Using EHR-Linked Biobank Data to Study Metformin Pharmacogenomics

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

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

1 Citation (Scopus)

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.

Original languageEnglish (US)
Title of host publicationStudies in Health Technology and Informatics
PublisherIOS Press
Pages914-918
Number of pages5
Volume210
ISBN (Print)9781614995111
DOIs
StatePublished - 2015
Event26th Medical Informatics in Europe Conference, MIE 2015 - Madrid, Spain
Duration: May 27 2015May 29 2015

Other

Other26th Medical Informatics in Europe Conference, MIE 2015
CountrySpain
CityMadrid
Period5/27/155/29/15

Fingerprint

Metformin
Medical problems
Genes
Proteins
Pharmacogenetics
Adenosine Monophosphate
Protein Kinases
Single Nucleotide Polymorphism
Phenotype
Pharmacogenomic Testing

Keywords

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

ASJC Scopus subject areas

  • Biomedical Engineering
  • Health Informatics
  • Health Information Management

Cite this

Breitenstein, M. K., Simon, G., Ryu, E., Armasu, S. M., Weinshilboum, R. M., Wang, L. M., & Pathak, J. (2015). Using EHR-Linked Biobank Data to Study Metformin Pharmacogenomics. In Studies in Health Technology and Informatics (Vol. 210, pp. 914-918). IOS Press. https://doi.org/10.3233/978-1-61499-512-8-914

Using EHR-Linked Biobank Data to Study Metformin Pharmacogenomics. / Breitenstein, Matthew K.; Simon, Gyorgy; Ryu, Euijung; Armasu, Sebastian M.; Weinshilboum, Richard M; Wang, Liewei M; Pathak, Jyotishman.

Studies in Health Technology and Informatics. Vol. 210 IOS Press, 2015. p. 914-918.

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

Breitenstein, MK, Simon, G, Ryu, E, Armasu, SM, Weinshilboum, RM, Wang, LM & Pathak, J 2015, Using EHR-Linked Biobank Data to Study Metformin Pharmacogenomics. in Studies in Health Technology and Informatics. vol. 210, IOS Press, pp. 914-918, 26th Medical Informatics in Europe Conference, MIE 2015, Madrid, Spain, 5/27/15. https://doi.org/10.3233/978-1-61499-512-8-914
Breitenstein MK, Simon G, Ryu E, Armasu SM, Weinshilboum RM, Wang LM et al. Using EHR-Linked Biobank Data to Study Metformin Pharmacogenomics. In Studies in Health Technology and Informatics. Vol. 210. IOS Press. 2015. p. 914-918 https://doi.org/10.3233/978-1-61499-512-8-914
Breitenstein, Matthew K. ; Simon, Gyorgy ; Ryu, Euijung ; Armasu, Sebastian M. ; Weinshilboum, Richard M ; Wang, Liewei M ; Pathak, Jyotishman. / Using EHR-Linked Biobank Data to Study Metformin Pharmacogenomics. Studies in Health Technology and Informatics. Vol. 210 IOS Press, 2015. pp. 914-918
@inproceedings{31236c69171544db8285ee65ac7918af,
title = "Using EHR-Linked Biobank Data to Study Metformin Pharmacogenomics",
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.",
keywords = "Biobank, Electronic Health Records, Metformin, Pharmacogenomics, Type 2 Diabetes Mellitus",
author = "Breitenstein, {Matthew K.} and Gyorgy Simon and Euijung Ryu and Armasu, {Sebastian M.} and Weinshilboum, {Richard M} and Wang, {Liewei M} and Jyotishman Pathak",
year = "2015",
doi = "10.3233/978-1-61499-512-8-914",
language = "English (US)",
isbn = "9781614995111",
volume = "210",
pages = "914--918",
booktitle = "Studies in Health Technology and Informatics",
publisher = "IOS Press",

}

TY - GEN

T1 - Using EHR-Linked Biobank Data to Study Metformin Pharmacogenomics

AU - Breitenstein, Matthew K.

AU - Simon, Gyorgy

AU - Ryu, Euijung

AU - Armasu, Sebastian M.

AU - Weinshilboum, Richard M

AU - Wang, Liewei M

AU - Pathak, Jyotishman

PY - 2015

Y1 - 2015

N2 - 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.

AB - 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.

KW - Biobank

KW - Electronic Health Records

KW - Metformin

KW - Pharmacogenomics

KW - Type 2 Diabetes Mellitus

UR - http://www.scopus.com/inward/record.url?scp=84937485223&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84937485223&partnerID=8YFLogxK

U2 - 10.3233/978-1-61499-512-8-914

DO - 10.3233/978-1-61499-512-8-914

M3 - Conference contribution

SN - 9781614995111

VL - 210

SP - 914

EP - 918

BT - Studies in Health Technology and Informatics

PB - IOS Press

ER -