Pharmacogenomic association between a variant in SLC47A1 gene and therapeutic response to metformin in type 2 diabetes

Utilising Endogenous Biomarkers in Drug Development to Streamline the Assessment of Drug-Drug Interactions Mediated by Renal Transporters: A Pharmaceutical Industry Perspective

The renal secretion of many drugs is facilitated by membrane transporters, including organic cation transporter 2, multidrug and toxin extrusion protein 1/2-K and organic anion transporters 1 and 3. Inhibition of these transporters can reduce renal excretion of drugs and thereby pose a safety risk. Assessing the risk of inhibition of these membrane transporters by investigational drugs remains a key focus in the evaluation of drug-drug interactions (DDIs). Current methods to predict DDI risk are based on generating in vitro data followed by a clinical assessment using a recommended exogenous probe substrate for the individual drug transporter. More recently, monitoring plasma-based and urine-based endogenous biomarkers to predict transporter-mediated DDIs in early phase I studies represents a promising approach to facilitate, improve and potentially avoid conventional clinical DDI studies. This perspective reviews the evidence for use of these endogenous biomarkers in the assessment of renal transporter-mediated DDI, evaluates how endogenous biomarkers may help to expand the DDI assessment toolkit and offers some potential knowledge gaps. A conceptual framework for assessment that may complement the current paradigm of predicting the potential for renal transporter-mediated DDIs is outlined.

Exploring metformin monotherapy response in Type-2 diabetes: Computational insights through clinical, genomic, and proteomic markers using machine learning algorithms

BACKGROUND

In 2016, the UK had 4.5 million people with diabetes, predominantly Type-2 Diabetes Mellitus (T2DM). The NHS allocates £10 billion (9% of its budget) to manage diabetes. Metformin is the primary treatment for T2DM, but 35% of patients don't benefit from it, leading to complications. This study aims to delve into metformin's efficacy using clinical, genomic, and proteomic data to uncover new biomarkers and build a Machine Learning predictor for early metformin response detection.

METHODS

Here we report analysis from a T2DM dataset of individuals prescribed metformin monotherapy from the Diastrat cohort recruited at the Altnagelvin Area Hospital, Northern Ireland.

RESULTS

In the clinical data analysis, comparing responders (those achieving HbA1c ≤ 48 mmol/mol) to non-responders (with HbA1c > 48 mmol/mol), we identified that creatinine levels and bodyweight were more negatively correlated with response than non-response. In genomic analysis, we identified statistically significant (p-value <0.05) variants rs6551649 (LPHN3), rs6551654 (LPHN3), rs4495065 (LPHN3) and rs7940817 (TRPC6) which appear to differentiate the responders and non-responders. In proteomic analysis, we identified 15 statistically significant (p-value <0.05, q-value <0.05) proteomic markers that differentiate controls, responders, non-responders and treatment groups, out of which the most significant were HAOX1, CCL17 and PAI that had fold change ∼2. A machine learning model was build; the best model predicted non-responders with 83% classification accuracy.

CONCLUSION

Further testing in prospective validation cohorts is required to determine the clinical utility of the proposed model.

Tailoring Type II Diabetes Treatment: Investigating the Effect of 5-HTT Polymorphisms on HbA1c Levels after Metformin Initiation

Aims

To investigate the effect of serotonin transporter (5-HTT) polymorphisms on change in HbA1c levels six months after metformin initiation in type 2 diabetes patients.

Materials and Methods

Participants of PROVALID (PROspective cohort study in patients with type 2 diabetes mellitus for VALidation of biomarkers) within the GIANTT (Groningen Initiative to ANalyse Type 2 Diabetes Treatment) cohort who initiated metformin were genotyped for combined 5-HTTLPR/rs25531 (L∗L∗, L∗S∗, and S∗S∗) and 5-HTT VNTR (STin 2.12, 12/-, and 10/-) polymorphisms, respectively. Multiple linear regression was applied to determine the change in HbA1c level from baseline date to six months across 5-HTTLPR/VNTR genotype groups, adjusted for baseline HbA1c, age, gender, triglyceride level, low-density lipoprotein level, and serum creatinine.

Results

157 participants were included, of which 56.2% were male. The average age was 59.3 ± 9.23 years, and the mean baseline HbA1c was 7.49% ± 1.21%. 5-HTTLPR was characterized in 46 patients as L∗L∗, 70 patients as L∗S∗, and 41 patients as S∗S∗ genotypes. No significant association was found between 5-HTTLPR and 5-HTT VNTR genotypes and change in HbA1c after adjustments.

Conclusions

5-HTT polymorphisms did not affect HbA1c levels six months after the start of metformin. Further long-term studies in large samples would be relevant to determine which polymorphisms can explain the variation in response to metformin treatment.

Association of SLC22A1, SLC47A1, and KCNJ11 polymorphisms with efficacy and safety of metformin and sulfonylurea combination therapy in Egyptian patients with type 2 diabetes

Background and purpose

Multidrug and toxin extrusion transporter 1 (MATE1), encoded by the SLC47A1 gene and single nucleotide polymorphisms of organic cation transport 1, may impact metformin's responsiveness and side effects. Inward-rectifier potassium channel 6.2 (Kir 6.2) subunits encoded by KCNJ11 may affect the response to sulfonylurea. This study aimed to evaluate the association between SLC22A1 rs72552763 and rs628031, SLC47A1 rs2289669 and KCNJ11 rs5219 genetic variations with sulfonylurea and metformin combination therapy efficacy and safety in Egyptian type 2 diabetes mellitus patients.

Experimental approach

This study was conducted on 100 cases taking at least one year of sulfonylurea and metformin combination therapy. Patients were genotyped via the polymerase chain reaction-restriction fragment length polymorphism technique. Then, according to their glycated hemoglobin level, cases were subdivided into non-responders or responders. Depending on metformin-induced gastrointestinal tract side effects incidence, patients are classified as tolerant or intolerant.

Findings/Results

KCNJ11 rs5219 heterozygous and homozygous mutant genotypes, SLC47A1 rs2289669 heterozygous and homozygous mutant genotypes (AA and AG), and mutant alleles of both polymorphisms were significantly related with increased response to combined therapy. Individuals with the SLC22A1 (rs72552763) GAT/del genotype and the SLC22A1 (rs628031) AG and AA genotypes were at a higher risk for metformin-induced gastrointestinal tract adverse effects.

Conclusion and implications

The results implied a role for SLC47A1 rs2289669 and KCNJ11 rs5219 in the responsiveness to combined therapy. SLC22A1 (rs628031) and (rs72552763) polymorphisms may be associated with increased metformin adverse effects in type 2 diabetes mellitus patients.

Systematic Critical Review of Genetic Factors Associated with Cisplatin-induced Ototoxicity: Canadian Pharmacogenomics Network for Drug Safety 2022 Update

BACKGROUND

Cisplatin is commonly used to treat solid tumors; however, its use can be complicated by drug-induced hearing loss (ie, ototoxicity). The presence of certain genetic variants has been associated with the development/occurrence of cisplatin-induced ototoxicity, suggesting that genetic factors may be able to predict patients who are more likely to develop ototoxicity. The authors aimed to review genetic associations with cisplatin-induced ototoxicity and discuss their clinical relevance.

METHODS

An updated systematic review was conducted on behalf of the Canadian Pharmacogenomics Network for Drug Safety, based on the Preferred Reporting Items for Systematic reviews and Meta-Analyses 2020 statement. Pharmacogenomic studies that reported associations between genetic variation and cisplatin-induced ototoxicity were included. The evidence on genetic associations was summarized and evaluated, and knowledge gaps that can be used to inform future pharmacogenomic studies identified.

RESULTS

Overall, 40 evaluated reports, considering 47 independent patient populations, captured associations involving 24 genes. Considering GRADE criteria, genetic variants in 2 genes were strongly (ie, odds ratios ≥3) and consistently (ie, replication in ≥3 independent populations) predictive of cisplatin-induced ototoxicity. Specifically, an ACYP2 variant has been associated with ototoxicity in both children and adults, whereas TPMT variants are relevant in children. Encouraging evidence for associations involving several other genes also exists; however, further research is necessary to determine potential clinical relevance.

CONCLUSIONS

Genetic variation in ACYP2 and TPMT may be helpful in predicting patients at the highest risk of developing cisplatin-induced ototoxicity. Further research (including replication studies considering diverse pediatric and adult patient populations) is required to determine whether genetic variation in additional genes may help further identify patients most at risk.

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.

Association between organic cation transporter genetic polymorphisms and metformin response and intolerance in T2DM individuals: a systematic review and meta-analysis

Background

Variants in organic cation transporter (OCT) genes play a crucial role in metformin pharmacokinetics and are critical for diabetes treatment. However, studies investigating the effect of OCT genetic polymorphisms on metformin response have reported inconsistent results. This review and meta-analysis aimed to evaluate the associations between OCT genetic polymorphisms and metformin response and intolerance in individuals with type 2 diabetes mellitus (T2DM).

Method

A systematic search was conducted on PubMed, EMBASE, CNKI, WANFANG DATA, and VIP database for identifying potential studies up to 10 November 2022. The Q-Genie tool was used to evaluate the quality of included studies. Pooled odds ratios (OR) or standardized mean differences (SMD) and 95% confidence intervals (95% CI) were calculated to determine the associations between OCT genetic polymorphisms and metformin response and intolerance that were reflected by glycemic response indexes, such as glycated hemoglobin level (HbA1c%) or change in glycated hemoglobin level (ΔHbA1c%), fasting plasma level (FPG) or change in fasting plasma glucose level (ΔFPG), the effectiveness rate of metformin treatment, and the rate of metformin intolerance. A qualitative review was performed for the variants identified just in one study and those that could not undergo pooling analysis.

Results

A total of 30 related eligible studies about OCT genes (SLC22A1, SLC22A2, and SLC22A3) and metformin pharmacogenetics were identified, and 14, 3, and 6 single nucleotide polymorphisms (SNPs) in SLC22A1, SLC22A2, and SLC22A3, respectively, were investigated. Meta-analysis showed that the SLC22A1 rs622342 polymorphism was associated with a reduction in HbA1c level (AA vs. AC: SMD [95% CI] = -0.45 [-0.73--0.18]; p = 0.001). The GG genotype of the SLC22A1 rs628031 polymorphism was associated with a reduction in FPG level (GG vs. AA: SMD [95 %CI] = -0.60 [-1.04-0.16], p = 0.007; GG vs. AG: -0.45 [-0.67-0.20], p < 0.001). No statistical association was found between the remaining variants and metformin response and intolerance.

Conclusion

SLC22A1 rs622342 and rs628031 polymorphisms were potentially associated with glycemic response to metformin. This evidence may provide novel insight into gene-oriented personalized medicine for diabetes.

The association study between changes in HbA1C with rs2250486 and rs67238751 genetic variants for SLC47A1 in newly diagnosed Iranian patients with type 2 diabetes mellitus: 6 months follow-up study

OBJECTIVES

One of the most well-known oral medications for the treatment of T2DM is metformin. Variants have been found in studies to be useful in detecting new genes connected to T2DM aetiology and affecting metformin's mechanism of action. In this research, we aimed to study two variations of the SLC47A1 gene; rs2250486 and rs67238751, in T2DM patients who had been taking metformin for the first 6 months after the diagnosis in the Iranian population for the first time.

DESIGN AND METHODS

A total of 200 individuals were recruited for the study. According to their glycosylated haemoglobin (HbA1c) levels, the patients were divided into two groups: responders (HbA1c levels were reduced by at least 1% after 6 months of metformin treatment.) and non-responders. DNA was extracted from whole blood and genotyped by Tetra ARMS PCR. High-performance liquid chromatography (HPLC) was used to measure HbA1c levels at the start of the treatment and again 6 months later.

RESULTS

rs2250486 variant in the dominant model reduces the HbA1C levels after 6 months of metformin treatment. In fact, when compared to the T/C + C/C genotypes, the T/T genotype improves HbA1C levels (p-value = .014). Furthermore, in the allelic model, the T allele improves HbA1C levels in comparison to the C allele (p-value = .008). After 6 months of metformin treatment, serum levels of HbA1C in responders were reduced significantly in both groups (T/T and T/C + C/C), (p-value = <.0001). However, the rs67238751 variant did not reveal a meaningful relationship with lower HbA1C levels in any of the models.

CONCLUSIONS

This study found that the rs2250486 variant could be associated with reducing HbA1C levels while the rs67238751 variant, had no relationship.

Implications of genetic variations, differential gene expression, and allele-specific expression on metformin response in drug-naïve type 2 diabetes

PURPOSE

Metformin is widely used to treat type 2 diabetes mellitus (T2DM) individuals. Clinically, inter-individual variability of metformin response is of significant concern and is under interrogation. In this study, a targeted exome and whole transcriptome analysis were performed to identify predictive biomarkers of metformin response in drug-naïve T2DM individuals.

METHODS

The study followed a prospective study design. Drug-naïve T2DM individuals (n = 192) and controls (n = 223) were enrolled. T2DM individuals were administered with metformin monotherapy and defined as responders and non-responders based on their glycated haemoglobin change over three months. 146 T2DM individuals were used for the final analysis and remaining samples were lost during the follow-up. Target exome sequencing and RNA-seq was performed to analyze genetic and transcriptome profile. The selected SNPs were validated by genotyping and allele specific gene expression using the TaqMan assay. The gene prioritization, enrichment analysis, drug-gene interactions, disease-gene association, and correlation analysis were performed using various tools and databases.

RESULTS

rs1050152 and rs272893 in SLC22A4 were associated with improved response to metformin. The copy number loss was observed in PPARGC1A in the non-responders. The expression analysis highlighted potential differentially expressed targets for predicting metformin response (n = 35) and T2DM (n = 14). The expression of GDF15, TWISTNB, and RPL36A genes showed a maximum correlation with the change in HbA1c levels. The disease-gene association analysis highlighted MAGI2 rs113805659 to be linked with T2DM.

CONCLUSION

The results provide evidence for the genetic variations, perturbed transcriptome, allele-specific gene expression, and pathways associated with metformin drug response in T2DM.

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.

A population study of clinically actionable genetic variation affecting drug response from the Middle East

Clinical implementation of pharmacogenomics will help in personalizing drug prescriptions and alleviate the personal and financial burden due to inefficacy and adverse reactions to drugs. However, such implementation is lagging in many parts of the world, including the Middle East, mainly due to the lack of data on the distribution of actionable pharmacogenomic variation in these ethnicities. We analyzed 6,045 whole genomes from the Qatari population for the distribution of allele frequencies of 2,629 variants in 1,026 genes known to affect 559 drugs or classes of drugs. We also performed a focused analysis of genotypes or diplotypes of 15 genes affecting 46 drugs, which have guidelines for clinical implementation and predicted their phenotypic impact. The allele frequencies of 1,320 variants in 703 genes affecting 299 drugs or class of drugs were significantly different between the Qatari population and other world populations. On average, Qataris carry 3.6 actionable genotypes/diplotypes, affecting 13 drugs with guidelines for clinical implementation, and 99.5% of the individuals had at least one clinically actionable genotype/diplotype. Increased risk of simvastatin-induced myopathy could be predicted in ~32% of Qataris from the diplotypes of SLCO1B1, which is higher compared to many other populations, while fewer Qataris may need tacrolimus dosage adjustments for achieving immunosuppression based on the CYP3A5 diplotypes compared to other world populations. Distinct distribution of actionable pharmacogenomic variation was also observed among the Qatari subpopulations. Our comprehensive study of the distribution of actionable genetic variation affecting drugs in a Middle Eastern population has potential implications for preemptive pharmacogenomic implementation in the region and beyond.

Association of SLC22A1 rs622342 and ATM rs11212617 polymorphisms with metformin efficacy in patients with type 2 diabetes

Metformin is the first-choice oral anti-hyperglycemic drug for type 2 diabetes mellitus (T2DM) patients. There are controversies about the association of SLC22A1 rs622342, which was not reported in the Chinese population, and ataxia-telangiectasia mutated (ATM) rs11212617 polymorphisms with metformin efficacy in T2DM. Our study was to investigate the effects of the two single nucleotide polymorphisms on the efficacy of metformin in T2DM of Han nationality in Chaoshan China. After enrollment, 82 newly diagnosed T2DM patients went on 2-month metformin monotherapy. According to BMI before treatment, the patients were divided into a normal weight group (≥18.5 and <25 kg/m2) and an overweight group (BMI ≥ 25 and <30 kg/m2). T-test, Pearson χ2 test, and regression analysis, which adjusted for age, BMI, sex, the dose of metformin, education, tea drink, smoking, and sweet, were used to evaluate the effects of rs622342 and rs11212617 on several variables, such as fasting plasma glucose (FPG). Compared with the AA or CC genotype, patients with AC genotype of rs622342 achieved greater reduction in Δ60FPG and Δ(60-30)FPG (P = 0.00820, 0.00089, respectively). For 11212617, the reduction in Δ30FPG and Δ60FPG was significantly different among patients with the AC genotype (P = 0.00026, 0.00820, respectively). Our results indicated that common variants of SLC22A1 rs622342 and ATM rs11212617 were associated with the efficacy of metformin in T2DM of Han nationality in Chaoshan China.

Genetic variants in SLC22A1 are related to serum lipid levels in Mexican women

Dyslipidemia is the main risk factor for coronary artery disease and is characterized by alterations in concentrations of lipids, including low-density lipoprotein cholesterol (LDL-c), high-density lipoprotein cholesterol (HDL-c), and triacylglycerols. The participation of several genes in the development of dyslipidemia has been evidenced. Genetic variants in SLC22A1 have been associated with elevated cholesterol and LDL-c levels. The aim of this study was to evaluate the association between single-nucleotide polymorphisms (SNPs) in the SLC22A1 gene with atherogenic risk lipid levels in Mexican women. Anthropometric and biochemical measurements were performed, and four SNPs in SLC22A1 were genotyped by real-time polymerase chain reaction. The Hardy-Weinberg equilibrium was verified, and haplotype frequencies were calculated. We found significant differences between the allele frequencies of the SNPs analyzed with those reported in Mexico and in the world, which could be due to differences in the historical admixture of the women studied. Generalized linear models were evaluated to determine the association between genotypes and haplotypes with lipids levels. We identified a significant increase in total cholesterol and LDL-c levels in women who were carriers of the GA and AG genotypes of the polymorphisms rs628031 and rs594709, respectively, significant effect that is also shown in a dominant inheritance model. Interestingly, we identified an important relationship of the AGC-GAT haplotype with the elevation in LDL-c levels and AGA-GAT haplotype with the elevation in HDL-c levels. On the other hand, we found a strong linkage disequilibrium between the polymorphisms studied. Our results show that variants in the SLC22A1 gene influence serum levels of atherogenic risk lipids, suggesting that these variants probably affect the function of organic cation transporter-1 and therefore, on the regulation of lipid metabolism.

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.

Current progress in pharmacogenomics of Type 2 diabetes: A systemic overview

INTRODUCTION

Type 2 diabetes mellitus (T2DM) is a prevalent disease with incidences increasing globally at a rapid rate. The goal of T2DM treatment is to control glucose levels and prevent the aggravation of glycemic symptoms.

TREATMENT OPTIONS

T2DM regimen include metformin as the first-line, with sulfonylurea, thiazolidinedione (TZD), GLP-1, DPP4I, and SGLT2 inhibitor as the second-line treatment options. However, even with a multitude of choices, patient-to-patient variability due to pharmacogenomic differences still prevail.

CONCLUSION

This review aims to discuss the responses of the major T2DM medications influenced by pharmacogenomics and investigate improved personalized therapy for T2DM patients.

Population pharmacokinetics and pharmacogenetics of ritonavir-boosted darunavir in the presence of raltegravir or tenofovir disoproxil fumarate/emtricitabine in HIV-infected adults and the relationship with virological response: a sub-study of the NEAT001/ANRS143 randomized trial

OBJECTIVES

NEAT001/ANRS143 demonstrated non-inferiority of once-daily darunavir/ritonavir (800/100 mg) + twice-daily raltegravir (400 mg) versus darunavir/ritonavir + tenofovir disoproxil fumarate/emtricitabine (245/200 mg once daily) in treatment-naive patients. We investigated the population pharmacokinetics of darunavir, ritonavir, tenofovir and emtricitabine and relationships with demographics, genetic polymorphisms and virological failure.

METHODS

Non-linear mixed-effects models (NONMEM v. 7.3) were applied to determine pharmacokinetic parameters and assess demographic covariates and relationships with SNPs (SLCO3A1, SLCO1B1, NR1I2, NR1I3, CYP3A5*3, CYP3A4*22, ABCC2, ABCC10, ABCG2 and SCL47A1). The relationship between model-predicted darunavir AUC0-24 and C24 with time to virological failure was evaluated by Cox regression.

RESULTS

Of 805 enrolled, 716, 720, 347 and 361 were included in the darunavir, ritonavir, tenofovir and emtricitabine models, respectively (11% female, 83% Caucasian). No significant effect of patient demographics or SNPs was observed for darunavir or tenofovir apparent oral clearance (CL/F); coadministration of raltegravir did not influence darunavir or ritonavir CL/F. Ritonavir CL/F decreased by 23% in NR1I2 63396C>T carriers and emtricitabine CL/F was linearly associated with creatinine clearance (P<0.001). No significant relationship was demonstrated between darunavir AUC0-24 or C24 and time to virological failure [HR (95% CI): 2.28 (0.53-9.80), P=0.269; and 1.82 (0.61-5.41), P=0.279, respectively].

CONCLUSIONS

Darunavir concentrations were unaltered in the presence of raltegravir and not associated with virological failure. Polymorphisms investigated had little impact on study-drug pharmacokinetics. Darunavir/ritonavir + raltegravir may be an appropriate option for patients experiencing NRTI-associated toxicity.

A Two-Stage Study Identifies Two Novel Polymorphisms in PRKAG2 Affecting Metformin Response in Chinese Type 2 Diabetes Patients

Objective

Individual differences in glycemic response to metformin in antidiabetic treatment exist widely. Although some associated genetic variations have been discovered, they still cannot accurately predict metformin response. In the current study, we set out to investigate novel genetic variants affecting metformin response in Chinese type 2 diabetes (T2D) patients.

Methods

A two-stage study enrolled 500 T2D patients who received metformin, glibenclamide or a combination of both were recruited from 2009 to 2012 in China. Change of HbA_1c, adjusted by clinical covariates, was used to evaluate glycemic response to metformin. Selected single nucleotide polymorphisms (SNPs) were genotyped using the Infinium iSelect and/or Illumina GoldenGate genotyping platform. A linear regression model was used to evaluate the association between SNPs and response.

Results

A total of 3739 SNPs were screened in Stage 1, of which 50 were associated with drug response. Except for one genetic variant preferred to affect glibenclamide, the remaining SNPs were subsequently verified in Stage 2, and two SNPs were successfully validated. These were PRKAG2 rs2727528 (discovery group: β=−0.212, P=0.046; validation group: β=−0.269, P=0.028) and PRKAG2 rs1105842 (discovery group: β=0.205, P=0.048; validation group: β=0.273, P=0.025). C allele carriers of rs2727528 and C allele carriers of rs1105842 would have a larger difference of HbA_1c level when using metformin.

Conclusion

Two variants rs2727528 and rs1105842 in PRKAG2, encoding γ2 subunit of AMP-activated protein kinase (AMPK), were found to be associated with metformin response in Chinese T2D patients. These findings may provide some novel information for personalized pharmacotherapy of metformin in China.

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.

Pharmacogenetics of Type 2 Diabetes-Progress and Prospects

Type 2 diabetes mellitus (T2D) is a chronic metabolic disease resulting from insulin resistance and progressively reduced insulin secretion, which leads to impaired glucose utilization, dyslipidemia and hyperinsulinemia and progressive pancreatic beta cell dysfunction. The incidence of type 2 diabetes mellitus is increasing worldwide and nowadays T2D already became a global epidemic. The well-known interindividual variability of T2D drug actions such as biguanides, sulfonylureas/meglitinides, DPP-4 inhibitors/GLP1R agonists and SGLT-2 inhibitors may be caused, among other things, by genetic factors. Pharmacogenetic findings may aid in identifying new drug targets and obtaining in-depth knowledge of the causes of disease and its physiological processes, thereby, providing an opportunity to elaborate an algorithm for tailor or precision treatment. The aim of this article is to summarize recent progress and discoveries for T2D pharmacogenetics and to discuss the factors which limit the furthering accumulation of genetic variability knowledge in patient response to therapy that will allow improvement the personalized treatment of T2D.

Pharmacogenetic Aspects of Type 2 Diabetes Treatment

In this article, we analyze the role of different variants of the KCNJ11, TCF7L2, SLC22A1, SLC22A3, CYP2C9, CYP2C8, PPARγ genes polymorphisms in efficacy of diabetes mellitus pharmacotherapy. T allele of the KCNJ11 rs2285676 gene polymorphism and G allele of KCNJ11 rs5218 gene polymorphism are associated with the response to IDPP-4 therapy; the presence of KCNJ11 gene rs5210 polymorphism A allele is a predictor of poor response. The effect of rs7903146 polymorphism of TCF7L2 gene was evaluated on the response to treatment of patients taking linagliptin. Linagliptin significantly reduced HbA1c levels for all three rs7903146 genotypes (CC: –0.82 %; CT: –0.77 %; TT: –0.57 %). A significantly smaller effect of therapy was observed with the genotype with ТТ. The rs622342 polymorphism of SLC22A1 gene was studied in effectiveness of metformin. The researches demonstrated that carriers of variant AA had an average decrease of HbA1c of 0.53 %, heterozygous – decrease of 0.32 %, and carriers of a minor variant of SS had an increase of 0.2 % in the level of HbA1c. A significant effect of CYP2C9 polymorphisms on the pharmacokinetic parameters of PSM was noted. When studying the kinetics of glibenclamide, it was found that carriage of the allele *2 significantly reduces glibenclamide metabolism: homozygous carriers had clearance 90 % lower than homozygous carriers of the wild variant. The studies confirmed the association of the allelic variants of Thr394Thr and Gly482Ser of PPARγ gene with higher efficacy of the rosiglitazone. The data obtained from the analysis of the association of the Pro12Ala polymorphism of PPARγ gene and the response to therapy is contradictory. Thus the personalized approach, based on the knowledge of polymorphism options, will allow choosing the most effective drug with transparent kinetics for each individual patient.

Role of SLC transporters in toxicity induced by anticancer drugs

INTRODUCTION

. Membrane transporters are integral to the maintenance of cellular integrity of all tissue and cell types. While transporters play an established role in the systemic pharmacokinetics of therapeutic drugs, tissue specific expression of uptake transporters can serve as an initiating mechanism that governs the accumulation and impact of cytotoxic drugs.

AREAS COVERED

. This review provides an overview of organic cation transporters as determinants of chemotherapy-induced toxicities. We also provide insights into the recently updated FDA guidelines for in vitro drug interaction studies, with a particular focus on the class of tyrosine kinase inhibitors as perpetrators of transporter-mediated drug interactions.

EXPERT OPINION

. Studies performed over the last few decades have highlighted the important role of basolateral uptake and apical efflux transporters in the pathophysiology of drug-induced organ damage. Increased understanding of the mechanisms that govern the accumulation of cytotoxic drugs has provided insights into the development of novel strategies to prevent debilitating toxicities. Furthermore, we argue that current regulatory guidelines provide inadequate recommendations for in vitro studies to identify substrates or inhibitors of drug transporters. Therefore, the translational and predictive power of FDA-approved drugs as modulators of transport function remains ambiguous and warrants further revision of the current guidelines.

Pharmacodynamics of Glyburide, Metformin, and Glyburide/Metformin Combination Therapy in the Treatment of Gestational Diabetes Mellitus

In gestational diabetes mellitus (GDM), women are unable to compensate for the increased insulin resistance during pregnancy. Data are limited regarding the pharmacodynamic effects of metformin and glyburide during pregnancy. This study characterized insulin sensitivity (SI), β-cell responsivity, and disposition index (DI) in women with GDM utilizing a mixed-meal tolerance test (MMTT) before and during treatment with glyburide monotherapy (GLY, n = 38), metformin monotherapy (MET, n = 34), or GLY and MET combination therapy (COMBO; n = 36). GLY significantly decreased dynamic β-cell responsivity (31%). MET and COMBO significantly increased SI (121% and 83%, respectively). Whereas GLY, MET, and COMBO improved DI, metformin (MET and COMBO) demonstrated a larger increase in DI (P = 0.05) and a larger decrease in MMTT peak glucose concentrations (P = 0.03) than subjects taking only GLY. Maximizing SI with MET followed by increasing β-cell responsivity with GLY or supplementing with insulin might be a more optimal strategy for GDM management than monotherapy.

Metformin strongly affects transcriptome of peripheral blood cells in healthy individuals

Metformin is a commonly used antihyperglycaemic agent for the treatment of type 2 diabetes mellitus. Nevertheless, the exact mechanisms of action, underlying the various therapeutic effects of metformin, remain elusive. The goal of this study was to evaluate the alterations in longitudinal whole-blood transcriptome profiles of healthy individuals after a one-week metformin intervention in order to identify the novel molecular targets and further prompt the discovery of predictive biomarkers of metformin response. Next generation sequencing-based transcriptome analysis revealed metformin-induced differential expression of genes involved in intestinal immune network for IgA production and cytokine-cytokine receptor interaction pathways. Significantly elevated faecal sIgA levels during administration of metformin, and its correlation with the expression of genes associated with immune response (CXCR4, HLA-DQA1, MAP3K14, TNFRSF21, CCL4, ACVR1B, PF4, EPOR, CXCL8) supports a novel hypothesis of strong association between metformin and intestinal immune system, and for the first time provide evidence for altered RNA expression as a contributing mechanism of metformin’s action. In addition to universal effects, 4 clusters of functionally related genes with a subject-specific differential expression were distinguished, including genes relevant to insulin production (HNF1B, HNF1A, HNF4A, GCK, INS, NEUROD1, PAX4, PDX1, ABCC8, KCNJ11) and cholesterol homeostasis (APOB, LDLR, PCSK9). This inter-individual variation of the metformin effect on the transcriptional regulation goes in line with well-known variability of the therapeutic response to the drug.

Common Variants in 22 Genes Regulate Response to Metformin Intervention in Children with Obesity: A Pharmacogenetic Study of a Randomized Controlled Trial

Metformin is a first-line oral antidiabetic agent that has shown additional effects in treating obesity and metabolic syndrome. Inter-individual variability in metformin response could be partially explained by the genetic component. Here, we aimed to test whether common genetic variants can predict the response to metformin intervention in obese children. The study was a multicenter and double-blind randomized controlled trial that was stratified according to sex and pubertal status in 160 children with obesity. Children were randomly assigned to receive either metformin (1g/d) or placebo for six months after meeting the defined inclusion criteria. We conducted a post hoc genotyping study in 124 individuals (59 placebo, 65 treated) comprising finally 231 genetic variants in candidate genes. We provide evidence for 28 common variants as promising pharmacogenetics regulators of metformin response in terms of a wide range of anthropometric and biochemical outcomes, including body mass index (BMI) Z-score, and glucose, lipid, and inflammatory traits. Although no association remained statistically significant after multiple-test correction, our findings support previously reported variants in metformin transporters or targets as well as identify novel and promising loci, such as the ADYC3 and the BDNF genes, with plausible biological relation to the metformin's action mechanism. Trial Registration: Registered on the European Clinical Trials Database (EudraCT, ID: 2010-023061-21) on 14 November 2011 (URL: https://www.clinicaltrialsregister.eu/ctr-search/trial/2010-023061-21/ES).

Clinical and genetic predictors of diabetes drug's response

Diabetes is a major health problem worldwide. Glycemic control is the main goal in the management of type 2 diabetes. While many anti-diabetic drugs and guidelines are available, almost half of diabetic patients do not reach their treatment goal and develop complications. The glucose-lowering response to anti-diabetic drug differs significantly between individuals. Relatively little is known about the factors that might underlie this response. The identification of predictors of response to anti-diabetic drugs is essential for treatment personalization. Unfortunately, the evidence on predictors of drugs response in type 2 diabetes is scarce. Only a few trials were designed for specific groups of patients (e.g. patients with renal impairment or older patients), while subgroup analyses of larger trials are frequently unreported. Physicians need help in picking the drug which provides the maximal benefit, with minimal side effects, in the right dose, for a specific patient, using an omics-based approach besides the phenotypic characteristics.

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.

The influence of SLC22A1 rs622342 and ABCC8 rs757110 genetic variants on the efficacy of metformin and glimepiride combination therapy in Egyptian patients with type 2 diabetes

Background: The incidence of Type 2 Diabetes Mellitus (T2DM) in Egypt is considered one of the highest in the world. Metformin and Sulfonylureas are usually prescribed together due to their efficacy and their relatively low cost. Organic cation transport 1, encoded by SLC22A1 gene, is the main transporter of metformin into hepatocytes, which is considered metformin site of action. Sulfonylureas enhance insulin release from pancreatic B-cells through binding to sulfonylurea receptor 1, encoded by ABCC8 gene. Single nucleotide polymorphisms in the SLC22A1 and ABCC8 genes might affect the response of each drug.

Aims: To investigate the influence of SLC22A1 rs622342 (A>C) and ABCC8 rs757110 (A>C) genetic variants on the efficacy of metformin and glimepiride combination therapy in Egyptian T2DM patients.

Methods: Observational cross-sectional study in which patients receiving metformin and glimepiride combination therapy for at least 6 months were included for genotyping and classified into either responders or non-responders, based on their HbA1C level.

Results: A total of 127 patients were included and genotyped. They were divided into 93 responders (HbA1C<7%) and 34 non-responders (HbA1C≥7%). Minor allele frequencies for rs622342 and rs757110 were 0.189 and 0.271, respectively. Only SLC22A1 rs622342 variant was found to be associated with the response of combination therapy, in which AA alleles carriers were 2.7-times more responsive to metformin than C allele carriers (Recessive model, odds ratio = 2.718, p = 0.025, 95% CI = 1.112–6.385).

Conclusion: Genotyping of rs622342 can be useful in predicting the response to metformin in combination therapy in Egyptian T2DM patients.

Altered Glycemic Control Associated With Polymorphisms in the SLC22A1 (OCT1) Gene in a Mexican Population With Type 2 Diabetes Mellitus Treated With Metformin: A Cohort Study

The organic cation transporters OCT1 and OCT2 and the multidrug and toxin extrusion transporter MATE1, encoded by the SLC22A1, SLC22A2, and SLC47A1 genes, respectively, are responsible for the absorption of metformin in enterocytes, hepatocytes, and kidney cells. The aim of this study was to evaluate whether genetic variations in the SLC22A1, SLC22A2, and SLC47A1 genes could be associated with an altered response to metformin in patients with type 2 diabetes mellitus. A cohort study was conducted in 308 individuals with a diagnosis of type 2 diabetes mellitus of less than 3 years and who had metformin monotherapy. Three measurements of blood glycated hemoglobin (HbA_1c ) were obtained at the beginning of the study and after 6 and 12 months. Five polymorphisms were analyzed in the SLC22A1 (rs622342, rs628031, rs594709), SLC22A2 (rs316019), and SLC47A1 (rs2289669) genes by real-time polymerase chain reaction. The results showed a significant association among genotypes CC-rs622342 (β = 1.36; P < .001), AA-rs628031 (β = 0.98; P = .032), and GG-rs594709 (β = 1.21; P = .016) in the SLC22A1 gene with an increase in HbA_1c levels during the follow-up period. Additionally, a significant association was found in the CGA and CAG haplotypes with an increase in HbA_1c levels compared to the highest-frequency haplotype (AGA). In conclusion, the genetic variation in the SLC22A1 gene was significantly related to the variation of the HbA_1c levels, an important indicator of glycemic control in diabetic patients. This information may contribute to identifying patients with an altered response to metformin before starting their therapy.

Metformin Pharmacogenetics: Effects of SLC22A1, SLC22A2, and SLC22A3 Polymorphisms on Glycemic Control and HbA1c Levels

Type 2 diabetes mellitus (T2DM) constitutes a major portion of Jordan’s disease burden, and incidence rates are rising at a rapid rate. Due to variability in the drug’s response between ethnic groups, it is imperative that the pharmacogenetics of metformin be investigated in the Jordanian population. The objective of this study was to investigate the relationship between twenty-one single nucleotide polymorphisms (SNPs) in the SLC22A1, SLC22A2, and SLC22A3 genes and their effects on metformin pharmacogenetics in Jordanian patients diagnosed with type 2 diabetes mellitus. Blood samples were collected from 212 Jordanian diabetics who fulfilled the inclusion criteria, which were then used in SNP genotyping and determination of HbA1c levels. The rs12194182 SNP in the SLC22A3 gene was found to have a significant association (p < 0.05) with lower mean HbA1c levels, and this association more pronounced in patients with the CC genotype (i.e., p-value was significant before correcting for multiple testing). Moreover, the multinomial logistic regression analysis showed that SNP genotypes within the SLC22A1, SLC22A2, and SLC22A3 genes, body mass index (BMI) and age of diagnosis were significantly associated with glycemic control (p < 0.05). The results of this study can be used to predict response to metformin and other classes of T2DM drugs, making treatment more individualized and resulting in better clinical outcomes.

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.

Predictors of cisplatin-induced ototoxicity and survival in chemoradiation treated head and neck cancer patients

OBJECTIVES

Cisplatin-induced ototoxicity is a common permanent consequence of curative chemoradiation for locally advanced head and neck squamous cell carcinoma (HNSCC). Predictors of ototoxicity in HNSCC were examined.

MATERIALS AND METHODS

In this prospective, observational cohort study, 206 adult HNSCC patients underwent audiometric testing at baseline, during and after treatment with cisplatin-based chemoradiation. Ototoxicity was defined as ≥grade 2 audiometric change from baseline (CTCAE v4.02). Relationships between clinical and pharmacogenetic (TPMT, COMT, ACYP2, CTR1, OCT2, MATE1, ABCC2, ABCC3, and ABCG2) covariates and ototoxicity, progression-free (PFS) and overall survival (OS) were assessed by Cox regression.

RESULTS

Weekly cisplatin resulted in lower ototoxicity risk while PFS and OS were similar compared to high dose cisplatin (P = 0.00035; HR = 0.18; 95% CI, 0.07-0.46). COMT (rs9332377) carriers had higher ototoxicity risk (P = 0.00556; HR = 1.72; 95% CI, 1.17-2.52) while MATE1 (rs2289669) A/A carriers were protected from ototoxicity (P = 0.01062; HR = 0.46; 95% CI, 0.26-0.84). Absence of the protective MATE1 allele among those who carry the risk allele in COMT predicted increased ototoxicity risk, (P = 0.00414; HR = 3.22; 95% CI, 1.45-7.17 and P = 0.00022; HR = 4.89; 95% CI, 2.11-11.36). Survival outcomes did not differ between carriers of protective or risk alleles.

CONCLUSIONS

Weekly cisplatin dosing, COMT and MATE1 are predictors of ototoxicity without affecting treatment efficacy. COMT and MATE1 genotyping and weekly dosing may be a potential strategy for mitigating cisplatin-induced ototoxicity in HNSCC.

Metformin transporter pharmacogenomics: insights into drug disposition-where are we now?

INTRODUCTION

Metformin is recommended as first-line treatment for type 2 diabetes (T2D) by all major diabetes guidelines. With appropriate usage it is safe and effective overall, but its efficacy and tolerability show considerable variation between individuals. It is a substrate for several drug transporters and polymorphisms in these transporter genes have shown effects on metformin pharmacokinetics and pharmacodynamics. Areas covered: This article provides a review of the current status of the influence of transporter pharmacogenomics on metformin efficacy and tolerability. The transporter variants identified to have an important influence on the absorption, distribution, and elimination of metformin, particularly those in organic cation transporter 1 (OCT1, gene SLC22A1), are reviewed. Expert opinion: Candidate gene studies have shown that genetic variations in SLC22A1 and other drug transporters influence the pharmacokinetics, glycemic responses, and gastrointestinal intolerance to metformin, although results are somewhat discordant. Conversely, genome-wide association studies of metformin response have identified signals in the pharmacodynamic pathways rather than the transporters involved in metformin disposition. Currently, pharmacogenomic testing to predict metformin response and tolerability may not have a clinical role, but with additional data from larger studies and availability of safe and effective alternative antidiabetic agents, this is likely to change.

Genetic polymorphisms of organic cation transporter 1 (OCT1) and responses to metformin therapy in individuals with type 2 diabetes: A systematic review

BACKGROUND

Metformin is one of the most commonly used drugs for the treatment of type 2 diabetes mellitus (T2DM). Despite its widespread use, there are considerable interindividual variations in metformin response, with about 35% of patients failing to achieve initial glycemic control. These variabilities that reflect phenotypic differences in drug disposition and action may indeed be due to polymorphisms in genes that regulate pharmacokinetics and pharmacodynamics of metformin. Moreover, interethnic differences in drug responses in some cases correspond to substantial differences in the frequencies of the associated pharmacogenomics risk allele.

AIM

This study aims to highlight and summarize the overall effects of organic cation transporter 1(OCT1) polymorphisms on therapeutic responses to metformin and to evaluate the potential role of such polymorphisms in interethnic differences in metformin therapy.

METHODS

We conducted a systematic review according to the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) guidelines. We searched for PubMed/MEDLINE, Embase, and CINAHL, relevant studies reporting the effects of OCT1 polymorphisms on metformin therapy in T2DM individuals. Data were extracted on study design, population characteristics, relevant polymorphisms, measure of genetic association, and outcomes. The presence of gastrointestinal side effects, glycated hemoglobin A1 (HbA1c) levels, fasting plasma glucose (FPG), and postprandial plasma glucose (PPG) concentrations after treatment with metformin were chosen as measures of the metformin responses. This systematic review protocol was registered with the International Prospective Register of Systematic Reviews (PROSPERO).

RESULTS

According to the data extracted, a total of 34 OCT1 polymorphisms were identified in 10 ethnic groups. Significant differences in the frequencies of common alleles were observed among these groups. Met408Val (rs628031) variant was the most extensively explored with metformin responses. Although some genotypes and alleles have been associated with deleterious effects on metformin response, others indeed, exhibited positive effects.

CONCLUSION

Genetic effects of OCT1 polymorphisms on metformin responses were population specific. Further investigations in other populations are required to set ethnicity-specific reference for metformin responses and to obtain a solid basis to design personalized therapeutic approaches for T2DM treatment.

Implication of critical pharmacokinetic gene variants on therapeutic response to metformin in Type 2 diabetes

Aim: Metformin, an oral hypoglycemic drug is the first line of treatment for Type 2 diabetes individuals. We studied the effect of critical gene single nucleotide polymorphisms  on the glucose lowering effect of metformin. Method: We performed a prospective study on 221 newly diagnosed, treatment-naive Type 2 diabetes subjects. Individuals were started with metformin monotherapy and followed up for 12 weeks. Results: Our association analysis revealed that SLC22A2 rs316019 and SLC47A2 rs12943590 were significantly associated with metformin drug response across co-dominant and dominant models, respectively. SLC22A2 rs316019 GG and SLC47A2 rs12943590 GA combined genotypes showed maximum average change in HbA1c level. Conclusion: The present study proposes a role of SLC22A2 rs316019 and SLC47A2 rs12943590 in the pharmacokinetic action of metformin.

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.

Pharmacogenetics of Antidiabetic Drugs

Pharmacogenetic studies of antidiabetic drugs have so far focused largely on response to metformin, which is the first-line therapy for treatment of type 2 diabetes (T2D). The first studies of metformin pharmacogenetics were focused on candidate genes that were implicated in metformin pharmacokinetics and transport. Since 2011, genome-wide association studies have been conducted in large cohorts of individuals with T2D identifying genes that are associated with glycemic response to metformin. There have been fewer pharmacogenetic studies of other antidiabetic drugs, and those have been largely limited to candidate gene studies with small sample sizes. Understanding the pharmacogenetics of antidiabetes medications is important for the integration of genetic screening into therapeutic decision making, and to achieve the goal of "precision medicine" for patients with T2D. In this chapter, we provide a review of the pharmacogenetics investigations of metformin and other antidiabetes medications. In addition, we highlight the importance of collaborative efforts with large sample size and representation from multiple ethnic groups in pharmacogenetics studies.

SLC04A1, SLC22A2 and SLC28A2 variants not related to methotrexate efficacy or toxicity in rheumatoid arthritis patients

AIM

A third of rheumatoid arthritis patients discontinue methotrexate treatment due to inefficacy or toxic side effects. Recently, an association between SLC04A1 rs2236553, SLC22A2 rs624249 and rs316019, and SLC28A2 rs10519020 and rs1060896 with the efficacy and toxicity of methotrexate was reported. This study aims to replicate these findings in an independent cohort (n = 324).

METHODS

Regression analyses tested the associations between genotype and methotrexate response or toxicity.

RESULTS

In the discovery study, there was a significant association between toxicity and rs624249, and rs1060896. These associations were not replicated in the independent cohort. Neither study observed an association between methotrexate efficacy and SLC04A1, SLC22A2 or SLC28A2 variants.

CONCLUSION

Current evidence does not support associations between variants in SLC04A1, SLC22A2 and SLC28A2 with methotrexate efficacy or toxicity.

Genotypic and Phenotypic Factors Influencing Drug Response in Mexican Patients With Type 2 Diabetes Mellitus

The treatment of Type 2 Diabetes Mellitus (T2DM) consists primarily of oral antidiabetic drugs (OADs) that stimulate insulin secretion, such as sulfonylureas (SUs) and reduce hepatic glucose production (e.g., biguanides), among others. The marked inter-individual differences among T2DM patients’ response to these drugs have become an issue on prescribing and dosing efficiently. In this study, fourteen polymorphisms selected from Genome-wide association studies (GWAS) were screened in 495 T2DM Mexican patients previously treated with OADs to find the relationship between the presence of these polymorphisms and response to the OADs. Then, a novel association screening method, based on global probabilities, was used to globally characterize important relationships between the drug response to OADs and genetic and clinical parameters, including polymorphisms, patient information, and type of treatment. Two polymorphisms, ABCC8-Ala1369Ser and KCNJ11-Glu23Lys, showed a significant impact on response to SUs. Heterozygous ABCC8-Ala1369Ser variant (A/C) carriers exhibited a higher response to SUs compared to homozygous ABCC8-Ala1369Ser variant (A/A) carriers (p-value = 0.029) and to homozygous wild-type genotypes (C/C) (p-value = 0.012). The homozygous KCNJ11-Glu23Lys variant (C/C) and wild-type (T/T) genotypes had a lower response to SUs compared to heterozygous (C/T) carriers (p-value = 0.039). The screening of OADs response related genetic and clinical factors could help improve the prescribing and dosing of OADs for T2DM patients and thus contribute to the design of personalized treatments.

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

The Effect of Famotidine, a MATE1-Selective Inhibitor, on the Pharmacokinetics and Pharmacodynamics of Metformin

INTRODUCTION

Pharmacokinetic outcomes of transporter-mediated drug-drug interactions (TMDDIs) are increasingly being evaluated clinically. The goal of our study was to determine the effects of selective inhibition of multidrug and toxin extrusion protein 1 (MATE1), using famotidine, on the pharmacokinetics and pharmacodynamics of metformin in healthy volunteers.

METHODS

Volunteers received metformin alone or with famotidine in a crossover design. As a positive control, the longitudinal effects of famotidine on the plasma levels of creatinine (an endogenous substrate of MATE1) were quantified in parallel. Famotidine unbound concentrations in plasma reached 1 µM, thus exceeding the in vitro concentrations that inhibit MATE1 [concentration of drug producing 50 % inhibition (IC50) 0.25 µM]. Based on current regulatory guidance, these concentrations are expected to inhibit MATE1 clinically [i.e. maximum unbound plasma drug concentration (C max,u)/IC50 >0.1].

RESULTS

Consistent with MATE1 inhibition, famotidine administration significantly altered creatinine plasma and urine levels in opposing directions (p < 0.005). Interestingly, famotidine increased the estimated bioavailability of metformin [cumulative amount of unchanged drug excreted in urine from time zero to infinity (A e∞)/dose; p < 0.005] without affecting its systemic exposure [area under the plasma concentration-time curve (AUC) or maximum concentration in plasma (C max)] as a result of a counteracting increase in metformin renal clearance. Moreover, metformin-famotidine co-therapy caused a transient effect on oral glucose tolerance tests [area under the glucose plasma concentration-time curve between time zero and 0.5 h (AUCglu,0.5); p < 0.005].

CONCLUSIONS

These results suggest that famotidine may improve the bioavailability and enhance the renal clearance of metformin.

The pharmacogenetics of metformin

Despite its widespread use as the first-line agent for the treatment of type 2 diabetes, it has become clear that metformin does not work optimally for everyone. Elucidating who are the likely metformin responders and non-responders is hampered by our limited knowledge of its precise molecular mechanism of action. One approach to achieve the related goals of stratifying patients into response subgroups and identifying the molecular targets of metformin involves the deployment of agnostic genome-wide approaches in cohorts of appropriate size to attain sufficient statistical power. While candidate gene studies have shed some light on the role of genetic variation in influencing metformin response, genome-wide association studies are beginning to provide additional insight that is unconstrained by prior knowledge. To fully realise their potential, much larger samples need to be assembled via international collaboration, preferably involving the academic community, government and the pharmaceutical industry.

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.