Pharmacogenetics of efficiency and tolerance of the peroral antidiabetic drug metformin

Elektroniskā versija nesatur pielikumusMetformīns ir pirmās izvēles medikaments jaundiagnosticētu 2.tipa cukura diabēta (T2DM) pacientu ārstēšanā. Mēs identificējām asociāciju starp metformīna blakusparādībām un 2 ģenētiskiem variantiem (rs628031 and rs36056065) Organisko Katjonu transportierī 1 (OCT1/SLC22A1). Polimorfismiem rs3119309, rs2481030 un rs7757336, lokalizētiem Organisko Katjonu transportieru 2 un 3 (OCT2/SLC22A2 un OCT3/SLC22A3) starpgēnu reģionā, tika noteikta būtiska asociācija ar metformīna īstermiņa terapijas efektivitāti. Divi no šiem variantiem tika analizēti replikācijas pētījumā ar 126 T2DM pacientiem no Slovākijas un farmakokinētikas pētījumā ar 15 veseliem brīvprātīgajiem. Visbeidzot, 33 ģenētiskas variācijas tika izpētītas ATM, STK11 un T2DM kandidātgēnos, bet tikai dažas no tām bija nomināli asociētas ar metformīna īstermiņa terapijas efektivitāti. Atslēgas vārdi: OCTs, metformīns, farmakoģenētika, blakusparādības, efektivitāte.Metformin is the first-line medication used in treatment of newly-diagnosticed Type 2 diabetes mellitus (T2DM). We show an association between metformin side-effects and two genetic variants (rs628031 and rs36056065) in Organic Cation Transporter 1 (OCT1/SLC22A1). Polymorphisms rs3119309, rs2481030 un rs7757336 in intergenic region between Organic Cation Transporter 2 and 3 (OCT2/SLC22A2 and OCT3/ SLC22A3) were found to be associated with short-term efficiency of metformin therapy. Two of these variants were analysed in replication study in 126 T2DM patients from Slovakia and in pharmacokinetic study with 15 healthy participants. At last, 33 genetic variants in ATM, STK11 and list of T2DM susceptibility genes were investigated, but only few showed a nominal association with short-term efficiency of metformin monotherapy. Keywords: OCTs, metformin, pharmacogenetics, side-effects, efficiency

Metformin Transport Rates Between Plasma and Red Blood Cells in Humans

Background Metformin has been used for the treatment of type 2 diabetes for over 60 years; however, its mechanism of pharmacological action is not fully clear. Different hypotheses exist regarding metformin distribution and redistribution mechanisms between plasma and erythrocytes/red blood cells (RBCs). Objective We aimed to test the hypothesis that the metformin distribution between plasma and RBC occurs via concentration difference-driven passive transport and estimated transport rate coefficient values based on metformin concentration time series in plasma and RBCs from in vivo studies. Methods An ordinary differential equation (ODE) system with two compartments was used to describe diffusion-based passive transport between plasma and RBCs. Metformin concentration time series in plasma and RBCs of 35 individuals were used for metformin transport parametrization. Plasma concentration has been approximated by biexponential decline. Results A single passive transport coefficient, k = 0.044 +/- 0.014 (h(-1)), can be applied, describing the uptake and release transport rate versus the linear equation v = k x (M-pl - M-RBC), where M-pl is the metformin concentration in plasma and M-RBC is the metformin concentration in RBCs. Conclusions Our research suggests that passive transport can explain metformin distribution dynamics between plasma and RBCs because transport speed is proportional to the metformin concentration difference and independent of the transport direction. Concentration difference-driven passive transport can explain the mechanism of faster metformin distribution to RBCs the first few hours after administration, and faster release and domination of the redistribution transport rate after metformin concentration in plasma becomes smaller than in RBCs.Peer reviewe

Novel susceptibility loci identified in a genome-wide association study of type 2 diabetes complications in population of Latvia

Funding Information: The study was supported by European Regional Development Fund (ERDF) On Implementation of Activity 1.1.1.2 “Post-doctoral Research Aid” of the Specific Aid Objective 1.1.1 “To increase the research and innovative capacity of scientific institutions of Latvia and the ability to attract external financing, investing in human resources and infrastructure” of the Operational Programme “Growth and Employment”. Project No 1.1.1.2/VIAA/2/18/287 “Identification of clinical subgroups of Type 2 diabetes mellitus and application of pharmacogenetics in the development of personalized antidiabetic therapy”. The funding body was not involved in the design of the study, collection, analysis or interpretation of data, or writing the manuscript. Publisher Copyright: © 2021, The Author(s).Background: Type 2 diabetes complications cause a serious emotional and economical burden to patients and healthcare systems globally. Management of both acute and chronic complications of diabetes, which dramatically impair the quality of patients' life, is still an unsolved issue in diabetes care, suggesting a need for early identification of individuals with high risk for developing diabetes complications. Methods: We performed a genome-wide association study in 601 type 2 diabetes patients after stratifying them according to the presence or absence of four types of diabetes complications: diabetic neuropathy, diabetic nephropathy, macrovascular complications, and ophthalmic complications. Results: The analysis revealed ten novel associations showing genome-wide significance, including rs1132787 (GYPA, OR = 2.71; 95% CI = 2.02–3.64) and diabetic neuropathy, rs2477088 (PDE4DIP, OR = 2.50; 95% CI = 1.87–3.34), rs4852954 (NAT8, OR = 2.27; 95% CI = 2.71–3.01), rs6032 (F5, OR = 2.12; 95% CI = 1.63–2.77), rs6935464 (RPS6KA2, OR = 2.25; 95% CI = 6.69–3.01) and macrovascular complications, rs3095447 (CCDC146, OR = 2.18; 95% CI = 1.66–2.87) and ophthalmic complications. By applying the targeted approach of previously reported susceptibility loci we managed to replicate three associations: MAPK14 (rs3761980, rs80028505) and diabetic neuropathy, APOL1 (rs136161) and diabetic nephropathy. Conclusions: Together these results provide further evidence for the implication of genetic factors in the development of type 2 diabetes complications and highlight several potential key loci, able to modify the risk of developing these conditions. Moreover, the candidate variant approach proves a strong and consistent effect for multiple variants across different populations.publishersversionPeer reviewe

Significantly altered peripheral blood cell DNA methylation profile as a result of immediate effect of metformin use in healthy individuals

Funding Information: The work was supported by the European Regional Development Fund under the project “Investigation of interplay between multiple determinants influencing response to metformin: search for reliable predictors for efficacy of type 2 diabetes therapy” (Project Nr.: 1.1.1.1/16/A/091). Publisher Copyright: © 2018 The Author(s).Background: Metformin is a widely prescribed antihyperglycemic agent that has been also associated with multiple therapeutic effects in various diseases, including several types of malignancies. There is growing evidence regarding the contribution of the epigenetic mechanisms in reaching metformin's therapeutic goals; however, the effect of metformin on human cells in vivo is not comprehensively studied. The aim of our study was to examine metformin-induced alterations of DNA methylation profiles in white blood cells of healthy volunteers, employing a longitudinal study design. Results: Twelve healthy metformin-naïve individuals where enrolled in the study. Genome-wide DNA methylation pattern was estimated at baseline, 10 h and 7 days after the start of metformin administration. The whole-genome DNA methylation analysis in total revealed 125 differentially methylated CpGs, of which 11 CpGs and their associated genes with the most consistent changes in the DNA methylation profile were selected: POFUT2, CAMKK1, EML3, KIAA1614, UPF1, MUC4, LOC727982, SIX3, ADAM8, SNORD12B, VPS8, and several differentially methylated regions as novel potential epigenetic targets of metformin. The main functions of the majority of top-ranked differentially methylated loci and their representative cell signaling pathways were linked to the well-known metformin therapy targets: regulatory processes of energy homeostasis, inflammatory responses, tumorigenesis, and neurodegenerative diseases. Conclusions: Here we demonstrate for the first time the immediate effect of short-term metformin administration at therapeutic doses on epigenetic regulation in human white blood cells. These findings suggest the DNA methylation process as one of the mechanisms involved in the action of metformin, thereby revealing novel targets and directions of the molecular mechanisms underlying the various beneficial effects of metformin. Trial registration: EU Clinical Trials Register, 2016-001092-74. Registered 23 March 2017, https://www.clinicaltrialsregister.eu/ctr-search/trial/2016-001092-74/LV.Peer reviewe

Single nucleotide polymorphisms in the intergenic region between metformin transporter OCT2 and OCT3 coding genes are associated with short-Term response to metformin monotherapy in type 2 diabetes mellitus patients

Publisher Copyright: © 2016 The authors Published by Bioscientifica Ltd. Copyright: Copyright 2017 Elsevier B.V., All rights reserved.Objective(s): High variability in clinical response to metformin is often observed in type 2 diabetes (T2D) patients, and it highlights the need for identification of genetic components affecting the efficiency of metformin therapy. Aim of this observational study is to evaluate the role of tagSNPs (tagging single nucleotide polymorphisms) from genomic regions coding for six metformin transporter genes with respect to the short-Term efficiency. Design: 102 tagSNPs in 6 genes coding for metformin transporters were genotyped in the group of 102 T2D patients treated with metformin for 3 months. Methods: Most significant hits were analyzed in the group of 131 T2D patients from Slovakia. Pharmacokinetic study in 25 healthy nondiabetic volunteers was conducted to investigate the effects of identified polymorphisms. Results: In the discovery group of 102 patients, minor alleles of rs3119309, rs7757336 and rs2481030 were significantly nominally associated with metformin inefficiency (P = 1.9 × 106 to 8.1 × 106). Effects of rs2481030 and rs7757336 did not replicate in the group of 131 T2DM patients from Slovakia alone, whereas rs7757336 was significantly associated with a reduced metformin response in combined group. In pharmacokinetic study, group of individuals harboring risk alleles of rs7757336 and rs2481030 displayed significantly reduced AUC∞ of metformin in plasma. Conclusions: For the first time, we have identified an association between the lack of metformin response and SNPs rs3119309 and rs7757336 located in the 5 flanking region of the genes coding for Organic cation transporter 2 and rs2481030 located in the 5 flanking region of Organic cation transporter 3 that was supported by the results of a pharmacokinetic study on 25 healthy volunteers.publishersversionPeer reviewe

Extending the Minimum Information About BIobank Data Sharing Terminology to Describe Samples, Sample Donors, and Events

Introduction: The Minimum Information About BIobank data Sharing (MIABIS) was initiated in 2012. MIABIS aims to create a common biobank terminology to facilitate data sharing in biobanks and sample collections. The MIABIS Core terminology consists of three components describing biobanks, sample collections, and studies, in which information on samples and sample donors is provided at aggregated form. However, there is also a need to describe samples and sample donors at an individual level to allow more elaborate queries on available biobank samples and data. Therefore the MIABIS terminology has now been extended with components describing samples and sample donors at an individual level. Materials and Methods: The components were defined according to specific scope and use cases by a large group of experts, and through several cycles of reviews, according to the new MIABIS governance model of BBMRI-ERIC (Biobanking and Biomolecular Resources Research Infrastructure-European Research Infrastructure Consortium). The guiding principles applied in developing these components included the following terms: model should consider only samples of human origin, model should be applicable to all types of samples and all sample donors, and model should describe the current status of samples stored in a given biobank. Results: A minimal set of standard attributes for defining samples and sample donors is presented here. We added an "event" component to describe attributes that are not directly describing samples or sample donors but are tightly related to them. To better utilize the generic data model, we suggest a procedure by which interoperability can be promoted, using specific MIABIS profiles. Discussion: The MIABIS sample and donor component extensions and the new generic data model complement the existing MIABIS Core 2.0 components, and substantially increase the potential usability of this terminology for better describing biobank samples and sample donors. They also support the use of individual level data about samples and sample donors to obtain accurate and detailed biobank availability queries

Harmonising and linking biomedical and clinical data across disparate data archives to enable integrative cross-biobank research

A wealth of biospecimen samples are stored in modern globally distributed biobanks. Biomedical researchers worldwide need to be able to combine the available resources to improve the power of large-scale studies. A prerequisite for this effort is to be able to search and access phenotypic, clinical and other information about samples that are currently stored at biobanks in an integrated manner. However, privacy issues together with heterogeneous information systems and the lack of agreed-upon vocabularies have made specimen searching across multiple biobanks extremely challenging. We describe three case studies where we have linked samples and sample descriptions in order to facilitate global searching of available samples for research. The use cases include the ENGAGE (European Network for Genetic and Genomic Epidemiology) consortium comprising at least 39 cohorts, the SUMMIT (surrogate markers for micro- and macro-vascular hard endpoints for innovative diabetes tools) consortium and a pilot for data integration between a Swedish clinical health registry and a biobank. We used the Sample avAILability (SAIL) method for data linking: first, created harmonised variables and then annotated and made searchable information on the number of specimens available in individual biobanks for various phenotypic categories. By operating on this categorised availability data we sidestep many obstacles related to privacy that arise when handling real values and show that harmonised and annotated records about data availability across disparate biomedical archives provide a key methodological advance in pre-analysis exchange of information between biobanks, that is, during the project planning phase

Variation in the Glucose Transporter gene <i>SLC2A2 </i>is associated with glycaemic response to metformin

Metformin is the first-line antidiabetic drug with over 100 million users worldwide, yet its mechanism of action remains unclear1. Here the Metformin Genetics (MetGen) Consortium reports a three-stage genome-wide association study (GWAS), consisting of 13,123 participants of different ancestries. The C allele of rs8192675 in the intron of SLC2A2, which encodes the facilitated glucose transporter GLUT2, was associated with a 0.17% (P = 6.6 × 10−14) greater metformin-induced reduction in hemoglobin A1c (HbA1c) in 10,577 participants of European ancestry. rs8192675 was the top cis expression quantitative trait locus (cis-eQTL) for SLC2A2 in 1,226 human liver samples, suggesting a key role for hepatic GLUT2 in regulation of metformin action. Among obese individuals, C-allele homozygotes at rs8192675 had a 0.33% (3.6 mmol/mol) greater absolute HbA1c reduction than T-allele homozygotes. This was about half the effect seen with the addition of a DPP-4 inhibitor, and equated to a dose difference of 550 mg of metformin, suggesting rs8192675 as a potential biomarker for stratified medicine

Совершенствование технологий для осуществления рентабельного процесса добычи нефти на малодебитном фонде скважин

Материалы XII Междунар. науч. конф. студентов, магистрантов, аспирантов и молодых ученых, Гомель, 16–17 мая 2019 г

Genome Database of the Latvian Population (LGDB): Design, Goals, and Primary Results

Background: The Genome Database of the Latvian Population (LGDB) is a national biobank that collects, maintains, and processes health information, data, and biospecimens collected from representatives of the Latvian population. These specimens serve as a foundation for epidemiological research and prophylactic and therapeutic purposes. Methods: Participant recruitment and biomaterial and data processing were performed according to specifically designed standard protocols, taking into consideration international quality requirements. Legal and ethical aspects, including broad informed consent and personal data protection, were applied according to legal norms of the Republic of Latvia. Results: Since its start in 2006, the LGDB is comprised of biosamples and associated phenotypic and clinical information from over 31,504 participants, constituting approximately 1.5% of the Latvian population. The LGDB represents a mixed-design biobank and includes participants from the general population as well as disease-based cohorts. The standard set of biosamples stored in the LGDB consists of DNA, plasma, serum, and white blood cells; in some cohorts, these samples are complemented by cancer biopsies and microbiome and urine samples. The LGDB acts as a core structure for the Latvian Biomedical Research and Study Centre (BMC), representing the national node of Latvia in Biobanking and BioMolecular resources Research Infrastructure – European Research Infrastructure Consortium (BBMRI-ERIC). Conclusions: The development of the LGDB has enabled resources for biomedical research and promoted genetic testing in Latvia. Further challenges of the LGDB are the enrichment and harmonization of collected biosamples and data, the follow-up of selected participant groups, and continued networking and participation in collaboration projects