Tacrolimus in a Patient With Systemic Lupus Erythematosus

Nirmatrelvir/ritonavir is a treatment for COVID-19 consisting of nirmatrelvir, which has anti-SARS-CoV-2 activity, and ritonavir, a booster to maintain blood levels. Ritonavir is known to be a potent inhibitor of cytochrome P450 3A (CYP3A), and interactions with CYP3A-metabolized drugs, such as the immunosuppressant tacrolimus, can be problematic. Ritonavir's inhibition of CYP3A is irreversible due to covalent binding, and its inhibitory effects are expected to persist until replaced by new CYP3A. Here, we report a case where the combination of nirmatrelvir/ritonavir and tacrolimus resulted in toxic tacrolimus blood levels. A patient on tacrolimus for systemic lupus erythematosus (SLE) developed COVID-19 and was prescribed nirmatrelvir/ritonavir. After starting the combination of nirmatrelvir/ritonavir and tacrolimus, the patient's tacrolimus blood levels became abnormally high, leading to the discontinuation of these drugs due to symptoms of tacrolimus toxicity. Even after ritonavir blood levels had fallen below the detection limit, the decline in tacrolimus blood levels was delayed. The CYP3A inhibition of ritonavir persists even when its blood concentration decreases, emphasizing the need for careful consideration of concomitant medications before starting nirmatrelvir/ritonavir therapy. Adjustments or discontinuation may be necessary.

Interindividual variability in statin pharmacokinetics and effects of drug transporters

INTRODUCTION

Statins are HMG-CoA reductase inhibitors that primarily lower plasma cholesterol levels. It has been suggested that the myotoxic response is a direct result of hydroxymethylglutaryl-CoA reductase inhibition and dose-dependent. Therefore, an accurate understanding of the combination of drugs that inhibit statin metabolism and factors that cause interindividual variability in the pharmacokinetics of statin is important to avoid serious side effects of statins. Relevant articles included in this review were identified through a PubMed search (through May 2023).

AREAS COVERED

This review provides an overview of hepatic and intestinal metabolism of statins, followed by a discussion of drug-drug interactions and interindividual variables that influence statin pharmacokinetics: gut bacteria, disease, and pharmacokinetics-related genetic polymorphisms.

EXPERT OPINION

Drug-drug interactions have a strong influence on statin pharmacokinetics, and gut microbiota, disease, and genetic polymorphisms all contribute significantly to interindividual variation in statin pharmacokinetics. Individual optimization of statin treatment requires studies that consider the progression of the disease and associated changes in concomitant medications.

Recent updates on nano-phyto-formulations based therapeutic intervention for cancer treatment

Cancer is a leading cause of death globally, with limited treatment options and several limitations. Chemotherapeutic agents often result in toxicity which long-term conventional treatment. Phytochemicals are natural constituents that are more effective in treating various diseases with less toxicity than the chemotherapeutic agents providing alternative therapeutic approaches to minimize the resistance. These phytoconstituents act in several ways and deliver optimum effectiveness against cancer. Nevertheless, the effectiveness of phyto-formulations in the management of cancers may be constrained due to challenges related to inadequate solubility, bioavailability, and stability. Nanotechnology presents a promising avenue for transforming current cancer treatment methods through the incorporation of phytochemicals into nanosystems, which possess a range of advantageous characteristics such as biocompatibility, targeted and sustained release capabilities, and enhanced protective effects. This holds significant potential for future advancements in cancer management. Herein, this review aims to provide intensive literature on diverse nanocarriers, highlighting their applications as cargos for phytocompounds in cancer. Moreover, it offers an overview of the current advancements in the respective field, emphasizing the characteristics that contribute to favourable outcomes in both in vitro and in vivo settings. Lastly, clinical development and regulatory concerns are also discussed to check on the transformation of the concept as a promising strategy for combination therapy of phytochemicals and chemotherapeutics that could lead to cancer management in the future.

A gene risk score using missense variants in SLCO1B1 is associated with earlier onset statin intolerance

BACKGROUND AND AIMS

The efficacy of statin therapy is hindered by intolerance to the therapy, leading to discontinuation. Variants in SLCO1B1, which encodes the hepatic transporter OATB1B1, influence statin pharmacokinetics, resulting in altered plasma concentrations of the drug and its metabolites. Current pharmacogenetic guidelines require sequencing of the SLCO1B1 gene, which is more expensive and less accessible than genotyping. In this study, we aimed to develop an easy, clinically implementable functional gene risk score (GRS) of common variants in SLCO1B1 to identify patients at risk of statin intolerance.

METHODS AND RESULTS

A GRS was developed from four common variants in SLCO1B1. In statin users from Tayside, Scotland, UK, those with a high-risk GRS had increased odds across three phenotypes of statin intolerance [general statin intolerance (GSI): ORGSI 2.42; 95% confidence interval (CI): 1.29-4.31, P = 0.003; statin-related myopathy: ORSRM 2.51; 95% CI: 1.28-4.53, P = 0.004; statin-related suspected rhabdomyolysis: ORSRSR 2.85; 95% CI: 1.03-6.65, P = 0.02]. In contrast, using the Val174Ala genotype alone or the recommended OATP1B1 functional phenotypes produced weaker and less reliable results. A meta-analysis with results from adjudicated cases of statin-induced myopathy in the PREDICTION-ADR Consortium confirmed these findings (ORVal174Ala 1.99; 95% CI: 1.01-3.95, P = 0.048; ORGRS 1.76; 95% CI: 1.16-2.69, P = 0.008). For those requiring high-dose statin therapy, the high-risk GRS was more consistently associated with the time to onset of statin intolerance amongst the three phenotypes compared with Val174Ala (GSI: HRVal174Ala 2.49; 95% CI: 1.09-5.68, P = 0.03; HRGRS 2.44; 95% CI: 1.46-4.08, P < 0.001). Finally, sequence kernel association testing confirmed that rare variants in SLCO1B1 are associated with the risk of intolerance (P = 0.02).

CONCLUSION

We provide evidence that a GRS based on four common SLCO1B1 variants provides an easily implemented genetic tool that is more reliable than the current recommended practice in estimating the risk and predicting early-onset statin intolerance.

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.

Characterization of Bile Acid Sulfate Conjugates as Substrates of Human Organic Anion Transporting Polypeptides

Drug interactions involving the inhibition of hepatic organic anion transporting polypeptides (OATPs) 1B1 and OATP1B3 are considered important. Therefore, we sought to study various sulfated bile acids (BA-S) as potential clinical OATP1B1/3 biomarkers. It was determined that BA-S [e.g., glycochenodeoxycholic acid 3-O-sulfate (GCDCA-S) and glycodeoxycholic acid 3-O-sulfate (GDCA-S)] are substrates of OATP1B1, OATP1B3, and sodium-dependent taurocholic acid cotransporting polypeptide (NTCP) transfected into human embryonic kidney 293 cells, with minimal uptake evident for other solute carriers (SLCs) like OATP2B1, organic anion transporter 2, and organic cation transporter 1. It was also shown that BA-S uptake by plated human hepatocytes (PHH) was inhibited (≥96%) by a pan-SLC inhibitor (rifamycin SV), and there was greater inhibition (≥77% versus ≤12%) with rifampicin (OATP1B1/3-selective inhibitor) than a hepatitis B virus myristoylated-preS1 peptide (NTCP-selective inhibitor). Estrone 3-sulfate was also used as an OATP1B1-selective inhibitor. In this instance, greater inhibition was observed with GDCA-S (76%) than GCDCA-S (52%). The study was expanded to encompass the measurement of GCDCA-S and GDCA-S in plasma of SLCO1B1 genotyped subjects. The geometric mean GDCA-S concentration was 2.6-fold (90% confidence interval 1.6, 4.3; P = 2.1 × 10^-4) and 1.3-fold (1.1, 1.7; P = 0.001) higher in individuals homozygous and heterozygous for the SLCO1B1 c.521T > C loss-of-function allele, respectively. For GCDCA-S, no significant difference was noted [1.2-fold (0.8, 1.7; P = 0.384) and 0.9-fold (0.8, 1.1; P = 0.190), respectively]. This supported the in vitro data indicating that GDCA-S is a more OATP1B1-selective substrate (versus GCDCA-S). It is concluded that GCDCA-S and GDCA-S are viable plasma-based OATP1B1/3 biomarkers, but they are both less OATP1B1-selective when compared to their corresponding 3-O-glucuronides (GCDCA-3G and GDCA-3G). Additional studies are needed to determine their utility versus more established biomarkers, such as coproporphyrin I, for assessing inhibitors with different OATP1B1 (versus OATP1B3) inhibition signatures.

Fluorescence-based methods for studying activity and drug-drug interactions of hepatic solute carrier and ATP binding cassette proteins involved in ADME-Tox

In humans, approximately 70% of drugs are eliminated through the liver. This process is governed by the concerted action of membrane transporters and metabolic enzymes. Transporters mediating hepatocellular uptake of drugs belong to the SLC (Solute carrier) superfamily of transporters. Drug efflux either toward the portal vein or into the bile is mainly mediated by active transporters of the ABC (ATP Binding Cassette) family. Alteration in the function and/or expression of liver transporters due to mutations, disease conditions, or co-administration of drugs or food components can result in altered pharmacokinetics. On the other hand, drugs or food components interacting with liver transporters may also interfere with liver function (e.g., bile acid homeostasis) and may even cause liver toxicity. Accordingly, certain transporters of the liver should be investigated already at an early stage of drug development. Most frequently radioactive probes are applied in these drug-transporter interaction tests. However, fluorescent probes are cost-effective and sensitive alternatives to radioligands, and are gaining wider application in drug-transporter interaction tests. In our review, we summarize our current understanding about hepatocyte ABC and SLC transporters affected by drug interactions. We provide an update of the available fluorescent and fluorogenic/activable probes applicable in in vitro or in vivo testing of these ABC and SLC transporters, including near-infrared transporter probes especially suitable for in vivo imaging. Furthermore, our review gives a comprehensive overview of the available fluorescence-based methods, not directly relying on the transport of the probe, suitable for the investigation of hepatic ABC or SLC-type drug transporters.

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

AIMS

The aim was to comprehensively investigate the effects of genetic variability on the pharmacokinetics of rosuvastatin.

METHODS

We conducted a genome-wide association study and candidate gene analyses of single dose rosuvastatin pharmacokinetics in a prospective study (n = 159) and a cohort of previously published studies (n = 88).

RESULTS

In a genome-wide association meta-analysis of the prospective study and the cohort of previously published studies, the SLCO1B1 c.521 T > C (rs4149056) single nucleotide variation (SNV) associated with increased area under the plasma concentration-time curve (AUC) and peak plasma concentration of rosuvastatin (P = 1.8 × 10^-12 and P = 3.2 × 10^-15 ). The candidate gene analysis suggested that the ABCG2 c.421C > A (rs2231142) SNV associates with increased rosuvastatin AUC (P = .0079), while the SLCO1B1 c.388A > G (rs2306283) and SLCO2B1 c.1457C > T (rs2306168) SNVs associate with decreased rosuvastatin AUC (P = .0041 and P = .0076). Based on SLCO1B1 genotypes, we stratified the participants into poor, decreased, normal, increased and highly increased organic anion transporting polypeptide (OATP) 1B1 function groups. The OATP1B1 poor function phenotype associated with 2.1-fold (90% confidence interval 1.6-2.8, P = 4.69 × 10^-5 ) increased AUC of rosuvastatin, whereas the OATP1B1 highly increased function phenotype associated with a 44% (16-62%; P = .019) decreased rosuvastatin AUC. The ABCG2 c.421A/A genotype associated with 2.2-fold (1.5-3.0; P = 2.6 × 10^-4 ) increased AUC of rosuvastatin. The SLCO2B1 c.1457C/T genotype associated with 28% decreased rosuvastatin AUC (11-42%; P = .01).

CONCLUSION

These data suggest roles for SLCO1B1, ABCG2 and SLCO2B1 in rosuvastatin pharmacokinetics. Poor SLCO1B1 or ABCG2 function genotypes may increase the risk of rosuvastatin-induced myotoxicity. Reduced doses of rosuvastatin are advisable for patients with these genotypes.

Effects of SLCO1B1 Genetic Variant on Metabolite Profile in Participants on Simvastatin Treatment

Organic-anion-transporting polypeptide 1B1 (OATP1B1), encoded by the solute carrier organic anion transporter family member 1B1 gene (SLCO1B1), is highly expressed in the liver and transports several endogenous metabolites into the liver, including statins. Previous studies have not investigated the association of SLCO1B1 rs4149056 variant with the risk of type 2 diabetes (T2D) or determined the metabolite signature of the C allele of SLCO1B1 rs4149056 (SLCO1B1 rs4149056-C allele) in a large randomly selected population. SLCO1B1 rs4149056-C inhibits OATP1B1 transporter and is associated with increased levels of blood simvastatin concentrations. Our study is to first to show that SLCO1B1 rs4149056 variant is not significantly associated with the risk of T2D, suggesting that simvastatin has a direct effect on the risk of T2D. Additionally, we investigated the effects of SLCO1B1 rs4149056-C on plasma metabolite concentrations in 1373 participants on simvastatin treatment and in 1368 age- and body-mass index (BMI)-matched participants without any statin treatment. We found 31 novel metabolites significantly associated with SLCO1B1 rs4149056-C in the participants on simvastatin treatment and in the participants without statin treatment. Simvastatin decreased concentrations of dicarboxylic acids, such as docosadioate and dodecanedioate, that may increase beta- and peroxisomal oxidation and increased the turnover of cholesterol into bile acids, resulting in a decrease in steroidogenesis due to limited availability of cholesterol for steroid synthesis. Our findings suggest that simvastatin exerts its effects on the lowering of low-density lipoprotein (LDL) cholesterol concentrations through several distinct pathways in the carriers of SLCO1B1 rs4149056-C, including dicarboxylic acids, bile acids, steroids, and glycerophospholipids.