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Research Article
The impact of CYP2C19 genotypes on steady-state plasma concentration of escitalopram in South Indian population with Major Depressive Disorder
expand article infoB. Jeevan Kumar‡, Vijayakumar Thangavel Mahalingam‡, Ganesh Kumar M§
‡ SRM College of Pharmacy, SRM Institute of Science and Technology, Kattankulathur, India
§ Department of Psychiatry, Sri Venkateswara Institute of Medical Sciences, Tirupati, India

Corresponding author: Vijayakumar Thangavel Mahalingam ( vijaypractice@yahoo.com )

Academic editor: Magdalena Kondeva-Burdina
© 2024 B. Jeevan Kumar, Vijayakumar Thangavel Mahalingam, Ganesh Kumar M.
This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Citation: Kumar BJ, Thangavel Mahalingam V, Kumar M G (2024) The impact of CYP2C19 genotypes on steady-state plasma concentration of escitalopram in South Indian population with Major Depressive Disorder. Pharmacia 71: 1-6. https://doi.org/10.3897/pharmacia.71.e123645
Open Access

Abstract

Background: Among depressed patients, escitalopram plasma levels differed between those who were considered as extensive metabolizers and poor metabolizers of CYP2C19. However, the majority of research utilized the dose-response relationship. Consequently, we investigated the effect of variations in the CYP2C19 gene on the levels of drug in the bloodstream of individuals suffering from Major Depressive Disorder (MDD) in south India.

Methods: A total of 109 individuals with MDD who were prescribed escitalopram at doses of 5, 10, 15, or 20 mg daily participated in this research. We used HPLC with SPD-10AVP UV-Visible detector to measure the escitalopram concentrations in the blood. The polymorphisms of the CYP2C19 were determined by employing the PCR techniques.

Results: Our study found that 55% of the subjects were intermediate metabolizers, followed by extensive (19.3%), poor (17.4%), and ultra-rapid (8.3%). The significant correlation is identified between the steady state plasma concentration and Sex with (P - Value < 0.05), insignificant correlation was seen in Age and BMI with (P - Value > 0.05). The majority of gene variants seen in the study population were CYP2C19*1/*2, accounting for 49 individuals (44.9%).

Conclusion: These findings showed that sex had a substantial impact on the CYP2C19 genetic variation. Medication administration to individuals with CYP2C19 PM requires special caution.

Keywords

CYP2C19, Major Depressive Disorder (MDD), metabolizers, escitalopram, South India, gene, Polymerase Chain Reaction (PCR)

Introduction

Major Depressive Disorder (MDD), often known as clinical depression, is a serious mental illness that may change a person’s life. Permanent sorrow, lack of interest or pleasure in activities, and physical and cognitive problems define it. MDD increases mortality and morbidity (Murray CJ and Lopez AD 1997). Depressed persons of all ages number over 264 million worldwide, according to the WHO (GBD 2018). It’s the fourth largest cause of disability (DALYs) and anticipated to be the second by 2030 (Murray and Lopez 1996). India’s National Mental Health Survey in 2015–2016 estimated the lifetime prevalence of depressive disorders as 1.8%–39.6%. MDD therapy often involves SSRIs (American Psychiatric Association 2010).

Escitalopram, a popular SSRI, treats MDD effectively (Burke et al. 2002). Serotonin transport is dose-dependently inhibited by escitalopram (Garnock-jones KP and McCormack PL 2010). It improves central nervous system serotonin by blocking presynaptic nerve ending reuptake (Kirino E 2012). Escitalopram is approved at 10 and 20 mg in clinical trials (5 mg in subpopulations or as a starting dosage). When administered orally, escitalopram achieves tmax in 5 hours and is 56% protein-bound. Within 1–2 weeks, escitalopram reaches steady-state blood concentrations (Pastoor D and Gobburu J 2014; Rao N 2007).

Escitalopram metabolism depends on an enzyme called CYP2C19. Genetic variants in the CYP2C19 gene may vary enzymatic activity, with the wild-type allele CYP2C19*1 encoding a fully functioning enzyme. Poor metabolizers often contain variant alleles *2 and *3, along with the *17 variation linked to increased enzyme activity. This genetic diversity produces extensive, intermediate, poor, and ultra-rapid metabolizers (Zhou and Duan W 2009).

About 15 to 25 percent of Asians are poor metabolizers (PM) of escitalopram, but less than 5 percent of white Europeans are PM (Man et al. 2010). Alleles for CYP2C19*2, CYP2C19*3, and CYP2C19*17 are responsible for the majority of cases of poor metabolism (Ota et al. 2015). The rates of CYP2C9*2 (2.6%) and *3 (6.7%) (Adithan et al. 2003) in the Tamilian population were about the same as in Caucasians (12.0% for *2 and 8.3% for *3) and Chinese (0% for *2 and 3.3% for *3) (Xie et al. 2002). Tamilians are more likely than Chinese to have CYP2C19*2 (37.9% vs. 30.0%) (Xie et al. 2002; Adithan et al. 2003). It has been found that 19.2% of the Tamil people in South India have the CYP2C19*17 gene (Anichavezhi et al. 2010).

However, although a few research studies demonstrate a connection between CYP2C19 genotypes to steady-state plasma escitalopram levels in White and Asian population (Tsai et al. 2010; Waade et al. 2014) there is still little information about these associations in the South Indian population. As a result, we looked at the influence of CYP2C19 genotypes on the steady-state plasma concentration of escitalopram in South Indian patients suffering from MDD. Additionally, a-part from CYP2C19 genotypes other variables like age, body weight, and sex differences were determined.

Materials and methods

This study enrolled 109 south Indian outpatients (76 female and 33 male) fulfilled the inclusion criteria mentioned as follows: (1) Patients of either sex, (2) age between 18 and 55 years, (3) patients with escitalopram treatment only and (4) individuals who exhibit depressive symptoms as defined by DSM V.

The exclusion criteria include: (1) patients with diabetes, hypertension, and ischemic heart disease (2) History of receiving antidepressants within the last six weeks; (3) Pregnant or lactating women; (4) History of substance abuse and drug allergies; (5) Chronic illness or taking drugs that cause depression; (7) Neurological disorders, like stroke, dementia, or seizures. The study was approved by the Institute Ethics Committee (Sri Venkateswara Institute of Medical Sciences (SVIMS), Tirupati) vide No.1299. Written informed consent to participate in this study was obtained from all the patients.

Study protocol

Escitalopram was given daily at 5, 10, 15, or 20 mg for 2–12 weeks. Previous escitalopram elimination half-lives were 26 hours (Pastoor D and Gobburu J 2014). Thus, all patients had steady-state plasma concentrations of these substances before the beginning of the study. We assessed patient compliance. Those with undetectable plasma escitalopram levels were eliminated from the trial (n = 15). Potential hepatic/renal dysfunction individuals were eliminated. Subjects were requested to stay away from alcohol and all medications, including OTC medications, for a minimum of three days preceding to and during the investigation period.

Assay for escitalopram

After 14–16 hours of last dose of escitalopram, in the tubes containing 100 μl of 10% EDTA, 5 ml of venous blood was collected from the antecubital vein. After being centrifuged at 1,225 × g for 5 minutes, the samples were collected as plasma. Before the test, the plasma was frozen at -20 °C. HPLC was used to measure plasma escitalopram levels in triplicate (Yasui-Furukori et al. 2016). The extraction process was the following: The following components were added to 2 L of plasma: 0.5 mL of 0.5 M NaOH, 100 mL of trifluperidol 200 mcg/mL, an internal standard solution, and 100 mL of methanol. The 5 mL of n-heptane-chloroform (70:30, vol/vol) extraction solvent was added after 10 seconds of vortexing. It was centrifuged at 2500 g for 10 minutes at 48 °C after 10 minutes of shaking, and then evaporated under vacuum at 408C until dry (TAITEC VC-960; Shimadzu, Kyoto, Japan). Adding 400 mL of the dissolved residue to 500 mL of mobile phase and injecting the mixture onto the stationary phase HPLC system. The HPLC system included Shimadzu LC-10AT pumps, CTO-10AVP column oven, Work station CLASS-VP chromatography integrator, SPD-10AVP UV-Visible detector, SIL-10ADVP (500-mL injection volume), and STR-ODS II C18 150 · 4.6, 3 mm column (Shimadzu, Tokyo, Japan). Phosphate buffer (0.02 M, pH = 4.6), acetonitrile, and perchloric acid (60%) formed the mobile phase with isocratic flow of 1.0 ml/min. The lower limits of detection were 1.0 ng/mL, and the inter assay coefficient of variation was less than 9.1% at all escitalopram calibration curve concentrations. The lower limit of quantification (LLOQ) in this study was found as 2.7 ng/ml (2.7–154 ng/mL).

Genotyping

DNA was extracted from leukocytes in the cellular fraction using phenol:chloroform after centrifugation and plasma separation. The following variables were used in 20 µl PCR reactions: 10 µl of Ex Taq (2X) (Probe qPCR) premix (Takara Bio Inc.), 0.4 µl of primer, 0.8 µl of probe mix, and 1 µl of genomic DNA as template. An Agentech Gentier real-time PCR 48E system with Ianlong® amplification was employed. The procedure included a 30-second pre-incubation at 95 °C and a two-step amplification procedure including 5 seconds at 95 °C and 30 seconds at 60 °C. At 60 °C read steps, fluorescence emission was measured. Allele frequency for CYP2C19 was used to divide the participants into four groups: extensive metabolizers (*1/*1), ultra-rapid metabolizers (*1/*17 or *17/*17), intermediate metabolizers (*1/*2 or *2/*17), and poor metabolizers (*2/*2 or *2/*3).

Statistical analysis

A one-way analysis of variance was utilized in order to achieve the comparison of plasma drug concentrations among the various genotypes of CYP2C19 expression. To compare continuous variables, an unpaired t-test was used, with means ± SD. In order to investigate the various factors that influence plasma medication concentrations, including age, gender, body mass index (BMI), co-morbidities, and CYP2C19 genotype, analysis of covariance was utilized. A p-value of 0.05 or less was necessary for statistical significance. This statistical study was carried out with the assistance of SPSS 22.0 for Windows.

Results

In this study, 124 individuals were assessed; 15 were non-adherent to the medication and were ineligible, whereas 109 (78 Females and 31 Males) were included. The mean ± SD (range) age and BMI were 43.92 ± 9.26 (18–55) years and BMI 25.122 ± 5.69. Our study found that 55% of the subjects were intermediate metabolizers, followed by extensive (19.3%), poor (17.4%), and ultra-rapid (8.3%) (Table 1).

Table 1.
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The parameters of the patient and distribution.

Daily Dose 5 mg 10 mg 15 mg 20 mg
No. of. Patients 38 31 22 18
Age (Yrs.) 40.5 ± 10.2 44.3 ± 9.4 43.9 ± 8.0 49.6 ± 5.8
Sex
Male 11 7 9 4
Female 27 24 13 14
BMI (kg/m2) 26.1 ± 5.9 23.8 ± 5.4 24.8 ± 6.7 26.5 ± 5.1
Phenotype
Extensive Metabolizer (EM) 13 2 1 5
Intermediate Metabolizer (IM) 19 19 14 8
Poor metabolizers (PM) 5 7 5 2
Ultra Rapid Metabolizers (UM) 1 3 2 3

Subjects were divided into four groups according to the number of CYP2C19 mutant alleles: extensive metabolizers (*1/*1), ultra-rapid metabolizers (*1/*17 or *17/*17), intermediate metabolizers (*1/*2 or *2/*17), and poor metabolizers (*2/*2 or *2/*3) (Hicks et al. 2015).

The average (± SD) plasma concentrations of escitalopram in EM, IM, PM & UM were 18.6 +/- 4.06.3, 28.25 +/- 6.12, 38.2 +/- 8.23 and 17.5 ng/mL in 5 mg/d, 28.5 +/- 14.8, 48.21 +/- 8.87, and 68.85 +/- 17.0 and 28.67 +/- 9.5 ng/mL in 10 mg/d, 34.2, 49.3 +/- 10.6, 76.2 +/- 21.1 and 41.5+/- 0.7 ng/mL in 15 mg/d, and 50.8 +/- 7.02, 72.87 +/- 18.3, 100.5 +/- 19.09 and 35.1 +/- 13.8 ng/mL in 20 mg/ d, respectively (Fig. 1).

Figure 1. 

Influence of CYP2C19 genotypes on the steady state plasma concentration of escitalopram in each dose with box-and-whisker plots.

The confounding factor (Age (above 50 years), sex, BMI (Above 25) other than genotype) of study population may have influence on the steady state plasma concentration (Table 2).

Table 2.
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Impact of patient factors on steady- state plasma concentration.

d. f. F - Value P - Value
Age 1 1.6 1.61
Sex 1 3.08 0.00004
BMI 1 0.72 0.139

d. f: degree of freedom.

The significant corelation is identified between the steady state plasma concentration and Sex with (P- Value < 0.05), insignificant correlation was seen in Age and BMI with (P – Value > 0.05). The majority of gene variants seen in the study population were CYP2C19*1/*2, accounting for 49 individuals (44.9%). This was followed by CYP2C19*1/*1, which represented 21% (19.2%) of the population. Other variants included CYP2C19*2/*2 (14.6%), CYP2C19*2/*17 (10.1%), CYP2C19*1/*17 (8.2%), and CYP2C19*2/*3 (2.7%). The study population consisted mostly of individuals who were CYP2C19*1/*2 and belonged to the category of Intermediate metabolizers. The Ultra-Rapid Metabolizers had lower plasma drug concentrations compared to Intermediate Metabolizers, with a P-value of all doses ≤ 0.05 (Table 3).

Table 3.
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The Influence of CYP2C19 genotype on Escitalopram.

Genotype
5 mg
Meaures CYP2C19 *1/*1 (N = 13) CYP2C19 *1/*17 (N = 1) CYP2C19 *1/*2 (N = 16) CYP2C19 *2/*17 (N = 3) CYP2C19 *2/*2 (N = 4) CYP2C19 *2/*3 (N = 1)
Concentration 18.7 17.5 28.56 30.66 35.5 49
95% CI 16.2–21.2 NA 25.74–31.38 23.13–38.17 29.05–41.95 NA
Log Fold changes -0.61 -0.706 NA 0.102 0.313 0.778
P – value 2.19 × 10-5 NA NA 0.64 0.116 NA
10 mg
Meaures CYP2C19 *1/*1 (N = 2) CYP2C19 *1/*17 (N = 2) CYP2C19 *1/*2 (N = 17) CYP2C19 *2/*17 (N = 2) CYP2C19 *2/*2 (N = 5) CYP2C19 *2/*3 (N = 2)
Concentration 28.5 28.66 47.8 53 69.8 66.5
95% CI 7.9–49.1 17.9–39.3 43.46–52.14 45.17–60.83 51.7–87.9 61.6–71.4
Log Fold changes -0.746 -0.737 NA 0.148 0.546 0.476
P – value 0.305 0.055 NA 0.396 0.075 0.0108
15 mg
Meaures CYP2C19 *1/*1 (N = 1) CYP2C19 *1/*17 (N = 3) CYP2C19 *1/*2 (N = 11) CYP2C19 *2/*17 (N = 3) CYP2C19 *2/*2 (N = 5) CYP2C19 *2/*3 (N = 0)
Concentration 34.2 41.5 52.2 51 76.2 0
95% CI NA 40.8–42.2 49.02–55.38 48.74–53.26 57.7–94.7 NA
Log Fold changes -0.61 -0.33 NA -0.0335 0.545 NA
P – value NA 0.00013 NA 0.57 0.063 NA
20 mg
Meaures CYP2C19 *1/*1 (N = 5) CYP2C19 *1/*17 (N = 3) CYP2C19 *1/*2 (N = 5) CYP2C19 *2/*17 (N = 3) CYP2C19 *2/*2 (N = 2) CYP2C19 *2/*3 (N = 0)
Concentration 50.8 35.1 69.2 79 100.5 0
95% CI 43.93–57.67 19.4–50.8 50.7–87.7 63.1–94.9 74.1–126.9 NA
Log Fold changes -0.445 -0.979 NA 0.191 0.538 NA
P – value 0.126 0.034 NA 0.463 0.192 NA

Discussion

South India encompasses the southern region of the Indian peninsula and comprises four states: Andhra Pradesh, Kerala, Karnataka, and Tamil Nadu. These limits refer to geographical and sociolinguistic divisions, and it is unlikely for intermarriage to occur. This study is the first to examine the association between the CYP2C19 genotype and the steady-state plasma concentration of escitalopram in patients with Major Depressive Disorder (MDD) in the South Indian population.

A substantial correlation was identified between CYP2C19 allele polymorphisms and escitalopram steady-state plasma levels in each dose. The escitalopram concentration in the plasma at steady state in patients given 5, 10, 15, or 20 mg was not significantly different, perhaps due to its considerable variability. This confirms earlier research (Rudberg et al. 2006; Noehr-Jensen et al. 2009; Tsai et al. 2010; Tsuchimine et al. 2018). Thus, CYP2C19 genotypes affect escitalopram steady-state plasma levels in MDD patients.

The prevalence of PMs among South Indians is 14%, greater than Caucasians (Goldstein et al. 1997) and Africans (Herrlin et al. 1998), but equivalent to Asians at 12–23%. North Indians had 11% PM frequency and South Indians 14% (Lamba et al. 1998). We observed 17.4% of CYP2C19 PM frequency, which affected steady state plasma concentration of escitalopram considerably. Patients aged 40 years and older who are CYP2C19 poor metabolizers (PMs) showed a 1.4-fold increase in the average concentration/dose ratio of escitalopram compared to patients aged 25 years. However, this difference did not attain statistical significance (P = 0.1).

No differences were identified across CYP2C19 genotypes at each dose, contrary to our prediction. An in vitro investigation found that both CYP2C19 and CYP3A4 are engaged in escitalopram N-demethylation. It has been demonstrated that CYP3A4 activity varies greatly across individuals and may have altered escitalopram plasma concentrations (Lamba et al. 2002). Others include deamination and dehydrogenation to a propionic acid derivative, N-oxidation, and glucuronide conjugations (Oyehaug et al. 1984; Rochat et al. 1995). These small metabolic pathways may have been triggered after repeated dosages and confounded the results. Compliance, drug-drug and drug-food interactions, and renal and hepatic impairment affected steady-state plasma levels in repeated doses.

For individuals above 50 years, there was a statistically significant correlation between escitalopram‘s steady-state plasma levels and age. Although this is an interesting finding, it is in line with what one would expect from a decline in renal function with age. Previous research demonstrated that citalopram‘s oral and renal clearance were around 15% and 40% lower than in healthy volunteers, respectively, and that the t1/2 of a single dose increased by about 35% in patients with minimal to moderate renal failure [Creatinine Clearance ranges from 10–53 mL/min] (Rao N 2007). Thus, both CYP2C19 PM and elderly patients require cautious dose initiation and, potentially, therapeutic medication monitoring. Patients aged 65 compared to 40 years old had statistically significant variations in mean concentration/dose ratios of escitalopram in the other CYP2C19 phenotypic categories (P < 0.02) (Waade et al. 2014).

This study found a strong relationship between metabolite ratio and CYP2C19 and sex. A study by Waade et al. (2014) found that women had 15% lower metabolic ratios than men, may-be due to the varied CYP3A4 activity across the sexes, which is a significant enzyme that demethylates escitalopram (Diczfalusy U et al. 2008). CYP2C19 PM genotype may be a risk factor for MDD in the female population due to physiological, hormonal and emotional differences. A study by Tomonori Akasaka et al. found that CYP2C19 PM genotype is a novel potential hazard component for Coronary microvascular disorder in the females (Tomonori Akasaka et al. 2016). Our study has various constraints. Initially, our sample size was limited, consisting of a small cohort of patients with PM. Additional factors encompass ambiguous or unverified data concerning partial compliance and the simultaneous utilization of possibly interfering medications or herbal substances.

Conclusion

This study offers conclusive evidence regarding the genetic influence of CYP2C19 on the response to escitalopram in patients with MDD from South India population. However, it remains uncertain whether the prognostic data related to CYP2C19 genotypes can be utilized to personalize and optimize therapeutic regimens for preventing future episodes of depression. The study also provides further evidence that sex and CYP2C19 genotypes have a role in the determination of dose-adjusted escitalopram concentrations. Patients with CYP2C19 PM should be given the medication with special consideration.

Abbreviations

MDD Major Depressive Disorder

DSM Diagnostic and Statistical Manual of Mental Disorders

CYP2C19 Cytochrome P450 2C19

OTC Over-The-Counter

WHO World Health Organization

EDTA Ethylenediaminetetraacetic acid

PCR Polymerase Chain Reaction

BMI Body Mass Index

EM Extensive Metabolizer

IM Intermediate Metabolizer

PM Poor Metabolizers

UM Ultra Rapid Metabolizers

Grants

No funds received from any organization or person.

Conflict of Interest

The authors declare that there is no conflict of interest regarding the publication of this article.

Acknowledgements

The authors would like to express their gratitude to all of their colleagues who were instrumental in the study‘s data collection and management efforts.

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Supplementary material

Supplementary material 1 

Institutional Ethics Committee vide No.1299.

B. Jeevan Kumar, Vijayakumar Thangavel Mahalingam, Ganesh Kumar M

Data type: png

Explanation note: The study was approved by the Institute Ethics Committee (Sri Venkateswara Institute of Medical Sciences (SVIMS), Tirupati) vide No.1299. Written informed consent to participate in this study was obtained from all the patients.

This dataset is made available under the Open Database License (http://opendatacommons.org/licenses/odbl/1.0). The Open Database License (ODbL) is a license agreement intended to allow users to freely share, modify, and use this Dataset while maintaining this same freedom for others, provided that the original source and author(s) are credited.
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