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Leveraging an Electronic Health Record-Linked Biorepository to Generate a Metformin Pharmacogenomics Hypothesis
Metformin is a first-line antihyperglycemic agent commonly prescribed in type 2 diabetes mellitus (T2DM), but whose pharmacogenomics are not clearly understood. Further, due to accumulating evidence highlighting the potential for metformin in cancer prevention and treatment efforts it is imperative...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Medical Informatics Association
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4525256/ https://www.ncbi.nlm.nih.gov/pubmed/26306225 |
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author | Breitenstein, Matthew K. Wang, Liewei Simon, Gyorgy Ryu, Euijung Armasu, Sebastian M. Ray, Balmiki Weinshilboum, Richard M. Pathak, Jyotishman |
author_facet | Breitenstein, Matthew K. Wang, Liewei Simon, Gyorgy Ryu, Euijung Armasu, Sebastian M. Ray, Balmiki Weinshilboum, Richard M. Pathak, Jyotishman |
author_sort | Breitenstein, Matthew K. |
collection | PubMed |
description | Metformin is a first-line antihyperglycemic agent commonly prescribed in type 2 diabetes mellitus (T2DM), but whose pharmacogenomics are not clearly understood. Further, due to accumulating evidence highlighting the potential for metformin in cancer prevention and treatment efforts it is imperative to understand molecular mechanisms of metformin. In this electronic health record(EHR)-based study we explore the potential association of the flavin-containing monooxygenase(FMO)-5 gene, a biologically plausible biotransformer of metformin, and modifying glycemic response to metformin treatment. Using a cohort of 258 T2DM patients who had new metformin exposure, existing genetic data, and longitudinal electronic health records, we compared genetic variation within FMO5 to change in glycemic response. Gene-level and SNP-level analysis identified marginally significant associations for FMO5 variation, representing an EHR-driven pharmacogenetics hypothesis for a potential novel mechanism for metformin biotransformation. However, functional validation of this EHR-based hypothesis is necessary to ascertain its clinical and biological significance. |
format | Online Article Text |
id | pubmed-4525256 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | American Medical Informatics Association |
record_format | MEDLINE/PubMed |
spelling | pubmed-45252562015-08-24 Leveraging an Electronic Health Record-Linked Biorepository to Generate a Metformin Pharmacogenomics Hypothesis Breitenstein, Matthew K. Wang, Liewei Simon, Gyorgy Ryu, Euijung Armasu, Sebastian M. Ray, Balmiki Weinshilboum, Richard M. Pathak, Jyotishman AMIA Jt Summits Transl Sci Proc Articles Metformin is a first-line antihyperglycemic agent commonly prescribed in type 2 diabetes mellitus (T2DM), but whose pharmacogenomics are not clearly understood. Further, due to accumulating evidence highlighting the potential for metformin in cancer prevention and treatment efforts it is imperative to understand molecular mechanisms of metformin. In this electronic health record(EHR)-based study we explore the potential association of the flavin-containing monooxygenase(FMO)-5 gene, a biologically plausible biotransformer of metformin, and modifying glycemic response to metformin treatment. Using a cohort of 258 T2DM patients who had new metformin exposure, existing genetic data, and longitudinal electronic health records, we compared genetic variation within FMO5 to change in glycemic response. Gene-level and SNP-level analysis identified marginally significant associations for FMO5 variation, representing an EHR-driven pharmacogenetics hypothesis for a potential novel mechanism for metformin biotransformation. However, functional validation of this EHR-based hypothesis is necessary to ascertain its clinical and biological significance. American Medical Informatics Association 2015-03-23 /pmc/articles/PMC4525256/ /pubmed/26306225 Text en ©2015 AMIA - All rights reserved. This is an Open Access article: verbatim copying and redistribution of this article are permitted in all media for any purpose |
spellingShingle | Articles Breitenstein, Matthew K. Wang, Liewei Simon, Gyorgy Ryu, Euijung Armasu, Sebastian M. Ray, Balmiki Weinshilboum, Richard M. Pathak, Jyotishman Leveraging an Electronic Health Record-Linked Biorepository to Generate a Metformin Pharmacogenomics Hypothesis |
title | Leveraging an Electronic Health Record-Linked Biorepository to Generate a Metformin Pharmacogenomics Hypothesis |
title_full | Leveraging an Electronic Health Record-Linked Biorepository to Generate a Metformin Pharmacogenomics Hypothesis |
title_fullStr | Leveraging an Electronic Health Record-Linked Biorepository to Generate a Metformin Pharmacogenomics Hypothesis |
title_full_unstemmed | Leveraging an Electronic Health Record-Linked Biorepository to Generate a Metformin Pharmacogenomics Hypothesis |
title_short | Leveraging an Electronic Health Record-Linked Biorepository to Generate a Metformin Pharmacogenomics Hypothesis |
title_sort | leveraging an electronic health record-linked biorepository to generate a metformin pharmacogenomics hypothesis |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4525256/ https://www.ncbi.nlm.nih.gov/pubmed/26306225 |
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