Effects of ABCB1 DNA methylation in donors on tacrolimus blood concentrations in recipients following liver transplantation

Abstract

Aims

To investigate the effects of ABCB1 DNA methylation in donors on individual differences in tacrolimus blood concentrations following liver transplantation.

Methods

Twenty‐three donor liver samples carrying the CYP3A5*3/*3 genotype were classified into 2 groups based on their initial tacrolimus blood concentrations (C₀ >10 μg/L or <5 μg/L) following liver transplantation. ABCB1 mRNA levels in liver tissues and HepG2 cells were determined by quantitative reverse transcriptase polymerase chain reaction. DNA methylation status in liver tissues and HepG2 cells was determined using Illumina 850 methylation chip sequencing technology and pyrosequencing. 5‐Aza‐2dC was used to reverse methylation in HepG2 cells. Intracellular tacrolimus concentrations were determined by liquid mass spectrometry.

Results

Genome‐wide methylation sequencing and pyrosequencing analyses showed that the methylation levels of 3 ABCB1 CpG sites (cg12501229, cg00634941 and cg05496710) were significantly different between groups with different tacrolimus concentration/dose (C₀/D) ratios. ABCB1 mRNA expression in donor livers was found to be positively correlated with tacrolimus C₀/D ratio (R = .458, P < .05). After treatment with 5‐Aza‐2‐Dc, the methylation levels of the ABCB1 CpG sites in HepG2 cells significantly decreased, and this was confirmed by pyrosequencing; there was also a significant increase in ABCB1 transcription, which induced a decrease in intracellular tacrolimus concentrations.

Conclusion

ABCB1 CpG site methylation affects tacrolimus metabolism in humans by regulating ABCB1 expression. Therefore, ABCB1 DNA methylation in donor livers might be an important epigenetic factor that affects tacrolimus blood concentrations following liver transplantation.

What is already known about this subject

• P‐glycoprotein (P‐gp) transporter encoded by the ABCB1 transporter gene may affect the metabolism of tacrolimus.

• Gene polymorphisms of drug metabolising enzymes or transporters in donor livers do not completely explain the individual differences in tacrolimus metabolism following liver transplantation.

• DNA methylation is an important epigenetic factor affecting gene expression through the external regulatory pathway without change the primary structure of DNA, thus affecting the metabolism of drugs.

What this study adds

• DNA methylation of 3 CpG sites (cg12501229, cg00634941 and cg05496710) on ABCB1 promoter could affect the expression of ABCB1.

• The methylation levels of ABCB1 CpG sites in donors are associated with individual differences in tacrolimus blood concentrations in recipients following liver transplantation.

• The findings will help provide data to fine tune the modalities of tacrolimus administrations in liver transplant recipients in order to improve patient outcomes.

1. INTRODUCTION

The P‐glycoprotein (P‐gp) transporter, which is encoded by the ABCB1 transporter gene (also known as the MDR1 gene), is widely distributed in intestinal epithelial cells, liver cells and renal proximal tubule epithelial cells. ¹ Previous studies have shown that ABCB1 may affect tacrolimus absorption, distribution and excretion. ² , ³ Thus, some studies have focused on evaluating the relationship between ABCB1 gene polymorphism (1236C > T, rs1128503, Gly412Gly; 677G > T/A, rs2032582, Ala893DSer/Thr; 3435C > T, rs1045642, Ile1145Ile of exons 12, 21 and 26) and tacrolimus pharmacokinetics. ³ , ⁴ However, the findings of these studies are inconsistent as concerns both single nucleotide polymorphisms and haplotypes, and systematic mechanistic studies to support their conclusions are still lacking. In addition, recent studies carried out on ABCB1 have shown that it functions mainly in prolonging drug retention time in intestinal cells by pumping drugs into the intestinal lumen i.e. on the surface of the gastrointestinal tract, and this also affects tacrolimus absorption. ⁵ , ⁶ , ⁷ However, the effects of ABCB1 on tacrolimus metabolism in liver cells have not been clearly elucidated.

Although CYP450 and transporter (e.g. ABCB1) gene polymorphisms are important for individual variations in drug metabolism and pharmacodynamics, they do not fully explain such individual differences. ⁸ , ⁹ In a previous study (in press), according to the therapeutic window concentration of tacrolimus in liver transplantation, we recruited 78 patients with significantly different initial tacrolimus blood concentrations (C₀ >10 or <5 μg/L) following liver transplantation at the First Affiliated Hospital of Zhengzhou University. Then corresponding donor liver samples were collected for the genotyping of CYP3A5 and other genes including ABCB1, which have been reported in the literature to be possibly related to tacrolimus metabolism (Tables S1, S2). We found that the polymorphisms of ABCB1 had no association with initial tacrolimus blood concentration. We also found that significant individual differences still existed in tacrolimus blood concentrations in CYP3A5 nonexpressors (CYP3A5*3/*3), indicating that other key factors may also affect tacrolimus metabolism (Figures S1, S2). In recent times, the influence of epigenetic factors on drug metabolism has received increasing research attention; among these factors, DNA methylation has become a new research hotspot. DNA methylation can alter gene expression through the external regulatory pathway without altering the primary structure of DNA, thereby affecting the metabolism of drugs and endogenous substances. ¹⁰ More specifically, cytosine on the CpG island combines with a methyl group transferred by DNA methyltransferase to produce methyl cytosine, which then inhibits DNA transcription. ¹¹ Previous studies have shown that DNA methylation is an important epigenetic factor that affects CYP450 gene expression. ¹² , ¹³ In a previous study, we also found DNA methylation to play an important role in CYP3A4 transcriptional regulation. ¹⁴ In addition, antitumour drugs, such as daunorubicin, activate ABCB1 transcription by hypomethylating its promoter region and this possibly results in multidrug resistance. ¹⁵ , ¹⁶

Therefore, for this study, we selected 23 donor liver samples carrying the CYP3A5*3/*3 genotype but exhibiting varied initial tacrolimus blood concentrations in recipients after liver transplantation and divided them into 2 groups (C₀ >10 or <5 μg/L). DNA methylation sequencing was performed to screen for the different methylation sites of drug metabolism enzymes or drug transporters (such as ABCB1), and then we evaluated the relationship between the different methylation sites and the tacrolimus C₀/D ratio. In addition, by treating HepG2 cells with methylase inhibitors, we further verified whether DNA methylation is a key epigenetic factor that affects tacrolimus metabolism.

2. MATERIALS AND METHODS

2.1. Patients and sample collection

All the liver transplantation recipients included in this study met the following criteria: age >18 years; postoperative survival time ≥3 months; normal liver function within 1 month following surgery; and patients having received treatment with tacrolimus in combination with steroids and mycophenolate mofelil after transplantation. The corresponding donors met the following criteria: hepatitis or other infectious disease free; normal liver and kidney function; and no treatment with any drug known to interact with tacrolimus within the 2 previous weeks.

Tacrolimus was administered orally at a dose of 0.05 mg/kg/d from the first day following transplantation. Routine therapeutic drug monitoring for tacrolimus was initiated 48 hours after the administration of its first dose. C₀ in whole blood was determined through an enzyme amplification immunoassay using the EMIT 2000 tacrolimus assay kit (Siemens Healthcare Diagnostics, DE, USA) on the day of blood collection. The tacrolimus C₀/D ratio was calculated by dividing the tacrolimus concentration by the corresponding weight‐adjusted dose. Liver samples of the included donors were collected during liver trimming at the time of transplantation, cut into small pieces and immediately stored in liquid nitrogen.

2.2. DNA methylation microarray screening

The DNA of the 15 donor livers (G1: low tacrolimus C₀/D ratio group, n = 7; G2: high tacrolimus C₀/D ratio group, n = 8) carrying the CYP3A5*3/*3 genotype was isolated using DNeasy Blood and Tissue Kit (Qiagen). The purity and concentration of the DNA was estimated using NanoDrop 2000 (Thermo Fisher Scientific). Approximately 500 ng of genomic DNA from each sample was sent to Shanghai Jingzhou Genomics Technology Co., Ltd. for sodium bisulfite conversion using the EZ DNA methylation–Gold Kit (Zymo Research, USA), the standard protocol of which was followed. Genome‐wide DNA methylation was assessed using the Illumina Infinium Human Methylation 850 K BeadChip (Illumina Inc., USA) according to the manufacturer's instructions. Array data (.IDAT files) were analysed using the ChAMP function in R for the determination of methylation levels. The methylation status of all probes was denoted as the β value, which is the ratio of the methylated probe intensity to the overall probe intensity (the sum of the methylated and unmethylated probe intensities plus the constant, α, where α = 100). CpG sites with |Δβ| ≥ 0.20 (in test vs. control) and adjusted P value ≤.05, were considered to be differentially methylated sites. A CpG site was considered to be hypermethylated if its Δβ was ≥0.20, or hypomethylated if its Δβ was ≤−0.20. The average β values for promoters and CpG islands were compared between Group 1 (G1: low tacrolimus C₀/D ratio group) and Group 2 (G2: high tacrolimus C₀/D ratio group). Promoters and CpG islands with |Δβ| ≥ 0.20 and adjusted P value ≤.05, were retained for further analysis.

2.3. Pyrosequencing analysis

Genomic DNA (500 ng) extracted from the 23 CYP3A5*3/*3 genotype donor livers was transformed by sodium bisulfite using the EZ DNA Methylation Kit (Zymo Research, Orange County, CA, USA) and further purified using the Wizard DNA Clean‐up System (Promega, Madison, WI, USA). The sequences of the primers used for the ABCB1 DNA methylation analysis are shown in Table 1. Each polymerase chain reaction (PCR) consisted of 100 ng of DNA converted by sodium bisulfite, 100 pM deoxyriboside triphosphate, 10 pM positive/reverse primers and 1 unit of Taq polymerase (Merck KGaA, Darmstadt, Germany), which resulted in a final volume of 25 μL. After initial denaturation at 95°C for 5 minutes, amplification was performed for 40 cycles at 95°C for 30 seconds, 60°C for 30 seconds and 72°C for 30 seconds, followed by a final elongation step at 72°C for 5 minutes. PCR products were analysed by nondenatured 6% polyacrylamide gel electrophoresis, following staining with ethidium bromide.

TABLE 1.

Primers used for ABCB1 DNA methylation analysis

Detected site	Segment	Primer sequence (5′–3′)	Product size (bp)
cg05496710	PCR sense	AAGTAGAATATTTAGGGGAGGTATG	84
	PCR antisense	ACCTTACATTCTCCAATTCTTTAAAA
	Sequencing	GGAGGTATGGGTTTT
cg00634941	PCR sense	TGGATTGTTGGATTTGTAGTTTTAATAG	102
	PCR antisense	AAACTCCAATCCCCTTTACTAATA
	Sequencing	GTTTTTAGGTGATGTTGAT
cg12501229	PCR sense	GTGAATAGTTGGTGATAATTATTTATTGTG	99
	PCR antisense	AAATAAACATCTCCTTTTTAAACATTTT
	Sequencing	TGGTGATAATTATTTATTGTGG

In addition, genomic DNA was extracted from cells treated with the methylation inhibitor, 5‐Aza‐2‐DC and changes in ABCB1 DNA methylation were also evaluated by pyrosequencing.

2.4. Cell culture and treatments

The human hepatocellular carcinoma cell line, HepG2, was purchased from the China Centre for Type Culture Collection (Wuhan, China) and confirmed by short tandem repeat analysis provided by the above company. HepG2 was cultured in Dulbecco’s modified Eagle medium (DMEM; HyClone/Thermo Fisher Scientific, Beijing, China) supplemented with 10% foetal bovine serum (LONSA SCIENCE S.R.L., Montevideo, Uruguay). To determine the optimum concentration and administration period for 5‐Aza‐2‐DC (Selleck, Shanghai, China) and tacrolimus (Selleck, Shanghai, China), HepG2 cells were seeded into 12‐well plates at a density of 4 × 10⁴ cells/well and cultured for 24 hours at 37°C in a 5% CO₂ atmosphere. For treatment with 5‐Aza‐2‐DC, the cells were exposed to 5‐Aza‐2‐DC dissolved in dimethyl sulfoxide (DMSO; 0.1% v/v) at a series of final concentrations (0, 0.1, 0.5, 1.0, 2.5, 5.0, 10 and 50 μM) for 24, 48 and 72 hours. Then, cell viability was evaluated using the CCK‐8 kit (Dojindo, Shanghai, China) according to the manufacturer's instructions, and ABCB1 mRNA and protein expression levels were evaluated by quantitative reverse transcriptase–PCR and western blotting, respectively. For treatment with tacrolimus, the cells were exposed to tacrolimus dissolved in DMSO (0.1% v/v) at a series of final concentrations (0, 0.01, 0.1, 1.0, 10, 50, 100 and 200 μM) for 24, 48 and 72 hours, and cell viability was evaluated using the CCK‐8 kit. Based on the results of the optimum time determined by CCK‐8 analysis, HepG2 cells were treated with 0, 40, 50, 60, 70, 80, 90 and 100 μM tacrolimus for 24 hours, and cell viability was evaluated using the CCK‐8 kit to determine the tacrolimus optimum concentration.

2.5. 5‐Aza‐2‐DC treatment

HepG2 cells at the logarithmic growth stage (1.2 × 10⁶ cells/well) were spread on 6‐well plates. After 24 hours of culturing, the cells were treated with 0 μM (DMSO; 0.1% v/v) or 10 μM 5‐Aza‐2‐DC, and the 5‐Aza‐2‐DC‐containing medium was replaced every 24 hours. After treatment with 5‐Aza‐2‐DC for 72 hours, the medium was discarded and replaced with a tacrolimus‐containing medium (60 μM), and the cells were cultured for another 48 hours. After 48 hours, the medium was replaced with tacrolimus‐free DMEM and the cells were further cultured. Samples of the medium were taken at 0, 4, 6 and 12 hours following its replacement. Next, the cells were digested with trypsin for 2 minutes, and then digestion was terminated by adding more medium. The cells were centrifuged at 300 × g for 3 minutes and washed thrice with phosphate‐buffered saline. The supernatant of cell culture and cells were stored at −80°C for further evaluation.

2.6. Total RNA extraction and RT‐qPCR analysis

Total RNA was extracted using the TRIzol Reagent (CoWin Biosciences, Jiangsu, China) according to the manufacturer's instructions. The extracted RNA was reverse transcribed into cDNA using Super Script III Reverse Transcriptase (Vazyme Biotech Co., Ltd., Nanjing, China). ABCB1 mRNA expression was evaluated through a relative quantitative method. The formula, 2^−ΔΔCT, was used to calculate the quantity of DNA amplified. The sequencing primers used for amplification, which were provided by Tsingke Biotechnology Co., Ltd., were:

• ABCB1‐F: 5′‐TTGCTGCTTACATTCAGGTTTCA‐3′,

• ABCB1‐R: 5′‐AGCCTATCTCCTGTCGCATTA‐3′,

• GAPDH‐F: 5′‐GCACCGTCAAGGCTGAGAAC‐3′,

• GAPDH‐R: 5′‐TGGTGAAGACGCCAGTGGA‐3′.

2.7. Western blot analysis

Lysates of HepG2 cells (which were treated with 5‐Aza‐2‐DC and tacrolimus) were run on 8% sodium dodecyl sulfate‐polyacrylamide gels, transferred to polyvinylidene difluoride membranes, and incubated with an antibody against P‐glycoprotein (Abcam Inc. Cambridge, MA, USA). Antibody binding was detected using enhanced chemiluminescence ECL Plus western blotting detection reagents (Merck Millipore Ltd. Tullagreen, Carrigtwohill, Co. Cork, Ireland).

2.8. Determination of tacrolimus intracellular concentrations by liquid‐mass spectrometry

The quantification of tacrolimus was performed by ultra‐high performance liquid chromatography–tandem mass‐spectrometry (UHPLC–MS/MS) according to previously described methods with minor modifications. ¹⁷ , ¹⁸ Specifically, the collected cells previously treated by 5‐Aza‐2‐DC were resuspended in 100 μL of phosphate‐buffered saline or medium and mixed with 50 μL of internal standard (ascomycin, 800 ng/mL, dissolved in methanol), 50 μL of methanol and 500 μL of methyl‐tert‐butyl ether. After vortexing and centrifugation (14 000 × g, 5 min, 4°C), 450 μL of the organic layer was dried on a nitrogen blow‐dry apparatus. The extract was redissolved in 50 μL of a complex solution (2 mM ammonium acetate and 0.1% formic acid). After vortexing and centrifugation (12 000 × g, 10 min, 4°C), the supernatant (45 μL) was placed in a liquid injection flask. The mobile phase for UHPLC–MS/MS detection was (acetonitrile [containing 0.1% formic acid]: 2 mmol/L ammonium acetate [containing 0.1% formic acid] = 9:1). An ACQUITY UPLC BEH C18 column (2.1 × 50 mm; 1.7 μm; Waters Chromatography Ireland Ltd., Ireland) was used, and the column temperature was 55°C. The specific product ions were m/z 821.5 and m/z 809.5 for tacrolimus and the internal standard, respectively. Ionisation was carried out in positive ion mode with a capillary voltage of 3.5 kV, a cone voltage of 22/29 (tacrolimus/internal standard), an ion source temperature of 120°C, a desolvation temperature of 350°C, a nitrogen flow rate of 600 L/h, a collision gas pressure of 5 × 10⁻³ bar and a collision energy of 17/21 (tacrolimus/internal standard).

2.9. Statistical analysis

SPSS software (Armonk, New York, NY, USA) was used for data analysis, and GraphPad Prism version 6.0 (GraphPad Software, San Diego, CA, USA) was used to plot graphs. All data are expressed as mean ± standard deviation. An independent sample t‐test was used to compare and analyse the data between the 2 groups, with the homogenous variance of a bivariate normal distribution. Pearson correlation test was used to analyse the correlation of ABCB1 mRNA expression with tacrolimus C₀/D ratio. P values <.05 were considered statistically significant.

3. RESULTS

3.1. Whole genome methylation microarray sequencing of CYP3A5*3/*3 genotype donor livers

Through principal component analysis, approximately 800 000 methylation sites were observed in the 2‐dimensional diagram after probe filtering and normalisation (Figure 1A). Based on the methylation β value between the 5 kb upstream and downstream transcription start sites, significant differences in methylation levels were observed between groups G1 and G2 (Figure 1B). In addition, heat and scatter maps showed that there was a large number of methylation sites, with different levels of methylation, between groups G1 and G2 (Figure 1C and D).

FIGURE 1.

Whole genome methylation microarray sequencing of CYP3A5*3/*3 genotype donor liver. (A) Principal component (PC) analysis diagram; (B) distribution of methylation degree between the 5 kb upstream and downstream transcription start sites (TSS); (C) heat map of differential methylation sites; (D) scatter plot of different methylation sites. G1: low tacrolimus C0/D ratio group, n = 7; G2: high tacrolimus C0/D ratio group, n = 8

3.2. Methylation levels and mRNA expression of ABCB1 in relation to tacrolimus blood concentration

Through methylation chip screening, the methylation levels of 3 ABCB1 sites (cg12501229, cg00634941 and cg05496710) located on chromosome 7 were found to be significantly different between the high and low tacrolimus blood concentration groups (Figure 2A). Using the pyrophosphorylation assay, the methylation levels of these 3 sites were further evaluated in the 23 donor liver specimens carrying the CYP3A5*3/*3 genotype. We found that the methylation levels of these sites in the high C₀/D group were all significantly lower than those in the low C₀/D group (Figure 2B–D).

FIGURE 2.

The methylation sites (red vertical bars) within the ABCB1 methylation region located on chromosome 7 (A), and the methylation level at cg12501229 site (B), cg00634941 site (C) and cg05496710 site (D) of ABCB1 gene in donor livers carried with CYP3A5*3/*3 genotype and different tacrolimus C₀/D ratio (High: n = 12, Low: n = 11); **P < .01

Furthermore, ABCB1 mRNA expression levels were determined by RT‐qPCR, and correlation analyses revealed that ABCB1 mRNA expression in donor livers was positively correlated with the tacrolimus C₀/D ratio (R = .458, P < .05; Figure 3A). An ABCB1 mRNA expression level of 0.15 was used as the cut‐off value to analyse the tacrolimus C₀/D ratio and differences between the low‐and high‐expression groups (Figure 3B and C). Meanwhile, the methylation level of the 3 CpG sites was significantly negatively correlated with ABCB1 mRNA expression (R = −.394, P = .063; R = −.358, P = .094; R = −.307, P = .154; Figure 3D). Our results showed that the greater proportion of patients with high blood tacrolimus concentrations were found in the high ABCB1 expression group.

FIGURE 3.

Correlation of ABCB1 mRNA expression with tacrolimus C0/D ratio and ABCB1 methylation level of 3 CpG sites in CYP3A5*3/*3 donor livers (n = 23). (A) Correlation analyses; (B, C) an ABCB1 mRNA expression level of 0.15 was used as the cut‐off value to analyse the tacrolimus C0/D ratio (B) and the tacrolimus C0/D ratio distribution (C); mRNA Low: relative mRNA level of ABCB1 < 0.15; mRNA High: relative mRNA level of ABCB1 > 0.15; *P < .05; (D) Correlation between ABCB1 mRNA expression level and methylation level of 3 CpG sites

3.3. Effects of 5‐Aza‐2‐DC on ABCB1 expression in HepG2 cells

First, the optimal concentration and administration time for 5‐Aza‐2‐DC were determined (Figure 4A–C). Then, based on findings in literature, 10 μM 5‐Aza‐2‐DC was used to investigate the effects of ABCB1 methylation status on its expression in HepG2 cells. We found that after treatment with 10 μM 5‐Aza‐2‐DC for 24, 48 and 72 hours, ABCB1 mRNA and protein expression levels significantly increased at 72 hours (Figure 4D–F). Therefore, 10 μM 5‐Aza‐2‐DC and 72 hours were selected as the optimal concentration and treatment duration, respectively, for the determination of the effects of 5‐Aza‐2‐DC on the methylation levels of the 3 ABCB1 CpG sites (cg12501229, cg00634941 and cg05496710).

FIGURE 4.

Effects of 5‐Aza‐2‐DC on cell viability, ABCB1 expression in HepG2 cells. (A–C) The effects of 5‐Aza‐2‐DC on cell viability after treated at indicated concentrations of 5‐Aza‐2‐DC for 24 (A), 48 (B) and 72 hours (C); (D–F) ABCB1 mRNA expression (D) and protein expression (E, F) after treatment with 5‐Aza‐2‐DC (10 μM) for 24, 48 or 72 hours; *P < .05, **P < .01, ***P < .001 vs. 0 μM 5‐Aza‐2‐DC (DMSO; 0.1% v/v)

3.4. Effects of 5‐Aza‐2‐DC on ABCB1 methylation levels and tacrolimus metabolism in HepG2 cells

A pyrophosphorylation assay was performed to investigate the effects of 5‐Aza‐2‐DC on ABCB1 methylation. As shown in Figure 5, we found that the methylation levels of the ABCB1 sites in the 5‐Aza‐2‐DC‐treated group (10 μM) were significantly lower (P < 0.001) than those in the untreated group (0 μM). To determine the effects of 5‐Aza‐2‐DC on tacrolimus efflux, intracellular tacrolimus concentrations were determined by UHPLC–MS/MS. We found the tacrolimus contents of 5‐Aza‐2‐DC‐treated cells to be significantly lower than those of untreated cells at 0, 4 and 6 hours following the removal of tacrolimus‐containing medium (P < .05). At 12 hours, although there was a slight increase in intracellular tacrolimus concentrations, its levels in the 5‐Aza‐2‐DC‐treated group were still significantly lower than those in the untreated group (0 μM), and this may be due to its intracellular metabolism in a dynamic equilibrium scenario (Figure 6).

FIGURE 5.

Effects of 5‐Aza‐2‐DC (10 μM) on DNA methylation at 3 CpG sites located on ABCB1 promoter region in HepG2 cells; ***P < .001 vs. 0 μM 5‐Aza‐2‐DC (DMSO; 0.1% v/v)

FIGURE 6.

Changes of tacrolimus concentration in HepG2 cells over time replaced with tacrolimus‐free DMEM after treated with 5‐Aza‐2‐DC (0 μM or 10 μM) 72 h and then incubated with 60 μM tacrolimus for 48 hours; *P < .05, ***P < .001 vs. 0 μM 5‐Aza‐2‐DC (DMSO; 0.1% v/v)

4. DISCUSSION

Several studies have reported that individual differences in drug response cannot be fully explained by polymorphisms in genes encoding drug‐metabolizing enzymes or transporters. ¹⁹ , ²⁰ Recently, epigenetic modifications, which regulate the expression of several enzymes and transporters involved in drug metabolism, have been recognised as important factors that affect individual differences in clinical drug response. ²¹ DNA methylation affects the expression of CYP450 (CYP1A1, CYP1A2, CYP1B1, CYP2C19, CYP2D6, CYP2E1 and CYP2W1), thus leading to significant individual differences in enzyme expression. ²² , ²³ , ²⁴ , ²⁵ In addition, DNA methylation regulates the expression of ABCG2 and ABCB1, which play a crucial role in determining the success or failure of cancer chemotherapy by mediating multidrug resistance and individual differences in drug transport. ²⁶ , ²⁷ As most studies on the methylation of genes encoding drug transporters have been carried out in the field of oncology, we investigated, for the first time, whether ABCB1 DNA methylation in donor livers affects tacrolimus blood concentrations in liver transplant recipients by regulating its expression.

In this study, we analysed 15 donor liver samples carrying the CYP3A5*3/*3 genotype using DNA methylation microarray technology and found ABCB1 methylation levels to be correlated with tacrolimus blood concentrations in liver transplantation patients. At present, the method we used for determining tacrolimus concentration is the most commonly used method despite its crossreactivity with tacrolimus metabolites. ²⁸ Based on the findings of previous studies on ABCB1 methylation and tacrolimus metabolism ² , ²⁹ , ³⁰ and ABCB1 mRNA expression level, which is regulated by DNA methylation ²⁷ and inversely correlated with the tacrolimus concentration–oral dose ratio in living‐donor liver transplant patients, ³¹ we speculated that ABCB1 DNA methylation might be another key factor that affects tacrolimus metabolism by regulating ABCB1 expression.

Previous studies have demonstrated that there exists no correlation between the frequency of ABCB1 gene polymorphisms and tacrolimus plasma concentrations following renal transplantation, ⁴ , ³² , ³³ and this is consistent with the findings of 1 of our previous studies (in press). However, our studies found that there exist significant individual differences in tacrolimus blood concentrations in liver transplant recipients who receive donor livers with the CYP3A5*3/*3 genotype; thus, for the first time, we evaluated the methylation status of 23 liver samples carrying the CYP3A5*3/*3 genotype using a methylation microarray assay validated by pyrosequencing. Our findings showed that DNA methylation levels at 3 ABCB1 CpG sites (cg12501229, cg00634941 and cg05496710) in donor livers were significantly different between the high and low tacrolimus C₀/D ratio groups following liver transplantation. In addition, in consonance with the findings of previous studies, ³⁰ , ³⁴ , ³⁵ ABCB1 mRNA levels in donor livers were found to be negatively correlated with its methylation levels.

To the best of our knowledge, no studies have been carried out on the effects of ABCB1 methylation, especially of its 3 CpG sites (cg12501229, cg00634941 and cg05496710), on tacrolimus metabolism. Therefore, in this study, the effects of ABCB1 methylation on tacrolimus efflux from target cells were first evaluated using the methylation inhibitor, 5‐Aza‐2‐DC. It was shown that in HepG2 cells, ABCB1 methylation levels at its 3 methylation sites significantly decreased following treatment with 5‐Aza‐2‐DC. Moreover, tacrolimus intracellular concentrations significantly decreased following treatment with 5‐Aza‐2‐DC. In addition, ABCB1 mRNA and protein levels significantly increased following treatment with 5‐Aza‐2‐DC. For clinical samples, the methylation levels of the cg12501229, cg00634941 and cg05496710 sites in the high C₀/D group were all significantly lower than those in the low C₀/D group, and ABCB1 mRNA expression was found to be positively correlated with tacrolimus C₀/D ratio. These findings indicate that a decrease in DNA methylation could result in an increase in ABCB1 expression in donor livers, which would lead to an increase in tacrolimus efflux from liver cells and a consequent increase in tacrolimus blood concentrations of the recipient.

This study had limitations, namely, we did not construct a methylation‐specific expression plasmid to determine which of the 3 ABCB1 methylation sites plays a leading role in the regulation of gene expression. Moreover, many factors, such as age, sex, drug exposure, diet and environment, could cause varying DNA methylation states in individuals. All these mechanisms should be further investigated in our future study. By contrast, although multiple studies ³⁶ , ³⁷ , ³⁸ have shown that influence factors, such as genotype, are more important for tacrolimus metabolism post‐liver transplant in donors than in recipients, the DNA methylation states of ABCB1 in recipients should be considered in the future investigation.

5. CONCLUSION

Our study demonstrated that DNA methylation of ABCB1 CpG sites (cg12501229, cg00634941 and cg05496710) could regulate its expression in donor livers, thus inducing individual differences in initial tacrolimus concentrations following liver transplantation.

CONTRIBUTORS

C.C.S.: conception, design, data collection, analysis of data, drafting and revision of manuscript. L.Y.: conception, interpretation of results and critical revision of manuscript. S.T.C.: analysis of data, interpretation of results. L.R.Z.: design and revision of manuscript.

Supporting information

TABLE S1 Distribution frequency of gene polymorphisms in donor livers (n = 78).

TABLE S2 Association of genotypes in donors with tacrolimus C₀/D ratio in recipients following liver transplantation (n = 78).

FIGURE S1 (A) Differences of tacrolimus C₀/D ratio in 78 recipients following liver transplantation. High: n = 12, Low: n = 11. (B) Correlation analysis between CYP3A5 rs776746 polymorphism in donors and tacrolimus C₀/D ratio in recipients following liver transplantation. n = 78.

FIGURE S2 Difference of tacrolimus C₀/D ratio in recipients who carried CYP3A5*3/*3 genotype donor livers, High: n = 12, Low: n = 11.

Shi C, Yan L, Gao J, Chen S, Zhang L. Effects of ABCB1 DNA methylation in donors on tacrolimus blood concentrations in recipients following liver transplantation. Br J Clin Pharmacol. 2022;88(10):4505‐4514. doi: 10.1111/bcp.15376

DATA AVAILABILITY STATEMENT

The data that support the findings of this study are available from the corresponding author upon reasonable request.