SLC47A1 gene rs2289669 G>A variants enhance the glucose-lowering effect of metformin via delaying its excretion in Chinese type 2 diabetes patients

Precision Medicine in Type 2 Diabetes Mellitus: Utility and Limitations

Type 2 diabetes mellitus (T2DM) is one of the most widespread diseases in Western countries, and its incidence is constantly increasing. Epidemiological studies have shown that in the next 20 years. The number of subjects affected by T2DM will double. In recent years, owing to the development and improvement in methods for studying the genome, several authors have evaluated the association between monogenic or polygenic genetic alterations and the development of metabolic diseases and complications. In addition, sedentary lifestyle and socio-economic and pandemic factors have a great impact on the habits of the population and have significantly contributed to the increase in the incidence of metabolic disorders, obesity, T2DM, metabolic syndrome, and liver steatosis. Moreover, patients with type 2 diabetes appear to respond to antihyperglycemic drugs. Only a minority of patients could be considered true non-responders. Thus, it appears clear that the main aim of precision medicine in T2DM is to identify patients who can benefit most from a specific drug class more than from the others. Precision medicine is a discipline that evaluates the applicability of genetic, lifestyle, and environmental factors to disease development. In particular, it evaluated whether these factors could affect the development of diseases and their complications, response to diet, lifestyle, and use of drugs. Thus, the objective is to find prevention models aimed at reducing the incidence of pathology and mortality and therapeutic personalized approaches, to obtain a greater probability of response and efficacy. This review aims to evaluate the applicability of precision medicine for T2DM, a healthcare burden in many countries.

Advances in multi-omics study of biomarkers of glycolipid metabolism disorder

Glycolipid metabolism disorder are major threats to human health and life. Genetic, environmental, psychological, cellular, and molecular factors contribute to their pathogenesis. Several studies demonstrated that neuroendocrine axis dysfunction, insulin resistance, oxidative stress, chronic inflammatory response, and gut microbiota dysbiosis are core pathological links associated with it. However, the underlying molecular mechanisms and therapeutic targets of glycolipid metabolism disorder remain to be elucidated. Progress in high-throughput technologies has helped clarify the pathophysiology of glycolipid metabolism disorder. In the present review, we explored the ways and means by which genomics, transcriptomics, proteomics, metabolomics, and gut microbiomics could help identify novel candidate biomarkers for the clinical management of glycolipid metabolism disorder. We also discuss the limitations and recommended future research directions of multi-omics studies on these diseases.

Association of the SLC47A1 Gene Variant With Responses to Metformin Monotherapy in Drug-naive Patients With Type 2 Diabetes

CONTEXT

Although metformin is the first-line treatment for type 2 diabetes, the blood sugar-lowering effect of metformin varies among populations. SLC47A1 plays an important role in metformin pharmacokinetics and pharmacodynamics.

OBJECTIVE

We performed a systematic review and meta-analysis to investigate the association between SLC47A1 rs2289669 (G > A) and the metformin response in drug-naive patients with type 2 diabetes.

METHODS

Studies published until January 27, 2022, were retrieved from Cochrane CENTRAL, Embase, PubMed, and Web of Science. Two reviewers independently screened titles, abstracts, and full-text articles. Studies conducted in newly diagnosed or drug-naive patients with type 2 diabetes who received metformin monotherapy were included. A total of 6 studies involving 953 patients were included in this meta-analysis. We extracted the study characteristics and changes in glycated hemoglobin (HbA1c) levels before and after treatment according to the SLC47A1 rs2289669 genotype. Changes in HbA1c levels were analyzed using mean differences (MDs) and 95% CIs. SLC47A1 rs2289669 was associated with changes in HbA1c levels (A carrier vs GG; MD = -0.55; 95% CI, -0.91 to - 0.20; I² = 63%). The sensitivity analysis yielded similar results to the main analysis (MD range, -0.64 to -0.37). When comparing all 3 genotypes, there were significant differences in HbA1c level changes between AA vs GG and GA vs GG, but not in GA vs AA.

CONCLUSION

This meta-analysis showed that SLC47A1 rs2289669 is associated with the glycemic response to metformin in drug-naive patients with type 2 diabetes.

The influence of metformin transporter gene SLC22A1 and SLC47A1 variants on steady-state pharmacokinetics and glycemic response

Interindividual variation is important in the response to metformin as the first-line therapy for type-2 diabetes mellitus (T2DM). Considering that OCT1 and MATE1 transporters determine the metformin pharmacokinetics, this study aimed to investigate the influence of SLC22A1 and SLC47A1 variants on the steady-state pharmacokinetics of metformin and the glycemic response. This research used the prospective-cohort study design for 81 patients with T2DM who received 500 mg metformin twice a day from six primary healthcare centers. SLC22A1 rs628031 A>G (Met408Val) and Met420del genetic variants in OCT1 as well as SLC47A1 rs2289669 G>A genetic variant in MATE1 were examined through the PCR-RFLP method. The bioanalysis of plasma metformin was performed in the validated reversed-phase HPLC-UV detector. The metformin steady-state concentration was measured for the trough concentration (Cssmin) and peak concentration (Cssmax). The pharmacodynamic parameters of metformin use were the fasting blood glucose (FBG) and glycated albumin (GA). Only SLC22A1 Met420del alongside estimated-glomerular filtration rate (eGFR) affected both Cssmax and Cssmin with an extremely weak correlation. Meanwhile, SLC47A1 rs2289669 and FBG were correlated. This study also found that there was no correlation between the three SNPs studied and GA, so only eGFR and Cssmax influenced GA. The average Cssmax in patients with the G allele of SLC22A1 Met408Val, reaching 1.35-fold higher than those with the A allele, requires further studies with regard to metformin safe dose in order to avoid exceeding the recommended therapeutic range.

Genomic editing of metformin efficacy-associated genetic variants in SLC47A1 does not alter SLC47A1 expression

Several pharmacogenetics studies have identified an association between a greater metformin-dependent reduction in HbA1c levels and the minor A allele at rs2289669 in intron 10 of SLC47A1, encoding multidrug and toxin extrusion 1 (MATE1), a presumed metformin transporter. It is currently unknown if the rs2289669 locus is a cis-eQTL, which would validate its role as predictor of metformin efficacy. We looked at association between common genetic variants in the SLC47A1 gene region and HbA1c reduction after metformin treatment using locus-wise meta-analysis from the MetGen consortium. CRISPR-Cas9 was applied to perform allele editing of, or genomic deletion around, rs2289669 and of the closely linked rs8065082 in HepG2 cells. The genome-edited cells were evaluated for SLC47A1 expression and splicing. None of the common variants including rs2289669 showed significant association with metformin response. Genomic editing of either rs2289669 or rs8065082 did not alter SLC47A1 expression or splicing. Experimental and in silico analyses show that the rs2289669-containing haploblock does not appear to carry genetic variants that could explain its previously reported association with metformin efficacy.

Pharmacogenomic Studies of Current Antidiabetic Agents and Potential New Drug Targets for Precision Medicine of Diabetes

Diabetes is a major threat to people's health and has become a burden worldwide. Current drugs for diabetes have limitations, such as different drug responses among individuals, failure to achieve glycemic control, and adverse effects. Exploring more effective therapeutic strategies for patients with diabetes is crucial. Currently pharmacogenomics has provided potential for individualized drug therapy based on genetic and genomic information of patients, and has made precision medicine possible. Responses and adverse effects to antidiabetic drugs are significantly associated with gene polymorphisms in patients. Many new targets for diabetes also have been discovered and developed, and even entered clinical trial phases. This review summarizes pharmacogenomic evidence of some current antidiabetic agents applied in clinical settings, and highlights potential drugs with new targets for diabetes, which represent a more effective treatment in the future.

Revealing Alteration in the Hepatic Glucose Metabolism of Genetically Improved Carp, Jayanti Rohu Labeo rohita Fed a High Carbohydrate Diet Using Transcriptome Sequencing

Although feed cost is the greatest concern in aquaculture, the inclusion of carbohydrates in the fish diet, and their assimilation, are still not well understood in aquaculture species. We identified molecular events that occur due to the inclusion of high carbohydrate levels in the diets of genetically improved 'Jayanti rohu' Labeo rohita. To reveal transcriptional changes in the liver of rohu, a feeding experiment was conducted with three doses of gelatinized starch (20% (control), 40%, and 60%). Transcriptome sequencing revealed totals of 15,232 (4464 up- and 4343 down-regulated) and 15,360 (4478 up- and 4171 down-regulated) differentially expressed genes. Up-regulated transcripts associated with glucose metabolisms, such as hexokinase, PHK, glycogen synthase and PGK, were found in fish fed diets with high starch levels. Interestingly, a de novo lipogenesis mechanism was found to be enriched in the livers of treated fish due to up-regulated transcripts such as FAS, ACCα, and PPARγ. The insulin signaling pathways with enriched PPAR and mTOR were identified by Kyoto Encyclopedia of Genes and Genome (KEGG) as a result of high carbohydrates. This work revealed for the first time the atypical regulation transcripts associated with glucose metabolism and lipogenesis in the livers of Jayanti rohu due to the inclusion of high carbohydrate levels in the diet. This study also encourages the exploration of early nutritional programming for enhancing glucose efficiency in carp species, for sustainable and cost-effective aquaculture production.

Repurposing Drugs for COVID-19: Pharmacokinetics and Pharmacogenomics of Chloroquine and Hydroxychloroquine

Background

A new coronavirus SARS-CoV-2 has been identified as the etiological agent of the severe acute respiratory syndrome, COVID-19, the source and cause of the 2019–20 coronavirus pandemic. Hydroxychloroquine and chloroquine have gathered extraordinary attention as therapeutic candidates against SARS-CoV-2 infections. While there is growing scientific data on the therapeutic effect, there is also concern for toxicity of the medications. The therapy of COVID-19 by hydroxychloroquine and chloroquine is off-label. Studies to analyze the personalized effect and safety are lacking.

Methods

A review of the literature was performed using Medline/PubMed/Embase database. A variety of keywords were employed in keyword/title/abstract searches. The electronic search was followed by extensive hand searching using reference lists from the identified articles.

Results

A total of 126 results were obtained after screening all sources. Mechanisms underlying variability in drug concentrations and therapeutic response with chloroquine and hydroxychloroquine in mediating beneficial and adverse effects of chloroquine and hydroxychloroquine were reviewed and analyzed. Pharmacogenomic studies from various disease states were evaluated to elucidate the role of genetic variation in drug response and toxicity.

Conclusion

Knowledge of the pharmacokinetics and pharmacogenomics of chloroquine and hydroxychloroquine is necessary for effective and safe dosing and to avoid treatment failure and severe complications.

Evaluation of the suitability of 19 pharmacogenomics biomarkers for individualized metformin therapy for type 2 diabetes patients

Objectives Type 2 Diabetes mellitus is a progressive metabolic disease characterized by relative insulin insufficiency and insulin resistance resulting in hyperglycemia. Despite the widespread use of metformin, there is considerable variation in treatment response; with approximately one-third of patients failing to achieve adequate glycemic control. Studies have reported the involvement of single nucleotide polymorphisms and their interactions in genetic pathways i.e., pharmacodynamics and pharmacokinetics. This study aims to investigate the association between 19 pharmacogenetics biomarkers and response to metformin treatment. Methods MassARRAY panels were designed and optimized by Inqaba Biotechnical Industries, to genotype 19 biomarkers for 140 type 2 diabetic outpatients. Results The CT genotype of the rs12752688 polymorphism was significantly associated with increased response to metformin therapy after correction (OR=0.33, 95% CI [0.16-0.68], p-value=0.006). An association was also found between the GA genotype of SLC47A2 rs12943590 and a decreased response to metformin therapy after correction (OR=2.29, 95% CI [1.01-5.21], p-value=0.01). Conclusions This is the first study investigating the association between genetic variants and responsiveness to medication for diabetic patients from the indigenous Nguni population in South Africa. It is suggested that rs12752688 and rs12943590 be included in pharmacogenomics profiling systems to individualize metformin therapy for diabetic patients from African populations.

Evaluation of the suitability of 19 pharmacogenomics biomarkers for individualized metformin therapy for type 2 diabetes patients

Objectives Type 2 Diabetes mellitus is a progressive metabolic disease characterized by relative insulin insufficiency and insulin resistance resulting in hyperglycemia. Despite the widespread use of metformin, there is considerable variation in treatment response; with approximately one-third of patients failing to achieve adequate glycemic control. Studies have reported the involvement of single nucleotide polymorphisms and their interactions in genetic pathways i.e., pharmacodynamics and pharmacokinetics. This study aims to investigate the association between 19 pharmacogenetics biomarkers and response to metformin treatment. Methods MassARRAY panels were designed and optimized by Inqaba Biotechnical Industries, to genotype 19 biomarkers for 140 type 2 diabetic outpatients. Results The CT genotype of the rs12752688 polymorphism was significantly associated with increased response to metformin therapy after correction (OR=0.33, 95% CI [0.16-0.68], p-value=0.006). An association was also found between the GA genotype of SLC47A2 rs12943590 and a decreased response to metformin therapy after correction (OR=2.29, 95% CI [1.01-5.21], p-value=0.01). Conclusions This is the first study investigating the association between genetic variants and responsiveness to medication for diabetic patients from the indigenous Nguni population in South Africa. It is suggested that rs12752688 and rs12943590 be included in pharmacogenomics profiling systems to individualize metformin therapy for diabetic patients from African populations.

A Protocol for the Study of Polymorphisms and Response to Metformin in Patients with Type 2 Diabetes in Trinidad

Background

Metformin is the drug of first choice in people newly diagnosed with type 2 diabetes. Most patients respond to metformin monotherapy, but many others remain uncontrolled even at maximal doses. Although non-adherence is a major contributor to non-response, genetic polymorphisms of organic cation transporters play an important role in clinical response. We hypothesize that genetic variants are partly responsible for non-response.

Objective

This study aims to determine the allele and genotype frequencies of three single nucleotide polymorphisms (SNPs; ATM rs11212617, SLC22A1 rs594709 and SLC47A1 rs2289669) most commonly associated with failure to respond to metformin.

Setting

Ten primary health care facilities in the North Central Regional Health Authority region of Trinidad.

Patients

The study population will include 216 patients with diabetes adherent to metformin monotherapy for at least three months.

Methods

Following a 12-hour overnight fast, blood samples will be taken to measure fasting insulin and HbA1c. DNA would be isolated and PCR will be used to determine the allele and genotype frequencies of these three SNPs in adherent diabetic patients. DNA samples will be stored for future sequencing of these three genes to determine whether other, possibly novel, mutations are associated with poor metformin response in Trinidad.

Clinical Significance

This study will highlight the prevalence of these polymorphisms in our population. Should an association be found between the polymorphisms tested and glycemic control in adherent patients on metformin monotherapy, this will have implications for further research on medication initiation in newly diagnosed patients with diabetes in Trinidad.

Renal Excretion of Dabigatran: The Potential Role of Multidrug and Toxin Extrusion (MATE) Proteins

Following oral administration, dabigatran etexilate (DABE) is rapidly hydrolyzed to its active form, dabigatran. DABE, but not dabigatran, presents as a P-glycoprotein (P-gp) substrate and has increasingly been used as a probe drug. Therefore, although dosed as DABE, a P-gp drug-drug interaction (DDI) is reported as a dabigatran plasma concentration ratio (perpetrator versus placebo). Because the majority of a DABE dose (80 to 85%) is recovered in urine as unchanged dabigatran (renal active secretion is ∼25% of total clearance), dabigatran was evaluated in vitro as a substrate of various human renal transporters. Active (pyrimethamine-sensitive) dabigatran uptake was observed with human embryonic kidney (HEK) 293 cells expressing multidrug and toxin extrusion protein 1 (MATE1) and 2K (MATE2K), with Michaelis-Menten constant (K_m) values of 4.0 and 8.0 μM, respectively. By comparison, no uptake of 2 μM dabigatran (versus mock-transfected HEK293 cells) was evident with HEK293 cells transfected with organic cation transporters (OCT1 and OCT2) and organic anion transporters (OAT1, 2, 3, and 4). The efflux ratios of dabigatran across P-gp- and BCRP (breast cancer resistance protein)-MDCK (Madin-Darby canine kidney) cell monolayers were 1.5 and 2.0 (versus mock-MDCK cell monolayers), suggesting dabigatran is a relatively poor P-gp and BCRP substrate. Three of five drugs (verapamil, ketoconazole, and quinidine) known to interact clinically with dabigatran, as P-gp inhibitors, presented as MATE inhibitors in vitro (IC₅₀ = 1.0 to 25.2 μM). Taken together, although no basolateral transporter was identified for dabigatran, the results suggest that apical MATE1 and MATE2K could play an important role in its renal clearance. MATE-mediated renal secretion of dabigatran needs to be considered when interpreting the results of P-gp DDI studies following DABE administration.

Lack of effect of the SLC47A1 and SLC47A2 gene polymorphisms on the glycemic response to metformin in type 2 diabetes mellitus patients

Background This work aimed to evaluate the influence of single nucleotide polymorphisms (SNPs) in the SLC47A1 (922-158G>A; rs2289669) and SLC47A2 (-130G>A; rs12943590) genes on the relative change in HbA1c in type 2 diabetes mellitus (T2DM) patients of South India who are taking metformin as monotherapy. It also aims to study the effects of these SNPs on the dose requirement of metformin for glycemic control and the adverse effects of metformin. Methods Diabetes patients on metformin monotherapy were recruited based on the eligibility criteria (n=105). DNA was extracted and genotyping was performed with a real-time PCR system using TaqMan® SNP genotyping assay method. The HbA1c levels were measured using Bio-Rad D-10™ Hemoglobin Analyzer. Results After adjusting for multiple comparisons (Bonferroni correction) the difference found in the glycemic response between the "GG" genotype and "AG/AA" genotype groups of the SLC47A2 gene was not significant (p=0.027; which was greater than the critical value of 0.025). Patients with "GG" genotype showed a 5.5% decrease in HbA1c from baseline compared to those with the "AG/AA" genotype (0.1% increase). The SNP in the SLC47A1 gene also did not influence the glycemic response to metformin (p=0.079). The median dose requirements based on the genotypes of the rs12943590 variant (p=0.357) or rs2289669 variant (p=0.580) were not significantly different. Similarly, there was no significant difference in the occurrence of adverse effects across the genotypes in both the SLC47A1 (p=0.615) and SLC47A2 (p=0.309) genes. Conclusions The clinical response to metformin was not associated with the SNPs in the SLC47A1 and SLC47A2 genes coding for the multidrug and toxin extrusion protein (MATE) transporters. Furthermore, the studied SNPs had no influence on the dose requirement or adverse effects of metformin.

Pharmacogenetics of type 2 diabetes mellitus, the route toward tailored medicine

Type 2 diabetes mellitus (T2DM) is a chronic disease that has reached the levels of a global epidemic. In order to achieve optimal glucose control, it is often necessary to rely on combination therapy of multiple drugs or insulin because uncontrolled glucose levels result in T2DM progression and enhanced risk of complications and mortality. Several antihyperglycemic agents have been developed over time, and T2DM pharmacotherapy should be prescribed based on suitability for the individual patient's characteristics. Pharmacogenetics is the branch of genetics that investigates how our genome influences individual responses to drugs, therapeutic outcomes, and incidence of adverse effects. In this review, we evaluated the pharmacogenetic evidences currently available in the literature, and we identified the top informative genetic variants associated with response to the most common anti-diabetic drugs: metformin, DPP-4 inhibitors/GLP1R agonists, thiazolidinediones, and sulfonylureas/meglitinides. Overall, we found 40 polymorphisms for each drug class in a total of 71 loci, and we examined the possibility of encouraging genetic screening of these variants/loci in order to critically implement decision-making about the therapeutic approach through precision medicine strategies. It is possible then to anticipate that when the clinical practice will take advantage of the genetic information of the diabetic patients, this will provide a useful resource for the prevention of T2DM progression, enabling the identification of the precise drug that is most likely to be effective and safe for each patient and the reduction of the economic impact on a global scale.

Precision medicine in diabetes prevention, classification and management

Diabetes has become a major burden of healthcare expenditure. Diabetes management following a uniform treatment algorithm is often associated with progressive treatment failure and development of diabetic complications. Recent advances in our understanding of the genomic architecture of diabetes and its complications have provided the framework for development of precision medicine to personalize diabetes prevention and management. In the present review, we summarized recent advances in the understanding of the genetic basis of diabetes and its complications. From a clinician's perspective, we attempted to provide a balanced perspective on the utility of genomic medicine in the field of diabetes. Using genetic information to guide management of monogenic forms of diabetes represents the best-known examples of genomic medicine for diabetes. Although major strides have been made in genetic research for diabetes, its complications and pharmacogenetics, ongoing efforts are required to translate these findings into practice by incorporating genetic information into a risk prediction model for prioritization of treatment strategies, as well as using multi-omic analyses to discover novel drug targets with companion diagnostics. Further research is also required to ensure the appropriate use of this information to empower individuals and healthcare professionals to make personalized decisions for achieving the optimal outcome.

A gene variant near ATM affects the response to metformin and metformin plasma levels: a post hoc analysis of an RCT

AIM

To determine the influence of polymorphisms on the effects of metformin on HbA1c, daily dose of insulin and metformin plasma concentration. Methods: In a post hoc analysis of a 4.3 year placebo-controlled randomized trial with 390 patients with Type 2 diabetes already on insulin, we analyzed the influence of polymorphisms in genes coding for ATM and the transporters OCT1 and MATE1. Outcome measures were a combined HbA1c + daily dose of insulin Z score and metformin plasma concentrations.

RESULTS

rs11212617 (ATM) was associated with an improved Z score and a lower metformin plasma concentration. In addition, the major allele of rs2289669 (MATE1) was also associated with an improved Z score.

CONCLUSION

The ATM SNP rs11212617 significantly affected the effect of metformin and metformin plasma concentration. Further research is needed to determine the clinical importance of these findings, in particular the effects on metformin plasma concentration.

A non-linear pharmacokinetic-pharmacodynamic relationship of metformin in healthy volunteers: An open-label, parallel group, randomized clinical study

Background

The aim of this study was to explore the pharmacokinetic-pharmacodynamic (PK-PD) relationship of metformin on glucose levels after the administration of 250 mg and 1000 mg of metformin in healthy volunteers.

Methods

A total of 20 healthy male volunteers were randomized to receive two doses of either a low dose (375 mg followed by 250 mg) or a high dose (1000 mg followed by 1000 mg) of metformin at 12-h intervals. The pharmacodynamics of metformin was assessed using oral glucose tolerance tests before and after metformin administration. The PK parameters after the second dose were evaluated through noncompartmental analyses. Four single nucleotide polymorphisms in MATE1, MATE2-K, and OCT2 were genotyped, and their effects on PK characteristics were additionally evaluated.

Results

The plasma exposure of metformin increased as the metformin dose increased. The mean values for the area under the concentration-time curve from dosing to 12 hours post-dose (AUC_0-12h) were 3160.4 and 8808.2 h·μg/L for the low- and high-dose groups, respectively. Non-linear relationships were found between the glucose-lowering effect and PK parameters with a significant inverse trend at high metformin exposure. The PK parameters were comparable among subjects with the genetic polymorphisms.

Conclusions

This study showed a non-linear PK-PD relationship on plasma glucose levels after the administration of metformin. The inverse relationship between systemic exposure and the glucose-lowering effect at a high exposure indicates a possible role for the intestines as an action site for metformin.

Trial registration

ClinicalTrials.gov NCT02712619

Evaluation and Quantitative Prediction of Renal Transporter-Mediated Drug-Drug Interactions

With numerous drugs cleared renally, inhibition of uptake transporters localized on the basolateral membrane of renal proximal tubule cells, eg, organic anion transporters (OATs) and organic cation transporters (OCTs), may lead to clinically meaningful drug-drug interactions (DDIs). Additionally, clinical evidence for the possible involvement of efflux transporters, such as P-glycoprotein (P-gp) and multidrug and toxin extrusion protein 1/2-K (MATE1/2-K), in the renal DDIs is emerging. Herein, we review recent progress regarding mechanistic understanding of transporter-mediated renal DDIs as well as the quantitative predictability of renal DDIs using static and physiologically based pharmacokinetic (PBPK) models. Generally, clinical DDI data suggest that the magnitude of plasma exposure changes attributable to renal DDIs is less than 2-fold, unlike the DDIs associated with inhibition of cytochrome P-450s and/or hepatic uptake transporters. It is concluded that although there is a need for risk assessment early in drug development, current available data imply that safety concerns related to the renal DDIs are generally low. Nevertheless, consideration must be given to the therapeutic index of the victim drug and potential risk in a specific patient population (eg, renal impairment). Finally, in vitro transporter data and clinical pharmacokinetic parameters obtained from the first-in-human studies have proven useful in support of quantitative prediction of DDIs associated with inhibition of renal secretory transporters, OATs or OCTs.

Differential increments of basal glucagon-like-1 peptide concentration among SLC47A1 rs2289669 genotypes were associated with inter-individual variability in glycaemic response to metformin in Chinese people with newly diagnosed Type 2 diabetes

AIM

To elucidate the effects of rs2289669, an intron variant of the SLC47A1 gene, on glucose response to metformin in Chinese people with newly diagnosed Type 2 diabetes.

METHODS

Rs2289669 was genotyped, using Sequenom, in 291 participants receiving 48 weeks of metformin monotherapy. The changes in HbA_1c were compared among rs2289669 genotypes, and associations with rs2289669 were evaluated using linear regression analysis.

RESULTS

We found that, compared with participants with a homozygous G allele, those carrying the minor A allele had significantly greater HbA_1c reduction and greater increases in basal glucagon-like peptide-1 concentration. Regression analysis showed that there was a significant association between rs2289669 and the glucose response to metformin after adjusting for confounding factors, except for changes in basal glucagon-like peptide-1, for which an association was not observed.

CONCLUSIONS

Our findings suggest that rs2289669 might help predict the glycaemic response to metformin in Chinese people newly diagnosed with Type 2 diabetes, and that differential increases in basal glucagon-like peptide-1 concentration among rs2289669 genotypes might be associated with inter-individual response to metformin.

Pharmacogenomic Variants May Influence the Urinary Excretion of Novel Kidney Injury Biomarkers in Patients Receiving Cisplatin

Nephrotoxicity is a dose limiting side effect associated with the use of cisplatin in the treatment of solid tumors. The degree of nephrotoxicity is dictated by the selective accumulation of cisplatin in renal tubule cells due to: (1) uptake by organic cation transporter 2 (OCT2) and copper transporter 1 (CTR1); (2) metabolism by glutathione S-transferases (GSTs) and γ-glutamyltransferase 1 (GGT1); and (3) efflux by multidrug resistance-associated protein 2 (MRP2) and multidrug and toxin extrusion protein 1 (MATE1). The purpose of this study was to determine the significance of single nucleotide polymorphisms that regulate the expression and function of transporters and metabolism genes implicated in development of acute kidney injury (AKI) in cisplatin treated patients. Changes in the kidney function were assessed using novel urinary protein biomarkers and traditional markers. Genotyping was conducted by the QuantStudio 12K Flex Real-Time PCR System using a custom open array chip with metabolism, transport, and transcription factor polymorphisms of interest to cisplatin disposition and toxicity. Traditional and novel biomarker assays for kidney toxicity were assessed for differences according to genotype by ANOVA. Allele and genotype frequencies were determined based on Caucasian population frequencies. The polymorphisms rs596881 (SLC22A2/OCT2), and rs12686377 and rs7851395 (SLC31A1/CTR1) were associated with renoprotection and maintenance of estimated glomerular filtration rate (eGFR). Polymorphisms in SLC22A2/OCT2, SLC31A1/CTRI, SLC47A1/MATE1, ABCC2/MRP2, and GSTP1 were significantly associated with increases in the urinary excretion of novel AKI biomarkers: KIM-1, TFF3, MCP1, NGAL, clusterin, cystatin C, and calbindin. Knowledge concerning which genotypes in drug transporters are associated with cisplatin-induced nephrotoxicity may help to identify at-risk patients and initiate strategies, such as using lower or fractionated cisplatin doses or avoiding cisplatin altogether, in order to prevent AKI.

Genetic polymorphisms of multidrug and toxin extrusion proteins (MATE1 and MATE2) in South Indian population

Introduction: Drug transporters are key determinants of pharmacokinetic and pharmacodynamic profiles of certain drugs. SLC47A1 (MATE1) and SLC47A2 (MATE2) are major efflux transporters involved in the hepatic and renal excretion of many cationic drugs including metformin. Our study was proposed to determine the normative frequencies of the single nucleotide polymorphisms (SNPs) rs2289669 and rs12943590 in the SLC47A1 and SLC47A2 genes, respectively, in South Indian population and also to compare those with those of the HapMap populations.

Methods: One hundred two unrelated healthy volunteers from South India were enrolled in the study. Genomic DNA was extracted by ‘phenol-chloroform extraction method’ from the peripheral blood leucocytes and genotyping was accomplished by real-time polymerase chain reaction using TaqMan SNP genotyping assay method.

Results: In contrast to other populations, the minor allele in SLC47A1 gene was found to be "G" with a frequency of 46.6% in South Indian population. The populations of Hans Chinese in Beijing (HCB) [P = 0.017] and Japanese in Tokyo (JPT) [P < 0.001] had significantly different genotype and allele frequencies (SNP rs2289669) compared to those of South Indian population. Similarly, in the SNP rs12943590 of SLC47A2 gene, the genotype and allele frequencies of South Indian population differed significantly from those of Yoruba in Ibadan, Nigeria (YRI) [P < 0.001] and Utah residents with Northern and Western European ancestry (CEU) [P = 0.005] populations.

Conclusion: Thus, the allele and genotype distributions of SLC47A1 and SLC47A2 gene polymorphisms were established in South Indian population and were found to be different from the frequencies of other ethnicities.

Quercetin intake, MATE1 polymorphism, and metabolic syndrome in Korean population: Hallym aging study

Multidrug and toxic compound extrusion transporter-1 (MATE1) is a quercetin transporter. We examined the associations of quercetin intake and polymorphism of MATE1 in relation to metabolic syndrome (MetS) in Hallym Aging Study. Quercetin intake and the measurements for MetS were assessed in 2004. Six tagging single nucleotide polymorphisms (SNPs) at MATE1 gene were genotyped in 428 Korean adults in 2012. We found a lower prevalence of MetS with quercetin intake; compared to the lowest quartile, odds ratios (ORs, 95% confidence intervals; CIs) were 0.44 (0.24-0.84) for the 3^rd quartile. Individuals with the minor allele of MATE1, rs2453589, tended to have a lower prevalence of MetS compared to those with the major allele (OR=0.69; CI=0.36-1.34). However, interactions between quercetin intake and six MATE1 polymorphisms in relation to MetS were not significant (p for interaction ≥0.37). In conclusion, intake of quercetin was associated with MetS in Korean populations.

Pharmacogenetic studies update in type 2 diabetes mellitus

Type 2 diabetes mellitus (T2DM) is a silent progressive polygenic metabolic disorder resulting from ineffective insulin cascading in the body. World-wide, about 415 million people are suffering from T2DM with a projected rise to 642 million in 2040. T2DM is treated with several classes of oral antidiabetic drugs (OADs) viz. biguanides, sulfonylureas, thiazolidinediones, meglitinides, etc. Treatment strategies for T2DM are to minimize long-term micro and macro vascular complications by achieving an optimized glycemic control. Genetic variations in the human genome not only disclose the risk of T2DM development but also predict the personalized response to drug therapy. Inter-individual variability in response to OADs is due to polymorphisms in genes encoding drug receptors, transporters, and metabolizing enzymes for example, genetic variants in solute carrier transporters (SLC22A1, SLC22A2, SLC22A3, SLC47A1 and SLC47A2) are actively involved in glycemic/HbA1c management of metformin. In addition, CYP gene encoding Cytochrome P450 enzymes also play a crucial role with respect to metabolism of drugs. Pharmacogenetic studies provide insights on the relationship between individual genetic variants and variable therapeutic outcomes of various OADs. Clinical utility of pharmacogenetic study is to predict the therapeutic dose of various OADs on individual basis. Pharmacogenetics therefore, is a step towards personalized medicine which will greatly improve the efficacy of diabetes treatment.

Different effect of testosterone and oestrogen on urinary excretion of metformin via regulating OCTs and MATEs expression in the kidney of mice

The aim of this study was to investigate the effect of testosterone and oestrogen on regulating organic cation transporters (Octs) and multidrug and toxin extrusions (Mates) expression in the kidney of mice and urinary excretion of metformin. 8 week‐old male db/db mice were treated with estradiol (5 mg/kg), testosterone (50 mg/kg) or olive oil with same volume. Metformin (150 mg/kg) was injected in daily for successive 7 days. Plasma, urine and tissue concentrations of metformin were determined by liquid chromatography‐tandem mass spectrometry (LCMS) assay. Western blotting and Real‐time PCR analysis were successively used to evaluate the renal protein and mRNA expression of Octs and MATEs. After treatment, the protein expression of Mate1 and Oct2 in testosterone group was significantly increased than those in control group (both P < 0.05). The protein expression of Mate1 and Oct2 in estradiol group was significantly reduced by 29.4% and 43.3%, respectively, compared to those in control group (all P < 0.05). These data showed a good agreement with the change in mRNA level (all P < 0.05). The plasma metformin concentration (ng/ml) in mice treated with estradiol was significantly higher than control and testosterone group (677.56 ± 72.49 versus 293.92 ± 83.27 and 261.46 ± 79.45; P < 0.01). Moreover, testosterone increased the metformin urine excretion of mice while estradiol decreasing (both P < 0.01). Spearman correlation analysis showed that gonadal hormone was closely associated with Mate1 and Oct2 expression and metformin urine excretion in db/db mice (all P < 0.05). Testosterone and oestrogen exerted reverse effect on metformin urinary excretion via regulating Octs and Mates expression in the kidney of mice.

Limited sampling strategy for determining metformin area under the plasma concentration-time curve

AIM

The aim was to develop and validate limited sampling strategy (LSS) models to predict the area under the plasma concentration-time curve (AUC) for metformin.

METHODS

Metformin plasma concentrations (n = 627) at 0-24 h after a single 500 mg dose were used for LSS development, based on all subsets linear regression analysis. The LSS-derived AUC(0,24 h) was compared with the parameter 'best estimate' obtained by non-compartmental analysis using all plasma concentration data points. Correlation between the LSS-derived and the best estimated AUC(0,24 h) (r(2) ), bias and precision of the LSS estimates were quantified. The LSS models were validated in independent cohorts.

RESULTS

A two-point (3 h and 10 h) regression equation with no intercept estimated accurately the individual AUC(0,24 h) in the development cohort: r(2)  = 0.927, bias (mean, 95% CI) -0.5, -2.7-1.8% and precision 6.3, 4.9-7.7%. The accuracy of the two point LSS model was verified in study cohorts of individuals receiving single 500 or 1000 mg (r(2)  = -0.933-0.934) or seven 1000 mg daily doses (r(2)  = 0.918), as well as using data from 16 published studies covering a wide range of metformin doses, demographics, clinical and experimental conditions (r(2)  = 0.976). The LSS model reproduced previously reported results for effects of polymorphisms in OCT2 and MATE1 genes on AUC(0,24 h) and renal clearance of metformin.

CONCLUSIONS

The two point LSS algorithm may be used to assess the systemic exposure to metformin under diverse conditions, with reduced costs of sampling and analysis, and saving time for both subjects and investigators.

Pharmacogenetic aspects of the treatment of Type 2 diabetes with the incretin effect enhancers

Incretin effect enhancers are drugs used in the treatment of Type 2 diabetes and include GLP-1 receptor agonists and dipeptidyl peptidase-4 inhibitors (gliptins). Variants in several genes were shown to be involved in the physiology of incretin secretion. Only two gene variants have evidence also from pharmacogenetic studies. TCF7L2 rs7903146 C>T and CTRB1/2 rs7202877 T>G minor allele carriers were both associated with a smaller reduction in HbA1c after gliptin treatment when compared with major allele carriers. After replication in further studies, these observations could be of clinical significance in helping to identify patients with potentially lower or higher response to gliptin treatment.

Structure and function of multidrug and toxin extrusion proteins (MATEs) and their relevance to drug therapy and personalized medicine

Multidrug and toxin extrusion (MATE; SLC47A) proteins are membrane transporters mediating the excretion of organic cations and zwitterions into bile and urine and thereby contributing to the hepatic and renal elimination of many xenobiotics. Transported substrates include creatinine as endogenous substrate, the vitamin thiamine and a number of drug agents with in part chemically different structures such as the antidiabetic metformin, the antiviral agents acyclovir and ganciclovir as well as the antibiotics cephalexin and cephradine. This review summarizes current knowledge on the structural and molecular features of human MATE transporters including data on expression and localization in different tissues, important aspects on regulation and their functional role in drug transport. The role of genetic variation of MATE proteins for drug pharmacokinetics and drug response will be discussed with consequences for personalized medicine.

Pharmacogenetics in type 2 diabetes: influence on response to oral hypoglycemic agents

Type 2 diabetes is one of the leading causes of morbidity and mortality, consuming a significant proportion of public health spending. Oral hypoglycemic agents (OHAs) are the frontline treatment approaches after lifestyle changes. However, huge interindividual variation in response to OHAs results in unnecessary treatment failure. In addition to nongenetic factors, genetic factors are thought to contribute to much of such variability, highlighting the importance of the potential of pharmacogenetics to improve therapeutic outcome. Despite the presence of conflicting results, significant progress has been made in an effort to identify the genetic markers associated with pharmacokinetics, pharmacodynamics, and ultimately therapeutic response and/or adverse outcomes to OHAs. As such, this article presents a comprehensive review of current knowledge on pharmacogenetics of OHAs and provides insights into knowledge gaps and future directions.

Pharmacogenetics: Implications for Modern Type 2 Diabetes Therapy

Many clinical treatment studies have reported remarkable interindividual variability in the response to pharmaceutical drugs, and uncovered the existence of inadequate treatment response, non-response, and even adverse drug reactions. Pharmacogenetics addresses the impact of genetic variants on treatment outcome including side-effects. In recent years, it has also entered the field of clinical diabetes research. In modern type 2 diabetes therapy, metformin is established as first-line drug. The latest pharmaceutical developments, including incretin mimetics, dipeptidyl peptidase 4 inhibitors (gliptins), and sodium/glucose cotransporter 2 inhibitors (gliflozins), are currently experiencing a marked increase in clinical use, while the prescriptions of α-glucosidase inhibitors, sulfonylureas, meglitinides (glinides), and thiazolidinediones (glitazones) are declining, predominantly because of reported side-effects. This review summarizes the current knowledge about gene-drug interactions observed in therapy studies with the above drugs. We report drug interactions with candidate genes involved in the pharmacokinetics (e.g., drug transporters) and pharmacodynamics (drug targets and downstream signaling steps) of the drugs, with known type 2 diabetes risk genes and previously unknown genes derived from hypothesis-free approaches such as genome-wide association studies. Moreover, some new and promising candidate genes for future pharmacogenetic assessment are highlighted. Finally, we critically appraise the current state of type 2 diabetes pharmacogenetics in the light of its impact on therapeutic decisions, and we refer to major problems, and make suggestions for future efforts in this field to help improve the clinical relevance of the results, and to establish genetically determined treatment failure.

The Impacts of SLC22A1 rs594709 and SLC47A1 rs2289669 Polymorphisms on Metformin Therapeutic Efficacy in Chinese Type 2 Diabetes Patients

Background. We aimed to investigate the distributive characteristics of SLC22A1 rs594709 and SLC47A1 rs2289669 polymorphisms and their influence on metformin efficacy in Chinese T2DM patients. Methods. The distributions of SLC22A1 rs594709 and SLC47A1 rs2289669 polymorphisms were determined in 267 T2DM patients and 182 healthy subjects. Subsequently, 53 newly diagnosed patients who received metformin monotherapy were recruited to evaluate metformin efficacy. Results. No significant difference was found between T2DM patients and healthy subjects in SLC22A1 rs594709 and SLC47A1 rs2289669 allele frequencies and genotype frequencies. After metformin treatment, SLC22A1 rs594709 GG genotype patients showed a higher increase in FINS (p = 0.015) and decrease in HOMA-IS (p = 0.001) and QUICKI (p = 0.002) than A allele carriers. SLC47A1 rs2289669 GG genotype patients had a higher decrease in TChol (p = 0.030) and LDL-C (p = 0.049) than A allele carriers. Among SLC22A1 rs594709 AA genotype, patients with SLC47A1 rs2289669 AA genotype showed a higher decrease in FBG (p = 0.015), PINS (p = 0.041), and HOMA-IR (p = 0.014) than G allele carriers. However, among SLC22A1 rs594709 G allele carriers, SLC47A1 rs2289669 AA genotype patients showed a higher decrease in TChol (p = 0.013) than G allele carriers. Conclusion. Our data suggest that SLC22A1 rs594709 and SLC47A1 rs2289669 polymorphisms may influence metformin efficacy together in Chinese T2DM patients.

Inhibition of the multidrug and toxin extrusion (MATE) transporter by pyrimethamine increases the plasma concentration of metformin but does not increase antihyperglycaemic activity in humans

We hypothesized that the pharmacodynamic (PD) characteristics of metformin would change with inhibition of the multidrug and toxin extrusion (MATE) transporter, which mediates renal elimination of metformin. Twenty healthy male subjects received two doses (750/500 mg) of metformin, with and without 50 mg of pyrimethamine (a potent MATE inhibitor), with 1 week of washout in between each dose. The PD characteristics of metformin were assessed using oral glucose tolerance tests (OGTTs) before and after the metformin dose. Metformin concentrations in plasma and urine were determined using liquid chromatography-electrospray ionization-tandem mass spectrometry. When metformin was co-administered with pyrimethamine, its area under the concentration-time curve from 0 to 12 h was 2.58-fold greater (p < 0.05), whereas the antihyperglycaemic effects of metformin were decreased. The mean differences (90% confidence interval) in mean and maximum serum glucose concentrations and in 2-h-post-OGTT serum glucose concentration were -0.6 (-1, -0.2), -0.9 (-1.6, -0.3) and -0.5 (-1.1, 0.1) mmol/l, respectively. These findings indicate that the response to metformin is not only related to the plasma exposure of metformin but is also related to other factors, such as inhibition of uptake transporters and the gastrointestinal-based pharmacology of metformin.