Evidence map›Paper›PMID 33691016›Full record

ArticlePacific Symposium on Biocomputing. Pacific Symposium on Biocomputing2021

Drug Response Pharmacogenetics for 200,000 UK Biobank Participants.

Gregory McInnes, Russ B Altman

Abstract read
In one paragraph

Article in Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing 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

19 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Review
  13. Review
  14. Drug-Drug-Gene Interactions in Cardiovascular Medicine.Pharmacogenomics and personalized medicine · 2022
    Review
  15. Article
  16. Article
  17. Genomewide Association Studies in Pharmacogenomics.Clinical pharmacology and therapeutics · 2021
    Review
  18. Article
  19. Review
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

2 authors.

Gregory McInnesBiomedical Informatics, Stanford University, 450 Serra Mall, Stanford, CA 94305, United States of America, gmcinnes@stanford.edu.
Russ B Altman

Funding

PharmGKB: pharmacogenomics knowledge for precision medicineR24GM061374 · NIGMS · STANFORD UNIVERSITY · PI ALTMAN, RUSS BIAGIO, KLEIN, TERI ELLEN · 2010 to 2018
$25.2M
PharmGKB: pharmacogenomics discovery and implementationU24HG010615 · NHGRI · STANFORD UNIVERSITY · PI TERI Ellen KLEIN, Michelle Whirl-Carrillo · 2020 to 2026
$9.5M
Undergraduate Summer Research Experiences Support for Combining systems biology and structural biology to find new therapeuticsR01GM102365 · NIGMS · STANFORD UNIVERSITY · PI ALTMAN, RUSS BIAGIO · 2012 to 2021
$3.0M
Biomedical Data Science Graduate Training at StanfordT32LM012409 · NLM · STANFORD UNIVERSITY · PI PLEVRITIS, SYLVIA KATINA · 2016 to 2020
$1.5M
NHGRI NIH HHS U24 HG010615NIGMS NIH HHS R01 GM102365NIGMS NIH HHS R24 GM061374NLM NIH HHS T32 LM012409
6 · The paper itself

Abstract

Pharmacogenetics studies how genetic variation leads to variability in drug response. Guidelines for selecting the right drug and right dose for patients based on their genetics are clinically effective, but are widely unused. For some drugs, the normal clinical decision making process may lead to the optimal dose of a drug that minimizes side effects and maximizes effectiveness. Without measurements of genotype, physicians and patients may adjust dosage in a manner that reflects the underlying genetics. The emergence of genetic data linked to longitudinal clinical data in large biobanks offers an opportunity to confirm known pharmacogenetic interactions as well as discover novel associations by investigating outcomes from normal clinical practice. Here we use the UK Biobank to search for pharmacogenetic interactions among 200 drugs and 9 genes among 200,000 participants. We identify associations between pharmacogene phenotypes and drug maintenance dose as well as differential drug response phenotypes. We find support for several known drug-gene associations as well as novel pharmacogenetic interactions.

Indexed as

Pharmaceutical PreparationsPharmacogeneticsBiological Specimen BanksComputational BiologyGenotypeHumansUnited KingdomPharmaceutical Preparations

Identifiers

PMID33691016
PMCPMC7951365

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.