Henry Dunnenberger

Dr. Henry Dunnenberger

orcid

Research Focus & Metrics

Academic Career Length

16Years (2011-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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20 December 2016 in Clinical Pharmacology & Therapeutics
Verified
Journal Article
Open access
PDF file
JHJk Hicks
Jk Hicks
KSK Sangkuhl
K Sangkuhl
JSJj Swen
Jj Swen
VEVl Ellingrod
Vl Ellingrod
DMDj Müller
Dj Müller
JSJc Stingl
Jc Stingl
Click on the article title to read more.

23 January 2014 in Clinical Pharmacology & Therapeutics
Verified
Journal Article
Closed access
KCKristine R. Crews
Kristine R. Crews
AGA Gaedigk
A Gaedigk
HDHenry Dunnenberger
Henry Dunnenberger
JLJ S Leeder
J S Leeder
TKT E Klein
T E Klein
TST C Skaar
T C Skaar

1 February 2017 in Genetics in Medicine
Verified
Journal Article
Open access
PDF file
KCKelly E Caudle
Kelly E Caudle
HDHenry Dunnenberger
Henry Dunnenberger
RFRobert R. Freimuth
Robert R. Freimuth
JPJosh F. Peterson
Josh F. Peterson
JBJonathan D. Burlison
Jonathan D. Burlison
JHJames M. Hoffman
James M. Hoffman
Reporting and sharing pharmacogenetic test results across clinical laboratories and electronic health records is a crucial step toward the implementation of clinical pharmacogenetics, but allele function and phenotype terms are not standardized. Our goal was to develop terms that can be broadly applied to characterize pharmacogenetic allele function and inferred phenotypes. Terms currently used by genetic testing laboratories and in the literature were identified. The Clinical Pharmacogenetics Implementation Consortium (CPIC) used the Delphi method to obtain a consensus and agree on uniform terms among pharmacogenetic experts. Experts with diverse involvement in at least one area of pharmacogenetics (clinicians, researchers, genetic testing laboratorians, pharmacogenetics implementers, and clinical informaticians; n = 58) participated. After completion of five surveys, a consensus (>70%) was reached with 90% of experts agreeing to the final sets of pharmacogenetic terms. The proposed standardized pharmacogenetic terms will improve the understanding and interpretation of pharmacogenetic tests and reduce confusion by maintaining consistent nomenclature. These standard terms can also facilitate pharmacogenetic data sharing across diverse electronic health care record systems with clinical decision support. Genet Med 19 2, 215–223.

6 January 2015 in Annual Review of Pharmacology and Toxicology
Verified
Journal Article
Closed access
HDHenry Dunnenberger
Henry Dunnenberger
KCKristine R. Crews
Kristine R. Crews
JHJames M. Hoffman
James M. Hoffman
KCKelly E Caudle
Kelly E Caudle
UBUlrich Broeckel
Ulrich Broeckel
MRMary V. Relling
Mary V. Relling
Although the field of pharmacogenetics has existed for decades, practioners have been slow to implement pharmacogenetic testing in clinical care. Numerous publications describe the barriers to clinical implementation of pharmacogenetics. Recently, several freely available resources have been developed to help address these barriers. In this review, we discuss current programs that use preemptive genotyping to optimize the pharmacotherapy of patients. Array-based preemptive testing includes a large number of relevant pharmacogenes that impact multiple high-risk drugs. Using a preemptive approach allows genotyping results to be available prior to any prescribing decision so that genomic variation may be considered as an inherent patient characteristic in the planning of therapy. This review describes the common elements among programs that have implemented preemptive genotyping and highlights key processes for implementation, including clinical decision support.

28 December 2011 in Clinical Pharmacology & Therapeutics
Verified
Journal Article
Closed access
PDF file
KCKristine R. Crews
Kristine R. Crews
AGA Gaedigk
A Gaedigk
HDHenry Dunnenberger
Henry Dunnenberger
TKT E Klein
T E Klein
DSD D Shen
D D Shen
TST C Skaar
T C Skaar

2 February 2018 in Clinical Pharmacology & Therapeutics
Verified
Journal Article
Open access
PDF file
EPElizabeth J. Phillips
Elizabeth J. Phillips
CSChonlaphat Sukasem
Chonlaphat Sukasem
MWMichelle Whirl‐Carrillo
Michelle Whirl‐Carrillo
DMDaniel J. Müller
Daniel J. Müller
HDHenry Dunnenberger
Henry Dunnenberger
MPMunir Pirmohamed
Munir Pirmohamed
The variant alleleHLA‐B*15:02is strongly associated with greater risk of Stevens–Johnson syndrome (SJS) and toxic epidermal necrolysis (TEN) in patients treated with carbamazepine or oxcarbazepine. The variant alleleHLA‐A*31:01is associated with greater risk of maculopapular exanthema, drug reaction with eosinophilia and systemic symptoms, and SJS/TEN in patients treated with carbamazepine. We summarize evidence from the published literature supporting these associations and provide recommendations for carbamazepine and oxcarbazepine use based onHLAgenotypes.