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1
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Chávez-Arreola OI, Lazalde B, López-López M, Ortega-Vázquez A, Torres-Salazar QL. Allele frequencies and genotype distribution of three metformin transporter polymorphisms in Mexican population and their application in pharmacogenomics of type 2 diabetes. Front Pharmacol 2024; 15:1466394. [PMID: 39555090 PMCID: PMC11565514 DOI: 10.3389/fphar.2024.1466394] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2024] [Accepted: 10/18/2024] [Indexed: 11/19/2024] Open
Abstract
Background Metformin is the first-line antidiabetic therapy for type 2 diabetes in Mexico, despite recent recommendations highlighting alternatives like GLP-1 receptor agonists for individuals with obesity. Metformin elimination is reliant on liver and kidney function, and variants in transport proteins such as Multidrug and Toxin Extrusion Protein 1 (MATE1), MATE2, and Organic Cation Transporter 2 (OCT2) can influence its pharmacokinetics. Understanding these variants' frequencies in the Mexican population is crucial for tailoring personalized treatment strategies. Objective This study aimed to determine the genotypic and allelic frequencies of key variants in metformin transporters within a Mexican population, addressing the interindividual variability in drug response. Methodology Genetic analysis was conducted on 101 healthy, unrelated Mexican subjects who were genotyped for the MATE1, MATE2, and OCT2 variants using allele-specific real-time PCR assays. Results The allele frequencies were 0.07 for OCT2, 0.23 for MATE1, and 0.67 for MATE2. The g.-66T→C variant was found only in wild-type and heterozygous forms. Comparative analysis indicated significant differences in allele frequencies between this Mexican population and other ethnic groups, highlighting potential implications for metformin efficacy and safety. Conclusion This study provides crucial insights into the genetic variability of metformin transporter genes in a Mexican population, offering a foundation for personalized therapeutic approaches in type 2 diabetes management.
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Affiliation(s)
| | | | - Marisol López-López
- Department of Biological Systems, Metropolitan Autonomous University-Xochimilco, México City, Mexico
| | - Alberto Ortega-Vázquez
- Biomedical Research Unit, Mexican Social Security Institute, Durango, Mexico
- Department of Biological Systems, Metropolitan Autonomous University-Xochimilco, México City, Mexico
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Mustafa A, Shabbir M, Badshah Y, Khan K, Abid F, Trembley JH, Afsar T, Almajwal A, Razak S. Genetic polymorphism in untranslated regions of PRKCZ influences mRNA structure, stability and binding sites. BMC Cancer 2024; 24:1147. [PMID: 39272077 PMCID: PMC11401371 DOI: 10.1186/s12885-024-12900-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2024] [Accepted: 09/04/2024] [Indexed: 09/15/2024] Open
Abstract
BACKGROUND Variations in untranslated regions (UTR) alter regulatory pathways impacting phenotype, disease onset, and course of disease. Protein kinase C Zeta (PRKCZ), a serine-threonine kinase, is implicated in cardiovascular, neurological and oncological disorders. Due to limited research on PRKCZ, this study aimed to investigate the impact of UTR genetic variants' on binding sites for transcription factors and miRNA. RNA secondary structure, eQTLs, and variation tolerance analysis were also part of the study. METHODS The data related to PRKCZ gene variants was downloaded from the Ensembl genome browser, COSMIC and gnomAD. The RegulomeDB database was used to assess the functional impact of 5' UTR and 3'UTR variants. The analysis of the transcription binding sites (TFBS) was done through the Alibaba tool, and the Kyoto Encyclopaedia of Genes and Genomes (KEGG) was employed to identify pathways associated with PRKCZ. To predict the effect of variants on microRNA binding sites, PolymiRTS was utilized for 3' UTR variants, and the SNPinfo tool was used for 5' UTR variants. RESULTS The results obtained indicated that a total of 24 variants present in the 3' UTR and 25 variants present in the 5' UTR were most detrimental. TFBS analysis revealed that 5' UTR variants added YY1, repressor, and Oct1, whereas 3' UTR variants added AP-2alpha, AhR, Da, GR, and USF binding sites. The study predicted TFs that influenced PRKCZ expression. RNA secondary structure analysis showed that eight 5' UTR and six 3' UTR altered the RNA structure by either removal or addition of the stem-loop. The microRNA binding site analysis highlighted that seven 3' UTR and one 5' UTR variant altered the conserved site and also created new binding sites. eQTLs analysis showed that one variant was associated with PRKCZ expression in the lung and thyroid. The variation tolerance analysis revealed that PRKCZ was an intolerant gene. CONCLUSION This study laid the groundwork for future studies aimed at targeting PRKCZ as a therapeutic target.
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Affiliation(s)
- Aneela Mustafa
- Department of Healthcare BiotechnologyAtta-Ur-Rahman School of Applied Biosciences (ASAB), National University of Sciences and Technology (NUST), Sector H-12, Islamabad, 44000, Pakistan
| | - Maria Shabbir
- Department of Healthcare BiotechnologyAtta-Ur-Rahman School of Applied Biosciences (ASAB), National University of Sciences and Technology (NUST), Sector H-12, Islamabad, 44000, Pakistan.
| | - Yasmin Badshah
- Department of Healthcare BiotechnologyAtta-Ur-Rahman School of Applied Biosciences (ASAB), National University of Sciences and Technology (NUST), Sector H-12, Islamabad, 44000, Pakistan
| | | | - Fizzah Abid
- Department of Healthcare BiotechnologyAtta-Ur-Rahman School of Applied Biosciences (ASAB), National University of Sciences and Technology (NUST), Sector H-12, Islamabad, 44000, Pakistan
| | - Janeen H Trembley
- Minneapolis VA Health Care System Research Service, Minneapolis, MN, USA
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN, USA
- Masonic Cancer Center, University of Minnesota, Minneapolis, MN, USA
| | - Tayyaba Afsar
- Department of Community Health Sciences, College of Applied Medical Sciences, King Saud University, Riyadh, Saudi Arabia
| | - Ali Almajwal
- Department of Community Health Sciences, College of Applied Medical Sciences, King Saud University, Riyadh, Saudi Arabia
| | - Suhail Razak
- Department of Community Health Sciences, College of Applied Medical Sciences, King Saud University, Riyadh, Saudi Arabia.
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3
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Feng J, Zhu Z, Zhou R, Liu H, Hu Z, Wu F, Wang H, Yue J, Zhou T, Yang L, Wu F. Differential methylation patterns from clusters associated with glucose metabolism: evidence from a Shanghai twin study. Epigenomics 2024; 16:445-459. [PMID: 38410918 DOI: 10.2217/epi-2023-0449] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/28/2024] Open
Abstract
Aim: To assess the associations between genome-wide DNA methylation (DNAm) and glucose metabolism among a Chinese population, in particular the multisite correlation. Materials & methods: Epigenome-wide associations with fasting plasma glucose (FPG) and hemoglobin A1c (HbA1c) were analyzed among 100 Shanghai monozygotic (MZ) twin pairs using the Infinium HumanMethylationEPIC v2.0 BeadChip. We conducted a Pearson's correlation test, hierarchical cluster and pairwise analysis to examine the differential methylation patterns from clusters. Results: Cg01358804 (TXNIP) was identified as the most significant site associated with FPG and HbA1c. Two clusters with hypermethylated and hypomethylated patterns were observed for both FPG and HbA1c. Conclusion: Differential methylation patterns from clusters may provide new clues for epigenetic changes and biological mechanisms in glucose metabolism.
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Affiliation(s)
- Jingyuan Feng
- School of Public Health, Fudan University, Shanghai, 200032, China
| | - Zhenni Zhu
- Division of Health Risk Factors Monitoring & Control, Shanghai Municipal Center for Disease Control & Prevention, 200336, Shanghai, China
| | - Rongfei Zhou
- School of Public Health, Fudan University, Shanghai, 200032, China
| | - Hongwei Liu
- School of Public Health, Fudan University, Shanghai, 200032, China
| | - Zihan Hu
- School of Public Health, Fudan University, Shanghai, 200032, China
| | - Fei Wu
- School of Public Health, Fudan University, Shanghai, 200032, China
| | - Huiting Wang
- School of Public Health, Fudan University, Shanghai, 200032, China
| | - Junhong Yue
- School of Public Health, Fudan University, Shanghai, 200032, China
| | - Tong Zhou
- Shanghai Precision Medicine Co. Ltd, Shanghai, 201406, China
| | - Li Yang
- Shanghai Precision Medicine Co. Ltd, Shanghai, 201406, China
| | - Fan Wu
- School of Public Health, Fudan University, Shanghai, 200032, China
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4
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Le J, Chen Y, Yang W, Chen L, Ye J. Metabolic basis of solute carrier transporters in treatment of type 2 diabetes mellitus. Acta Pharm Sin B 2024; 14:437-454. [PMID: 38322335 PMCID: PMC10840401 DOI: 10.1016/j.apsb.2023.09.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2023] [Revised: 07/10/2023] [Accepted: 08/09/2023] [Indexed: 02/08/2024] Open
Abstract
Solute carriers (SLCs) constitute the largest superfamily of membrane transporter proteins. These transporters, present in various SLC families, play a vital role in energy metabolism by facilitating the transport of diverse substances, including glucose, fatty acids, amino acids, nucleotides, and ions. They actively participate in the regulation of glucose metabolism at various steps, such as glucose uptake (e.g., SLC2A4/GLUT4), glucose reabsorption (e.g., SLC5A2/SGLT2), thermogenesis (e.g., SLC25A7/UCP-1), and ATP production (e.g., SLC25A4/ANT1 and SLC25A5/ANT2). The activities of these transporters contribute to the pathogenesis of type 2 diabetes mellitus (T2DM). Notably, SLC5A2 has emerged as a valid drug target for T2DM due to its role in renal glucose reabsorption, leading to groundbreaking advancements in diabetes drug discovery. Alongside SLC5A2, multiple families of SLC transporters involved in the regulation of glucose homeostasis hold potential applications for T2DM therapy. SLCs also impact drug metabolism of diabetic medicines through gene polymorphisms, such as rosiglitazone (SLCO1B1/OATP1B1) and metformin (SLC22A1-3/OCT1-3 and SLC47A1, 2/MATE1, 2). By consolidating insights into the biological activities and clinical relevance of SLC transporters in T2DM, this review offers a comprehensive update on their roles in controlling glucose metabolism as potential drug targets.
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Affiliation(s)
- Jiamei Le
- Shanghai Key Laboratory of Molecular Imaging, Zhoupu Hospital, Shanghai University of Medicine and Health Sciences, Shanghai 201318, China
- School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China
| | - Yilong Chen
- School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China
| | - Wei Yang
- Metabolic Disease Research Center, Zhengzhou Central Hospital Affiliated to Zhengzhou University, Zhengzhou 450007, China
| | - Ligong Chen
- School of Pharmaceutical Sciences, Tsinghua University, Beijing 100084, China
| | - Jianping Ye
- Metabolic Disease Research Center, Zhengzhou Central Hospital Affiliated to Zhengzhou University, Zhengzhou 450007, China
- Research Center for Basic Medicine, Academy of Medical Sciences, Zhengzhou University, Zhengzhou 450052, China
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Galiero R, Caturano A, Vetrano E, Monda M, Marfella R, Sardu C, Salvatore T, Rinaldi L, Sasso FC. Precision Medicine in Type 2 Diabetes Mellitus: Utility and Limitations. Diabetes Metab Syndr Obes 2023; 16:3669-3689. [PMID: 38028995 PMCID: PMC10658811 DOI: 10.2147/dmso.s390752] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/14/2023] [Accepted: 10/27/2023] [Indexed: 12/01/2023] Open
Abstract
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.
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Affiliation(s)
- Raffaele Galiero
- Department of Advanced Medical and Surgical Sciences, University of Campania “Luigi Vanvitelli”, Naples, Italy
| | - Alfredo Caturano
- Department of Advanced Medical and Surgical Sciences, University of Campania “Luigi Vanvitelli”, Naples, Italy
| | - Erica Vetrano
- Department of Advanced Medical and Surgical Sciences, University of Campania “Luigi Vanvitelli”, Naples, Italy
| | - Marcellino Monda
- Department of Experimental Medicine, University of Campania “Luigi Vanvitelli”, Naples, Italy
| | - Raffaele Marfella
- Department of Advanced Medical and Surgical Sciences, University of Campania “Luigi Vanvitelli”, Naples, Italy
| | - Celestino Sardu
- Department of Advanced Medical and Surgical Sciences, University of Campania “Luigi Vanvitelli”, Naples, Italy
| | - Teresa Salvatore
- Department of Precision Medicine, University of Campania “Luigi Vanvitelli”, Naples, Italy
| | - Luca Rinaldi
- Department of Advanced Medical and Surgical Sciences, University of Campania “Luigi Vanvitelli”, Naples, Italy
| | - Ferdinando Carlo Sasso
- Department of Advanced Medical and Surgical Sciences, University of Campania “Luigi Vanvitelli”, Naples, Italy
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Yokoyama S, Nakagawa J, Kudo M, Aiuchi N, Seito T, Isida M, Mikami T, Ihara K, Nakaji S, Niioka T. Impact of solute carrier transporter gene polymorphisms on serum creatinine concentrations in healthy volunteers. Pharmacol Res Perspect 2023; 11:e01048. [PMID: 36594679 PMCID: PMC9809111 DOI: 10.1002/prp2.1048] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Accepted: 12/11/2022] [Indexed: 01/04/2023] Open
Abstract
In this study, we investigated the impact of single nucleotide polymorphisms in solute carrier (SLC) transporters, that is, SLC22A7 c.1586 + 206A > G, SLC22A2 c.808G > T, SLC22A3 c.1233G > A, SLC47A1 c.922-158G > A, and SLC47A2 c.-130G > A, on serum creatinine (SCr) concentrations. This cross-sectional study included residents who participated as volunteers in a health promotion study. Lifestyle data, blood chemical analysis data, and SLC gene polymorphism information were collected from each participant. Univariate analyses were carried out to determine differences between groups and correlations in SCr. Stepwise multiple regression analysis was performed to confirm the independence of factors that were significantly different in the univariate analyses. In multiple regression analyses, muscle mass, serum cystatin C concentrations, body fat percentage, serum albumin concentrations, and SLC47A2 c.-130G/G had the highest contribution to SCr concentrations, in that order (standardized regression coefficients = .505, .332, -.234, .123, and .084, respectively). The final model explained 72.2% of the variability in SCr concentrations. The SLC47A2 c.-130G > A polymorphism may affect creatinine dynamics in the proximal tubules. Further studies are needed to determine the effects of SLC transporter gene polymorphisms on SCr concentrations in patients with various diseases in real-world clinical settings.
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Affiliation(s)
- Satoshi Yokoyama
- Department of Pharmaceutical ScienceHirosaki University Graduate School of MedicineHirosakiAomoriJapan
- Department of PharmacyHirosaki Central HospitalHirosakiAomoriJapan
| | - Junichi Nakagawa
- Department of PharmacyHirosaki University HospitalHirosakiAomoriJapan
| | - Masakiyo Kudo
- Department of PharmacyHirosaki University HospitalHirosakiAomoriJapan
| | - Naoya Aiuchi
- Department of PharmacyHirosaki University HospitalHirosakiAomoriJapan
| | - Tatsuya Seito
- Department of PharmacyHirosaki Central HospitalHirosakiAomoriJapan
| | - Mizuri Isida
- Department of Innovation Center for Health PromotionHirosaki University Graduate School of MedicineHirosakiAomoriJapan
| | - Tatsuya Mikami
- Department of Innovation Center for Health PromotionHirosaki University Graduate School of MedicineHirosakiAomoriJapan
| | - Kazushige Ihara
- Department of Social MedicineHirosaki University Graduate School of MedicineHirosakiAomoriJapan
| | - Shigeyuki Nakaji
- Department of Social MedicineHirosaki University Graduate School of MedicineHirosakiAomoriJapan
| | - Takenori Niioka
- Department of Pharmaceutical ScienceHirosaki University Graduate School of MedicineHirosakiAomoriJapan
- Department of PharmacyHirosaki University HospitalHirosakiAomoriJapan
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7
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Marie S, Frost KL, Hau RK, Martinez-Guerrero L, Izu JM, Myers CM, Wright SH, Cherrington NJ. Predicting disruptions to drug pharmacokinetics and the risk of adverse drug reactions in non-alcoholic steatohepatitis patients. Acta Pharm Sin B 2023; 13:1-28. [PMID: 36815037 PMCID: PMC9939324 DOI: 10.1016/j.apsb.2022.08.018] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2022] [Revised: 07/29/2022] [Accepted: 08/03/2022] [Indexed: 12/18/2022] Open
Abstract
The liver plays a central role in the pharmacokinetics of drugs through drug metabolizing enzymes and transporters. Non-alcoholic steatohepatitis (NASH) causes disease-specific alterations to the absorption, distribution, metabolism, and excretion (ADME) processes, including a decrease in protein expression of basolateral uptake transporters, an increase in efflux transporters, and modifications to enzyme activity. This can result in increased drug exposure and adverse drug reactions (ADRs). Our goal was to predict drugs that pose increased risks for ADRs in NASH patients. Bibliographic research identified 71 drugs with reported ADRs in patients with liver disease, mainly non-alcoholic fatty liver disease (NAFLD), 54 of which are known substrates of transporters and/or metabolizing enzymes. Since NASH is the progressive form of NAFLD but is most frequently undiagnosed, we identified other drugs at risk based on NASH-specific alterations to ADME processes. Here, we present another list of 71 drugs at risk of pharmacokinetic disruption in NASH, based on their transport and/or metabolism processes. It encompasses drugs from various pharmacological classes for which ADRs may occur when used in NASH patients, especially when eliminated through multiple pathways altered by the disease. Therefore, these results may inform clinicians regarding the selection of drugs for use in NASH patients.
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Affiliation(s)
- Solène Marie
- College of Pharmacy, Department of Pharmacology & Toxicology, University of Arizona, Tucson, AZ 85721, USA
| | - Kayla L. Frost
- College of Pharmacy, Department of Pharmacology & Toxicology, University of Arizona, Tucson, AZ 85721, USA
| | - Raymond K. Hau
- College of Pharmacy, Department of Pharmacology & Toxicology, University of Arizona, Tucson, AZ 85721, USA
| | - Lucy Martinez-Guerrero
- College of Pharmacy, Department of Pharmacology & Toxicology, University of Arizona, Tucson, AZ 85721, USA
| | - Jailyn M. Izu
- College of Pharmacy, Department of Pharmacology & Toxicology, University of Arizona, Tucson, AZ 85721, USA
| | - Cassandra M. Myers
- College of Pharmacy, Department of Pharmacology & Toxicology, University of Arizona, Tucson, AZ 85721, USA
| | - Stephen H. Wright
- College of Medicine, Department of Physiology, University of Arizona, Tucson, AZ 85724, USA
| | - Nathan J. Cherrington
- College of Pharmacy, Department of Pharmacology & Toxicology, University of Arizona, Tucson, AZ 85721, USA,Corresponding author. Tel.: +1 520 6260219; fax: +1 520 6266944.
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8
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Vohra M, Sharma AR, Mallya S, Prabhu NB, Jayaram P, Nagri SK, Umakanth S, Rai PS. Implications of genetic variations, differential gene expression, and allele-specific expression on metformin response in drug-naïve type 2 diabetes. J Endocrinol Invest 2022; 46:1205-1218. [PMID: 36528847 DOI: 10.1007/s40618-022-01989-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Accepted: 12/08/2022] [Indexed: 12/23/2022]
Abstract
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.
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Affiliation(s)
- M Vohra
- Department of Biotechnology, Manipal School of Life Sciences, Manipal Academy of Higher Education, Manipal, India
| | - A R Sharma
- Department of Biotechnology, Manipal School of Life Sciences, Manipal Academy of Higher Education, Manipal, India
| | - S Mallya
- Department of Bioinformatics, Manipal School of Life Sciences, Manipal Academy of Higher Education, Manipal, India
| | - N B Prabhu
- Department of Biotechnology, Manipal School of Life Sciences, Manipal Academy of Higher Education, Manipal, India
| | - P Jayaram
- Department of Cell and Molecular Biology, Manipal School of Life Sciences, Manipal Academy of Higher Education, Manipal, India
| | - S K Nagri
- Department of Medicine, Kasturba Medical College, Manipal Academy of Higher Education, Manipal, India
| | - S Umakanth
- Department of Medicine, Dr. T.M.A. Pai Hospital, Manipal Academy of Higher Education, Manipal, India
| | - P S Rai
- Department of Biotechnology, Manipal School of Life Sciences, Manipal Academy of Higher Education, Manipal, India.
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9
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Chen P, Cao Y, Chen S, Liu Z, Chen S, Guo Y. Association of SLC22A1, SLC22A2, SLC47A1, and SLC47A2 Polymorphisms with Metformin Efficacy in Type 2 Diabetic Patients. Biomedicines 2022; 10:2546. [PMID: 36289808 PMCID: PMC9599747 DOI: 10.3390/biomedicines10102546] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2022] [Revised: 10/03/2022] [Accepted: 10/10/2022] [Indexed: 02/05/2023] Open
Abstract
Response to metformin, first-line therapy for type 2 diabetes mellitus (T2DM), exists interindividual variation. Considering that transporters belonging to the solute carrier (SLC) superfamily are determinants of metformin pharmacokinetics, we evaluated the effects of promoter variants in organic cation transporter 1 (OCT1) (SLC22A1 rs628031), OCT2 (SLC22A2 rs316019), multidrug and toxin extrusion protein 1 (MATE1) (SLC47A1 rs2289669), and MATE2 (SLC47A2 rs12943590) on the variation in metformin response. The glucose-lowering effects and improvement of insulin resistance of metformin were assessed in newly diagnosed, treatment-naive type 2 diabetic patients of Han nationality in Chaoshan China (n = 93) receiving metformin. Fasting plasma glucose (FPG), fasting insulin (FINS), glycated hemoglobin A1 (HbA1C), homeostasis model assessment-insulin sensitivity (HOMA-IS), and homeostasis model assessment-insulin resistance (HOMA-IR) were the main metformin efficacy measurements. There were significant correlations between both SLC47A1 rs2289669 and SLC47A2 rs12943590 and the efficacy of metformin in individuals with T2DM. In normal weight T2DM patients, significant associations between the AA and GG genotypes of the rs2289669 variant of SLC47A1 and a greater reduction in FINS and HOMA-IR were detected. A significant correlation was observed between the AG genotype of the rs12943590 polymorphism of SLC47A2 and a greater reduction in HOMA-IR. Gene-environment interaction analysis showed that in the FINS interaction model, the second-order of dose30_g-SLC47A2 rs12943590 was statistically significant. The variants of SLC47A1 rs2289669 and SLC47A2 rs12943590 could be predictors of insulin resistance in type 2 diabetic patients treated with metformin. The second-order interaction of dose30_g-SLC47A2 rs12943590 may have a significant effect on FINS in patients with T2DM on metformin treatment. These findings suggest that promoter variants of SLC47A1 and SLC47A2 are important determinants of metformin transport and response in type 2 diabetes mellitus.
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Affiliation(s)
- Peixian Chen
- Department of Endocrinology and Metabolism, the Second Affiliated Hospital of Shantou University Medical College, Shantou 515000, China
| | - Yumin Cao
- Department of Endocrinology and Metabolism, the Second Affiliated Hospital of Shantou University Medical College, Shantou 515000, China
| | - Shenren Chen
- Department of Endocrinology and Metabolism, the Second Affiliated Hospital of Shantou University Medical College, Shantou 515000, China
| | - Zhike Liu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing 100191, China
| | - Shiyi Chen
- Department of Endocrinology and Metabolism, the Second Affiliated Hospital of Shantou University Medical College, Shantou 515000, China
| | - Yali Guo
- Department of Endocrinology and Metabolism, the Second Affiliated Hospital of Shantou University Medical College, Shantou 515000, China
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10
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Avsar O. Analysis of missense SNPs in the SLC47A1 and SLC47A2 genes affecting the pharmacokinetics of metformin: Computational approach. EGYPTIAN JOURNAL OF MEDICAL HUMAN GENETICS 2022. [DOI: 10.1186/s43042-022-00306-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Abstract
Abstract
Background
Metformin as an anti-hyperglycaemic drug is commonly used for the treatment of type 2 diabetes mellitus (T2DM). The metformin response is variable due to the interindividual variation of pharmacokinetics which is based on strong genetic background. MATE1 and MATE2 proteins are significantly implicated in the pharmacokinetics of metformin. Missense SNPs with high risk of pathogenicity are expected to affect response to metformin via pharmacokinetics. Therefore, the aim of the current study is to determine the effects of missense SNPs in the SLC47A1 and SLC47A2 genes. The structural and functional consequences of all known SLC47A1 and SLC47A2 missense SNPs of the human MATE1 and MATE2 proteins were identified by various bioinformatics methods (SIFT, PhD-SNP, PolyPhen-2, PROVEAN, PMut, MUpro, I-Mutant 3.0, COACH, RaptorX Binding, ConSurf, STRING).
Results
The SLC47A1 variants P186T, L116P and the SLC47A2 variants I158N, L112P, V118G exhibited ΔΔG values less than − 1 kcal/mol, and these variants are considered to disrupt the structure and function of MATE1 and MATE2 proteins. SLC47A1 R118Q and SLC47A2 Y273C, V118G may significantly disturb protein function and transporting activities according to the analysis of ligand-binding regions.
Conclusion
It is suggested that high-risk deleterious missense SNPs may mediate the pharmacokinetics of metformin and may be associated with altered tissue distribution, renal clearance and metformin toxicity. We suppose that our results might serve as potential targets for the studies composed of the development of potential diagnostic and therapeutic strategies based on the relationship between mutations and metformin response.
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11
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Trujillo-Del Río C, Tortajada-Pérez J, Gómez-Escribano AP, Casterá F, Peiró C, Millán JM, Herrero MJ, Vázquez-Manrique RP. Metformin to treat Huntington disease: a pleiotropic drug against a multi-system disorder. Mech Ageing Dev 2022; 204:111670. [DOI: 10.1016/j.mad.2022.111670] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2021] [Revised: 03/24/2022] [Accepted: 03/25/2022] [Indexed: 12/17/2022]
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12
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Chen P, Cao Y, Guo Y, Xu Q, Wang X, Zhang L, Liu Z, Chen D, Chen S, Chen S. Association of SLC22A1 rs622342 and ATM rs11212617 polymorphisms with metformin efficacy in patients with type 2 diabetes. Pharmacogenet Genomics 2022; 32:67-71. [PMID: 34545025 DOI: 10.1097/fpc.0000000000000454] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
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.
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Affiliation(s)
- Peixian Chen
- Department of Endocrinology
- Department of Infection Control
| | - Yumin Cao
- Department of Neurology, Meizhou People's Hospital, Meizhou, Guangdong Province
| | - Yali Guo
- Department of Endocrinology, Central Hospital of Shenzhen Guangming New District, Shenzhen
| | - Qi Xu
- Department of Endocrinology, the Second Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong Province
| | - Xiaozhu Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, People's Republic of China
| | - Liuwei Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, People's Republic of China
| | - Zhike Liu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, People's Republic of China
| | - Dafang Chen
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, People's Republic of China
| | - Shiyi Chen
- Department of Endocrinology, the Second Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong Province
| | - Shenren Chen
- Department of Endocrinology, the Second Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong Province
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13
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Rizvi AA, Abbas M, Verma S, Verma S, Khan A, Raza ST, Mahdi F. Determinants in Tailoring Antidiabetic Therapies: A Personalized Approach. Glob Med Genet 2022; 9:63-71. [PMID: 35707783 PMCID: PMC9192178 DOI: 10.1055/s-0041-1741109] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2021] [Accepted: 11/20/2021] [Indexed: 11/02/2022] Open
Abstract
AbstractDiabetes has become a pandemic as the number of diabetic people continues to rise globally. Being a heterogeneous disease, it has different manifestations and associated complications in different individuals like diabetic nephropathy, neuropathy, retinopathy, and others. With the advent of science and technology, this era desperately requires increasing the pace of embracing precision medicine and tailoring of drug treatment based on the genetic composition of individuals. It has been previously established that response to antidiabetic drugs, like biguanides, sulfonylureas, dipeptidyl peptidase-4 (DPP-4) inhibitors, glucagon-like peptide 1 (GLP-1) agonists, and others, depending on variations in their transporter genes, metabolizing genes, genes involved in their action, etc. Responsiveness of these drugs also relies on epigenetic factors, including histone modifications, miRNAs, and DNA methylation, as well as environmental factors and the lifestyle of an individual. For precision medicine to make its way into clinical procedures and come into execution, all these factors must be reckoned with. This review provides an insight into several factors oscillating around the idea of precision medicine in type-2 diabetes mellitus.
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Affiliation(s)
- Aliya A. Rizvi
- Department of Personalized and Molecular Medicine, Era University, Lucknow, Uttar Pradesh, India
| | - Mohammad Abbas
- Department of Personalized and Molecular Medicine, Era University, Lucknow, Uttar Pradesh, India
| | - Sushma Verma
- Department of Personalized and Molecular Medicine, Era University, Lucknow, Uttar Pradesh, India
| | - Shrikant Verma
- Department of Personalized and Molecular Medicine, Era University, Lucknow, Uttar Pradesh, India
| | - Almas Khan
- Department of Personalized and Molecular Medicine, Era University, Lucknow, Uttar Pradesh, India
| | - Syed T. Raza
- Department of Biochemistry, Era University, Lucknow Medical College and Hospital, Lucknow, Uttar Pradesh, India
| | - Farzana Mahdi
- Department of Personalized and Molecular Medicine, Era University, Lucknow, Uttar Pradesh, India
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14
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Guo Z, Priefer R. Current progress in pharmacogenomics of Type 2 diabetes: A systemic overview. Diabetes Metab Syndr 2021; 15:102239. [PMID: 34371302 DOI: 10.1016/j.dsx.2021.102239] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/05/2021] [Revised: 07/23/2021] [Accepted: 07/29/2021] [Indexed: 12/17/2022]
Abstract
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.
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Affiliation(s)
- Zhichun Guo
- Massachusetts College of Pharmacy and Health Sciences University, Boston, MA, USA
| | - Ronny Priefer
- Massachusetts College of Pharmacy and Health Sciences University, Boston, MA, USA.
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15
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Favela-Mendoza AF, Fricke-Galindo I, Cuevas-Sánchez WF, Aguilar-Velázquez JA, Martínez-Cortés G, Rangel-Villalobos H. Population diversity of three variants of the SLC47A2 gene (MATE2-K transporter) in Mexican Mestizos and Native Americans. Mol Biol Rep 2021; 48:6343-6348. [PMID: 34383246 DOI: 10.1007/s11033-021-06628-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2021] [Accepted: 08/05/2021] [Indexed: 11/25/2022]
Abstract
BACKGROUND MATE2-K is an efflux transporter protein of organic cation expressed mainly in the kidney and encoded by the SLC47A2 gene. Different variants of this gene have shown an impact on the pharmacokinetics of various drugs, including metformin, which represents one of the most widely used drugs in treating type 2 diabetes. The SLC47A2 gene variants have been scarcely studied in Mexican populations, especially in Native American groups. For this reason, we analyzed the distribution of the variants rs12943590, rs35263947, and rs9900497 within the SLC47A2 gene in 173 Native Americans (Tarahumara, Huichol, Maya, Puerépecha) and 182 Mestizos (admixed) individuals from Mexico. METHODS AND RESULTS Genotypes were determined through TaqMan probes (qPCR). The Hardy-Weinberg agreement was confirmed for all three SLC47A2 gene variants in all the Mexican populations analyzed. When worldwide populations were included for comparison purposes, for alleles and genotypes a relative interpopulation homogeneity was observed for rs35263947 (T allele; range 23.3-51.1%) and rs9900497 (T allele; range 18.6-40.9%). Conversely, heterogeneity was evident for rs12943590 (A allele, range 22.1-59.1%), where the most differentiated population was the Huichol, with high frequencies of the risk genotype associated with decreased response to metformin treatment (A/A = 40.9%). CONCLUSIONS Although the SLC47A2 gene variants allow predicting favorable response to the metformin treatment in Mexican populations, the probable high frequency of ineffectiveness should be discarded in Huichols.
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Affiliation(s)
- Alma Faviola Favela-Mendoza
- Instituto de Investigación en Genética Molecular, Centro Universitario de la Ciénega, Universidad de Guadalajara (CUCiénega-UdeG), Av. Universidad, No. 1115, Col. Lindavista, CP. 47810, Ocotlán, Jalisco, Mexico.
| | - Ingrid Fricke-Galindo
- HLA Laboratory, Instituto Nacional de Enfermedades Respiratorias Ismael Cosío Villega, Mexico City, Mexico
| | - Wendy Fernanda Cuevas-Sánchez
- Instituto de Investigación en Genética Molecular, Centro Universitario de la Ciénega, Universidad de Guadalajara (CUCiénega-UdeG), Av. Universidad, No. 1115, Col. Lindavista, CP. 47810, Ocotlán, Jalisco, Mexico
| | - José Alonso Aguilar-Velázquez
- Instituto de Investigación en Genética Molecular, Centro Universitario de la Ciénega, Universidad de Guadalajara (CUCiénega-UdeG), Av. Universidad, No. 1115, Col. Lindavista, CP. 47810, Ocotlán, Jalisco, Mexico
| | - Gabriela Martínez-Cortés
- Instituto de Investigación en Genética Molecular, Centro Universitario de la Ciénega, Universidad de Guadalajara (CUCiénega-UdeG), Av. Universidad, No. 1115, Col. Lindavista, CP. 47810, Ocotlán, Jalisco, Mexico
| | - Héctor Rangel-Villalobos
- Instituto de Investigación en Genética Molecular, Centro Universitario de la Ciénega, Universidad de Guadalajara (CUCiénega-UdeG), Av. Universidad, No. 1115, Col. Lindavista, CP. 47810, Ocotlán, Jalisco, Mexico.
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16
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Morales-Rivera MI, Alemón-Medina R, Martínez-Hernández A, Gómez-Garduño J, Mirzaeicheshmeh E, Altamirano-Bustamante NF, Ilizaliturri-Flores I, Mendoza-Caamal EC, Pérez-Guillé MG, García-Álvarez R, Contreras-Cubas C, Centeno-Cruz F, Revilla-Monsalve C, García-Ortiz H, Barajas-Olmos F, Orozco L. The L125F MATE1 variant enriched in populations of Amerindian origin is associated with increased plasma levels of metformin and lactate. Biomed Pharmacother 2021; 142:112009. [PMID: 34388523 DOI: 10.1016/j.biopha.2021.112009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2021] [Revised: 07/26/2021] [Accepted: 08/02/2021] [Indexed: 11/28/2022] Open
Abstract
Genetic factors that affect variability in metformin response have been poorly studied in the Latin American population, despite its being the initial drug therapy for type 2 diabetes, one of the most prevalent diseases in that region. Metformin pharmacokinetics is carried out by members of the membrane transporters superfamily (SLCs), being the multidrug and toxin extrusion protein 1 (MATE1), one of the most studied. Some genetic variants in MATE1 have been associated with reduced in vitro metformin transport. They include rs77474263 p.[L125F], a variant present at a frequency of 13.8% in Latin Americans, but rare worldwide (less than 1%). Using exome sequence data and TaqMan genotyping, we revealed that the Mexican population has the highest frequency of this variant: 16% in Mestizos and 27% in Amerindians, suggesting a possible Amerindian origin. To elucidate the metformin pharmacogenetics, a children cohort was genotyped, allowing us to describe, for the first time, a MATE1 rs77474263 TT homozygous individual. An additive effect of the L125F variant was observed on blood metformin accumulation, revealing the highest metformin and lactate serum levels in the TT homozygote, and intermediate metformin values in the heterozygotes. Moreover, a molecular dynamics analysis suggested that the genetic variant effect on metformin efflux could be due to a decreased protein permeability. We conclude that pharmacogenetics could be useful in enhancing metformin pharmacovigilance in populations having a high frequency of the risk genotype, especially considering that these populations also have a higher susceptibility to the diseases for which metformin is the first-choice drug.
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Affiliation(s)
- Monserrat I Morales-Rivera
- Immunogenomics and Metabolic Diseases Laboratory, Instituto Nacional de Medicina Genómica, SS, CDMX, Mexico; Posgrado en Ciencias Biológicas, Universidad Nacional Autónoma de México, CDMX, Mexico
| | | | | | | | - Elaheh Mirzaeicheshmeh
- Immunogenomics and Metabolic Diseases Laboratory, Instituto Nacional de Medicina Genómica, SS, CDMX, Mexico
| | | | | | - Elvia C Mendoza-Caamal
- Immunogenomics and Metabolic Diseases Laboratory, Instituto Nacional de Medicina Genómica, SS, CDMX, Mexico
| | | | | | - Cecilia Contreras-Cubas
- Immunogenomics and Metabolic Diseases Laboratory, Instituto Nacional de Medicina Genómica, SS, CDMX, Mexico
| | - Federico Centeno-Cruz
- Immunogenomics and Metabolic Diseases Laboratory, Instituto Nacional de Medicina Genómica, SS, CDMX, Mexico
| | - Cristina Revilla-Monsalve
- Medical Research Unit in Metabolic Diseases, UMAE Hospital de Cardiología, Centro Médico Nacional Siglo XXI, IMSS, CDMX, Mexico
| | - Humberto García-Ortiz
- Immunogenomics and Metabolic Diseases Laboratory, Instituto Nacional de Medicina Genómica, SS, CDMX, Mexico
| | - Francisco Barajas-Olmos
- Immunogenomics and Metabolic Diseases Laboratory, Instituto Nacional de Medicina Genómica, SS, CDMX, Mexico
| | - Lorena Orozco
- Immunogenomics and Metabolic Diseases Laboratory, Instituto Nacional de Medicina Genómica, SS, CDMX, Mexico.
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17
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Xiao D, Liu JY, Zhang SM, Liu RR, Yin JY, Han XY, Li X, Zhang W, Chen XP, Zhou HH, Ji LN, Liu ZQ. A Two-Stage Study Identifies Two Novel Polymorphisms in PRKAG2 Affecting Metformin Response in Chinese Type 2 Diabetes Patients. PHARMACOGENOMICS & PERSONALIZED MEDICINE 2021; 14:745-755. [PMID: 34188521 PMCID: PMC8236263 DOI: 10.2147/pgpm.s305020] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/29/2021] [Accepted: 05/25/2021] [Indexed: 12/29/2022]
Abstract
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 HbA1c, 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 HbA1c 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.
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Affiliation(s)
- Di Xiao
- Department of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha, People's Republic of China.,Department of pharmacy, Xiangya Hospital, Central South University, Changsha, People's Republic of China
| | - Jun-Yan Liu
- Department of orthopaedics, Xiangya Hospital, Central South University, Changsha, People's Republic of China
| | - Si-Min Zhang
- Department of Endocrinology and Metabolism, The People's Hospital of Peking University, Beijing, People's Republic of China
| | - Rang-Ru Liu
- Department of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha, People's Republic of China.,Key Laboratory of Tropical Diseases and Translational Medicine of the Ministry of Education & Hainan Provincial Key Laboratory of Tropical Medicine, Hainan Medical College, Haikou, People's Republic of China
| | - Ji-Ye Yin
- Department of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha, People's Republic of China.,Institute of Clinical Pharmacology, Hunan Key Laboratory of Pharmacogenetics, Central South University, Changsha, People's Republic of China
| | - Xue-Yao Han
- Department of Endocrinology and Metabolism, The People's Hospital of Peking University, Beijing, People's Republic of China
| | - Xi Li
- Department of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha, People's Republic of China.,Institute of Clinical Pharmacology, Hunan Key Laboratory of Pharmacogenetics, Central South University, Changsha, People's Republic of China
| | - Wei Zhang
- Department of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha, People's Republic of China.,Institute of Clinical Pharmacology, Hunan Key Laboratory of Pharmacogenetics, Central South University, Changsha, People's Republic of China.,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, People's Republic of China
| | - Xiao-Ping Chen
- Department of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha, People's Republic of China.,Institute of Clinical Pharmacology, Hunan Key Laboratory of Pharmacogenetics, Central South University, Changsha, People's Republic of China
| | - Hong-Hao Zhou
- Department of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha, People's Republic of China.,Institute of Clinical Pharmacology, Hunan Key Laboratory of Pharmacogenetics, Central South University, Changsha, People's Republic of China.,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, People's Republic of China
| | - Li-Nong Ji
- Department of Endocrinology and Metabolism, The People's Hospital of Peking University, Beijing, People's Republic of China
| | - Zhao-Qian Liu
- Department of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha, People's Republic of China.,Institute of Clinical Pharmacology, Hunan Key Laboratory of Pharmacogenetics, Central South University, Changsha, People's Republic of China.,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, People's Republic of China
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18
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Neul C, Hofmann U, Schaeffeler E, Winter S, Klein K, Giacomini KM, Eichelbaum M, Schwab M, Nies AT. Characterization of cytochrome P450 (CYP) 2D6 drugs as substrates of human organic cation transporters and multidrug and toxin extrusion proteins. Br J Pharmacol 2021; 178:1459-1474. [PMID: 33434947 DOI: 10.1111/bph.15370] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2020] [Revised: 11/24/2020] [Accepted: 12/21/2020] [Indexed: 12/21/2022] Open
Abstract
BACKGROUND AND PURPOSE The metabolic activity of cytochrome P450 (CYP) 2D6 is highly variable and CYP2D6 genotypes insufficiently explain the extensive and intermediate metabolic phenotypes, limiting the prediction of drug response plus adverse drug reactions. Since CYP2D6 prototypic substrates are positively charged, the aim of this study was to evaluate the organic cation transporters (OCTs) and multidrug and toxin extrusion proteins (MATEs) as potential contributors to the variability of CYP2D6 hydroxylation of debrisoquine, dextromethorphan, diphenhydramine, perhexiline and sparteine. EXPERIMENTAL APPROACH OCT1/SLC22A1-, OCT2/SLC22A2-, OCT3/SLC22A3-, MATE1/SLC47A1-, and MATE2K/SLC47A2-overexpressing cell lines were used to investigate the transport of the selected drugs. Individuals from a study cohort, well defined with respect to CYP2D6 genotype and sparteine pharmacokinetics, were genotyped for the common OCT1 variants rs12208357 (OCT1-R61C), rs34130495 (OCT1-G401S), rs202220802 (OCT1-Met420del), rs34059508 (OCT1-G465R), OCT2 variant rs316019 (OCT2-A270S) and MATE1 variant rs2289669. Sparteine pharmacokinetics was stratified according to CYP2D6 and OCT1, OCT2 or MATE1 genotype. KEY RESULTS OCTs and MATE1 transport sparteine and debrisoquine with high affinity in vitro, but OCT- and MATE1-dependent transport of dextromethorphan, diphenhydramine and perhexiline was not detected. Sparteine and debrisoquine transport depends on OCT1 genotype; however, sparteine pharmacokinetics is independent from OCT1 genotype. CONCLUSIONS AND IMPLICATIONS Some drugs that are substrates of CYP2D6 are also substrates of OCTs and MATE1, suggesting overlapping specificities. Variability in sparteine hydroxylation in extensive and intermediate metabolizers cannot be explained by OCT1 genetic variants indicating presence of other factors. Dose-dependent toxicities of dextromethorphan, diphenhydramine and perhexiline appear to be independent from OCTs and MATEs.
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Affiliation(s)
- Claudia Neul
- Dr. Margarete Fischer-Bosch Institute of Clinical Pharmacology, Stuttgart, Germany.,University of Tuebingen, Tuebingen, Germany
| | - Ute Hofmann
- Dr. Margarete Fischer-Bosch Institute of Clinical Pharmacology, Stuttgart, Germany.,University of Tuebingen, Tuebingen, Germany
| | - Elke Schaeffeler
- Dr. Margarete Fischer-Bosch Institute of Clinical Pharmacology, Stuttgart, Germany.,University of Tuebingen, Tuebingen, Germany.,Cluster of Excellence iFIT (EXC2180) "Image-Guided and Functionally Instructed Tumor Therapies", University of Tuebingen, Tuebingen, Germany
| | - Stefan Winter
- Dr. Margarete Fischer-Bosch Institute of Clinical Pharmacology, Stuttgart, Germany.,University of Tuebingen, Tuebingen, Germany
| | - Kathrin Klein
- Dr. Margarete Fischer-Bosch Institute of Clinical Pharmacology, Stuttgart, Germany.,University of Tuebingen, Tuebingen, Germany
| | - Kathleen M Giacomini
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, California, USA.,Institute of Human Genetics, University of California, San Francisco, California, USA
| | - Michel Eichelbaum
- Dr. Margarete Fischer-Bosch Institute of Clinical Pharmacology, Stuttgart, Germany.,University of Tuebingen, Tuebingen, Germany
| | - Matthias Schwab
- Dr. Margarete Fischer-Bosch Institute of Clinical Pharmacology, Stuttgart, Germany.,University of Tuebingen, Tuebingen, Germany.,Cluster of Excellence iFIT (EXC2180) "Image-Guided and Functionally Instructed Tumor Therapies", University of Tuebingen, Tuebingen, Germany.,Departments of Clinical Pharmacology, Pharmacy and Biochemistry, University of Tuebingen, Tuebingen, Germany
| | - Anne T Nies
- Dr. Margarete Fischer-Bosch Institute of Clinical Pharmacology, Stuttgart, Germany.,University of Tuebingen, Tuebingen, Germany.,Cluster of Excellence iFIT (EXC2180) "Image-Guided and Functionally Instructed Tumor Therapies", University of Tuebingen, Tuebingen, Germany
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19
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Sayed S, Nabi AHMN. Diabetes and Genetics: A Relationship Between Genetic Risk Alleles, Clinical Phenotypes and Therapeutic Approaches. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2021; 1307:457-498. [PMID: 32314317 DOI: 10.1007/5584_2020_518] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Unveiling human genome through successful completion of Human Genome Project and International HapMap Projects with the advent of state of art technologies has shed light on diseases associated genetic determinants. Identification of mutational landscapes such as copy number variation, single nucleotide polymorphisms or variants in different genes and loci have revealed not only genetic risk factors responsible for diseases but also region(s) playing protective roles. Diabetes is a global health concern with two major types - type 1 diabetes (T1D) and type 2 diabetes (T2D). Great progress in understanding the underlying genetic predisposition to T1D and T2D have been made by candidate gene studies, genetic linkage studies, genome wide association studies with substantial number of samples. Genetic information has importance in predicting clinical outcomes. In this review, we focus on recent advancement regarding candidate gene(s) associated with these two traits along with their clinical parameters as well as therapeutic approaches perceived. Understanding genetic architecture of these disease traits relating clinical phenotypes would certainly facilitate population stratification in diagnosing and treating T1D/T2D considering the doses and toxicity of specific drugs.
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Affiliation(s)
- Shomoita Sayed
- Department of Biochemistry and Molecular Biology, University of Dhaka, Dhaka, Bangladesh
| | - A H M Nurun Nabi
- Department of Biochemistry and Molecular Biology, University of Dhaka, Dhaka, Bangladesh.
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20
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Sarah EH, El Omri N, Ibrahimi A, El Jaoudi R. Metabolic and genetic studies of glimepiride and metformin and their association with type 2 diabetes. GENE REPORTS 2020. [DOI: 10.1016/j.genrep.2020.100787] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
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21
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Zeng Z, Huang SY, Sun T. Pharmacogenomic Studies of Current Antidiabetic Agents and Potential New Drug Targets for Precision Medicine of Diabetes. Diabetes Ther 2020; 11:2521-2538. [PMID: 32930968 PMCID: PMC7548012 DOI: 10.1007/s13300-020-00922-x] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/22/2020] [Indexed: 12/29/2022] Open
Abstract
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.
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Affiliation(s)
- Zhiwei Zeng
- Center for Precision Medicine, School of Medicine and School of Biomedical Sciences, Huaqiao University, Xiamen, 361021, China
| | - Shi-Ying Huang
- College of Food and Biological Engineering, Jimei University, Xiamen, 361021, China
| | - Tao Sun
- Center for Precision Medicine, School of Medicine and School of Biomedical Sciences, Huaqiao University, Xiamen, 361021, China.
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Jones VC, Dietze EC, Jovanovic-Talisman T, McCune JS, Seewaldt VL. Metformin and Chemoprevention: Potential for Heart-Healthy Targeting of Biologically Aggressive Breast Cancer. Front Public Health 2020; 8:509714. [PMID: 33194937 PMCID: PMC7658387 DOI: 10.3389/fpubh.2020.509714] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2019] [Accepted: 09/24/2020] [Indexed: 12/14/2022] Open
Abstract
Currently, tamoxifen is the only drug approved for reduction of breast cancer risk in premenopausal women. The significant cardiovascular side effects of tamoxifen, coupled with lack of a survival benefit, potential for genotoxicity, and failure to provide a significant risk-reduction for estrogen receptor-negative breast cancer, all contribute to the low acceptance of tamoxifen chemoprevention in premenopausal women at high-risk for breast cancer. While other prevention options exist for postmenopausal women, there is a search for well-tolerated prevention agents that can simultaneously reduce risk of breast cancers, cardiovascular disease, and type-2 diabetes. Metformin is a well-tolerated oral biguanide hypoglycemic agent that is prescribed worldwide to over 120 million individuals with type-2 diabetes. Metformin is inexpensive, safe during pregnancy, and the combination of metformin, healthy lifestyle, and exercise has been shown to be effective in preventing diabetes. There is a growing awareness that prevention drugs and interventions should make the “whole woman healthy.” To this end, current efforts have focused on finding low toxicity alternatives, particularly repurposed drugs for chemoprevention of breast cancer, including metformin. Metformin's mechanisms of actions are complex but clearly involve secondary lowering of circulating insulin. Signaling pathways activated by insulin also drive biologically aggressive breast cancer and predict poor survival in women with breast cancer. The mechanistic rationale for metformin chemoprevention is well-supported by the scientific literature. Metformin is cheap, safe during pregnancy, and has the potential to provide heart-healthy breast cancer prevention. On-going primary and secondary prevention trials will provide evidence whether metformin is effective in preventing breast cancer.
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Affiliation(s)
- Veronica C Jones
- City of Hope Comprehensive Cancer Center, Duarte, CA, United States
| | - Eric C Dietze
- City of Hope Comprehensive Cancer Center, Duarte, CA, United States
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Cravalho CKL, Meyers AG, Mabundo LS, Courville A, Yang S, Cai H, Dai Y, Walter M, Walter PJ, Sharma S, Chacko S, Cogen F, Magge SN, Haymond MW, Chung ST. Metformin improves blood glucose by increasing incretins independent of changes in gluconeogenesis in youth with type 2 diabetes. Diabetologia 2020; 63:2194-2204. [PMID: 32728891 DOI: 10.1007/s00125-020-05236-y] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/07/2020] [Accepted: 06/09/2020] [Indexed: 01/06/2023]
Abstract
AIMS/HYPOTHESIS Metformin is the only approved oral agent for youth with type 2 diabetes but its mechanism of action remains controversial. Recent data in adults suggest a primary role for the enteroinsular pathway, but there are no data in youth, in whom metformin efficacy is only ~50%. Our objectives were to compare incretin concentrations and rates of glucose production and gluconeogenesis in youth with type 2 diabetes before and after short-term metformin therapy compared with peers with normal glucose tolerance (NGT). METHODS This is a case-control observational study in youth with type 2 diabetes who were not on metformin (n = 18) compared with youth with NGT (n = 10) who were evaluated with a 2 day protocol. A 75 g OGTT was administered to measure intact glucagon-like 1 peptide (iGLP-1), gastric inhibitory polypeptide (GIP) and peptide YY (PYY). Insulinogenic index (IGI) and whole-body insulin sensitivity were calculated using glucose and insulin levels from the OGTT. Basal rates of gluconeogenesis (2H2O), glucose production ([6,6-2H2]glucose) and whole-body lipolysis ([2H5]glycerol) were measured after an overnight fast on study day 2. Youth with type 2 diabetes (n = 9) were subsequently evaluated with an identical 2 day protocol after 3 months on the metformin study. RESULTS Compared with individuals with NGT, those with type 2 diabetes had higher fasting (7.8 ± 2.5 vs 5.1 ± 0.3 mmol/l, mean ± SD p = 0.002) and 2 h glucose concentrations (13.8 ± 4.5 vs 5.9 ± 0.9 mmol/l, p = 0.001), higher rates of absolute gluconeogenesis (10.0 ± 1.7 vs 7.2 ± 1.1 μmol [kg fat-free mass (FFM)]-1 min-1, p < 0.001) and whole-body lipolysis (5.2 ± 0.9 vs 4.0 ± 1.4 μmol kgFFM-1 min-1, p < 0.01), but lower fasting iGLP-1 concentrations (0.5 ± 0.5 vs 1.3 ± 0.7 pmol/l, p < 0.01). Metformin decreased 2 h glucose (pre metformin 11.4 ± 2.8 vs post metformin 9.9 ± 1.9 mmol/l, p = 0.04) and was associated with ~20-50% increase in IGI (median [25th-75th percentile] pre 1.39 [0.89-1.47] vs post 1.43 [0.88-2.70], p = 0.04), fasting iGLP-1 (pre 0.3 ± 0.2 vs post 1.0 ± 0.7 pmol/l, p = 0.02), 2 h iGLP (pre 0.4 ± 0.2 vs post 1.2 ± 0.9 pmol/l, p = 0.06), fasting PYY (pre 6.3 ± 2.2 vs post 10.5 ± 4.3 pmol/l, p < 0.01) and 2 h PYY (pre 6.6 ± 2.9 vs post 9.0 ± 4.0 pmol/l, p < 0.01). There was no change in BMI, insulin sensitivity or GIP concentrations pre vs post metformin. There were no differences pre vs post metformin in rates of glucose production (15.0 ± 3.9 vs 14.9 ± 2.2 μmol kgFFM-1 min-1, p = 0.84), absolute gluconeogenesis (9.9 ± 1.8 vs 9.7 ± 1.7 μmol kgFFM-1 min-1, p = 0.76) or whole-body lipolysis (5.0 ± 0.7 vs 5.3 ± 1.3 μmol kgFFM-1 min-1, p = 0.20). Post metformin iGLP-1 and PYY concentrations in youth with type 2 diabetes were comparable to levels in youth with NGT. CONCLUSIONS/INTERPRETATION Overall, the improved postprandial blood glucose levels and increase in incretins observed in the absence of changes in insulin sensitivity and gluconeogenesis, support an enteroinsular mechanistic pathway in youth with type 2 diabetes treated with short-term metformin.
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Affiliation(s)
- Celeste K L Cravalho
- National Institute of Diabetes, Digestive and Kidney Diseases/National Institutes of Health, 10 Center Dr. Bld 10-CRC, RM 5-3671, Bethesda, MD, 20892, USA
| | - Abby G Meyers
- National Institute of Child Health and Development, National Institutes of Health, Bethesda, MD, USA
| | - Lilian S Mabundo
- National Institute of Diabetes, Digestive and Kidney Diseases/National Institutes of Health, 10 Center Dr. Bld 10-CRC, RM 5-3671, Bethesda, MD, 20892, USA
| | - Amber Courville
- National Institutes of Health, Clinical Center, Bethesda, MD, USA
| | - Shanna Yang
- National Institutes of Health, Clinical Center, Bethesda, MD, USA
| | - Hongyi Cai
- National Institute of Diabetes, Digestive and Kidney Diseases/National Institutes of Health, 10 Center Dr. Bld 10-CRC, RM 5-3671, Bethesda, MD, 20892, USA
| | - Yuhai Dai
- National Institute of Diabetes, Digestive and Kidney Diseases/National Institutes of Health, 10 Center Dr. Bld 10-CRC, RM 5-3671, Bethesda, MD, 20892, USA
| | - Mary Walter
- National Institute of Diabetes, Digestive and Kidney Diseases/National Institutes of Health, 10 Center Dr. Bld 10-CRC, RM 5-3671, Bethesda, MD, 20892, USA
| | - Peter J Walter
- National Institute of Diabetes, Digestive and Kidney Diseases/National Institutes of Health, 10 Center Dr. Bld 10-CRC, RM 5-3671, Bethesda, MD, 20892, USA
| | - Susan Sharma
- National Institute of Diabetes, Digestive and Kidney Diseases/National Institutes of Health, 10 Center Dr. Bld 10-CRC, RM 5-3671, Bethesda, MD, 20892, USA
| | - Shaji Chacko
- Department of Pediatrics, Children's Nutrition Research Center and Division of Pediatric Endocrinology and Metabolism, U.S. Department of Agriculture/Agricultural Research Service, Baylor College of Medicine, Houston, TX, USA
| | - Fran Cogen
- Children's National Health Systems, Department of Pediatric Diabetes and Endocrinology, Washington, DC, USA
| | - Sheela N Magge
- Division of Pediatric Endocrinology and Diabetes, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Morey W Haymond
- Department of Pediatrics, Children's Nutrition Research Center and Division of Pediatric Endocrinology and Metabolism, U.S. Department of Agriculture/Agricultural Research Service, Baylor College of Medicine, Houston, TX, USA
| | - Stephanie T Chung
- National Institute of Diabetes, Digestive and Kidney Diseases/National Institutes of Health, 10 Center Dr. Bld 10-CRC, RM 5-3671, Bethesda, MD, 20892, USA.
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Nasykhova YA, Tonyan ZN, Mikhailova AA, Danilova MM, Glotov AS. Pharmacogenetics of Type 2 Diabetes-Progress and Prospects. Int J Mol Sci 2020; 21:ijms21186842. [PMID: 32961860 PMCID: PMC7555942 DOI: 10.3390/ijms21186842] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2020] [Revised: 09/11/2020] [Accepted: 09/16/2020] [Indexed: 12/11/2022] Open
Abstract
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.
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Affiliation(s)
- Yulia A. Nasykhova
- Department of Genomic Medicine, D.O. Ott’s Institute of Obstetrics, Gynecology and Reproductology, 199034 Saint-Petersburg, Russia; (Y.A.N.); (Z.N.T.); (A.A.M.); (M.M.D.)
- Laboratory of Biobanking and Genomic Medicine, Saint-Petersburg State University, 199034 Saint-Petersburg, Russia
| | - Ziravard N. Tonyan
- Department of Genomic Medicine, D.O. Ott’s Institute of Obstetrics, Gynecology and Reproductology, 199034 Saint-Petersburg, Russia; (Y.A.N.); (Z.N.T.); (A.A.M.); (M.M.D.)
| | - Anastasiia A. Mikhailova
- Department of Genomic Medicine, D.O. Ott’s Institute of Obstetrics, Gynecology and Reproductology, 199034 Saint-Petersburg, Russia; (Y.A.N.); (Z.N.T.); (A.A.M.); (M.M.D.)
- Laboratory of Biobanking and Genomic Medicine, Saint-Petersburg State University, 199034 Saint-Petersburg, Russia
| | - Maria M. Danilova
- Department of Genomic Medicine, D.O. Ott’s Institute of Obstetrics, Gynecology and Reproductology, 199034 Saint-Petersburg, Russia; (Y.A.N.); (Z.N.T.); (A.A.M.); (M.M.D.)
| | - Andrey S. Glotov
- Department of Genomic Medicine, D.O. Ott’s Institute of Obstetrics, Gynecology and Reproductology, 199034 Saint-Petersburg, Russia; (Y.A.N.); (Z.N.T.); (A.A.M.); (M.M.D.)
- Laboratory of Biobanking and Genomic Medicine, Saint-Petersburg State University, 199034 Saint-Petersburg, Russia
- Correspondence: ; Tel.: +7-9117832003
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Xhakaza L, Abrahams-October Z, Pearce B, Masilela CM, Adeniyi OV, Johnson R, Ongole JJ, Benjeddou M. Evaluation of the suitability of 19 pharmacogenomics biomarkers for individualized metformin therapy for type 2 diabetes patients. Drug Metab Pers Ther 2020; 35:/j/dmdi.ahead-of-print/dmdi-2020-0111/dmdi-2020-0111.xml. [PMID: 32609649 DOI: 10.1515/dmdi-2020-0111] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2020] [Accepted: 04/14/2020] [Indexed: 12/16/2022]
Abstract
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.
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Affiliation(s)
- Lettilia Xhakaza
- Precision Medicine Unit, Department of Biotechnology, Faculty of Natural Sciences, University of the Western Cape, Bellville, South Africa
| | - Zainonesa Abrahams-October
- Precision Medicine Unit, Department of Biotechnology, Faculty of Natural Sciences, University of the Western Cape, Bellville, South Africa
| | - Brendon Pearce
- Precision Medicine Unit, Department of Biotechnology, Faculty of Natural Sciences, University of the Western Cape, Bellville, South Africa
| | - Charity Mandisa Masilela
- Precision Medicine Unit, Department of Biotechnology, Faculty of Natural Sciences, University of the Western Cape, Bellville, South Africa
| | | | - Rabia Johnson
- South African Medical Research Council, Parow, Cape Town, South Africa
- Division of Medical Physiology, Faculty of Medicine and Health Sciences, Stellenbosch University, Tygerberg, South Africa
| | - Joven Jebio Ongole
- Department of Family Medicine, Center for Teaching and Learning, Piet Retief Hospital, Mkhondo, Mpumalanga, South Africa
| | - Mongi Benjeddou
- Precision Medicine Unit, Department of Biotechnology, Faculty of Natural Sciences, University of the Western Cape, Bellville, South Africa
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Xhakaza L, Abrahams-October Z, Pearce B, Masilela CM, Adeniyi OV, Johnson R, Ongole JJ, Benjeddou M. Evaluation of the suitability of 19 pharmacogenomics biomarkers for individualized metformin therapy for type 2 diabetes patients. Drug Metab Pers Ther 2020; 35:/j/dmdi.2020.35.issue-2/dmpt-2020-0111/dmpt-2020-0111.xml. [PMID: 32681778 DOI: 10.1515/dmpt-2020-0111] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2020] [Accepted: 04/14/2020] [Indexed: 11/15/2022]
Abstract
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.
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Affiliation(s)
- Lettilia Xhakaza
- Precision Medicine Unit, Department of Biotechnology, Faculty of Natural Sciences, University of the Western Cape, Bellville, South Africa
| | - Zainonesa Abrahams-October
- Precision Medicine Unit, Department of Biotechnology, Faculty of Natural Sciences, University of the Western Cape, Bellville, South Africa
| | - Brendon Pearce
- Precision Medicine Unit, Department of Biotechnology, Faculty of Natural Sciences, University of the Western Cape, Bellville, South Africa
| | - Charity Mandisa Masilela
- Precision Medicine Unit, Department of Biotechnology, Faculty of Natural Sciences, University of the Western Cape, Bellville, South Africa
| | | | - Rabia Johnson
- South African Medical Research Council, Parow, Cape Town, South Africa
- Division of Medical Physiology, Faculty of Medicine and Health Sciences, Stellenbosch University, Tygerberg, South Africa
| | - Joven Jebio Ongole
- Department of Family Medicine, Center for Teaching and Learning, Piet Retief Hospital, Mkhondo, Mpumalanga, South Africa
| | - Mongi Benjeddou
- Precision Medicine Unit, Department of Biotechnology, Faculty of Natural Sciences, University of the Western Cape, Bellville, South Africa
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Association between metformin medication, genetic variation and prostate cancer risk. Prostate Cancer Prostatic Dis 2020; 24:96-105. [PMID: 32424261 DOI: 10.1038/s41391-020-0238-y] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2020] [Revised: 04/15/2020] [Accepted: 05/06/2020] [Indexed: 01/01/2023]
Abstract
BACKGROUND The relationship between metformin use and prostate cancer risk remains controversial. Genetic variation in metformin metabolism pathways appears to modify metformin glycemic control and the protective association with some cancers. However, no studies to date have examined this pharmacogenetic interaction and prostate cancer chemoprevention. METHODS Clinical data and germline DNA were collected from our prostate biopsy database between 1996 and 2014. In addition to a genome-wide association study (GWAS), 27 single nucleotide polymorphisms (SNPs) implicated in metformin metabolism were included on a custom SNP array. Associations between metformin use and risk of high-grade (Grade Group ≥ 2) and overall prostate cancer were explored using a case-control design. Interaction between the candidate/GWAS SNPs and the metformin-cancer association was explored using a case-only design. RESULTS Among 3481 men, 132 (4%) were taking metformin at diagnosis. Metformin users were older, more likely non-Caucasian, and had higher body mass index, Gleason score, and number of positive cores. Overall, 2061 (59%) were diagnosed with prostate cancer, of which 922 (45%) were high-grade. After adjusting for baseline characteristics, metformin use was associated with higher risk of high-grade prostate cancer (OR = 1.76, 95% CI 1.1-2.9, p = 0.02) and overall prostate cancer (OR = 1.77, 95% CI 1.1-2.9, p = 0.03). None of the 27 candidate SNPs in metformin metabolic pathways had significant interaction with the metformin-cancer association. Among the GWAS SNPs, one SNP (rs149137006) had genome-wide significant interaction with metformin for high-grade prostate cancer, and another, rs115071742, for overall prostate cancer. They were intronic and intergenic SNPs, respectively, with largely uncharacterized roles in prostate cancer chemoprevention. CONCLUSIONS In our cohort, metformin use was associated with increased risk of being diagnosed with prostate cancer. While SNPs involved in metformin metabolism did not have modifying effects on the association with disease risk, one intronic and one intergenic SNP from the GWAS study did, and these require further study.
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Radouani F, Zass L, Hamdi Y, Rocha JD, Sallam R, Abdelhak S, Ahmed S, Azzouzi M, Benamri I, Benkahla A, Bouhaouala-Zahar B, Chaouch M, Jmel H, Kefi R, Ksouri A, Kumuthini J, Masilela P, Masimirembwa C, Othman H, Panji S, Romdhane L, Samtal C, Sibira R, Ghedira K, Fadlelmola F, Kassim SK, Mulder N. A review of clinical pharmacogenetics Studies in African populations. Per Med 2020; 17:155-170. [PMID: 32125935 PMCID: PMC8093600 DOI: 10.2217/pme-2019-0110] [Citation(s) in RCA: 33] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
Effective interventions and treatments for complex diseases have been implemented globally, however, coverage in Africa has been comparatively lower due to lack of capacity, clinical applicability and knowledge on the genetic contribution to disease and treatment. Currently, there is a scarcity of genetic data on African populations, which have enormous genetic diversity. Pharmacogenomics studies have the potential to revolutionise treatment of diseases, therefore, African populations are likely to benefit from these approaches to identify likely responders, reduce adverse side effects and optimise drug dosing. This review discusses clinical pharmacogenetics studies conducted in African populations, focusing on studies that examined drug response in complex diseases relevant to healthcare. Several pharmacogenetics associations have emerged from African studies, as have gaps in knowledge.
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Affiliation(s)
- Fouzia Radouani
- Research Department, Chlamydiae & Mycoplasmas Laboratory, Institut Pasteur du Maroc, Casablanca 20360, Morocco
| | - Lyndon Zass
- Computational Biology Division, Department of Integrative Biomedical Sciences, IDM, CIDRI Africa Wellcome Trust Centre, University of Cape Town, South Africa
| | - Yosr Hamdi
- Laboratory of Biomedical Genomics & Oncogenetics, Institut Pasteur de Tunis, Université Tunis El Manar, 13, Place Pasteur BP 74, 1002 Tunis, Belvédère, Tunisie
| | - Jorge da Rocha
- Sydney Brenner Institute for Molecular Bioscience, University of The Witwatersrand, Johannesburg, South Africa
| | - Reem Sallam
- Medical Biochemistry & Molecular Biology Department, Faculty of Medicine, Ain Shams University, Abbaseya, Cairo 11381, Egypt
| | - Sonia Abdelhak
- Laboratory of Biomedical Genomics & Oncogenetics, Institut Pasteur de Tunis, Université Tunis El Manar, 13, Place Pasteur BP 74, 1002 Tunis, Belvédère, Tunisie
| | - Samah Ahmed
- Centre for Bioinformatics & Systems Biology, Faculty of Science, University of Khartoum, 321 Khartoum, Sudan.,Faculty of Clinical & Industrial Pharmacy, National University, Khartoum, Sudan
| | - Maryame Azzouzi
- Research Department, Chlamydiae & Mycoplasmas Laboratory, Institut Pasteur du Maroc, Casablanca 20360, Morocco
| | - Ichrak Benamri
- Research Department, Chlamydiae & Mycoplasmas Laboratory, Institut Pasteur du Maroc, Casablanca 20360, Morocco.,Systems & Data Engineering Team, National School of Applied Sciences of Tangier, Morocco
| | - Alia Benkahla
- Laboratory of Bioinformatics, Biomathematics & Biostatistics LR 16 IPT 09, Institute Pasteur de Tunis, Tunisia
| | - Balkiss Bouhaouala-Zahar
- Laboratory of Venoms & Therapeutic Molecules, Pasteur Institute of Tunis, 13 Place Pasteur, BP74, Tunis Belvedere- University of Tunis El Manar, Tunisia
| | - Melek Chaouch
- Laboratory of Bioinformatics, Biomathematics & Biostatistics LR 16 IPT 09, Institute Pasteur de Tunis, Tunisia
| | - Haifa Jmel
- Laboratory of Biomedical Genomics & Oncogenetics, Institut Pasteur de Tunis, Université Tunis El Manar, 13, Place Pasteur BP 74, 1002 Tunis, Belvédère, Tunisie
| | - Rym Kefi
- Laboratory of Biomedical Genomics & Oncogenetics, Institut Pasteur de Tunis, Université Tunis El Manar, 13, Place Pasteur BP 74, 1002 Tunis, Belvédère, Tunisie
| | - Ayoub Ksouri
- Laboratory of Bioinformatics, Biomathematics & Biostatistics LR 16 IPT 09, Institute Pasteur de Tunis, Tunisia.,Laboratory of Venoms & Therapeutic Molecules, Pasteur Institute of Tunis, 13 Place Pasteur, BP74, Tunis Belvedere- University of Tunis El Manar, Tunisia
| | - Judit Kumuthini
- H3ABioNet, Bioinformatics Department, Centre for Proteomic & Genomic Research, Cape Town, South Africa
| | - Phumlani Masilela
- Computational Biology Division, Department of Integrative Biomedical Sciences, IDM, CIDRI Africa Wellcome Trust Centre, University of Cape Town, South Africa
| | - Collen Masimirembwa
- Sydney Brenner Institute for Molecular Bioscience, University of The Witwatersrand, Johannesburg, South Africa.,DMPK Department, African Institute of Biomedical Science & Technology, Harare, Zimbabwe
| | - Houcemeddine Othman
- Sydney Brenner Institute for Molecular Bioscience, University of The Witwatersrand, Johannesburg, South Africa
| | - Sumir Panji
- Computational Biology Division, Department of Integrative Biomedical Sciences, IDM, CIDRI Africa Wellcome Trust Centre, University of Cape Town, South Africa
| | - Lilia Romdhane
- Laboratory of Biomedical Genomics & Oncogenetics, Institut Pasteur de Tunis, Université Tunis El Manar, 13, Place Pasteur BP 74, 1002 Tunis, Belvédère, Tunisie.,Département des Sciences de la Vie, Faculté des Sciences de Bizerte, Université Carthage, 7021 Jarzouna, BP 21, Tunisie
| | - Chaimae Samtal
- Biotechnology Laboratory, Faculty of Sciences Dhar El Mahraz, Sidi Mohammed Ben Abdellah University, Fez 30000, Morocco.,Department of Biology, University of Mohammed Premier, Oujda, Morocco.,Department of Biology Faculty of Sciences, University of Sidi Mohamed Ben Abdellah, Fez, Morocco
| | - Rania Sibira
- Centre for Bioinformatics & Systems Biology, Faculty of Science, University of Khartoum, 321 Khartoum, Sudan.,Department of Neurosurgery, National Center For Neurological Sciences, Khartoum, Sudan
| | - Kais Ghedira
- Laboratory of Bioinformatics, Biomathematics & Biostatistics LR 16 IPT 09, Institute Pasteur de Tunis, Tunisia
| | - Faisal Fadlelmola
- Centre for Bioinformatics & Systems Biology, Faculty of Science, University of Khartoum, 321 Khartoum, Sudan
| | - Samar Kamal Kassim
- Medical Biochemistry & Molecular Biology Department, Faculty of Medicine, Ain Shams University, Abbaseya, Cairo 11381, Egypt
| | - Nicola Mulder
- Computational Biology Division, Department of Integrative Biomedical Sciences, IDM, CIDRI Africa Wellcome Trust Centre, University of Cape Town, South Africa
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Shuster DL, Shireman LM, Ma X, Shen DD, Flood Nichols SK, Ahmed MS, Clark S, Caritis S, Venkataramanan R, Haas DM, Quinney SK, Haneline LS, Tita AT, Manuck TA, Thummel KE, Brown LM, Ren Z, Brown Z, Easterling TR, Hebert MF. Pharmacodynamics of Glyburide, Metformin, and Glyburide/Metformin Combination Therapy in the Treatment of Gestational Diabetes Mellitus. Clin Pharmacol Ther 2020; 107:1362-1372. [PMID: 31869430 DOI: 10.1002/cpt.1749] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2019] [Accepted: 10/23/2019] [Indexed: 12/16/2022]
Abstract
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.
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Affiliation(s)
- Diana L Shuster
- Clinical Pharmacology - Scientific Affairs, PRA Health Sciences, Lenexa, Kansas, USA
| | - Laura M Shireman
- Departments of Pharmaceutics, University of Washington, Seattle, Washington, USA
| | - Xiaosu Ma
- Global PK/PD & Pharmacometrics, Eli Lilly and Company, Indianapolis, Indiana, USA
| | - Danny D Shen
- Departments of Pharmaceutics, University of Washington, Seattle, Washington, USA
| | - Shannon K Flood Nichols
- Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, Madigan Army Medical Center, Tacoma, Washington, USA
| | - Mahmoud S Ahmed
- Department of Obstetrics & Gynecology, University of Texas Medical Branch in Galveston, Galveston, Texas, USA
| | - Shannon Clark
- Department of Obstetrics & Gynecology, University of Texas Medical Branch in Galveston, Galveston, Texas, USA
| | - Steve Caritis
- Departments of Obstetrics & Gynecology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Raman Venkataramanan
- Departments of Obstetrics & Gynecology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.,Department of Pharmacy, Pharmaceutical Sciences and Pathology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - David M Haas
- Departments of Obstetrics & Gynecology, Indiana University, Indianapolis, Indiana, USA
| | - Sara K Quinney
- Departments of Obstetrics & Gynecology, Indiana University, Indianapolis, Indiana, USA
| | - Laura S Haneline
- Department of Pediatrics, Indiana University, Indianapolis, Indiana, USA
| | - Alan T Tita
- Department of Obstetrics & Gynecology, Center for Women's Reproductive Health, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Tracy A Manuck
- Department of Obstetrics & Gynecology, University of North Carolina, Chapel Hill, North Carolina, USA
| | - Kenneth E Thummel
- Departments of Pharmaceutics, University of Washington, Seattle, Washington, USA
| | - Linda Morris Brown
- RTI International, Environmental, and Health Science Unit, Biostatistics and Epidemiology Division, Rockville, Maryland, USA
| | - Zhaoxia Ren
- Obstetric and Pediatric Pharmacology and Therapeutic Branch, Eunice Kennedy Shriver National Institute of Child Health and Human Development, Bethesda, Maryland, USA
| | - Zane Brown
- Department of Obstetrics & Gynecology, University of Washington, Seattle, Washington, USA
| | - Thomas R Easterling
- Department of Obstetrics & Gynecology, University of Washington, Seattle, Washington, USA.,Department of Pharmacy, University of Washington, Seattle, Washington, USA
| | - Mary F Hebert
- Department of Obstetrics & Gynecology, University of Washington, Seattle, Washington, USA.,Department of Pharmacy, University of Washington, Seattle, Washington, USA
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Abstract
The organic cation transporters (OCTs) OCT1, OCT2, OCT3, novel OCT (OCTN)1, OCTN2, multidrug and toxin exclusion (MATE)1, and MATE kidney-specific 2 are polyspecific transporters exhibiting broadly overlapping substrate selectivities. They transport organic cations, zwitterions, and some uncharged compounds and operate as facilitated diffusion systems and/or antiporters. OCTs are critically involved in intestinal absorption, hepatic uptake, and renal excretion of hydrophilic drugs. They modulate the distribution of endogenous compounds such as thiamine, L-carnitine, and neurotransmitters. Sites of expression and functions of OCTs have important impact on energy metabolism, pharmacokinetics, and toxicity of drugs, and on drug-drug interactions. In this work, an overview about the human OCTs is presented. Functional properties of human OCTs, including identified substrates and inhibitors of the individual transporters, are described. Sites of expression are compiled, and data on regulation of OCTs are presented. In addition, genetic variations of OCTs are listed, and data on their impact on transport, drug treatment, and diseases are reported. Moreover, recent data are summarized that indicate complex drug-drug interaction at OCTs, such as allosteric high-affinity inhibition of transport and substrate dependence of inhibitor efficacies. A hypothesis about the molecular mechanism of polyspecific substrate recognition by OCTs is presented that is based on functional studies and mutagenesis experiments in OCT1 and OCT2. This hypothesis provides a framework to imagine how observed complex drug-drug interactions at OCTs arise. Finally, preclinical in vitro tests that are performed by pharmaceutical companies to identify interaction of novel drugs with OCTs are discussed. Optimized experimental procedures are proposed that allow a gapless detection of inhibitory and transported drugs.
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Affiliation(s)
- Hermann Koepsell
- Institute of Anatomy and Cell Biology and Department of Molecular Plant Physiology and Biophysics, Julius-von-Sachs-Institute, University of Würzburg, Würzburg, Germany
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Briviba M, Silamikelis I, Kalnina I, Ansone L, Rovite V, Elbere I, Radovica-Spalvina I, Fridmanis D, Aladyeva J, Konrade I, Pirags V, Klovins J. Metformin strongly affects transcriptome of peripheral blood cells in healthy individuals. PLoS One 2019; 14:e0224835. [PMID: 31703101 PMCID: PMC6839856 DOI: 10.1371/journal.pone.0224835] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2019] [Accepted: 10/22/2019] [Indexed: 01/22/2023] Open
Abstract
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.
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Affiliation(s)
- Monta Briviba
- Latvian Biomedical Research and Study Centre, Riga, Latvia
| | | | - Ineta Kalnina
- Latvian Biomedical Research and Study Centre, Riga, Latvia
| | - Laura Ansone
- Latvian Biomedical Research and Study Centre, Riga, Latvia
| | - Vita Rovite
- Latvian Biomedical Research and Study Centre, Riga, Latvia
| | - Ilze Elbere
- Latvian Biomedical Research and Study Centre, Riga, Latvia
| | | | | | | | | | - Valdis Pirags
- Latvian Biomedical Research and Study Centre, Riga, Latvia
| | - Janis Klovins
- Latvian Biomedical Research and Study Centre, Riga, Latvia
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The genetic landscape of the human solute carrier (SLC) transporter superfamily. Hum Genet 2019; 138:1359-1377. [PMID: 31679053 PMCID: PMC6874521 DOI: 10.1007/s00439-019-02081-x] [Citation(s) in RCA: 87] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2019] [Accepted: 10/26/2019] [Indexed: 12/22/2022]
Abstract
The human solute carrier (SLC) superfamily of transporters is comprised of over 400 membrane-bound proteins, and plays essential roles in a multitude of physiological and pharmacological processes. In addition, perturbation of SLC transporter function underlies numerous human diseases, which renders SLC transporters attractive drug targets. Common genetic polymorphisms in SLC genes have been associated with inter-individual differences in drug efficacy and toxicity. However, despite their tremendous clinical relevance, epidemiological data of these variants are mostly derived from heterogeneous cohorts of small sample size and the genetic SLC landscape beyond these common variants has not been comprehensively assessed. In this study, we analyzed Next-Generation Sequencing data from 141,456 individuals from seven major human populations to evaluate genetic variability, its functional consequences, and ethnogeographic patterns across the entire SLC superfamily of transporters. Importantly, of the 204,287 exonic single-nucleotide variants (SNVs) which we identified, 99.8% were present in less than 1% of analyzed alleles. Comprehensive computational analyses using 13 partially orthogonal algorithms that predict the functional impact of genetic variations based on sequence information, evolutionary conservation, structural considerations, and functional genomics data revealed that each individual genome harbors 29.7 variants with putative functional effects, of which rare variants account for 18%. Inter-ethnic variability was found to be extensive, and 83% of deleterious SLC variants were only identified in a single population. Interestingly, population-specific carrier frequencies of loss-of-function variants in SLC genes associated with recessive Mendelian disease recapitulated the ethnogeographic variation of the corresponding disorders, including cystinuria in Jewish individuals, type II citrullinemia in East Asians, and lysinuric protein intolerance in Finns, thus providing a powerful resource for clinical geneticists to inform about population-specific prevalence and allelic composition of Mendelian SLC diseases. In summary, we present the most comprehensive data set of SLC variability published to date, which can provide insights into inter-individual differences in SLC transporter function and guide the optimization of population-specific genotyping strategies in the bourgeoning fields of personalized medicine and precision public health.
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Fodor A, Cozma A, Suharoschi R, Sitar-Taut A, Roman G. Clinical and genetic predictors of diabetes drug's response. Drug Metab Rev 2019; 51:408-427. [PMID: 31456442 DOI: 10.1080/03602532.2019.1656226] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
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.
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Affiliation(s)
- Adriana Fodor
- Department of Diabetes and Metabolic Diseases, University of Medicine and Pharmacy "Iuliu Hatieganu", Cluj-Napoca, Romania.,Clinical Center of Diabetes, Nutrition and Metabolic Disease, Cluj-Napoca, Romania
| | - Angela Cozma
- 4th Internal Medicine Department, University of Medicine and Pharmacy "Iuliu Hatieganu", Cluj-Napoca, Romania
| | - Ramona Suharoschi
- Department of Food Science, University of Agricultural Sciences and Veterinary Medicine of Cluj-Napoca, Cluj-Napoca, Romania
| | - Adela Sitar-Taut
- 4th Internal Medicine Department, University of Medicine and Pharmacy "Iuliu Hatieganu", Cluj-Napoca, Romania
| | - Gabriela Roman
- Department of Diabetes and Metabolic Diseases, University of Medicine and Pharmacy "Iuliu Hatieganu", Cluj-Napoca, Romania.,Clinical Center of Diabetes, Nutrition and Metabolic Disease, Cluj-Napoca, Romania
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34
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Garfunkel D, Anagnostou EA, Aman MG, Handen BL, Sanders KB, Macklin EA, Chan J, Veenstra-VanderWeele J. Pharmacogenetics of Metformin for Medication-Induced Weight Gain in Autism Spectrum Disorder. J Child Adolesc Psychopharmacol 2019; 29:448-455. [PMID: 31188026 DOI: 10.1089/cap.2018.0171] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Objectives: We recently found that metformin attenuated weight gain due to mixed dopamine and serotonin receptor antagonists, commonly termed atypical antipsychotics, in children and adolescents with autism spectrum disorder (ASD). Previous studies have found that genetic variation predicts response to metformin in diabetes. In this study, we aimed to assess whether response to metformin for weight gain in this population is associated with variants in five genes previously implicated in metformin response in diabetes. Methods: Youth with ASD who experienced significant weight gain while taking mixed receptor antagonist medications were randomly assigned to metformin or placebo for 16 weeks, followed by open-label metformin treatment for 16 weeks. In the 53 participants with available DNA samples, we used a linear, mixed model analysis to assess response in the first 16 weeks of metformin treatment, whether in the randomized or open-label period, based upon genotypes at polymorphisms in five genes previously associated with metformin response in diabetes: ATM, SLC2A2, MATE1, MATE2, and OCT1. Results: In the primary analysis, both ATM and OCT1 showed significant effects of genotype on change in body mass index z-scores, the primary outcome measure, during the first 16 weeks of treatment with metformin. No other polymorphism showed a significant difference. Conclusion: As has been shown for metformin treatment in diabetes, genetic variation may predict response to metformin for weight gain in youth with ASD treated with mixed receptor antagonists. Further work is needed to replicate these findings and evaluate whether they can be used prospectively to improve outcomes.
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Affiliation(s)
- Danielle Garfunkel
- 1Department of Psychiatry, Columbia University Medical Center, New York, New York
| | - Evdokia A Anagnostou
- 2Bloorview Research Institute, Holland Bloorview Kids Rehabilitation Hospital, Toronto, Canada.,3Department of Pediatrics, University of Toronto, Toronto, Canada
| | - Michael G Aman
- 4Nisonger Center, The Ohio State University, Columbus, Ohio
| | - Benjamin L Handen
- 5Department of Psychiatry, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania
| | - Kevin B Sanders
- 6Department of Psychiatry, Vanderbilt University, Nashville, Tennessee
| | - Eric A Macklin
- 7Biostatistics Center, Massachusetts General Hospital, Boston, Massachusetts.,8Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts
| | - James Chan
- 7Biostatistics Center, Massachusetts General Hospital, Boston, Massachusetts
| | - Jeremy Veenstra-VanderWeele
- 1Department of Psychiatry, Columbia University Medical Center, New York, New York.,9Center for Autism and the Developing Brain, NewYork-Presbyterian Hospital, White Plains, New York.,10New York State Psychiatric Institute, New York, New York
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35
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Verma S, Rizvi S, Abbas M, Raza T, Mahdi F. Personalized medicine- future of diagnosis and management of T2DM. Diabetes Metab Syndr 2019; 13:2425-2430. [PMID: 31405654 DOI: 10.1016/j.dsx.2019.06.017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/21/2019] [Accepted: 06/12/2019] [Indexed: 11/24/2022]
Affiliation(s)
- Sushma Verma
- Department of Personalized and Molecular Medicine, Era University, Lucknow, 226003, Uttar Pradesh, India.
| | - Saliha Rizvi
- Department of Personalized and Molecular Medicine, Era University, Lucknow, 226003, Uttar Pradesh, India.
| | - Mohd Abbas
- Department of Microbiology, Era University, Lucknow, 226003, Uttar Pradesh, India.
| | - Tasleem Raza
- Department of Biotechnology, Era's Lucknow Medical College & Hospital, Era University, Lucknow, 226003, Uttar Pradesh, India.
| | - Farzana Mahdi
- Department of Personalized and Molecular Medicine, Era University, Lucknow, 226003, Uttar Pradesh, India.
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Raj GM, Mathaiyan J, Wyawahare M, Priyadarshini R. Lack of effect of the SLC47A1 and SLC47A2 gene polymorphisms on the glycemic response to metformin in type 2 diabetes mellitus patients. Drug Metab Pers Ther 2019; 33:175-185. [PMID: 30433870 DOI: 10.1515/dmpt-2018-0030] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2018] [Accepted: 10/26/2018] [Indexed: 01/15/2023]
Abstract
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.
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Affiliation(s)
- Gerard Marshall Raj
- Department of Pharmacology, Sri Venkateshwaraa Medical College Hospital and Research Centre (SVMCH & RC), Pondy-Villupuram Main Road, Ariyur, Puducherry 605102, India
| | - Jayanthi Mathaiyan
- Department of Pharmacology, Jawaharlal Institute of Postgraduate Medical Education and Research (JIPMER), Puducherry, India
| | - Mukta Wyawahare
- Department of General Medicine, Jawaharlal Institute of Postgraduate Medical Education and Research (JIPMER), Puducherry, India
| | - Rekha Priyadarshini
- Department of Pharmacology, Jawaharlal Institute of Postgraduate Medical Education and Research (JIPMER), Puducherry, India
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Chang HH, Hsueh YS, Cheng YW, Ou HT, Wu MH. Association between Polymorphisms of OCT1 and Metabolic Response to Metformin in Women with Polycystic Ovary Syndrome. Int J Mol Sci 2019; 20:E1720. [PMID: 30959948 PMCID: PMC6479575 DOI: 10.3390/ijms20071720] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2019] [Revised: 04/03/2019] [Accepted: 04/04/2019] [Indexed: 02/06/2023] Open
Abstract
Insulin-sensitizer treatment with metformin is widely used in polycystic ovary syndrome (PCOS). However, the treatment effectiveness shows individual differences in PCOS patients. Organic cation transporter (OCT) 1 and 2 have been reported to mediate metformin transport in the liver and kidney, respectively. In this study, we investigated the association between the polymorphisms of OCT1 and OCT2 and the treatment effectiveness of metformin in PCOS patients. The single nucleotide polymorphisms (SNPs) of OCT1 (rs683369 and rs628031) and OCT2 (rs316019) were analyzed in 87 PCOS and 113 control women. Oral glucose tolerance tests (OGTTs), which represented metformin treatment response, were conducted at the start of treatment and after six-month treatment. The results demonstrated that the SNP frequencies of OCT1 and OCT2 were not associated with PCOS pathophysiology, and that the polymorphisms of OCT1 and OCT2 were not associated with the OGTT parameters at baseline. However, PCOS patients with the G allele of OCT1 rs683369 and/or with the A allele of OCT1 rs628031 had increased insulin sensitivity compared to those with wild-type genotype after receiving metformin treatment. Moreover, the interactions of metformin*SNP were significant in both OCT1 rs683369 (p < 0.001) and rs628031 (p = 0.001) during the treatment period. Taken together, genetic polymorphisms of OCT1 contributed to different metformin treatment responses, and further study is needed to establish personalized treatment programs using a pharmacogenomic algorithm approach in PCOS patients.
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Affiliation(s)
- Hui Hua Chang
- Institute of Clinical Pharmacy and Pharmaceutical Sciences, College of Medicine, National Cheng Kung University, Tainan 701, Taiwan.
- School of Pharmacy, College of Medicine, National Cheng Kung University, Tainan 701, Taiwan.
- Department of Pharmacy, National Cheng Kung University Hospital, Dou-Liou Branch, Yunlin 640, Taiwan.
| | - Yuan-Shuo Hsueh
- International Center for Wound Repair and Regeneration, National Cheng Kung University, Tainan 701, Taiwan.
| | - Yung Wen Cheng
- Institute of Clinical Pharmacy and Pharmaceutical Sciences, College of Medicine, National Cheng Kung University, Tainan 701, Taiwan.
| | - Huang-Tz Ou
- Institute of Clinical Pharmacy and Pharmaceutical Sciences, College of Medicine, National Cheng Kung University, Tainan 701, Taiwan.
- School of Pharmacy, College of Medicine, National Cheng Kung University, Tainan 701, Taiwan.
- Department of Pharmacy, National Cheng Kung University Hospital, Tainan 704, Taiwan.
| | - Meng-Hsing Wu
- Department of Obstetrics and Gynecology, College of Medicine and Hospital, National Cheng Kung University, Tainan 704, Taiwan.
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Shen H, Scialis RJ, Lehman-McKeeman L. Xenobiotic Transporters in the Kidney: Function and Role in Toxicity. Semin Nephrol 2019; 39:159-175. [DOI: 10.1016/j.semnephrol.2018.12.010] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
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Mannino GC, Andreozzi F, Sesti G. Pharmacogenetics of type 2 diabetes mellitus, the route toward tailored medicine. Diabetes Metab Res Rev 2019; 35:e3109. [PMID: 30515958 PMCID: PMC6590177 DOI: 10.1002/dmrr.3109] [Citation(s) in RCA: 56] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/08/2018] [Revised: 11/27/2018] [Accepted: 11/30/2018] [Indexed: 12/11/2022]
Abstract
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.
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Affiliation(s)
- Gaia Chiara Mannino
- Department of Medical and Surgical SciencesUniversity Magna Graecia of CatanzaroCatanzaroItaly
| | - Francesco Andreozzi
- Department of Medical and Surgical SciencesUniversity Magna Graecia of CatanzaroCatanzaroItaly
| | - Giorgio Sesti
- Department of Medical and Surgical SciencesUniversity Magna Graecia of CatanzaroCatanzaroItaly
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40
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Lam YWF, Duggirala R, Jenkinson CP, Arya R. The Role of Pharmacogenomics in Diabetes. Pharmacogenomics 2019. [DOI: 10.1016/b978-0-12-812626-4.00009-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022] Open
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Bokelmann K, Brockmöller J, Tzvetkov MV. Impact of Promoter Polymorphisms on the Transcriptional Regulation of the Organic Cation Transporter OCT1 (SLC22A1). J Pers Med 2018; 8:jpm8040042. [PMID: 30544975 PMCID: PMC6313513 DOI: 10.3390/jpm8040042] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2018] [Revised: 11/20/2018] [Accepted: 12/05/2018] [Indexed: 01/12/2023] Open
Abstract
The organic cation transporter 1 (OCT1, SLC22A1) is strongly expressed in the human liver and facilitates the hepatic uptake of drugs such as morphine, metformin, tropisetron, sumatriptan and fenoterol and of endogenous substances such as thiamine. OCT1 expression is inter-individually highly variable. Here, we analyzed SNPs in the OCT1 promoter concerning their potential contribution to the variability in OCT1 expression. Using electrophoretic mobility shift and luciferase reporter gene assays in HepG2, Hep3B, and Huh7 cell lines, we identified the SNPs −1795G>A (rs6935207) and −201C>G (rs58812592) as having effects on transcription factor binding and/or promoter activity. The A-allele of the −1795G>A SNP showed allele-specific binding of the transcription factor NF-Y leading to 2.5-fold increased enhancer activity of the artificial SV40 promoter. However, the −1795G>A SNP showed no significant effects on the native OCT1 promoter activity. Furthermore, the −1795G>A SNP was not associated with the pharmacokinetics of metformin, fenoterol, sumatriptan and proguanil in healthy individuals or tropisetron efficacy in patients undergoing chemotherapy. Allele-dependent differences in USF1/2 binding and nearly total loss in OCT1 promoter activity were detected for the G-allele of −201C>G, but the SNP is apparently very rare. In conclusion, common OCT1 promoter SNPs have only minor effects on OCT1 expression.
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Affiliation(s)
- Kristin Bokelmann
- Institute of Clinical Pharmacology, University Medical Center, Georg-August-University, 37075 Göttingen, Germany.
| | - Jürgen Brockmöller
- Institute of Clinical Pharmacology, University Medical Center, Georg-August-University, 37075 Göttingen, Germany.
| | - Mladen V Tzvetkov
- Institute of Pharmacology, Center of Drug Absorption and Transport (C_DAT), University Medicine Greifswald, 17487 Greifswald, Germany.
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OCT3 promoter haplotype is associated with metformin pharmacokinetics in Koreans. Sci Rep 2018; 8:16965. [PMID: 30446679 PMCID: PMC6240047 DOI: 10.1038/s41598-018-35322-6] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2018] [Accepted: 10/31/2018] [Indexed: 12/13/2022] Open
Abstract
Organic cation transporter 3 (OCT3) is expressed in various organs in humans and plays an important role in the transport of organic cations and drugs including metformin. In this study, we identified genetic variations of the OCT3 promoter and functionally characterized each variant by in vitro assays. Next, the association between the functional haplotype of the OCT3 promoter and pharmacokinetics of metformin was evaluated. In our study population, 7 variations and 2 major haplotypes were identified, of which H2 haplotype yielded a significantly higher luciferase activity than did the wild type. Two variants of H2, c.-1603G > A and c.-1547T > G, yielded significantly lower luciferase activities, whereas the luciferase activity of another variant, c.-29G > A, was significantly higher. Two transcription factors, Sp1 and USF1, were involved in the regulation of OCT3 transcription. Analysis of clinical data revealed that 25 subjects, either homozygous or heterozygous for H2, showed increased AUCinf and Cmax by 17.2% and 15.9%, respectively [P = 0.016 and 0.031, GMR (90% CI) = 1.17 (1.06–1.29) and 1.17 (1.04–1.31), respectively], compared to the 20 subjects in the control group. Our study suggests that an OCT3 promoter haplotype affects the pharmacokinetics of metformin in Koreans as well as the OCT3 transcription rate.
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Chan P, Shao L, Tomlinson B, Zhang Y, Liu ZM. Metformin transporter pharmacogenomics: insights into drug disposition-where are we now? Expert Opin Drug Metab Toxicol 2018; 14:1149-1159. [PMID: 30375241 DOI: 10.1080/17425255.2018.1541981] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
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.
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Affiliation(s)
- Paul Chan
- a Division of Cardiology, Department of Internal Medicine, Wan Fang Hospital , Taipei Medical University , Taipei City , Taiwan
| | - Li Shao
- b The VIP Department, Shanghai East Hospital , Tongji University School of Medicine , Shanghai , China
| | - Brian Tomlinson
- c Research Center for Translational Medicine , Shanghai East Hospital Affiliated to Tongji University School of Medicine , Shanghai , China.,d Department of Medicine & Therapeutics , The Chinese University of Hong Kong , Shatin , Hong Kong
| | - Yuzhen Zhang
- c Research Center for Translational Medicine , Shanghai East Hospital Affiliated to Tongji University School of Medicine , Shanghai , China
| | - Zhong-Min Liu
- e Department of Cardiac Surgery, Shanghai East Hospital , Tongji University , Shanghai , China
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Xie F, Chan JCN, Ma RCW. Precision medicine in diabetes prevention, classification and management. J Diabetes Investig 2018; 9:998-1015. [PMID: 29499103 PMCID: PMC6123056 DOI: 10.1111/jdi.12830] [Citation(s) in RCA: 49] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/05/2018] [Accepted: 02/12/2018] [Indexed: 12/18/2022] Open
Abstract
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.
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Affiliation(s)
- Fangying Xie
- Department of Medicine and TherapeuticsPrince of Wales HospitalThe Chinese University of Hong KongShatinHong Kong
| | - Juliana CN Chan
- Department of Medicine and TherapeuticsPrince of Wales HospitalThe Chinese University of Hong KongShatinHong Kong
- Hong Kong Institute of Diabetes and ObesityPrince of Wales HospitalThe Chinese University of Hong KongShatinHong Kong
- Li Ka Shing Institute of Health SciencesPrince of Wales HospitalThe Chinese University of Hong KongShatinHong Kong
- CUHK‐SJTU Joint Research Centre in Diabetes Genomics and Precision MedicinePrince of Wales HospitalThe Chinese University of Hong KongShatinHong Kong
| | - Ronald CW Ma
- Department of Medicine and TherapeuticsPrince of Wales HospitalThe Chinese University of Hong KongShatinHong Kong
- Hong Kong Institute of Diabetes and ObesityPrince of Wales HospitalThe Chinese University of Hong KongShatinHong Kong
- Li Ka Shing Institute of Health SciencesPrince of Wales HospitalThe Chinese University of Hong KongShatinHong Kong
- CUHK‐SJTU Joint Research Centre in Diabetes Genomics and Precision MedicinePrince of Wales HospitalThe Chinese University of Hong KongShatinHong Kong
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45
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Yee SW, Brackman DJ, Ennis EA, Sugiyama Y, Kamdem LK, Blanchard R, Galetin A, Zhang L, Giacomini KM. Influence of Transporter Polymorphisms on Drug Disposition and Response: A Perspective From the International Transporter Consortium. Clin Pharmacol Ther 2018; 104:803-817. [PMID: 29679469 DOI: 10.1002/cpt.1098] [Citation(s) in RCA: 82] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2018] [Revised: 04/10/2018] [Accepted: 04/11/2018] [Indexed: 12/21/2022]
Abstract
Advances in genomic technologies have led to a wealth of information identifying genetic polymorphisms in membrane transporters, specifically how these polymorphisms affect drug disposition and response. This review describes the current perspective of the International Transporter Consortium (ITC) on clinically important polymorphisms in membrane transporters. ITC suggests that, in addition to previously recommended polymorphisms in ABCG2 (BCRP) and SLCO1B1 (OATP1B1), polymorphisms in the emerging transporter, SLC22A1 (OCT1), be considered during drug development. Collectively, polymorphisms in these transporters are important determinants of interindividual differences in the levels, toxicities, and response to many drugs.
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Affiliation(s)
- Sook Wah Yee
- Department of Bioengineering and Therapeutic Sciences, Schools of Pharmacy and Medicine, University of California, San Francisco, San Francisco, California, USA
| | - Deanna J Brackman
- Department of Bioengineering and Therapeutic Sciences, Schools of Pharmacy and Medicine, University of California, San Francisco, San Francisco, California, USA
| | - Elizabeth A Ennis
- Department of Bioengineering and Therapeutic Sciences, Schools of Pharmacy and Medicine, University of California, San Francisco, San Francisco, California, USA
| | - Yuichi Sugiyama
- Sugiyama Laboratory, RIKEN Innovation Center, Research Cluster for Innovation, RIKEN, Yokohama, Japan
| | - Landry K Kamdem
- Department of Pharmaceutical Sciences, Harding University College of Pharmacy, Searcy, Arkansas, USA
| | | | - Aleksandra Galetin
- Centre for Applied Pharmacokinetic Research, School of Health Sciences, University of Manchester, UK
| | - Lei Zhang
- Office of Research and Standards, Office of Generic Drugs, Center for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, Maryland, USA
| | - Kathleen M Giacomini
- Department of Bioengineering and Therapeutic Sciences, Schools of Pharmacy and Medicine, University of California, San Francisco, San Francisco, California, USA.,Institute of Human Genetics, University of California, San Francisco, San Francisco, California, USA
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Srinivasan S, Yee SW, Giacomini KM. Pharmacogenetics of Antidiabetic Drugs. ADVANCES IN PHARMACOLOGY (SAN DIEGO, CALIF.) 2018; 83:361-389. [PMID: 29801583 PMCID: PMC10999281 DOI: 10.1016/bs.apha.2018.04.005] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
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.
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Affiliation(s)
- Shylaja Srinivasan
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA, United States; Division of Pediatric Endocrinology and Diabetes, University of California, San Francisco, San Francisco, CA, United States
| | - Sook Wah Yee
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA, United States
| | - Kathleen M Giacomini
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA, United States.
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Santoro AB, Botton MR, Struchiner CJ, Suarez-Kurtz G. Influence of pharmacogenetic polymorphisms and demographic variables on metformin pharmacokinetics in an admixed Brazilian cohort. Br J Clin Pharmacol 2018; 84:987-996. [PMID: 29352482 DOI: 10.1111/bcp.13522] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2017] [Revised: 12/07/2017] [Accepted: 01/12/2018] [Indexed: 12/15/2022] Open
Abstract
AIMS To identify pharmacogenetic and demographic variables that influence the systemic exposure to metformin in an admixed Brazilian cohort. METHODS The extreme discordant phenotype was used to select 106 data sets from nine metformin bioequivalence trials, comprising 256 healthy adults. Eleven single-nucleotide polymorphisms in SLC22A1, SLC22A2, SLC47A1 SLC47A2 and in transcription factor SP1 were genotyped and a validated panel of ancestry informative markers was used to estimate the individual proportions of biogeographical ancestry. Two-step (univariate followed by multivariate) regression modelling was developed to identify covariates associated with systemic exposure to metformin, accessed by the area under the plasma concentration-time curve, between 0 and 48 h (AUC0-48h ), after single oral doses of metformin (500 or 1000 mg). RESULTS The individual proportions of African, Amerindian and European ancestry varied widely, as anticipated from the structure of the Brazilian population The dose-adjusted, log-transformed AUC0-48h 's (ng h ml-1 mg-1 ) differed largely in the two groups at the opposite ends of the distribution histogram, namely 0.82, 0.79-0.85 and 1.08, 1.06-1.11 (mean, 95% confidence interval; P = 6.10-26 , t test). Multivariate modelling revealed that metformin AUC0-48h increased with age, food and carriage of rs12208357 in SLC22A1 but was inversely associated with body surface area and individual proportions of African ancestry. CONCLUSIONS A pharmacogenetic marker in OCT1 (SLC22A1 rs12208357), combined with demographic covariates (age, body surface area and individual proportion of African ancestry) and a food effect explained 29.7% of the variability in metformin AUC0-48h .
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Park HJ, Kim JH, Yoon JS, Choi YJ, Choi YH, Kook KH, Choi JH. Identification and Functional Characterization of ST3GAL5 and ST8SIA1 Variants in Patients with Thyroid-Associated Ophthalmopathy. Yonsei Med J 2017; 58:1160-1169. [PMID: 29047240 PMCID: PMC5653481 DOI: 10.3349/ymj.2017.58.6.1160] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/03/2017] [Revised: 08/09/2017] [Accepted: 08/24/2017] [Indexed: 01/13/2023] Open
Abstract
PURPOSE This study was conducted to identify and to functionally characterize genetic variants in ST3GAL5 and ST8SIA1 in Korean patients with thyroid-associated ophthalmopathy (TAO). MATERIALS AND METHODS Genetic analyses were conducted using DNA samples from TAO patients (n=50) and healthy subjects (n=48) to identify TAO-specific genetic variants of ST3GAL5 or ST8SIA1. The effect of each genetic variant on the transcription or expression of these genes was examined. Additionally, correlations between functional haplotypes of ST3GAL5 or ST8SIA1 and clinical characteristics of the patients were investigated. RESULTS Six promoter variants and one nonsynonymous variant of ST3GAL5 were identified, and four major promoter haplotypes were assembled. Additionally, three promoter variants and two major haplotypes of ST8SIA1 were identified. All ST3GAL5 and ST8SIA1 variants identified in TAO patients were also found in healthy controls. Promoter activity was significantly decreased in three promoter haplotypes of ST3GAL5 and increased in one promoter haplotype of ST8SIA1. Transcription factors activating protein-1, NKX3.1, and specificity protein 1 were revealed as having roles in transcriptional regulation of these haplotypes. The nonsynonymous variant of ST3GAL5, H104R, did not alter the expression of ST3GAL5. While no differences in clinical characteristics were detected in patients possessing the functional promoter haplotypes of ST3GAL5, exophthalmic values were significantly lower in patients with the ST8SIA1 haplotype, which showed a significant increase in promoter activity. CONCLUSION These results from genotype-phenotype analysis might suggest a possible link between the ST8SIA1 functional promoter haplotype and the clinical severity of TAO. However, further studies with larger sample sizes are warranted.
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Affiliation(s)
- Hyo Jin Park
- Department of Pharmacology, College of Medicine, Ewha Womans University, Seoul, Korea
- Tissue Injury Defense Research Center, College of Medicine, Ewha Womans University, Seoul, Korea
| | - Ju Hee Kim
- Department of Pharmacology, College of Medicine, Ewha Womans University, Seoul, Korea
- Tissue Injury Defense Research Center, College of Medicine, Ewha Womans University, Seoul, Korea
| | - Jin Sook Yoon
- Department of Ophthalmology, Yonsei University College of Medicine, Seoul, Korea
| | - Yang Ji Choi
- Department of Pharmacology, College of Medicine, Ewha Womans University, Seoul, Korea
- Tissue Injury Defense Research Center, College of Medicine, Ewha Womans University, Seoul, Korea
| | - Yoon Hee Choi
- Tissue Injury Defense Research Center, College of Medicine, Ewha Womans University, Seoul, Korea
- Department of Physiology, College of Medicine, Ewha Womans University, Seoul, Korea
| | - Koung Hoon Kook
- Department of Ophthalmology, Ajou University School of Medicine, Suwon, Korea.
| | - Ji Ha Choi
- Department of Pharmacology, College of Medicine, Ewha Womans University, Seoul, Korea
- Tissue Injury Defense Research Center, College of Medicine, Ewha Womans University, Seoul, Korea.
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Abstract
Transporters in proximal renal tubules contribute to the disposition of numerous drugs. Furthermore, the molecular mechanisms of tubular secretion have been progressively elucidated during the past decades. Organic anions tend to be secreted by the transport proteins OAT1, OAT3 and OATP4C1 on the basolateral side of tubular cells, and multidrug resistance protein (MRP) 2, MRP4, OATP1A2 and breast cancer resistance protein (BCRP) on the apical side. Organic cations are secreted by organic cation transporter (OCT) 2 on the basolateral side, and multidrug and toxic compound extrusion (MATE) proteins MATE1, MATE2/2-K, P-glycoprotein, organic cation and carnitine transporter (OCTN) 1 and OCTN2 on the apical side. Significant drug-drug interactions (DDIs) may affect any of these transporters, altering the clearance and, consequently, the efficacy and/or toxicity of substrate drugs. Interactions at the level of basolateral transporters typically decrease the clearance of the victim drug, causing higher systemic exposure. Interactions at the apical level can also lower drug clearance, but may be associated with higher renal toxicity, due to intracellular accumulation. Whereas the importance of glomerular filtration in drug disposition is largely appreciated among clinicians, DDIs involving renal transporters are less well recognized. This review summarizes current knowledge on the roles, quantitative importance and clinical relevance of these transporters in drug therapy. It proposes an approach based on substrate-inhibitor associations for predicting potential tubular-based DDIs and preventing their adverse consequences. We provide a comprehensive list of known drug interactions with renally-expressed transporters. While many of these interactions have limited clinical consequences, some involving high-risk drugs (e.g. methotrexate) definitely deserve the attention of prescribers.
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Affiliation(s)
- Anton Ivanyuk
- Division of Clinical Pharmacology, Lausanne University Hospital (CHUV), Bugnon 17, 1011, Lausanne, Switzerland.
| | - Françoise Livio
- Division of Clinical Pharmacology, Lausanne University Hospital (CHUV), Bugnon 17, 1011, Lausanne, Switzerland
| | - Jérôme Biollaz
- Division of Clinical Pharmacology, Lausanne University Hospital (CHUV), Bugnon 17, 1011, Lausanne, Switzerland
| | - Thierry Buclin
- Division of Clinical Pharmacology, Lausanne University Hospital (CHUV), Bugnon 17, 1011, Lausanne, Switzerland
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Xu D, You G. Loops and layers of post-translational modifications of drug transporters. Adv Drug Deliv Rev 2017; 116:37-44. [PMID: 27174152 DOI: 10.1016/j.addr.2016.05.003] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2016] [Accepted: 05/03/2016] [Indexed: 12/19/2022]
Abstract
Drug transporters encoded by solute carrier (SLC) family are distributed in multiple organs including kidney, liver, placenta, brain, and intestine, where they mediate the absorption, distribution, and excretion of a diverse array of environmental toxins and clinically important drugs. Alterations in the expression and function of these transporters play important roles in intra- and inter-individual variability of the therapeutic efficacy and the toxicity of many drugs. Consequently, the activity of these transporters must be highly regulated to carry out their normal functions. While it is clear that the regulation of these transporters tightly depends on genetic mechanisms, many studies have demonstrated that these transporters are the target of various post-translational modifications. This review article summarizes the recent advances in identifying the posttranslational modifications underlying the regulation of the drug transporters of SLC family. Such mechanisms are pivotal not only in physiological conditions, but also in diseases.
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