Literature DB >> 20415552

Biobanking and pharmacogenomics.

Catherine A McCarty1, Russell A Wilke.   

Abstract

The study of genetic determinants underlying drug outcome is rapidly advancing. Initial success was realized within the context of candidate pharmacokinetic genes and serious adverse drug reactions, particularly for drugs with narrow therapeutic indices. Although genetic predictors of outcome have proven useful in other contexts, effect size has typically been small. To address these challenges, the clinical and scientific communities have begun studying larger numbers of gene variants (often at the genome-wide level) in cohorts of increasing sample size. Electronic health records are being increasingly used for this purpose. Longitudinal data available in practice-based datasets will position investigators to characterize genetic factors with small but reproducible effects on drug outcome in the context of gene-environment interactions.

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Year:  2010        PMID: 20415552     DOI: 10.2217/pgs.10.13

Source DB:  PubMed          Journal:  Pharmacogenomics        ISSN: 1462-2416            Impact factor:   2.533


  25 in total

1.  Strategies for maintaining patient privacy in i2b2.

Authors:  Shawn N Murphy; Vivian Gainer; Michael Mendis; Susanne Churchill; Isaac Kohane
Journal:  J Am Med Inform Assoc       Date:  2011-10-07       Impact factor: 4.497

2.  A common 5'-UTR variant in MATE2-K is associated with poor response to metformin.

Authors:  J H Choi; S W Yee; A H Ramirez; K M Morrissey; G H Jang; P J Joski; J A Mefford; S E Hesselson; A Schlessinger; G Jenkins; R A Castro; S J Johns; D Stryke; A Sali; T E Ferrin; J S Witte; P-Y Kwok; D M Roden; R A Wilke; C A McCarty; R L Davis; K M Giacomini
Journal:  Clin Pharmacol Ther       Date:  2011-09-28       Impact factor: 6.875

3.  Importance of multi-modal approaches to effectively identify cataract cases from electronic health records.

Authors:  Peggy L Peissig; Luke V Rasmussen; Richard L Berg; James G Linneman; Catherine A McCarty; Carol Waudby; Lin Chen; Joshua C Denny; Russell A Wilke; Jyotishman Pathak; David Carrell; Abel N Kho; Justin B Starren
Journal:  J Am Med Inform Assoc       Date:  2012 Mar-Apr       Impact factor: 4.497

Review 4.  Using electronic health records to drive discovery in disease genomics.

Authors:  Isaac S Kohane
Journal:  Nat Rev Genet       Date:  2011-05-18       Impact factor: 53.242

Review 5.  Asthma Pharmacogenomics: 2015 Update.

Authors:  Joshua S Davis; Scott T Weiss; Kelan G Tantisira
Journal:  Curr Allergy Asthma Rep       Date:  2015-07       Impact factor: 4.806

6.  Facilitating pharmacogenetic studies using electronic health records and natural-language processing: a case study of warfarin.

Authors:  Hua Xu; Min Jiang; Matt Oetjens; Erica A Bowton; Andrea H Ramirez; Janina M Jeff; Melissa A Basford; Jill M Pulley; James D Cowan; Xiaoming Wang; Marylyn D Ritchie; Daniel R Masys; Dan M Roden; Dana C Crawford; Joshua C Denny
Journal:  J Am Med Inform Assoc       Date:  2011 Jul-Aug       Impact factor: 4.497

Review 7.  Risk factors for autism: translating genomic discoveries into diagnostics.

Authors:  Stephen W Scherer; Geraldine Dawson
Journal:  Hum Genet       Date:  2011-06-24       Impact factor: 4.132

8.  Genotype-environment interactions and their translational implications.

Authors:  Tesfaye M Baye; Tilahun Abebe; Russell A Wilke
Journal:  Per Med       Date:  2011-01       Impact factor: 2.512

9.  Modeling drug exposure data in electronic medical records: an application to warfarin.

Authors:  Mei Liu; Min Jiang; Vivian K Kawai; Charles M Stein; Dan M Roden; Joshua C Denny; Hua Xu
Journal:  AMIA Annu Symp Proc       Date:  2011-10-22

10.  Characterization of statin dose response in electronic medical records.

Authors:  W-Q Wei; Q Feng; L Jiang; M S Waitara; O F Iwuchukwu; D M Roden; M Jiang; H Xu; R M Krauss; J I Rotter; D A Nickerson; R L Davis; R L Berg; P L Peissig; C A McCarty; R A Wilke; J C Denny
Journal:  Clin Pharmacol Ther       Date:  2013-10-04       Impact factor: 6.875

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