Evidence map›Paper›PMID 23651022›Full record

ArticlePharmacogenomics2013

Assessment of a pharmacogenomic marker panel in a polypharmacy population identified from electronic medical records.

Matthew T Oetjens, Joshua C Denny, Marylyn D Ritchie, Niloufar B Gillani, Danielle M Richardson, Nicole A Restrepo, Jill M Pulley, Holli H Dilks, Melissa A Basford, Erica Bowton and 4 more

Abstract read
In one paragraph

Article in Pharmacogenomics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

16 citing papers in PubMed.

  1. Article
  2. ThePharmacogenomics and personalized medicine · 2022
    Article
  3. Article
  4. Precision Pharmacotherapy: Integrating Pharmacogenomics into Clinical Pharmacy Practice.Journal of the American College of Clinical Pharmacy : JACCP · 2019
    Article
  5. Review
  6. Implementation of inpatient models of pharmacogenetics programs.American journal of health-system pharmacy : AJHP : official journal of the American Society of Health-System Pharmacists · 2016
    Review
  7. Article
  8. Article
  9. Article
  10. Article
  11. THE CHALLENGES IN USING ELECTRONIC HEALTH RECORDS FOR PHARMACOGENOMICS AND PRECISION MEDICINE RESEARCH.Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing · 2016
    Article
  12. Article
  13. Review
  14. Review
  15. Article
  16. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors.

Matthew T OetjensCenter for Human Genetics Research & Department of Molecular Physiology & Biophysics, Vanderbilt University, 2215 Garland Avenue, 519 Light Hall, Nashville, TN 37232-0700, USA.
Joshua C Denny
Marylyn D Ritchie
Niloufar B Gillani
Danielle M Richardson
Nicole A Restrepo
Jill M Pulley
Holli H Dilks
Melissa A Basford
Erica Bowton
Dan R Masys
Russell A Wilke
Dan M Roden
Dana C Crawford

Funding

The Vanderbilt Institute for Clinical and Translational Research (VICTR)UL1TR000445 · NCATS · VANDERBILT UNIVERSITY MEDICAL CENTER · PI BERNARD, GORDON RAPHAEL · 2012 to 2016
$41.4M
Pharmacogenomics of Arrhythmia TherapyU19HL065962 · NHLBI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI RODEN, DAN M · 2010 to 2014
$17.4M
VESPA: Vanderbilt Electronic Systems for Pharmacogenomic AssessmentRC2GM092618 · NIGMS · VANDERBILT UNIVERSITY · PI DENNY, JOSHUA C., RODEN, DAN M · 2009 to 2010
$6.4M
Vanderbilt Genome Electronic Records ProjectU01HG006378 · NHGRI · VANDERBILT UNIVERSITY · PI RODEN, DAN M · 2011 to 2014
$4.0M
Training Program on Genetic Variation and Human PhenotypesT32GM080178 · NIGMS · VANDERBILT UNIVERSITY · PI COX, NANCY J, SAMUELS, DAVID C · 2007 to 2021
$3.1M
Training Program in Quantitative Ocular GenomicsT32EY021453 · NEI · VANDERBILT UNIVERSITY · PI BRANTLEY, MILAM A, COX, NANCY J · 2011 to 2020
$1.4M
NCATS NIH HHS UL1 TR000445NEI NIH HHS T32 EY021453NHGRI NIH HHS U01 HG006378NHLBI NIH HHS U19 HL065962NIGMS NIH HHS RC2 GM092618NIGMS NIH HHS T32 GM080178
6 · The paper itself

Abstract

backgroundThe ADME Core Panel assays 184 variants across 34 pharmacogenes, many of which are difficult to accurately genotype with standard multiplexing methods.

methodsWe genotyped 326 frequently medicated individuals of European descent in Vanderbilt's biorepository linked to de-identified electronic medical records, BioVU, on the ADME Core Panel to assess quality and performance of the assay. We compared quality control metrics and determined the extent of direct and indirect marker overlap between the ADME Core Panel and the Illumina Omni1-Quad.

resultsWe found the quality of the ADME Core Panel data to be high, with exceptions in select copy number variants and markers in certain genes (notably CYP2D6). Most of the common variants on the ADME panel are genotyped by the Omni1, but absent rare variants and copy number variants could not be accurately tagged by single markers.

conclusionOur frequently medicated study population did not convincingly differ in allele frequency from reference populations, suggesting that heterogeneous clinical samples (with respect to medications) have similar allele frequency distributions in pharmacogenetics genes compared with reference populations.

Indexed as

Electronic Health RecordsPharmacogeneticsPolypharmacyAdultAgedAged, 80 and overCytochrome P-450 CYP2D6DNA Copy Number VariationsFemaleGene FrequencyGenetic MarkersGenome-Wide Association StudyGenotypeHumansMaleMiddle AgedCytochrome P-450 CYP2D6Genetic Markers

Identifiers

PMID23651022
PMCPMC3725600

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.