Skip to main content

Genetic polymorphism of organic cation transporter 2 (OCT2) and its effects on the pharmacokinetics and pharmacodynamics of Metformin: a narrative review

Abstract

Background

Organic cation transporter 2 (OCT2) is a renal carrier transporter protein found in the basolateral membrane of proximal epithelial cells, which facilitates active secretion of Metformin. The genetic polymorphism of OCT2 influences the pharmacodynamic and pharmacokinetic effect of Metformin in type 2 diabetes mellitus (T2DM) patients. This is also mainly associated with frequencies of the associated risk allele in a particular population.

Objective

The purpose of the study is to determine the impact of OCT2 genetic polymorphism on Metformin pharmacodynamics (PD) and pharmacokinetics (PK).

Method of study

Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were used for performing the research. Following databases were used to conduct the search: PubMed/MEDLINE, Google Scholar, and the Cochrane Library. Relevant studies were retrieved and literatures were appraised for methodology, demographic characteristics, relevant SNPs, genetic intervention trials, and outcomes.

Results

Based on the data collected, 13 OCT2 Single nucleotide polymorphisms (SNPs) were identified across various ethnic groups. There were significant differences between the frequency distribution of shared alleles and impact of thirteen SNPs on Metformin. Among the thirteen OCT2 variants studied, rs316019 variant produced the most diverse responses in population by showing positive and negative impact on PK & PD of Metformin.

Discussion and conclusion

Each population's OCT2 polymorphism had a distinct effect on Metformin responsiveness. The findings of this study could bring significant benefits to patients with OCT2 genetic polymorphism if individualised T2DM therapy is introduced. Patient-centered treatment would improve the Metformin efficacy leading to new research in personalised medicine.

Introduction

Organic cation transporters (OCTs) remain a kind of transport proteins that secrete and uptake cationic substances. Knockout mice examination studies have demonstrated their involvement in a very functional manner. It is the most common OCT on the proximal tubular epithelium's basolateral membrane. It is essential for the renal clearance of cationic drugs, including oxyanions, from the bloodstream onto the reticuloendothelial system [1]. Diabetes is a chronic metabolic disorder characterized by high glucose levels (hyperglycemia), which over time can severely injure the heart, blood vessels, eyes, kidneys, and nerves. It mainly develops from insufficient insulin synthesis, secretion and resistance, or from a combination of the three [2].

Metformin, an antihyperglycemic medicine, is regarded as a firstline treatment for Type 2 diabetes mellitus (T2DM) and is an effective and extensively used medication. Additionally, Metformin is also beneficial in reducing some macro and microvascular complications including weight loss [2,3,4,5]. Despite the fact that the thorough mechanism of action of Metformin is unknown or unverified, some researchers claim that it serves as a metabolic inhibitor.

Metformin influences whole-body and cellular energy metabolism by activating AMP-activated protein kinase (AMPK) via a decrease in hepatic energy position, i.e., increasing the concentration ratios of Adenosine monophosphate (AMP): Adenosine di-phosphate (ADP) and/or ADP/Adenosine triphosphate (ATP), hence lowering transcription of gluconeogenic genes. Additionally, it reduces hepatic glucose production and increases insulin sensitivity, making it easier for the body to absorb and use glucose [3]. Evidence-based studies have repeatedly shown that genetic polymorphism of OCT2 role in the interindividual heterogeneity of metformin response. As a result, suggestive data emphasize the importance of future research into the effect of genetic polymorphisms on Metformin efficacy [6]. Plasma Membrane Monoamine Transporter (PMAT) and organic cation transporter 3 (OCT3) and are involved in absorption of Metformin in the gastrointestinal tract. Organic cation transporter 1 then transports the drug into the bloodstream (OCT1). Metformin cannot enter the liver without these OCT1 and OCT3 transporter protein genes. OCT2-gene (SLC22A2), mostly expressed in the basolateral membrane of renal tubules, plays a key role in the Metformin uptake from circulation into renal epithelial cells. Multidrug and toxic compound extrusion 1 (MATE1) (SLC47A1) and Multidrug and toxic compound extrusion 2 (MATE2-K) are involved in the transport of Metformin from the tubule cell to the lumen during renal excretion (SLC47A2) The impact of OCT2 (gene SLC22A2) genetic polymorphisms on pharmacokinetics of Metformin has been investigated in healthy population. In comparison to the reference genotype, the pharmacokinetics of OCT2 [c.596C > T, c.602C > T, and c.808G > T (rs316019)] genetic variations varied, with an increase in Area under the Curve (AUC) and Peak concentration (Cmax) and a decrease in renal clearance (CLr) [7].

Metformin is primarily eliminated through the kidneys and its tubular secretion has been demonstrated to be exclusively mediated by OCT2. Many literatures has demonstrated the existence of OCT2 genetic polymorphism in humans. Metformin activity has been found to be altered by OCT2 genetic polymorphism strongly indicating the significance of these genes in determining Metformin response. Few studies have found an association between OCT2 genetic polymorphism and Metformin efficacy and clearance, whereas others have found no association. Research examining the relationship between the genetic polymorphism of OCT2 and Metformin in various ethnic groups has a wide range of results. In order to examine the impacts of multiple SNPs in relation to Metformin clearance and response, it is vital to compile all the information into one review, which is why this study is significant. Extensive research is needed to comprehend the interindividual variation with different OCT2 SNPs for individualising the dosage regimen for patients with T2DM. This study aims to gather all available data on the impact of the OCT2 Single nucleotide polymorphism on the pharmacodynamics and pharmacokinetics of Metformin in patients with T2DM. It also seeks to understand and describe the distribution of OCT2 genetic variations throughout populations and their impact with Metformin responsiveness.

Materials and method

Inclusion criteria

We included the studies that evaluated the influence of OCT2 genetic polymorphism or SNPs on the pharmacodynamics and pharmacokinetics of Metformin in T2DMpatients.

Exclusion criteria

Studies involving the influence of OCT2 gene polymorphisms on the effect of Metformin in conditions other than T2DM are excluded.

Literature survey strategy

Electronic search

An electronic literature search was done using search engines like Google Scholar, PubMed/MEDLINE and the Cochrane Library. We searched for articles that addressed the influence of OCT2 genetic polymorphism on the pharmacodynamics and pharmacokinetic of Metformin in treating T2DM.

Keywords

Relevant keywords were used to retrieve the studies based on inclusion and exclusion criteria. We have selected this search strategy approach to find relevant articles in PubMed: (“SLC22A2”[All Fields] AND “OCT2”[All Fields]) AND “genetic variant”[All Fields] AND “genetic polymorphism”[All Fields] AND, along[All Fields] AND (“metformin”[All Fields] AND “diabetes mellitus”[All Fields]) AND “type 2 diabetes”[All Fields] AND (“pharmacokinetics”[Subheading] OR “pharmacokinetics”[All Fields] OR “pharmacokinetics”[MeSH Terms]) AND (“pharmacology”[Subheading] OR “pharmacology”[All Fields] OR “pharmacodynamics”[All Fields] OR “pharmacology”[MeSH Terms] OR “pharmacodynamics”[All Fields]). Searches in the other databases were also conducted in the same manner. In addition, a systematic search of all citations to published research in journals was done to identify any relevant publications.

Quality assessment

The accuracy and validity of the included studies were assessed by screening the title, description, and complete text of each article.

Measures of different outcomes

Primary outcome

  • Pharmacokinetics: AUC, Renal Clearance.

  • Pharmacodynamics: Glycated hemoglobin (HbA1c).

Secondary outcome

  • Pharmacokinetics: C max, Maximun Velocity (V max), The Michaelis constant (Km).

  • Pharmacodynamics: Fasting blood glucose, Postprandial blood glucose.

Data collection

Replicas were removed from the search engine results before they were imported into Zotero. Four authors examined individual articles, and any discrepancies were resolved with a fifth author. The total number of participants in the study, endpoints, minor allele frequencies (MAF) were used to assess Metformin effectiveness, and changes in the context of SNP were extricated from the seven studies analysed (Fig. 1).

Fig. 1
figure 1

Workflow procedure of literature search

Results

Study features

After a preliminary examination of multiple databases with the relevant keywords, we retrieved 182 articles. Amongst these, 151 articles were from PubMed, 27 from Google scholar, and four from Cochrane. Duplicates were removed, after the second screening. We excluded 123 articles based on the titles, abstracts,language selection and availability of full-text articles. Twenty-eight articles were found to be possibly eligible. Twenty one studies were excluded as they did not match the review's inclusion criteria with non relevance and unmatched end points. Finally seven studies are included based on the studies eligibility criteria.The majority of the research found to be done in Asian people. The duration of the research studies ranged from 24 h for single dosage studies on healthy volunteers to 6 months for patients who had been taking Metformin. The average participants age in the study ranged between 18 and 80 years.

The participants in the study were either healthy volunteers or diagnosed with T2DM on Metformin monotherapy. The Metformin's pharmacodynamic parameters were assessed through HbA1c, fasting blood glucose, postprandial blood glucose, or oral glucose tolerance test. Metformin's pharmacokinetics were evaluated by Peak Concentration (C max), Area Under the Curve (AUC), Maximum Time to achieve Cmax (Tmax), Elimination Rate Constant (K or kel), Metformin Uptake Extent and Half-Life (t1/2).

The genetic variants of the OCT2 polymorphism

A total of 13 SNPs were found from the included studies. The SNPs observed were rs7757336, rs316019, rs201919876, rs17588242, rs10755577, rs17589858, rs3127573, rs2928035, rs316024, rs316026, rs316025, rs662301, rs533452. The effects of the observed SNPs on metformin response were quite diverse and appeared to be either positive, negative, or both.

rs316019

Negative impact

A study in a healthy volunteer Chinese population reported one SNP, 808G > T (Ala270Ser), with a Minor allele frequency of 13.3%. This study further substantiated the nonsynonymous SNP 808G > T polymorphism in the OCT2 gene with amino acid change: alanine to serine is linked with a decreased Metformin CLr (renal clearance) and Metformin CLr and Tubular Clearance (CLt) were found to be significantly reduced in homozygous TT carriers (homozygous for 808G > T). Initially, the GT and TT groups seemed to have a higher total plasma concentration (AUC) of Metformin than the GG group, although this difference did not achieve statistical significance. However, it was discovered that there were significant differences in the CLr and CLt of Metformin between the three genotype groups (P = 0.024 and 0.037, one-way ANOVA). Additionally, the mean Metformin CLr and CLt values were 26.1% (P = 0.022) and 28.0% (P = 0.036) less in TT carriers than in GG carriers respectively [8].

Positive impact

The SNP rs316019 (808G/T) was genotyped in European Americans (94) andAfrican Americans (66). The study was conducted only in healthy participants who are homozygous reference and heterozygous 808G/T gene as there were no homozygotes 808T/T found in the study. There is no significant difference in the mean Tmax and Cmax between the two genotype groups. The CLR, Serum renal clearance (SrCLR), and total clearance of Metformin were considerably higher in heterozygous variant allele (808G/T) of OCT2 compared to those reference allele (808G/G) homozygous. Statistically, significant difference was not found with the total clearance, presumably because of the diversity in the bioavailability of the subjects. The following variables (race, gender, OCT2 genotype, creatinine clearance (CLCR) and age) were evaluated using multi-variant analysis as Metformin CLR predictors. Merely, genotype and CLCR were found to be good measures of Metformin CLR among these variables. With genotype alone accounting for 28% versus 22% of the total variance in Metformin CLR and CLCR, respectively concluding OCT2 genotype as the only predictor of Metformin SrCLR) which is significant [9].

A study included fifty healthy Caucasian volunteers and were genotyped for c.808G > T. Both peak plasma concentration (Cmax) and area under the curve of plasma concentration–time to infinity (AUC0-∞) were lesser in the homozygous variant group compared to homozygous and heterozygous and wild types. The apparent (CL/F = Dose/AUC0-∞)) total clearance, CLrenal, secretory clearance CLsec, and volume of distribution (Apparent Vd/F) appeared to be higher in variant homozygous group compared to both the homozygous and heterozygous wild types. For all pharmacokinetic parameters, there were no statistically significant variations among the various c.808G > T genotype groups. On average, the GFR contributed for 22% of the variation in the CLrenal, and the addition of the OCT2 c.808 (G > T) genotype elevated this to 24% [10].

No impact

The study involved 212 Denmark healthy population in total, and it determined that OCT2 c.808 (G > T) genotypes have no affect on the Clrenal [11].

rs201919874

Positive impact

The study established the frequencies of the SNP rs201919874 in Pakistani diabetes patients. The distributional properties of SNPs SLC22A2 rs201919874 in T2DM patients receiving Metformin monotherapy and in combination with sulfonylureas were compared to those of healthy individuals. There was a statistical difference between groups in terms of HbA1c, fasting, and random glucose levels. This study discovered an association between the SLC22A2 gene's allele A and the therapeutic effectiveness of Metformin. The Metformin response was associated with the heterozygous genotype GA of SLC22A2 rs201919874 in both patient groups (p < 0.05). As Group A patients failed to achieve normal levels of HbA1c as well as fasting and random blood glucose levels, GA and AA genotypes were associated with therapeutic efficacy of Metformin in these population (p < 0.05). Significant associations were observed in Metformin T2DM patients in terms of random blood glucose, fasting glucose, and HbA1c, however, no strong correlation were detected in combination T2DM patients. Patients treated with combination treatment versus metformin showed a significant variation in genotypes with regard to HbA1c levels [12].

rs7757336

Negative imapact

The study was conducted in Latvia and Slovakia population and reported that the minor alleles of the SNP rs7757336 of OCT2 is strongly linked with Metformin inefficiency in newly diagnosed T2DM patients (n = 233). 25 healthy, non-diabetic volunteers participated in a pharmacokinetic study to understand the influence of the identified SNPs on Metformin. The findings of a pharmacokinetic study on 25 healthy volunteers supported the finding that SNP rs7757336 in the 5′ flanking regions of the genes coding for organic cation transporter 2 was associated with the absence of Metformin response and the minor alleles of rs775336 consistently related with lower concentrations of Metformin and AUC∞ of plasma. According to the results, allele probabilities for the major and minor alleles remained at 0.118 and 0.132, respectively. The study subjects were divided into a reference group (n = 12) and a risk group (n = 13) with at least one risk allele. Metformin's AUC∞ in plasma was considerably lower (P = 0.009) in the risk group (4.62 ± 1.29 µg/h/mL) compared with reference group (6.30 ± 1.51 µg/h/mL). In the reference group, there was indeed a significant rise in Cmax (0.84 ± 0.25 g/mL compared to 0.60 ± 0.18 g/mL, P = 0.022); meanwhile, the apparent clearance had grown significantly in the risk group (59.64 ± 18.11 g/h compared to 42.47 ± 9.50 g/h, P = 0.01). The genetic variant rs7757336 was strongly related to lower Metformin response [13].

rs17588242, rs2928035, rs316024, rs316026 rs662301, rs10755577, rs17589858, rs3127573, rs316025, rs533452

No impact

A study by Al-Eitan et al., 212 Jordanians population were screened for 10 OCT2 polymorphisms, and they found nil significant association of glycemic control in T2DM patients on Metformin. The Study showed that there was no discernible correlation between renal Metformin clearance and these specific SLC22A2 SNPs (rs2928035, rs17588242, rs316024, rs316026 rs662301, rs10755577, rs17589858, rs3127573, rs316025 and rs533452.). Furthermore, no statistically significant evidence was found in the present investigation to support any of these examined SLC22A2 SNPs having effect on glycemic control. Polymorphisms found in this study had a p value greater than 0.05, indicating no statistical significance [14].

Discussion

OCTs, notably OCT2, are the kidney's Organic Cation Transporters. These proteins facilitate the metformin transport from blood stream to renal epithelial cells.. During the uptake of Metformin or other cationic medications from the blood to renal tubular epithelial compartments, OCT2 plays a critical role. Even though Metformin, the most commonly used drugs for the treatment of T2DM, there are reports which has shown treatment failure with Metformin at the right dose.. Multiple studies have suggested that the OCT2 genetic polymorphism stands as one of the reason for inter-individual disparity in the response of Metformin. Based on the information collected, with the present study, we reported 13 genetic polymorphisms (SNPs) of OCT2 from various ethnic groups which has shown association with metofromin Pharmacokinetics and Pharmacodynamics (Table 1).

Table 1 Organic cation transporter 2 (OCT2) and its effects on the pharmacokinetics and pharmacodynamics of Metformin

When numerous ethnic groups were examined, there were variations in the frequency of the genetic polymorphisms. Out of all SNPs, the most commonly studied was found to be rs316019. Which showed diverse effects in different population with either positive, neagtive, no impact. The effects of rs316019 on the activity of metformin were statistically significant in the conducted studies of Chinese, European Americans, and African Americans. There were variations in Metformin CLr and CLt, AUC, and t1/2 between genotype groups. Reduced renal and tubular Metformin clearance was a main component. In the Jordanian group, the genetic variant rs316019 demonstrated a favourable therapeutic impact (pharmacodynamic) of Metformin. The OCT2 genotypes in the Danish and Caucasian populations had no effect on CLrenal.

The rs7757336 allele was investigated in the Latvian population. The allele was substantially connected with Metformin inefficiency. rs775736 exhibited a diminished Metformin response, as measured by a decreased AUC∞ of Metformin in plasma. rs201919874 was scrutinised to understand better Metformin's PK/PD effects in T2DM individuals from Pakistan. The polymorphism rs201919874 was strongly associated with a greater plasma concentration of Metformin and decreased renal clearance. An association between the SLC22A2 gene's allele A and the therapeutic effectiveness of Metformin is found. Many pharmacodynamic measures, including glycated haemoglobin, random, and fasting glucose levels, were significantly associated with genotypes.

The alleles rs10755577, rs17588242, rs17589858, rs2928035, rs3127573, rs316024, rs316025, rs316026, rs533452, rs662301 have no significant correlation with renal Metformin clearance but there was no statistically significant evidence found to support SLC22A2 SNPs effect on glycemic control. When we looked at how OCT2 polymorphisms affected Metformin's pharmacokinetic and pharmacodynamic profile, we noticed that ethnic groups exhibited considerably different outcomes and frequencies. Other confounding variables, such as age, the present status of the disease condition, and environmental circumstances, may substantially affect the result. Due to the data's inconsistency, the studies could not presume a genotype–phenotype link. The review's limitations include the scarcity of literature in this area of study.

Additionally, some studies reported a low sample size, implying that the study group may not wholly reflect the OCT2 variances. Consequently, a bigger sample size allows for establishing a more robust link between OCT2 genetic polymorphism and substrate drug reactions. The study's results might not have been as conclusive as they could be because of disparities in the types of participants and the methodology used to examine the influences of OCT2 genetic polymorphisms on Metformin response.

Conclusion

This narrative review examined the genetic influences of OCT2 polymorphisms upon the pharmacotherapeutic impacts of OCT2 as to its substrate drug, mainly Metformin. OCT2 polymorphisms were found to have positive and negative impacts, which were unique to the population. The findings of this study could bring significant benefits to patients with OCT2 genetic polymorphism if individualised T2DM therapy is introduced. Timely patient-centered treatment would improve the Metformin efficacy and disease prognosis. Presumably, resulting in decreased rates of macrovascular and microvascular T2DM consequences with better and more targeted treatment regimens.

Availability of data and materials

Not applicable.

References

  1. Saad AAA, Zhang F, Mohammed EAH, Wu X (2022) Clinical aspects of drug-drug interaction and drug nephrotoxicity at renal organic cation transporters 2 (OCT2) and multidrug and toxin exclusion 1, and 2-K (MATE1/MATE2-K). Biol Pharm Bull [Internet] 45(4):382–393

    Article  CAS  Google Scholar 

  2. Diabetes [Internet]. WHO. 2021 [cited 2022 Mar 3]. https://www.who.int/news-room/fact-sheets/detail/diabetes

  3. Bailey CJ, Turner RC (1996) Metformin. N Engl J Med 334(9):574–579

    Article  CAS  Google Scholar 

  4. Holman R (2007) Metformin as the first choice in oral diabetes treatment: the UKPDS experience. Journées annuelles de diabétologie del’ Hôtel-Dieu 2007:13–20

    Google Scholar 

  5. Association AD (2014) Standards of medical care in diabetes. Diabetes Care 37(1):S14–S80

    Article  Google Scholar 

  6. Todd JN, Florez JC (2014) An update on the pharmacogenomics of Metformin: progress, problems, and potential. Pharmacogenomics [Internet] 15(4):529–539

    Article  CAS  Google Scholar 

  7. Gong L, Goswami S, Giacomini KM, Altman RB, Klein TE (2012) Metformin pathways: pharmacokinetics and pharmacodynamics. Pharmacogenet Genom [Internet] 22(11):820–827

    Article  CAS  Google Scholar 

  8. Wang Z-J, Yin OQP, Tomlinson B, Chow MSS (2008) OCT2 polymorphisms and in-vivo renal functional consequence: studies with Metformin and cimetidine. Pharmacogenet Genom [Internet] 18(7):637–645

    Article  CAS  Google Scholar 

  9. Chen Y, Li S, Brown C, Cheatham S, Castro RA, Leabman MK et al (2009) effect of genetic variation in the organic cation transporter 2 on the renal elimination of Metformin. Pharmacogenet Genom [Internet] 19(7):497–504

    Article  Google Scholar 

  10. Christensen MMH, Pedersen RS, Stage TB, Brasch-Andersen C, Nielsen F, Damkier P et al (2013) A gene-gene interaction between polymorphisms in the OCT2 and MATE1 genes influence the renal clearance of Metformin. Pharmacogenet Genom [Internet] 23(10):526–534

    Article  CAS  Google Scholar 

  11. Kuhlmann I, Arnspang Pedersen S, Skov Esbech P, Bjerregaard Stage T, Hougaard Christensen MM, Brøsen K (2021) Using a limited sampling strategy to investigate the interindividual pharmacokinetic variability in Metformin: A large prospective trial. Br J Clin Pharmacol [Internet] 87(4):1963–1969

    Article  CAS  Google Scholar 

  12. Moeez S, Khalid Z, Jalil F, Irfan M, Ismail M, Arif MA et al (2019) Effects of SLC22A2 (rs201919874) and SLC47A2 (rs138244461) genetic variants on Metformin pharmacokinetics in Pakistani T2DM patients. J Pak Med Assoc [Internet] 69(2):155–163

    Google Scholar 

  13. Zaharenko L, Kalnina I, Geldnere K, Konrade I, Grinberga S, Židzik J et al (2016) Single nucleotide polymorphisms in the intergenic region between metformin transporter OCT2 and OCT3 coding genes are associated with short-term response to metformin monotherapy in type 2 diabetes mellitus patients. Eur J Endocrinol [Internet] 175(6):531–540

    Article  CAS  Google Scholar 

  14. Al-Eitan LN, Almomani BA, Nassar AM, Elsaqa BZ, Saadeh NA (2019) Metformin pharmacogenetics: effects of SLC22A1, SLC22A2, and SLC22A3 polymorphisms on glycemic control and HbA1c levels. J Personal Med [Internet] 9(1):17

    Article  Google Scholar 

Download references

Acknowledgements

The authors would like to thank our department staff for their constant support.

Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Author information

Authors and Affiliations

Authors

Contributions

SSB, NRV, MAP and AKP was involved in the Conceptualization, Methodology, Drafting, Editing, Reviewing and Overall Supervision. SGK, RS, DP contributed in Literature Review, Drafting, Visualization, Investigation and Data Curation. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Arun Kanniyappan Parthasarathy.

Ethics declarations

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Borra, S.S., Jane, N.R., Palaniappan, D. et al. Genetic polymorphism of organic cation transporter 2 (OCT2) and its effects on the pharmacokinetics and pharmacodynamics of Metformin: a narrative review. Egypt J Med Hum Genet 24, 13 (2023). https://doi.org/10.1186/s43042-023-00388-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s43042-023-00388-z

Keywords

  • Genetic polymorphism
  • OCT2
  • SLC22A2
  • Substrate drugs
  • Metformin
  • Type 2 diabetes mellitus (T2DM)
  • Pharmacogenetics
  • Personalised medicine