Evidence map›Paper›PMID 27984508›Full record

ArticlePharmacogenetics and genomics2017

Characterization of ADME gene variation in 21 populations by exome sequencing.

Daniel H Hovelson, Zhengyu Xue, Matthew Zawistowski, Margaret G Ehm, Elizabeth C Harris, Sophie L Stocker, Annette S Gross, In-Jin Jang, Ichiro Ieiri, Jong-Eun Lee and 4 more

Open access · hybridAbstract read
In one paragraph

Article in Pharmacogenetics and genomics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed
3.8field-weighted citation impact, top 8% of its field
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

30 citing papers in PubMed, 49 citations in OpenAlex.

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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 at 2 institutions in 3 countries.

Daniel H HovelsonaGlaxoSmithKline Research and Development, Durham, North Carolina bGlaxoSmithKline Research and Development, King of Prussia, Pennsylvania cDepartment of Biostatistics and/or Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan, USA dGlaxoSmithKline Research and Development, Sydney, New South Wales, Australia eSeoul National University fDNA Link Inc., Seoul, Korea gKyushu University, Fukuoka, Japan.
Zhengyu Xue
Matthew Zawistowski
Margaret G Ehm
Elizabeth C Harris
Sophie L Stocker
Annette S Gross
In-Jin Jang
Ichiro Ieiri
Jong-Eun Lee
Lon R Cardon
Stephanie L Chissoe
Gonçalo Abecasis
Matthew R Nelson
Creative Commons · USSt Vincent's Hospital Sydney · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveProteins involving absorption, distribution, metabolism, and excretion (ADME) play a critical role in drug pharmacokinetics. The type and frequency of genetic variation in the ADME genes differ among populations. The aim of this study was to systematically investigate common and rare ADME coding variation in diverse ethnic populations by exome sequencing. MATERIALS AND

methodsData derived from commercial exome capture arrays and next-generation sequencing were used to characterize coding variation in 298 ADME genes in 251 Northeast Asians and 1181 individuals from the 1000 Genomes Project.

resultsApproximately 75% of the ADME coding sequence was captured at high quality across the joint samples harboring more than 8000 variants, with 49% of individuals carrying at least one 'knockout' allele. ADME genes carried 50% more nonsynonymous variation than non-ADME genes (P=8.2×10) and showed significantly greater levels of population differentiation (P=7.6×10). Out of the 2135 variants identified that were predicted to be deleterious, 633 were not on commercially available ADME or general-purpose genotyping arrays. Forty deleterious variants within important ADME genes, with frequencies of at least 2% in at least one population, were identified as candidates for future pharmacogenetic studies.

conclusionExome sequencing was effective in accurately genotyping most ADME variants important for pharmacogenetic research, in addition to identifying rare or potentially de novo coding variants that may be clinically meaningful. Furthermore, as a class, ADME genes are more variable and less sensitive to purifying selection than non-ADME genes.

Indexed as

ExomeGenetics, PopulationGenetic VariationHigh-Throughput Nucleotide SequencingHumansMaleOligonucleotide Array Sequence AnalysisPolymorphism, Single NucleotidePopulation GroupsPrincipal Component AnalysisSequence Analysis, DNA

Identifiers

PMID27984508
PMCPMC5287433
OpenAlexW2562778304

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

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.