Evidence map›Paper›PMID 27537706›Full record

ArticleGenetics in medicine : official journal of the American College of Medical Genetics2017

Assessing the capability of massively parallel sequencing for opportunistic pharmacogenetic screening.

David Ng, Celine S Hong, Larry N Singh, Jennifer J Johnston, James C Mullikin, Leslie G Biesecker

Abstract read
In one paragraph

Article in Genetics in medicine : official journal of the American College of Medical Genetics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 1 pooled it
–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

13 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Review
  5. Review
  6. Article
  7. Targeted Genotyping in Clinical Pharmacogenomics: What Is Missing?The Journal of molecular diagnostics : JMD · 2022
    Article
  8. Article
  9. Article
  10. Review
  11. Review
  12. Review
  13. 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

6 authors.

David NgMedical Genomics and Metabolic Genetics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, USA.ORCID 0000-0003-0574-751X
Celine S HongMedical Genomics and Metabolic Genetics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, USA.
Larry N SinghMedical Genomics and Metabolic Genetics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, USA.ORCID 0000-0002-2478-5864
Jennifer J JohnstonMedical Genomics and Metabolic Genetics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, USA.ORCID 0000-0002-1012-6358
James C MullikinNIH Intramural Sequencing Center, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, USA.ORCID 0000-0003-0825-3750
Leslie G BieseckerMedical Genomics and Metabolic Genetics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, USA.

Funding

Inter- and Intra-Species Comparative SequencingZIBHG000196 · NHGRI · NATIONAL HUMAN GENOME RESEARCH INSTITUTE · PI THOMAS, JAMES · 2009 to 2025
$177.6M
Genomic Ascertainment - Molecular and Genetic AspectsZIAHG200359 · NHGRI · NATIONAL HUMAN GENOME RESEARCH INSTITUTE · PI BIESECKER, LESLIE · 2009 to 2025
$19.7M
Comparative Genomics Unit ResearchZIAHG200330 · NHGRI · NATIONAL HUMAN GENOME RESEARCH INSTITUTE · PI MULLIKIN, JAMES C · 2009 to 2022
$17.9M
Genomic Ascertainment - Clinical and Behavioral AspectsZIAHG200387 · NHGRI · NATIONAL HUMAN GENOME RESEARCH INSTITUTE · PI BIESECKER, LESLIE · 2013 to 2025
$15.5M
Intramural NIH HHS ZIA HG200359Intramural NIH HHS ZIA HG200387
6 · The paper itself

Abstract

purposeThe aim of the study was to assess exome data for preemptive pharmacogenetic screening for 203 clinically relevant pharmacogenetic variant positions from the Pharmacogenomics Knowledgebase and Clinical Pharmacogenetics Implementation Consortium and identify copy-number variants (CNVs) in CYP2D6.

methodsWe examined the coverage and genotype quality of 203 pharmacogenetic variant positions in 973 exomes compared with five genomes and with five genotyping chip data sets. Then, we determined the agreement of exome and chip genotypes by evaluating concordance in a three-way comparison of exome, genome, and chip-based genotyping at 1,929 variant positions in five individuals. Finally, we evaluated the utility of exomes for detecting CYP2D6 CNVs.

resultsFor 5 individuals examined for 203 pharmacogenetic variants (5 × 203 = 1,015), 998/1,015 were identified by genome, 849/1,015 were identified by exome, and 295/1,015 by genotyping chip. Thirty-six pharmacogenetic star allele variants with moderate to strong Clinical Pharmacogenetics Implementation Consortium (CPIC) therapeutic recommendations were identified in 973 exomes. Exomes had high (98%) genotype concordance with chip-based genotyping. CYP2D6 CNVs were identified in 57/973 exomes.

conclusionsExomes outperformed the current chip-based assay in detecting more important pharmacogenetic variant positions and CYP2D6 CNVs for preemptive pharmacogenetic screening. Tools should be developed to derive pharmacogenetic variants from exomes.Genet Med 19 3, 357-361.

Indexed as

AllelesCytochrome P-450 CYP2D6DNA Copy Number VariationsExomeGenotypeHigh-Throughput Nucleotide SequencingHumansOligonucleotide Array Sequence AnalysisPharmacogeneticsPharmacogenomic TestingCytochrome P-450 CYP2D6

Identifiers

PMID27537706
PMCPMC5316383

What OpenQuestion holds

Textmetadata
LicenceTDM
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.