Using EHR-Linked Biobank Data to Study Metformin Pharmacogenomics

Matthew K. Breitenstein, Gyorgy J Simon, Euijung Ryu, Sebastian M. Armasu, Richard M. Weinshilboum, Liewei Wang, Jyotishman Pathak

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations


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.

Original languageEnglish (US)
Title of host publicationDigital Healthcare Empowering Europeans - Proceedings of MIE 2015
EditorsRonald Cornet, Lacramioara Stoicu-Tivadar, Ronald Cornet, Carlos Luis Parra Calderon, Stig Kjaer Andersen, Alexander Horbst, Mira Hercigonja-Szekeres
PublisherIOS Press
Number of pages5
ISBN (Electronic)9781614995111
StatePublished - 2015
Event26th Medical Informatics in Europe Conference, MIE 2015 - Madrid, Spain
Duration: May 27 2015May 29 2015

Publication series

NameStudies in Health Technology and Informatics
ISSN (Print)0926-9630
ISSN (Electronic)1879-8365


Other26th Medical Informatics in Europe Conference, MIE 2015

Bibliographical note

Publisher Copyright:
© 2015 European Federation for Medical Informatics (EFMI).


  • Biobank
  • Electronic Health Records
  • Metformin
  • Pharmacogenomics
  • Type 2 Diabetes Mellitus


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