Evidence map›Paper›PMID 26776201›Full record

ArticlePacific Symposium on Biocomputing. Pacific Symposium on Biocomputing2016

THE CHALLENGES IN USING ELECTRONIC HEALTH RECORDS FOR PHARMACOGENOMICS AND PRECISION MEDICINE RESEARCH.

Sarah M Laper, Nicole A Restrepo, Dana C Crawford

Abstract read
In one paragraph

Article in Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Lessons Learned When Introducing Pharmacogenomic Panel Testing into Clinical Practice.Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research · 2017
    Article
  4. Article
  5. 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

3 authors.

Sarah M LaperEastern Virginia Medical School, Norfolk, VA, 23507, USA, lapersm@evms.edu.
Nicole A Restrepo
Dana C Crawford

Funding

VANDERBILT UNIVERSITY CTSA FOR PEDIATRIC RESEARCHUL1RR024975 · NCRR · VANDERBILT UNIVERSITY · PI BERNARD, GORDON RAPHAEL · 2007 to 2011
$45.7M
The Vanderbilt Institute for Clinical and Translational Research (VICTR)UL1TR000445 · NCATS · VANDERBILT UNIVERSITY MEDICAL CENTER · PI BERNARD, GORDON RAPHAEL · 2012 to 2016
$41.4M
Epidemiologic Architecture for Genes Linked to Environment (EAGLE)U01HG004798 · NHGRI · VANDERBILT UNIVERSITY · PI CRAWFORD, DANA C · 2008 to 2013
$8.8M
TRAINING IN COMPUTATIONAL GENOMIC EPIDEMIOLOGY OF CANCERR25CA094186 · NCI · CASE WESTERN RESERVE UNIVERSITY · PI LI, LI · 2002 to 2016
$6.8M
NCATS NIH HHS 2 UL1 TR000445-06NCATS NIH HHS UL1 TR000445NCI NIH HHS R25 CA094186NCRR NIH HHS UL1 RR024975NCRR NIH HHS UL1 RR024975-01NHGRI NIH HHS U01 HG004798
6 · The paper itself

Abstract

Access and utilization of electronic health records with extensive medication lists and genetic profiles is rapidly advancing discoveries in pharmacogenomics. In this study, we analyzed ~116,000 variants on the Illumina Metabochip for response to antihypertensive and lipid lowering medications in African American adults from BioVU, the Vanderbilt University Medical Center's biorepository linked to de-identified electronic health records. Our study population included individuals who were prescribed an antihypertensive or lipid lowering medication, and who had both pre- and post-medication blood pressure or low-density lipoprotein cholesterol (LDL-C) measurements, respectively. Among those with pre- and post-medication systolic and diastolic blood pressure measurements (n=2,268), the average change in systolic and diastolic blood pressure was -0.6 mg Hg and -0.8 mm Hg, respectively. Among those with pre- and post-medication LDL-C measurements (n=1,244), the average change in LDL-C was -26.3 mg/dL. SNPs were tested for an association with change and percent change in blood pressure or blood levels of LDL-C. After adjustment for multiple testing, we did not observe any significant associations, and we were not able to replicate previously reported associations, such as in APOE and LPA, from the literature. The present study illustrates the benefits and challenges with using electronic health records linked to biorepositories for pharmacogenomic studies.

Indexed as

AdultAgedAged, 80 and overApolipoproteins EBlack or African AmericanBlood PressureCholesterol, LDLComputational BiologyElectronic Health RecordsFemaleGenetic Association StudiesHumansHypoglycemic AgentsHypolipidemic AgentsLipoprotein(a)MaleApolipoproteins ECholesterol, LDLHypoglycemic AgentsHypolipidemic AgentsLipoprotein(a)

Identifiers

PMID26776201
PMCPMC4720980

What OpenQuestion holds

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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.