Impacts of Pharmacokinetic Gene Polymorphisms on Steady‐State Plasma Concentrations of Simvastatin in Thai Population

ABSTRACT

Simvastatin, an HMG‐CoA reductase inhibitor, is widely used for hypercholesterolemia but may cause myotoxicity linked to its plasma concentration. Pharmacokinetic gene polymorphisms influence inter‐individual variability in simvastatin exposure. This study investigated the effects of pharmacokinetic gene polymorphisms on steady‐state simvastatin plasma levels in Thai patients. Eighty‐nine Thai patients with dyslipidemia or coronary artery disease on simvastatin treatment for at least 2 weeks without dose adjustment were recruited from King Chulalongkorn Memorial Hospital. Simvastatin lactone and acid concentrations were measured 12 h post‐dose using UHPLC–MS/MS. Pharmacokinetic gene polymorphisms, including ABCB1, ABCC2, ABCG2, SLCO1B1, SLCO1B3, CYP3A4, and CYP3A5, were genotyped by MassARRAY System. The results showed that patients with the SLCO1B1 c.521TC+CC genotype had significantly higher simvastatin acid levels than those with c.521TT (0.53 vs. 0.19 ng/mL, p = 0.03). Similarly, the SLCO1B1*1b/*15 genotype was associated with higher simvastatin acid levels than SLCO1B1*1a/*1a (0.58 vs. 0.16 ng/mL, p < 0.001). These findings suggest that SLCO1B1 c.521T>C, alone or with c.388A>G (SLCO1B1*1b/*15), reduces OATP1B1 function, leading to elevated simvastatin acid levels and increased myotoxicity risk. This study confirms the association of SLCO1B1 rs4149056 (c.521T>C) with higher simvastatin plasma levels in Thai patients. The study highlights the potential role of SLCO1B1 genotyping, particularly rs4149056 (c.521T>C) and rs2306283 (c.388A>G), in guiding statin therapy for Thai patients, which could help optimize treatment and reduce adverse effects such as statin‐induced myotoxicity.

Summary.

• What is the current knowledge on the topic?

  • ○
    Statin therapy is an effective approach to managing hypercholesterolemia; however, it may result in serious adverse effects, such as myotoxicity. Polymorphisms in pharmacokinetic genes, particularly SLCO1B1, ABCB1, ABCC2, ABCG2, and CYP3A4/5, may contribute to interindividual variability in simvastatin exposure and the associated risk of adverse effects. To date, no studies have demonstrated the impact of pharmacokinetic (drug‐metabolizing enzyme and transporter) gene polymorphisms on steady‐state plasma concentrations of simvastatin in the Thai population.
• What question did this study address?

  • ○
    How do pharmacokinetic gene polymorphisms influence the steady‐state plasma concentrations of simvastatin in Thai patients, potentially leading to an increased risk of simvastatin‐induced myotoxicity?
• What does this study add to our knowledge?

  • ○
    This study specifically demonstrates that the SLCO1B1 c.521T>C variant, alone or in combination with c.388A>G (SLCO1B1*1b/*15), leads to decreased OATP1B1 function, resulting in significantly higher plasma concentrations of simvastatin acid (the active form). These findings confirm that patients with these genetic variants may have an increased risk of simvastatin‐induced myotoxicity.
• How might this change clinical pharmacology or translational science?

  • ○
    The study highlights the potential role of SLCO1B1 genotyping, particularly rs4149056 (c.521T>C) and rs2306283 (c.388A>G), in guiding statin therapy for Thai patients, which may help optimize treatment and reduce adverse effects such as statin‐induced myotoxicity.

1. Introduction

Simvastatin, a 3‐hydroxy‐3‐methylglutaryl‐coenzyme A (HMG‐CoA) reductase inhibitor, is widely used to manage hypercholesterolemia [1, 2]. It is included in the National List of Essential Medicines (NLEM) and is commonly prescribed for dyslipidemia in the Thai population [1]. Statins, including simvastatin, are recommended as the primary lipid‐lowering therapy in the Royal College of Physicians of Thailand's 2024 clinical practice guidelines [2]. Additionally, its availability in generic form makes it a cost‐effective and accessible option. While other statins are available, simvastatin remains a preferred choice due to its effectiveness, affordability, and frequent use in clinical practice. Typically prescribed in doses of 10–40 mg per day, it effectively lowers low‐density lipoprotein cholesterol (LDL‐C) levels by 30%–50% through enhanced LDL uptake via hepatic LDL receptors [3, 4]. However, despite its efficacy, simvastatin can occasionally lead to serious adverse effects, particularly involving the skeletal muscles. These adverse events range from muscle pain (myalgia) and muscle weakness (myopathy) to, in rare cases, the potentially life‐threatening condition of rhabdomyolysis. The increased systemic exposure to simvastatin, due to pharmacokinetic changes, is associated with an elevated risk of simvastatin‐induced myotoxicity [5, 6, 7, 8, 9].

Simvastatin is administrated as an inactive form, simvastatin lactone (SVL) which is then hydrolyzed in vivo into its active form, simvastatin hydroxy acid (SVA), by nonspecific carboxylesterases present in the intestinal wall, liver, and plasma [10]. Both SVL and SVA are primarily metabolized through oxidative processes mediated by the cytochrome P450 enzymes CYP3A4 and CYP3A5 [11, 12, 13]. Due to its lipophilic property of simvastatin, the distribution, including influx and efflux across hepatocytes, mainly occurs via passive diffusion. Conversely, SVA, being relatively more hydrophilic than the lactone form, relies on active transport for its distribution [14]. The uptake of simvastatin acid is predominantly mediated by the OATP1B1 transporter, which is encoded by the SLCO1B1 gene. Besides SLCO1B1, other members of the SLC transporter family, SLCO1B3, may also serve as transporters for simvastatin acid [15, 16]. Nonetheless, their roles in simvastatin pharmacokinetics are still unclear. Additionally, P‐glycoprotein (P‐gp) encoded by the ABCB1 gene, and breast cancer resistance protein (BCRP) encoded by the ABCG2 gene, are also involved in the metabolism and elimination of simvastatin [17, 18]. Hence, the factors affecting the activity of the protein in the pharmacokinetic pathway may increase the risk of simvastatin‐induced myotoxicity [5, 6, 7, 8, 9].

Single nucleotide polymorphisms (SNPs) in various genes encoding metabolizing enzymes and transporters have been implicated in inter‐individual differences in systemic exposure to simvastatin lactone (SVL) and simvastatin acid (SVA). For instance, the SNP rs4149056 c.521T>C in the SLCO1B1 gene is strongly linked to increased systemic exposure to SVA and an elevated risk of myopathy in diverse populations [19, 20, 21]. Additionally, SNPs in the ABCG2 gene, which encodes the ATP‐binding cassette G2 (ABCG2) efflux transporter, have been shown to affect simvastatin exposure [18, 22]. However, the effect ofABCG2 on simvastatin pharmacokinetics is still inconclusive [18, 22, 23]. There is also evidence suggesting that SNPs in metabolizing genes, such as CYP3A4*22 and CYP3A5*3, are associated with alterations in simvastatin pharmacokinetics [24, 25].

However, previous studies have been inconclusive, except for the SLCO1B1 gene, which has a guideline for adjusting simvastatin and other statin dosages when the genotype is known [26]. Furthermore, most research has focused on Caucasian and some Asian populations. To date, there are no studies demonstrating the impact of pharmacokinetic (drug‐metabolizing enzyme and transporter) gene polymorphisms on steady‐state plasma concentrations of simvastatin in the Thai population. Therefore, our study aimed to investigate the effects of pharmacokinetic gene polymorphisms on steady‐state simvastatin plasma concentrations in Thai patients undergoing simvastatin treatment.

2. Materials and Methods

2.1. Participants

Eighty‐nine Thai patients (n = 89) with dyslipidemia or coronary artery diseases (CAD) and treated with simvastatin were recruited from King Chulalongkorn Memorial Hospital (KCMH). The inclusion criteria are as follows: (1) aged < 80 years; (2) taking simvastatin for at least 2 weeks without dose adjustment; and (3) taking medicine regularly (as confirmed by the patient surveyed and the information in their electronic medical record). Participants who had the following factors were excluded from our study: (1) having hypothyroidism, advanced cancer, heavy exercise, or alcohol abuse; (2) using drugs that are CYP3A4 or OATP1B1 strong inhibitors; and (3) having hepatic or renal diseases. The study received approval from the Institutional Review Board of the Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand (IRB No. 328/63). All procedures were conducted in compliance with the international guidelines for human research protection, such as the Declaration of Helsinki, The Belmont Report, the Council for International Organizations of Medical Sciences (CIOMS) Guideline, and the International Conference on Harmonization in Good Clinical Practice (ICH‐GCP). Informed consent was obtained from all participants or their legal guardians prior to their participation in the study.

2.2. Blood Collection

Blood samples were obtained from each eligible patient in the morning at approximately 12 h after the final dose of simvastatin. The blood samples from each patient were collected in EDTA‐coated tubes (3 mL, 2 tubes) for the following analysis: (1) the whole blood from an EDTA‐coated tube (3 mL) was used for DNA extraction and genetic analysis; and (2) the 12‐h post‐dose plasma sample from an EDTA‐coated tube (3 mL) was used for the quantification of simvastatin lactone (SVL) and simvastatin hydroxy acid (SVA) concentrations in plasma using the UHPLC–MS/MS method. It was immediately separated (within 2 h) by centrifugation at 3000 rpm for 10 min at room temperature. Plasma samples used for simvastatin analysis were immediately mixed with 1 M ammonium acetate (pH 4.5) at a 5:100 (buffer/plasma) ratio after separation and stored at −80°C until usage.

2.3. Simvastatin Concentration Analysis Method

The steady‐state plasma concentrations (12 h after the final dose) of simvastatin lactone (SVL) and simvastatin acid (SVA) from the patients were analyzed using ultra‐high performance liquid chromatography–tandem mass spectrometry (UHPLC–MS/MS). This method was adjusted from Partini et al. [27] by the Drug Metabolism and Pharmacokinetics (DMPK) unit at the Chulalongkorn Drug Discovery and Drug Development Research (Chula4DR) center. In brief, 300 μL of human EDTA‐plasma, which contained 1 M ammonium acetate at pH 4.5 and was processed immediately after blood collection, was spiked with 30 μL of 50% acetonitrile (ACN) (Burdick & Jackson), 60 μL of combined internal standards (IS) (40 ng/mL) simvastatin‐d6 (SV‐d6) and simvastatin‐d6 hydroxy acid ammonium salt (SVA‐d6), and 100 μL of 1 M ammonium acetate at pH 4.5. The analytes SVL and SVA were isolated from plasma by liquid–liquid extraction (LLE) using methyl tert‐butyl ether (MTBE) (Tokyo Chemical Industry, Japan). After centrifugation, the organic phases were transferred into new pre‐labeled microcentrifuge tubes, dried under a nitrogen evaporator, and then reconstituted with 40% ACN combined with 60% 2 mM ammonium acetate at pH 4.5. All solutions were transferred to a 96‐well U‐shaped plate and analyzed using UHPLC–MS/MS with positive and negative electrospray ionization (ESI) modes at two different periods. All standard analytes were purchased from Toronto Research Chemicals. The chemical reagents (ammonium acetate, ACN, and ammonia solution (28% in Water)) were purchased from Tokyo Chemical Industry and glacial acetic acid was obtained from Merck.

Chromatographic separation was performed on a Kinetex 1.7 μm C18 100 Å, 50 × 2.1 mm ID column with SecurityGuard Ultra (C18 for 2.1 mm ID column) at 45°C with a total run time per sample of 3 min. Separation of SVL and SVA was performed with gradient elution by using two different mobile phases: (A) 90% (v/v) of 2 mM ammonium acetate (pH 4) combined with 10% (v/v) ACN; and (B) 10% (v/v) of 2 mM ammonium acetate (pH 4) combined with 90% (v/v) ACN, pumping at a flow rate of 0.6 mL/min. The analytes were monitored by using multiple‐reaction monitoring (MRM) with the transition 435.2 → 319.0 m/z for SVA, 441.2 → 318.9 m/z for SVA‐d6, 436.1 → 199.0 m/z for SVL, and 442.4 → 199.0 m/z for SVL‐d6. Integration of peak areas and determination of the concentrations were performed with Analyst 1.6.3 software (SCIEX) and MultiQuantTM 3.0.2 software.

The validated calibration standard concentrations were 0.05, 0.1, 0.2, 0.5, 1, 2, 5, 10, and 50 ng/mL for SVL and 0.2, 0.5, 1, 2, 5, 10, and 50 ng/mL for SVA. The lower limit of quantification (LLOQ) was 0.05 ng/mL for SVL and 0.2 ng/mL for SVA. Linearity of all analytes was observed within the range of 0.05–50 ng/mL for SVL and 0.2–50 ng/mL for SVA. Intra‐ and inter‐day precisions were ≤ 15% for three quality control levels (LQC: 0.1 ng/mL for SVL and 0.5 ng/mL for SVA, MQC: 20 ng/mL, HQC: 40 ng/mL) and ≤ 20% for the LLOQ. The accuracy of the QC samples was 80%–120% of the theoretical concentrations at the LLOQ level and 85%–115% at the three other quality control levels for the analytes.

The steady state of SVL and SVA plasma concentrations (Css) was normalized by dividing SVL and SVA concentrations by the administrated dose in milligrams (5–40 mg/day). The steady‐state concentrations per dose were presented as Css/Dose.

2.4. Genomic DNA Preparations by QIAamp Blood Mini Kit

The genomic DNA was extracted from EDTA‐whole blood 200 μL using the QIAamp Blood Mini Kit (QIAGEN, Valencia, CA). The concentration of genomic DNA was assessed by using NanoDrop One for measuring genomic DNA as well as purity. The three different wavelengths were used, including 260 nm, which is suitable for measuring the amount of genomic DNA; 280 nm, which is used to evaluate contaminated protein in the sample; and 230 nm, which is used for determining the organic compound. The purity of DNA was evaluated by the ratio of optical density (OD) at 260/280 nm, which should be in the range of 1.8–2.0, and the ratio of OD at 260/230 will be in the range of 1.8–2.2.

2.5. SNPs Genotyping Assay Using MassARRAY System by Agena Bioscience

MassARRAY System (Agena Bioscience, USA) genotyping platform was used to genotype the 10 variants from seven candidate genes which were previously reported to be associated with statin‐induced myotoxicity and/or pharmacokinetic parameters of statins including ABCB1 (rs1045642), ABCC2 (rs717620 and rs3740066), ABCG2 (rs2231142), SLCO1B1 (rs4149056, and rs2306283), SLCO1B3 (rs7311358 and rs4149117), CYP3A4*1G (rs2242480), and CYP3A5*3 (rs776746). Genotyping quality control was ensured by assessing Hardy–Weinberg equilibrium (HWE) deviation and potential batch effects. The QC call rate exceeded 95% for all SNPs and samples, ensuring accuracy. TyperAnalyzer software was used to generate and report the results.

2.6. Statistical Analysis

Genetic polymorphisms were assessed for concordance with Hardy–Weinberg equilibrium (HWE). The data were tested for the normality of data distribution. Of these, our data showed a non‐normal distribution. Thus, the following analyses were performed using tests for non‐normal distribution data. Descriptive statistics of patients were presented as median and interquartile range (IQR) for non‐normal distribution of the data. The Mann–Whitney U test was used to compare the continuous variables between two groups. The comparison of data from more than two groups, such as the genetic polymorphisms (wildtype, heterozygous, and homozygous variant) and simvastatin plasma concentrations, was analyzed by using Kruskal–Wallis. Multiple regression analysis was performed to evaluate the potential impact of batch effects on the association between SLCO1B1 c.521T>C and simvastatin acid levels. All statistical analyses were carried out using SPSS version 28.0 for Windows (SPSS Inc., Chicago, IL, United States). The p values < 0.05 were considered statistically significant.

3. Results

3.1. Characteristics of Study Participants

The clinical data revealed that the median age of the patients in this study was 68 years, with 33% male and 67% female. The average body mass index (BMI) in this group was 23.83 kg per square meter (kg/m²). In this patient group, 47.20% received a simvastatin dose of 10 mg/day, followed by 20 mg/day (38.20%), 5 mg/day (9.00%), and 40 mg/day (5.60%). Characteristics of the study participants were summarized in Table 1.

TABLE 1.

Characteristics of study participants.

Characteristics	Simvastatin‐treated patients (n = 89)
Age, years	68.00 (60.75–75.00)
Gender, M/F, n (%)	29/60 (32.60/67.40)
BMI, kg/m2	23.83 (21.62–27.19)
Biochemical parameters
Total cholesterol, TC (mg/dL)	168.00 (146.50–187.25)
Low‐density lipoprotein cholesterol, LDL‐C (mg/dL)	97.00 (72.75–108.25)
High‐density lipoprotein cholesterol, HDL‐C (mg/dL)	50.00 (45.00–66.00)
Triglyceride, TG (mg/dL)	104.50 (80.75–140.50)
Fasting blood sugar, FBS (mg/dL)	103.00 (94.00–120.50)
Aspartate transaminase, AST (U/L)	21.00 (17.00–25.00)
Alanine transaminase, ALT (U/L)	18.00 (14.75–24.75)
Blood urea nitrogen, BUN (mg/dL)	15.00 (12.00–17.00)
Creatinine, Cr (mmol/L)	0.83 (0.68–0.99)
Estimated glomerular filtration rate, eGFR (mL/min/1.73m2)	76.85 (67.42–86.09)
Creatine phosphokinase, CPK (U/L)	98.00 (68.00–131.00)
Dose, n (%)
5 mg	8 (9.00)
10 mg	42 (47.20)
20 mg	34 (38.20)
40 mg	5 (5.60)
Median concentration per dose (ng/mL)
Simvastatin lactone (SVL)	0.02 (0.01–0.03)
Simvastatin hydroxy acid (SVA)	0.20 (0.13–0.44)

Note: The continuous data was presented as median (IQR).

3.2. Allele and Genotype Frequencies Among the Study Participants

The genotype and allele frequencies for all analyzed polymorphisms are summarized in Table 2, based on a sample size of 89 individuals. For rs4149056 (SLCO1B1 c.521T>C), the observed genotype frequencies were 89.89% for TT (wild type), 10.11% for TC (heterozygous), and 0.00% for CC (homozygous variant), with a C allele frequency of 5.06%. For rs2306283 (SLCO1B1 c.388A>G), the genotype frequencies were 19.10% for AA (wild type), 37.08% for AG (heterozygous), and 43.82% for GG (homozygous variant), with a G allele frequency of 62.36%.

TABLE 2.

Allele and genotype frequencies among the study participants (n = 89).

Gene	rs number	SNP	Allele	Frequency	Genotype	Frequency	Hardy–Weinberg p value
Efflux transporters
ABCB1	rs1045642	3435C>T	C	58.43	CC	15.73	0.74
			T	41.57	CT	51.69
					TT	32.58
ABCC2	rs717620	−24C>T	C	78.65	CC	61.80	1.00
			T	21.35	CT	33.71
					TT	4.49
ABCC2	rs3740066	3971C>T	C	74.72	CC	55.06	0.98
			T	25.28	CT	39.33
					TT	5.62
ABCG2	rs2231142	421C>A	C	72.47	CC	55.06	0.32
			A	27.53	CA	34.83
					AA	10.11
Uptake transporters
SLCO1B1	rs4149056	521T>C	T	94.94	TT	89.89	1.00
			C	5.06	TC	10.11
					CC	0.00
SLCO1B1	rs2306283	388A>G	A	37.64	AA	19.10	0.07
			G	62.36	AG	37.08
					GG	43.82
SLCO1B3	rs7311158	699G>A	G	28.09	GG	6.74	0.84
			A	71.91	GA	42.70
					AA	50.56
SLCO1B3	rs4149117	334T>G	T	24.16	TT	6.74	0.80
			G	75.84	TG	34.83
					GG	58.43
Drug‐metabolizing enzymes
CYP3A4*1G	rs2242480	20230G>A	G	69.10	GG	48.31	0.95
			A	30.90	GA	41.47
					AA	10.11
CYP3A5*3	rs776746	6986A>G	A	47.19	AA	15.73	0.03
			G	52.81	AG	62.92
					GG	21.35

3.3. Impacts of Pharmacokinetic (PK) Gene Polymorphisms on 12‐h Simvastatin Plasma Concentrations

Among 10 SNPs from seven genes in the pharmacokinetic pathway of statins, patients with the SLCO1B1 c.521TC+CC genotype had a significantly higher SVA compared to those with the c.521TT genotype (0.53 vs. 0.19 ng/mL, respectively) with a p value of 0.03 (Table 3, Figure 1B). According to the CPIC 2022 guidelines [26], the SLCO1B1 loss‐of‐function alleles include *5 and *15, while the normal function allele is *1, comprising *1a and *1b. The diplotype‐predicted phenotypes are classified as follows: *1a/*1a, *1a/*1b, and *1b/*1b are considered normal function, whereas *1 (*1a or *1b) combined with *5 or *15 is categorized as decreased function. SLCO1B1*1b/*15 (decrease function) had significantly higher SVA concentrations compared to SLCO1B1*1a/*1a (0.58 vs. 0.16 ng/mL, p value < 0.001, Table 4). Moreover, patients with decreased OATP1B1 function, including those with *1b/*5 and *1b/*15, showed consistent increases in simvastatin acid concentrations compared to patients with normal OATP1B1 function, with a p value trending towards significance (p = 0.07).

TABLE 3.

Impacts of PK gene polymorphisms on 12‐h simvastatin plasma concentrations (n = 89).

Gene	rs number	Alleles	Genotype	N (%)	Median Css/Dose (ng/mL)
					SVL	p	SVA	p
Efflux transporters
ABCB1	rs1045642	3435C>T	CC	29 (32.58)	0.02 (0.01–0.04)	0.70	0.19 (0.13–0.45)	1.00
			CT+TT	60 (67.42)	0.02 (0.01–0.03)		0.25 (0.12–0.44)
ABCC2	rs717620	−24C>T	CC	55 (61.79)	0.02 (0.01–0.03)	0.45	0.22 (0.13–0.48)	0.67
			CT+TT	34 (38.21)	0.02 (0.01–0.03)		0.20 (0.12–0.42)
ABCC2	rs3740066	3971C>T	CC	49 (55.05)	0.02 (0.01–0.03)	0.96	0.21 (0.12–0.49)	0.84
			CT+TT	40 (44.95)	0.02 (0.01–0.03)		0.19 (0.12–0.44)
ABCG2	rs2231142	421C>A	CC	49 (55.05)	0.02 (0.01–0.03)	0.54	0.26 (0.15–0.52)	0.11
			CA+AA	40 (44.95)	0.02 (0.01–0.03)		0.18 (0.10–0.34)
Uptake transporters
SLCO1B1	rs4149056	521T>C	TT	80 (89.88)	0.02 (0.01–0.03)	0.33	0.19 (0.11–0.41)	0.03*
			TC+CC	9 (10.12)	0.01 (0.01–0.03)		0.53 (0.22–0.73)
SLCO1B1	rs2306283	388A>G	AA	17 (19.10)	0.02 (0.01–0.03)	0.53	0.16 (0.14–0.25)	0.13
			AG+GG	72 (80.90)	0.02 (0.01–0.03)		0.23 (0.12–0.53)
SLCO1B3	rs7311158	699G>A	GG+GA	44 (49.44)	0.02 (0.01–0.03)	0.46	0.19 (0.11–0.46)	0.86
			AA	45 (50.56)	0.02 (0.01–0.04)		0.22 (0.13–0.40)
SLCO1B3	rs4149117	334T>G	TT+TG	37 (41.57)	0.02 (0.01–0.03)	0.21	0.19 (0.07–0.45)	0.94
			GG	52 (58.43)	0.02 (0.01–0.04)		0.21 (0.13–0.43)
Drug‐metabolizing enzymes
CYP3A4*1G	rs2242480	20230G>A	GG	43 (48.31)	0.02 (0.01–0.04)	0.92	0.23 (0.15–0.53)	0.16
			GA+AA	46 (51.69)	0.02 (0.01–0.03)		0.19 (0.07–0.41)
CYP3A5*3	rs776746	6986A>G	AA	14 (15.73)	0.02 (0.01–0.03)	0.65	0.17 (0.05–0.44)	0.23
			AG+GG	75 (84.27)	0.02 (0.01–0.04)		0.22–0.13‐0.45)

Note: The Css/dose of simvastatin acid and lactone is presented as median (IQR).

^* p value < 0.05.

FIGURE 1.

SVL (A) and SVA (B) plasma concentrations (Css/Dose) of c.521TT and TC+CC genotype.

TABLE 4.

Impacts of SLCO1B1 diplotypes and OATP1B1 functions on 12‐h simvastatin plasma concentrations (n = 89).

Polymorphisms	Frequency (%)	Median Css/Dose (ng/mL)
		SVL	p	SVA	p
SLCO1B1 diplotypes
*1a/*1a (reference)	17 (19.10)	0.01 (0.01–0.03)	—	0.16 (0.12–0.24)	—
*1a/*1b	31 (34.83)	0.01 (0.01–0.04)	0.51	0.30 (0.11–0.49)	0.10
*1b/*1b	32 (35.95)	0.01 (0.01–0.04)	0.97	0.20 (0.08–0.48)	0.37
*1b/*5	2 (2.25)	0.02 (0.01–0.03) a	0.57	0.14 (0.13–0.15) a	0.57
*1b/*15	7 (7.87)	0.01 (0.01–0.03)	0.71	0.58 (0.27–0.74)	< 0.001*
OATP1B1 function
Normal function (*1a/*1a, *1a/*1b, *1b/*1b)	80 (89.88)	0.02 (0.01–0.03)	0.41	0.19 (0.11–0.41)	0.07
Decrease function (*1b/*5, *1b/*15)	9 (10.12)	0.01 (0.01–0.03)		0.53 (0.16–0.73)

Note: The Css/dose of simvastatin acid and lactone is presented as median (IQR). Allele function: *1a and *1b = normal function; *5 and *15 = no function. Diplotype‐predicted phenotype: *1a/*1a, *1a/*1b, *1b/*1b = normal function; *1b/*5, *1b/*15 = decreased function [26].

^a Mean (minimum–maximum).

^* p value < 0.05 compared to the reference (*1a/*1a).

To ensure the reliability of our findings, we assessed Hardy–Weinberg equilibrium (HWE) deviation and potential batch effects. Multivariate analysis confirmed that batch effects had no impact on SLCO1B1 c.521T>C in relation to simvastatin acid levels (Table S1). Furthermore, the QC call rate exceeded 95% for both samples and SNPs, ensuring the accuracy and robustness of the genotyping results. No significant relationship was observed between other pharmacokinetic gene polymorphisms and simvastatin lactone or acid concentrations.

3.4. Influence of Simvastatin Dose on Plasma SVL and SVA Levels

The influence of different simvastatin doses on plasma SVL and SVA levels was evaluated (Tables S2 and S3). The results showed that patients with the SLCO1B1 c.521T>C (rs4149056) TC+CC genotype exhibited higher steady‐state plasma levels of simvastatin acid (SVA) compared to TT carriers at a dose of 10 mg/day (5.83 vs. 1.95 ng/mL, p = 0.06). Additionally, SLCO1B1 rs2306283 was associated with significantly higher SVA levels in patients carrying the G allele (AG+GG genotype) at the same dose (3.63 vs. 1.59 ng/mL, p = 0.04). There was no association between the other doses and plasma SVL and SVA levels.

4. Discussion

Among pharmacokinetic gene polymorphisms affecting statin metabolism, SLCO1B1 c.521T>C and *1b/*15 diplotype were significantly associated with increased steady‐state plasma concentrations of simvastatin acid, reflecting reduced OATP1B1 function. In contrast, other SNPs, including ABCB1 (rs1045642), ABCC2 (rs717620, rs3740066), ABCG2 (rs2231142), SLCO1B3 (rs7311158, rs4149117), CYP3A4*1G (rs2242480), and CYP3A5*3 (rs776746), showed no significant association, suggesting a limited impact on simvastatin pharmacokinetics in this cohort. These results emphasize the clinical significance of the SLCO1B1 c.521T>C variant in pharmacogenetic testing.

The solute carrier organic anion transporter family member 1B1 gene (SLCO1B1), encoding the organic anion‐transporting polypeptide 1B1 (OATP1B1), is primarily expressed in the sinusoidal membrane of hepatocytes. It is responsible for the transport of endogenous compounds and various drugs into the liver, including statins [28, 29]. Since simvastatin acid, an active form of simvastatin, is one of the OATP1B1 substrates, the OATP1B1‐mediated uptake of simvastatin acid from the bloodstream into liver cells is essential for both the effectiveness and safety of simvastatin treatment [30].

Several single nucleotide polymorphisms (SNPs) of the SLCO1B1 gene can affect the function of the OATP1B1 transporter and alter the pharmacokinetics of statins [31, 32]. Among the previous publications, SLCO1B1 c.388A>G (rs2306283, N130D) and SLCO1B1 c.521T>C (rs4149056, V174A) are the most investigated SNPs. In our study, the allele frequencies for SLCO1B1 c.388G and c.521C were observed to be 62.36% and 5.06%, respectively. The frequency of c.388G is lower than the approximately 75%–80% reported in previous studies on the Thai population [33, 34, 35]. For c.521C, the observed frequency is lower than the 12%–18% reported in other Thai studies but aligns closely with findings from another Thai cohort, which reported a 5.2% frequency for this allele [36]. This variation in allele frequencies could be due to differences in the genotyping methods performed.

The SLCO1B1 c.521T>C variant (V174A) is a well‐characterized polymorphism that affects OATP1B1 localization to the cell membrane, leading to reduced hepatic uptake, increased systemic statin exposure, and a higher risk of muscle‐related adverse events [14, 31, 37, 38, 39]. This variant causes a valine‐to‐alanine substitution at position 174, located in transmembrane domain 5, a region critical for transporter stability and function [38]. In vitro studies showed that the c.521C allele results in reduced membrane expression of OATP1B1 due to mislocalization, decreasing hepatic uptake of simvastatin acid [14]. Functional assays demonstrated abolished transporter activity and the protein expression levels [14, 38, 40, 41], providing a mechanistic basis for the elevated simvastatin acid concentrations observed in c.521C carriers. Our findings align with previous studies, demonstrating that c.521T>C carriers have a significantly higher simvastatin acid concentrations than those with the c.521T allele [21, 42, 43, 44]. For instance, Pasanen et al. reported that c.521CC carriers had significantly higher C _max and AUC_0–∞ for simvastatin acid than c.521TC or c.521TT carriers [21]. Similarly, Birmingham et al. and Jiang et al. observed significantly increased AUC and C _max of simvastatin acid exposure in Caucasian and Korean participants carrying the variant [42, 43], emphasizing its role in simvastatin pharmacokinetics and its clinical relevance to pharmacogenetic testing. In contrast, SLCO1B1 c.388A>G (rs2306283) showed no significant association with simvastatin concentrations in our study, consistent with previous findings [22, 42]. This polymorphism has been linked to normal or slightly altered OATP1B1 function, with minimal impact on statin pharmacokinetics unless co‐inherited with c.521T>C [42]. However, dose‐specific analysis revealed significantly higher SVA levels in G allele carriers (AG+GG) at 10 mg/day (3.63 vs. 1.59 ng/mL, p = 0.04). Similarly, SLCO1B1 c.521T>C (rs4149056) TC+CC carriers had higher SVA than TT carriers at this dose (5.83 vs. 1.95 ng/mL, p = 0.06), with no associations at other doses. Given the small sample size in each dose group, further studies are warranted to confirm the dose‐dependent effects of pharmacokinetic gene polymorphisms on simvastatin exposure.

The SLCO1B1 c.521T>C variant is a component of the SLCO1B1*5 and *15 haplotypes (combined with c.388G), both of which are associated with reduced transporter function [14, 38]. Previous studies have reported that individuals with one normal function allele (SLCO1B1*1a or *1b) and one no function allele (SLCO1B1*5 or *15) are at an increased risk of statin‐induced myotoxicity due to impaired hepatic uptake [14, 21, 42, 44]. The SEARCH Collaborative Group reported a 45‐fold higher myotoxicity risk in *15/*15 carriers [7], while the Heart Protection Study found a significant association between SLCO1B1*5 and muscle side effects (p = 0.004) [20].

Considering that SLCO1B1*5 and *15 haplotypes are commonly associated with altered OATP1B1 function, we investigated the impact of genotype‐predicted phenotypes on steady‐state simvastatin plasma concentrations in the Thai population. According to the Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines, SLCO1B1 phenotypes are classified as normal (two normal function alleles: *1a/*1a or *1a/*1b), decreased (one normal and one no function allele: *1/*5 or *1/*15), or poor (two no function alleles: *5/*5 or *15/*15) function [26]. In our study, 89.88% of participants exhibited normal function, while 10.12% had decreased function (*1b/*5, *1b/*15). No poor function phenotypes were observed. Consistent with the CPIC guideline and prior studies, participants with decreased OATP1B1 function (*1b/*15 and *1b/*5) showed higher simvastatin acid concentrations than those with normal function (0.53 vs. 0.19 ng/mL, p = 0.07). This confirms that decreased OATP1B1 function leads to increased SVA exposure and a higher risk of myotoxicity [26].

For clinical implementation, our findings, supported by existing evidence, emphasize the critical need for genotype‐guided dosing in SLCO1B1 c.521T>C or *1b/*15 carriers to reduce the risk of myotoxicity. Given that simvastatin is in widespread use in Thailand under the National List of Essential Medicines (NLEM) due to its affordability, optimizing its use is clinically important. Additionally, when the SLCO1B1 genotype is known, the CPIC guidelines provide guidance for clinicians to adjust statin dosage and switch statin types to reduce the risk of statin‐induced myopathy (SIM), facilitating personalized therapy that minimizes adverse drug reactions (ADR) while preserving therapeutic efficacy. However, further studies are needed to determine the direct impact of these variants on SIM outcomes in Thailand.

This study has limitations. The small sample size reduced the statistical power, potentially limiting the ability to detect significant differences in pharmacokinetic parameters. Furthermore, when stratifying by dose, the sample size in each subgroup became even smaller, further reducing statistical robustness. Future studies should include larger sample sizes to improve the reliability of dose‐specific analyses. Additionally, focusing on steady‐state levels restricted the analysis to a single time point. Future research should involve larger, more diverse cohorts and multiple time points to better characterize simvastatin pharmacokinetics over time.

5. Conclusion

Our study is the first to examine genetic polymorphisms in drug‐metabolizing enzymes and transporters that influence steady‐state simvastatin plasma levels in the Thai population. The SLCO1B1 c.521T>C variant, either alone or in combination with c.388A>G (*1b/*15), was significantly associated with elevated simvastatin acid levels, potentially increasing the risk of myotoxicity. According to CPIC guidelines, SLCO1B1 genotyping (rs4149056, rs2306283) may help guide statin therapy for the Thai population once the genotype is known. However, larger studies are needed to further evaluate these pharmacogenetic effects on simvastatin exposure and myotoxicity risk.

Author Contributions

S.T. and N.V. wrote the manuscript. S.T., S.S., Y.V., C.S., P.C., V.Y., and N.V. designed the research. S.T., U.U., S.S., Y.V., T.S., and N.V. performed the research. S.T., C.S., M.C., and N.V. analyzed the data; U.U. and T.P. contributed new reagents/analytical tools.

Conflicts of Interest

The authors declare no conflicts of interest.

Supporting information

Data S1.