Literature DB >> 25991289

Using EHR-Linked Biobank Data to Study Metformin Pharmacogenomics.

Matthew K Breitenstein1, Gyorgy Simon2, Euijung Ryu1, Sebastian M Armasu1, Richard M Weinshilboum3, Liewei Wang3, Jyotishman Pathak1.   

Abstract

Metformin is a commonly prescribed diabetes medication whose mechanism of action is poorly understood. In this study we utilized EHR-linked biobank data to elucidate the impact of genomic variation on glycemic response to metformin. Our study found significant gene- and SNP-level associations within the beta-2 subunit of the heterotrimeric adenosine monophosphate-activated protein kinase complex. Using EHR phenotypes where were able to add additional clarity to ongoing metformin pharmacogenomic dialogue.

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Year:  2015        PMID： 25991289      PMCID： PMC5051541     

Source DB:  PubMed          Journal:  Stud Health Technol Inform        ISSN： 0926-9630


  13 in total

Review 1.  Metformin pathways: pharmacokinetics and pharmacodynamics.

Authors:  Li Gong; Srijib Goswami; Kathleen M Giacomini; Russ B Altman; Teri E Klein
Journal:  Pharmacogenet Genomics       Date:  2012-11       Impact factor: 2.089

2.  Estimating the contribution of genes and environment to variation in renal drug clearance.

Authors:  Maya K Leabman; Kathleen M Giacomini
Journal:  Pharmacogenetics       Date:  2003-09

3.  The pharmacogenetics of metformin and its impact on plasma metformin steady-state levels and glycosylated hemoglobin A1c.

Authors:  Mette M H Christensen; Charlotte Brasch-Andersen; Henrik Green; Flemming Nielsen; Per Damkier; Henning Beck-Nielsen; Kim Brosen
Journal:  Pharmacogenet Genomics       Date:  2011-12       Impact factor: 2.089

4.  Mayo Genome Consortia: a genotype-phenotype resource for genome-wide association studies with an application to the analysis of circulating bilirubin levels.

Authors:  Suzette J Bielinski; High Seng Chai; Jyotishman Pathak; Jayant A Talwalkar; Paul J Limburg; Rachel E Gullerud; Hugues Sicotte; Eric W Klee; Jason L Ross; Jean-Pierre A Kocher; Iftikhar J Kullo; John A Heit; Gloria M Petersen; Mariza de Andrade; Christopher G Chute
Journal:  Mayo Clin Proc       Date:  2011-06-06       Impact factor: 7.616

5.  Use of diverse electronic medical record systems to identify genetic risk for type 2 diabetes within a genome-wide association study.

Authors:  Abel N Kho; M Geoffrey Hayes; Laura Rasmussen-Torvik; Jennifer A Pacheco; William K Thompson; Loren L Armstrong; Joshua C Denny; Peggy L Peissig; Aaron W Miller; Wei-Qi Wei; Suzette J Bielinski; Christopher G Chute; Cynthia L Leibson; Gail P Jarvik; David R Crosslin; Christopher S Carlson; Katherine M Newton; Wendy A Wolf; Rex L Chisholm; William L Lowe
Journal:  J Am Med Inform Assoc       Date:  2011-11-19       Impact factor: 4.497

Review 6.  AMP-activated protein kinase, a metabolic master switch: possible roles in type 2 diabetes.

Authors:  W W Winder; D G Hardie
Journal:  Am J Physiol       Date:  1999-07

Review 7.  Pharmacogenetic variation and metformin response.

Authors:  Suning Chen; Jie Zhou; Miaomiao Xi; Yanyan Jia; Yan Wong; Jinyi Zhao; Likun Ding; Jian Zhang; Aidong Wen
Journal:  Curr Drug Metab       Date:  2013-12       Impact factor: 3.731

Review 8.  Management of hyperglycemia in type 2 diabetes: a patient-centered approach: position statement of the American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD).

Authors:  Silvio E Inzucchi; Richard M Bergenstal; John B Buse; Michaela Diamant; Ele Ferrannini; Michael Nauck; Anne L Peters; Apostolos Tsapas; Richard Wender; David R Matthews
Journal:  Diabetes Care       Date:  2012-04-19       Impact factor: 19.112

9.  Metformin pharmacogenomics: current status and future directions.

Authors:  Aaron C Pawlyk; Kathleen M Giacomini; Catherine McKeon; Alan R Shuldiner; Jose C Florez
Journal:  Diabetes       Date:  2014-08       Impact factor: 9.461

Review 10.  Metformin therapy and risk of cancer in patients with type 2 diabetes: systematic review.

Authors:  Monica Franciosi; Giuseppe Lucisano; Emanuela Lapice; Giovanni F M Strippoli; Fabio Pellegrini; Antonio Nicolucci
Journal:  PLoS One       Date:  2013-08-02       Impact factor: 3.240
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  1 in total

Review 1.  Pharmacogenomics cascade testing (PhaCT): a novel approach for preemptive pharmacogenomics testing to optimize medication therapy.

Authors:  Don Roosan; Angela Hwang; Moom R Roosan
Journal:  Pharmacogenomics J       Date:  2020-08-25       Impact factor: 3.550
  1 in total

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