Polymorphisms in CYP1A2,CYP2C9 and ABCB1 affect agomelatine pharmacokinetics

Abstract

Background:

Agomelatine is an agonist of the melatoninergic receptors used for the treatment of depression. Our aim was to evaluate the effect of genetic polymorphisms in metabolising enzymes and the P-glycoprotein transporter on agomelatine pharmacokinetics and pharmacodynamics.

Methods:

Twenty-eight healthy volunteers receiving a single 25 mg oral dose of agomelatine, were genotyped for nine polymorphisms in cytochrome P450 enzymes (CYP1A2, CYP2C9 and CYP2C19) and adenosine triphosphate-binding cassette subfamily B member 1 (ABCB1), by real-time polymerase chain reaction . Agomelatine concentrations were measured by high performance liquid chromatography coupled to a tandem mass spectrometry detector.

Results:

We calculated a CYP1A2 activity score that was directly correlated with agomelatine pharmacokinetics. Individuals with a decreased enzyme activity (*1C carriers) had a lower clearance and accumulated higher concentrations of agomelatine. In contrast, individuals with a high CYP1A2 inducibility (*1F or *1B carriers) showed an extensive clearance and lower agomelatine concentrations. The apparently marked differences between races were due to the different CYP1A2 genotype distribution. CYP2C9 intermediate/poor metabolisers showed a higher area under the concentration-time curve and maximum concentration. ABCB1 G2677T/A polymorphism affected the time to reach maximum concentration, as subjects carrying A/A+A/T genotypes showed higher values. No association was found for CYP2C19 phenotype. Agomelatine did not produce any change in blood pressure, heart rate or QT interval.

Conclusions:

CYP1A2 polymorphisms affect agomelatine pharmacokinetics. CYP1A2 phenotype inferred from the genotyping of CYP1A2*1C, *1F and *1B alleles might be a potential predictor of agomelatine exposure. ABCB1 G2677T/A could affect agomelatine absorption, as subjects with A/A+A/T genotypes had lower agomelatine concentration and they take more time to reach the maximum concentration.

Keywords

Pharmacogenetics antidepressant agomelatine pharmacokinetics cytochrome P450

Introduction

Agomelatine is an antidepressant drug used for the clinical management of major depressive disorder (MDD), which is one of the most common mental disorders in the world (World Health Organization, 2018). Agomelatine has a distinctive mechanism of action, acting synergistically as an agonist of the melatoninergic receptors MT1 and MT2 and as an antagonist of the post-synaptic serotonergic 5-HT_2c receptor (Laux et al., 2017). MT1 and MT2 are involved in sleep regulation, while 5-HT_2c receptors inhibit the release of dopamine and norepinephrine in the prefrontal cortex. Agomelatine binds to MT1 and MT2 acting as a sleep inducer and blocks 5-HT_2c, acting as an antidepressant (by augmenting the release of monoamines, which levels are compromised in depressive patients) (Buoli et al., 2017; de Bodinat et al., 2010; Stahl, 2014). These agomelatine combined actions help to resynchronise the circadian rhythm, normalise sleep patterns and resolve mood disorders (Srinivasan et al., 2012).

After oral administration (25–50 mg), agomelatine is rapidly absorbed (80%) in the gastrointestinal tract, reaching peak plasma concentrations at approximately two hours. However, it has extensive first-pass metabolism that reduces its bioavailability to less than 5% from the initial oral dose (Freiesleben and Furczyk, 2015). It has a moderate volume of distribution (Vd), of around 35 L, and a short plasma half-life (T_½), of around 1–2 h. It binds to the plasma proteins albumin and glycoprotein alfa-1 (Li et al., 2017). Agomelatine is metabolised in the liver by various cytochrome P450 (CYP) isoenzymes. Around 90% of the drug is hydroxylated by CYP1A2 while the remaining 10% is metabolised by demethylation via CYP2C9 and CYP2C19. The drug has at least four metabolites, but none of them has a pharmacological effect. These are conjugated with glucuronic acid and, thereafter, sulfonated. About 80% of the drug is eliminated through urinary excretion whereas a small number of metabolites are excreted by faecal excretion (Buoli et al., 2017).

Since CYP1A2 is the main enzyme responsible for the metabolism of agomelatine, variants in its coding gene could affect its disposition. Indeed, CYP1A2*1C (rs2069514) has been associated with a decreased enzyme activity (Nakajima et al., 1999) while *1F (rs762551) and *1B (rs2470890) alleles were associated with a lower plasma concentration of agomelatine (Song et al., 2014). Thus, it would be expected that subjects carrying CYP1A2*1C allele show higher agomelatine plasma levels. On the other hand, individuals with either *1F or *1B alleles would show lower levels of agomelatine, due to an enhanced metabolism.

Moreover, although CYP2C9 and CYP2C19 have a less important role in agomelatine metabolism, they might also have an influence on its disposition. CYP2C9*2 (rs1799853) and *3 (rs1057910) alleles are commonly related to a decreased enzyme activity (The Pharmacogene Variation (PharmVar) Consortium, 2018a), as well as CYP2C19*2 (rs4244285) and *3 (rs4986893) alleles (The Pharmacogene Variation (PharmVar) Consortium, 2018b). On the contrary, CYP2C19*17 (rs12248560) is associated with an increased enzyme activity (The Pharmacogene Variation (PharmVar) Consortium, 2018b). However, the influence of these polymorphisms on the pharmacokinetics of agomelatine has not been studied.

Additionally, P-glycoprotein (P-gp), encoded by ABCB1, is an adenosine triphosphate (ATP)-dependent efflux pump that exports substances outside the cell (Ambudkar et al., 1999; Gottesman et al., 1996), thus, influencing the absorption and accumulation of several drugs. A particular polymorphism located in ABCB1, commonly known as C3435T (rs1045642), has been linked to differences in agomelatine response, suggesting that carriers of the T allele showed a lower response to the drug (Jeleń et al., 2015). Moreover, two other polymorphisms, C1236T (rs1128503) and G2677T/A (rs2032582), have been widely studied in the literature, but they have not been related to agomelatine response or disposal.

Agomelatine interindividual variability has not only been associated with polymorphisms in CYP1A2 and ABCB1, but also with different races (Song et al., 2014).

Thus, this remarkable variability in agomelatine exposure suggests that it is necessary to understand the pharmacogenetic background. Our aim was to evaluate the effect of genetic polymorphisms in metabolising enzymes and in one transporter on the pharmacokinetics and pharmacodynamics of agomelatine in healthy volunteers, in order to elucidate if there is any relevant pharmacogenetic factor affecting the disposition of agomelatine.

Materials and methods

Study population

The study population comprised 36 healthy volunteers from a clinical trial performed in the Clinical Trial Unit of Hospital Universitario de La Princesa (Madrid, Spain). The protocol complied with the Spanish Legislation in clinical research in humans and was approved by the Research Ethics Committee, authorised by the Spanish Agency of Drugs and performed according to the guidelines of Good Clinical Practice. All subjects provided their written informed consent for the clinical trial and 28 of them for the pharmacogenetic study.

Inclusion criteria were as follows: age 18–55 years, volunteers free from any psychiatric or organic conditions, normal vital signs and electrocardiogram (ECG), normal medical records and physical examination and no clinically significant abnormalities in serology, haematology, biochemistry and urine test. Exclusion criteria were: subjects who had received pharmacological treatment in the last 15 days or any kind of medication in the 48 h prior to receiving the study medication, body mass index (BMI) outside the 18.5–30 kg/m² range, having donated blood in the previous month, history of sensitivity to any drug, suspected consumption of controlled substances, smokers, daily consumers of alcohol and/or acute alcohol poisoning in the previous week, or pregnant or breastfeeding women.

Study design and procedures

We used the data from a bioequivalence clinical trial of two formulations of agomelatine 25 mg tablets after single oral dose administration to healthy volunteers under fasting conditions. The clinical trial was randomised, open-label, crossover, replicated, four-period, four-sequence, with a wash-out period of seven days and with blinded determination of agomelatine plasma concentrations. Agomelatine was administered with 240 mL of water. For pharmacokinetic analysis, 20 blood samples were obtained between pre-dose and 24 h post-dose. Samples were centrifuged at 4°C for 10 min at 3500 rpm (1900×g). All plasma samples were stored at −20±5°C until its shipment to an accredited external analytical laboratory.

Agomelatine plasma concentrations were determined using high performance liquid chromatography coupled to a tandem mass spectrometry detector (HPLC/MS/MS). The method was validated according to European Medicines Agency (EMA, 2011) guidelines. The lower limit of quantification for agomelatine was 50.25 pg/mL. Chromatographic separation was performed on a reversed phase column (Zorbax Eclipse Plus C18, 3.0×5 0 mm, 3.5 µm, from Agilent Technologies, Madrid, Spain). Ammonium formate 2.5 mM, formic acid 0.02% prepared in water/acetonitrile (60/40 v/v) was used as the mobile phase. Isocratic separation of agomelatine was carried out at room temperature with a flow rate of 0.70 mL/min. Protein precipitation was used as the sample preparation method for agomelatine and its internal standard. The extraction of agomelatine was performed in 100 µL of plasma by adding 50 µL of internal standard for each sample (study sample, calibration standard or quality control). Proteins were precipitated with formic acid 0.1% in acetonitrile.

Pharmacokinetic analysis

Pharmacokinetic parameters were calculated by non-compartmental method using WinNonlin Professional Edition, version 7.0 (Pharsight Corporation, USA). The maximum plasma concentration (C_max) and the time to reach the maximum plasma concentration (T_max) were obtained directly from raw data. The area under the curve (AUC) was calculated from administration to the last measured concentration (AUC_0–t) by linear trapezoidal integration. The total AUC from administration to infinity (AUC_0–∞) was calculated as the sum of AUC_0–t and the residual area (C_t divided by k_e, with C_t as the last measured concentration and k_e as the apparent terminal elimination rate constant, which was estimated by log-linear regression from the terminal portion of the log-transformed concentration-time plots). Half-life (T_1/2) was calculated by dividing 0.693 by k_e. Total clearance of drug adjusted for bioavailability (Cl/F) was calculated by dividing the dose by AUC_0–∞ and adjusting for weight. The volume of distribution adjusted for bioavailability (Vd/F) was calculated as Cl/F divided by k_e. AUC and C_max were adjusted for dose and weight (AUC/dW and C_max/dW, divided by dose/weight ratio) and logarithmically transformed for statistical analysis. For each parameter only the reference formulation (Valdoxan) was analysed for each individual and, since it was a replicated clinical trial, we considered the mean of the two reference formulation values.

Pharmacodynamic analysis and safety

Blood pressure (BP), heart rate (HR) and 12-lead ECG were measured in supine position at pre-dose and two hours post-dose. The QT and HR values were calculated automatically by the ECG device. For the corrected QT interval (QT_c), the Bazett correction formula (Bazett, 1997) was used. According to the Guideline of the International Harmonization Council (2005), we considered as QTc interval prolongation an absolute QTc interval greater than 450 milliseconds or a change from baseline in QTc interval greater than 30 milliseconds.

Throughout the study, volunteers were asked about any adverse event (AE) experienced. Additionally, those AEs that were spontaneously notified by the volunteers were documented. Causality was determined using the Karch and Lasagna criteria (Karch and Lasagna, 1977), according to five types of AE: definite, probable, possible, unlikely and unrelated. Only definite, probable or possible AEs were considered as adverse drug reactions (ADRs) and included in the statistical analysis. Time sequence, intensity and outcome of AEs were also recorded.

Genotyping

DNA was extracted from 1 mL of peripheral blood samples using a DNA automatic extractor (MagNa Pure System, Roche Applied Science, Indianapolis, Indiana, USA) and quantified spectrophotometrically in NanoDrop ND-1000 (Wilmington, Delaware). The 260/280 absorbance ratio was used to measure the purity of the samples.

All polymorphisms analysed were selected given the pharmacokinetic properties of agomelatine. CYP2C9*2 and *3 and CYP2C19*2, *3 and *17 polymorphisms were studied by real-time polymerase chain reaction (PCR) using the LightCyler 2.0 instrument (Roche Diagnostics, Mannheim, Germany). A set of primers and probes were designed by TIB MOLBIOL (Berlin, Germany) for this purpose. ABCB1 (C3435T, C1236T and G2677T/A) and CYP1A2*1C, *1F and *1B polymorphisms were genotyped using a StepOne Real-Time PCR System (Applied Biosystems, Forest City California), using TaqMan probes.

Statistical analysis

To simplify the analysis, CYP2C9 and CYP2C19 genotypes were classified according to the number of functional alleles in poor metabolisers (PMs; carriers of two defective alleles), intermediate metabolisers (IMs; carriers of one defective allele), normal metabolisers (NMs; carriers of two functional alleles) and rapid metabolisers (RMs; CYP2C19 *17 carriers) (Caudle et al., 2017).

As there is no functionality table regarding the activity of CYP1A2 alleles that allows inferring a phenotype, we assigned an activity score to CYP1A2 alleles based on their functionality, as shown in Table 1. This activity score was translated into a comprehensive phenotype to simplify the gene association analysis.

Table 1.

Activity score proposed for each cytochrome P450 (CYP)1A2 allele and inferred phenotype.

CYP1A2 allele	Value assigned to the allele	Activity score	Inferred phenotype
*1C	0.5	1–1.5	PM
*1	1	1.75–2.5	NM/RM
*1F	1.5	2.75–3	UM
*1B	1.25

NM: normal metabolizer; PM: poor metabolizer; RM: rapid metabolizer; UM: ultra-rapid metabolizer.

The activity score for a genotype is calculated as the sum of the values assigned to each allele (e.g. CYP1A2 *1C/*1C genotype has an activity score of one, considered then a PM).

Statistical analysis was performed using SPSS 24.0 software (SPSS Inc., Chicago, Illinois, USA). Statistical significance was set at p values lower than 0.05. Since this study was designed as an exploratory analysis, we did not adjust p values for multiple testing, which is consistent with prior recommendations (Rothman, 1990; Savitz and Olshan, 1998; Thompson, 1998). The Hardy-Weinberg equilibrium was estimated for all analysed variants. Balance deviations were detected by comparing the frequencies observed and expected using a Fisher exact test based on the De Finetti program (“Hardy-Weinberg equilibrium, http://ihg.gsf.de/cgi-bin/hw/hwa1.pl,” 2018). Differences in genotype frequencies according to sex and ethnic groups were determined using a corrected Pearson chi-square test. Differences in pharmacokinetic parameters between individuals with different sex, ethnic groups and genotypes were analysed by univariate parametric analysis (t-test or analysis of variance (ANOVA)). Multiple linear regression models were used to study factors related to all the pharmacokinetic and pharmacodynamic dependent variables. For this purpose, variables with more than two categories, such as polymorphisms, were analysed using dummy variables.

Results

Demographic and genotypic characteristics

Thirty-six healthy volunteers (19 men and 17 women) were included in the study. The mean age was 26.7±7.1 years for men and 28.3±8.5 years for women. Men were taller than women (1.74±0.06 m vs 1.63±0.05 m, p<0.001), weighed more (72.1±10.6 kg vs 59.8±6.9 kg, p<0.001) but exhibited a similar BMI (23.8±2.9 kg/m² vs 22.3±2.6 kg/m² for women, p=0.106). Thirty subjects were Caucasians, five were Latin and one was Black.

From those, 28 healthy volunteers (16 men and 12 women; 22 Caucasian, five Latin and one Black) gave their written informed consent for the pharmacogenetic study. Table 2 shows genotypic frequencies according to sex and race. All the genetic variants were in Hardy-Weinberg equilibrium (p>0.05), except for ABCB1 C1236T.

Table 2.

Genotype frequencies of enzymes and the transporter in the study subjects, stratified by sex and races.

Genotype	Total	Sex		Races
		Men	Women	Caucasian	Latin	Black
CYP1A2*1C	n=28	n=16	n=12	n=22	n=5	n=1^a
1/1	19 (67.9)	12 (75.0)	7 (58.3)	19 (86.4)	0 (0.0)	0 (0.0)
1/1C	7 (25.0)	2 (12.5)	5 (41.7)	3 (13.6)	3 (60.3)	1 (100.0)
1C/1C	2 (7.1)	2 (12.5)	0 (0.0)	0 (0.0)^b	2 (40.0)	0 (0.0)
CYP1A2*1F
1/1	16 (57.1)	8 (50.0)	8 (66.7)	11 (50.0)	5 (100.0)	0 (0.0)
1/1F	9 (32.1)	7 (43.8)	2 (16.7)	8 (36.4)	0 (0.0)	1 (100.0)
1F/1F	3 (10.7)	1 (6.3)	2 (16.7)	3 (13.6)	0 (0.0)	0 (0.0)
CYP1A2*1B
1/1	7 (25.0)	4 (25.0)	3 (25.0)	3 (13.6)	3 (60.0)	1 (100.0)
1/1B	14 (50.0)	8 (50.0)	6 (50.0)	12 (54.5)	2 (40.0)	0 (0.0)
1B/1B	7 (25.0)	4 (25.0)	3 (25.0)	7 (31.8)^b	0 (0.0)	0 (0.0)
CYP1A2 phenotype
PM/IM	3 (10.7)	2 (12.5)	1 (8.3)	0 (0.0)	3 (60.0)	0 (0.0)
NM/RM	15 (53.6)	8 (50.0)	7 (58.3)	12 (54.5)	2 (40.0)	1 (100.0)
UM	10 (35.7)	6 (37.5)	4 (33.3)	10 (45.5)^b	0 (0.0)	0 (0.0)
CYP2C9 phenotype
NM	16 (57.1)	9 (56.3)	7 (58.3)	11 (50.0)	4 (80.0)	1 (100.0)
IM	11 (39.2)	6 (37.5)	5 (41.7)	10 (45.5)	1 (20.0)	0 (0.0)
PM	1 (3.7)	1 (6.3)	0 (0.0)	1 (4.5)	0 (0.0)	0 (0.0)
CYP2C19 phenotype
NM	14 (50.0)	9 (56.3)	5 (41.7)	11 (50.0)	3 (60.0)	0 (0.0)
IM	7 (25.0)	3 (18.7)	4 (33.3)	6 (27.3)	1 (20.0)	0 (0.0)
PM	1 (3.7)	0 (0.0)	1 (8.3)	1 (4.5)	0 (0.0)	0 (0.0)
RM	6 (21.4)	4 (25.0)	2 (16.7)	4 (18.1)	1 (20.0)	1 (100.0)
ABCB1 C3435T
C/C	8 (28.6)	4 (25.0)	4 (33.3)	6 (27.3)	1 (20.0)	1 (100.0)
C/T	18 (64.3)	11 (68.8)	17 (58.3)	15 (68.2)	3 (60.0)	0 (0.0)
T/T	2 (7.1)	1 (6.3)	1 (8.3)	1 (4.5)	1 (20.0)	0 (0.0)
ABCB1 C1236T
C/C	9 (32.1)	6 (37.5)	3 (25.0)	7 (31.8)	1 (20.0)	1 (100.0)
C/T	18 (64.3)	9 (56.3)	9 (75.0)	14 (63.3)	3 (60.0)	0 (0.0)
T/T	1 (3.7)	1 (6.3)	0 (0.0)	1 (4.5)	1 (20.0)	0 (0.0)
ABCB1 G2677T/A
C/C	10 (35.7)	6 (37.5)	4 (33.3)	8 (36.4)	1 (20.0)	1 (100.0)
C/A	16 (57.1)	8 (50.0)	8 (66.7)	13 (59.0)	3 (60.0)	0 (0.0)
A/A	1 (3.7)	1 (6.3)	0 (0.0)	0 (0.0)	1 (20.0)	0 (0.0)
A/T	1 (3.7)	1 (6.3)	0 (0.0)	1 (4.5)	0 (0.0)	0 (0.0)

CYP: cytochrome P450; IM: intermediate metabolizer; NM: normal metaboliser; PM: poor metabolizer; RM: rapid metaboliser.

Values are expressed as number of individuals (%).

This subject was excluded from the chi-square analysis; ^bp<0.05 compared to Latin.

No differences were observed between men and women. However, some differences were observed in the main metabolising enzyme between ethnic groups (Table 2), as CYP1A2*1C allele frequency was lower in Caucasians (7%) than in Latin (70%) (p=0.001). Moreover, CYP1A2*1F had an allele frequency of 32% in Caucasians but 0% in Latin (p=0.060). Finally, CYP1A2*1B allele frequency was 60% in Caucasians but 20% in Latin (p=0.056). As a consequence, CYP1A2 phenotype frequencies were statistically different among races (p=0.002), since all the individuals considered CYP1A2 PM/IM were Latin and all individuals considered CYP1A2 ultra-rapid metabolizers (UMs) were Caucasian. No differences were observed in the genotype frequencies of CYP2C9, CYP2C19 and ABCB1 among races (Table 2).

Pharmacokinetic analysis

Mean and standard deviation (SD) of pharmacokinetic parameters are shown in Table 3. Agomelatine pharmacokinetic parameters were not affected by sex. However, when stratifying individuals by ethnicity, we observed a significantly higher Vd/F and Cl/F in Caucasians subjects compared with Latin (p<0.05). In addition, although not significant, Caucasians exhibited lower AUC and C_max (Table 3). However, after correction for other covariates, such as CYP1A2 phenotype, the multivariate analysis indicated that there was no association between race and any pharmacokinetic parameter (data shown later).

Table 3.

Pharmacokinetic parameters of agomelatine after a single 25 mg oral dose.

Pharmacokinetic parameter	Total(n=36)	Men(n=19)	Women(n=17)	p-Value	Caucasian (n=30)	Latin(n=5)	Black(n=1)^a	p-Value
AUC (ng·h/mL)	261.2 (230.4)	236.9 (201.0)	288.4 (263.1)	0.590	223.5 (218.0)	459.2 (235.3)	403.9	0.033
AUC/dW (ng·h·mg/mL·kg)	684.3 (594.7)	665.4 (527.9)	705.4(677.7)	0.981	587.8 (553.4)	1129.5 (666.7)	1353.9	0.060
C_max (ng/mL)	211.3 (220.1)	176.5 (142.7)	250.2 (282.9)	0.633	182.6 (212.3)	385.1 (230.8)	203.8	0.060
C_max/dW (ng·mg/mL·kg)	548.5 (546.2)	492.0 (363.2)	611.6 (704.3)	0.950	475.5 (518.1)	959.5 (639.0)	683.3	0.100
T_max (h)	1.2 (0.5)	1.2 (0.5)	1.2 (0.5)	0.967	1.3 (0.6)	1.0 (0.2)	1.0	0.262
T_1/2 (h)	0.9 (0.1)	0.9 (0.2)	0.9 (0.1)	0.788	0.9 (0.2)	0.9 (0.2)	1.0	0.696
Vd/F (L/kg)	52.8 (62.4)	50.4 (59.0)	55.4 (67.8)	0.699	59.6 (66.2)	19.2 (15.7)	15.9	0.045
Cl/F (L/h·kg)	38.6 (41.3)	36.0 (38.0)	41.5 (45.7)	0.616	43.6 (43.4)	14.2 (11.7)	9.9	0.028

ANOVA: analysis of variance; AUC: area under the curve; C_max: maximum plasma concentration; Cl/F: total drug clearance adjusted for bioavailability; dW: adjusted for dose and weight ratio; SD: standard deviation; T_1/2: half-life; T_max: time to reach the maximum plasma concentration; Vd/F: volume of distribution adjusted for bioavailability.

Values are shown as mean (SD).

This subject was excluded from the ANOVA analysis.

The univariate analysis revealed an association between some pharmacokinetic parameters and polymorphisms in CYP1A2, CYP2C9 and ABCB1 (Table 4). Although there were some non-statistically significant tendencies regarding the influence of CYP1A2 alleles alone, when analysing them in an inferred phenotype we observed that UM subjects showed a significant lower AUC and higher Vd/F and CL/F (Figure 1). The differences in AUC, Vd/F and Cl/F were confirmed in the multivariate analysis after correction for other covariates (Table 5). Moreover, we found that CYP1A2 PM/IM had a significant higher C_max (Table 5).

Table 4.

Association between agomelatine pharmacokinetic parameters and polymorphisms in the studied enzymes and transporter.

Gene	n	AUC (ng·h/mL)	Cmax (ng/mL)	Tmax (h)	T1/2 (h)	Vd/F (L/kg)	Cl/F (L/h·kg)
CYP1A2*1C
1/1	19	214.3 (226.0)	185.0 (245.1)	1.2 (0.5)	0.9 (0.2)	57.6 (56.2)	42.6 (36.0)
1/1C	7	320.8 (255.2)	255.9 (244.2)	1.2 (0.7)	1.0 (0.1)	52.6 (76.4)	37.1 (53.4)
1C/1C	2	426.3 (184.5)	333.9 (70.1)	1.2 (0.0)	0.8 (0.2)	15.7 (10.5)	12.4 (5.2)
CYP1A2*1F
1/1	16	289.1 (210.6)	235.9 (182.3)	1.2 (0.6)	0.9 (0.2)	39.2 (51.5)	29.3 (37.0)
1/1F	9	241.6 (298.6)	218.0 (341.9)	1.1 (0.5)	0.9 (0.2)	68.5 (60.4)	50.8 (41.6)
1F/1F	3	123.3 (84.2)	79.5 (49.9)	1.3 (0.5)	0.9 (0.4)	84.2 (95.2)	56.0 (45.6)
CYP1A2*1B
1/1	7	338.7 (248.9)	241.4 (192.2)	1.1 (0.4)	0.9 (0.3)	44.3 (66.6)	29.7 (36.2)
1/1B	14	248.5 (274.4)	223.3 (302.8)	1.1 (0.6)	0.9 (0.2)	67.9 (68.3)	50.0 (47.2)
1B/1B	7	188.4 (75.3)	165.5 (103.8)	1.4 (0.6)	0.9 (0.2)	33.8 (16.5)	27.0 (18.9)
CYP1A2 phenotype
PM/IM	3	532.3 (225.3)	415.9 (150.4)	1.0 (0.3)	1.0 (0.3)	13.8 (8.2)	10.0 (5.6)
NM/RM	15	238.9 (164.9)	186.7 (157.8)	1.3 (0.6)	0.9 (0.1)	41.5 (52.5)	31.2 (37.6)
UM	10	198.9 (282.2)^a	192.6 (328.2)	1.1 (0.5)	0.9 (0.3)	83.4 (67.2)^a	59.6 (40.3)^a
CYP2C9 phenotype
NM	16	264.6 (275.1)	219.9 (283.5)	1.1 (0.4)	0.9 (0.2)	67.7 (73.7)	47.8 (46.5)
IM/PM	12	244.6 (172.5)	204.6 (163.4)	1.4 (0.7)	0.9 (0.2)	34.5 (23.5)	27.4 (25.0)§
CYP2C19 phenotype
NM	14	281.0 (277.0)	239.6 (292.9)	1.2 (0.6)	0.9 (0.2)	40.9 (26.2)	31.6 (24.7)
IM/PM	7	276.4 (227.7)	244.4 (2111.7)	1.1 (0.4)	0.8 (0.2)	53.7 (72.2)	41.0 (46.1)
RM	7	185.9 (135.6)	129.9 (92.9)	1.3 (0.5)	1.0 (0.2)	78.3 (89.8)	52.1 (56.9)
ABCB1 C3435T
C/C	8	256.6 (234.1)	196.4 (206.2)	1.0 (0.1)	1.0 (0.2)	78.1 (88.8)	53.9 (59.7)
C/T	18	267.7 (249.3)	235.0 (261.1)	1.3 (0.5)	0.9 (0.2)	44.3 (44.0)	33.7 (29.3)
T/T	2	149.3 (0.7)	86.8 (44.5)	1.8 (1.2)§	0.9 (0.0)	37.5 (10.7)	28.0 (8.1)
ABCB1 C1236T
C/C	9	256.2 (215.0)	211.1 (188.1)	1.0 (0.2)	1.0 (0.2)	53.8 (59.0)	35.4 (34.2)
C/T+T/T	19	256.0 (246.6)	214.5 (260.1)	1.3 (0.6)	0.9 (0.2)	53.3 (61.2)	40.8 (42.6)
ABCB1 G2677T/A
C/C	10	233.4 (215.2)	192.9 (186.5)	1.0 (0.2)	1.0 (0.2)	72.6 (80.6)	50.2 (54.2)
C/A	16	274.4 (261.4)	227.7 (278.9)	1.3 (0.5)	0.9 (0.2)	44.8 (44.9)	34.6 (29.8)
A/A+A/T	2	222.3 (103.9)	201.3 (117.3)	1.9 (1.0)^a,b	0.9 (0.0)	26.6 (4.8)	19.2 (4.4)

AUC: area under the curve; C_max: maximum plasma concentration; Cl/F: total drug clearance adjusted for bioavailability; CYP: cytochrome P450; IM: intermediate metabolizer; NM: normal metabolizer; PM: poor metabolizer; RM: rapid metabolizer; SD: standard deviation; T_1/2: half-life; T_max: time to reach the maximum plasma concentration; UM: ultra-rapid metabolizers; Vd/F: volume of distribution adjusted for bioavailability.

Values are shown as mean (SD).

p<0.05; ^bp<0.05 in Caucasians.

Table 5.

Factors influencing agomelatine pharmacokinetic parameters. Results from the multivariate analysis.

Independent variable	Pharmacokinetic parameters
	AUC (ng·h/mL)	C_max (ng/mL)	T_max (h)	T_1/2 (h)	Vd/F (L/kg)	Cl/F (L/h·kg)
Sex	—	—	—	—	—	—
Age	β=0.064; p=0.001	β=0.079; p<0.001	—	—	—	—
Race	—	—	—	—	—	—
CYP1A2 PM/IM	β=10577; p=0.004	β=2.055; p<0.001	—	—	—	—
CYP1A2 UM	β=-0.589; p=0.052	—	—	—	β=0.953; p=0.006	β=1.002; p=0.004
CYP2C9 PM/IM	β=0.673; p=0.029	β=0.903; p=0.004	—	—	—	—
CYP2C19 PM/IM	—	—	—	—	—	—
CYP2C19 RM	—	—	—	—	—	—
ABCB1 C3435T C/T	—	—	—	—	—	—
ABCB1 C3435T T/T	—	—	—	—	—	—
ABCB1 C1236T C/T+T/T	—	—	—	—	—	—
ABCB1 G2677T/A C/A	—	—	—	—	—	—
ABCB1 G2677T/A A/A+A/T	—	—	β=0.765; p=0.047	—	—	—
R²	0.558	0.599	0.144	—	0.258	0.283

β: non-standardised β coefficient; AUC: area under the curve; C_max: maximum plasma concentration; Cl/F: total drug clearance adjusted for bioavailability; CYP: cytochrome P450; IM: intermediate metabolizer; NM: normal metabolizer; PM: poor metabolizer; RM: rapid metabolizer; T_1/2: half-life; T_max: time to reach the maximum plasma concentration; UM: ultra-rapid metabolizer; Vd/F: volume of distribution adjusted for bioavailability.

Likewise, when analysing the pharmacokinetic values stratified by ethnicity, CYP2C9 IM/PM showed a lower Cl/F compared with NM in Caucasians. Indeed, in the multivariate analysis, when including race, CYP1A2 and sex as covariates, CYP2C9 IM/PM showed a significant relationship towards a higher AUC and C_max (Table 5). On the contrary, we found no significant association between polymorphisms in CYP2C19 and agomelatine pharmacokinetics.

Regarding the transporter P-gp, we observed a significantly higher T_max in carriers of ABCB1 G2677T/A A/A or A/T genotype (Table 4), which continued to be statistically significant after multivariate correction (Table 5). Moreover, when stratifying into races, ABCB1 C3435T T/T and G2677T/A A/A or A/T carriers showed a significantly higher T_max in Caucasians.

Pharmacodynamic analysis

In regard to sex, women showed lower BP, which was an expected finding. Moreover, agomelatine did not produce a significant change in BP, HR and QTc. There was one subject with a prolonged QTc (an increase of 30.5 ms from baseline) at two hours post-dose, which was not considered clinically relevant. According to the European Medicines Agency criteria (European Medicines Agency, Committee for Medicinal Products for Human Use (CHMP), 2010), an increase of 60 ms from the initial QTc interval is considered a risk of a potential fatal ventricular tachyarrhythmia, also known as torsade de pointes. No volunteer experienced this increase.

Regarding the safety profile, only one individual experienced one AE considered possibly related to agomelatine, which was abdominal pain of mild-moderate intensity. This ADR has been previously described in the agomelatine drug label (AEMPS, 2018).

Discussion

Agomelatine is an antidepressant that has demonstrated non-inferior effectiveness as compared with selective serotonin reuptake inhibitors (SSRIs) or serotonin and norepinephrine reuptake inhibitors (SNRIs) (Kasper et al., 2010; Laux and the VIVALDI Study Group, 2012) and has a better tolerability profile regarding sleep or sexual disorders (Kennedy and Rizvi, 2010; Laux and the VIVALDI Study Group, 2012). Given the limited efficacy of antidepressants, pharmacogenetic studies are crucial to determine markers that can predict treatment failure. In the case of agomelatine, which has extremely variable pharmacokinetic features (Pei et al., 2014), not many studies analysing its pharmacogenetic background have been performed as it is a relatively new antidepressant.

Agomelatine pharmacokinetics

In our study, consistent with the previously reported results, agomelatine pharmacokinetic parameters varied widely among individuals, possibly due to its extensive first-pass metabolism and a large Vd with high lipophilicity (Li et al., 2017).

The pharmacokinetic parameters of agomelatine that we obtained differed from those found in another bioequivalence trial conducted in healthy Chinese subjects (Li et al., 2017). It has been previously stated that the pharmacokinetic profile of agomelatine could be different among races (Song et al., 2014), which was also shown in our study, as Caucasians showed approximately 50% lower AUC compared with Latins. However, no association was found after correction for the studied genotypes. Thus, these apparently marked differences were due to the different CYP1A2 genotype distribution among the two groups. However, all CYP1A2 allele frequencies were similar to those reported in the 1000-genome database for each ethnic group (1000 Genomes Project Consortium et al., 2015).

Besides, as CYP1A2 isoenzyme plays a critical role in the hepatic metabolism of agomelatine, variations in its activity by any inducing or inhibitory factor could affect agomelatine pharmacokinetics and increase its variability. In our study, each polymorphism itself was not capable of predicting any significant change in agomelatine pharmacokinetic parameters, probably due to the small sample size. However, we demonstrated that a CYP1A2 phenotype inferred from the presence of both inactivating and inducible polymorphisms is able to predict agomelatine disposition. Compatible with the expected, we observed that individuals with a lower metabolism (PMs/IMs), namely carriers of CYP1A2*1C, had lower Cl/F and, consequently, accumulated higher concentrations of agomelatine. However, our results contradict those of Song et al., who performed a study in Chinese healthy volunteers and did not find any difference in the pharmacokinetic parameters of CYP1A2*1C carriers compared with the wild-type (Song et al., 2014). On the other hand, in our study, individuals with a high inducibility (UMs), namely carriers of CYP1A2*1F or *1B, showed an extensive Cl/F and lower concentrations of agomelatine. This is consistent with the study carried out by Song et al. in which carriers of CYP1A2*1F and *1B presented significantly lower agomelatine exposure (AUC, C_max) (Song et al., 2014). Thus, CYP1A2 phenotype might be a potential predictor of agomelatine exposure.

Indeed, it can be hypothesised that carriers of the CYP1A2 PM/IM phenotype would not only show a better response to agomelatine treatment due to higher plasma concentrations, but also could have a higher risk of adverse reactions. Conversely, it can be expected that CYP1A2 UM patients would show a poorer response, as a consequence of higher drug clearance. Further studies need a larger sample size to better calculate a dose adjustment and to demonstrate if it is a useful tool to reach a better response. However, according to these preliminary results, we propose genotyping CYP1A2*1C, *1F and *1B and combination of the genotyping results into a phenotype (Table 1) to predict agomelatine pharmacokinetic parameters.

Regarding the CYP2C9 phenotype, IM/PM Caucasian subjects showed a lower agomelatine Cl/F as compared with NM, as they had a lower enzyme activity. Moreover, in the multivariate analysis, IMs/PMs showed a significantly higher AUC and C_max, which is consistent with the expected finding. Since CYP2C9 and CYP2C19 play a minor role in agomelatine metabolism, this finding might only be relevant in CYP1A2 PM. Further research is needed to confirm if there is any association between polymorphisms in CYP2C9 and CYP2C19 and agomelatine pharmacokinetics.

With regard to ABCB1, we found that C3435T and G2677T/A affected agomelatine T_max in Caucasian individuals. Indeed, after multivariate analysis corrected by race, sex and polymorphisms, G2677T/A continued to be a significant factor affecting T_max, as subjects carrying A/A or A/T genotype showed higher values. The influence of ABCB1 C3435T polymorphism on antidepressant disposition has been widely studied and has produced contradictory results (Saiz-Rodríguez et al., 2018). As our group has previously reviewed, ABCB1 C3435T can affect the elimination of some drugs in different ways: enhanced elimination has been found in some antipsychotics such as risperidone and dehydro-aripiprazole, while diminished elimination was found for olanzapine and citalopram (Saiz-Rodríguez et al., 2018). ABCB1 C3435T, which is a synonymous variant, is in partial linkage disequilibrium with G2677T/A, which is a missense polymorphism. Thus, it is more likely that G2677T/A is the responsible polymorphism affecting the transporter activity. The fact that individuals carrying the A/A or A/T genotype showed a higher T_max could mean that this polymorphism enhances P-gp activity, as they show a lower drug concentration and thus it takes more time to reach the C_max. Further studies with sufficient statistical power are needed to determine the clinical relevance of ABCB1 polymorphisms in agomelatine treatment. Since P-gp is involved in the drug’s passage to the central nervous system, it is problematic to predict what the effect of ABCB1 polymorphism will be on the efficacy and safety of agomelatine from the results of the current study. Further studies in patients receiving this drug must be performed.

Study limitations

The study was performed after single-dose administration to healthy subjects, which prevents us from assessing long-term effectiveness and safety. Agomelatine pharmacokinetics and pharmacodynamics might vary in depressive patients receiving chronic treatment. However, a single-dose design in healthy subjects can assess the effect of genetic polymorphisms over agomelatine without other confounding factors such as smoking or concomitant treatment. As this is an exploratory study, it is important that these results are interpreted with caution given the small sample size. Although our results cannot be directly applicable in the clinical setting, the correlation of pharmacokinetics differences with genotypes is noteworthy, since it is the first study that can provide sufficient data to guide more exhaustive clinical research. Larger studies are needed to increase the statistical power of these results.

Another potential limitation is that no correction was made for multiple testing, which could lead to false positive results. Nevertheless, some statisticians recommend no correction for multiple comparisons when analysing data (Rothman, 1990; Savitz and Olshan, 1998; Thompson, 1998). It is recommended to account for multiple comparison once interpreting the results, rather than in calculations. Indeed, it has been reasoned that the use of multiple comparison corrections is an inefficient approach to perform empirical research, since it could lead to a control of false positives at the potential cost of many more false negatives (Feise, 2002; Perneger, 1998).

Conclusion

CYP1A2 activity score is directly correlated with agomelatine pharmacokinetic parameters. Thus, the CYP1A2 phenotype inferred from the genotyping of CYP1A2*1C, *1F and *1B alleles might be a potential predictor of agomelatine exposure. Based on this activity score, individuals with a slower metabolism had a lower Cl/F and, consequently, accumulated higher concentrations of agomelatine. On the other hand, individuals with high CYP1A2 inducibility showed an extensive Cl/F and lower concentrations of agomelatine. In addition, individuals CYP2C9 IM/PM showed a significantly higher AUC and C_max. However, no association was found between CYP2C19 phenotype and agomelatine pharmacokinetics. Regarding the transporter P-gp, the ABCB1 G2677T/A polymorphism was a significant factor affecting T_max, as subjects carrying A/A or A/T genotype showed higher values, suggesting that this polymorphism enhances P-gp activity, as subjects show a lower drug concentration and thus it takes more time to reach C_max. Agomelatine did not produce a significant change in BP, HR or QT_c interval.

Footnotes

Acknowledgements

The authors are grateful to the volunteers and the effort of the staff of the Clinical Trial Unit of Hospital Universitario de La Princesa.

Declaration of conflicting interests

The author(s) declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: F Abad-Santos and D Ochoa have been consultants or investigators in clinical trials sponsored by the following pharmaceutical companies: Abbott, Alter, Chemo, Cinfa, FAES Farma, Farmalíder, Ferrer, GlaxoSmithKline, Galenicum, Gilead, Italfarmaco, Janssen-Cilag, Kern Pharma, Normon, Novartis, Servier, Silverpharma, Teva and Zambon. The remaining authors declare no conflicts of interest.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship and/or publication of this article: D Koller is co-financed by the H2020 Marie Sklodowska-Curie Innovative Training Network 721236 grant. P Zubiaur is co-financed by Consejería de Educación, Juventud y Deporte from Comunidad de Madrid and Fondo Social Europeo. Clinical Trial Registry URL, . Clinical Trial Registry Number 2016-000445-31.

ORCID iDs

Miriam Saiz-Rodríguez

Danilo Vieira de Lara

Dora Koller

Francisco Abad-Santos

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