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Quantifying rare, deleterious variation in 12 human cytochrome P450 drug-metabolism genes in a large-scale exome dataset

Overview of attention for article published in Human Molecular Genetics, November 2013
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (84th percentile)
  • Good Attention Score compared to outputs of the same age and source (77th percentile)

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Title
Quantifying rare, deleterious variation in 12 human cytochrome P450 drug-metabolism genes in a large-scale exome dataset
Published in
Human Molecular Genetics, November 2013
DOI 10.1093/hmg/ddt588
Pubmed ID
Authors

Adam S. Gordon, Holly K. Tabor, Andrew D. Johnson, Beverly M. Snively, Themistocles L. Assimes, Paul L. Auer, John P.A. Ioannidis, Ulrike Peters, Jennifer G. Robinson, Lara E. Sucheston, Danxin Wang, Nona Sotoodehnia, Jerome I. Rotter, Bruce M. Psaty, Rebecca D. Jackson, David M. Herrington, Christopher J. O'Donnell, Alexander P. Reiner, Stephen S. Rich, Mark J. Rieder, Michael J. Bamshad, Deborah A. Nickerson

Abstract

The study of genetic influences on drug response and efficacy ('pharmacogenetics') has existed for over 50 years. Yet, we still lack a complete picture of how genetic variation, both common and rare, affects each individual's responses to medications. Exome sequencing is a promising alternative method for pharmacogenetic discovery as it provides information on both common and rare variation in large numbers of individuals. Using exome data from 2203 AA and 4300 Caucasian individuals through the NHLBI Exome Sequencing Project, we conducted a survey of coding variation within 12 Cytochrome P450 (CYP) genes that are collectively responsible for catalyzing nearly 75% of all known Phase I drug oxidation reactions. In addition to identifying many polymorphisms with known pharmacogenetic effects, we discovered over 730 novel nonsynonymous alleles across the 12 CYP genes of interest. These alleles include many with diverse functional effects such as premature stop codons, aberrant splicesites and mutations at conserved active site residues. Our analysis considering both novel, predicted functional alleles as well as known, actionable CYP alleles reveals that rare, deleterious variation contributes markedly to the overall burden of pharmacogenetic alleles within the populations considered, and that the contribution of rare variation to this burden is over three times greater in AA individuals as compared with Caucasians. While most of these impactful alleles are individually rare, 7.6-11.7% of individuals interrogated in the study carry at least one newly described potentially deleterious alleles in a major drug-metabolizing CYP.

X Demographics

X Demographics

The data shown below were collected from the profiles of 12 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 86 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Colombia 1 1%
Brazil 1 1%
Sweden 1 1%
South Africa 1 1%
India 1 1%
United Kingdom 1 1%
Mexico 1 1%
United States 1 1%
Unknown 78 91%

Demographic breakdown

Readers by professional status Count As %
Researcher 25 29%
Student > Ph. D. Student 11 13%
Professor 8 9%
Other 8 9%
Professor > Associate Professor 8 9%
Other 18 21%
Unknown 8 9%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 24 28%
Agricultural and Biological Sciences 20 23%
Medicine and Dentistry 11 13%
Pharmacology, Toxicology and Pharmaceutical Science 5 6%
Chemistry 3 3%
Other 5 6%
Unknown 18 21%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 8. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 25 May 2014.
All research outputs
#4,506,170
of 24,598,501 outputs
Outputs from Human Molecular Genetics
#1,953
of 8,215 outputs
Outputs of similar age
#50,728
of 317,860 outputs
Outputs of similar age from Human Molecular Genetics
#25
of 109 outputs
Altmetric has tracked 24,598,501 research outputs across all sources so far. Compared to these this one has done well and is in the 81st percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,215 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.1. This one has done well, scoring higher than 76% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 317,860 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 84% of its contemporaries.
We're also able to compare this research output to 109 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 77% of its contemporaries.