Abstract This study investigated the allele frequencies of UGT1A1, ABCG2, NR1I2, and SLC22A2 in Thai people living with HIV (PLWH) and compared the allele frequencies with those of other populations. Four single nucleotide polymorphisms (SNPs); UGT1A1*6 221G>A, ABCG2 421C>A, NR1I2 63396C>T, and SLC22A2 808G>T were genotyped using Taq_Man allelic discrimination assays with a real time polymerase chain reaction system. The genotyping of (TA)n repeat polymorphisms, including UGT1A1*28 (TA7), *36 (TA5), and *37 (TA8), was performed by Sanger DNA sequencing. The Chi-square test was used to evaluate the distribution of observed genotypes according to Hardy-Weinberg equilibrium and to compare genetic polymorphisms between populations. A total of 266 PLWH with 266 blood samples were included in this study. The frequencies of the homozygous variants of UGT1A1*6 221G>A, ABCG2 421C>A, NR1I2 63396C>T, and SLC22A2 808G>T were 0.38%, 6.77%, 34.59%, and 4.14%, respectively. UGT1A1*1/*1 (TA6/TA6) was the most frequent genotype (74.6%) among the (TA)_n repeat polymorphisms. The frequencies of UGT1A1*6 221G>A, ABCG2 421C>A, and NR1I2 63396C>T observed in this study were consistent with previous studies in the Thai population. However, these polymorphisms, including SLC22A2 808G>T, show significant deviation from those observed in Caucasian populations.

This study provides evidence that can inform future clinical research on the impact of these polymorphisms on the pharmacokinetics of substrate drugs, which may impact variability in drug responses and safety.

Keywords: UGT1A1, ABCG2, NR1I2, SLC22A2, Polymorphisms, Allele frequencies

Funding: This research project is supported by National Research Council of Thailand (Contact No N41A640208 and NRCT5-RSA63004-13) and the Health Systems Research Institute in the code of HSRI 63-106, 63-020, 65-030 and Chiang Mai University.

Citation: Chanruang, A., Jayadhira, D., Chupradit, S., Sirilun, S., Avihingsanon, A., and  Punyawudho, B. 2025. Genetic polymorphisms of UGT1A1, ABCG2, NR1I2 and SLC22A2 in Thai people living with HIV: Comparative analysis with other populations. Natural and Life Sciences Communications. 24(2): e2025024.

INTRODUCTION

Genetic polymorphisms in drug metabolizing enzymes and drug transporters significantly influence the variation of a drug's pharmacokinetics. Drug metabolism primarily involves Phase I and Phase II enzymes.  Phase I metabolism is largely mediated by cytochrome P (CYP) 450 enzymes, while Phase II includes glucuronidation, sulfation, and acetylation (Zhao et al. 2021).

Uridine diphosphate glucuronosyl transferase (UGT) is a principal phase II metabolism enzyme and responsible for glucuronidation of a diverse range of xenobiotics and endogenous compounds in humans including bilirubin. Currently, there are 4 families of UGT: UGT1, UGT2, UGT3, and UGT8 (Mackenzie et al. 2005). The UGT1A1 enzyme plays a crucial role in the metabolism of several drugs, including irinotecan, acetaminophen, carvedilol, atazanavir, lamotrigine, simvastatin, and dolutegravir (Marques and Ikediobi 2010). Genetic polymorphisms in UGT1A1 have been linked to variation in drug concentrations, treatment outcomes, safety (Marques and Ikediobi 2010; Atasilp et al. 2016; Elliot et al. 2020; Atasilp et al. 2022). Additionally, the genetic polymorphism of UGT1A1 is also associated with total bilirubin level as it is a conjugating enzyme of bilirubin (Marques and Ikediobi 2010). Over 30 genetic variations in the promoter region and exon 1 of UGT1A1 have been documented to reduce enzyme activities and have been linked to disorders such as Criegler-Najjar (CN) and Gilbert syndrome (Farheen et al. 2006; Mackenzie et al. 2005). These UGT1A1 polymorphisms are characterized by the presence of thymine-adenine (TA)n insertions or deletions in the wild-type sequence A(TA)6TAA of the TATA box promoter in the UGT1A1 gene (Gammal et al. 2016). The UGT1A1*1 (TA6) variant has normal enzyme activity, while the UGT1A1*36 (TA5) variant results in increased UGT1A1 enzyme activity. Conversely, the UGT1A1*28 (TA7) and UGT1A1*37 (TA8) decrease their activity (Gammal et al. 2016). Another significant variant, UGT1A1*6 221G>A, has also been linked to reduced enzyme's activity (Gammal et al. 2016). These genetic polymorphisms exhibit variability across different ethnic groups, affecting drug concentrations and the potential for toxicities.

Drug transporters, essential for the transport of drugs across biological membranes, belong to two major transporter superfamilies: ATP-binding cassette (ABC) and solute carriers (SLC) transporters (Nigam 2015). The ABC superfamily includes multidrug resistance protein-1 (ABCB1/MDR1) or P-glycoprotein (P-gp), multidrug resistance-associated proteins (MRP), and breast cancer resistance protein (BCRP) (Shugarts and Benet 2009; Gong and Kim 2013). Genetic variation of these transporters can impact drug disposition and treatment responses (Shugarts and Benet 2009).

The BCRP, encoded by the ABCG2 gene, has a wide range of substrates, including exogenous substrates such as dolutegravir, irinotecan, doxorubicin, atorvastatin, gefitinib, apixaban, and rivaroxaban, as well as endogenous substrates such as urate and haem (de Jong et al. 2004; Mirošević Skvrce et al. 2015; Heyes et al. 2018; Elliot et al. 2020; Kim et al. 2023). A notable SNP in the nucleotide sequence of ABCG2 from C to A at position 421 (ABCG2 421C>A), which decreases ABCG2 expression and activity, leading to increased drug concentrations (Heyes et al. 2018). The ABCG2 421C>A variant is highly observed among Asians. However, data on the Thai population remains limited.

The pregnane X receptor (PXR), encoded by gene nuclear receptors (NR)1I, regulates both drug metabolizing enzymes, such as CYP3A and UGT, and drug transporters including P-gp, MRP2, and OATs (Zhang et al. 2008; Barraclough et al. 2012). Polymorphism in the NR1I2 gene affects the pharmacokinetics of various drugs such as tacrolimus, rosuvastatin, atazanavir, and efavirenz (Siccardi et al. 2008; Barraclough et al. 2012; Swart et al. 2012; Liu et al. 2016).

The influx solute-linked carrier (SLC) superfamily includes organic cation transporters (OCTs), organic anion transporters (OATs), and organic anion-transporting peptides (OATPs/SLCO). The SLC, particularly the SLC22 transporter, also plays a crucial role in drug pharmacokinetics. These transporters are predominantly expressed in the basolateral membrane of renal proximal tubule cells and influence the absorption, distribution, and elimination of drugs. (Gong and Kim 2013). Genetic variation in SLC22 has been linked to alterations in the pharmacokinetics of various drugs, such as acetylsalicylate, amantadine, cisplatin, lamivudine, memantine, metformin, oxaliplatin, quinine, and dolutegravir (Shugarts and Benet 2009; Li et al. 2010; Gong and Kim 2013; Wilson et al. 2017; Borghetti et al. 2019). However, evidence regarding the prevalence of SLC22A2 in the Thai population is sparse (John et al. 2024).

Antiretroviral (ARV) drugs show a high interindividual variability in drug exposure, affecting their safety and efficacy. This variability stems from both genetics and non-genetic factors, i.e., age, sex, body weight, and co-medications (Pavlos and Phillips 2012). The genetic variations of UGT1A1, ABCG2, NR1I2, and SLC22A2 have been shown to impact the exposure of various major ARV used in HIV treatment (Chen et al. 2014; Tsuchiya et al. 2014; Gammal et al. 2016; Tsuchiya et al. 2017; Belkhir et al. 2018; Borghetti et al. 2019;  Elliot et al. 2020). These genetic variants have been shown as associated with the pharmacokinetics and clinical outcomes of dolutegravir. Dolutegravir is now regarded as the first-line regimen for Thai PLWH. Previous study showed that the concurrent presence of UGT1A1*28 and NR1I2 63396 TT, or ABCG 421 AA and NR1I2 63396 TT, correlated with increased area under the curve (AUC) and maximum concentration (Cmax) of dolutegravir, respectively (Elliot et al. 2020). The study conducted by Borghetti et al. indicated that PLWH possessing the SLC22A2 CA genotype exhibited higher dolutegravir concentrations, which correlated with a considerably increased incidence of neuropsychiatric toxicities (Borghetti et al. 2019). Furthermore, genetic polymorphisms of UGT1A1, ABCG2, NR1I2, and SLC22A2 have been investigated in different ethnic groups of people living with HIV (PLWH) (Yagura et al. 2017; Borghetti et al. 2019).

Due to the lack of comprehensive data and the small sample sizes employed in previous studies (Chaikan et al. 2008; Avihingsanon et al. 2015), which limited generalizability and understated some of the rare genetic polymorphisms in population, such as UGT1A1*36 (TA5) or *37 (TA8), which have never been found in Thai populations, further study is necessary given the limited understanding of these genetic variations in Thai PLWH. The diversity of these genetic variants among ethnic groups may elucidate some of the variability in the pharmacokinetics and treatment outcomes of dolutegravir among diverse populations, Therefore, this study aimed to investigate the allele frequencies of UGT1A1, ABCG2, NR1I2, and SLC22A2 in a large sample of Thai people living with HIV (PLWH) and compare them with other populations.

MATERIAL AND METHODS

Patients and blood samples

This cross-sectional descriptive study was performed in Thai PLWH at the HIV Netherland Australia Thailand collaboration (HIV-NAT), Thai Red Cross AIDS Research Centre in Bangkok, Thailand. A total of 266 PLWH aged > 18 years were recruited after obtaining informed consent. The study was approved by the Institutional Review Board of the Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand, and the Institutional Review Board Committee on Human Research at the Faculty of Pharmacy, Chiang Mai University, Chiang Mai, Thailand. At the beginning of the study, a single blood sample was collected from each participant, along with their baseline characteristic information. Peripheral blood mononuclear cells (PBMCs) were extracted and stored at -20°C until analysis.

Genotyping analysis

Genotyping of UGT1A1*28 (TA7), *36 (TA5), and *37 (TA8) polymorphism, characterized by variation in the number of (TA)n repeats in the UGT1A1 promoter region, was performed using polymerase chain reaction (PCR) with a forward primer (5’- AAA TTC CAG CCA GTT CAA CTG TTG TT-3’) and a reverse primer (5’-CTG CTG GAT GGC CCC AAG-3’). The PCR reaction, with a total volume of 50 μl, contained 25 ng of template genomic DNA, 25 μl of DreamTaq PCR Master Mix (2X) (consisting of DreamTaq buffer, dATP, dCTP, dGTP, and dTTP, 0.4 mM each, and 4 mM MgCl₂), and 0.4 mM of each primer. Amplification was carried out in a T960 PCR thermal cycle (Drawell) for 34 cycles, with denaturation at 94°C for 45 seconds, annealing at 62°C for 45 seconds, and extension at 72°C for 60 seconds. The initial denaturation was set at 94°C for 2 minutes, followed by a final extension at 72°C for 1 minute (Babaoglu et al. 2006). PCR products were sequenced by Sanger DNA sequencing and the number of (TA)n repeats in the UGT1A1 promoter were determined by Sequence Scanner Software v2.0 (Thermo Fisher Scientific, USA).

Genotyping of UGT1A1*6 211 G>A, ABCG2 421 C>A, NR1I2 63396 C>T, and SLC22A2 808 G>T was determined by TaqMan allelic discrimination assay on a QuantStudio7 Flex Real-Time PCR System (Applied Biosystems Inc., USA), according to the manufacturer’s standard protocol. The real-time PCR conditions included an initial step at 95°C for 10 minutes, followed by 40 cycles at 95°C for 15 second and 60°C for 1 minute. Each reaction was performed in a total volume of 10 μl, containing 5 μl of TaqMan Genotyping Master Mix(2x), 0.5 μl of SNP assay, and 4.5 μl (10 ng) of template genomic DNA. The allele probes for each SNP are listed in Table 1.

Table 1. Specific allele probes for the detection of genetic polymorphisms.

Statistical analysis

Statistical analysis was performed using STATA version 14.0 (StataCorp LP, USA) software. To ascertain an adequate sample size for detecting rare alleles in this study, the allele frequency proportions from the prior Thai population and other ethnic groups were utilized to calculate the sample size using the following equation (Wang and Chow 2007):

              n = (Z_α/2+Z_β)² * (p₁(1-p₁) + p₂(1-p₂)) / (p₁-p₂)²

Where Z_α/2 is 1.96 for a confidence level of 95% and α is 0.05, Z_β is 0.84 for a power of 80% and β is 0.2, and p₁ and p₂ are the sample proportions of Thai and other ethnicities. Considering the reported frequency of rare alleles in Thai and other ethnic groups (Innocenti et al. 2002; de Jong et al. 2004; Svärd et al. 2010; , Borghetti et al. 2019; Singkham et al. 2019; Rattanacheeworn et al. 2020; Atasilp et al. 2022;  John et al. 2024) the minimal sample sizes necessary to detect differences across populations for each genetic polymorphism—UGT1A1 (TA)n repeat, UGT1A1*6 221G>A, ABCG2 421C>A, NR1I2 63396C>T, and SLC22A2 808G>T—were 77, 110, 47, 71, and 389, respectively.

Patients' characteristics were summarized as frequencies (percentages) for categorical data and as median with interquartile range (IQR) for continuous data. The allele frequencies of UGT1A1, ABCG2, NR1I2, and SLC22A2 polymorphisms were computed. The distribution of the observed genotype according to Hardy-Weinberg equilibrium was assessed by the chi-square test. Genotypes were categorized into three groups: wild type (two copies of the common allele), heterozygous (one copy of the variant allele), and homozygous variant (two copies of the variant allele). Additionally, UGT1A1 phenotype were classified into three groups based on genotypes according to the Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines: extensive metabolizer (*1/*1, *1/*36), intermediate metabolizer (*1/*28, *1/*6), and poor metabolizer (*28/*28, *28/*37, *6/*6) (Gammal et al. 2016).

The allele frequencies of each genotype in Thai population were compared with those of other ethnicities, including Asians (Japanese and Chinese), Caucasians, and African Americans, using the chi-square test. A P-value of less than 0.05 was considered statistically significant.

RESULTS

Demographic data

A total of 266 blood samples from 266 PLWH were genotyped. The demographic data are summarized in Table 2. The allele frequencies of UGT1A1*6 211 G>A, ABCG2 421 C>A, NR1I2 63396 C>T, and SLC22A2 808 G>T are shown in Table 3. All SNPs were in Hardy-Weinberg equilibrium, except SLC22A2 808 G>T. The allele frequencies of UGT1A1*28 (TA7), *36 (TA5), and *37 (TA8) are presented in Figure 1, with UGT1A1*1/*1 (TA6/TA6) being the most prevalent genotype at 74.06%, representing the wild type. The frequencies of UGT1A1 extensive, intermediate, and poor metabolizers based on CPIC guideline were 165 (62.03%), 75 (28.20%), and 26 (9.77%) PLWH, respectively. Comparisons of allele frequencies between the Thai PLWH and other ethnicities are presented in Tables 4 and 5. When comparing the allele frequencies of (TA)n repeats in the UGT1A1 promoter region, specifically *36 (TA5), *1 (TA6), *28 (TA7), and *37 (TA8), among various populations, it was found that the frequencies of these alleles in this study were similar to previous reports in Thai and Japanese populations but differed from those in Caucasian and African American populations. The allele frequency of UGT1A1*6 was 7.33%, consistent with previously reported frequencies in the Thai population (7.95%) (Atasilp et al. 2016). However, this frequency was lower than the 13.0% reported in another Thai study (Atasilp et al. 2022). Furthermore, the UGT1A1*6 allele frequency observed in our study was significantly lower than in Japanese (7.33% vs. 77.83% and 86.31%, P <0.01) and African Americans population (7.33% vs. 28.38%, P <0.01) (Akiyama et al. 2008; Yagura et al. 2017; Innocenti et al. 2002).

The frequency of the ABCG2 421 C>A variant allele was 25.75%, similar to previous findings in Thai and Japanese populations (Rattanacheeworn et al. 2020; Yamagishi et al. 2010). Nevertheless, this frequency was higher than those reported in African Americans (25.75% vs. 5.30%, P <0.01) and both American and European Caucasian (25.75% vs. 12.00% and 11.00%, P <0.01) (de Jong et al. 2004). The NR1I2 variant T allele frequency was 59.21%, aligning with earlier findings in both Thai and Caucasian populations (Singkham et al. 2019; Svärd et al. 2010). However, this frequency was slightly higher than that observed in Sub-Saharan Africans (59.21% vs. 38.10%, P <0.01) but lower than in the Japanese population (59.21% vs. 72.44%, p = 0.024) (Svärd et al. 2010; Nishijima et al. 2014). The variant T allele frequency for SLC22A2 808G>T was 16.01%, which is comparable to the frequencies observed in the previous Thai and Chinese Han population (16.01% vs. 13.00% and 12.90%, P > 0.05) but significantly different from those in Caucasians (16.01% vs. 7.67%, P = 0.007) (John et al. 2024; Borghetti et al. 2019; Li et al. 2010).

Table 2. Demographic characteristics of study participants (n = 266).

Table 3. The frequencies of genetic polymorphisms.

  Note:  †Obtained using Chi-Square test

Figure 1. The frequencies of UGT1A1 (TA5-8) repeat in promoter region.

Table 4. Comparison of allele frequencies among different population.

Note: †Obtained using Chi-Square test

Table 5. Comparison of allele frequencies of UGT1A1 (TA)_n repeats in promoter region among different population.

Note: †Obtained using Chi-Square test

DISCUSSION

Genetic polymorphisms of drug metabolism enzymes and transporters vary significantly across populations, which can affect the way drugs undergo metabolism and their potential for toxicity. Our study investigated the genetic polymorphisms of UGT1A1, ABCG2, NR1I2, and SLC22A2 in a large sample of Thai PLWH. The results showed that the allele frequencies of UGT1A1, ABCG2, and NR1I2 conformed to Hardy-Weinberg equilibrium, while SLC22A2 808G>T did not. Several factors could explain the deviation from Hardy-Weinberg equilibrium, including ethnic admixture, inbreeding, population stratification, genotyping errors, and random chance (Li and Leal 2009). While we lack data on the participants' ethnic backgrounds, we hypothesize that ethnic admixture, which frequently occurs in this diverse world, may contribute to Hardy-Weinberg disequilibrium. Another potential explanation may be population stratification (selection bias), as the participants in our study indicated a selected rather than a random sampling.

The frequency of the UGT1A1*6 variant allele in this Thai cohort was consistent with previous studies (Atasilp et al. 2016; Atasilp et al. 2022). However, this frequency was significantly lower than those reported in Japanese and African-American populations (Innocenti et al. 2002; Akiyama et al. 2008; Yagura et al. 2017). In contrast, the frequencies of UGT1A1*36 (TA5), UGT1A1*28 (TA7), and UGT1A1*37 (TA8) were consistent with prior reports from Thai and Japanese populations (Atasilp et al. 2022; Premawardhena et al. 2003; Yagura et al. 2017), suggesting similar (TA)n repeat patterns in the promoter region among Asians. Yet, the frequencies in the Thai population were significantly different from Caucasian and African-American (Innocenti et al. 2002). Notably, UGT1A1*36 (TA5) and UGT1A1*37 (TA8) were detected in this study, which had not been previously reported in Thai and Japanese populations, possibly due to the larger sample size in our investigation.

Intermediate and poor metabolizers of UGT1A1 have been shown to reduce the metabolism of certain antiretrovirals (ARVs), such as atazanavir and dolutegravir, leading to higher drug exposures (Yagura et al. 2017; Elliot et al. 2020; Kane 2023) and increased risk of toxicities. Previous studies have shown that UGT1A1 intermediate and poor metabolizers are at higher risk of developing hyperbilirubinemia when taking atazanavir, potentially leading to the need to discontinue the drug (Babaoglu et al. 2006; Ribaudo et al. 2013; Gammal et al. 2016; Liu et al. 2022). Moreover, poor metabolizers for UGT1A1 may have an increased risk of neuropsychiatric adverse events with dolutegravir (Yagura et al. 2017). Our study found that approximately 28% and 10% of PLWH were classified as intermediate and poor metabolizers for UGT1A1 based on CPIC guidelines, indicating a need for careful monitoring of toxicities when atazanavir or dolutegravir is administered to this group.

ABCG2 is a key efflux transporter, and the presence of the homozygous variant of ABCG2 decreases efflux activity, potentially altering drug pharmacokinetics, including those of ARVs. Previous research has demonstrated that the ABCG2 421 C>A polymorphism affects the raltegravir concentrations in cerebrospinal fluid (CSF), which is particularly important for PLWH with encephalitis (Tsuchiya et al. 2014). Additionally, dolutegravir plasma concentrations were significantly higher in PLWH with the ABCG2 AA genotype compared to those with CC and CA genotypes (Tsuchiya et al. 2017: Elliot et al. 2020), though other studies have found no such correlation (Zhu et al. 2020). Therefore, further research is needed to clarify the impact of ABCG2 polymorphisms on the pharmacokinetics of ARVs. In addition, multiple reports have shown that different genetic variations of ABCG2 are related to the safety and efficacy of non-antiretroviral (ARV) medications, including resistance to anticancer treatments, dose-dependent adverse drug reactions (ADRs) of atorvastatin, and significant bleeding complications with apixaban or rivaroxaban (Mo and Zhang 2012; Mirošević Skvrce et al. 2015; Kim et al. 2023). Our study found that the frequency of the ABCG2 421 variant A allele in Thai PLWH was significantly higher than that of African Americans and Caucasians (de Jong et al. 2004; Rattanacheeworn et al. 2020). This suggests that ABCG2 421 C>A polymorphism may have a more prominent impact on drug pharmacokinetics and clinical outcomes in the Thai population, warranting further investigation.

Our research also revealed that the prevalence of the NR1I2 63396 variant T allele in our population was similar to that in Caucasians but differed significantly from African and Japanese populations. The influence of NR1I2 63396 C>T may therefore vary across populations. Previous studies have shown that individuals with the NR1I2 63396 TT genotype exhibit significantly reduced atazanavir concentrations, leading to subtherapeutic levels (Siccardi et al. 2008; Schipani et al. 2010). This could be due to the T allele’s association with increased expression of PXR and enhanced CYP3A4 activity, resulting in increased drug metabolism (Lamba et al. 2008; Schipani et al. 2010). However, research on Thai PLWH did not find any influence of the NR1I2 63396 C>T polymorphism on the pharmacokinetics of atazanavir (Singkham et al. 2019). Surprisingly, Elliot et al. discovered that the NR1I2 63396 C>T variation increases dolutegravir concentration (Elliot et al. 2020). This suggests that the impact of the NR1I2 63396 C>T polymorphism on drug pharmacokinetics may vary depending on the specific substrates and ethnic groups.

Furthermore, we discovered that there was no significant difference in the allele frequency of SLC22A2 between the Chinese Han and Thai populations compared to earlier studies (John et al. 2024; Li et al. 2010). However, the prevalence of the SLC22A2 808 TT genotype was found to be significantly higher than in Caucasians (Borghetti et al. 201). Genetic variations in SLC22A2 808 G>T have been linked to an increased risk of dolutegravir-induced neuropsychiatric side effects, potentially making Thai PLWH more susceptible. However, the SLC22A2 808 G>T polymorphism's effect on the pharmacokinetics and toxicities of dolutegravir in the Thai population has not yet been studied and needs more investigation.

The genetic polymorphisms of UGT1A1, ABCG2, NR1I2, and SLC22A2 were identified as being linked with the pharmacokinetics of dolutegravir. Moreover, the polymorphisms of UGT1A1 were demonstrated to be associated with atazanavir-induced hyperbilirubinemia. (Ribaudo et al. 2013; Avihingsanon et al. 2015; Gammal et al. 2016). Consequently, the frequency of these genes reported in this study may provide preliminary data for potential dose modification. For instance, 9.2% were identified as poor metabolizers for UGT1A1. These patients may possess a higher probability of experiencing toxicities, neuropsychiatric side effects associated with dolutegravir, and hyperbilirubinemia linked to atazanavir. Therefore, dose reduction may be required in this group.

This study possesses limitations. The study focused on determining genotype and allele frequencies and comparing them among different ethnic groups. The influence of these genetic variants on the pharmacokinetics of the drug or clinical outcomes was not examined. Furthermore, while the sample size was sufficient for identifying rare alleles for most polymorphisms, it may be inadequate for detecting rare alleles in SLC22A2. However, the allele frequencies of SLC22A2 identified in our study were similar to those reported in prior research within the Thai population (John et al. 2024).

In conclusion, this study examined the genetic polymorphisms of UGT1A1, ABCG2, NR1I2, and SLC22A2 in Thai PLWH. The importance of genetic polymorphisms findings from this study could serve as evidence for future clinical research investigating variations in treatment responses and safety, as well as their effects on the pharmacokinetics of substrate drugs. Furthermore, these may provide as evidence for pharmacogenetic-based dose recommendations of ARV drugs.

CONCLUSION

This study examined the genetic polymorphisms of UGT1A1, ABCG2, NR1I2, and SLC22A2 in Thai PLWH. Significant genetic variations were found between Thai and other ethnicities. These findings could serve as evidence for future clinical research exploring variations in treatment responses and safety, as well as their effects on the pharmacokinetics of substrate drugs.

ACKNOWLEDGEMENTS

The authors thank all participants and HIV-NAT staff.

AUTHOR CONTRIBUTIONS

Anan Chanruang performed the research, genotyped, analyzed the data, and wrote the manuscript. Dhiravara Jayadhira performed the research, analyzed the data, and wrote the manuscript. Suthunya Chupradit performed the research, genotyped, and analyzed the data. Anchalee Avihingsanon designed the research, performed the research and wrote the manuscript. Sasithorn Sirilun performed the research, genotyped, and wrote the manuscript. Baralee punyawudho designed the research and evaluation of experiments, performed the research, analyzed the data, and wrote the manuscript. All the authors have read and approved the final manuscript.

CONFLICT OF INTEREST

The authors declare that they hold no competing interests.

REFERENCES

Akiyama, Y., Fujita, K., Nagashima, F., Yamamoto, W., Endo, H., Sunakawa, Y., Yamashita, K., Ishida, H., Mizuno, K., Araki, K., et al. 2008. Genetic testing for UGT1A1*28 and *6 in Japanese patients who receive irinotecan chemotherapy. Annals of Oncology. 19(12): 2089–2090.

Atasilp, C., Chansriwong, P., Sirachainan, E., Reungwetwattana, T., Chamnanphon, M., Puangpetch, A., Wongwaisayawan, S., and Sukasem, C. 2016. Correlation of UGT1A1*28 and *6 polymorphisms with irinotecan-induced neutropenia in Thai colorectal cancer patients. Drug Metabolism and Pharmacokinetics. 31: 90-94.

Atasilp, C., Kanjanapipak, J., Vichayaprasertkul, J., Jinda, P., Tiyasirichokchai, R., Srisawasdi, P., Prempunpong, C., Chamnanphon, M., Puangpetch, A., Vanwong, N., et al. 2022. Associations between UGT1A1 and SLCO1B1 polymorphisms and susceptibility to neonatal hyperbilirubinemia in Thai population. BMC Pediatrics. 22(1): 243.

Avihingsanon, A., Tongkobpetch, S., Kerr, S. J., Punyawudho, B., Suphapeetiporn, K., Gorowara, M., Ruxrungtham, K., and Shotelersuk, V. 2015. Pharmacogenetic testing can identify patients taking Atazanavir at risk for hyperbilirubinemia. Journal of Acquired Immune Deficiency Syndromes. 69: e36-e37.

Babaoglu, M. O., Yigit, S., Aynacioglu, A. S., Kerb, R., Yurdakok, M., and Bozkurt, A. 2006. Neonatal jaundice and bilirubin UDP-glucuronosyl transferase 1A1 gene polymorphism in Turkish patients. Basic & Clinical Pharmacology & Toxicology. 98(4): 377-380.

Barraclough, K. A., Isbel, N. M., Lee, K. J., Bergmann, T. K., Johnson, D. W., McWhinney, B. C., Ungerer, J. P., Campbell, S. B., Leary, D. R., Bialasiewicz, S., et al. 2012. NR1I2 polymorphisms are related to tacrolimus dose-adjusted exposure and BK viremia in adult kidney transplantation. Transplantation. 94(10): 1025-1032.

Belkhir, L., Seguin-Devaux, C., Elens, L., Pauly, C., Gengler, N., Schneider, S., Ruelle, J., Haufroid, V., and Vandercam, B. 2018. Impact of UGT1A1 polymorphisms on Raltegravir and its glucuronide plasma concentrations in a cohort of HIV-1 infected patients. Scientific Reports. 8(1): 7359.

Borghetti, A., Calcagno, A., Lombardi, F., Cusato, J., Belmonti, S., D'Avolio, A., Ciccarelli, N., La Monica, S., Colafigli, M., Delle Donne, V., et al. 2019. SLC22A2 variants and dolutegravir levels correlate with psychiatric symptoms in persons with HIV. The Journal of Antimicrobial Chemotherapy. 74(4): 1035-1043.

Chaikan, A., Chierakul, N., Saguenwong, N., Chuchuttaworn, C., Owen, A., Dickinson, L., Khoo, S. H., Back, D. J., and Davies, G. R. 2008. Frequency of functional drug disposition gene polymorphism in Thai population: Relevance to antiretroviral drugs. Journal of the International AIDS Society. 11: P237.

Chen, S., St Jean, P., Borland, J., Song, I., Yeo, A. J., Piscitelli, S., and Rubio, J. P. 2014. Evaluation of the effect of UGT1A1 polymorphisms on dolutegravir pharmacokinetics. Pharmacogenomics. 15(1): 9-16.

de Jong, F. A., Marsh, S., Mathijssen, R. H., King, C., Verweij, J., Sparreboom, A., and McLeod, H. L. 2004. ABCG2 pharmacogenetics: Ethnic differences in allele frequency and assessment of influence on irinotecan disposition. Clinical Cancer Research. 10(17): 5889–5894.

Elliot, E. R., Neary, M., Else, L., Khoo, S., Moyle, G., Carr, D. F., Wang, X., McClure, M., Boffito, M., and Owen, A. 2020. Genetic influence of ABCG2, UGT1A1 and NR1I2 on dolutegravir plasma pharmacokinetics. The Journal of Antimicrobial Chemotherapy. 75(5): 1259-1266.

Farheen, S., Sengupta, S., Santra, A., Pal, S., Dhali, G. K., Chakravorty, M., Majumder, P. P., and Chowdhury, A. 2006. Gilbert's syndrome: High frequency of the (TA)7 TAA allele in India and its interaction with a novel CAT insertion in promoter of the gene for bilirubin UDP-glucuronosyltransferase 1 gene. World Journal of Gastroenterology, 12(14): 2269-2275.

Gammal, R. S., Court, M. H., Haidar, C. E., Iwuchukwu, O. F., Gaur, A. H., Alvarellos, M., Guillemette, C., Lennox, J. L., Whirl-Carrillo, M., Brummel, S. S., et al. 2016. Clinical pharmacogenetics implementation consortium (CPIC) guideline for UGT1A1 and atazanavir prescribing. Clinical Pharmacology and Therapeutics. 99(4): 363-369.

Gong, I. Y. and Kim, R. B. 2013. Impact of genetic variation in OATP transporters to drug disposition and response. Drug Metabolism and Pharmacokinetics. 28(1): 4-18.

Heyes, N., Kapoor, P., and Kerr, I. D. 2018. Polymorphisms of the multidrug pump ABCG2: A systematic review of their effect on protein expression, function, and drug pharmacokinetics. Drug Metabolism and Disposition: The Biological Fate of Chemicals, 46(12): 1886-1899.

Innocenti, F., Grimsley, C., Das, S., Ramírez, J., Cheng, C., Kuttab-Boulos, H., Ratain, M. J., and Di Rienzo, A. 2002. Haplotype structure of the UDP-glucuronosyltransferase 1A1 promoter in different ethnic groups. Pharmacogenetics. 12(9): 725-733.

John, S., Klumsathian, S., Own-eium, P., Charoenyingwattana, A., Eu-ahsunthornwattana, J., Sura, T., Dejsuphong, D., Sritara, P., Vathesatogkit, P., Thongchompoo, N., et al. 2024. Thai pharmacogenomics database −2 (TPGxD-2) sequel to TPGxD-1, analyzing genetic variants in 26 non-VIPGx genes within the Thai population. Clinical and Translational Science. 17: e70019.

Kane, M. 2023. Atazanavir therapy and UGT1A1 genotype. In V.M. Pratt, S.A. Scott, M. Pirmohamed, B. Esquivel, B.L. Kattman, and A.J. Malheiro (eds) Medical Genetics Summaries [Internet] National Center for Biotechnology Information, United State.

Kim, H., Song, T. J., Yee, J., Kim, D. H., Park, J., and Gwak, H. S. 2023. ABCG2 gene polymorphisms may affect the bleeding risk in patients on Apixaban And Rivaroxaban. Drug Design, Development and Therapy. 17: 2513-2522.

Lamba, J., Lamba, V., Strom, S., Venkataramanan, R., and Schuetz, E. 2008. Novel single nucleotide polymorphisms in the promoter and intron 1 of human pregnane X receptor/NR1I2 and their association with CYP3A4 expression. Drug Metabolism and Disposition: The Biological Fate of Chemicals. 36(1): 169–181.

Li, B., and Leal, S. M. 2009. Deviations from hardy-weinberg equilibrium in parental and unaffected sibling genotype data. Human Heredity, 67(2), 104–115.

Li, Q., Liu, F., Zheng, T. S., Tang, J. L., Lu, H. J., and Jia, W. P. 2010. SLC22A2 gene 808 G/T variant is related to plasma lactate concentration in Chinese type 2 diabetics treated with metformin. Acta Pharmacologica Sinica. 31(2): 184-190.

Liu, D., Yu, Q., Ning, Q., Liu, Z., and Song, J. 2022. The relationship between UGT1A1 gene & various diseases and prevention strategies. Drug Metabolism Reviews. 54(1): 1-21.

Liu, M., Wu, X. J., Zhao, G. L., Zhang, T., Xu, S. S., Sun, Y. X., Qiu, F., and Zhao, L. M. 2016. Effects of polymorphisms in NR1H4, NR1I2, SLCO1B1, and ABCG2 on the pharmacokinetics of Rosuvastatin in healthy Chinese volunteers. Journal of Cardiovascular Pharmacology. 68(5): 383-390.

Mackenzie, P. I., Bock, K. W., Burchell, B., Guillemette, C., Ikushiro, S., Iyanagi, T., Miners, J. O., Owens, I. S., and Nebert, D. W. 2005. Nomenclature update for the mammalian UDP glycosyltransferase (UGT) gene superfamily. Pharmacogenetics and Genomics. 15(10): 677-685.

Marques, S. C., and Ikediobi, O. N. 2010. The clinical application of UGT1A1 pharmacogenetic testing: Gene-environment interactions. Human Genomics. 4(4): 238-249.

Mirošević Skvrce, N., Macolić Šarinić, V., Šimić, I., Ganoci, L., Muačević Katanec, D., and Božina, N. 2015. ABCG2 gene polymorphisms as risk factors for Atorvastatin adverse reactions: A case-control study. Pharmacogenomics. 16(8): 803-815.

Mo, W., and Zhang, J. T. 2012. Human ABCG2: Structure, function, and its role in multidrug resistance. International Journal of Biochemistry and Molecular Biology. 3(1): 1-27.

Nigam, S. K. 2015. What do drug transporters really do? Nature Reviews. Drug Discovery. 14(1): 29-44.

Nishijima, T., Tsuchiya, K., Tanaka, N., Joya, A., Hamada, Y., Mizushima, D., Aoki, T., Watanabe, K., Kinai, E., Honda, H., et al. 2014. Single-nucleotide polymorphisms in the UDP-glucuronosyltransferase 1A-3' untranslated region are associated with atazanavir-induced nephrolithiasis in patients with HIV-1 infection: A pharmacogenetic study. The Journal of Antimicrobial Chemotherapy. 69(12): 3320-3328.

Pavlos, R., and Phillips, E. J. 2012. Individualization of antiretroviral therapy. Pharmacogenomics and Personalized Medicine. 5: 1-17.

Premawardhena, A., Fisher, C. A., Liu, Y. T., Verma, I. C., de Silva, S., Arambepola, M., Clegg, J. B., and Weatherall, D. J. 2003. The global distribution of length polymorphisms of the promoters of the glucuronosyltransferase 1 gene (UGT1A1): Hematologic and evolutionary implications. Blood Cells, Molecules & Diseases. 31(1): 98-101.

Rattanacheeworn, P., Chamnanphon, M., Thongthip, S., Kittanamongkolchai, W., Townamchai, N., Avihingsanon, Y., Udomnilobol, U., Prueksaritanont, T., Jianmongkol, S., and Chariyavilaskul, P. 2020. SLCO1B1 and ABCG2 gene polymorphisms in a Thai population. Pharmacogenomics and Personalized Medicine. 13: 521-530.

Ribaudo, H. J., Daar, E. S., Tierney, C., Morse, G. D., Mollan, K., Sax, P. E., Fischl, M. A., Collier, A. C., and Haas, D. W. 2013. Impact of UGT1A1 Gilbert variant on discontinuation of ritonavir-boosted atazanavir in AIDS clinical trials group study A5202. Journal of Infectious Diseases. 207(3): 420-425.

Schipani, A., Siccardi, M., D'Avolio, A., Baietto, L., Simiele, M., Bonora, S., Rodríguez Novoa, S., Cuenca, L., Soriano, V., et al. 2010. Population pharmacokinetic modeling of the association between 63396C->T pregnane X receptor polymorphism and unboosted atazanavir clearance. Antimicrobial Agents and Chemotherapy. 54(12): 5242-5250.

Shugarts, S., and Benet, L. Z. 2009. The role of transporters in the pharmacokinetics of orally administered drugs. Pharmaceutical Research. 26(9): 2039-2054.

Siccardi, M., D'Avolio, A., Baietto, L., Gibbons, S., Sciandra, M., Colucci, D., Bonora, S., Khoo, S., Back, D. J., Di Perri, G., et al. 2008. Association of a single-nucleotide polymorphism in the pregnane X receptor (PXR 63396C-->T) with reduced concentrations of unboosted atazanavir. Clinical Infectious Diseases. 47(9): 1222-1225.

Singkham, N., Avihingsanon, A., Thammajaruk, N., Ruxrungtham, K., Bunupuradah, T., Kiertiburanakul, S., Chetchotisakd, P., Burger, D. M., Emery, S., and Punyawudho, B. 2019. Influence of CYP3A5 and SLCO1B1 polymorphisms on Atazanavir/r concentrations in Thai HIV-infected patients. Pharmacogenomics. 20(7): 517-527.

Svärd, J., Spiers, J. P., Mulcahy, F., and Hennessy, M. 2010. Nuclear receptor-mediated induction of CYP450 by antiretrovirals: Functional consequences of NR1I2 (PXR) polymorphisms and differential prevalence in whites and sub-Saharan Africans. Journal of Acquired Immune Deficiency Syndromes. 55(5): 536-549.

Swart, M., Whitehorn, H., Ren, Y., Smith, P., Ramesar, R. S., and Dandara, C. 2012. PXR and CAR single nucleotide polymorphisms influence plasma efavirenz levels in South African HIV/AIDS patients. BMC Medical Genetics. 13: 112.

Tsuchiya, K., Hayashida, T., Hamada, A., Kato, S., Oka, S., and Gatanaga, H. 2014. Low raltegravir concentration in cerebrospinal fluid in patients with ABCG2 genetic variants. Journal of Acquired Immune Deficiency Syndromes. 66(5): 484-486.

Tsuchiya, K., Hayashida, T., Hamada, A., Oki, S., Oka, S., and Gatanaga, H. 2017. High plasma concentrations of dolutegravir in patients with ABCG2 genetic variants. Pharmacogenetics and Genomics. 27(11): 416-419.

Wang, H. and Chow, S.C. 2007. Sample size calculation for comparing proportions. In R.B. D'Agostino, L. Sullivan and J. Massaro (eds) Wiley Encyclopedia of Clinical Trials. https://doi.org/10.1002/9780471462422.eoct005

Wilson, N. C., Choudhury, A., Carstens, N., and Mavri-Damelin, D. 2017. Organic cation transporter 2 (OCT2/SLC22A2) Gene variation in the south African Bantu-speaking population and functional promoter variants. Omics: A Journal of Integrative Biology. 21(3): 169-176.

Yagura, H., Watanabe, D., Kushida, H., Tomishima, K., Togami, H., Hirano, A., Takahashi, M., Hirota, K., Ikuma, M., Kasai, D., et al. 2017. Impact of UGT1A1 gene polymorphisms on plasma Dolutegravir trough concentrations and neuropsychiatric adverse events in Japanese individuals infected with HIV-1. BMC Infectious Diseases. 17(1): 622.

Yamagishi, K., Tanigawa, T., Kitamura, A., Köttgen, A., Folsom, A. R., and Iso, H. 2010. The rs2231142 variant of the ABCG2 gene is associated with uric acid levels and gout among Japanese people. Rheumatology (Oxford). 49(8): 1461-1465.

Zhang, B., Xie, W., and Krasowski, M. D. 2008. PXR: A xenobiotic receptor of diverse function implicated in pharmacogenetics. Pharmacogenomics. 9(11): 1695-1709.

Zhao, M., Ma, J., Li, M., Zhang, Y., Jiang, B., Zhao, X., Huai, C., Shen, L., Zhang, N., He, L., et al. 2021. Cytochrome P450 Enzymes and Drug Metabolism in Humans. International Journal of Molecular Sciences. 22(23): 12808.

Zhu, J., Tian, X., Shehu, A. I., McMahon, D. K., and Ma, X. 2020. ABCG2 Deficiency does not alter dolutegravir metabolism and pharmacokinetics. The Journal of Pharmacology and Experimental Therapeutics. 374(1): 38-43.

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